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Emergy basis of forest systems

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Title:
Emergy basis of forest systems
Added title page title:
Emergy basis of forested systems
Creator:
Tilley, David Rogers, 1969-
Publication Date:
Language:
English
Physical Description:
xiv, 296 leaves : ill. ; 29 cm.

Subjects

Subjects / Keywords:
Forests and forestry -- Economic aspects -- North Carolina ( lcsh )
Forest management -- North Carolina ( lcsh )
Ecosystem management -- North Carolina ( lcsh )
Environmental Engineering Sciences thesis, Ph.D ( lcsh )
Dissertations, Academic -- Environmental Engineering Sciences -- UF ( lcsh )
simulation modeling
emergy
Spatial Coverage:
United States -- North Carolina -- Macon -- Macon County Watershed
Coordinates:
35.15 x -83.42

Notes

Thesis:
Thesis (Ph.D.)--University of Florida, 1999.
Bibliography:
Includes bibliographical references (leaves 287-295).
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by David Rogers Tilley.

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The University of Florida George A. Smathers Libraries respect the intellectual property rights of others and do not claim any copyright interest in this item. This item may be protected by copyright but is made available here under a claim of fair use (17 U.S.C. §107) for non-profit research and educational purposes. Users of this work have responsibility for determining copyright status prior to reusing, publishing or reproducing this item for purposes other than what is allowed by fair use or other copyright exemptions. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. The Smathers Libraries would like to learn more about this item and invite individuals or organizations to contact the RDS coordinator (ufdissertations@uflib.ufl.edu) with any additional information they can provide.
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002486730 ( ALEPH )
43164352 ( OCLC )
AMK2356 ( NOTIS )

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.EMERGY BASIS OF FOREST SYSTEMS By DAVID ROGERS TILLEY A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHll..OSOPHY UNIVERSITY OF FLORIDA 1999

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.UMI Number: 9946054 UMI Microfonn 9946054 Copyright 1999, by UMI Company. All rights reserved. This microfonn edition is protected against unauthorized copying under Title 17, United States Code. UMI 300 North Zeeb Road Ann Arbor, MI 48103

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.ACKNOWLEDGMENTS ,f' The success of a graduate student is directly proportional to the care, friendship, and fellowship offered by family and friends. Conversely, the extent of ones academic career indicates how much love, support, and camaraderie was available. My extended educational experience was a success due to the unconditional support of both myoid and new families. Thanks to my parents for faithfully professing the value of education and to my older siblings for graciously demonstrating and reinforcing this truism. A special loving thanks to Cathey for tolerating the emotional journey of graduate student life. Special thanks go to my committee members: Dr. Mark Brown for offering intellectual guidance, keen insight, and patient support on top of his jovial character; Dr. H. T. Odum, a man with the most powerfully, diverse intellect, for including me in his quest to educate the world on how to understand itself, Dr. Clay Montague for sharing his discerning disposition; Dr. Clyde Kiker for providing the economist's viewpoint on understanding the link between nature and humanity; and Dr. Wayne T. Swank for having the foreknowledge to appreciate the unique abilities of our work, and for committing research resources of the U.S. Forest Service to fund my doctoral stipend. Financial support for this research was provided by the Coweeta Hydrologic Laboratory of the U.S. Department of Agriculture Forest Service, Mark T. Brown, principal investigator (contract # A8FS-9, 961-113). u

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.TABLE OF CONTENTS ACKN"OWLEDGMENTS ............................................................................................... ii LIST OF TABLES ......................................................................................................... vi LIST OF FIGURES ...................................................................................................... viii ABSTRACT ................................................................................................................. xiii 1 INTRODUCTION ........................................................................................................ 1 Statement of Problem ............................................................................................... 1 Why Study Forests .................................................................................................... 2 Description of Concepts and Principles ....................................................... .............. 3 Previous Emergy Evaluations of Forests, Watersheds, and Other Ecosystems ........... 6 Description of Systems Studied .............. ................................................................... 9 Plan of Study .......................................................................................................... 16 2 MElHODS ................................................................................................................ 18 Systems DiagraIllS ................................................................................................... 18 Emergy Systems Evaluations .................................................................................. 19 Computer Simulation Models ........... ............................................................ ........... 20 Environmental Driving Energies .............................................................................. 25 Energy and Emergy ofWmd .............................................................................. 25 Emergy of the Calcium Cycle .............................................................. ............... 25 Spatial Distribution of Empower in the Wme Spring Creek Watershed ............... 26 Spatial Distribution of Soil Organic Matter, Wme Spring Creek Watershed ...................................................... .............................................. 27 Spatial Distribution of Empower in North Carolina ................................... ......... 27 Emergy of the U.S. Forest Products Industry ..................................................... 29 3 RESULTS ............................................................................................................ ...... 30 Emergy Evaluation of Forested Watersheds ....................... ..................................... 30 Environmental Driving Energies ........................................................................ 32 Imported Driving Energies ................................................................................. 38 Internal Processes .............................................................................................. 39 III

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Emergy of Forest Exports ........................................................................... ....... 45 Transfonnity of Forest Exports .......................................................................... 47 Dynamic Simulation ofEmergy in Forest Storages ............................................ .48 Emergy Evaluation of Forest Economies .............................................. ................... 66 Macon County, North Carolina .......................................................................... 69 North Carolina ................................................................................................... 76 U.S. Forest Products Industry ...................................................... ...................... 97 International Trade of Forest Products ............................................................. 112 Global Forest Stocks and Consumption ............................................ ................ 115 Emergy Indices for Overview of Forested Systems ................................................ 118 Sensitivity ofEmergy Simulation Models .............................................................. 124 Sensitivity ofEmergy and Transformity to Depreciation and Export ................. 124 Sensitivity of Species Simulation Model EMSPECIES ..................................... 125 Comparing Curves of Empower-species and Species-area ................................ 128 Simulating Management Alternatives of Forest Ecosystems ................................... 130 Logging Rotation Schedules and Forest Empower ............................................ 130 A Model for Simulating the Empower of Multiple Forest Benefits .................... 137 4 DISCUSSION .......................................................................................................... 145 Summary .............................................................................................................. 145 The Significance of Environmental Driving Energies to the Southern Appalachians .............................................................................................. 145 Values of Forests in the Southern Appalachian Mountains ................................ 145 The Importance of Forested Systems and Other Ecosystems to Economic Production ................................................................................................. 147 Incorporating the Temporal and Spatial Dynamics of Emergy and Transfonnity into Emergy Evaluations ........................................................ 148 Management Policies ........ ................................................................................ 149 New Solar Transformities ............................................. .................................... 149 Emergy of Southern Appalachian Watersheds ....................................................... 151 Environmental Driving Energies and Empower Spectra .................................... 151 Emdollar Values of Forest Processes, Exports, and Storages ............................ 153 Comparisons of the Ecological Economics of Forest Systems ................................ 156 Emergy Measures of Living Standard ............................................................... 156 Emergy Measures of Sustainability ................................................................... 157 The Dynamics ofEmergy, Empower, and Transfonnity ......................................... 163 Calculating Transformities Dynamically ............................................................ 163 Accounting for the Energy Transformation Processes of the Landscape ........ .... 164 Spatial Distribution of Empower in North Carolina ........................................... 164 An Explanation for the Fluctuating Empower Spectra of North Carolina .......... 167 Plans for Future Research ..................................................................................... 171 GLOSSARy ................................................................................................................ 173 lV

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.APPENDICES A SOLAR TRANSFORMITIES USED FROM PREVIOUS WORK AND FOOTNOTES TO EMERGY EVALUATION TABLES ................................. 175 B CALffiRATION OF EMERGYDYN AND EMSPECIES .................................... 218 C WATER VAPOR SATURATION DEFICIT OF THE ATMOSPHERE OVERL YmG LAND ...................................................... ................................ 234 D CALCULATING ENERGY ABSORBED FROM WIND .................................... 251 E SOLAR TRANSFORMITY OF MOUNTAIN DEEP HEAT AND EROSION ....................................................................................................... 257 F PROGRAM CODE FOR EXTEND BLOCKS USED IN SIMULATION MODELS ...................................................... .................................................. 266 G MISCELLANEOUS EMERGY EVALUATIONS ............................................... 274 REFERENCES ...................................................................................................... ...... 287 BIOGRAPIDCAL SKETCH ...................................................... ................................. 296 v

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.LIST OF TABLES Table 2I Emergy evaluation template for calculating solar emergy, erndollars, and solar transformity ........................................................................................ 19 2-2 Rules for simulating the temporal dynamics ofemergy (Odurn 1996) ............. 21 3-1 Emergy evaluation of I ha of watershed 18, Coweeta, NC .............................. 34 3-2 Emergy evaluation of 1 ha of Wine Spring Creek watershed (ca. 1995) .......... 36 3-3 Empower and weathering rates for seven (7) sub-basins of Coweeta watershed ................................................................................................... 40 3-4 Emergy evaluation of storages in one hectare of the forest at WS 18 (Coweeta) ................................................................................................... 50 3-5 OMII lED 3-6 Soil organic matter in WSC watershed by soil type ......................................... 65 3-7 Emergy evaluation of resource basis of Macon Co., N.C. ca. 1992 ................. 71 3-8 Summary offlows in Macon county, N. C. circa, 1992 .................................. 75 3-9 Emergy evaluation of resource basis for North Carolina, ca. 1992 ................... 80 3-10 Emergy evaluation of resource storages of North Carolina, 1992 ................... 92 3-11 Summary offlows in North Carolina, ca. 1992 ............................................... 94 3-12 Emergy evaluation of forest growth in North Carolina .................................... 99 3-13 Emergy evaluation of the logging industry in the United States, 1992 ........... 100 3-14 Emergy evaluation of wood pulp production in the United States, 1990 ........ 101 3-15 Emergy evaluation of paperboard production in the United States, 1990 ....... 102 3-16 Emergy evaluation of paper production in United States, 1990 ...................... 103 3-17 Emergy evaluation of plywood production in United States, 1990 ................. 104 3-18 Emergy evaluation oflumber production in United States, 1990 ................... 105 3-19 Indices using emergy for overview ofWme Spring Creek watershed (1128 ha) ........................................................................................................... 119 3-20 Indices using emergy for overview of Macon county, N.C. 1992 .................. 120 3-21 Indices using ernergy for overview of North Carolina, 1992 .......................... 121 4-1 Summary of solar transformities calculated in this dissertation ...................... ISO vi

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.4-2 Emergy investment ratios offorested systems ............................................... 160 A-I Summary of solar transformities previously calculated and used in this dissertation ............................................................................................... 176 B-1 Calibration ofEMERGYDYN for simulating biomass, emergy, and transformity of wood in Coweeta watershed ............................................. 219 B-2 Calibration ofEMERGYDYN for simulating biomass, emergy, and transformity of total organic matter in Coweeta watershed ........................ 223 B-3 Calibration ofEMERGYDYN for simulating saprolite, emergy, and emergy per mass of saprolite (regolith) in Coweeta watershed .................. 226 B-4 Calibration ofEMSPEClES for simulating species abundance, stored emergy, and emergy per species in the WSC watershed ............................ 229 C-l Derivation of the vertical profile of the annual water vapor saturation deficit (mb) by latitude ............................................................................. 246 C-2 Energy (J) of water vapor saturation deficit by latitude and altitude ............... 247 C-3 Solar transformity of the water vapor satw"ation deficit overlying the continents ................................................................................................. 250 0-1 Equations and data used to calculate annual wind energy absorbed in the Coweeta watershed ................................................................................... 252 D-2 Equations and data used to calculate annual wind energy absorbed in the Wine Spring Creek watershed ................................................................... 254 0-3 Equations and data used to calculate annual wind energy absorbed within a 1000m prism overlying Macon County, N.C ............................................. 255 0-4 Equations and data used to calculate annual wind energy absorbed within a l000m prism overlying North Carolina ..................................................... 256 E-1 Solar transformity and empower density of deep heat as a function of altitude ..................................................................................................... 263 E-2 Solar emergy per gram of mountain erosion as a function of altitude ............. 264 G-l Emergy evaluation of the University of Florida Arboretum ........................... 276 G-2 Evaluation of the emergy, water, and sediment budgets of the continents ...... 280 G-3 Sediment and emergy budgets for the main river basins of N.C. based on historic, agriculture, and present day sediment yield ............................. 282 G-4 Emergy evaluation of North Carolina leaf tobacco, 1987 .............................. 283 G-5 Computation of North Carolina trade in manufactured goods ........................ 286 vii

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.LIST OF FIGURES Figure 1-1 Location of Southern Appalachian Mountains, Macon County, Wine Spring Creek watershed, and Coweeta watershed within North Carolina ................ 10 1-2 Systems diagrams comparing the environmental-economic interface of Southern Appalachian watersheds for the period 1880-1920 (a) to the late 20th Century (b) .................................................................................. 11 2-1 Systems diagram and equations for the model EMERGYDYN, used to simulated the energy, emergy, and transformity of watershed storages ......... 22 2-2 Systems diagram and equations for the model EMSPECIES, used to simulated the species abundance, emergy of tree species, and transformity of tree species ............................................................................................. 23 3-1 Systems diagram of the forested watershed (WSI8) at Coweeta Creek ............ 31 3-2 Systems diagram of the environmental--economic interface ofWme Spring Creek: watershed ......................................................................................... 33 3-3 Power (a) and empower (b) spectra of environmental energy inputs to Wme Spring Creek (squares) and Coweeta (circles) watersheds ........................... 37 3-4 Emergy per gram of weathered rock as function of total suspended sediment concentration for streams in seven (7) sub-basins of Coweeta and for total discharge from of the six (6) continents and the globe .......................... 41 3-5 Energy systems diagrams of the calcium cycle ofws18 at Coweeta watershed. A) driving energies and calcium kinetics, B) calcium budget, and C) emergy of calcium inputs, internal cycle, and output ......................... 43 3-6 Tree species as a function of area (a) and as a function of annual empower (b) for high-elevation (> 1200m) forest in the Wme Spring Creek watershed .................................................................................................. 46 3-7 Energy systems diagrams ofEMERGYDYN used to simulate dynamics of emergy accumulation for wood biomass of the Coweeta watershed. Calibration of energy and material flows (a) and empower sources (b) ........ 51 3-8 Simulation results ofEMERGYDYN calibrated in Figure 3-7 for wood biomass of Coweeta. Time series of wood biomass, emergy of wood biomass, and transformity of wood biomass are shown ................................ 52 viii

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.3-9 Energy systems diagrams ofEMERGYDYN used to simulate dynamics of emergy accumulation for total (live + dead) organic matter of the Coweeta watershed. CalIbration of energy and material flows (a) and transformity and empower sources (b) ......................................................... 53 3-10 Simulation results ofEMERGYDYN calibrated in Figure 3-9 for total organic matter of Coweeta. Gross production, respiration, and net production (a), empower and transformity of use and export (b), and transformity and emergy of storage (c) are shown ....................................... 55 3-11 Energy systems diagrams ofEMERGYDYN used to simulate dynamics of emergy accumulation for saprolite of the Coweeta watershed. CalIbration of energy and material flows (a) and empower sources (b) ......... 56 3-12 Simulation results ofEMERGYDYN calibrated in Figure 3-11 for saprolite (regolith) at Coweeta. Emergy, emergy per mass of saprolite, and quantity of saprolite are shown .................................................................... 58 3-13 Model EMSPECIES used to calculate tree species abundance and emergy stored as tree species for the Wme Spring Creek watershed. A) systems diagram of model EMSPECIES shown with calibration values for an area of 0.08 ha, B) tree species-area curves for elevations above 1200m: simulation results compared to observations made by K. Eliott (unpublished data, Coweeta Hydro. Lab.), and C) simulated emergy stored per tree species for elevations above 120Om. .................................... 59 3-14 Spatial distribution of environmental empower density in the Wme Spring Creek watershed. A) systems diagram demonstrating how upstream empower from rain and deep heat converge from the ridge line down to the mid-basin region which in turn feeds the stream channel. B) map of the total environmental empower density ..................................................... 62 3-15 Frequency distnbution of environmental empower density in the Wme Spring Creek watershed .............................................................................. 64 3-17 Elevation gradient of soil organic matter in Wme Spring Creek watershed. Average organic matter per soil type as a function of mean elevation of soil type ..................................... ................................................................ 67 3-18 Topographic coverage ofWme Spring Creek watershed (a) and spatial distribution of soil organic matter by soil type (b) ........................................ 68 3-19 Systems diagram of Macon County, North Carolina (1992) ............................. 70 3-20 Summary diagram of emergy flows of Macon County, N.C. (1992) ................. 74 3-21 Power and empower spectra of the main resource inputs used in Macon County, N.C. (1992) ................................................................................... 77 3-22 Systems diagram of North Carolina (1992) ...................................................... 78 3-23 Map of the renewable empower density of North Carolina by county ............... 81 IX

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.3-24 Historical consumption of primary fuels and electricity in North Carolina in units of emergy (1960-1994) ....................................................................... 84 3-25 Map of purchased empower density of North Carolina by county .................... 85 3-26 Maps of growth in growing stock (a), forest cover (b), and additions to growing stock for North Carolina by county ................................................ 86 3-27 Systems diagrams of North Carolina's water budget (a) and the water evaluated as emergy (b) (1990) ................................................................... 89 3-28 Summary diagram of emergy flows of North Carolina (1992) .......................... 95 3-29 Power (a) and empower (b) spectra of the main resource inputs used in North Carolina (1992) ..................................... ........................................... 96 3-30 Systems diagrams of the emergy inputs to the individual sectors of the forest products industry. The sectors are: forest growth in North Carolina (a), logging (b), pulpwood (c), paperboard (d), paper ( e), plywood (t) and lumber (g) ................................................................................................. 106 3-31 Systems diagram summarizing the emergy flow (a), transformities (b), and emergy-to-dollar ratios (c) for the U.S. forest products industry (1990) .... 110 3-32 The emergy-to-dollar ratio (sej/S) as a function of solar transformity for major wood products. ............................................................................. 113 3-33 Balance ofintemational trade in forest products. Trade in forest products (logs, woopulp, and paper) between the NAFTA (North American Free Trade Agreement) countries (U.S., Canada, and Mexico). Values for the forest products traded are shown in US dollars (S) and emdollars (EmS) ... 114 3-34 International trade in forest products between the NAFTA countries (1990). From/to matrices of money exchange for (a) wood logs, (b) pulp, (c) paper, and (d) all wood products; and from/to matrices of emdollar exchange for (e) wood logs, (t) pulp, (g) paper, and (h) all wood products .... .. .. ... .. ... .... .............. ... ......... .. .... .... ... .. ... .. .. ... ..... ..... ..... .. 116 3-35 Empower of the global forest harvest (1950-97) ............................................ 117 3-36 Spatial distn1>ution of the emergy investment ratio (purchased to renewable) in North Carolina by county ...................................................................... 122 3-37 Rank order distributions of North Carolina counties by (a) emergy investment ratio (purchased to renewable) and (b) total empower density of the year 1992 ........................................................................................ 123 3-38 Transformity of total organic matter (TOM) simulated with EMERGYDYN for the Coweeta watershed. a) time series when total loss (export + depreciation) was held to a constant fraction of 0.03 of storage and the partitioning between export and depreciation was varied, percentages refer to exportltotalloss; b) steady-state values from (a); c) depreciation x

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.was held to a constant fraction of 0.023 of storage while export was varied from 0.006 to 0.094 of storage ....................................................... 126 3-39 Simulation of species area curves for Wme Spring Creek watershed and two tropical rainforests .................................................................................... 127 3-40 Species-area curve (a) and empower-species curve (b) for the forest ofWme Spring Creek (> 1200m), the Arboretum at the University of Florida., Gainesville (see Appendix G for emergy evaluation), and the tropical rainforest at East Kalimantan, Borneo (Kartiwinata 1984) ......................... 129 3-41 Simulated temporal dynamics of the quantity, emergy, and transformity of wood biomass for a 100-year rotation (a) and 300-year rotation (b) schedule .................................................................................................... 131 3-42 Simulated steady-state value of the response offore emergy to frequency of harvest. Energy systems diagram (a), yield-wood & emergy (b), emergy inputs (c), emergy yield ratio & environmental loading ratio (d), renewable fraction in yield & emergy sustainability index ( e), and transformity of yield and forest (t) ............. ............................................... 134 3-43 MULTIBEN, a model for simulating the empower of multiple forest benefits given different management scenarios ...... ................................................ 138 3-44 Model MUL TIBEN with sub-module added for simulating the sustainability of providing multiple benefits .................................................................... 142 4-1 Summary diagram of the emdollar value of the forcing factors and products of the ofWme Spring Creek watershed ..................................................... 146 4-2 North Carolina's per capita empower consumption and per capita gross state product ..................................................................................................... 158 4-3 Emergy-to-dollar ratio of North Carolina from 1977 to 1994. Total empower used in N. C. per dollar of gross state product ............................. 159 4-4 An empower difference spectra of the U.S. woodpulp production industry (1972 vs. 1990} ......................................................................................... 166 4-5 A possible explanation for the dynamics observed in the empower spectra of the forest systems evaluated ...................................................................... 168 4-6 Ratio of the mean transformity offorest yield (Y in Figure 3-42a) divided by average transformity offorest wood (Q in Figure 3-42a) calculated from the EMERGYDYN simulation modeL ...................................................... 169 C-1 Systems diagram of the hydrologic cycle overlaid with the heat budget of the atmosphere highlighting the role of the water vapor saturation deficit over land ................................................................................................... 240 C-2 Map of the vapor saturation deficit at the surface for a) June and b) December ................................................................................................ 241 xi

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.C-3 Annual and seasonal meridional profiles of the mean zonal saturation deficit (mb) at the surface of the continents. (DJF-Dec, Jan, Feb; JJA--Jun,July, Aug) ......................................................................................................... 243 C-4 Mean monthly (1961-90) saturation deficit at the surface (1000 mb) of the continents for the globe and northern and southern hemispheres ................ 244 C-5 Meridional profiles of mean zonal saturation deficit at various altitudes ......... 245 C-6 Meridional profile of the vertically integrated distribution of total energy of saturation deficit over the continents ......................................................... 247 C-7 Vertical profile of saturation deficit for continents ......................................... 248 C-8 Seasonal mean monthly saturation deficit across the Southern Appalachians along the 35th parallel from eastern North Carolina to western Tennessee. 249 D-l Profile of wind velocity over Coweeta watershed ........................................... 244 E-l Diagram illustrating how total heat flow decreased with altitude .................... 261 E-2 Mean flow of deep heat versus elevation ........................................................ 262 E-3 Solar emergy per gram of mountain erosion as a function of altitude .............. 265 F-l Extend representation of model EMERGYDYN used of simulating the emergy an transformity of wood biomass of the Coweeta watershed ......... 267 G-l Systems diagram of the environmentaI-economic interface oftne UF Arboretum, Gainesville, Florida ................................................................. 275 G-2 Concentration of suspended sediment in continental river discharge as a function of (a) total empower of continental precipitation and (b) empower density of continental precipitation ............................................. 281 XlI

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy EMERGY BASIS OF FORESTED SYSTEMS By David Rogers Tilley August 1999 Chairman: Mark T. Brown Major Department: Environmental Engineering Sciences A major question in natural resource management is how to integrate economicuse activities with the supporting ecosystems to maximize performance of the ecological-economic system. In this dissertation, the natural wealth of forested systems of three different sizes was evaluated with emergy: two watersheds of the Southern Appalachians, Macon County (N.c.), and North Carolina. Emergy is the total amount of energy of one form that was required directly and indirectly to make another form of energy. Values are reported as emdollars (Em$) which represent the economic activity reSUlting from resource use. Benefits provided by forested watersheds were quantified based on emergy required to develop and maintain each service or product. Total wealth contributed by the multiple-use Wine Spring Creek (WSC) watershed was 4300 Em$/haly, and was divided among scientific research (3450 Em$lhaly), water yield (2060 Em$lhaly), recreation (1880 Em$lha), and timber (1440 Em$lhaly). xiii

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.In the 1990's, timber accounted for 3% of world emergy use, 1% in the United States, 9'110 in North Carolina, 14% in Macon County, and 8% in the WSC watershed. Forest ecosystems captured 53% of environmental emergy in North Carolina, 81% in Macon County, and 100% in the WSC watershed. The importance of forest ecosystems to the U.S. economy were evaluated based on emergy flows of the U.S. forest products industry and international trade offorest products in North America. In 1993, the U.S. had an annual trade surplus in forest products worth 63 billion Em$. Simple models were developed to explore the temporal and spatial dynamics of emergy and transformity in forested watersheds. Transformity is the ratio of emergy to energy; it measures position in the energy hierarchy of energy forms. Temporally, transformity and emergy lagged energy levels in reaching steady-state. Spatially, emergy from mountain uplands converged to the stream network, making water and its carved basin locations of high empower density. A model, MUL TIBEN, evaluated forest empower of multiple benefIts given various combinations of economic investment in recreation and timbering. Maximum empower was found at an intermediate level of economic investment, suggesting that an optimum intensity of forest development exists. xiv

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.CHAPTER 1 INTRODUCTION Statement of Problem At the end of the 20th century, a major question in forest resource management is how to integrate economic use activities with the supporting ecosystems to maximize performance of the ecological-economic system. Methods of evaluation that can quantitatively integrate across systems are needed so that resource managers and the public can make informed policy decisions regarding the environment and its multiple uses. Ascertaining the value of the goods and services provided 'free' from forests and other environments has increased in importance due to a shrinking environmental base and an expanding, industrialized global economy (Daily, 1997). The world's annual emergy flow is now three and a half time greater than what is capable from renewable resources alone due to our use of energy obtained from fossil fuels (Brown and Ulgiati, 1999). In the developed countries, fossil-fueled economies are often ten times more intense than would be capable if only renewable, environmental sources of energy were used. Quantitative measures are needed that signify how necessary the services and products of forested ecosystems are to human endeavors. When abundant fossil fuels no longer exist, civilization may find itself once again relying heavily upon forest ecosystems for economic stability. If this occurs, an energetically grounded knowledge of forested 1

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.2 ecosystems will be necessary so that they may be managed for maximum ecologicaleconomic benefit. Specific Issues The following questions were addressed in this dissertation. 1. In Southern Appalachian mountain watersheds, how does the empower contnouted from different driving energies compare? What are the relationships between the driving empower and internal processes, watershed exports of goods and services, and the stores of materials, energy, and information? 2. How does the ecological-economic relationship change for forested systems as the scale of analysis shifts from Southern Appalachian watersheds to the county, the state, the U.S. forest products industry, and finally to international trade? 3. How are the temporal, spatial, and process dynamics of emergy, empower, and transformity of forested systems incorporated into emergy evaluations of forests? 4. What intensity of development of U.S. National Forests maximizes empower? Why Study Forests Civilization has forever acquired food, fueL and fiber from its forests (Mather, 1990). The expansion and success of early Mediterranean civilizations, ifnot entirely reliant upon forest resources, was at least significantly aided by their presence. Hughes & Tbirgood (1982) estimated that in ancient Greece and Rome 90010 offorest biomass was used as fuelwood for cooking and metal working. Forests provided the raw material for such final products as houses, war machines, and writing material, in addition to providing foods such as nuts, berries, and wildlife. The governments of Greece and Rome understood the importance of maintaining productive forests so well that they assumed ownership of much forested land and restricted export offorest products (Mather, 1990).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Some researchers point to archeological finds as an indication that soil erosion, accelerated from harvesting hillslope forests, devastated the fertility of agricultural lands downslope and led to the collapse of ancient Mediterranean civilizations (Mather 1990). 3 Up to the beginning of the fossil fuel boom of the late 19th Century in the United States, forests were the main source of raw material for the naval stores industry; turpentines of gum, wood, and sulfate were produced along with pine oil, rosin, pitch, and tar. Turpentine farming began as early as 1606 in North America, but peaked in 1909 at 750,000 barrels per year (Kurth, 1952). Today, forests are recognized as much for their production of material goods, as they are for their aesthetics, recreational amenities, biological preservation, maintenance of mineral cycles, soil conservation and water enhancement (Myers 1997). While National Forest lands in the U.S are increasingly being viewed as a last vestige of wilde mess, the public debate on how best to manage those lands continues to intensify. What is needed to address public concerns is a better understanding of the value of non-marketed, as well as marketed, goods and services provided by forests. Description of Concepts and Principles This dissertation used systems diagramming, simulation modeling, and emergy analysis to evaluate forested systems. Brief descriptions of the concepts behind each method follow. Energy Systems Diagramming and Simulation Modeling The energy systems language ofOdum (1994), with its explicit mathematical and energetic definitions of symbols (see the Glossary for names and definitions of symbols), is

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.4 helpful in describing system architecture in overview and in mathematical detail. At an overview level, systems diagrams are a rigorous statement of how main units are organized and interact with external driving energies. To study system behavior over time or across space, the language can be used to develop computer models of any type of system. Emergy Analysis Emergy analysis is a form of energy analysis useful for evaluating systems that have multiple forms of driving energies. Emergy is defined as the total amount of energy of one form that was used directly and indirectly to make another form of energy (Odum, 1996). Thus, when the energy basis of any system is evaluated, the multiple forms of energy can be converted to emergy and expressed in a common unit. Proper energy systems analysis recognizes the unique properties of energy forms (e.g., solar radiation, chemical bonds of wood, river currents, electricity) by accounting for the emergy used in the supporting network. The end result being that emergy systems analyses of all processes occurring on earth draw the system boundary so as to include the ultimate energy source, the sun. The fundamental premise behind emergy analysis is that different forms of energy have unique properties associated with their position in the universal energy hierarchy and that the position is accurately measured with the transformity. The transformity is defined as the emergy required to make a certain form of energy (Odum 1996). The transformity of solar radiation is defined as unity (1) so that all other energy forms can be expressed as solar emergy. The System International (S1) unit for energy is the joule (J), so the unit for solar emergy is the solar emjoule (sej). The unit for the transformity is solar emjoules per

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.joule (sej/J). Forms of energy which occupy a higher position in a chain of energy transformations have higher transformities (e.g., the transformity of electricity is greater than that of coal or wood). Definitions of terms used in the dissertation are given in the Glossary. 5 In the realm of peopled systems where market systems and money are used to exchange goods and services, it is sometimes convenient to express emergy in terms of the currency that it is driving. When expressed in this manner the quantity is called emdollars (Em$) and is defined as the amount of currency (e.g., dollars) being driven by a flow of emergy. Emergy is translated to emdollars by dividing emergy flow by the average emergy-to-money ratio of an economic system. The emergy-to-money ratio is found by dividing total emergy use by a measure of economic product such as the gross domestic product. In this dissertation, the solar emjoules associated with the use of a resource or an environmental energy were often also reported as North Carolina emdollars. These emdollars were found by dividing solar emergy by the emergy-to-dollar ratio of North Carolina (i.e., total emergy use divided by gross state product). System Self Organization for Maximum Empower The principle that systems self organize to maximize empower (rate of emergy use) was put forth by Odum (1996). It states that systems self-organize by emphasizing those structures and functions that can provide feedback to the production process in order to capture more empower. At least two different strategies of systems development can be explained with the principle. When energy ( or resource) availability is high, as with a recently burned forest that has high nutrient aVailability, it is advantageous for the system to respond quickly by emphasizing fast growing units with little regard for the longevity of

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.the unit. On the other hand, when there is not a great surplus of unused energy (low availability), as with an old growth forest, net growth is minimal or non-existent, and long-lasting, large units are emphasized that promote tight material cycles and efficient energy use. 6 The principle of systems self-organization for maximum empower is the premise that behind using emergy to value systems. It assumes that the self-organized system values its units and interconnections by how much emergy they use. Productive functions that use a lot ofemergy are valued highly. Wasteful functions can use a lot ofemergy also, but only for a short while. They will be selected against because they do not feed back properly to increase system empower. Previous EmerS)' Evaluations of Forests. Watersheds. and Other Ecosystems The energy systems analysis methodology has been used to evaluate watersheds and ecosystems since the 1970's with the most complete review given by Odum (1996). Many aspects of forest ecosystems, including watersheds, have been evaluated using emergy (Doherty 1995; Odum 1995; Romitelli and Odum 1996; Romitelli 1997; Kharecha 1997; Orrell 1998; and Howington 1999). Doherty (1995) evaluated the net emergy yield of forest production systems which had rotation cycles ranging from fast (5 years) to slow (300+ years). Net emergy yield to the economy was discovered to increase with longer forest rotation cycles. The energy basis of self-organization of mountain watersheds was investigated for the east coast of Brazil (Romitelli 1997) and the Coweeta basin (Romitelli and Odum 1996). Chemical potential and geopotential energies of water were found to be coupled;

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.7 the geopotential energy accumulated in the mountains was used to spread the chemical potential in the lowlands to maximum benefit to the whole watershed. Use of the chemical potential energy of water, a measure ofproductMty, increased downstream. Odum et al. (1987) and Diamond (1984) evaluated the environmental and economic empower of the Mississippi River basin. Transfomrity of the river's geopotential energy was found to increase downstream and suggested as a novel system for classifying stream orders. Empower within the Cache River watershed of Arkansas was found to converge downstream to the Black Swamp (Odum et al. 1998). Kharecha (1997) and Doherty et al. (1997) found that empower density of the forest ecosystems ofLuquillo Forest in Puerto Rico increased as elevation decreased. Orrell (1998) studied the relationship between ecosystem respiration and plant diversity for ecosystems throughout the world. The empower required to support the tree diversity of north central Florida was found to be on the order of 1 x 1020 solar emjoules per species per year. Keitt (1991) related empower to tree diversity in the Luquillo Experimental Forest of Puerto Rico. Empower requirements were discovered to increase as the square of the number of tree species. The spatial distribution of empower in watersheds was related to phosphorus cycling for the Upper Kissimmee River basin of central Florida (Boggess 1995) and for the karst-dominated St. Mark's watershed in the Florida panhandle (parker 1998). In both watersheds, empower was found to increase downstream. Howington (1999) evaluated the emergy of a Colombian-Venezuelan watershed and developed policy plans based on results. Methods for evaluating the spatial dynamics of the emergy of river water were refined.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.8 Emergy evaluations and computer minimodels of tropical forests and their economic interfaces were developed to explore the ramifications of various public policy alternatives (Odum 1995). The environmental empower density of one (l) hectare of tropical forest was found to be 630 E12 sej/ha/y. The environmental empower was matched by 120 E12 sej/ha/y of goods and services, 41 E12 sej/ha/y of fuels, and 546 EI2 sej/ha/y of tourism. This represented an emergy investment ratio of 1.12. The 153 species of trees in the Luquillo National Forest were determined to represent a storage of 1.18 E23 sej. Minimodels developed included: MATCHUSE that evaluated the emergy yields of wood sales and non-marketed goods and services, for a forest with competing woody and non-woody species; CACAO which evaluated the ecological interactions and economic yields of harvesting an understory crop; ELVERDE explored the relationship between nutrient cycling and gross productivity; and CLIMAX looked at the effects of wood harvesting on biodiversity. A systems diagram of moderate complexity was given for the EI Verde forest at Puerto Rico which included such forcing factors as sunlight, wind, vapor, heat, nitrogen, carbon dioxide, rain, atmospheric deposition, and geologic uplift, and internal components such as seedlings, trees, epiphytes, earthwonns, insects, and soil properties. In an effort to determine the total benefits of recycling building materials, Buranakam (1998) evaluated the emergy needed to make plywood and lumber in the United States. The transformities for softwood and hardwood plywood were 6.3E4 sej/J, while the transformity oflumber was determined to be 4.6 E4 sej/J. McGrane (1998) estimated the emergy associated with the main lithospheric units: cratons, mountains, and continental and oceanic sediments. The global average emergy

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.9 per gram of mountain-material cycled was found to be on the order of 2 E9 solar emjoules per gram. This was less than that found for the continental platforms (cratons), and greater than ocean sediments. Descriptions of Systems Studied The Southern Appalachian Mountains are centered in western North Carolina, but cross into northern Georgia and eastern Tennessee (Figure 1-1). The region was uplifted during three (3) mountain building episodes: the Taconic Orogeny during the Ordivician (505-438 million years ago); the Acadian during the Carboniferous (360-290 mya); and finally by the Alleghenian Orogeny of the Permian (290-245 mya) (Beyer 1991). The region is home to the highest mountain peaks in the eastern U.S (e.g., Mt. Mitchell and Clingman's Dome). Headwater streams for the Tennessee, Savannah, Chatahoochee, and Yadkin-Pee Dee drainage basins are located in the region. The U.S. National Forest Service and National Park Service manage a significant portion of the land as the Pisgah and Nantahala National Forests and thE! Great Smokey Mountain National Park. Figure 1-2 shows how the energies driving the ecological-economic system of the Southern Appalachians changed over the past 120 years. At the end of the 19th Century, local "mountaineers" populated the valleys, subsisting mainly on natural resources but with a small amount of trade (Lewis et aI. 1978). During this period, logging and mining companies moved down from the northeast U.S. into the region and bought timber and minerals rights from the mountaineers. When timber was extracted from the steep mountain slopes, the relatively small area of farmland held by mountaineers in coves was devastated by erosion (Whisnant, 1994).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Southern Appalach" Lake Franklin North Carolina Counties Macon County CoNeeta __ (location) Wine Spring Creek Watershed Figure 1-1. Location of Southern Appalachian Mountains, Macon County, Wme Spring Creek watershed, and Coweeta watershed within North Carolina. 10

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.( ---Southern Appalachian Watersheds (1880-1920) Tilley, 1999 Soil Erosion Forest l Southern Appalachian Tilley, 1999 Watersheds (late 20th Century) Service ""--" Timber Recreation Research Water Figure 1-2. Systems diagrams comparing the environmental-economic interface of South em Appalachian watersheds for the period 1880-1920 (a) to the late 20th Century (b). In the earlier period, mountaineers farmed the coves and depended little upon trade. During this period, capitalists from the north logged the old-growth forests, causing heavy soil erosion and accelerated water runoff (Whisnant 1994). At the end of the 20th Century, the region's economy relied heavily upon tourism, but timbering was still significant. The U.S. Forest Service managed a large portion of the land and promoted research on forestry management. 11

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.12 By the end of the 20th Century, the region had broadened its spectra of driving energies and developed into a recreational and tourist haven for the eastern United States, and once again supported a substantial timber industry with its vast forests (Southern Appalachian Assessment, 1996). The State of North Carolina North Carolina spans over 800 Ian from the Atlantic Ocean to the Appalachian Mountains. The state has the most diverse topographic relief of all states east of the Mississippi. The extensive lowland region of the east is known as the Coastal Plain, the rolling landscape of central North Carolina is called the Piedmont Plateau, and the rugge
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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.13 elevation is 988 m. Climate is marine tropical with abundant precipitation (1350 nun y-l) that includes some snowfall. Summers are warm while winters are mild to cold. Franklin is the county seat and largest city with 42% of the county's 23,500 (1992) residents (US Census Bureau 1996). The Watershed ofWme Spring Creek The 1130 ha Wine Spring Creek (WSC) watershed lies within the Nantahala National Forest of the North Carolina Blue Ridge physiographic province in western Macon county (35 Latitude, 83 Longitude; see Figure 1-1). Elevations in the basin range from 1660m at Wme Spring Bald to 900m at Nantahala Lake. The basin is unpopulated (U.S. Forest Service, 1995), but receives over 10,000 tourists per year (Cordell et al. 1996). The -1800 nun of annual rainfall is evenly distributed throughout the year with more than 100mm of rain falling each month. Mean temperatures in January and July are 3.3 and 22C, respectively (Swift et al. 1988). The Wme Spring Creek Ecosystem Demonstration project, a research effort to quantify effects of several forest management prescriptions, was begun in 1994 as a collaboration between the managers of the Wayah Ranger District; scientists of the Coweeta Hydrologic Laboratory and other Southern Research Station research work units; and scientists from seven universities (Swank 1998). The Watershed of Coweeta Creek The Coweeta Hydrologic Laboratory, a 2185 ha research station of the USDA Forest Service in southwestern North Carolina, was set up in the 1930's to study the effects of land management practices on the hydrology of mountainous terrain. Later the

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.14 research scope was broadened to include ecosystem management and watershed response to natural and man-made disturbance (Swank and Crossley, 1988). Watershed 18 (wsI8), a 12.5 ha mixed hardwood sub-basin of the Coweeta basin that has been undisturbed since 1927, was investigated in this dissertation due to its pristine status and long-term research history. In wsl8, elevations range from 993 m down to 726 m. The basin faces the NW with a mean slope of 52% (Swank and Crossley (1988). Solar radiation over the annual cycle varies from a minimum mean of7.0 E6 J m-2 dol in December to a maximum mean of 19 E6 J m-2 d-1 in June (Swift et al. 1988). Mean monthly wind velocities are greatest from late fall through early spring, presumably from the passage of cold fronts. Wmds are generally lighter from late spring to early fall. The Coweeta Lab is situated in the "temperate rainforest of the East" where average annual precipitation is greater than 1900 mm and well distnlmted throughout the year with every month receiving more than 110 mm. Based on the difference between stream discharge (1034 mm/y) and precipitation in wsl8, the average evapotranspiration is 2.48 mmld (Swift et al. 1988). The bedrock geology (Tallulah Falls Formation) consists of meta sandstones rich in feldspar and biotite, interlayered with mafic volcanic rocks and aluminous schists (Hatcher 1988). Directly overlying the bedrock is the residual regolith known as saprolite. It is subsoil which has formed from the in situ isovolumetric dissolution of the crystalline rocks into less dense (bulk density of -1.6 g/cm3) material. Thus, it has high porosity which allows for enhanced storage of subsurface water and augmented base flow. Information on the saprolite was extracted from Velbel (1988). Swank: and Douglass (1975) reported

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.that the average depth to bedrock was -6m for the Coweeta basin. of which 95% was most likely saprolite. Uplift ofland at Coweeta was estimated as 3.8 em per 1000 years (VelbeI1988), giving a replacement time of 160,000 years for the saprolite. Other Forested Systems 15 The emergy budget of the University of Florida's Arboretum was evaluated and compared to the forest ofWme Spring Creek and several tropical forests ofMalesia. The University of Florida Arboretum, located in Gainesville, was established in 1993 by Dr. Bijan Dehgan. Professor of Environmental Horticulture. There were 135 north central Florida tree species, each represented by three (3) individuals, planted on two (2) ha. Data on tree species richness of Indo-Malayan rain forests on the islands of Borneo, Sulawesi, and New Guinea were compared to the tree diversity of the Wme Spring Creek forest to gain perspective on the energetic basis of tree species diversity. The forest at East Kalimantan (l.10oS, 116.5E) is located 38 Ian north ofBaIikpapan on the island of Borneo at an altitude of 50 m (Kartawinata et al. 1981). Forest soils are alluvial and the annual rainfall is greater than 2300 mm, evenly distributed throughout the year. The Toraut forest (O.5N, 124E) of the northern peninsula of Sulawesi has alluvial soils derived from volcanic rocks and annual rainfall greater than 2100 mm (Whitmore and Sidiyasa, 1986). New Guinea forest, located in the Northern District of Papua, 160 km northeast of Port Moresby and 30 Ian inland from the coast, received -2300 mm of annual rainfall (Paijmans 1970).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.16 Plan of Study To better understand the environmental and economic basis of forest wealth and to clarify policy alternatives, the emergy values of four (4) forested systems and their main units were evaluated using systems diagrams, emergy analysis, and computer simulation models. The suite of energies, driving the processes of two forested watersheds in the Southern Appalachian Mountains (-lxl03 hal, were evaluated to quantify their emergy contributions to the forest. The many benefits provided by forests, such as wood, water, preservation of species diversity, tourism, and biogeochemical cycling, were also quantified as part of the evaluation of forest units. Macroscopic mini-simulation models and geographic information system-based models were used to explore temporal and spatial dynamics of emergy and transformity of forested watersheds. To determine the value of the goods and services contributed by forest ecosystems to the economy, emergy evaluations of the economies of Macon County, N.C. (-lxl OS ha) and North Carolina (-lxl07 hal were completed along with an emergy analysis of the United States forest products industry. International trade in forest products was assessed with emergy, using the North American Free Trade Agreement (NAFTA) between the U.S., Canada and Mexico as the case study. Finally, the total world consumption of wood was evaluated in terms of emergy. More specifically, the following analyses of forests, forest components and processes, and forest products and services were undertaken: 1. To understand the relative importance of driving energies to the forested watersheds of the Southern Appalachians, power and empower spectra were developed.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.2. To include the work of the atmosphere's water vapor saturation deficit in driving transpiration (productivity), the mean global transformity of the vapor deficit was calculated and included as a climatic input in emergy evaluations of all forested systems. 3. To determine how empower density and transformity of mountain energies changed with altitude, altitude-specific transformities for earth deep heat were calculated by accounting for the supporting emergy base. 4. To value biogeochemical cycling of forested watersheds, emergy of the calcium cycle was computed. 5. To determine the value of National Forest lands as reserves for preserving species, emergy was related to tree diversity with species area curves and a simulation model. 6. To determine the total benefit of the multiple uses (recreation, research, timbering) and products (water yield) of the Wme Spring Creek watershed, the product of each use was evaluated as emergy. 7. To explore how emergy and transformity of main forest units change over time, dynamic computer models were developed and simulated. 8. To see how dynamic emergy models could be used in sustainable forestry management, temporally dynamic emergy models of forest units were developed. The models were used to explore the effects of logging rotation cycles and various levels economic investment in recreation and logging on total empower, sustainable empower, wood yield, environmental loading ratios, and emergy yield ratios. 9. To understand how empower and transformity change spatially, Geographic Infonnation System (GIS) models were developed for the Wme Spring Creek watershed that converged upland empower to stream channels. 10. To gain perspective on the level of economic activity supported by forests, emergy evaluations of Macon County, N.C., North Carolina, the U.S. forest products industry, and North American trade in forest products were conducted. 11. To see how emergy, transformity, and ratios of emergy-to-money changed for wood products throughout the ecological-economic system, emergy evaluations of the U.S. forest products industry were executed. 17

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.CHAPTER 2 lvfETHODS The general approach in this dissertation was to use systems diagramming, emergy evaluations, and dynamic simulation models to explore the emergy basis of forest wealth. A detailed description of each method is given in this chapter. Systems Diagrams To gain an overview perspective on the systems evaluated, system diagrams were drawn with the energy systems language (Odum 1994, see Appendix A for definition of symbols). The process of developing each energy systems diagram was as follows: 1. The spatial and temporal boundaries of the system were defined, 2. A list of exogenous energy sources that crossed the system boundary was formulated, 3. The internal units (state variables) of concern--those considered to vary over time-were listed, 4. Preliminary, complex diagrams of the systems were drawn, arranging all driving energy sources and internal components according to their transformity, 5. Driving energy sources and components were connected with appropriate pathways, 6. Symbols of complex diagrams were aggregated, reducing visual complexity to increase understanding of overall system organization. The system diagrams were then used as the foundation for creating the emergy evaluation tables. The system diagrams were also used as the basis for developing computer simulation models. 18

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.19 Emergy Systems Evaluations The energy of flows and storages of the systems investigated were evaluated in energy and mass and then converted to emergy. The methodology of emergy evaluation was to construct a system diagram that included all flows and storages thought to be important and then to construct an emergy evaluation table from the diagram. Each energy or material crossing the system boundary appeared as a line item in the emergy table. A table like that in Table 2-1 was developed for each system based on its systems diagram. Table 2-1 demonstrates how energy and material flows were converted to solar em joules by mUltiplying by solar transformity. The emdollars of a flow or storage were found by dividing the solar emergy by the mean emergy-to-dollar ratio of the regional economy (NCEDR). Unless calculated within this work or otherwise noted, transformities used in this research were taken from Odum (1996). Generally, transformities of environmental inputs (e.g., solar radiation, rain) were based on global data, and thus represent global means. Table 2-1. Emergy evaluation template for calculating solar emergy, emdollars, and solar transformity Note Item Inputs: 1 A 2 B Outputs: Physical Units (J, g, $, etc) Solar emergy per unit sej/J, sej/g, sej/$) Solar Emergy (sej) Ma=EaxTa Mb=EbxTb 3 C Ec Tc=MJEc Mc=Ma+Mb Note: NCEDR = emergy-to-$ ratio of North Carolina Emdollars* (NC Em$) Em$a = Ma / (NCEDR) Em$b = Mb / (NCEDR) Transformities for inputs were generally based on a system of larger scale. The transformity of outputs, on the other hand, were calculated for the system evaluated. In

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 2-1 the transformity ofC (Tc) was calculated by dividing the total input emergy (Me) by the energy ofC (Ec). Ifhowever, the two inputs were from the same source of emergy, the greater of the two inputs were taken as the emergy input to avoid double counting. Computer Simulation Models Computer models were developed with the iconographic simulation software Extend to explore the dynamics of forest emergy. The process of developing models was as follows: 1. using the Extend software, pre-programmed energy systems icons represent sources, interactions and storages were positioned on the modeling worksheet and connected (since the icons were pre programmed with mathematical definitions, the differential equations were created once the energy systems icons were connected), 2. the kinetics of models were calibrated by entering rates for pathways and states for storages directly into dialog boxes of energy systems icons (generally models were calibrated based on a steady state condition), 3. to simulate emergy, the transformity of sources was calibrated, 4. simulations were conducted and output (time series graphs) produced on screen. See Tilley (1996) or Odum and Odum (in press) for more details on simulating energy systems models with Extend. Odum (1996) suggested the general rules (see Table 2-2) for simulating emergy. 20

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 2-2. Rules for simulating the temporal dynamics of emergy (Odum 1996) Condition of energy storage Rules for accumulation of emergy Amount of energy stored is increasing The gross accumulation of emergy is the sum of all inputs; Amount of energy stored is decreasing The net accumulation is the gross less the export of 'usable' emergy. Gross accumulation is zero; The loss of emergy equals the energy lost times its transformity. 21 Amount of energy stored is not changing The accumulated emergy remains the same. Two simulation models, EMERGYDYN and EMSPECIES, were developed to investigate the temporal dynamics of forest components and to explore the dynamic calculation of transformities The first model, 8vfERGYDYN (Figure 2-1), was developed to simulate the temporal dynamics offorest storages, and the second modeL EMSPECIES (Figure 2-2), was developed to simulate the emergy of tree diversity. Figure 2-1 shows the system diagram and equations ofEMERGYDYN. In EMERGYDYN a single storage of energy was a balance between production-an autocatalytic process driven by rain and deep heat-and losses from export and depreciation. Export was a loss from storage that carried away emergy with the same transformity as the storage, whereas depreciation was unavoidable loss from storage that did not subtract emergy. Emergy inputs from rain and deep heat were the sources included because they are considered to be independent sources of emergy. Rain emergy is a co-product of the earth's biogeo spheric system which is driven by sunlight, tides, and deep heat. This precludes adding sunlight as a source of emergy because it and rain are from the same

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Dispersed material with NO emergy Material EMERGYDYN Equations for energy R, & G are constant sources of energy; Q is storage of energy. Rr = RI (1 + k1QG) dQ = k2Rr QG k3 Q -ksQ Equations for emergy MQ is emergy ofQ, T R, T G, T Q are transformities of R,G,Q. IfdQ > 0 dMQ = T R(k1 RrQG) + T G(ksRrQG) TQ(ks Q ) If dQ < 0, then dMQ =TQ(dMQ) Else dMQ=O. Ta=Ma'Q Figure 2-1. Systems diagram and equations for the model EMERGYDYN, used to simulate the energy, emergy. and transformity of watershed storages. 22

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.EMSPECIES r, G & C are constants R=rxArea Ry.=R/(l +k1S) -=-MV' MS: emergy in V & S, respectively; TR, Tu. Te, TV, & TS: transformity of rain, deep heat, new tree species, biomass, and stored tree species. Equations of state: dV= k2RrS -k3V-ksVS2 -k7VGC If dS>O then, dS = kaVGC kgS k13S2 Emergy equations: If dV>O then, dMv = T R *k1 RrS -T V*k7VGC IfdV < 0 then dMv=TV*dV ElsedMv=O dMS = T V*k7 VGC + T G *ksVGC + T C *k11 VGC -T 5 *kg 5 IfdS < 0 then dMS = TS*dS Else dMS = 0 23 Figure 2-2. Systems diagram and equations of model EMSPECIES, used to simulate the species abundance, emergy of tree species, and transfonnity of tree species.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.24 emergy source. Doing so would be double counting emergy. Deep heat released from mountains, on the other hand, is considered to represent an emergy contribution from an earth storage that was created long ago. Therefore, its source of emergy was different from that which created rain and it can be added as an independent source of emergy. For each type of forest storage simulated with EMERGYDYN, the transformities ofrain and deep heat were 1.8 E4 and 3.4 E4 sej/J, respectively. Calibration values for production, depreciation, and export were specific to each forest component. The mini-model EMSPECIES (Figure 2-2) was used to determine emergy values of tree species. As previously proposed by Odum (1996), Orrell (1998), and Keitt (1991) respiration increased as the square of the number of species to account for the energetic loss of supporting not only more species, but more possible interactions between them. The number of species was a function of biomass, mountain uplift and the number of species available to colonize the forest (i.e., seeds). Equations for simulating emergy were programmed into EMSPECIES and transformities of driving energies (rain, earth deep heat, and species recruitment) were added so that the emergy value of species diversity could be explored. The transformities were 1.8 E4 sej/J for rain, and 3.4 E4 sej/J for deep heat. The empower per tree species (2 E20 sej/y/tree species) was taken from Orrell's (1998) work in north central Florida.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.25 Environmental Driving Energies Energy and Emergy of Wind A new methodology was developed and used for estimating the energy contributed from wind. First, wind speeds aloft (lOOOm) were approximated based on the general observation that, over land, near-surface speeds are 600/0 of speeds aloft (Barry and Chorley, 1992). Next, a vertical profile of wind speed was fitted to the two endpoints based on the curve-shape typically observed (Barry and Chorley, 1992). The total energy absorbed was found by numerically integrating the wind energy absorbed over the vertical profile in a spreadsheet (see Appendix D for details). The advantage of the method was that only near-surface wind speed data (typically reported at weather stations) were required. Emergy of the Calcium Cycle The emergy of the calcium cycle was investigated i) to refine the emergy methodology for evaluating nutrient cycles, ii) to develop baseline data on the calcium budget of a relatively undisturbed watershed, and iii) because calcium is an essential element for healthy forest growth that may become a limiting factor due to its scarcity in the bedrock. Calcium enters the Coweeta watershed via three vectors: dryfall by wind (aeolian), wetfall from precipitation, and mineralization of bedrock. In forested watersheds, calcium and other minerals circulate among three major reservoirs: aqueous solution in the soil, live vegetation, and soil organic matter. The fluxes and reserves of calcium and other nutrients (Mg, K, P, S, N, Na) in the Coweeta basin (WS 18) were derived from Swank and Waide's (1988) analyses of

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.precipitation and stream water chemistry, Monk and Day's (1988) calculations of the nutrient balance of vegetation, and Velbel's (1985) estimates of rock weathering and chemistry. 26 All of the external sources of energy that interact to operate the forest system are simultaneously cycling mineral nutrients. Therefore, the internal cycling of mineral nutrients is driven by the total empower of the watershed. For mountain watersheds, such as Coweeta, the independent sources of empower were rain, earth cycle (deep heat), and atmospheric deposition. (See the previous section on calibrating EMERGYDYN for an explanation of why rain and deep heat were independent emergy sources). As for the atmospheric deposition, it was considered an independent source of emergy as well. The majority of the minerals transported to the forest were of terrestrial origin, which means that they were eroded from land elsewhere (e.g., agricultural fields, forest fires). The forests gained minerals that were lost by another system. Emergy accounting protocol subtracts the emergy of erosion, so the emergy gain can be added to the forest without double counting. Bedrock weathering was a function of the rate at which the hydrosphere interacted with the lithosphere, with the process accelerated by the development of vegetation and soil. Thus, the emergy per mass of weathered bedrock was detennined by adding the empower of rain and deep heat, and dividing by the weathering rate. Spatial Distribution of Empower in the Wine Spring Creek Watershed The spatial configuration of stream empower within the Wine Spring Creek watershed was developed by converging upstream empower, provided by rain and deep

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.heat, into the stream channels. The coverage was developed according to the following steps: 1. The elevation gradient of empower density for each incoming emergy source, rain and deep heat, was developed by linearly interpolating between the low (900m) and high (l600m) extremes. 2. Topographic coverages (developed from DEM's-digital elevation models) were converted to empower density coverages based on the elevation gradient developed in step 1, and added to produce a coverage of incoming empower density. 3. A coverage of the stream network was developed using the routine in the GIS software ArcView that is generally used to define stream channels and watershed boundaries. 4. The convergence of empower to the stream channels was calculated by weighting upstream cells with their total empower density (rain plus deep heat) when running the same "hydrologic" routines in the GIS software. Spatial Distribution of Soil Organic Matter in the Wine Spring Creek Watershed 27 The spatial distribution of soil organic matter was investigated based on soil data collected by Forest Service personnel and soil coverages produced by the USDA Soil Survey. Soil data was provided in tabular form along with a hard copy map of sampling locations, courtesy ofH. McNab and S. Browning of the US Forest Service. The average organic content of each soil type was determined from the soil database. The average elevation of each soil type was determined from the USDA soil survey. The elevation gradient of soil organic matter was then estimated by plotting average soil organic matter content of each soil type against its average elevation. Coverages of soil organic matter plotted the average soil organic by soil type. Spatial Distribution of Empower in N.C. To investigate the spatial distribution of empower in North Carolina, coverages of environmental empower were developed and combined with a coverage of purchased

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.28 empower to create a coverage of emergy investment ratio (empower purchased to locally renewable). The locally renewable empower of a county was the sum of rain, natural erosion, and waves. The spatial distribution of rainfall was simplified from a detailed map (Clay et al. 1975) into three divisions, corresponding approximately with the three physiographic provinces (Coastal Plain, Piedmont, and Blue Ridge). A similar spatial division was made for natural erosion based on Simmons' (1993) long-term investigation of the sediment yield from various types of drainage basins (Le., pristine forest, agriculture, urban). Wave energy was added to the coastal counties based on coastline length. The length of coastline for each coastal county was measured from the GIS coverage. The purchased empower for each county was estimated as the product of county income ($/y), the emergy-to-$ ratio of N.C. (1.1 E12 sej/$), and a correction factor (1.92). The correction factor accounted for the difference between personal income and gross state product and was calculated here as gross state product divided by total personal income. County income was from 1990 (US Census Bureau, 1996). The estimator of emergy imported to a county was a sole function of dollar flows and the renewable emergy was based only on rainfall, geologic uplift, and waves. The estimate of imported emergy could be improved by considering each county in detail, taking into account the emergy of fuel use, road construction, services of state government, activity at universities and colleges, and any other major source of emergy. The estimate of the renewable emergy inputs could be improved by considering use of groundwaters, rivers, and soils.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.29 Emergy of the U.S. Forest Products IndustIy The majority of data for the emergy evaluations of forest products came from four sources. The U.S. Census Bureau (1992) provided information on services, labor and capital as well as on the dollar value of production. A USDA Forest Service resource bulletin by Ulrich (1990) gave necessary statistics for total wood use by various economic sectors. Data on energy use came from the U.S. Department of Energy's Energy Information Administration (EIA 1991) and the American Paper Institute's annual reports (APL 1989). Minor amounts of data were supplied by Commerce Research Bureau (CRB 1996). The trade in forest products between Mexico, Canada and the U.S. was evaluated by converting reported dollar flows of exports and imports (Lyke, 1998) into emergy flows based on each forest products emergy to dollar ratio that was calculated in this work. The emergy flows were then converted to emdollars using the average U.S. emergy-to-$ ratio for 1995 (1.5 E12 sej/$, Odum 1996).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.CHAPTER 3 RESULTS The results chapter is organized into two broad sections with several subsections within each. In the first section, results of the emergy evaluations of the Coweeta and Wine Spring Creek watersheds are given which include evaluations of the major internal processes and main storages. In the second section, the value of forest products to economic systems is addressed. The section comprises emergy evaluations of the economies of Macon County, N.C. and the state of North Carolina, including the contribution of forests. Also given in this section are results of the emergy evaluations of the forest products industry of the United States, and an emergy evaluation of the international trade in forest products. Finally, the historical (1950 to present) world consumption of wood was evaluated as emergy. Emergy Evaluation of Forested Watersheds The diagram in Figure 3-1 demonstrates not only the interconnectedness of the units of the Coweeta watershed (WSlS), but also highlights the important role that external energy sources play in determining the architecture of the watershed. The energies of the meteorological system--solar radiation, kinetic energy of wind, atmospheric vapor saturation deficit, and rain-interacted with the ancient geology to create a mixed-hardwood forest with rich soils. 30

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Coweeta watershed Tilley I 1998 Figure 3 -1. Systems diagram of the forested watershed (WS 18) at Coweeta Creek (N-nutrients, e-water vapor, O.M.-organic matter). \.H ....

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.32 Figure 3-2 shows the system diagram of Wine Spring Creek (WSC) watershed. The diagram emphasizes the multi-purpose role of the watershed. In addition to the forest and mountain capturing the energies of the environment (similar to the Coweeta watershed) the diagram reveals the interconnections of environment and economy, and highlights the fact that the environment is the basis of the human-built infrastructure and outside attraction. The natural features of the watersheds were quite similar except for elevationCoweeta (WS IS) was lower, but public use of the watersheds represented two different cases for the Southern Appalachian Mountains. WS IS was chosen for the analysis because it represented a relatively pristine watershed with little economic activity, other than scientific investigation and Forest Service management, and because it has been heavily studied over the past SO years. The WSC watershed on the other hand had significant economic inputs in the form of tourists, scientists, Forest Service management, and timbering activities. In the sections that follow, the empower of each environmental energy (sunlight, atmospheric deposition, wind, water vapor, rain, and mountain uplift) was evaluated for the two watersheds, Coweeta WSlS (Figure 3-1) and Wine Spring Creek (WSC; Figure 3-2) and used to determine values for watershed processes, storages, and exports. Imported energies were evaluated for the WSC watershed, as well as its economic outputs. Environmental Driving Energies Table 3-1 lists each of the environmental energies used at Coweeta WSIS. In order of the amount of emergy contributed they were: chemical potential of rain

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Environment Wine Spring Creek watershed Water Runoff Tilley, 1999 Timber Research Figure 3-2. Systems diagram of the environmental--economic interface of Wine Spring Creek watershed. w w

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.34 Table 3-1. Emergy evaluation of watershed 18 (WSI8), Coweeta Hydrologic Lab {annual flows Eer hal. Emergy Solar Emdollar Note Item Physical Unit per unit Empower Value (sej/unit) (E12 sej) (1992 Em$) ENVIRONMENTAL ENERGY SOURCES: 1 Sunlight 5.0E+13 J 1 50 45 2 Vapor saturation deficit 1.2E+12 J 5.9E+02 715 650 3 Wind, kinetic 1.9E+11 J I.5E+03 281 256 4 Water evapotranspired 4.5E+1O J 1.8E+04 814 740 5 Precipitation, chemical 9.6E+1O J 1.8E+04 1744 1586 6 Deep heat 1.4E+1O J 3.4E+04 462 420 7 Precipitation, geopotential 1.4E+1O J 1.0E+04 141 128 8 Atmospheric deposition 3.0E+04 g 1.0E+09 30 27 9 Ca as dryfall (wind) 9.1E+02 g 1.0E+09 1 1 10 Ca as wetfall (rain) 3.7E+03 g 1.0E+09 4 3 11 Ca from rock weathering I.SE+04 g 4.6E+09 84 76 INTERNAL PROCESSES (transformities calculated) 12 NPP, total live biomass 2.1E+11 J 6.1E+03 1306 1187 13 NPP aboveground 1.2E+ll J 1.1E+04 1306 1187 14 RootNPP 8.8E+1O J 1.5E+04 1306 1187 15 Wood accumulation 6.2E+1O J 2.1E+04 1306 1187 16 Litterfall 6.4E+1O J 2.0E+04 1306 1187 17 Leaf production 6.2E+1O J 2.1E+04 1306 1187 IS Rock weathering 4.8E+05 g 4.6E+09 2237 2033 19 Calcium cycle 8.4E+04 g 2.1+10 2237 2033 20 Total mineral cycle 3.6E+05 g 6.2E+09 2237 2033 EXPORT (transformities calculated) 21 Stream discharge (chern) 5.1E+1O J 4.4E+04 2237 2033 Stream discharge (goo) 6.4E+1O J 3.5E+04 2237 2033 Stream discharge (mass) 1.0E+I0 g 2.2E+05 2237 2033 22 Calcium export 7.0E+03 g 2.7E+1O 186 169 23 Dissolved mineral export I.5E+05 g 6.2E+09 926 842 NPP net primary production Empower for primary production: evapotranspiration + deep heat + atmos. deposition. EmpoWer for rock weathering. Ca cycle, and stream discharge: rain + deep heat + atmos. deposition. Transformity = annual empower divided by annual energy flow. Footnotes to Table 3-1 appear in Appendix A

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.(transpiration), water vapor saturation deficit, geologic uplift (deep heat), wind (physical), geopotential of rain, sunlight, and atmospheric deposition. 35 In Table 3-2 the environmental energies ofWSC are shown. The rank order was different from Coweeta WS18: geopotential chemical potential of rain (transpiration), geologic uplift (deep heat), water vapor saturation deficit, wind (Physical), sunlight, and atmospheric deposition. From Table 3-1 the total incoming environmental empower for the Coweeta watershed (2240 EI2 sej/ha/y; 2040 Em$/ha/y) was found by summing the three (3) sources which had independent sources of emergy: chemical potential of rain, deep heat, and atmospheric deposition. Based on identical energy sources, WSC (Table 3-2) had approximately the same total environmental empower (2260 E12 sejlha/y, -2060 Em$/haly). Figure 3-3 shows power (rate of energy) and empower (rate of emergy) spectra, highlighting the differences and similarities in environmental inputs to Coweeta and WSC watersheds. When graphed as power used versus transformity (Figure 3-3a) the graph demonstrated the hierarchical property of energy quality. Energy oflow transformity (e.g., sunlight) was more abundant than energy of high transformity (e.g, deep heat). Figure 3-3b compares the empower spectra of the two watersheds. Normalizing energy to solar emergy corrected the vast discrepancies in the quantitative differences contributed by energy sources. All emergy flows were within an order of magnitude of each other.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.36 Table 3-2. Emergy evaluation ofWme Spring Creek watershed (annual flows per ha, -1995}. Emergy Solar EmdolIar Note Item Physical Unit per unit Empower Value (sejlunit) (E12 (1992 Em$) ENVIRONMENTAL ENERGY INPUTS: 1 Sunlight 5.0E+13 J 1 50 46 2 Vapor saturation deficit 7.2E+l1 J 5.9E+02 423 384 3 Wind, kinetic (annual) 1.9E+11 J I.5E+03 281 256 4 Precip., geopotential 5.6E+1O J 1.0E+04 577 525 5 Hurricanes (long tenn) 5.2E+1O J 1.0E+04 522 474 6 Precip., chemical 9.1+10 J 1.8E+04 1763 1,603 7 Transpiration 2.1+10 J 1.8E+04 484 440 8 Deep heat 1.4E+I0 J 3.4E+04 468 425 9 Atmospheric deposition 3.0E+04 g 1.0E+09 30 27 IMPORTED ENERGY SOURCES: 10 Auto-fuel, visitors within 2.1E+08 J 6.6E+04 14 12 11 Auto-fuel, thru traffic 2.1E+09 J 6.6E+04 136 124 12 Visitors, length of stay 8.6E+07 J 8.9E+06 768 699 13 Timbering, services 9 $ 1.5E+12 13 12 14 Timbering, fuels 1.6E+07 J 6.6E+04 1 1 15 Road maintenance 88 $ 1.5E+12 133 121 Forest Service 13 $ 1.5E+12 20 18 16 Researchers time 4.0E+06 J 3.4E+08 1377 1,252 INTERNAL PROCESSES (transfonnities calculated): 17 NPP, total live biomass 2.1E+ll J 4.7E+03 982 892 18 Wood accumulation 6.2E+1O J 1.6E+04 982 892 19 Litterfall 6.4E+I0 J 1.5E+04 982 892 20 Rock weathering 6.0E+05 g 3.8E+09 2261 2,055 21 **Tree diversity 30 species 3.3E+13 982 892 EXPORTS (transformities calculated): 22 Stream discharge (chern) 7.0E+I0 J 3.2E+04 2261 2,055 Stream discharge (goo) 1.3E+11 J 1.8E+04 2261 2,055 Stream discharge (mass) 1.4E+I0 g 1.6E+05 2261 2,055 23 Timber w/out service 4.1E+09 J 3.0E+04 124 113 Timber with service 4.1E+09 J 7.0E+04 291 264 24 Recreated people 8.6E+07 J 2.4E+07 2065 1,877 25 Research information I.2E+03 J 3.1E+12 3790 3,446 26 Total export (items 6,8-16) 4722 4,293 ** Tree diversity varies with sampling area, 30 species observed in first ha sampled. Footnotes to Table 3-2 appear in Appendix A

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.1.0E+14 .::---'>, l.OE+13 -WSC -;'tU ::: l.OE+12 '-' 1.0E+ll CZl ::> Q., B l.OE+I0 l.OE+09 1.0E +08 -t-........... """"!----..... ............ "I--' ........... """'+-..................... 't--" ........... """'+-..................... 't--" ........... A lE+O lE+l lE+2 lE+3 lE+4 lE+5 lE+6 lE+7 Transformity (sej/J) 1000 900 800 700 600 500 400 300 200 100 o lE+O lE+l lE+2 lE+3 lE+4 lE+5 lE+6 lE+7 Transformity (sej/J) Figure 3-3. Power (a) and empower (b) spectra of environmental energy inputs to Wine Spring Creek (squares) and Coweeta (circles) watersheds. S-sunJight, V-vapor saturation deficit, W -wind,RG-geopotentiaI precipitation, ET -evapotranspiration, D-deepheat, F-fuels, H-human service. (see Tables 3-1 and 3-2 for details of calculations). 37

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.38 Figure 3-3b (empower spectrum) also revealed differences in the distribution of environmental energies used by the watersheds at Coweeta and WSC. Coweeta used more energy from the vapor saturation deficit and the chemical potential of transpiration, but less in the form of rain geopotential. The higher altitude of WSC (900 to 1600m v. 726 to 993m) likely contributed to the differences. Imported Driving Energies As shown in Figure 3-2, non-renewable, non-indigenous forms of energy (e.g., road construction material) were imported and matched with the locally 'free: environmental energies to build and maintain an infrastructure (e.g., roads, scenic overlooks) within the WSC watershed. The infrastructure made it possible for the forest's resources to be utilized by scientists, local travelers, tourists, hunters, and loggers. Table 3-2 shows the value of the energies imported to the WSC watershed. The watershed received over 15,000 visitors annually as part of the regional Southern Appalachian tourist attraction (Cordell et a1.1996). People used various energies, notably automotive fuel and their human services, to enjoy the recreational opportunities. In one year, visitors consumed 14 E12 sej/haly (12 Em$/ha) of automobile fuel travelling around inside the WSC watershed. An additional 136 E12 sej/haly of auto-fuels were consumed by local through-traffic. Cordell et al. (1996) determined that the average length of stay for visitors was 19 hrs (an overnight stay). This represented about 200 people-hrs/ha, the equivalent of768 E12 sej/haly assuming that the transformity of a recreating individual was equal to a typical U. S. citizen on an average day. Table 3-2 also gives the values of the services imported to the WSC to extract timber, maintain the roads, manage the forest, and conduct science. The Forest Service,

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.39 over the last 25 yr was paid an average of $91ha/y by logging companies to harvest timber. This, combined with the fuels used in timber harvesting was valued at 14 E12 sej/ha/y. This was an order of magnitude less than the Forest Service expended (133 E 12 sej/haly) to maintain thirty-two (32) Ian of roads-nine (9) Ian of paved road and twenty three (23) Ian of unpaved service roads. Table 3-2 shows that the largest imported source of emergy was the scientist participating in the WSC Ecosystem Demonstration Project (1377 EI2 sej/haly). Internal Processes The internal processes of forest production, biogeochemical cycling, and maintenance of tree diversity were evaluated with emergy and are given next. Forest production Tables 3-1 and 3-2 list the elements of forest production evaluated and give the empower that operated them in the Coweeta (1306 E12 sejlha/y) and WSC (9S2 sej/ha/y) watersheds, respectively. In each empower of forest production was the sum of transpiration, deep heat, and atmospheric deposition. Tables 3-1 and 3-2 also provide the transformities for net primary production, root production, wood growth, litter and leaf production for Coweeta and WSC watersheds. They ranged from 4.7 E3 sej/J for total net primary production in the WSC watershed to 2. I E4 sej/J for wood accumulation in WS IS (Coweeta). Biogeochemical C!}'cIes Given in Table 3-3 are data for seven (7) sub-basins of the Coweeta watershed (#'s 2, 14, IS, 27, 32, 34, 36) used to calculate the empower of the weathering process and the emergy of weathered material. Figure 3-4 is a graph of select data from

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-3. Empower and weathering rates for seven (7) sub-basins of Coweeta watershed. Altitude-specific Total Emergy Sediment Sun Rain Geologic empower empower per gram discharge Relative Precipit Mid-Weatheri Empower Empower Empower per mass per mass of water, per water Area, solar ation, Runoff, elevation, ng rate, Density, Density, Density, weathered, weathered I E5 sej/g-runoH: WS# ha radiation cmly cmly m kglhaly sej/haly sej/haly sej/haly lE9 sej/g IE9 sej/g 36 49 81 222 168 1282 779 4.1E+13 2.0E+15 1.5E+15 2 12 95 177 85 857 652 4.8E+13 1.6E+ 15 8.9E+14 34 33 90 201 118 1018 529 4.5E+l3 1.8E+15 8.2E+14 18 13 50 194 103 860 482 2.5E+13 1. 7 E+l 5 6.6E+14 32 41 81 240 171 1078 328 4.1E+13 2.2E+l5 5.3E+14 27 39 40 245 174 1258 325 2.0E+13 2.2E+15 6.1E+14 14 61 50 188 99 850 292 2.5E+13 1.7E+15 3.9E+14 Footnotes to Table 3-3 Area, precipitation, and runoff (Swank and Crossley, 1988) Mid-elevation = (max. + min)/2 (max and min from Swank and Crossley, 1988) Relative solar radiation: aspect scaled between 100 and 50. South=IOO; South-southeast=95, etc. Weathering rate calculated from Velbel (1984) Sun empower, sej/haly = (mean empower density, 50E12 sej/haly) x (relative radiation/IOO) Rain empower, sej/haly = (precipitation, cm/y)/IOO x (lE4 m"2/ha) x (IE6 glm"3) x (9E4 sej/g) 1.9 1.4 1.5 1.4 1.6 1.9 1.4 Geologic empower, sej/haly = (weathering rate, kglhaly) x (altitude-specific emergy per gram, sej/g) Altitude-specific empower pel' mass, sej/g: globally averaged empower per mountain erosion (see Table E-2) Total empower per mass weathered, sej/g = (Rain empower + geologic empower, sej/haly) / (weathering rate, glha/y) Emergy per gram of water, sej/g-H20 = Rain empower + geologic empower, sej/haly) / (water runoff, g-H20/ha/y) Sediment discharge per water runoff, glm"3 = (weathering rate, g/ha/y) I (water runoff, m"3/ha/y) 4.5 3.8 5.0 5.0 8.2 8.7 7.2 H2O g/m"3 2.1 46.4 2.9 76.7 2.2 44.8 2.3 46.8 1.6 19.2 1.6 18.7 2.1 29.4

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.50 0.0 s = 4.23E-4*U 49.5 1""2=0.92 / /-1.0 2.0 3.0 U, Emergy per gram of water, lE5 sej/g-water Figure 3-4. Concentration of suspended sediment in streams of the Coweeta basin as a function of emergy (rain+geology) per gram of water. 4.0 41

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-3. The graph shows that the concentration of sediment in stream waters increased as the emergy per mass of stream waters increased. The total empower flux (rain + geologic uplift) per mass of rock weathered ranged from 3.8 E9 to 8.7 E9 sej/g for the seven (7) Coweeta sub-basins (Table 3-3, column 12). 42 Figure 3-5a shows an overview systems diagram highlighting the energy basis of the calcium cycle. Atmospheric deposition of calcium penetrates the soil is used by falls to the ground as litter, and is mineralized by soil processes. Acidic runoff waters percolate through the soil, down to the regolith, mineralizing the bedrock. Calcium ions from the mineralized bedrock and organic matter are placed in soil solution where the cycle begins again. Growth of forest biomass accelerates the mineralization process due to the addition of carbonic acid from soil respiration Thus, the calcium cycle evolves over time, maturing with the forest. Figure 3-5b shows that the three sources of calcium (wind, and bedrock) provided 1.0,3.8, and 18 kg-Calha/y, respectively, to WS 18 of the Coweeta watershed. The rate ofintemal cycle, measured at plant uptake, was 82 kg-Calhaly, -3.5 times the annual input. The watershed exported 7 kg-Ca/ha!y. The internal reservoir of calcium, live vegetation (830 kg-Calha) plus soil (620 kg-Calha), had a residence time of -63 y assuming a constant rate of influx. Figure 3-5c shows the emergy budget of the calcium cycle of Coweeta. Calcium which entered the forest via dryfall and wetfall contributed, I E12 and 4 E12 sej/haly,

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.--... Calcium Water & Energy A. Energetics of Calcium cycle at Coweeta RAIN ROCKS Terrestrial Flows: kgJha/y Reserves: B. Calcium budget at Coweeta Figure 3-5. Energy systems diagrams of the calcium cycle of WS18 at Coweeta watershed. A) driving energies and calcitnn kinetics, B) calcium budget, and C) emergy of calcium inputs, internal cycle, and output. 43

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission..' Annucil -, Cycle 2237-" Flows: lE12 sej/ha/y C. Emergy associated with calcium inputs, internal cycle, and output. Figure 3-5. continued. 44

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.respectively, to the forest. The 18 kg-Ca/ha/y that weathered from bedrock represented 83 E12 sejlha/y. Maintenance of tree diversity 45 Figure 3-6a shows the tree species-area curve for high-elevation forests of the WSC watershed. The species area curve was developed from unpublished data gathered by K. Elliot (USDA Coweeta Hydro Lab) in the WSC watershed at altitudes greater than 1200 m. The number of tree species increased with area, but at a decreasing rate. Thirty two (32) tree species were found in total; twenty-nine (29) of which were found in the first hectare (10,000 m 2 ). Figure 3-6b shows the empower-species curve for the WSC forest which was developed by substituting annual empower for area. Approximately 2000 X1012 sej/y supported thirty (30) tree species in the WSC forest, but a 50% increase in empower (1000 XI012 sej/y) over this amount was needed to support thirty-two (32) tree species. Thus, the curve points out that to support another tree species, the additional amount of empower required is large. Emergy of Forest Exports Table 3-1 list the energy, emergy, and transformity of water, calcium, and minerals exported from the Coweeta watershed, while Table 3-2 lists the same information for the WSC watershed along with exports of recreated people, timber, and research information. Shown in Tables 31 and 3-2, water yield from the Coweeta and WSC watersheds were on the order of 2250 E 1 2 sej/haly.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.o xxxxxxxxxxxxx xxXX 10000 20000 Area, m2 30000 40000 35 CIJ CIJ-30 Q) 25 a. : 20 15 B x 10 x 5 z x xXX x XXXXxxxxxxxxx XXXX 1,000 2,000 xxxxxxxxxxxxxxxxxxx 3,000 4,000 Empower, 1012 sej y-1 5,000 Figure 3-6. Tree species as a function of area (a) and as a function of annual empower (b) for high-elevation (> 1200m) forest in the WIDe Spring Creek watershed. 46

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-1 shows that the calcium exported in stream water of the Coweeta watershed carried 186 E12 sej/haly. The total value of the minerals dissolved in the stream water was 926 E12 sej/haly. (Stream chemistry data were not available for the WSC watershed). 47 Table 3-2 shows that wood accumulation in the WSC forest was 982 E12 sej/ha/y, about eight (8) times the value of the harvest, excluding services (124 E12 sej/haly). With the services added, the wood harvest was valued at 291 E12 sej/haly. Table 3-2 shows that the 15,000 people who visited the WSC watershed within a year (1995-96) enjoyed a total of2065 E12 sej/ha/y. This was the sum of environmental and economic inputs. Environmental inputs were taken as half of the annual empower of rain, deep heat, and atmospheric deposition, since the watershed was only open to the public for half the year, from April to November. Economic inputs were the sum of fueL human metabolism during their visit, road maintenance, and Forest Service empower. The research effort put forth to study the WSC Ecosystem Management Project by the team of Forest Service and university scientists, Forest Service personnel, and graduate students represented 3790 E12 sej/haly (Table 3-2). Research publications were produced at the rate of9.5 per year and their emergy value estimated at 450 E15 sej/publication (409, 000 EmS/pub). Transformity of Forest Exports Table 3-1 and 3-2 show the solar transformities calculated for the exports from the Coweeta (WS 18) and WSC watersheds. Due to its higher elevation, the chemical and geopotential energy of water exported from the WSC watershed was higher than that exported from the Coweeta watershed. This led to the WSC having lower transformities.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.The water leaving WS18 (1 EIO gIhaIy) had a mean emergy per mass of2.2 E5 sej/g water, while the water yield from WSC (1.4 EI0 gIhaIy) was 1.6 E5 sej/g. For comparison, global rainfall had an emergy per mass of 0.9 E5 sej/g. 48 Whereas the mean transfonnity of all wood accumulation in the WSC was 1.6 E4 sej/J, the harvested timber had a transfonnity 2 times greater (3.0 E4 sej/J; Table 3-2). The difference in transformity was due to the fonner being a flow and the latter a storage. That is, the transfonnity of wood accumulation was calculated as annual empower divided by annual growth and the transformity of harvested wood was emergy accumulated over its life span divided by its energy content. The transfonnity of the tourists' metabolic energy, while visiting the watershed, was estimated to the 15 E6 sejlJ (Table 3-2), about 700/0 greater than the 9 E6 sej/J for the average American (Odum 1996). The transformity of the research publications was estimated to be 3.1 E 12 sej/J (Table 3-2). Dvnamic Simulation ofEmergy in Forest Storages The natural wealth accumulated and stored as soil moisture, wood, total calcium, root biomass, total organic matter, saprolite, and tree species was evaluated for the forested watersheds using dynamic simulation. A simple product function that produced asymptotic growth to steady-state was used to estimate emergy stored as soil moisture, calcium, and root biomass. The two simulation models used for dynamic emergy accounting were EMERGYDYN and EMSPECIES. EMERGYDYN was used to simulate emergy of wood, total organic matter, and saprolite while EMSPECIES was used to simulate the emergy of tree species.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.49 Table 3-4 summarizes the dynamic simulation of emergy in soil moisture, wood, root biomass, calcium, total organic matter, living vegetation, saprolite, and tree species. Tree species were found to represent the largest storage of emergy that was measured (2,300,000 E15 sej/ha). Saprolite was two orders of magnitude less at 360,000 E15 sej/ha (330 million EmS/ha). Emergy in total organic matter, calcium, and wood were 795 E 15, 261 E15, and 169 E15 sej/ha, respectively. Water retained as soil moisture was 4 E15 sej/ha (4000 Em$lha). Emergy of wood Figure 3-7 is the systems diagram ofEMERGYDYN showing the calibration values for the energy and emergy flows. Figure 3-8 is a graph of the simulated values for emergy and transformity of wood in the Coweeta watershed. EMERGYDYN simulated the emergy accumulated in wood as 169 E 15 sej/ha by age 500 years, while the transformity of wood was 3.0 E4 sej/J. Emergy of total organic matter Figure 3-9 shows EMERGYDYN with values for energy, material, and emergy flows calibrated to simulate the total (live + dead) organic matter of WS 18. Calibration values for gross primary productivity (25 MT/ha/y), respiration (8 MT/ha/y), and export (2 MT/ha/y) were estimated based on the net primary productivity (15 MT/ha/y) measured in WS 18 by Day and Monk (1977) and on other values found for Southern Appalachian forests (Waide, 1988). Total empower input was the sum of rain (100 E9 J/ha/y x 1.8 E4 sej/J = 1800 E12 sej/ha/y) and deep heat (14 E9 J/ha/y x 3.4 E4 sej/J = 476 E12 sej/ha/y). Atmospheric deposition was excluded from the simulation models as a simplifying measure and since its contribution represented only 1% of total empower.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-4. Emergy evaluation of storages in one hectare of the forest at WS18 (Coweeta) Emergy per Item Physical Units unit a Emergy b (sej/unit) (E 15 sejlha) I Soil moisture 8.5E+lO J 5.2E+04 4 2 Wood 5.7E+l2 J lOE+04 169 3 Total organic matter 3.2E+13 J 2.5E+04 795 4 Calcium reserve I.5E+06 g 1.8E+1I 261 5 Sub-soil (saprolite) 9.2E+lO g 7.9E+09 725,000 6 Tree species 0.062 species 3.7E+22 2,300,000 Equations: a Transformity (sej/J) = emergy stored divided by energy a Emergy-to-mass ratio (sejlg) = emergy stored divided by energy (or mass) available. a Emergy per species (sej/unit) = emergy stored divided by species. b see individual footnotes in Appendix A C Emdollar value = emergy divided by North Carolina emergy-to-dollar ratio (ca. 1992) Footnotes to Table 3-4 In Appendix A Emdollar Valuec Em$lha 4.0E+03 1.5E+05 7.2E+05 2.4E+05 6.6E+08 2.lE+09

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.EMERGYDYN R, G, J1, JS: 1 E9 Jfna/y Q: MTJha a} Energy and material flows EMERGYDYN Transformity of rain & deepheat, T R & T G: sej/J Empower used from rain & deep heat, MJ1 & MJS: 1 E12 sej/haly b} transformity and empower of sources Figure 3-7. Energy systems diagrams ofEMERGYDYN used to simulate dynamics of emergy accumulation for wood biomass of the Coweeta watershed. Calibration of energy and material flows (a) and empower sources (b). 51

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.400 Transformity 35 (lJ Wood 30 L:; -j::: (lJ ar 300 25 m -.CD' ('I') -m 0 mit) 20 m ..... 200 -0 >. 15 E :.a CD Emergy .E "0 Q) ..L 10 CJ) 0 E 100 I c: 0 W (lJ 5 a a 250 500 750 Time, yr Figure 3-8. Simulation results ofEMERGYDYN calibrated in Figure 3-7 for wood biomass of Coweeta. Time series of wood biomass, emergy of wood biomass, and transformity of wood biomass are shown. 52

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.EMERGYDYN R, G, J1, J5: 1 E9 Jfna/y Q: Mffna a) Energy and material flows EMERGYDYN -Transformity of rain & deepheat, T R & T G: sej/J Empower used from rain & deep heat, MJ1 & MJ5: 1 E12 sej/ha/y b) transformity and empower of sources Figure 3-9. Energy systems diagrams of EMERGYDYN used to simulate dynamics of emergy accumulation for total (live + dead) organic matter of the Coweeta watershed. Calibration of energy and material flows (a) and transformity and empower sources (b). 53

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.These estimates of empower were each about 3% greater than the values given in the emergy evaluation table of Coweeta (fable 3-1) due to rounding. Figure 3-10 presents simulation output for total organic matter. Gross primary productivity (GPP) was within 10010 of its maximum value by year 100 and respiration lagged GPP by about 75 years. Net production peaked at year 50, and decreased asymptotically to zero (Figure 3-10a). Figure 3-10b shows empower and transformity of process rates for total organic matter. Empower used was at its maximum by the 200th year, but the empower export rate did not equal the input until year 750. The transformity of organic matter that was exported increased over time, reaching its maximum value of 11,000 sej/J by the 600th year. 54 Shown in Figure 3-1 Oc are the simulated values for the emergy and total organic matter stored. Although the physical quantity of organic matter required about 250 years to reach its maximum value (-1600 MT/ha), its transformity increased at a slower rate, requiring 500+ years to level-off at 11,300 sej/J. By year 750, the value of the total organic matter stored was 400 EI5 sej/ha (360,000 Em$/ha). Emergy of saprolite (regolith) EMERGYDYN was calibrated to simulate the emergy dynamics of saprolite formation in the Coweeta watershed (Figure 3-11). Formation and storage of saprolite was a function of the energy inputs of rain and deep heat, export, and dispersion. The two (2) meters of rainfall (equivalent to 100 E9 J/ha/y as chemical potential) and deep heat (14 E 9 J/haly) were the driving energies for saprolite production. The 91.5 E9 glha of saprolite was assumed to be in steady state with the production rate calibrated to equal

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Gross PP 45 15 Net Production of organic matter o o 250 500 750 A Years 2500 -r--------------. N a 2000 ->. --Q; o m (1)1000 w Transformity Empower Export ..... of Export Transformity 500 of Input o o 250 500 750 B Years 12 10 8 6 4 2 1800 -r-------------, 12 as o as $.1500 10t'b -ffi 10(1) 1200 -m -.! = 600 o m '-300 w Emergy 8 --.--, 6 E '-m .E (I) 4 (I) c: 2 o -r-=---,---,----r---,---.--+ 0 o 250 500 750 c Years Figure 3-10. Simulation results ofEMERGYDYN calibrated in Figure 3-9 for total organic matter of Coweeta. Gross production, respiration, and net production (a), empower and transformity of use and export (b), and transformity and emergy of storage (c) are shown. 55

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Dispersed Material EMERGYDYN R, G, J1, JS: 1 E9 Jlha/y S: 1 E9 g/ha J2, JS, J3: 1 E6 gJhaly a) Energy and material flows EMERGYDYN Empower of x, Mx: 1 E12 sejlhaly b) empower input 56 Figure 3-11. Energy systems diagrams ofEMERGYDYN used to simulate dynamics of emergy accumulation for saprolite of the Coweeta watershed. Calibration of energy and material flows (a) and empower sources (b).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.total loss (0.57 E6 glhaly). As a first approximation, total loss of saprolite was split evenly between dispersion and export (Le., each equaled 0.285 E6 g/haly). 57 The calibration value for the empower input from rain (1800 E12 sejlhaly) was energy input multiplied by 1.8 E4 sej/J. Similarly, deep heat empower (476 E12 sej/haly) was energy flow times 3.4 E4 sej/J (Figure 3-11 b). Figure 3-12 shows simulation of emergy of saprolite formation. Beginning with essentially bare rock and nearly no saprolite, the present day amount of saprolite (91.5 E9 g/ha) required 500,000 years to fonn. The emergy per mass of saprolite increased over time and reached its maximum (8 E9 sej/g) at year 1.5 E6. At the same time, the emergy accumulated in the saprolite leveled offat 715 E18 sej/ha (650 E6 Em$/ha). Emergy of tree diversity Figure 3-13a shows the model EMSPECIES with its mathematical equations. The model was used to simulate the emergy of tree diversity. Figure 3-13b shows the close correlation between the modeled and observed species area curves for the WSC watershed. The graph in Figure 3-13c is the emergy accumulated in tree species ofWSC watershed at elevations above 1200 m as a function of area. The graph is the simulated result of the model EMSPECIES shown in Figure 3-13a. In Figure 3-13c it can be seen that within an area of3.5 E4 m2 the emergy accumulated as tree species was 13 E22 sej (120 E9 Em$). Spatial Gradients ofEmergy and Empower in Mountain Watersheds The spatial dynamics of emergy empower, and transformity were evaluated for the mountain watershed and are presented in this section.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.800 700 600 m m r:.cE Emergy per mass 0> 'ii)' 500 01 en 0> T"' .... 0 400 oj'T"' .... := >. e 300 a. a> m E OOw 200 100 -{ / Saprolite a a 5 10 15 Time, 105 yr Figure 3-12. Simulation results ofEMERGYDYN calibrated in Figure 3-11 for saprolite (regolith) at Coweeta, Emergy, emergy per mass of saprolite, and quantity of saprolite are shown, ---9 8 7 0> en 6 010 T"' 5 m E 4 L-8. 3 L-a> 2 J] I 1 I a 20 VI oc

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.T-en ui Q) '0 Q) a. m Q) Q) '-+J '0 '-Q) .0 E ::l Z EMSPECIES Units: -Area-ha; biomass(V)-MT; species(S)-number of trees species; rain(r)-1 E9 J/ha/y; uplift(G)-1 E9 J/ha/y; new species(C)-trees. J1,J2,J3,J6,J7-1E9J per 0.08 ha per y; J8,J9,J11 ,J13-tree species per 0.08 ha per y. 50 40 30 20 10 0 0 1E4 2E4 3E4 4E4 8 Area, m 2 Figure 3-13. Model EMSPECIES used to calculate tree species abundance 59 and emergy stored as tree species for the Wme Spring Cree watershed. A) systems diagram of model EMSPEClES shown with calibration values for an area of 0.08 ha, B) tree species-area curves for elevations above 120Om: simulation results compared to observations made by K. Eliott (unpublished data, Coweeta Hydro. Lab.), and C) simulated emergy stored per tree species for elevations above 120Om.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.! 1 i 10 ctJ 0 8 I a o 0 4 ctJ Q) :>. Q. a e> en 2 6 i 0 +a ________ +-______ -r ______ W 0 10000 c Figure 3-13. continued. 20000 Area, m2 30000 40000 60

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.61 Spatial gradients of empower input Figure 3-14a is a systems diagram that explains how the spatial configuration of stream empower was calculated. Figure 3-14b is a map showing the spatial distribution of empower input across the mountain surface. Incoming empower density was greatest at the mountain peaks and decreased with elevation. Even though forest productivity has generally been found to be less at higher elevations (Odum 1970, Doherty et al. 1997), this map shows that the quality of the productivity may be greater since the empower density is greater. Figure 3-14c is a map of the stream empower showing the increase in empower downstream. First order streams carried in the range of 1 E 16 to 1 E 17 sej/y, while second order streams had from 1 E 17 to 1 E 18 sej/y, and the main segment of the Wine Spring Creek was carrying 5 E 18 sej/y at the watershed outlet. Figure 3-15 shows the areal distribution of the total empower density for the WSC watershed which was determined from the combination of the input empower and stream empower maps shown in Figures 3-14b and 3-14c. The distribution had a mode of 4500 E12 sej/ha/y with about 300 ha having this value. Ninety-eight percent (98%) of the watershed had an empower density less than 1 E 16 sej/ha/y. The greatest empower density (4 E18 sej/ha/y) at the mouth of the watershed represented a very small amount of the watershed. Spatial distribution of soil organic matter Table 3-6 shows estimates of soil organic matter for the WSC watershed by soil type. The mean organic content ofWSC soil was 232 MT ha -1. As shown in column 2 of Table 3-6, the floodplain soil Cullasaja, at 565 MT -O.M.lha, had more than twice the organic matter of any other soil type. However, by virtue of its limited coverage in the

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Overland & flow A Stream Upland empower density (lE12 sej/y) Mid-basin recharge grid 1 !Stream l ., )stream I flow 8 N 62 c:=J 3300 -3800 .. 3800-4300 ,,4300-4800 .. 4800-5300 1 0 1 Kilometers + !"'R_ Figure 3-14. Empower ofstrearns in the Wine Spring Creek watershed. A) systems diagram demonstrating how upstream empower from rain and deep heat converge from the ridge line down through the mid-basin region into the stream channel. B) map of upland empower density, C) map of stream empower.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Empower of stream (1 E12 sej/y) _Upland L:=J 1E4 to 1 E5 ,,1E5to 1E6 ,,1E6to5E6 Figure 3-14. continued. 63 N + 1 0 1 2 Kilometers ----

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.350 300 250 J ctJ 200 J .c I cO I I 150 1 < I 100 I 50 1 o 1000 10000 100000 1000000 10000000 Empower density, 1E12 sej/ha/y Figure 3-15. Areal distribution of environmental empower density in the 1128 ha Wme Spring Creek watershed. 64

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.65 Table 3-6. Soil organic matter in WSC watershed soil type. Mean soil Total soil orgamc Mean orgamc matter, elevation, Area, matter, Soil Type MTlha m ha MT Cullasaja 565 1315 129 72610 Plott 269 1382 349 93984 Tuckasegee-Cullasaja 231 1208 14 3216 Tuckasegee-Whiteside 231 1258 6 1448 Wayah 229 1523 51 11743 Cheoh 202 1207 126 25419 Edneyville-Chestnut 116 1351 259 30038 Chestnut 90 1454 2 147 Spivey-SanteetIah 89 1085 52 4589 Soco-Stecoah 87 1195 71 6176 Porter 72 1068 27 1949 Total 1085 251318 Mean 232 Footnotes to Table 3-6 Mean soil organic matter, MT/ha = mean soil depth x mean bulk density x mean organic fraction Mean elevation of soil type from GIS coverages of topography and soils.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.watershed, it only represented the second largest storage of soil organic matter (12.6 E3 MT). The Plott series, which generally has a north facing slope contained the greatest amount of soil organic matter. Figure 3-11 graphs average organic matter per soil type as a function of the average elevation of the soil type. The elevation gradient was 215 Mf-O.M./ha per km of elevation. Translating the soil organic matter to emergy based on a transformity calculated for the Coweeta soil organic matter (9.3 E4 sej/J), an emergy gradient of 482 E12 sej/ha m-1 resulted. 66 Figure 3-18 shows the spatial distribution of soil organic matter classified by soil type. Generally, north-facing slopes had soils with high organic matter content (116-210 MT-O.M./ha), although, the floodplain CuUasaja, had the highest organic content. Emergy Evaluation of Forest Economies The emergy basis of the state of North Carolina (-lxl07 hal and one of its counties, Macon (-lxlOs hal, was appraised to ascertain the prominence offorested ecosystems in linking environmental energies to the economic system of people. Macon County was chosen because it contained the two forested watersheds evaluated in this study. Emergy evaluations of the U.S. forestry industry were undertaken to determine how much wealth was contributed from forest ecosystems to economic systems. Lumber, plywood, pulp, and paper were included in the analysis. International trade in forest products between the U.S., Canada, and Mexico in the wake of passage of the North American Free Trade Agreement (NAFT A) was evaluated. Finally, empower consumed from the world's forests since 1950 was determined.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Q) --co E co .2 ..c 0 (J) 600 500 400 300 200 J 100 o I 900 O.M. = 0.275H 153 0 ,-2=0.08; p-value=0.05 1100 1300 o Elevation, m o 1500 Figure 3-17. Elevation gradient of soil organic matter in Wine Spring Creek watershed. Average organic matter per soil type as a function of mean elevation of soil type. 67

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.s Soil Organic Matter MTIha 72 -116 116 -270 _565 400 0 400 800 Meters ----a) topography of WSC watershed b) soil organic matter by soil type Figure 3-18. Topographic coverage ofWSC watershed (a) and spatial distribution of soil organic matter by soil type (b). 68

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.69 Macon County. N.C. The systems diagram of Macon County (Figure 3-19) highlighted the fundamental relationship that existed between forest ecosystems, mountains, and economy. Covering, 84% of the county land surface, forested ecosystems transformed the dilute, low transformity energies of sun, vapor deficit, wind, water, and geologic uplift into ecological commodities. Rainfall in the county, above the state average, was aided by the mountain system. These two main features of the landscape, forests and mountains, together provided the environmental basis for much of the county's economic activities. The county was chosen for analysis because it is home to both the Coweeta and WSC watersheds (see Figure 1-1). It also is a county representative of the Southern Appalachian Mountains. Environmental driving energies of Macon County As can be seen in Table 3-7, of the renewable energy sources used within the county, deep heat (0.63 E20 sej/y; 32 E6 Em$/y) was the largest. The use of rain chemical potential in transpiration (0.48 E20 sej/y), the use of rain geopotential (0.46 E20 sej/y), depression of the vapor saturation deficit (0.42 E20 sej/y), and wind (0.38 E20 sej/y) were not much less. Table 3-7 also shows the emergy values of the indigenous renewable energies used in Macon. These were ecosystem products made by the interaction of the environmental and imported driving energies. Of the three economic sectors linked directly to the environment (i.e., electrical power supply, agriculture, and forestry), hydro-electricity production (1.41 E20 sej/y) offered the most empower. Agriculture was second with 1.31 E20 sej/yand forestry was third, harvesting 0.60 E20 sej/y.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Forest 1 ", e =--+--J.. .. Agri-" La f, arkets J I Macon County, N.C. n.R. Tilley, 1997 Figure 3-19. Systems diagram of Macon county, N.C. (1992). C}

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.71 Table 3-7. Emergy evaluation ofresource basis of Macon Co., N.C. ca. 1992. Trans-Solar Value to Macon Note Item Physical Units fonnity Emergy County Economy {lE6 EmS, 1992! RENEW ABLE RESOURCES: 1 Sunlight 7.1SE+1S J 1 7.2 3.3 2 Rain (transpired) 5.96E+15 J 1.SE+04 IOS.4 49.3 3 Rain. geopotential 2.01E+15 J 1.1E+04 21.1 9.6 4 Wind, kinetic 2.56E+16 J 1.5E+03 3S.3 17.4 5 Saturation deficit 1.6lE+17 J 5.9E+02 94.S 43.1 6 Historic erosional loss 2.01E+10 g l.OE+09 20.1 9.1 7 Geologic Uplift 6.42E+14 J 3.4E+04 21.S 9.9 S Deep heat 1.SL.E+15 J 3.4E+04 62.0 2S.2 INDIGENOUS RENEW ABLE ENERGY: 9 Hydroelectricity S.S5E+14 J 1.6E+05 140.7 64.0 10 Total electricity use 1.41E+15 J 1.6E+05 223.S 101.8 11 Agriculture prod 3.86E+l4 J 2.0E+05 77.2 35.1 12 Livestock prod 2.70E+13 J 2.0E+06 53.9 24.5 13 Forest growth 4.25E+l5 J 2.lE+04 S9.1 40.5 14 Forest extraction 1.47E+15 J 4.1E+04 60.1 27.4 15 Fuelwood use 2.S7E+14 J 4.1E+04 11.8 5.4 NONRENEWABLE SOURCES FROM WITHIN SYSTEM: 16 Present erosional loss 1.07E+11 g 1.0E+09 107.2 4S.8 17 Gemstones 50,000 $ 1.5E+l2 0.1 0.0 IS Non-fuel minerals 3.52E+ll g 5.0E+OS 175.S 79.9 IMPORTS AND OUTSIDE SOURCES: 19 Petroleum Prods. 1.96E+15 J 6.6E+04 129.6 5S.9 20 Natural Gas J 4.SE+04 0.0 0.0 21 Coal J 4.0E+04 0.0 0.0 22 Electricity 5.22E+l4 J 1.6E+05 83.1 37.S 23 Livestock J 2.0E+06 0.0 0.0 24 Net Immigration 1.92E+12 J 2.5E+07 47.3 21.5 25 Machinery, Equipment 3.00E+09 g 6.7E+09 20.1 9.1 26 Wood J 1.7E+04 0.0 0.0 27 Fed. Government 3.S7E+07 $ 1.5E+12 58.1 26.4 28 Imports. non-tourism 2.58E+07 $ L5E+l2 38.7 17.6 29 Tourist (time) 1.11E+l3 J 2.5E+07 274.0 124.6 30 Tourist services 3.26E+07 $ L5E+12 48.9 22.2 EXPORTS: 31 Tobacco 8.79E+ll J 1.5E+06 1.4 0.6 32 Wood/wood prod 5.08E+14 J 1.7E+04 8.7 4.0 33 Livestock 6.69E+12 I 2.0E+06 13.4 6.1 34 Minerals 2.75E+ll g 5.0E+OS 137.6 62.6 35 Service in exports 2.5SE+07 $ L5E+l2 38.7 17.6 36 Fed. Government 3.87E+07 $ L5E+12 58.1 26.4 Footnotes to Table 3-7 are in Appendix A

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.72 The value of mineral resources extracted in Macon are also shown in Table 3-7. "--The county was mining sand and gravel aggregate for construction at the rate of 1.76 E20 sej/y. The quantity of gemstones used for the analysis were only commercially mined. An appropriate emergy/gram was not available, but the emergy associated with the money paid for the gems was calculated to be of minor importance (0.001 E20 sej/y). Present-day loss of mountain structure (80 g/m2/y) in Macon County was five (5) times as great as estimated pre-historic levels (15 g/m 2 /y). The value of the natural rate ofloss--the proxy for pre-historic rates-was 0.20 E20 sej/y (10 E6 Em$/y). With the introduction of man to the landscape, erosion rates were accelerated and the loss was 1.07 E20 sej/y (Table 3-7). The difference between the pre-historic and present-day rates amounted to an additional 0.87 E20 sej/y (44 E6 Em$/y) being lost from the county. Imported driving energies Table 3-7 includes the emergy values for the driving energies that were imported to Macon. In step with the rest of the state, Macon County imported significant quantities of petroleum products (1.30 E20 sej/y). However, Macon did not import natural gas or coal, leaving its diversity of fuel-use lower than North Carolina's. The use of nuclear powered electricity in Macon was not investigated, but its possible that some of the electricity used was produced in this manner and delivered via an electrical grid network. In fact 3']0/0 (0.83 E20 sej/y) of the total electricity used in the county was imported directly. In 1992, the net migration rate to Macon County was 503 people per year, 2% of the present population. Assuming they consumed resources at the rate of the average American, these additional people increased the empower demand of Macon county by

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.0.47 E20 sej/y (9% of annual total use). Money spent by tourist represented 0.49 E20 sej/y, while their time visiting was valued at (2.74 E20 sej/y, Table 3-7). This was the largest single source of empower to the county. Other imports included federal spending (0.58 E20 sejly), machinery & equipment (0.20 E20 sej/y), and services associated with imported products (0.39 E20 sej/y). Exports 73 Exports from Macon county are shown in Table 3-7. Exported products included tobacco, wood & wood products, livestock, non-fuel minerals, and services in exports and federal taxes. The total emergy value was 2.61 E20 sej/y (PIE plus N2 in Figure 320). Summary of Macon County emergy use Table 3-8 summarizes the emergy flows of Macon County by aggregating line items of Table 3-7 into categories that were based on the source of the energy. Figure 320 is a system diagram that defines the symbols used in Table 3-8. The emergy analysis of the resource basis of Macon county's economy revealed that total emergy use was 5.08 E20 sej/yfor the year 1992 (the sum ofR, NO, Nl, F, G, and P21 in Table 3-8). Assuming that the total emergy used was necessary to produce a county personal income of $258 million for 1992, then the emergy-to-dollar ratio was 1.97 E12 sej/$ (PI in Table 3-8). That same year, North Carolina's was lower (1.18 E12 sej/$); money in Macon purchased L 75 times more wealth than the state average.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.74 Table 3-8. Summary of flows in Macon county, N. C. circa, 1992. Symbol Item Solar Emergy Dollars (E 18 senl R Renewable sources 170 (rain chemical used, deep heat) N Slow-renewable sources flow within Macon 272 (NO, Nl, N2) NO Dispersed Rural Source 87 (accelerated loss of sediment) Nl Concentrated Use 38 (non-fuel minerals, gemstones) N2 Exported without Use 146 (non-fuel minerals, wood) F Imported Fuels and MineraIs 213 (oil derivatives, electricity) G Imported Goods 20 (machinery, transportation equip.) I Dollars Paid for Imports 2.58E+07 P2I Emergy Value of Goods & SeIVice Imports 39 E Dollars Received for Exports & Tourism 5.84E+07 PIE Emergy Value of Goods & SeIVice Exports 128 x County Personal Income 2.58E+08 P2 U.S. emergy/$ ratio, used in imports 1.50E+l2 PI Macon County Emergy/$ ratio 2.20E+l2 Z POQulation. 1992 23,500 Letters are given on pathways in Figure 3-20 for reference.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Rural systems 1.11 F' EMERGY (E20 solar emjoules/yr) I / / V x $ \ $0.258 '--" $ flows (E9 $/yr) Figure 3-20. Summary diagram of emergy flows of Macon County, N.C. (1992). ---...I VI

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.76 Shown in Figure 3-21 are the power and empower spectra developed for Macon County. The county's power spectrum demonstrated the hierarchical property of energy use, just as the spectra for the Coweeta and WSC watersheds did. The use of low quality energy (e.g., sunlight) was vastly greater than the use of high transformity energies such as that associated with tourists and migrants (Figure 3-21a). The empower spectrum in Figure 3-21b highlighted the significance of electricity and tourism in the county. Electricity use (2.2 E20 sej/y) was about four and a half (4. 5) times that of transpiration. Total people flux (tourism plus net migration) at 3.2 E20 sej/y was 6.1 times transpiration. North Carolina The systems diagram of North Carolina (Figure 3-22) described the role of external environmental and economic energies in supporting the interconnections of the state's main ecological and economic units. Beginning on the left of the diagram, the main ecosystems of the coastal zone (beaches, estuaries, and shelf), forests, and agriculture seized the diverse spectrum of environmental energies--sun, wind (vapor deficit and kinetic energy), rain, tides, waves and geologic uplift--and transformed them to ecosystem goods and services available for economic production and life support. Mineral deposits (phosphate and aquifers) and mountains, large reserves created by past environmental processes, provided the foundation for such industries as hydroelectric power production and phosphate mining. Continuing rightward in the diagram, the economic sectors of electric power generation, mining, logging, manufacturing and commercial services transformed the goods and services of the ecosystems, with the assistance of imported fuels and services, into products and services for peoples'

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.l.00E+20 -r---------------------.., -';:... 1.00E+18 t::!, l.00E+16 o 1.00E+14 1.00E+ 12 -+---'---'-...................... '"""!--................................ ""'"'+'--'-.......... ........ r__-------........... IE+O IE+2 IE+4 lE+6 lE+8 Transfonnity (solar emjoules/Joule) 4.0 -r-----------------------, _-3.0 ';:... Q Q) o rn 0.0 2.0 E NO X l.0 H E / 0.0 ........................... IE+O IE+2 IE+4 IE+6 IE+8 Transformity (solar emjoules/Joule) Figure 3-21. Power and empower spectra of the main resource inputs used in Macon County, N.C. (1992). Abbreviations: S-sunlight, V-water vapor deficit, W -kinetic wind, RG-geopotential of rain, RC-chemical potential of rain, G-geologic uplift, F-wood, P-petroleum, E-electricity, A-agricultural crops, H-human migration and tourism. 77

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.'6 VI Forest .. -....... ... --_ ..... __ .-----North Carolina Figure 3-22. Systems diagram of North Carolina (1992).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.consumption.. Furthest to the right in the diagram. N.C. traded goods and services, and exchanged money with outside markets and the federal government. The state also attracted tourists to its beaches and mountains. At every energy transformation, energy was irreversibly lost to the heat sink, shown at the bottom of the diagram. Environmental driving energies of North Carolina 79 Renewable energy sources used in North Carolina are shown in Table 3-9. Rain chemical-potential (177 E20 sej/y; 15 E9 EmS/y) provided the most empower. Depression of the water vapor saturation deficit (95 E20 sej/y), wind kinetic energy (81 E20 sej/y), and deep heat (74 E20 sej/y) were nearly equal. The use of rain geopotential (18 E20 sej/y), waves (6 E20 sej/y), and tide (2 E20 sej/y) were significantly less. Figure 3-23 shows that spatially, the intensity of environmental empower was greatest along the coastal counties, averaging as much as 8600 E 12 sej/ha/y in Dare county. Coastal empower was due to the interaction of rain and wave energies. Tides were also important to coastal counties, but for the emergy analysis, tides could not be added as that would be double counting emergy. Mountain counties had an intensity of environmental empower which averaged around 1300 E12 sej/ha/y. Piedmont and interior coastal plain counties had the lowest environmental empower density since rainfall was average, wave energy was of course zero, and geologic input (erosion) was smaller than the mountains. Table 3-9 lists emergy values for the non-renewable resources used in North Carolina. Extraction of non-fuel minerals such as granite, clay, mica, and feldspar

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.80 Table 3-9. Emergy evaluation of resource basis for North Carolina, ca. 1992. Physical TransSolar Value to North Note Item Units formity Emergy Carolina Economy (sej/unit) ( sej) (lE9 EmS, 1992) RENEW ABLE RESOURCES: 1 Sunlight 8.65E+20 J 1 8.7 0.7 2 Rain, chemical 9. 74E+17 J 1.8E+04 177.2 15.0 3 Rain, geopotential 1.14E+17 J 1.1E+04 12.0 1.0 4 Wmd. kinetic 5.4lE+18 J 1.5E+03 81.2 6.9 5 Saturation deficit 1.61E+19 J 5.9E+02 95.1 8.0 6 Hurricanes 3.0IE+16 J 4.1E+04 12.4 1.0 7 Waves 1.80E+16 J 3.1E+04 5.5 0.5 8 Tide 1. 12E+16 J 1.7E+04 1.9 0.2 9 Deep heat (state) 2. 16E+17 J 3.4E+04 74.1 6.3 Deep heat (mtn) 2.73E+16 J 3.4E+04 9.4 0.8 10 Historic sediment loss 1.38E+12 g 1.0E+09 13.8 1.2 INDIGENOUS RENEWABLE ENERGY USE: II Hydroelectricity 2.09E+16 J 1.6E+05 33.3 2.8 12 Agriculture production 8.40E+16 J 2.0E+05 168.0 14.2 13 Livestock production 9.49E+15 J 2.0E+06 189.9 16.1 14 Fisheries harvest 2.50E+14 J 2.0E+06 5.0 0.4 15 Forest growth 4.75E+17 J 2.1E+04 99.3 8.4 16 Forest extraction 3.72E+17 J 4.IE+04 152.4 12.9 17 Fuelwood use 2.9lE+16 J 4.lE+04 11.9 1.0 18 Direct water use 2.69E+15 J 5.4E+04 1.4 0.1 NONRENEWABLE SOURCES FROM WITHIN SYSTEM: 19 Phosphate Rock 5.50E+12 g 3.9E+09 214.5 18.1 20 Present sediment loss 5.05E+12 J 1.0E+09 50.5 4.3 21 Total Electricity Use 3.44E+17 J 1.6E+05 547.6 46.3 22 Non-fuel minerals 5.61E+13 g 5.0E+08 280.3 23.7 23 Soil loss, agriculture 2.92E+16 J 6.3E+04 18.4 1.6 Soil gain, forest land 3.25E+16 J 6.3E+04 20.5 1.7 IMPORTS AND OUTSIDE SOURCES: 24 Petroleum Prods. 8.81E+17 J 6.6E+04 581.3 49.2 25 Natural Gas 1.99E+17 J 4.8E+04 95.3 8.1 26 Coal 7.66E+17 J 4.0E+04 304.7 25.8 27 Nuclear, electricity 8. 16E+16 J 1.6E+05 129.7 11.0 28 Livestock, meat 1.08E+15 J 2.0E+06 21.5 1.8 29 Agriculture produce 4.34E+16 J 2.0E+05 86.7 7.3 30 Net Immigration 2.44E+14 J 2.5E+07 60.1 5.1 31 Metals 4.03E+12 g 1.0E+09 40.3 3.4 32 Wood, logs 2.58E+16 J 4.1E+04 10.6 0.9 33 Mach., transp. Equip 2.48E+08 $ 1.4E+12 3.5 0.3 34 Other imports. service 1.47E+10 $ 1.4E+12 210.2 17.8 35 Tourism 2. 13E+09 $ 1.4E+12 30.4 2.6 36 Fed. Government 2.89E+10 $ 1.4E+12 412.7 34.9

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.81 Table 3-9. continued. EXPORTS: 37 Tobacco 3.82+15 J 1.2+06 43.9 3.7 38 Fishery Products 4.23E+13 J 2.0E+06 0.8 0.1 39 Livestock 7.46E+15 J 2.0E+06 149.1 12.6 40 Phosphate Rock 5.45E+12 g 3.9E+()9 212.4 18.0 41 Cotton 5.21E+14 J 1.2E+06 6.0 0.5 42 Crushed stone 2.58E+13 g 5.0E+08 129.0 10.9 43 Lumber, fum., paper L42E+08 L. hr L3E+13 17.8 L5 44 Service in exports 5.54E+I0 $ L2E+12 655.1 55.4 45 Fed. Government 2.89E+I0 $ 1.2E+12 341.2 28.9 Footnotes to Table 3-9 in Appendix A

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.70 N + o 70 Empower density (1 E 12 sej/haly) 140 Kilometers ( Rain + geologic uplift + wave energy CJ <1100 1100-1700 1700-6000 6000+ Figure 3-23. Renewable empower density of North Carolina by county. Mountain counties of western N.C. (gray) have average rainfall and high geologic uplift, counties of the piedmont and interior coastal plain (white) have average rainfall and low geologic input, counties abutting the sea (dark)have average rainfall and high wave energy. 00 N

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.83 occurred at the rate of280 E20 sej/y. Mining of phosphate rock in eastern N.C. depleted the non-renewable stock at a rate of215 E20 sej/y, but only 2 E20 sej/y %) of the phosphate rock was used within N.C. The present rate of erosion was valued Cit 47 E20 sejly, which was accelerated beyond the background (pre-historic) rate (13 E20 sej/y) for a net difference of34 E20 sej/y (see Table 3-9). Imported driving energies Table 3-9 also provides estimates for the emergy of imported goods, services, and fuel-energies. North Carolina relied heavily upon fossil fuels for economic production. Petroleum (581 E20 sej/y), coal (305 E20 sej/y), and natural gas (95 E20 sej/y) represented 52% of the total emergy used in the state. Production of electricity from nuclear power plants required the importation of uranium and added 130 E20 sej/y to N.C.'s emergy budget. Imported meat and agricultural products were worth 147 E20 sej/y (Table 3-9). The state's industries imported metals, wood products and mechanical equipment, totaling 54 E20 sej/y. From 1983 to 1992, net migration to N.C. averaged 100,000 people per year (1.4% of the 1992 population). The empower of the immigrants was 60 E20 sej/y (3.2% of state annual empower) assuming they represented the average American. Tourism added a considerable amount of emergy to the state, 30 E20 sej/y (2.5 E9 Em$/y). Temporal trends in imported empower use in North Carolina. North Carolina's economy relied heavily upon an assortment of fuel energies to operate. From 1960 to

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.84 1994, N.C.'s total empower consumption from coal, natural gas, nuclear and hydroelectricity intensified 2.5-fold from 4.8 E22 sej/yto 12.3 E22 sej/y(Figure 3-24). Petroleum products provided the majority of fuel emergy used, while coal was the second most important. In 1975, nuclear electricity was first produced in the state and has continued to increase in significance. In 1994 nuclear provided 15% of the empower from "fuel-energies". Spatial configuration of imported empower. Spatially, the majority of counties receiving high inputs of imported energies were located in the Piedmont region (Figure 325). The exceptions to this pattern were New Hanover (Wilmington) and Cumberland (Fayetteville) counties in the Coastal Plain and Buncombe (Asheville) in the Blue Ridge province. Mecklenburg County, home to Charlotte, had the highest empower density due to imported resources (133 E15 sej/haly). Internal processes Forest growth. Figure 3-26 shows the growth in the forest growing stock and distribution offorest land in North Carolina. The data were calculated based on the U.S. Forest Service's Forest Inventory and Analysis (U.S. Forest Service, 1999). Growth in the growing stock in every county of N.C. was at least 1.25 MT/haly(500 E12 sej/haly) and greater than 2.75 MT/haly (1100 E12 sej/haly) in several eastern counties (Figure 3-26a). Growth in the growing stock was highest in the east and decreased toward the west. It was least in the mountain counties and intermediate to low in the piedmont counties. However, every mountain county had at least half(500/o) of its land cover as forest, whereas urbanized piedmont counties and a few agricultural counties of the east had forest coverage less than SOO/o (Figure 3-26b). Therefore, many of the mountain counties

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.'0)' U) 1.4E+23 1'". ---------------------------, Total 1,2E+23 1E+23 --8E+22 L-CD a. Petroleum 6E+22 .. -'''-"" / """ ""_.f''''' .. / --'" ,"",----./.-L-CD E w 4E+22 Coal ........ ""-._.' --_._----".,. ., Nudear .-. Hydroelectricity 2E+22 + .. ---.-.--.. ". .. '--. 0 1960 1965 1970 1975 1980 1985 1990 Year Figure 3-24. Historical consumption of primary fuels and electricity in North Carolina in units of emergy (1960-1994). ()O VI

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.N + 60 120 Kilometers o 60 Purchased empower density (1 E 12 sej/ha/y) D Less than 25000 25000 -50000 50000 -1 00000 100000 + Figure 3-25. Purchased empower density of North Carolina by county. Urbanized counties of the piedmont region showed the greatest empower density derived from purchased goods and services. Mecklenburg county in the south central section of thr-state had the highest empower density.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.(a) Growth rate of growing stock MT/ha/y i 11.25 to 2.00 2.00 to 2.75 2.75 to 3.75 (b) County Forest Cover % of total area 30 to 50% 50 to 75A, 75 to 98% Additions to growing stock per county ha of county 0.25 to 1.00 1.00 to 1.75 1.75 to 2.50 N + 87 100 200 Kilometers __ __ L-_---.l1 o 100 Figure 3-26. Maps of growth in growing stock (a), forest cover (b) and additions to growing stock (c) in North Carolina by county.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.were accumulating forest stocks at total rates commensurate with the productive eastern counties (Figure 3-26c). 88 For the state as whole, wood accumulated at the rate of 99 E20 sej/y (25 E6 MT/y), but was harvested at the rate of 152 E20 sej/y (19 E6 MT/y). In terms of biomass, the harvest rate was less than the growth rate, but in emergy terms, more was being extracted than was growing. The harvested wood was a storage that accumulated emergy over its lifetime. As a result, it had a higher transformity than the annual growth. This difference in transformity explained the difference in emergy flow. Water use. Figure 3-27a is a systems diagram of the water budget of North Carolina. Evaluation of the state water budget revealed that evapotranspiration equaled 115 billion m 3/y, approximately 66% of total rainfall on land. The remaining 34% (59 billion m 3 /y) left as surface runoff. The overwhelming majority of river flow was directed outward from N.C. and in three directions: west, south, and east. (The Roanoke drainage basin straddled the northern border abutting Virginia. Since the inflow from Virginia was a small part of the overall state water budget, its contribution was overlooked for this study). West and south bound waters entered either Tennessee, Georgia or South Carolina, and were no longer available to do work in N.C. On the other hand, eastbound rivers entered the coastal waters of N.C. where the interaction of their geopotential and chemical potential energies still had the ability to contribute to the state. The use of rainwater via evapotranspiration was 113 E20 sej/y (9.4 E9 Em$/y; Figure 3-27b). Rainfall over the continental shelf added another 24 E20 sej/y (2.0 E9 EmS/y).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.(a) Forests, grasslands, wetlands Water budget of North Carolina Water flows: 1 x1 0 9 m 3 y-1 Water storage: 1 x1 0 9 m 3 River & groundwater discharge 59 Figure 3-27. Systems diagrams of North Carolina's water budget (a) and water evaluated as emergy (b) (1990). 00 \0

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.(b) Forests, grasslands, wetlands Emergy of North Carolina water Figure 3-27. continued. Water flows: 1x10 20 sej y-1. Water storage: 1 x1 0 20 sej River & groundwater discharge .. 101 \0 o

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.91 Forestry was the largest direct benefactor ofN.C.'s rain, receiving 64 E20 sej/y (5.3 E9 EmS/y; Figure 3-27b). Agriculture used 32 E20 sej/y (2.7 E9 EmS/y) of rain water and supplemented it with 3.6 E20 sej/y (0.3 E9 EmS/y) of irrigation water. Approximately 10 billion m 3 /y of water worth 19 E20 sej/y (1.6 E9 EmS/y) was used as the coolant in thermoelectric power plants in 1990. Water for drinking and washing (potable), lawn irrigation, and industrial and commercial processes required less than 1 % (1.11 billion m3/ y) of the total rainfall. Although this form of water consumption was small relative to forestry, agriculture and power plants, the value of the water (26 E20 sej/y) was comparable once the resources used to extract, and transport were included. North Carolina's abundant rainfall and elevated landscape interacted to provide an average of 47 billion kWh (169 E15 1) of water geopotential energy per year worth 18 E20 sej (1.5 E9 EmS; see Table 3-9). Of this total, 5.4 billion kWh was transformed to hydroelectricity, with an upgraded value of33 E20 sej (2.7 E9 EmS). For comparison, in 1992, electricity produced from nuclear reactors provided 130 E20 sej and total electricity consumption was 548 E20 sej. Natural capital Table 3-10 shows the emergy evaluation of major storages in North Carolina. Population represented the largest amount of stored emergy (673 E22 sej). Economic assets of roads, bridges, buildings and other infrastructure were the next largest (384 E22). The largest stock of natural capital, topsoil, was valued at 255 E22 sej. Wood biomass and groundwater were determined to store 37 E22 sej and 38 E22 sej, respectively. The non-renewable reserve of phosphate rock represented 140 E22 sej.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-10. Emergy evaluation of resource storages of North Carolina, ca. 1992. Trans-Solar EmdoUar Not Item Raw Units formity Emergy Value (sgIunit) (E22 sej) (lE9 EmS, 1992) Storages 1 Phosphate 1.00E+14 g 14.0E+9 140 1167 2 Groundwater 2.52E+18 J 150,000 38 315 3 Wood Biomass 8.92E+18 J 41,000 37 305 4 Topsoil 2.75E+19 J 93,000 255 2128 5 Economic Assets 3.20E+12 $ 1.2E+12 384 3200 6 Population 2. 11E+08 p-y 31.0E+15 673 5606 7 Surface Water 3.70E+16 J 41,000 0.2 Footnotes to Table 3-10 in Appendix A 92

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.93 Summary of North Carolina emergy use Table 3-11 summarizes the emergy flows of North Carolina by aggregating line items of Table 3-9 into categories that were based on the energy source. Figure 3-28 is a system diagram that defines the letters used in Table 3-11. Total emergy use in North Carolina (R+NO+Nl+F+G+P21 in Table 3-11) was 1890 E20 sej/y for the year 1992. Assuming that the total emergy use was necessary to produce a gross state product of S160 billion for 1992, then the emergy-to-dollar ratio was 1.18 E12 sej/S. That is, every dollar of economic product generated in N.C. represented, on average, a flow of 1.18 E 12 sej of exogenous resource. Figure 3-29 shows the power and empower spectra for North Carolina. As with the power and empower spectra developed for Coweeta watershed, WSC watershed, and Macon County, the spectra demonstrated the hierarchical property of energy use. That is, the vast majority of incoming energy was in the form of low transformity sunlight, while the highest quality energy source (human metabolism) contributed nearly the least amount of energy (Figure 3-29a). When energies were instead expressed as empower, the numerical differences between the sources were less, but still ranged well over two orders of magnitude (Figure 3-29b). Interesting to note was how the mid-quality energy sources (1E4 to lE5 sej/J) vacillated in sequence with increasing transformity (Figure 329b). The spectra highlight, visually, the importance of petroleum in the N.C. economy. The graphs were also a means of acknowledging the diversity of energy use. In total, nineteen (19) forms of energy contributed at least 1 E20 sej/y to the system ofN.C (Figure 3-29b).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.94 Table 3-1 1. Summary offlows in North Carolina, ca. 1992. Solar Emergy Dollars Letter Item (E20 sej/y) R Renewable sources 187 (rain-land, rain-shelf. mountain deep heat) N Nonrenewable sources flow within N.C. 556 (NO+NI+N2) NO Dispersed Rural Source 212 (fish. forestry, soil loss, accelerated sediment loss) NI Concentrated Use 2 (phophate rock used within) N2 Exported without Use 341 (phophate rock. granite) F Imported Fuels and Minerals llll (oil prods., coal, nuclear elect., natural gas) G Imported Goods 159 (meat, ago produce., metals, wood) I Dollars Paid for Imports 1.41+10 P2I Emergy Value of Goods & Service Imporu 221 B Exported Goods 217 (tobacco, cotton, livestock, wood prod., furniture) E Dollars Received for Exports 5.54E+1O PIE Emergy value of goods & service export 655 X Gross State Product 1.60E+ll P2 U.S. emergyl$ ratio, used in imports 1.50E+12 PI North Carolina emergy/S ratio 1.18E+12 Z Population, 1992 6,910,000 Letters are given on pathways in Figure 3-25 for reference.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Rural systems 187 FI EMERGY (E20 solar emjouleslyr) / / ,--<. V x $ \ $160 --" $ flows (E9 $/yr) Figure 3-28. Summary diagram of emergy flows of North Carolina in 1992. \0 IJI

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.1.00E+21 tt----------------------, ---'>-. 1.00E+19 1-0 1.00E+ 17 o 1.00E+1S \ \1 1.00E+13 +-------r-----,.------,.--------l lE+O lE+2 IE+4 IE+6 IE+8 Transformity (solar emjoules/Joule) 1-0 '>-. 400 Q) .=0 00 Q..<'O E 0 X 200 ---L o lE+O lE+2 lE+4 lE+6 Transforrnity (solar em joules/Joule) Figure 3-29. Power (a) and empower (b) spectra of the main resource inputs used in North Carolina, ca. 1992 (see Table 3-9 for details). Abbreviations: S-sunlight, V-water vapor deficit, W -kinetic wind, RG-geopotential of rain, T -tide, RC-chemical potential of rain, B-waves, G-geologic uplift, C-coal, F-wood, N-natural gas, D-soil, P-petroleum, HE-hydroelectricity, IE+8 NE-nuclear electricity, A-agricultural crops, L-livestock, PH-phosphate mined & used, H-human migration and tourism. 96

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.97 u.s. Forest Products Industry Emergy evaluation of the forest products industry included evaluations of seven (7) individual sectors: forest growth, logging, pulp mills, paperboard mills, paper mills, saw mills and plywood factories. Emergy evaluations of each sector are shown in Tables 3-12 through 3-18 and summarized in systems diagrams shown in Figure 3-30. Only independent sources of emergy are shown in the systems diagrams. Table 3-12 and Figure 3-3Oa show the emergy evaluation offorest growth in North Carolina. This transformity was used as the transformity of wood biomass in the emergy evaluations of the lumber, plywood and pulpwood. The transformity offorest growth (2.1 E4 sej/J) was a function of transpiration and geologic weathering. The input of emergy from the two sources differed by only 28%. The emergy evaluation of the logging industry is shown in Table 3-13 and Figure 3-30b. After wood, the energy of human service was the most important. Petroleum and electricity provided only 7% of the emergy that services did. The solar transformity of harvested and delivered logs was 2.7 E4 sej/J. Table 3-14 and Figure 3-30c shows the emergy evaluation of the woodpulp industry. The forms of energy used were broadly and equally represented. Services, electricity, petroleum, coal, natural gas, and water ranged narrowly between 4 E20 sej/y to 26 E20 sej/y. The solar transformity of wood pulp was 6.0 E4 sej/J. Paperboard production, shown in Table 3-15 and Figure 3-30d, required 193 E20 sej/y of services, which was more than any other input besides woodpulp (250 E20 sej/y). Recycled paper accounted for 69 E20 sej/y. Electricity (60 E20 sej/y), petroleum (15 E20

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.sej/y), coal (35 E20 sej/y), natural gas (42 E20 sej/y), and water (5 E20 sej/y) were all important inputs. The solar transformity of paperboard was 1.3 E5 sej/J. 98 In Table 3-16 and Figure 3-30e, the human service inputs (443 E20 sej/y) to the paper making industry were shown to be greater than the feedstock of woodpulp and recycled paper (319 E20 sej/y). More emergy was used in the form of electricity (188 E20 sej/y) than any other fuel source, although natural gas (133 E20 sej/y) was nearly as significant. Coal (109 E20 sej/y) was the next greatest source of emergy. Petroleum (47 E20 sej/y) and water {l0 E20 sej/y) were significant. The solar transformity of paper was 2.4 E5 sej/J which was similar to Keller's (1992) estimate of2.3 E5 sej/J calculated for a pulp mill in northern Florida. Table 3-17 and Figure 3-30 shows that logs were the biggest source of emergy to the plywood and veneer industry. Next in importance was services, followed distantly by electricity, natural gas, and petroleum. The solar transformity of plywood was 1.1 E5 sej/J. Emergy requirements of the lumber industry are shown in Table 3-18 and Figure 30g. After logs, services were the largest source of emergy. Electricity was by far the greatest source offueI power. The soIartransformity oflumberwas 7.9 E4 sej/J. Figure 3-31 shows systems diagrams that summarize the emergy, transformity and emergy-to-$ ratios for the U.S. forest products industry (ca. 1990). Figure 3-31a shows that the tree harvest of the United States, the base of the wood products industry, was worth 1300 E20 sej/y (118 billion Em$/y). This amount of natural emergy was matched with purchased inputs to the individual wood sectors totaling 1977 E20 sej/y (I80 billion Em$/y).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-12. Emergy evaluation offorest growth in North Carolina. TransSolar Emdollar Note Item Physical Units formity Emergy Value (sej/unit) (E20 sej) (109 1992 Em$) Forest growth 1 Sunlight 212.0E+18 J 1 2.1 0.2 2 Rain, chemical 317.0E+15 J 1.8E+04 57.7 5.2 3 Geologic input 120.1E+15 J 3.4E+04 41.5 3.8 Sumof2and3 99.2 9.0 4 Forest growth 474.9E+15 J 5 Forest transforrni!r 2.1E+04 Footnotes to Table 3-12 1 SOLAR ENERGY Total Land Area of N.C. = Insolation @ Atmos = Albedo Forested area = Energy(J)= 2 Rain, chemical Total Land Area of N.C. = Rain (land) = 136.4E+9 m"2 (US Statistical Abstract 1995) 6.3E+9 J/m"2Iyr (Barry & Chorley, 1992, p. 23) 0.15 fraction absorbed at surface (Barry & Chorley, 1992) 56% (US Statistical Abstract 1995) (area)*(avg insolation)*(I-albedo) L-m"2)*L-J/m"21y)*(l-aibedo) 212.0E+lS 1.36E+ 11 m/2 (US Statistical Abstract 1995) 1.27 m.Iyr Water Atlas of U.S., 1973. Evapotrans rate= 0.84 mIyr Water Atlas of U.S., 1973. Forested area = 56% Energy on forest land (1) = (area)(transpiration)(Gibbs no.) L-m"2)*L-m)*(lOOO kglm"3)*(4940 JJkg) 3. 17E+l7 3 Geologic input Avg. deep heat generated in NC, J/m"2/y = 1.5SE+06 (avg. from Pollack et al, 1991) Deep heat offorested land, JIy = (lE6 J/m"2/y)x(land area. m"2)x(fraction forested) Deep heat offorested land, JIy = 1.21E+17 4 Forest Growth New Growth = Energy(1) = 4.95E+07 m"3 Avg. 1983-89. Sheffield and Knight, 1986. '--m"3)(IE+06 g1m"3)(O.5 g DW/GW)(19,200 JIg DW) 4.75E+l7 5 Transfonnity of forest growth Transformity forest growth, sej/J = (Rain used + geologic input)/(energy of forest growth) Transformity, sejfl = (57.7 E20 sej + 41.5 E20 se.J)/(475 E15 1) 99

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.100 Table 3-13. evaluation of the logging industry in the United States, 1992. Trans-Solar Emdollar Note Item Raw Units fonnity Ernergy Value (sej/unit) (E20 sej) (lE91990) Logging 1 Services 1.4E+I0 $ I.5E+12 208 13.S 2 Total Wages 1.7E+09 $ 1.5E+I2 25 1.7 3 Non-labor wages 3.9E+OS $ I.5E+12 6 0.4 4 Labor 6.0E+13 I 2.5E+07 15 1.0 5 Capital, @ 20 y life 1.9E+01 $ 1.5E+12 0.3 0.0 6 Biomass 6.2E+18 I 2.IE+04 1298 86.5 7 Electricity 1.6E+I5 J 1.6E+05 2 0.2 8 Petroleum 2.3E+16 J 5.3E+04 12 O.S Sum of 1,6-8 1520 101.3 9 Timber Output 5.6E+lS J 10 Timber Output, transformity(sej/J) 2.7E+04 11 Emergy/$ ratio for logs = 11.0E+ 12 sej/$ Footnotes to Table 3-13 in Appendix

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-14. Emergy evaluation of wood pulp production in the United States, 1990. TransSolar Macroeconomic Note Item Raw Units formity Emergy Value (sej/unit) (E20 sej) (E9 1990 US$) Woodpulp production 1 Services L7E+09 $ I.SE+12 2S.6 L7 2 Total Wages 6.9E+08 $ 1.SE+12 10.3 0.7 3 Non-labor wages L9E+08 $ LSE+12 2.8 0.2 4 Labor 1.1E+13 J 2.5E+07 2.6 0.2 S Capital, @ 20 y life 3.9E+07 $ LSE+12 0.6 0.0 6 Biomass, logs 1.SE+18 J 2.7E+04 412.8 27.5 7 Electricity 9.1E+IS J 1.6E+OS 14.5 1.0 8 Petroleum 3.0E+16 J S.3E+04 16.0 1.1 9 Coal LIE+16 J 4.0E+04 4.2 0.3 10 Natural Gas 3.5E+16 J 4.8E+04 16.9 1.1 II Water 4.IE+16 J 4.9E+04 20.1 L3 Sum of 1,6-11 SlO.1 34.0 12 Woodpulp output 8.SE+17 J 13 Woodpulp output, transfonnity (sej/J) 6.0E+04 Emergy/$ ratio for woodpulp = sum of 1,6-11 divided by $ value of wood pulp Emergyl$ ratio for woodpulp 9 .3E+ 12 sej/$ Footnotes to Table 3-14 are in Appendix 101

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-l5. Emergy evaluation of paperboard production in the United States, -l990. Trans-Solar Macroeconomic Note Item Raw Units fonnity Emergy Value (scti/unit) (E20 seD (E9 1990 US$) Paperboard production 1 Services 1.3E+1O $ 1.5E+12 193.3 12.9 2 Total Wages 2.1E+09 $ l.5E+l2 32.0 2.1 3 Non-labor wages 6.0E+08 $ 1.5E+l2 9.0 0.6 4 Labor 3.4E+13 J 2.5E+01 8.4 0.6 5 Capital, @ 20 y life l.OE+08 $ I.5E+12 1.5 0.1 6 Woodpulp 4.2E+l1 J 6.0E+04 250.3 16.1 7 Recycled paper 1.1E+11 J 6.0E+04 68.8 4.6 8 Electricity 3.7E+16 J 1.6E+05 59.6 4.0 9 Petroleum 2.8E+16 J 5.3E+04 14.9 l.0 lOCoai 8.7E+16 J 4.0E+04 34.7 2.3 11 Natural Gas 8.8E+16 J 4.8E+04 42.2 2.8 12 Water 9.6E+15 J 4.9E+04 4.6 0.3 Sum of 1,6-12 668.4 44.6 13 Paperboard output 5.lE+11 J 14 Paperboard output, transfonnity (sej/J) 1.3E+05 Emergy/$ ratio for paperboard = sum of 1,6-12 divided by $ value of paperboard Emergyl$ ratio for paperbd = 4.1E+12 sej/$ Footnotes to Table 3-15 in Appendir 102

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.103 Table 3-16. Emergy evaluation of paper production in the United States, -1990. TransSolar Macroeconomic Note Item Raw Units formity Emergy Value (sej/unit) (E20 sej) (E9 1990 US$) Paper production 1 Services 3.0E+1O $ LSE+12 443.0 29.5 2 Total Wages S.4E+09 $ I.SE+12 81.3 5.4 3 Non-labor wages L5E+09 $ I.5E+12 22.6 1.5 4 Labor 8.7E+13 J 2.5E+07 21.5 1.4 S Capital, @ 20 y life I.5E+08 $ LSE+I2 2.2 0.1 6 Woodpulp 4.2E+17 J 6.0E+04 250.3 16.7 7 Recycled paper I.IE+17 J 6.0E+04 68.8 4.6 8 Electricity L2E+17 J L6E+OS 187.7 12.5 9 Petroleum 8.9E+16 J 5.3E+04 46.9 3.1 10 Coal 2.7E+17 J 4.0E+04 109.3 7.3 11 Natural Gas 2.8E+17 J 4.8E+04 133.1 8.9 12 Water 2.1E+16 J 4.9E+04 10.0 0.7 Sum of 1,6-12 1249.0 83.3 13 Paper output 5.2E+17 J 14 Paper output, transfonnity (sej/J) 2.4E+05 Emergy/$ ratio for paper = sum of 1,6-12 divided by $ value of paper Emergy/$ ratio for paper = 3.8E+12 sej/$ Footnotes to Table 3-16 in Appendix

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.104 Table 3-17. Emergy evaluation of plywood & veneer production in the U.S., -1990. TransSolar Macroeconomic Note Item Raw Units fomrity Emergy Value (sej/unit) (E20 sej) (E9 1990 US$) Plywood & veneer production 1 Services 6.6E+09 $ 1.5E+12 98.3 6.6 2 Total Wages 1.2E+09 $ 1.5E+12 18.3 1.2 3 Non-labor wages 2.3E+08 $ 1.5E+12 3.5 0.2 4 Labor 3.9E+13 I 2.5E+07 9.6 0.6 5 Capital, @ 20 y life 7.3E+06 $ 1.5E+12 0.1 0.0 6 Logs 4.6E+17 I 2.1E+04 125.3 8.4 7 Electricity 6.IE+IS J 1.6E+05 9.6 0.6 8 Petroleum 2.4E+lS I 5.3E+04 1.3 0.1 9 Coal 2.8E+14 J 4.0E+04 0.1 0.0 10 Natural Gas 4.0E+lS I 4.8E+04 1.9 0.1 Sum of 1,6-10 236.6 15.8 11 Plywood output 2.1E+17 J 12 Plywood output, transfomrity J 1.1E+05 Emergy/$ ratio for plywood = sum of 1,6-10 divided by $ value of plywood Emergy/$ ratio for plywood = 3.1E+12 sej/$ Footnotes to Table 3-17 in Appendix

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 3-18. Emergy evaluation of lumber production in the United States, -1990. TransSolar Macroeconomic Note Item Raw Units formity Emergy Value (sej/unit) (E20 sej) (E9 1990 US$) Lumber production 1 Services 1.5E+1O $ 1.5E+12 231.4 15.4 2 Total Wages 3.0E+09 $ 1.5E+12 45.7 3.0 3 Non-labor wages 6.5E+08 $ 1.5E+12 9.7 0.6 4 Labor 1.0E+14 J 2.5E+07 25.3 1.7 5 Capital, @ 20 y life 2.3E+07 $ 1.5E+12 0.3 0.0 6 Logs 2.3E+18 J 2.7E+04 622.8 41.5 7 Electricity 1.1E+16 J 1.6E+05 26.4 1.8 8 Petroleum 6.6E+15 J 5.3E+04 3.5 0.2 9 Coal 7.5E+14 J 4.0E+04 0.3 0.0 10 Natural Gas 1.1E+16 J 4.8E+04 5.3 0.4 Sum of 1,6-10 889.7 59.3 11 Lumber output 1.IE+18 J 12 Lumber output, transformity 7.9E+04 Emergy/$ ratio for lumber = sum of 1,6-10 divided by $ value of lumber Emergy/$ ratio for lumber = 4.2E+ 12 sej/$ Footnotes to Table 3-18 in Appendix 105

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Wood biomass 1298 Forest of North Carolina (a) Logging Industry, U.S. (b) 99.2 1520 Logs EMERGY Flows: 1x1020 sej y-1 Figure 3-30. Systems diagrams of the emergy inputs to the individual sectors of the forest products industry. The sectors are: forest growth in North Carolina (a) logging (b), pulpwood (c), paperboard (d), paper (e), plywood (t), and lumber (g). 106

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Logs 413 Woodpulp 250 Recycled paper 69 Figure 3-30. continued. Pulpwood Industry, U.S. (c) Paperboard Industry, U.S. (d) \ -8 $-.---510 Pulpwood ---8 668 Paperboard EMERGY Flows: 1x1020 sej y-1 107

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Recycled paper 69 Logs 125 Figure 3-30. continued. Paper Industry, U.S. (e) Plywood & Veneer Industry, u.S. (f) --..... 1249 Paper ____ -_-_oooot-.. E, 237 Plywood & Veneer EMERGY Flows: 1x1020 sej y-1 108

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Logs 623 Figure 3-30. continued. Lumber Industry, U.S. (g) \ -E, $-.----890 Lumber EMERGY Flows: 1x1020 sej y-1 109

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.a) EMERGY Flows: 1x1020 sej y-1 b) TRANSFORMITlES: 1 x1 0 4 solar emjoules/Joule 110 1977 Figure 3-31. Systems diagrams summarizing the emergy flow (a), transformities (b), and emergy-to-dollar ratios (c) for the U.S. forest products industry (ca. 1990).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Lil c) Emergy-to-Dollar ratio: 1 x1 0 12 solar emjoules/$ Figure 3-3 I. continued.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.112 Figure 3-31b shows that the transformities offorest products increased throughout the chain of industrial processes. The transformity of harvested tree biomass was 2.1 E4 sej/J, while at the other end of the industrial chain, paper had a transformity of2.4 E5 sej/J; an increase of 115%. Paper with a transformity of2.4E5 sej/J, represented only 7% of the total timber harvest in terms of biomass, but had an emergy value (1250 E20 sej/y) equivalent to 83% of the timber harvest. Shown in Figure 3-31c is the progressive decrease in the emergy-to-dollar ratio of forest products. The emergy-to-dollar ratio was the total empower in a production sector divided by the total revenue for that sector. Each dollar of revenue in the logging-sector had 11.0 E12 sej associated with it, while the paper-sector had 3.8E12 sej. The average emergy-to-S ratio for the whole U.S. economy in 1993 was 1.5 E12 sej/S. Figure 3-32 shows the emergy-to-dollar ratio as a function of solar transforrnity for wood products. Lower transformity products had higher emergy-to-dollar ratios. International Trade of Forest Products Shown in Figure 3-33 is a systems diagram of the balance of trade in forest products between the U.S., Canada, and Mexico. The diagram compares emdollar flows to the counter-current dollar flow. The U.S. received 3.4 E9 EmS offorest products from Mexico and 87 E9 EmS from Canada, for which the U.S. paid SO.7 E9 and S20 E9, respectively. The U.S. shipped 28 E9 EmS of product and received S6.4 E9. Mexico received 8.5 E9 EmS worth of wood products from the U.S., for which they paid $2.1 E9. Canada paid $4.3 E9 for product valued at 19 E9 EmS. In total, after enactment ofNAFT A (North American Free Trade Agreement), the U.S. had an annual trade surplus in forest products (wood logs, pulpwood, and paper)

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.12 10 -8 r-6 + 4 r-2 ILogs 0 OPulpwood Lumber ---""_ Paperboard o 0." 0 Plywood O "'-Paper 10,000 100,000 1,000,000 Transformity, sej I J Figure 3-32. The emergy-to-dollar ratio (sej/$) for major wood products as a function of solar transformity. The emergy-to-$ ratio is the total emergy flow per a industrial sector divided by the total revenue for that sector. 113

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission./ I / / /' --/ I $2.1 /.i 8.5 Em$ \. \ I 3.4Em$ \ \ \ $20 $4.3\ \19 Em$ \ U.S. Forest Products Industry / .,.,. -$6.4 --. 1x109 US$ of forest products --........ 1 x1 0 9 Em$ of forest products Figure 3-33. Balance of international trade in forest products. Trade in forest products (logs, woopulp, and paper) between the NAFTA (North American Free Trade Agreement) countries (U.S., Canada, and Mexico). Values for the forest products traded are shown in US dollars ($) and emdollars (Em$). (See Appendix F for detail by product). --""

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.115 worth 63 E9 Em$ (950 E20 sej) in 1995. The net surplus was a balance between the net loss to Mexico (5 E9 Em$/y; the difference between 8.5 E9 Em$ shipped to Mexico and 3.4 E9 Em$ received from Mexico) and the net gain from Canada of(68 billion Em$/y). Trade between Canada and Mexico was not evaluated. Since the emergy per dollar was higher for wood products (7.6 E12 to 3.6 E12 sej/$) than the emergy to dollar ratio of the U.S. economy as a whole (1.5 E12 sej/$), emdollar flows were always greater than the associated dollar flows (Figure 3-33). What looked to be a total trade deficit of$14.3 billion (US$) for the United States in dollar terms-a deficit of$15.7 billion with Canada and a surplus of$L4 billion with Mexico (Lyke 1998)-was actually a trade surplus of63 E9 Em$. The U.S. received more emergy from Canada and Mexico in the form of wood products than it gave up using its currency. Figure 3-34 shows exchange matrices (Le., from:to) by type offorest product traded. Pulp was the most widely traded forest product in terms of emdoIIars. The U.S. received 1.9 E9 Em$ (29 E20 sej) from Mexico and 43 E9 Em$ (650 E20 sej) from Canada, but shipped 6.1 E9 Em$ (92 E20 sej) to Mexico and 11.7 E9 Em$ (176 E20 sej) to Canada (Figure 3-34b). The net advantage to the U.S. was 27.6 billion Em$/y (415 E20 sej/y) for pulp, 30 billion Em$/y (450 E20 sej/y) for wood logs, and 5 billion Em$/y (75 E20 sej/y) for paper (Figure 3-34b). Global Forest Stocks and Consumption The graph of empower of global tree harvest in Figure 3-35 was constructed using the average solar transformity for wood from the North Carolina analysis (2.1 E4 sej/J). The empower of world tree harvest doubled over the last half of the 20th Century, but has

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Value of trade in US$ (1 x 109 ) (from Lyke 1998) a) Wood logs b) Pulp c) Paper d) All Wood Products To U M C U M C U M C U -'M C total total total total From U XX 0.3 7.0 7.3 U XX 0.4 9.3 9.7 U XX 0.0 3.3 3.3 U XX 0.7 19.6 20.3 M 0.2 XX XX M 1.3 XX XX M 0.6 XX XX M 2.1 XX XX C 1.2 XX XX C 2.5 XX XX C 0.6 XX XX C 4.3 XX XX tot 1.4 tot 3.8 tot 1.2 tot 6.4 Value of trade in Em$ (1 x 109 ) e) Wood logs f) Pulp g) Paper h) All Wood Products To U M C total U M C total U M C total U M C total U XX 1.0 6.1 7.1 U XX 6.1 11.7 ### U XX 1.4 1.4 2.9 U XX B.S 19.2 27.7 From M 1.5 XX XX M 1.9 XX XX M 0.0 XX XX M 3.4 XX XX C 35.5 XX XX C 43.4 XX XX C 7.9 XX XX C 86.8 XX XX tot I 37.0 tot 45.3 tot 7.9 tot 90.2 sej/$ 7.6 sej/$ 7.0 sej/$ 3.6 Figure 3-34. International trade in forest products between the NAFTA countries (1990). From/to matrices of money excbange for (a) wood logs, (b) pulp, (c) paper, and (d) all wood products; and from/to matrices of em dollar exchange for (e) wood logs, (f) pulp, (g) paper, (h) all wood products. U-United States, M-Mexico, C-Canada, XX not evaluated. Emdollar value of wood product, Em$ = US$ x emergy-to-dollar ratio per wood product type. .... .... 0\

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. I j SE+23 i 4E+23 1 o E w 2E+ 231 o r 1950 .. I I I .. I 1960 1970 1980 1990 2000 Year Figure 3-35. Empower of the global forest 1950-97. The transfonnity of wood was assumed constant and equal to the transfonnity of wood growth in North Carolina in the early 1990's (2.1 E4 sej/J). 117

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.118 leveled off at a rate of 6.8 E23 sej/y since 1987. In 1997, 3416 E6 m3 of wood biomass, valued at 6.9 E23 sej (-345 E9 Em$), was being harvested. In terms of biomass, this was less than 1% of the 400 E9 m3 of timber stock (Mather 1990). Emergy Indices for Overview of Forested Systems Indices that related the empower use of environmental and economic energies to each other and the human population were developed for the forested systems of Wine Spring Creek watershed (Table 3-19), Macon County (Table 3-20), and North Carolina (Table 3-21). The indices provide perspective on how the relationship between economy and environment changes with the forested system. Figure 3-36 displays a map of the emergy investment ratio (purchased to renewable) by county for North Carolina. The index ranged from near zero (0.3) for the coastal county of Hyde to 125 for Mecklenburg County. Much of the emergy investment was in the Piedmont region, centered about Interstate 85 from Charlotte through Greensboro to Raleigh. Figure 3-37 shows the rank order distributions of North Carolina counties by emergy investment ratio (EIR; purchased to renewable) and by total empower density. The graphs demonstrated the hierarchical organization of the state since well over half of the counties had an emergy investment index and total empower density that was less than the state average. In totaL sixty (60) counties had an emergy investment index below 9.1, and sixty-seven (67) had a total empower density less than 14,000 E12 sej/ha/y. There were definite categories of counties evident from the graphs. For example, Mecklenburg County, home to Charlotte, clearly stands above all others according to its

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.119 Table 3-19. Indices using emergy for overview ofWSC (1128 ha) Item Name of Index Value 1 Renewable emergy flow R LIE+18 2 Flow from indigenous nonrenewable reserves N L4E+17 3 Flow of imported emergy F+G+P21 3.0E+lS 4 Total emergy inflows R+N+F+G+P2I 4.2E+1S 5 Total emergy U NO+Nl+R+F+G+P21 4.1E+lS 6 Total exported emergy B 4.3E+18 7 Fraction emergy use derived from home sources (NO+NI +R)/u 0.27 8 Imports minus exports (F+G+P2I)-(N2+B+P IE) -L5E+lS 9 Export to Imports (N2+B)/(F+G+P2I) L49 10 Fraction locally renewable RIU 0.27 11 Fraction ofuse purchased (F+G+P2I)1U 0.73 12 Fraction imported service P2IIU 0.05 13 Fraction of use that is free (R+NO)/u 0.27 14 Ratio of concentrated to rural (F+G+P2I+Nl )/(R+NO) 2.7E+OO 15 Useperml\2 U/(area) 3.6E+ll 16 Use per tourist-year Ultourist-year L6E+17 17 Use per visitor U/# of visitors 3.4E+14 IS Carrying capacity: Number of tourists if only used renewable (RIU) (# visitors) 3.3E+03 19 Standard of living if current population supported with only renewables R/(tourist-yr) 4.3E+16 20 Ratio of use to GNP. emergy/dollar ratio PI=U/GNP 3.3E+13 21 Environmental Loading Ratio (ELR) (NO+Nl+F+G+P2I)1R 2.6S 22 Use to Import Ratio (VIR) U/(F+G+P2I) 1.37 23 Emergy Sustainability Index (ESI) (UlRlELR) 0.51 25 Purchased to indigenous renewable (F+G+P2I)1R 2.68 26 Fraction of Use from Tnnber (forest extractionlU) O.OS 27 Fraction ofR captured Forest (forest growthlR) LOO Letters are given on pathways in Figure 3-20 for reference.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.120 Table 3-20. Indices emergy for overview of Macon county, N.C. circa 1992 Item Index Expression Value 1 Renewable emergy flow R 1.1E+20 2 Flow from indigenous nonrenewable reserves N 2.1E+20 3 Flow of imported emergy F+G+P21 2.1E+20 4 Total emergy inflows R+N+F+G+P2I 6.5E+20 5 Total emergy used, U NO+Nl +R+F+G+P2I 5.1E+20 6 Total exported emergy PIE 1. 1 E+20 7 Fraction emergy use derived from home sources (NO+NI+R)IU 0.46 8 Imports minus exports (F+G+P21)-(N2+B+P IE) 1.3E+20 9 Export to Imports (N2+PIE)/(F+G+P21) 0.54 10 Fraction used, locally renewable RIU 0.22 11 Fraction of use purchased (F+G+P2I)IU 0.54 12 Fraction imported service P2IIU 0.08 13 Fraction of use that is free (R+NO)/U 0.39 14 Ratio of concentrated to rural (F+G+P2I+Nl)/(R+NO) 1.57 15 Use perm"2 U/(area) 3.8E+ll 16 Use per person U/population 2.2E+16 17 Carrying capacity: Use renewabIes only to remain at present living standard (RIU) (population) 5106 18 Standard of living if current population supported with only renewables R/popuIation 4.1E+15 19 Ratio of use to county personal income, emergy/doilar ratio Pl=U/GNP 2.0E+12 20 Ratio of electricity to total use (el)/U 0.44 21 Fuel use per person fueVpopulation 1.5E+16 22 Enviromnental Loading Ratio (ELR) (NO+NI +F+G+P2I)IR 3.60 23 Use to import ratio (UIR) U/(F+G+P21) 1.87 24 Emergy Sustainability Index (ESI) (UlRJELR) 0.52 25 Purchased to indigenous renewable (F+G+P2I)1R 2.46 26 Fraction of Use from Forest (forest extractionfU) 0.14 27 Fraction of R captured bl: Forest (forest growth/R) 0.81 Letters are given on pathways in Figure 3-20 for reference.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.121 Table 3-21. Indices using emergy for overview of North Carolina, ca. 1992. Item Index Value 1 Renewable emergy flow R 1.9E+22 2 Flow from indigenous nonrenewable reserves N 5.6E+22 3 Flow of imported emergy F+G+P21 L5E+23 4 Total emergy inflows R+N+F+G+P21 2.2E+23 5 Total emergy used, U NO+Nl+R+F+G+P21 L9E+23 6 Total exported emergy PIE 6.6E+22 7 Fraction emergy use derived from home sources (NO+Nl+R)1U 0.21 8 Imports minus exports (F+G+P2I)-(N2+B+P IE) 4.9E+22 9 Export to Imports (N2+P lE)/(F+G+P2I) 0.67 10 Fraction used, locally renewable RIU 0.10 11 Fraction of use purchased (F+G+P2I)IU 0.79 12 Fraction imported service P2IIU 0.12 13 Fraction of use that is free (R+NO)/u 0.21 14 Ratio of concentrated to rural (F+G+P2I+NI)/(R+NO) 3.74 15 Use perml\2 U/(area) 1.39E+12 16 Use per person (6.9 e6 people) U/population 2.7E+16 17 Carrying capacity: Use renewables only to remain at present living standard (RIU) (population) 6.8E+05 18 Standard of living if current population supported with only renewables R/population 2.7E+15 19 Ratio of use to Gross State Product empower per dollar flow PI=U/GNP L2E+12 20 Ratio of electricity to use (el)IU 0.29 21 Fuel use per person fueVpopuIation L6E+16 22 Environmental Loading Ratio (ELR) 9.14 23 Use to Import Ratio (UIR) U/(F+G+P2I) 1.27 24 Emergy Sustainability Index (ESI) (UIRlELR) 0.14 25 Purchased to indigenous renewable 8.00 26 Fraction of Use from Forest (forest extractionlU) 0.09 27 Fraction of R captured by Forest (forest growtbIR) 0.53 Letters are given on pathways in Figure 3-25 for lefeIence.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Emergy Investment Ratio-Purchased to Renewable 0-10 10 -30 30 -100 100+ 50 o 50 100 Kilometers E ii2 N + Figure 3-36. Spatial distribution of the emergy investment ratio (purchased to renewable) for North Carolina (ca. 1992). s

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.100 80 Q) 60 u 0 c 40 as a:: 20 0 100 80 Q) 60 "E o c as 40 a::: 20 0 North Carolina's average emergy investment ratioa = 9.1 .. .. 50 100 Emergy Investment Ratio (Purchased to Renewable) North Carolina average = 14.000 E 12 sej/haly 150 o __ __ __ o 50000 100000 150000 Total empower density. 1 E12 sej/haly Figure 3-37. Rank order distributions of North Carolina counties by (a) emergy investment ratio (purchased to renewable) and (b) total empower density for the year 1992. 123

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.124 ErR. and total empower density. It has international recognition as a banking center and is home to two professional sports teams. Next, there was a group of regional centers (Forsyth-Winston-Salem. Durham. Wake-Raleigh, and Guilford-Greensboro) with EIR's ranging from 60 to 80 (Figure 3-37a). There was one county, Gaston, with an ErR. of 46 that was set apart from the other counties because it occupied a lone spot on both the EIR graph (Figure 3-37a) and total empower density (Figure 3-37b). It bordered Charlotte and was therefore influenced by that metropolitan center. There were distinct breaks in both rank: order distnlmtions where 80 counties were below and 20 counties above. In Figure 3-37a, an EIR of 15 was the breaking point and in Figure 3-37b, a total empower density of -20,000 divided the counties into two groupings. Sensitivity ofEmergy Simulation Models Sensitivity ofEmergy and Transformity to Depreciation and Export Emergy accumulation and transformity were sensitive to rates of storage depreciation and export in the model EMERGYDYN. Coefficients for export and depreciation were changed in EMERGYDYN to determine the sensitivity of the transformity of total organic matter (TOM). In EMERGYDYN, stored total organic matter (TOM) was lost via two pathways, depreciation and export (see Figure 3-8). Depreciation was assumed to be a process necessary for maintaining the storage, and therefore did not subtract emergy from the storage. On the other hand, material lost as export was a loss of emergy. Material exported had the same transformity as the stored organic material.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.125 In Figure 3-38, the total loss (export + depreciation) was held constant at 3%, but the proportion between the export and depreciation was varied. Figure 3-38a shows that the transformity of the stored organic matter increased logistically over time, and that the smaller the percentage export was of total loss, the higher the growth rate of the transformity. Figure 3-38b plots transformity of storage as a function of percent export, showing that the smaller transformities result from higher export rates. As export approached 1000/0 of total storage loss (i.e., depreciation approached zero), the transformity of the storage approached the transformity of the incoming material. At an export rate of 1000/0 there was no increase in transformity of the organic matter because there was no time for the organic matter to depreciation and increase its transformity. Holding depreciation constant at 2.3% of storage, but varying export from 0.1 % to 9% of storage resulted in the transformity of the storage decreasing as export increased (Figure 3-38c). Small increases in the export fraction caused large drops in the transformity of the organic matter, especially for increases occurring between 00/0 and 2%. Sensitivity of Species Simulation Model EMSPECIES EMSPECIES was used to simulate the dynamics of tree species abundance for the \VSC watershed, and to calculate the emergy stored as tree species. The ability of the model to duplicate species area curves for other forested systems was explored. Notoriously diverse ecosystems, rainforests, were compared. Tree species-area curves observed for rainforests ofMalesia were much steeper than the observed curves for the WSC watershed (Figure 3-39). For EMSPECIES to duplicate the steeper curves, the seed source was increased by a factor of 10 for the curve

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.>. E:;::" L.. Q) o f/) cw m L.. f-100 80 j 5% :] 20 0 20% 0 0 SOO 1000 1500 2000 2500 years a) time series for levels of export 100000 J 0 0 i 1:: +f ----'--'---'-' ..L..J' '-L-' '-'-t' I 1% 10% 100% b) export as percent of total loss from storage [steady-state values from (a)] 30000 -y--------------, 25000 20000 f/) 10000 0 15000 Transformity of productZO j j .= 0% 5% 10% 15% 20% c) percentage of storage exported Figure 3-38. Transformity of total organic matter (TOM) simulated with EMERGYDYN for the Coweeta watershed. a) time series when total loss (export + depreciation) was held to a constant fraction of 0.03 of storage and the partitioning between export and depreciation was varied. percentages refer to exportltotalloss; b) steady-state values from (a); c) depreciation was held to a constant fraction of 0.023 of storage while export was varied from 0.006 to 0.094 of storage. 126

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.300 .-----------------, en ui 250 CD 200 en CD 150 -'0 bserved mulated [] o c [] L... 100 CD .0 E z c [] i [] lIP ,""::111.11 :A .. I I OI.I I. 1ia0'4' o I o 10000 20000 30000 Area, ml\2 40000 Seeds (C) = 1000 xC in Seeds (C) = 10xC WSC (C=1 Figure 3-39. Simulation of species area curves for Wme Spring Creek (WSC) and two tropical rainforests. Seed availability was increased by factors of 10 and 1000 times seed availability in WSC (see Figure 3-13a) to duplicate relationships for tropical forests. 127

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.appearing in the middle of the graph and by a factor of 1000 for the top curve. For an area of3.5 ha (35,000 m2), the number of tree species present in the different forested ecosystems ranged over lO-fold from 30 to 320. Thus, according to the EMSPECIES tree species abundance measured at one locale, was dependent upon the tree species abundance in the surrounding landscape. 128 The sensitivity of tree species abundance in EMSPECIES to external seeding indicated that the high elevation (l200m) forest ofWSC watershed was limited by the availability of tree species from the surrounding landscape. Malesian rainforests, on the other hand, must have had a much greater supply of tree species from which to recruit, since they had a higher abundance of tree species. Comparing Curves of Empower-species and Species-area Using data from the WSC forest, the University of Florida's Arboretum, and the tropical rainforest at East Kalimantan (Malesia), species-area curves were contrasted with empower-species curves. First, the species-area curves for each forested system were different (Figure 3-40a). The tropical rainforest at East Kalimantan had a much greater number of tree species for the same area. Likewise, the UF Arboretum had a steeper slope than the WSC forest. The UF Arboretum was heavily subsidized with purchased services and resources including weeding, mowing, pruning, fertilizer, irrigation, herbicides and pesticides (see Appendix G for the emergy evaluation of the UF Arboretum). Although the UF Arboretum had more tree species per unit of area than the WSC forest, on an emergy basis the WSC forest had more tree species for the same empower input (Figure 340b). The WSC forest maintained 30 tree species with about 1000 E12

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.250 :_ 200 1 A 150 f m i 100 i 6 A East Kalimantan A 50 A University of Florida Z 0 D wsc o 5000 250 B 200 CfJ CD '0 150 0 en CD 100 r-0 -Wine 0 :u: 0 Spring 50 Crpek [J 10000 Area, m2 a o a a I 15000 East Kalimantan o [J [J [J University of I ., I i 20000 0 [J Florida Arboretum 0 1000 2000 3000 4000 5000 Annual Empower, 1012 sej y"1 Figure 3-40. Species-area curve (a) and empower-species curve (b) for the forest ofWme Spring Creek (>1200m). the Arboretum at the University of Florida, Gainesville (see Appendix G for emergy evaluation). and the tropical rainforest at East Kalimantan, Borneo (Kartiwinata 1984). 129

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.130 sej/y, while the UF Arboretum required 2000 E 12 sej/y for the same number of tree species. Thus, the WSC forest was more efficient with its empower at maintaining tree species. The tropical rainforest was even more efficient with its empower, having about 120 tree species for an empower of 1000 E12 sej/y (Figure 3-40b). Simulating Management Alternatives of Forest Ecosystems Logging Rotation Schedules and Forest Empower A ubiquitous question in forest management is how often should the forest be cut. Setting the forest rotation cycle to maximize total empower could be a driving principle. A log harvesting function was added on to the model EMERGYDYN (see Figure 3-7) so that the effects that rotation length had on total forest empower could be investigated. The empower associated with the harvesting effort was based on the emergy analysis of the U.S. forest products industry (see previous section). The same empower per logging cycle (37 E15 sej/ha/cycle) was used for all logging cycles. It was figured by multiplying the emergy investment ratio of logging (EIR = 0.27) by the emergy yield of a 100-yr cutting cycle (1.38 E17 sej/ha/cycle). Harvest magnitude was set at 15% of wood biomass stored. Figure 3-41 shows the systems diagram, model equations, and time series charts for simulating the wood biomass and emergy properties in EMERGYDYN under rotation cycles of 100-years and 300-years. For a 100-year rotation cycle--a typical management scheme of forest stands in the southern Appalachians-wood biomass reached a value of 269 MT/ha, 91% of its climax value (Figure 3-41b). Its stored emergy at harvest (82 E15 sej/ha) was only 47% of the climax value of 175 E15 sej/ha (152,000 EmS/ha, compare Figure 3-41b with Figure 3-8). Conversely, logging forest stands when the stored emergy

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Energy Rr = R I (1 + k 1 (0) P=k2RrOG W=kSQH D=k3Q dO =P-W-D R,G. Hare oonstants Errerav Mp = T R(k1 RrQG) + TG(ksRrQG) MO=O Mw=TQW My=Mvv+MH IfdQ>O dMQ=Mp-M./v IfdQ. :0 e> "0 Q) 100 o E w o 250 500 750 b) Time, yr Figure 3-41. The temporal dynamics of the quantity, emergy, and transformity of wood biomass simulated in EMERGYDYN (a) for a IOO-year rotation (b) and 300-year rotation (c) schedule. (see Figure 3-7 for calibration values). 131

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.co 400 I Wood(Q) W 300 -en enID en_ 200 o >. :0 e> "0 CD 100 o E o a 250 500 750 c) Time, yr Figure 3-41. continued. 35 30 ..., -'ar U) 25 )0 20 15 10 5 132

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.133 reached 91% of climax (139 E15 sej/ha) resulted in a rotation cycle of300 years (Figure 3-4lc). Next, Figure 3-42 shows the effects of varying harvest frequency from 10 to 300 years on wood yield, total empower, emergy yield ratio, environmental loading ratio, emergy sustainability index, and the transformity of yield and forest. According to the simulations, wood yield was maximum for a 25-year cutting cycle, but the value of the harvested wood before adding empower from harvesting, was maximum for a 100-year cycle time (Figure 3-42b). Figure 3-42c shows that total empower (rain + geologic uplift + harvest) was maximum for a rotation cycle of about 40-years. The total renewable empower input (rain + geologic uplift) increased asymptotically with longer cutting intervals, whereas the empower of harvesting peaked between a cycle times of20 and 50 years (Figure 3-42c). The emergy yield ratio increased linearly with cycle time, varying from 1.2 at the 10 y cycle time to 3.9 at 300 y. The environmental loading ratio decreased asymptotically to zero as cycle time increased (Figure 3-42d). The ratio of these two indices, the emergy sustainability index (ESI), increased exponentially with increased cycle time (Figure 3-42e). An index comparable to the ESL the fraction of yield which was renewable emergy, had an opposing relationship; it increased asymptotically toward 80% as cutting frequency decreased (Figure 3-42e). The average transformity of the forest and the mean transformity of the yield increased with longer cycle time (Figure 3-42t). Of course, the transformity of the yield

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.(a) Energy Ernergy R r = R I (1 + k 1 00) Mp = T R(k1 RrQG) + Transforrrity Tp=MpIP P =k2RrOG W=k6QH D =k3Q dQ=P-W-O TG(k5RrQG) MO=O TQ=MQ/Q Tw=MWIW R, G, H are constants Myv=TQW IfdQ>O LO w >--CDL:. 3::::::" o CD a.UJ E w dMa=Mp-Mw IfdQ
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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 5 1: -r (c) :':::::.. I .6 .. I ( -& --& 2.51 : -.. -. -i (renewable) a., -----(harvest) E 0 W o 100 Figure 3-42. continued 200 Cycle time, y 300 400 135

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.30000 --.---------------(f)---, -m->; 20000 --E 10000 c: _---_--;a To 4----s---_-IiI---1iI.1iI-----t-o o 100 Figure 3-42_ continued_ 200 Cycle time, y 300 400 136

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.was always the greater of the two because it was wood taken from the forest near the peak of its transformity. A Model for Simulating the Empower of Multiple Forest Benefits 137 Forestry management can no longer afford to be solely concerned with maximizing timber yield. The importance of the ecological and recreational services, and other benefits must be recognized. Therefore, a crucial question to address is what combination of forest services (e.g., timber, recreation, ecological) maximizes the total empower on a sustainable basis. By placing all benefits in terms of emergy, all the benefits can be compared quantitatively. Here, the model MUL TIBEN was developed (Figure 3-43a) to compare the multiple forest benefits given varying levels ofinvestment in each activity. Figure 3-43a shows the systems diagram of the MULTIBEN model with the energy and emergy equations. In this simplified forest production was a function of the environmental inputs of rain and geologic uplift, and there were only three forest products exported. Two exports (recreation and timber) required an economic investment and one (ecological services) was provided free without any investment. The forest's reserve of organic matter and structure were diminished to supply each forest benefit to society In Figures 3-43b and 3-43c the empower of each forest benefit as well as the total was plotted as a function of the energy invested in recreation. In this case, the level of investment in timber harvesting was held constant at its present-day value while the recreation intensity factor was varied from 0.5 to 10 in Figure 3-43b and 0.5 to 500 in Figure 3-43c.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.(a) ....... FOREST Energy & material equations: Rr = R / (1 + k 1 QG) dQ/dt = k2RrQG -k3Q --ksQFt -kt5QFc 1= kSQ W=kgQFw C = klOQFc Recreation C kl0 Timber W k9 SOCIETY & ECONOMY Total Emergy Yield My=Mc+Mw+Mi Emergy equations: Mp=TMkl Rr GQ)+Tg(k7Rr GQ) Mc=TtFc + Tq(ktiQFd Mw=TrFw + Tq{kSQFt ) Mi=Tq(k4 Q ) My=Mc+Mw+Mi If dQ/dt > 0 138 P = k2RrQG ksQFw+ke>QFd If dQ/dt < 0 dMq/dt=Tq*(dQ/dt) Tq=Mq/Q Figure 3-43. MUL TIBEN, a model for simulating the empower of multiple forest benefits given different management scenarios. Abbreviations: R, rainfall; G, geologic uplift; Q, total organic matter including wood; P, production of organic matter; Fw,Fc, feedbacks from the economy used to capture Q for timber and recreation, respectively; Tr, T g, T q, Tf are transformities of respective energy sources; C, recreated people; W, timber; L ecological services; Mc, emergy of recreated people; Mw, emergy of harvested timber, Mi, emergy of ecological services; My, total emergy yield. a) systems diagram with energy and emergy equations, b) model output-empower of recreation, timber, ecological services, and total as function of investment in recreation (Fc), c) same graph as in (b) except the x-axis was extended to Fc = 500 so that the maximum total empower could be seen, d) environmental loading ratio and emergy yield ratio as functions of recreation investment.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.139 14000 12000 10000 ;>. 8000 Q,).,c o Q,) 0..(1) SC"I 6000 J .... 4000 ....--Me-recreation 2000 Mw-timber 0 0 2 4 6 8 10 Fw (harvest effort) =1 (b) Fe (recreation investment) = x 14000 My-total yield Me-recreation 12000 10000 8000 ::: -e. o Q,) Q.,(I) SC"I 6000 -4000 Mi-ecological 2000 Mw-timber 0 0 100 200 300 400 500 Fw (harvest effort) = 1 (e) Fe (recreation investment) = x Figure 3-43. continued.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.(d) 12 I 10 >c 8 "0 c: -6 8 UJ 4 I -.,,----I Environmental Loading Ratio (Mf/Mp) ----------------------------Emergy Yield Ratio (MylMf) 2 ( .. o o 100 200 300 400 500 Fw (harvest effort) =1 Fc (investment in recreation) = x Figure 3-43. continued. 140

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.141 The graph in Figure 3-43b shows that the emergy yield of recreation and total benefits increased at a decelerating rate, while the timber and ecological services decreased to near zero by the time recreation intensity was 10 times present levels. Thus, there was a trade-otfbetween each benefit since some of the forest resources were required to provide each export. Figure 3-43c plots the same graph as in Figure 3-43b except that the x-axis is extended to reveal the negative marginal rate of retmn of investing in recreation. The total empower was maximum at 1200 E 12 sej/ha/y when the investment in recreation was 100 (100 times its present level). However, at this level of investment, the ecological amenities and timber products were not provided. Figure 3-43d shows the environmental loading ratio and emergy yield ratio as a function of the investment in recreation. The environmental loading ratio increased asymptotically to five (5) as recreation intensity was heightened. The emergy yield ratio behaved exactly opposite; it decreased rapidly and asymptotically to one (1). MUL TIBEN is shown in Figure 3-44a with the sustainability sub-module and equations. The sustainability product, S, is a function of recreation, timber, and ecological services. The rationale for the sustainability product is that all three individual forest exports are required for a properly functioning society and economy. A deficiency in any single export may limit the sustainability product while an excess of one may go unused, or it is simply a luxury that is not used in a productive process. In other words, there is an optimum mix of the forest exports that is sustainable. Emergy is associated with S, the sustainability product, in proportion to the amount each forest product is used to make S.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.142 F,Tfr---------..... ---.-,..---...:....j Cr=klOQF c/ (1 +k13 I r W d Ir=ksQ/( 1 +k11 CrWr ) S=k17CrWrIr MS=Ti*(k11 C r W rId + (a) Tw*(k12CrW rid + Tc*(k13C r W rid SOCIE'I Y 85 ECONOMY TimberW Indirect I r--.---.. -----------, lSOCIETY 85 ECONOMYl : : ; Recreation C,TCl C' i Timber W,Tw' Indirect I Ti I Figure 3-44. Model MULTIBEN with sub-module added for simulating the sustainability of providing mulitiple benefits. Abbreviations (see Figure 3-44 for others): S, sustainable product yield to the regional economy based on the availability ofCr,Wr, & Ir, CU,Wu, & Ill, the used fractions ofC,W, & I; Cr,Wr,&Ir, the remaining (unused) fractions ofC,W,&I; Ms, the emergy yield in proportion to S. (a) Systems diagram with supplemental equations for calculating S (see Figure 3-44 for more on equations); (b) S as a function of investment in recreation and timber harvesting; (c) SIF, effective emergy yield ratio as a function of investment in recreation and Y/S, index of imbalance.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.3000 I :g Q} .>' Logging Effort 513 ;:.f000 ... -= (Fw) = 15 Q} .5' Q} en :eN = --1000 =' rn rJf .. Fw=1 0 0 5 10 15 20 (b) Fe (investment in recreation) o I 40 "'OeQ}-0. 751 SIF--Effective ./ L 30 emergy yield ratio / / .>' / ;>. / Y/S-index of / .... 0.5 / S Q} Q} > E 0.25 imbalance I 20 10 o o 20 (c) Figure 3-44. continued. 40 60 Fw (harvest) =15 Fe (recreation) = x 80 100 I 4-25 Q} (.) -= .c .5 c... o "'0 C -143

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.144 In Figure 3-44b, the empower of the sustainability product (Ms) is plotted as a function of the investment in recreation for various levels of timber harvesting. For each level of timber harvesting, there existed a maximum value for Ms. For example, at a timbering rate of 15 (i.e., IS times the present day rate), the maximum empower of S (Ms) was 2500 E12 sej/ha/y at an investment in recreation of three (3) times the presentday rate. For lower levels ofinvestment in timber harvesting, the empower of the sustainability product (Ms) had a lower maximum at lower levels of investment in recreation. Figure 3-44c shows the sustainable emergy yield ratio (SIF), as a function of investment in recreation. SIF had a maximum of 0.75 when the investment in recreation was three (3) times the present-day rate and the investment in timber harvesting was fifteen (15) times current levels. Figure 3-44c also shows the index of imbalance (Y/S) which is the ratio of the actual yield from the forest to the sustainable yield. A value of one (1) indicates that the yield is in balance with what is sustainable. A value greater than one (1) measures how much greater the actual yield is than the sustainable level. A high index of imbalance indicates that there is luxury uptake of one of the forest products and that the matching of outputs is poor. For example, if recreation were produced in excess in the Wine Spring Creek watershed, then timber and ecological services were likely produced in deficient quantities. To make up for the deficiency, timber and ecological services need to be produced elsewhere, or the recreation needs to be decreased at the Wine Spring Creek watershed.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.CHAPTER 4 DISCUSSION Summary The Significance of Environmental Driving Energies to the Southern Appalachians The forested watersheds of the Southern Appalachian Mountains are driven by a spectrum of environmental and economic energies. In this dissertation, it was found that the rates of emergy contribution by the environmental energies of wind kinetics, water vapor saturation deficit, rainfall, and geologic uplift were similar to each other (see Figure 3-3). Direct solar radiation on the other hand. provided emergy at one-tenth the rate of the other driving energies. Rates of emergy contribution to the Wine Spring Creek (WSC) watershed, from fuels, logging activities, tourists, U.S. Forest Service management. and other economic inputs were similar to the rates of environmental empower. Values of Forests in the Southern Appalachian Mountains Benefits provided by the forested watersheds of the Southern Appalachian Mountains were determined based on the rate of use of emergy from environmental and economic sources. The Wine Spring Creek watershed contributed wealth to the economy at an annual rate of 4300 EmS per hectare of watershed (see Figure 4-1). In terms of emergy, the four most significant exports were stream water discharge, research information, recreated people, and timber (see Figure 4-1). The balanced values of the 145

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.e a saturation vapor pressure Z7 1600 425 '.t.-..I384 ...-....... 146 Wine Spring Creek watershed (1992, Values are Em$/ha/y Research 3450 .......... information Stream ........ .. discharge ........ Recreated people 2060 1880 t--..... Timber 260 Totru of Independent 4300 Sources Figure 4-1. Summary diagram of the emdollar value of the forcing factors and products of the of Wine Spring Creek watershed.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.147 exports indicated that the multiple-use management strategy maximized total empower in the watershed. The development and maintenance of biogeochemical cycles is an important service provided by ecosystems. As an indication of this free service, the emergy required to maintain the calcium cycle of the Coweeta watershed was determined. It was found that 27 E9 sej/y were needed to cycle each gram of calcium annually within the watershed, which translated to 25 EmS/kg-Ca based on a driving empower of2240 EmS/ha/y (see Figure 3-5c). Emergy values calculated for the main stores of material, energy, and information (see Table 3-4) showed that tree species represented the largest accumulation of emergy. Saprolite (regolith) was the second largest storage of emergy and an order of magnitude less than tree species. Emergy stored as total organic matter (live & dead) was next, followed by calcium, wood, and soil moisture. The Importance of Forested Systems and Other Ecosystems to Economic Production As the scale of analysis shifted from the Southern Appalachian Mountain watersheds to the economies of Macon County and North Carolina, the contribution of emergy from environmental sources decreased relative to that derived from economic sources, but remained important to each system. Based on emergy indices, the three forested systems of Wine Spring Creek, Macon County, and North Carolina were not self-sustaining. They each depended upon outside resources, especially fossil fuels, for significant amounts of their emergy. North Carolina derived only 21% of its emergy from within its own boundaries (Table 3-21). Macon County, which produced 46% of its

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.148 own emergy (Table 3-20), was more self-reliant than the Wine Spring Creek watershed with indigenous resources providing 27% (Table 3-19). Forestry and forested systems played significant roles in each ecological economic system. Timber extraction provided 3% of the world's emergy use, 90/0 of North Carolina's (Table 3-21), 14% of Macon County's (Table 3-20), and 8% of Wine Spring Creek's (Tables 3-19). Forests were responsible for capturing the majority of the renewable, environmental empower in North Carolina, Macon County, and the Wine Spring Creek watershed because they covered the majority of the land area. In North Carolina forests were responsible for capturing 53% of the renewable, environmental emergy input; in Macon County forests captured 81 %; and in the Wine Spring Creek watershed forests captured 100%. Globally, forests were estimated to capture between 10 and 15% of the renewable empower. Incoz:porating the Temporal and Spatial Dynamics ofEmergy and Transfonnity into Emergy Evaluations The transformity and emergy of forest storages were calculated with temporally dynamic computer simulation models (Figures 3-7, 3-9, 3-11). The transformity and accumulated emergy of a storage lagged the energy and material of the forest reserves in the models, requiring more time to reach a plateau (see Figures 3-8, 3-10, and 3-12). A simple spatial model was developed which converged the empower contributed by rain and mountain uplift to the lower elevation land and ultimately to the stream channel. This was a modification to Romitelli's (1997) suggested methodology. The model was applied to the Wine Spring Creek watershed to quantify how the empower of the streams increased downstream (see Figure 3-14). According to the area-based

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.149 frequency distribution of empower density, a large portion of the watershed with low empower densities E 16 sej/ha/y) was required to make a small area of high empower density (>IEI7 sej/ha/y) (see Figure 3-15). Management Policies To fully appreciate the social and economic benefits offorest lands, the new philosophy of ecosystem management must take a systems viewpoint which can realize the importance of the multiple forcing factors over varying scales of space and time, and can relate these forcing factors to the services and products. Only then will we be able to understand the physical, material and energy basis of forest wealth and the consequences of management decisions. Evaluation of the MUL TIBEN model highlighted the synergism that exists between the various products of the forest. Over a small geographical scale and short time horizon it may seem that managing the forest for a single output is the wisest choice. Results in Figure 3-43 did show that forest empower could be maximized at an intermediate intensity of outside investment, but that only one product was produced; recreation was provided at the exclusion of ecological services and timber products. A better management strategy, one which appreciates the trade-offs between the multiple benefits, was evaluated with the sustainability product function in the MUL TIBEN model. Maximum empower from multiple forest benefits was achieved at an intermediate intensity of outside investment and an even mix of forest products (see Figure 3-44). New Solar Tranformities Table 4-1 shows a list of the solartransformities calculated in this dissertation.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.150 Table 4-1. Swnmary of solar transformities calculated in this dissertation. Emergy Transfonnity, per mass, Item sej/J sej/g Source Environmental Energies Atmospheric water vapor saturation deficit 5.9E+02 Table C-3 assumed equal to earth Atmospheric deposition LOE+09 cycle Altitude dependent earth deep heat variable Table E-l Altitude dependent mountain erosion variable Table E-2 Internal processes at Cowf'eta WS18 Rock weathering 4.6E+09 Table 3-1 Forest calcium cycle (l00 yr old forest) 2.7E+1O Wood growth 2.1E+04 Net primary production, aboveground LIE+04 Net primary production, roots only L5E+04 Litterfiill 2.0E+04 Stream discharge, chemical potential 4.4E+04 Outputs from Wine Spring Creek watershed Recreated people 2.4E+07 Table 3-2 Research information 3.1E+12 Stream discharge, chemical potential 3.2E+04 Timber, harvested wi services 7.0E+04 Forest products of U.S. Forest growth, average for North Carolina 2.1E+04 Table 3-12 Logs delivered to sawmill 2.7E+04 Table 3-13 Woodpulp 6.0E+04 Table 3-14 Paperboard L3E+05 Table 3-15 Paper 2.4E+05 Table 3-16 Plywood LIE+05 Table 3-17 Lumber 7.9E+04 Table 3-18 Storages at WS18 Coweeta Soil moisture, chemical potential 5.2E+04 Table 3-4 Wood 3.0E+04 Table 3-4IFigure 3-8 Total organic matter 2.5E+04 Table 3-4 Saprolite 7.9E+09 Table 3-4IFigure 3-12

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.151 Emergy of Southern Appalachian Watersheds Environmental Driving Energies and Empower Spectra Environmental energies that drive development of forested watersheds in the Southern Appalachian Mountains were shown to have similar empower (Figure 3-3). In the 'Vine Spring Creek watershed, the contribution of empower from the water vapor deficit, wind kinetics, rain geopotential, rain chemical potential and deep heat ranged narrowly between 280 E12 and 520 E12 sej/ha/y. Does the fact that the empower of all environmental inputs were nearly equal indicate that the forested watershed self organized so that all inputs are equally limiting? In the case of the Wine Spring Creek watershed, sunlight contributed the least amount of empower (50 E12 sej/ha/y) of the energy forms evaluated, which may indicate that it was the limiting factor. New perspectives concerning the relationships between driving energies and their role in organizing the architecture of the forested watersheds may be gained from analyzing the empower spectra. With the empower spectra, an ecosystems unique pattern of use of different energy forms is described graphically. The spectra quantitatively describe the setting in which the ecosystem operates. For example, differences in the empower spectra of the two Southern Appalachian Mountains watersheds indicated that use of chemical potential energy of water was more important in the Coweeta basin (i.e., transpiration was higher), but the use of water's geopotential energy dominated in the Wine Spring Creek (Wine Spring Creek) watershed (Figure 3-3). The ratio of the empower of chemical energy used (evapotranspiration) to the empower of geopotential energy used (waterrunofl) was 5.7 (850/150 E12 sej/ha/y) for WS18 of the Coweeta basin, but only 0.83 (500/600 E12 sej/ha/y) for the Wine Spring Creek basin. This fits

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.152 with Romitelli's (1997) observation that this ratio increased as altitude decreased. That is, in tenns of emergy, geological productivity was greater than biological productivity in the mountain headwater streams, but that the dominant form of energy use shifted downstream. The chemical to geopotential ratio of water use is but one emergy ratio that could be measured. Other ratios, developed from the empower spectra, may provide vital information about the general properties of system energetics. The ratio of vapor deficit use to sunlight was calculated for the Southern Appalachian watersheds. Coweeta's index of vapor deficit use to sunlight was 15 (750/50 E12 sej/ha/y) while it was 8 (400150 E12 sej/ha/y) for the Wme Spring Creek basin. Another emergy index calculated was geologic input (deep heat) to vapor deficit use. This index was 0.65 for Coweeta's ws 18 and 1.12 for the Wine Spring Creek. Therefore, the change of both emergy indices with altitude (mid-points for the basins were 860m for Coweeta's ws18 and 1320m for Wine Spring Creek) demonstrated that the proportional contribution from the forms of energy adjusted to the changing availability of energy forms. These indices have properties analogous to the emergy investment ratio that has been used often to indicate the intensity at which the environment was being used by an economic activity. Values for the emergy investment index were often in the range of 1 to 100. Values near one (1) have typically been found for forest lands (Odum and Odum 1987, Doherty 1995), while urban landscapes have been observed to have values greater than 100 (Mecklenburg County, N.C., this study). Since the transformity of the vapor deficit (590 sej/J) was higher than sunlight (1 sej/J), the vapor deficit was the high quality energy that was matched to the lower quality energy, sunlight. Most remarkable was the

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.fact that the ratio of vapor deficit use to sunlight was in the realm of an order of magnitude (l0). Emdollar Values of Forest Processes, ExPorts, and Storages 153 The Wine Spring Creek watershed contributed wealth to the economy at the annual rate of 4300 Em$ per hectare of watershed. This was the combination of environmental and imported energies. The role of the watershed as a research facility was of greatest value (3450 Em$1ha; see Table 3-2). Water yield was second at 2060 Em$/ha, while recreational value was 1880 Em$/ha. Much of the basin has been excluded from timbering in order to maintain high "visual qUality" for tourists. Thus timbering was not the major focus of forestry management and it showed in the analysis. Harvested timber (300 Em$/ha) was an order of magnitude less than the other activities. However, timber, once harvested, continues to attract emergy investment. It serves as raw material for the forest products industry, and eventually becomes a consumer product. For example, if the wood were to be made into plywood, the 300 EmS value would attract another 200 EmS, based on the multipliers developed from the emergy evaluation of the U.S. forest products industry. Applying North Carolina's average emergy investment ratio to the timber harvested from Wine Spring Creek indicated that the wood could attract outside resources at the rate of 3.8 to I. Thus, 1140 EmS could be added on top of the timber's environmental value of300 Em$ for a total value of 1440 Em$. This places timber's economic benefit in line with the value of the other ecosystem goods and services, slightly below its recreational value. This indicated that multiple-use function of the Wme Spring Creek watershed was satisfied, and that

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.total empower was maximized over the long-term since all activities were equally represented. Value of biogeochemical cycles 154 Maintenance of nutrient cycles is an important ecological service that was evaluated for the forested watersheds of the Southern Appalachian Mountains. According to the emergy evaluation of Coweeta watershed, nutrients were being cycled at the rate of360 kglha/y (see Table 3-1). The empower required to operate all of the individual biogeochemical cycles (i.e., calcium, sodium, ammonium, magnesium, potassium, sulfate, nitrate, chlorine, bicarbonate, phosphate, and silicon dioxide) of the watershed was 5.6 EmS per kilogram of total constituent (6.2 E9 sej/g; see Table 3-1). Calcium was selected as an important element to evaluate with emergy. The emergy evaluation of the calcium cycle revealed that ratio of environmental empower to mass flow (emergy per mass) was 25 EmS/kg-Ca (27 E9 sej/g-Ca), which was higher than the average determined for the total mineral cycle. The reason being that the calcium cycle was assumed to be a co-product (co-cycler) of the internal mineral cycle. Any mineral recycled within the forest must be necessary for the system to operate or it would not be re-used. Therefore, any process that is critical to the functioning of the total system required all of the system's inputs in order to work properly. With this accounting philosophy, the total empower driving anyone elemental cycle was the same as the empower driving the whole watershed. For the Coweeta watershed, this meant that the empower of the calcium cycle was 2030 EmS/ha/y (2237 E12 sej/haly; see Table 3-1). The question arose of how to allocate empower to the watershed's exported calcium. In this study, the calcium exported was considered a split of the internal

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.155 calcium cycle. Therefore it had the same emergy per mass as the internally cycled calcium (27 E9 sej/g). This meant that the exported calcium had the same quality as the internally cycled calcium. The value of the dissolved calcium in the stream water was determined to be 170 EmS/ha/y. Value of recreation in Wine Spring Creek watershed The Em$ value of recreation and tourism within the Wine Spring Creek watershed was determined to be 1880 EmS/haly (2.1 E6 Em$/y). Of this total value, the environment contributed 55% and 45% was imported. Thus, the environmental loading ratio ofeco-tourism was 0.83 (935 E12 to 1130 E12 sej/ha/y). An environmental loading ratio (ELR) of one (I) may be the match that optimizes environmental use. A value much lower, may indicate that the environment was under utilized, and resembled wilderness. On the other hand, an ELR much greater than one was probably "unhealthy" for the ecology of the watershed. Value of research at Coweeta A complete emergy analysis of the long-term research (60+ years) at Coweeta was not conducted, but an approximation of the total value of the research was made based on the emergy analysis of research publication record for the Wine Spring Creek Ecosystem Demonstration Project. If the 880 publications associated with the Coweeta Hydrologic Lab (Stickney et al., 1994) had the same emergy-to-publication ratio (450 E15 sej/publication) as those of the Wme Spring Creek, then the total value was 396 E18 sej (360 million Em$). Most likely, this was a conservative estimate, since the intensity of investigation at Coweeta has been much greater, historically, than that of the Wine Spring Creek.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.156 Value of tree species in Wine Spring Creek watershed Tree species were estimated by the EMSPECIES model to be worth about 2.6 E24 sej (2.2 E12 Em$) for the entire 1128 ha Wine Spring Creek watershed. The six (6) meters of saprolite, which required about 5 E5 years to form, was worth 7.3 E20 sej/ha (700 E9 Em$). The 350 MT/ha oftota! organic matter was valued at 8.0 El7 sej/ha (765 E6 Em$) and the 135 MT/ha of wood was worth 1.7 E17 sej/ha (163 E6 Em$). Comparisons of the Ecological Economics afForest Systems Emergy Measures of Living Standard The total emergy use per area was 1.38 Xl012 sej m-2/y in N.C. (Table 3-21),0.38 Xl012 sej m-2 /y, in Macon county (Table 3-20), and 0.46 Xl012 sej m-2 /y in Wine Spring Creek basin (Table 3-19). Thus, the multiple-use activities of the Wine Spring Creek watershed were occurring at an intensity less than the average for North Carolina, but greater than Macon County's. Annual per capita empower, a measure of living standard, was 2.73 E 16 sej/person/y (23,000 Em$/person/y) in N.C, and slightly less in Macon county at 2.16 E16 sej/person/y (18,000 Em$/person/y). Wine Spring Creek had no permanent residents, but a comparable measure was the annual empower per tourist-year (20.4 E 16 sej/person/y; 174,000 Em$/person/y). The high value experienced by the tourists showed how rewarding the nature experience was. Even the renewable fraction of the empower per capita in the Wine Spring Creek watershed was 4.34 E16 sej/person/y (34,000 Em$/person/y). This may explain why people are drawn to the unpopulated forested mountains; they experience a high rate of free empower.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.157 If per capita empower consumption is an appropriate measure of living standard, then North Carolinians have had the same standard of living since 1973. The growth in per capita empower consumption stopped increasing in 1973 and remained near 24 E 15 sej/personly to 1994 (Figure 4-2). In contrast, the per capita gross state product increased at an average annual rate of2.9'% from 1977 to 1994 (Figure 4-2). The combination of these two phenomena led to a temporal pattern of exponential decay in North Carolina's emergy-to-dollar ratio over the period from 1977 to 1994 (Figure 4-3). In 1977, the emergy-to-dollar ratio of N.C. was 4 E12 sej/$, but had declined to 1 E12 sej/$ by 1994. This pattern was similar to that of the U.S. economy as calculated by Odum (1996). Some interpretations of this phenomenon are i) N.C.'s economy has increased its efficiency of empower use, acquiring more product for the same emergy use, ii) the divergence of emergy use and GSP represents inflation, more dollars are needed for the same resources, iii) the economy has become more urbanized, forcing more market exchanges to take place for the same amount emergy use, or iv) a mix of all three. Emergy Measures of Sustainability One gauge of system sustainability is its ability to support itself for an extended period of time. Long term sustainability means to rely solely upon indigenous, renewable energy sources. Thus, the simplest measure of system sustainability may be the fraction of total empower derived from indigenous, renewable sources. For N.C. the fraction was 0.10 (Table 3-21), for Macon County it was 0.22 (Table 3-20) and for the Wme Spring Creek watershed it was 0.27 (Table 3-19). None of the forested systems were sustainable by this definition.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.30,000 25000 --, c: g 20,000 .... c: Q) Q) rn 0. 15,000 w .. >. L..; Q) Q) c: 0 o::E 0. 10,000 E w 5,000 1960 per capita Empower Use 1965 1970 1975 '" ,. .... per capita Gross State Product 1980 1985 1990 Figure 4-2. North Carolina's per capita empower consumption and per capita gross state product. .... VI 00

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.4E+12 3E+12 !!! 'iii' 3E+12 I/) "",-.i'! '0 b 2E+12 2E+12 w 1E+12 5E+11 o 1977 1979 1981 1983 1985 Timey 1987 1989 1991 Figure 4-3. Emergy-to-dollar ratio of North Carolina from 1977 to 1994. Total empower used in N.C. per unit of gross state product. 1993 .u. \0

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.160 Using only renewable resources, North Carolina could sustain a population of 772,OOO-one-ninth of its current population of seven (7) million-at the present standard of living (Table 3-21). Conversely, the present population could be sustained with the renewable base if the standard of living was reduced to one-ninth (2.7 E 15 sej/person/y; 2500 Em$/person/y). In Macon County, a population of 5100 could be sustained at the current standard of living if only renewable resources were used (Table 3-20). Or, the present standard of living could be reduced to 4.7E1S sej/person/y (4300 Em$/person/y) to fit with the availability of renewable resources and sustain the present population. Two other indices that related environmental empower to imported empower were also used to gauge sustainability. The first, the ratio of total imported empower to locally free empower (renewable + non-renewable) indicated each systems' reliance on outside sources. The second, the ratio of concentrated empower (imported + indigenous nonrenewable) to locally renewable empower indicated the intensity with which the environment was being used. The latter was termed the environmental loading ratio (ELR). Table 4-2 compares the value of the indices for North Carolina, Macon County, and Wine Spring Creek watershed. Table 4-2. Emergy investment ratios offorested systems System Concentrated to Freea Environmental Loading Ratiob North Carolina 3.8 9.1 Macon Co. 1.6 3.6 Wine Spring Creek 2.7 2.7 watershed 8ConcentIated to Free = (F+G+P2I+Nl)/(R+NO); see Figures 3-19 and 3-28. Loading Ratio = NO+Nl+F+G+P2I)IR; see Figures 3-19 and 3-28.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.North Carolina was importing 3.8 solar emjoules for every free solar emjoule (column 2 of Table 4-2), while Macon County was importing less, 1.6 per one free. In the Wine Spring Creek watershed the environmental empower was matched with imported empower at 2.7:1, a rate less than the state's average of3.8, but more than the county's 1.6. 161 The environmental loading ratio showed that economic emergy use in N. C. was 9.1 times greater than environmental empower (Table 4-2). In Macon County the environmental empower was matched with empower from non-indigenous, non renewable resources at 3.6: 1, while in the Wine Spring Creek basin the ratio was 2.7: 1. Over the long-term, none of these systems were sustainable at this level of use. For their current levels of use, each required the importation of outside resources. Once external resources become scarce, these systems likely will falter to keep up with their present levels of activity. Spatial configuration of sustainability in North Carolina Since the environmental loading ratio (ELR), purchased to renewable, was an index of sustainability, it was calculated for all 100 counties of North Carolina to gain some perspective on the spatial configuration of sustainability. Thirty-four (34) of the one-hundred (100) counties had ELR's greater than the state average of9.I, while sixty six (66) counties were below the average. The majority of the unsustainable counties were located in the Piedmont region, centered about U.S. Interstate 85 from Charlotte to Greensboro to Raleigh (see Figure 3-36). The majority of the counties of the mountain region and coastal plain had ELR's less than the state average of9: L

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.162 Sustainability of forestry The mean environmental loading ratio (ELR) of forest logging in the U. S. was 0.17. Relative to other agricultural activities this ratio was quite low. Pine plantations of New Zealand (Odum and Odum 1983), Texas cotton (Odum and Odum 1987), North Carolina tobacco (this study, see Appendix G) had ELR's of 1.4, 9.6, and 20.0, respectively. This meant that forestry impacted the environment less and was more sustainable than these other forms of agriculture. Sustainability of tourism and human immigration in Macon County Western N.C. has been a popular tourist attraction for many decades. Controversial though, are the benefits of large-scale tourism. Tourists can impact their destination by acquiring much more of the local emergy budget than they give back to the local economy. The cumulative impact of tourism in Macon County equaled 2.74 E20 sej y-l, but only one-fifth (0.49 E20 sej/y) of this input benefited the local economy in form of money payments (Table 3-7). The tourist gained four (4) units of emergy for every one (1) unit they spent. Of course, this may be an inevitable property of a tourist driven economy; people will only recreate where the emergy benefit greatly exceeds their emergy forfeiture. The coupled aging of the U.S. population and their growing personal financial wealth has increased the demand for both retirement and vacation homes. Macon County, surrounded by National Forest lands and only a couple of hours drive from large metropolitan areas such as Atlanta and Charlotte, has been a favorite locality for people to retire and to purchase second homes. In 1992, the net migration to the county was 503 people, 2% of the population. One measure of the impact of this phenomenon is the

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.163 additional flow of emergy the people will demand from the County's total resources. Table 3-7 showed that county immigrants increased the flow of emergy in Macon county by 0.47 E20 sej/y (90/0 of annual total use). Thus, adding residents caused empower use to increase faster than population growth. The Dynamics ofEmergy. Empower and Transfonnity Calculating Transformities Dynamically A simple, one state variable model (EMERGYDYN) was used to calculate the transformity of processes and storages, dynamically through time. The technique, modified from Odum's (1996) initial suggestions, was based on the premise that a unit accumulated emergy up to the point when emergy outflow equals emergy inflow. In the simulations conducted in this work, the condition that there was some export of emergy had to be satisfied in order not to invoke an automatic cut-off for the emergy accumulation process. The temporal simulations of emergy accumulation by wood biomass, total organic matter, and saprolite, showed that emergy and transfonnity lagged the state variable, reaching their respective steady state values much later. In forest ecosystem management, 'old-growth' forest could be defined according to a minimum emergy accumulation. The simulations conducted here (Figure 3-8 and 3-10) showed that the Coweeta forest required -300 years for the transformity of its wood to reach steady state, although the wood biomass had climaxed by the one-hundredth year. In future emergy evaluations, it will be important to use this dynamic calculator when the window of interest covers the whole growth cycle, from birth to maturity. If an analyst was only interested in the emergetics of a unit of a short period of its life-cycle,

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.164 then temporally dynamic calculation may not be necessary. In this work, the focus was on forests management which spanned 100 years or more. The length of that time scale allowed for significant accumulation of emergy. Thus, it was important to distinguish between young and old stands of forests by their transformity and emergy values. Accounting for the Energy Transformation Processes of the Landscape Environmental energies impinge on the watershed landscape perpendicular to the surface. The drainage basin, formed with past hydrogeologic work. captures the empower of the diffuse environmental energies (uplift, rain, vapor deficit) in the uplands and accumulates the empower as the water is converged downstream through the stream network. Thus, the stream flow leaving a watershed accumulated the empower of the whole basin. The drainage network is organized as a continuous chain of energy transformations, and has properties similar to any chain of energy transformations. In the work presented here, a simple method for calculating this convergence of empower across the landscape was demonstrated for the Wine Spring Creek watershed. The method follows the framework given by Romitelli (1997) and Diamond (1984), but extends the concept to include the land's geologic contribution, and applies the techniques in a grid (raster) based geographic information framework. Since properly defining the spatial configuration of the empower of the watershed is critical to understanding the energy transformation processes of the landscape, and since the methodology is quite simple to apply, it should be incorporated in future emergy evaluations of watersheds. Dynamics ofEmergy-to-money Ratio and Transformity in the Forest Products Industry For the wood products industry, the emergy-to-$ ratio correlated with the inverse of the logarithm of the transformity of the product (see Figure 3-32). The simplified units

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.165 of the slope were energy per dollar. An intriguing idea is what the slope of the graph would be for other natural materials such as petroleum, metals, water or agricultural products. Possibly, the slope would be identical for all materials, but just as likely, it would indicate some inherent difference in the materials themselves or the system of which they were a part (e.g., the economy). In any case, the energy quality of a material explained the variability in the emergy-to-dollar ratio. Shown in Figure 4-4 is a temporal empower difference spectra, a new category of empower spectra that plots the difference between two empower spectra representing the same process, but calculated for different time periods. It was constructed to note the change in individual inputs to the u.s. pulpwood industrial sector between 1972 and 1990. For each energy input (e.g., biomass, electricity, labor, etc.), the difference between empower input per power output for 1972 and 1990 were calculated and plotted as a function of their solar transformity. Empower use per unit of pulp output decreased for all major energy sources except electricity, which increased by 500 sej per J of pulp output. The biggest decrease was in petroleum, which was down 5000 sej per J of pulp output. (Note: the transformity of the inputs was held constant to evaluate the change in empower. The consequences of this simplifying assumption should be explored in the future). The data in Figure 4-4 was derived from Tables G-l and 3-14. In 1972, the industry produced pulp that had a mean transformity of6.9 E4 sej/J (Table G-l). By 1990, the transformity dropped 13% to 6.0 E4 sej/J (Table 3-14). Conversely, the emergy-to-dollar ratio decreased from 47.3 E12 to 9.3 E12 sej/J over the same period.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.1000 woOd narn1l .. 11 (1)-, 0 1ft a. ::;:. 'V G> t >; ::l en -1000 __ a.. .-5. -2000 co __ .-..-0 :J 0 -3000 craG>>. (,) EC w G> -5000 1E4 1E5 1E6 1E7 Transformity of input, sej/J Figure 4-4. An empower difference spectra of the U.S. woodpulp production industry (1972 vs. 1990). Transformity of wood pulp in 1972 was 6.9E4 sej/J, but decreased 13% to 6.0E4 sej/J by 1990. The graph shows the differences between the empower inputs, normalized to a unit of output (sej/J), plotted as a function oftransformity of the input (sej/J). Values above zero indicate that more of that input was used in 1990 than in 1972. 1E8 166

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.167 Thus, the change in solar transfonnity of a manufactured product (woodpulp) was modest over a period of 18 years. The decrease in solar transformity, averaged over the 18 year period was 0.7% per a year. On the other hand, the emergy-to-dollar ratio ofa manufactured product decreased significantly, by a factor of five (5), overthe 18 year period. This change represents inflation. A dollar spent in 1990 only purchased 20% of the wood pulp that a 1972 dollar did. An Explanation for the Fluctuating Empower Spectra of North Carolina The spectra of empower use in North Carolina (Figure 3-26b) exhibited a fluctuating pattern in the domain of solar transformity between 1 E4 and 1 E5 sej/J. Figure 4-5 offers a possible explanation for the phenomenon. First, assume that two energy transformation processes (1 and 2 in Figure 4-Sa) in series were a function of three energy sources (L, N in Figure 4-Sa), where L, and N had increasing solar transformities (a popular configuration according to emergy systems theory). Next, consider that total production (P2) remains the same, but that N increases (a shift along the isoquant for process 2 in Figure 4-Sb). Assuming that over a small interval, Nand PI are substitutable inputs to process 2, then PI must be decreased to accommodate the change. A drop in PI results in lower demand for M ifL remains the same (a move to the lower isoquant for process 1 in Figure 4-5b). The end result is a fluctuation in the empower spectra for the combination of process 1 and 2 (Figure 4-Sc). Tranformity of yield versus transformity of contributing resource storage The ratio of the transformity of the extracted timber to the time-averaged transformity of the wood of the contributing forest was calculated for the Coweeta forest under various logging rotations. In Figure 4-6, the ratio is shown to decrease

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.M Empower L--.. t P1 _-N P2 a) diagram of energy chain necessary for producing P2 Fadors, process G Factors, process 8 P1" --"""P1' L N P1' P1" Pi P2 b) production isoquants for process G and process 8 input levels Input levels after increas N L M N L M Empower Transformity Transformity c) empower spectra for diagram in (a) before and after changes in M and N Figure 4-5. A possible explanation for the dynamics observed in the empower spectra of the forest systems evaluated. A simple system of three inputs (L,M,N) and two interactions (1&2) produce a final product P2 (a). Production isoquants demonstrate the substitutability ofM for L, and N for PI (b). In (c), changes in the empower spectra are shown. Originally, the empower of inputs L,M&N were equivalent when producing P2. Later, N was increased but P2 was held constant. This decreased the need for PI in process 2 which, in this case, decreased the need for M assuming that L did not change. 168

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.'-:J\ 8.'5 u>-.-E u o (I) 0 o c 02 e o Q) (I) >-0(1) :: (; 1 E .E m I enQ) O! t I t t I t t I t E --r '-.-..... a 100 200 300 400 Cycle time, y Fig. 4-6. Ratio of the mean transformity offorest yield (Y in Figure 3-42a) divided by average transfonruty of forest wood (Q in Figure 3-42a) calculated from the EMERGYDYN simulation modeL At cutting frequencies> 100 y, the quality of the wood yielded to the economy was double that of the forest, averaged over the growing period. The quality of the yield for rotations < 20 y was from 3 to 3.5 times greater than the quality of the growing forest. l69

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.170 asymptotically to two (2) as the interval between cuttings increased. This means that when logging rotations were greater than 100 years the quality of the timber (yield) was twice as great as the quality of the forest. For shorter cycle times, the ratio was greater than two (2) indicating that the receiver of the timber was getting a much higher quality product than was left behind in the forest. Comparisons of mountains and urban landscapes based on empower density Cities are places of high empower density, as are mountains. In a well-organized ecological-economic system, cities feedback high quality energy (e.g., legal, religious, etc.) and recycle waste materials (e.g., solid and liquid wastes) to the surrounding landscape. The feedback is necessary to maintain the foundation of the city's energy network Development of urban systems as centers for controlling the activities of the landscape seems analogous to the development of mountains as agents that control landscape processes. The analogy can be extended quantitatively by comparing the empower density of the two different landscapes. The empower density of mountain landscapes was found to increase with altitude (see Appendix D). The mean empower density of North Carolina and a mountain 2800 m (-9200 feet) above sea level were both 12.8 E15 sej/ha/y. The county of Mecklenburg, home of the state's largest city, Charlotte, had a mean empower density of 134 E 15 sej/haly coinciding with the empower density ofa 5100 m (16,750 ft) mountain. Humans living in high altitude environments are stressed by low oxygen pressure, a condition known as hypoxia. At sea level, blood hemoglobin is nearly 1000/0 saturated to 19.5 mL-02l' 1 00 mL-blood. At this concentration, 5 mL-02 can be transferred to tissue for each 100 mL of blood (a drop to 14.5 mL-02l'100 mL blood). The atmosphere's

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.171 partial pressure of oxygen decreases with altitude. At 6000 m oxygen pressure is -40mm Hg, which corresponds to the 14.5 mL-O:JlOO mL-blood where oxygen transfer to tissue is minimal. Interestingly, the empower density of mountains at an altitude of 6000m is 343 E15 sej/haly, which is over two and a halftimes (2.6) the empower density of Charlotte. Pawson and lest (1978) as reported in Stone (1992) suggest that an elevation of2500m is the delimiter of hypoxia. The empower density of mountains at 2500 m was 8.9 E15 sej/ha/y, which in North Carolina was the empower density at which the emergy investment ratio of several counties was 7: 1 (purchased:renewable). Does the empower density of natural landscapes offer clues as to how much urbanization is locally sustainable? In the future it would be interesting to pursue this line of evidence more thoroughly. Some questions to investigate would be: where is the highest empower density on earth? Is it a man-made or natural feature? If it is man made, how does its empower density compare to Mt. Everest or the mouth of the Amazon River? Does the empower density of mountains which corresponds to the ecological limit of trees (the tree line) or other life forms correspond to the empower density of the largest cities? Plans for Future Research Emergy evaluation is a powerful tool for analyzing and quantifying the importance of the multiple forcing factors, internal pathways and units, and outputs of forested systems. In this dissertation, the utility of the emergy spectra as both a visual and analytical tool for studying the interrelationships between the multiple forms of energy was emphasized. To fully realize the strength of this analytical tool, spectra need to be developed for all the world's biomes and compared to one another. Only then will

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.172 the emergy spectra's ability to integrate and synthesize our understanding of ecosystems be appreciated. The ramifications of calculating transformities and emergy accumulation dynamically need to be investigated further. This is especially important when the time scale of interest is as long or longer than the time required for the transformity of a process to reach its steady state. The methodology for calculating the empower and transformity of mountains, which was introduced here, needs to be more thoroughly investigated. The emergy contributed by land resources (e.g., minerals, uplift) to ecological and economic systems needs to be accounted for more thoroughly. Emergy valuations of biogeochemical cycles, begun here with the calcium cycle, need to be undertaken and explored. Work that strives for systems evaluations of forest management needs to continue. Emergy evaluation shows promise in comparing the multiple functions of forest systems and can lend valuable insight into the consequences of meeting the publics increasingly diverse set of goals. Therefore, emergy evaluation should playa central role in evaluating forest policy for its total, long-term benefit to society.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Available Energy Useful Energy Power Emergy Transformity Empower Solar Emergy Solar Transfonnity Solar Empower Emdollars (Em$) Earth deep heat GLOSSARY TERMS AND DEFINITIONS Potential energy capable of doing work and being degraded in the process (units: kilocalories, joules, etc.) Available energy used to increase system production and efficiency Useful energy flow per unit time Available energy of one form previously required directly and indirectly to make a product or service (units: emjoules, emkilocalories, etc.) Emergy per unit available energy (units: emjoule per joule) Emergy flow per unit time (units: em joules per unit time) Solar energy required directly and indirectly to make a product or service (units: solar em joules, sej) Solar emergy per unit available energy (units: solar em joules per joule, sej/J) Solar emergy flow per unit time (units: solar emjoules per unit time) The commensurate amount of dollar circulation resulting from the use of emergy Heat emanating from deep within earth from radiogenic and residual sources 173

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.0---Or I = Energy circuit: A pathway whose flow is proportional to the quantity in the storage or source upstream. Source: Outside source of energy delivering forces or flows according to a program controlled from outside; a forcing function. Tank: A compartment of energy storage within the system storing a quantity as the balance of inflows and outflows; a state variable. Heat sink: Dispersion of potential energy into heat that accompanies all real transformation processes and storages; loss of potential energy from further use by the system. Interaction: Interactive intersection of two pathways coupled to produce an outflow in proportion to a function ofboth;control action of one flow on another, limiting factor action;work gate. Consumer: Unit that transforms energy quality, stores it, and feeds it back autocatalytically to improve inflow. Switching action: A symbol that indicates one or more switching actions. Producer: Unit that collects and transforms low-quality energy under control interactions of high-quality flows. Box: Miscellaneous symbol to use for whatever unit or function is labeled. Constant-gain amplifier: A unit that delivers an output in proportion to the input I but is changed by a constant factor as long as the energy source S is sufficient. Transaction: A unit that indicates a sale of goods or services (solid line) in exchange for payment of money (dashed line). Price is shown as an external source. Figure Glossary-I. Energy systems symbols and definitions. 174

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.APPENDIX A SOLAR TRANSFORMITlES USED FROM PREVIOUS WORK AND FOOTNOTES TO EMERGY EVALUATION TABLES Appendix A contains a list of the solar transformities, previously calculated by others, which were used in this work (Table A-I). This appendix also has the footnotes for the majority of the emergy evaluation tables. A few tables with short footnotes (Table 3-6,3-12) are listed at the bottom of the tables themselves. Here, footnotes are given for the watershed analyses (Table 3-1,3-2,3-4,3-5), Macon county (Table 3-1), North Carolina (Table 3-9,3-11), and the U.S. forest products industry (Table 3-13, 3-14,3-15, 3-16,3-17,3-18). 175

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.176 Table A-I. Summary of solar transfonnities previously calculated and used in this dissertation. Transformit-y Emergy per Item sej/J mass, sej/g Source Environmental Energies Sun 1.0E+OO Odwn, 1996 Wmd, kinetic (global average) I.5E+03 Precipitation, geopotentiaI (global average) LOE+04 Tide (global average) L1E+04 Hurricanes, wind I.OE+04 ? Precipitation, chemicalpotential (global average) L8E+04 Odum, 1996 Waves (global average) 3.IE+04 Earth deep heat (global average) 3.4E+04 Hwnan metabolism (United States) VISitors to Wme Spring Creek 8.9E+06 Immigrants to Macon 2.4E+07 Scientists 3.4E+08 Erosion (global average) l.OE+09 Fuels, electricity, & minerals Petrolewn 6.6E+04 ? Coal 4.0E+04 Odum, 1996 Natural gas 4.8E+04 Electricity 1.6E+05 Hydroelectricity 1.6E+05 Non-fuel minerals (e.g., granite, sand&gravel) 5.0E+08 Machinery, heavy 6.9E+09 ? Phosphate rock, mined (Florida) 3.9E+09 Odum, 1996 Metals 1.OE+09 ? Agricultural products Odum & Odum, Livestock (Texas cattle) 2.0E+06 1987. Crops (Texas grains) 2.0E+05 assumed same as Fish 2.0E+06 livestock

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-1 (emergy evaluation of Coweeta watershed) 1 SOLAR ENERGY 2 Land Area of 1.0 ha = 10,000 m"2 Insolation @ ground = 5.00E+9 J/m"2/yr (Swift et aI., 1988) Energy(J)= (area)*(avg insolation) = L-m"2)*L-.J/m"21y) = 50.0E+12 Mean conditions Effects of ET Difference Atmos. pressure, mb 1000 1,000 Mean annual temp. C 12.6 12.6 sat. vap. press.(eJ, mb 14.60 14.60 sat. mix. ratio (qJ, glkg 9.08 9.08 Evapotranspiraton (ET), gly 9.10E+09 Air exchange, m3/y 3.75E+11 Depression of mix. ratio, glkg 0.0202 vapor press.(e), mb 12.20 12.24 0.0325 mix. ratio (q), g/kg 7.59 7.61 0.0202 sat. deficit (qs-Q), glkg 1.49 1.47 -0.0202 sat. deficit (es-e), mb 2.39 2.36 -0.03 free energy, Jlkg 198.3 195.6 -2.69 free J/m3 238.0 234.8 -3.23 Mean annual temperature at climate station CS01 in Coweeta basin. Saturation vapor pressure (eJ, mb = 611*EXP.27*T)/(237.3+n)/100 Where T is mean annual temperature, C Saturation mixing ratio, g/kg = 622x(es,mb)/(air pressure,mb) Evapotranspiration, gIy = (0.91 m/y)x(1 0,000m"2Iha)x(1 E6 glm"3) Air exchange, see Table cow-wind Depression of mix. ratio, glkg = (ET, gIy)/(Air exchange, m"3/y)/(1.2 kglm"3) mix. ratio, glkg is mean annual for CS01 Vapor pressure, mb = (mixing ratio, glkg)x{air pressure,mb)/622 sat. deficit, glkg = sat. mix. ratio mix. ratio sat. deficit, mb = sat. vapor pressure vapor pressure free energy, Jlkg = -8.33*(273+n*LNO-qJ/(1000-q/18*100 177 .. ree energy or_mass = JlmoIeIdeg C)X{ I deg C)X (Loge({1uuu-sat. mIX. rabO.gIkg)l{1UUO-moc. ratIO, gIkg) I Energy of the saturation deficit used. J/y = (dlrfetellce in free energy. J/m-'3)x(air exchange. mA3Iy) Energy of the saturation deficit used, J/y = (3.23 J/m"3)x(375 E9 mA3/y) Energy of the saturation deficit used, J/y = 1.21E+12 3 Wind, kinetic energy Energy, J/y = 1.88E+11 see Table 0-1

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-1 (emergyevaluation of Coweeta watershed) 4 Water transpired Land area, m2 = Rain, mJy = Transpiration rate, m1y 10,000 1.94 0.91 WS 18 @ Coweeta (Swift et aI., 1988) WS 18 @ Coweeta (Swift et aI., 1988) Energy on forest land (J) = (area)(Et){Gibbs no.) = L-m"2)*L-m)*(1000 kg/m"3)*(4940 Jlkg) = 4.47E+10 5 PRECIPITATION CHEMICAL POTENTIAL Land Area, m"2 = 1.00E+04 WS 18 @ Coweeta (Swift et aI., 1988) Rainfall, rnJy= 1.94 WS 18@Coweeta(Swiftetal., 1988) 178 Water chemical energy used (J) = (area)(rainfall)(density of water)(Gibbs no.) = L-mA2)*L-m)*(1000 kglmA3)*{4940 Jlkg) = 9.58E+10 6 Deepheat 1.00E+04 Land Area (mA2) = Heat flow 1 Area = 1.36E+06 J/m"21y, @ Bryson City, NC (Smith et aI., 1981; in Pollack et aI., 1991). Energy (Jlha) = 1.36E+10 Transformity, 34,400 sej/J was the mean calculated for the continents by Odum, 1996. 7 PRECIPITATION, GEOPOTENnAL Mid-elevation of WS 18, m =-(max + min)/2 = (993 + 726)12 Mid-elevation of WS 18, m =-860 Energy @ mean elev. (J) = (area)(runoff)(mid-elev min. elev)(density)(gravity) = <-m"2)*<-mmly)/(1000 mmlm)*<-m)*(1000 kg m-,*(9.8m1s"2) Energy, geopotential (Jlha) = 13.5E+9 8 Atmospheric deposition, total ions Ion Atmospheric Input, kglhaly Ca+ 3.63 Na+ 3.17 NH/ 1.78 Mg2+ 0.76 K+ 1.76 S042-S 9.69 N03 -2.67 cr 5.07 Total 1.27 0.08 0.55 30

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.179 Footnotes to Table 3-1 (emergy evaluation of Coweeta watershed) Source: Swank and Waide, 1988. Empower per ion influx (sejlg) assumed equivalent to mean global land cycle. 9 ca as dryfall (wind) Dryfall deposition, kg/ha/y : 0.91 swank and Waide, 1988. 10 ca as wetfall (rain) 10a Marine Origin Concentration of Ca in rain of marine origin, mg/l = 0.005 swank and Waide, 1988. Marine contribution, kg/ha/y = L mgll)(1.93 mIy)(1 E4 m"2Iha)(1 000Um"3)(1 kg/1 E6mg) Marine contribution, kg/ha/y = 0.097 Empower-to-flux of cyclic salts = global empower divided by total minerals transported from sea to land; (9.44E24 sejly)/{2.6E14 g-saltsfy) = 36E9 sejlg-cyclic sea salt 10b Terrestrial Origin Concentration of Ca in rain of terrestrial origin, mg/l = 0.190 Swank and Waide, 1988. Terrestrial contribution, kglha/y = (0.190 mg/I)x(1.93 m/y)x (1 E4m"2Iha)x(1 000Um"3)x{1 kg/1 E6mg) Terrestrial contribution, kglha/y = 3.7 Emergy per gram is mean for global sedimentary-rock cycle 11 ca from rock weathering Majority of rock weathered is calcium feldspar (molecular wt. 1064 of which 40 is Cal Thus, Ca is 40/1064 of 482 kglha/y = 18 12 Total Net Primary Prod. (NPP) Annual NPP per ha = 14.6 MlMonkand DaY,1988. Energy(J) = ( MT)(1 E+06 gtMT)(3.5kcaVg)(4186 Jig) = 2.14E+11 13 NPP aboveground Annual NPP per ha = 8.4 Ml Monk and Day, 1988. ( M1)(1 E+06 g/MT)(3.5kcaVg)(4186 Jig) 1.23E+11 14 RootNPP Annual NPP per ha = 6 Ml Monk and Day, 1988. ( MT)(1 E+06 glMT)(3.5kcaVg)(4186 Jig) 8.79E+10 15 Wood Accumulation Annual accum. per ha = 4.2 Ml Monk and Day, 1988. Energy(J) = ( MT)(1 E+06 glMT)(3.5kcaVg)( 4186 Jig) = 6.1SE+10 16 liUerFail Annual litter per ha = 4.4 Ml Monk and Day, 1988. Energy(J) = ( M11(1E+06 glMT)(3.SkcaVg)(4186 Jig) = 6.4SE+10

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-1 (emergy evaluation of Coweeta watershed) 17 Leaf production Annualleat prod per ha = 42 M1 Monk and Day, 1988. ( MT)(1E+06 gJMT)(3.5kcallg)(4186 JIg) 6.15E+10 18 Rock weathering mean rate for all of Coweeta, cm/100Oy = Area, ha mean rate for WS 18, kg/haly = Mass of material = 3.8 Velbel, 1985. 1 482 Velbel, 1985. (rate,cm/y)x(area,ha)x(1 ml1 OOcm)x(1 O,000m A 2/ha)x(1.5glcm A 3)x(1 E6cm A 3/m A 3) Mass of material, g/y = 570,000 Empower necessary for rock weathering is rain plus earth deep heat. 19 calcium cycle Net annual uptake by vegetation, kg/haly = 84 Monk and Day, 1989. 180 Emergy per mass, sejlg = (input empower: sum of rain + earth cycle as deep heat + dryfall Ca + wetfall Ca)/(intemal Ca cycle) Emergy per mass, sej/g = (84.2E12 sejlhaly)/(84000 g-Ca/ha/y) 20 Total mineral cycle ______ rate, kg/ha/y Calcium 82 Potassium Magnesium Phosphorus Nitrogen Sulfur Sodium Total Source: Monk and Day, 1988. 88 21 15 156 ? ? 362 Empower of mineral cycle = (Empower input from rain + deep heat + atmospheric mineral deposition) Empower-ta-flux of mineral cycle, sej/g = L-sejlha/y)/(362 E3 g/ha/y) = 6.2 E9 sejlg EXPORTS 21 Stream discharge Runoff = 1.035 rnf.WS 18 @ Coweeta (Swift et aI., 1988) Chemical Energy(J) = <--mA2)*L-m/y)*(1000 kg/m A 3)*(4940 J/kg) Chemical Energy(J) = 5.11 E+1 0 Geopotential Energy (J) = (area)(runoff)(stream elev. above sea level)(density)(gravity) = ( mA2)L-mly)*<--m)*(10oo kg Geopotential Energy (J) = 6.37E+10 relative to sea level Runoff (g) = 1.04E+10 All calculated transformities (or empower-ta-flux): [empower of rain + deep heat11 energy (or mass) 22 CalCium export

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.181 Footnotes to Table 3-1 (emergy evaluation of Coweeta watershed) Ca export, kg/ha/y = 7 Swank and Waide, 1988. Empower-ta-flux ratio: assumed a split of internal cycle, therefore similar ratios. Empower of Ca export = (Ca export, g/ha/y) x (emergy per mass of internally cycled calcium, sejlg-Ca) 23 Total dissolved mineral export (based on WS 2) Ion Ca+ Na+ NH/ Mg2+ K+ 504 2.5 N03 -cr Total Output, kglha/y 5.45 11.43 0.02 3.05 4.66 1.37 0.02 6.18 40.4 0.02 77.25 150 Source: Swank and Waide, 1988.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-2 (emergy evaluation of Wine Spring Creek watershed) 1 SOLAR ENERGY: 1128 Forest Service 10,000 Land area of WSC, ha = Unit of analysis, m"2 = Insolation @ ground = 5.02E+09 J/m"2/yr (taken from Coweeta, Swift at al., 1988) Energy(J)= = = Larea)*(avg Insolation @ ground) (_m"2)*(_J/m"21y) 5.02E+13 2 VAPOR SATURATION DEFICIT Mean conditions transe Difference Atmos. pressure, mb 1000 1,000 Mean annual temp. C 12.6 12.6 sat. yap. press.(e.), mb 14.60 14.60 sat. mix. ratio (qs), gfkg 9.08 9.08 Evapotranspiraton (ED, g/y 5.38E+09 Air exchange, m3/y 3.75E+11 Depression of mix. ratio, g/kg 0.0120 vapor press.(e), mb 12.20 12.22 mix. ratio (q), g/kg 7.59 7.60 sat. deficit (qs-q), g/kg 1.49 1.48 sat. deficit (es-e), mb 2.39 2.37 free energy, J/kg 198.3 196.7 free energy, J/m3 238.0 236.1 Mean annual temperature at climate station CS301 in WSC basin. Saturation vapor pressure (a8), mb = 611"EXP.27*n/(237.3+D)/100 Where T is mean annual temperature, C 0.0192 0.0120 .0120 -0.02 -1.59 -1.91

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-2 (emergy evaluation of Wine Spring Creek watershed) Saturation mixing ratio, g/kg = 622x(es,mb)/(air pressure,mb) Evapotranspiration, g/y = (0.91 m/y)x(10,OOOmIl2lha)x(1E6 g/mll3) Air exchange, see Table cow-wind Depression of mix. ratio, g/kg = (ET, g/y)/(Air exchange, mIl3/y)/(1.2 kg/mll3) mix. ratio, g/kg: assumed mean annual for WSC Vapor pressure, mb = (mixing ratio, g/kg)x(alr pressure,mb)/622 sat. deficit, g/kg = sat. mix. ratio -mix. ratio sat. deficit, mb = sat. vapor pressure -vapor pressure free energy, J/kg = -8.33*(273+ T)*LN 000-qa)/(1 000-q*1 00 Free energy of air masa = (8.33 JlmoleJdeg C)x(T deg C)x (Loge-sal. mix. ratlo,glkg)/(1000-mlx. /1Itio, glkg) I (18 glmole) x (1000 glkg) Energy of the saturation deficit used, Jty = (difference In free energy, J/mA3)x(alr exchange, mA3ty) Energy of the saturation deficit used, J/y = (1.91 J/m"3)x(423 E12 m"3/y) Energy of the saturation deficit used, J/y = 7.17E+11 3 WIND ENERGY: Sec Table 0-2 Energy, Total (J)= 1. 88E+ 11 llyr Growing season only (AprilSeptember): Energy, grow season (1)= 4.81E+lO llyr Non-growing season (October-March) Energy, winter (1)= 1.04E+ll llyr 4 PRECIPITATION, GEOPOTENTIAL ENERGY: Hi-Wayah Bald La-Nanla. Lake Area Rainfall Runoff = Elevation = 1839 1625 Mean elev. determined from GIS topo-coverage 1697 920 Mean 10000 1961 1423 1318 mA2 mm mm m .... 00 w

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-2 (emergy evaluation of Wine Spring Creek watershed) Energy @ mean elev. (1) = (area)(runoft)(mean elev -min elev)(dcnsity)(gravity) <-m"2)*<-mmly)/(IOOO mmlm)*<-m)*(lOOO kg m,3)*(9.8m1s"2) Energy, geopotential (J) = 55.5E+9 5 HURRICANES Energy, J/event = Energy, J/y = 5.22E+ 11 (see Table Hurricane estimate) 5.22E+IO 6 PRECIPITATION, CHEMICAL POTENTIAL ENERGY: Rain @ 925 10 = 1,697 mm/YI Forest Service (long term) Rain@ 133010 = 1,961 nunlYlForest Service (1995-1997) Rain@ 162510 = 1,839 mm/YIForest Service (long term) Mean E-T = 538 mm/YIForest Service (1995-1997) Total energy assuming rainfall @ 1330rn (J )= (area)(rainfall)(Gibbs no.) = <-m"2)*<--mm)/(1000 mmlrn)*(1000 kg/m"3)*(4940 J/kg) = 9.69E+I0 Total energy (1) = 9.69E+lO 7 EVAPOTRANSPIRATION, Mean E-T = 538 mmly CS30lt (pers. comm. L. Swift, Coweeta) Total energy assuming rainfall @ 1330rn (J )= (area)(evapotranspiration)(Gibbs no.) = <-m"2)*<--mrn)/(1000 mmlm)*(1000 kg/m"3)*(4940 J/kg) Total energy (J) = 2.66E+ 10 8 DEEP HEAT (1) Land Area (10"2) = 1.00E+04 Heat flow 1 Area = l.36E+06 J/m"2ly, @ Bryson City, NC Energy (J) = l.36E+IO (Smith et al., 1981; in Pollack et al., 1991). Transfonnity, 34,400 sej/J was the mean calculated for the continents by Odum, 1996. If deep heat figured as a function of altitude. Transformity, 75.000 sejlJ based on height of geologic uplift (Appendix E) 9 ATMOSPHERIC DEPOSITION -

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-2 (emergy evaluation of Wine Spring Creek watershed) Deposition rate, kglhaly = 30 30 estimate based on Coweeta (see Table IMPORTED ENERGY SOURCES: 10 Gasoline of visitors Gas within WSC = Energy(J) = Energy(J/ha) = II Gasoline of thm traffic Gas witbin WSC;;; Energy(J) = Energy(Jlha) = 3.70E+OI (bbVyr) ( _bbVyr)*(6.28e9 Jlbbl) 2.06E+08 3.70E+02 (bbVyr) ( __ bbVyr)*(6.28e9 Jlbbl) 2.06E+09 Table wsc3 Table wsc3 ]2 Visitors, length of stay in WSC Cordell et aI., 1996. no. of groups/yr = 4,361 mean group size = 2.7 people mean length of stay = 19.0 bours Energy(J) = CaVhr)*(4186 J/Cal) Energy(Jlha) = 8.63E+07 Transforrnity of 8,900,000 sej/J is the avg. for a U.S. citizen during avg. day. 13 TIMBERING Services Revenue from timber sales from 1973-1999 (26y) was $250,000 (Wayah Ranger District, B. CuUpepper). Revenue, $lhaly;;; 8.5 Fuels U.S. National average: 23 El5 J/y to harvest 648 E6 mA3 of wood (see Table wood-log) U.S. National average IlmA3= 3. 55E+07 Fuel use in WSC timbering, J/haly = (harvest, m"3Ihaly)x(3.55E7 J/mA) Fuel use in WSC timbering, J/haly = 1. 56E+07 ]4 ROAD MAINTENANCE Length of unpaved roads = 24 km (GIS database) .-00 I.Jl

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-2 (emergy evaluation of Wine Spring Creek watershed) Length of paved roads = 9 km (GIS database, FS 711) Cost to maintain roads 5,000 S/milely (Bill Culpepper, FS Silviculturalist, Wayah Ranger District) Cost of rd, Sly = (length of rds, km)x(S5000/mile/y)x(l milell.609 km) Cost afro, Sly = 9.98E+04 Cost, Slbaly = 8.84E+Ol 15 FOREST SERVICE MANAGEMENT Wayah Ranger District budget, $/y Area of Wayah R.D., ha Slba/y = 16 RESEARCH EFFORT 750000 56000 13 At least 52 forest scientist, forest managers, university scientists and graduate students worked on the WSC Ecosystem Project from 1992-99. Assume they devoted 10% of their total work per year to gathering, analY71ng, publishing and sharing their research efforts. Effort, hr/y = 1.04E+04 Energy (Jlba) = <---People-hrs/yr)"'(I04 Cal/hr)"'(4186 J/Cal)/(1l28 ha) Energy (Jlba) = 4.01E+06 Transformity: post -college educated person (Odum 1996) INTERNAL PROCESSES 17 NET PRODUCTION OF LIVE BIOMASS Roots+wood+leaves Energy(J) = 14390 kglha/y; @ Coweeta Hydrologic Laboratory; Monk and Day, 1977,. (NPP,kglhaly)x(area, ha)(lOOO glkg)(3.5 kcal/g-dry wt)(4186 J/kcal) 2. 11 E+ 11 Transformity = (empower of evapotranspiration + deep heat + atmos. dep.) / (net production) 18 WOOD ACCUMULATION RATE Net accumulation 4.20E+03 kg/ha/y; @ Coweeta Hydrologic Laboratory; Monk and Day, 1977,. Energy(J) = (net accum.,kglha/y)x(area, ha)(1000 glkg)(3.5 kcal/g-dry wt)(4186 J/kcal) 6.15E+1O

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-2 (emergy evaluation of Wine Spring Creek watershed) Transformity = (empower of evapotranspiration + deep heat + atmos. dep.) I (wood accumulation) 19 LITTERF ALL Net accumulation 4.40E+03 kg ha Avg. 1984-89. US Forest Service, 1990. Energy(J) = (Litterfall,kglhaly)x(area, ha)(I000 g/kg)(3.5 kcallg-dry wt)(4186 Jlkcal) = 6.4SE+IO Transfonnity = (empower of evapotranspiration + deep heat + atmos. dep.) I (litterfall) 20 ROCK WEA mERINO Erosion rate, glm"2/y = 60 Velbel, 1988. Sediment lost, glhaly 6.00E+05 (sej/g) = (empower ofrain+deep heat+atmos. dep.) I (weathering rate) 21 TREE DIVERSITY From the species-area curve, there were 30 species found within the first ha sampled. See Figure _. EXPORTS 22 Stream discharge Runoff = Chemical Energy(J) = Chemical Energy(J) = Chemical Energy (Jlba) = 1.42 mly mean 1995-96. Source: Coweeta Hydro. Lab L-m"2)*L-m/y)*(1000 kglm"3)*(4940 Jlkg) 7.03E+I0 Available geopotential energy (J) = (area)(runofi)(stream mouth elev above sea level)(density)(gravity) = L-m"2)L-mly)"'L-m)"'(1000 kg m-1)"'(9.8m1s"2) Oeopotential Energy (J) = 1.26E+ 11 relative to sea level Runoff (g) = 1.42E+I0 All transformities: (empower of rain + deep heat] I energy (or mass) 23 TIMBER EXTRACTION Since 1973 (26 y), timber harvest from WSC watershed was 8623 m"3 sawtimber and 4259 m"3 of round wood, valued at $251,000 (Wayah Ranger District, courtesy or Bill Culpepper) -

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-2 (emergy evaluation of Wine Spring Creek watershed) Timber harvest rate, m"3lbaly = 0.44 Energy(J) = (m"3)*(5 E5 glm"3)*(4.5 KcaVg) *(4 186 IICal) Energy(J) = 4.14E+09 Energy (Jlba) = 4.l4E+09 Transformity of timber before hanrest was based on simulation with EMERGYDYN for wood in Coweeta WS 18 (see Table 3-4) Timber with services: senrices added were road maintenance, FS management, and timbering fuels and services. Transformity of timber after harvest was emergy/energy 24 RECREATED PEOPLE Same energy as visitor's length ofstay above (#24) Transfonnity = [sum of empower inputs I[metabolism of visitors during length of stayJ Empower inputs were sum of environmental and economic Environmental inputs were taken as half the annual flow of rain+deepheat+atmospheric deposition since the main road is only opened from Apr. to Nov. Economic inputs were sum of auto-fuel use, visiting time, road maintenance, and Forest Service management. 25 RESEARCH INFORMATION From 1992 to 1998, 47 publications and 10 reports were produced (Swank 1999) Publication rate over the six years was 57 16 = 9.5 pubslyr Publications average 10 pages in length Page weighs 1 gram Grams of research articles published, gly = 9.5 articlesly x 10 pages x I glpage Grams of research articles published, gly = 95 Energy of articles, J/y = grams x 3.5 kcaVg x 4186 J/kcal Energy of articles, J/y = 1.39E+06 Energy of articles, Jlba/y = 1,234 Transfonllity = (sum of empower inputs (rain, deepheat, atmospheric deposition, road maintenance, Forest Service management, and research eft'ort)]l(energy of publications, annual rate] 26 Total Export Total export was rain + deep heat + atmos. deposition + all imported sources (items 10-18) roo 00

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-4 (emergy of watershed storages) 1 Soil moisture Soli water in S.2m soil = 1.46 m Helvey and Patric, 1988. Depth of saprolite, m 6.1 Douglass and Swank, 1975. Cubic meters per ha = 17127 Water chemical potential available (J) = (area)(ralnfa")(denslty of water)(Glbbs no.) = L-,mA3(1000 kg/m"3)*(4940 J/kg) = 8.46E+10 Emergy stored (sej) = (Accumulaton period of 2 y) x (annual empower: rain + deepheat, sej/y). 2 Wood Wood stored per ha = 295 MT from model EMERGYDYN Energy(J) = L-MT)(1E+06 glMT)(19,200 Jig DW) = 5.66E+12 Emergy stored (sej) = 169 E15 sej/ha (based on simulation of EMERGYDYN) 3 Total Organic Matter Total OM stored per ha = 1660 MT from model EMERGYDYN L-MT)(1 E+06 glMT)(19,200 Jig DW) 3.19E+13 Emergy stored (sej) = 795 E15 sej/ha (based on simulation of EMERGYDYN) 4 Calcium reserve Ca reserve In live vegetation, kg/ha = 830 Monk and Day, 1989. 620 Monk and Day, 1989. Ca reserve in soil (extractable) and litter, kg/ha = Emergy stored (sej) = (Accumulaton period of 200 y) x (annual empower: transplratlon+deepheat+ atmospheric deposition, sej/y). 5 Saprolite Depth of saprolite, m Per ha, m3 = 6.1 Douglass and Swank, 1975. 61000 .... 00 \0

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-4 (cmergy of watershed storages) Density of sapr., g/cm"3 = 1.5 Mass of saprolite = (vol., m"3)x(1 E6cm"3/rn"3)x(1.5 g/cm"3) Mass of saprolite = 91.5E+9 Emergy stored (sej) = 3.6 E20 sej/ha (based on simulation of EMERGYDYN) 6 Tree species Eliott and Hewitt (1997) observed 32 tree species in 3.5 ha at altitude> 1200m. Based on simulations with EMSPECIES, .... 70 tree species existed In the whole watershed, an average of 0.0621 specleslha. Emergy accumulated based on EMSPECIES, was 2.6 E24 sej for 1128 ha or 2.31 E21 sej/ha. STOP HERE 7 Forest tree bits Based on EMSPECIES, 1763 bits (42 tree species) existed at 3.5 ha or 500 blts/ha. Emergy accumulated based on EMSPECIES, was 131 E21 sej for 3.5 ha or 37.5 E21 sej/ha. 7 Forest tree bits 500 bits 4.6E+lS 2,300,000 2.lE+09 -

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.191 Footnotes to Table 3-7 (emergy evaluation of Macon County. N.C.) 1 SOLAR ENERGY: Land Area = 1.34E+09 ml\2 (US Statistical Abstract 1995) Insolation @ Atmos = 6.31 E+09 J/ml\2/yr (Barry & Chorley, 1992, p. 23) Albedo 0.15 fraction absorbed at surface (Barry & Chorley. 1992. p. 23) 3. 15E+07 7.12E+09 225.65322 Energy(1)= (area inel sheIf)*(avg insolation)*(I-aIbedo) <-m"2)*<"-J/m"2Iy)*(I-aIbedo) 7. 18E+l8 2 RAIN USED, CHEMICAL POTENTIAL ENERGY USED IN TRANSPIRATION: Land Area 1.34E+09 ml\2 Rain (land) = 135 mIyr Water Information Center. 1973. Transpiration rate= 0.90 mIyr Energy (land) (1)= (area)(transpiration)(Gibbs no.) <-mI\2)*L-m)*(IOOO kg/m"3)*(4940 J/kg) Total energy (1) = 5.96E+ 15 3 GEOPOTENTIAL ENERGY in RAIN USED: (US Statistical Absttact 1995) Water Information Center. 1973. Area (m"2) Rainfall (mIy) Avg EIev (m) = Runoff(mIy) = County L34E+09 1.35 340.00 0.45 From digital USGS 'OEM' coverages wI ARCview Water Information Center. 1973. Energy(J)= 4 WIND ENERGY: Area, ml\2 = (area)(runofl)(avg elevation)( density)(gravity) <-m"2)*L-mly)*<-m)*(I000 kg m-3)*(9.8m1sI\2) 2_01E+15 Jan. Apr July L34E+09 Oct a Eddy Diffusion. m"2/s = 1.38 3.33 3.25 LIS a Vertical Gradient,mlslm = 0.0104 0.0069 0.0025 0.0037 (1000 m)(1.23 kglm"3)(Eddy diffusion m"2/s)(7.884.000 seclQtr-yr)(Velocity Grad mlslm)2(area mJ\2) Energy/Qtr. (1)= L93E+l5 2.05E+15 2.56E+14 2.05E+14 Energy, Total (J1y)= 4.43E+lS J/yr B For Macon county, from Swaney, 1978. WIND ENERGY ACCORDING TO "PROFILE MEmOD" (see Table G-3) Energy, Total (1)= 2.56E+l6 J/yr 5 VAPOR SATURATION DEFICIT Atmos. pressure, mt: Mean annual temp. ( Mean conditions 1000 12.6 Effects of ET Difference 1,000 12.6

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-7 (emergy evaluation of Macon County, N.C.) sat. vap. press.(eJ, I 14.60 14.60 sat. mix. ratio (QJ, g. 9.08 9.08 Evapotranspiraton (ET), gJy 1.21E+15 Air exchange, m3/y 5.05E+16 Depression of mix. ratio, gJkg 0.0199 vapor press. (e) mb 12.20 12.23 0.0320 mix. ratio (Q), gJkg 7.59 7.61 0.0199 sat. deficit (Qs-Q), 1.49 1.47 -0.0199 sat. deficit (es-e), mt 2.39 2.36 -0.03 free energy, J/kg 198.3 195.7 -2.65 free J/m3 238.0 234.8 -3.18 Mean annual temperature at climate station CS01 in Coweeta basin. Saturation vapor pressure (eJ, mb = 611*EXP.27*T)/(237.3+n)/100 Where T is mean annual temperature, C Saturation mixing ratio, g/kg = 622x(es,mb)/(air pressure,mb) Evapotranspiration, g/y = (0.91 m/y)x(1 O,OOOmA2Iha)x(1 E6 g/m"3) Air exchange, see Table cow-wind Depression of mix. ratio, g/kg = (ET, g/y)/{Air exchange, m"3/y)/(1.2 kg/mA3) mix. ratio, g/kg is mean annual for CS01 Vapor pressure, mb = (mixing ratio, g/kg)x(air pressure,mb)/622 sat. deficit, g/kg = sat. mix. ratio -mix. ratio sat. deficit, mb = sat. vapor pressure -vapor pressure free energy, Jlkg = -8.33*(273+n*lN-qJ/(1000-q)/18*100 Free energy of air mass = (8.33 Jimoleideg C)x(T deg C)x (Loge-sat. mix. ratio,g/kg)l(10Q0.mix. ratio, g/kg) I (18 g/moIe) x (1000 g/kg) Energy of the saturation deficit used, J/y = (difference in free energy, J/rn-'3)x(air exchange. rn-'3Iy) Energy of the saturation deficit used, J/y = L-J/m"3)xL mA3/y) Energy of the saturation deficit used, JIy' 1.61 E+17 6 mSTORIC EROSIONAL LOSSES (based on forested land) Annual erosion rate from forested land in Southern App., = IS g/m1\2 (Simmons, 1993.) Loss (g!y) = (Area, mA2)x(erosion rate, g/mI\2Iy) Loss (g/y) = 2.0IE+I0 7 GEOLOGIC UPLIFT Land Area (mA2) = Uplift (cm/lOOOyr)= Height of Uplift,m= Uplift (J1yr)= Uplift (J1yr)= 1.34E+09 Isostatic uplift from denudation rate 4.0 of Southern Appalachians (Hack, 1980). 940 (uplift cmllOOOy)x(2.6 g/cmA3)x(area mA2)x(lmllOOcm)x (Ie6cmA3/m"3)x(0.5)x(ht. of uplift m)x(gravity, 9.8m1sI\2) 6.42E+14 192

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-7 (emergy evaluation of Macon County. N.C.) 8 DEEPHEAT Land Area (mI\2) = Heat flow I Area = 1. 34E+09 1.36E+06 Ilml\2Iy. @ Bryson City. NC 193 (Smith et al 1981; in Pollack et al., 1991: Energy(J) = Energy(J) = (heat flow/area)x(land area) 1.82E+15 INDIGENOUS RENEWABLE ENERGY 9 HYDROELECTRICITY: Kilowatt HrsIyr = Energy(J) = Energy(J) = 2.45E+08 Federal Energy Regulatory Commission, 1981. ( _kWh!yr)*(3606e3 IIkWh) 8.85E+14 10 TOTAL ELECTRICITY USE: Kilowatt HrsIyr = (39.650 kWhlhoushold in NC)x(9843 Households in Macon) Kilowatt HrsIyr = 3.90E+08 kWhlyr (1992) Energy(J) = ( _kWh!yr)*(3606e3 IIkWh) Energy(J) = 1.41E+15 11 AGRICULTURAL PRODUCTION: Ag. Prod 26,337 MT (1992 Census of Agriculture, NC.) Energy(J) = ( MT)*(1E06 gIM1)*(3.5 KcaJlg)*(4186 IICal) Energy(J) = 3.86E+l4 12 LIVESTOCK PRODUCTION: L'stock Prod = 2,285 MT (Cattle Sold., 1992 Census of Agriculture, NC.) Cattle Sold x 1550 IbsIcattle Energy'(J) = '--MT)*(IE+06 gIM1)*(2.82 CalIg)*(4186 J/Cal) 2.70E+13 13 Forest Growth New Growth = 4.42E+05 ml\3 1983-89. USFS, 1990. Energy(J) = L-mI\3)(lE+06 glmI\3)(0.5 g dry wt/g green wt)(l9,200 JIg dry wt) 4.25E+15 Transformity for annual wood growt at WS18 (see Table 3-1) 14 FOREST EXIRACTION Harvest l.S3E+OS ml\3 Avg. 1983-89. Forest statistics of North Carolina, 1990. Energy(J)= L-mI\3)(IE+06 glm"3)(0.S g dry wt/g green wt)(19,200 11g dry wt) 1.47E+lS

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-7 (emergy evaluation of Macon County, N.C.) Transformity for wood at WS18 (see Table 3-4) 15 FUELWOOD USE: Use, J/y 2.S7E+ 14 (see Table Energy(J) = 2.87E+14 NONRENEWABLE RESOURCE USE WITHIN MACON COUNTY 16 PRESENT EROSIONAL LOSSES 194 Annual sediment yield in Little Tennessee River = 80 glm"2 (Simmons. 1993.) Loss (g/y) = (Area. m"2)x(erosion rate, glm"2/y) Loss (g/y) = L07E+ 11 17 GEMSTONES PRODUCTION Production (Sly) = $ 50,000 (Minerals Yearbook, 1983, U.S.Dept. of Interior) IS NON-FUEL MINERALS PRODUCTION Production, 19S1 ($) = 1,406,000 (Minerals Yearbook, 1983, U.S.Dept. of Interior) Price,I981 (SIMT) = 4 Production = 3.52E+OS MT/yr Quantity (g) = (MTIy)*(lE6 g!MT) 3.52E+lI IMPORTS OF OUTSIDE ENERGY SOURCES: 19 PETROLEUM PRODUCTS Imports of oil prod = 1.96E+lS J/y (see Table Mac-fuel) Energy(J) = 1.96E+15 20 NATURALGAS Inconsequential amount. if any, used in county 21 COAL: None used in county 22 ELECTRICITY IMPORTED Imports = Consmnption minus Production Cons, JIy = L41E+l5 Prod., J/y = 8.8SE+l4 Imports, JIy = 5.22E+l4 23 LIVESTOCK Imports Energy(J) = 24 NET IMMIGRATION (IE5 MTIyr)*(IE6 g!MT)*(4 KcalIg)*(4186 J/Kcal)*(.22 protein) O.OOE+OO

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.195 Footnotes to Table 3-7 (emergy evaluation of Macon County. N.C.) Immigration = 503 peoplelyr. 1990-95. (U.S Census Bureau:countyprofiles. 1996) Energy/person = 3.82E+09 JIy. energy expended per individual per day = 2500 CalId Energy(J) = <-PeoP1eIyr)*(2SOO CaIld)*(4186 J/Cal)*(365 daysIyr) I.92E+l2 25 MACHINERY. TRANSPORTATION. EQUIPMENT Auto & truck registered 20000 Assume lifetime = lOy and replacements balance losses. Purchases 2.00E+03 autos per year Mass (g) = Mf/auto)*(lE6g1M1) 26 WOOD Imports = Energy(J) = = 3.00E+09 O.OOE+OO m"3 m"3)(lE+{)6 glm"3)(0.5 g dry wt/g green wt)(19.200 J/g dry wt) O.OOE+OO 27 FEDERAL GOVERNMENT Personal Income. Sly: 2.58E+08 Assume 15% of Income paid in taxes and payout = payin. 3.87E+07 28 IMPORTS OTIIER mAN TOURISM Household Income.SIy 258.0E+6 (US Census Bureau. 1996) Co. Incomelm"2 = 0.192537 497.1E+3 $/mi"2 Import $'s were proportional to income density (see M.T. Brown. 1980). Dollar Value of non-tourism imports = total imports less tourism Dollar Value of non-tourism imports = $25,800,000 29 TOURISM (input of tourist's time) Tourism to Macon Co. was based on extrapolating observed visitation rate to Wine Spring Creek Visitation rate to WSC was 224.000 tourist-hrs in one year (1995-96. see Table WSC-tour). Area of WSC. ha = 1.128 Visitation rate per ha = 198.6 tourist-hrsIyearlhectare Estimated visitation to Macon co hours/year = (134.000 ha)x(198.6 visitor-hrlhaly) visitor-hrly = 2.66E+07 Eacru. JIy -(viHnIy)x(100Ia:aIIIIr)x(411611b:a1) EDeru. J/y = I.IIE+l3 30 TOURISM (support of employment) Number __ n:IID:d jolla ia MII:OD Co. 2000 {ED&IiIII 199'>. "-_ per c.piIa pcnoaaI ia taarism cq;IIIIed ovcnIIlIICIIII rtr M&:OIl Co ..... mcc.ac.Sfpc:I_/p $16.303 (NC Dept of Commerce 1996) Tourism Income in Macon. $Iy = $32.606.000 EXPORTS OF ENERGY, MATERIALS AND SERVICES 31 TOBACCO

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-7 (emergy evaluation of Macon County, N.C.) Tobacco TOTAL Energy(J) = 6.00E+Ol MI' (NC Census of Ag., 1992) 6.00E+Ol MI' ( MfIy)*(lE+06 gIMI)*(3.5 CaIlg)* (4186 J/Cal) 8.79E+ll 32 WOODIWOOD PRODUCTS: Fuelwood use = 2.87E+14 J/y Other use = (23,500 people) x (NC uselperson, 28.6E9 J/y) Other use = 6.721E+14 J/y Production = 1.47E+15 J/y Consumption = fuelwood + Other use Exports = Prod Cons = 507.6E+ 12 J/y Energy(J/y) = 5.08E+14 33 LIVESTOCK: Est. consumption = Production = Exports = Prod Cons Exports: Energy(J) = 34 MINERALS: Cons. per Capita = Consumption = Exports Energy (g) 469 MI' Est. meanNC per capita cons (44lbs) x population 2,285 MI' 1,816 MI' L-MfIyr)(lE6 gIMT)(4 KcaVg)(4186 J/Cal)(.22 protein) 6.69E+12 3.25 MI'/person, U.S. avg. 1995 (US Bureau of Mines) 76375 MI' Assume export = prod less consumption. 2. 75E+05 L-MT)*(lE6 gIMT) 2. 75E+ll 35 SERVICES IN EXPORTS: Gross State Prod. = Dollar Value = 36 FEDERAL GOVERNMENT Assume $ paid to federal gov't equal $ received from fed. gov't O.OOE+OO O.OOE+OO Imported monies must balance exported monies. 196

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.197 Footnotes to Table 3-9 (emergy evaluation of North Carolina) 1 SOLAR ENERGY: Cont Shlf Area = 2.5E+ 10 mJ\2 at ISO m dpth., (est-from Goode's World Atlas. 1990). Land Area 1.36E+ll mJ\2 (US Statistical Abstract 1995) Insolation @ Atmos 6.3IE+09 IlmJ\2Iyr (Barry & Chorley, 1992, p. 23) Albedo O.IS fraction absorbed at surface (Barry & Chorley, 1992. p. 23) 3. 15E+07 Energy(J)= (area inel sheIf)*(avg insolation)*(l-albedo) L-mJ\2)*L-J/mJ\2/y)*(I-albedo) 8.65E+20 2 RAIN, CHEMICAL POTENTIAL ENERGY: Land Area 1.36E+11 mJ\2 (US Statistical Abstract 1995) Cont Shlf Area = 2.SOE+I0 mJ\2 ISO (est-from Goode's World Atlas, 1990). 3 Rain (land) = 1.27 mIyr Water Atlas of U.S., 1973. Rain (shelf) = 0.9S mIyr (esL as 75% of tot. rain) Evapotrans rate= 0.84 mIyr Water Atlas of U.S 1973. Energy (land) (1)= (area)(rainfall)(Gibbs no.) L-m"2)*L-m)*(I000 kglm"3)*(4940 I/kg) 8.56E+l7 Energy (shIt) (1)= (area of shelf)(Rainfall)(Gibbs no.) = 1. I 8E+l 7 Total energy(J) = 9.74E+l7 RAIN, GEOPOTENTIAL ENERGY: State a Mountainsb Piedmontb Area. m2 1.26E+ll 17.3E+9 5S.3E+9 RainfaI1 mIy = 1.27 1.397 1.143 AvgElev., m = 214.00 1000 150 MinElev., m = 0.00 600 10 Runoff rate, mIy = 0.43 1 0.4 Energy(J)= 1. 14E+17 6.77E+16 3.03E+l6 a-US Statistical Abstract 1995, b-US Census Bureau, 21 Co. a.b-Water Atlas of U.S 1973. Water Information Center Publication. a.bUSGS, Elevations & Distances in U.S., 1990, 1983. Water Atlas of U.S 1973. Water Information Center Publication. Energy(J)= (area)(mnoff)(avg elevation)(densily)(gravity) Coastal Plain 53.7E+9 1.2192 10 0 0.4 2.11E+l5 L-mJ\2)*L-mIy)*L-m)*(I000 kg 4 WIND ENERGY: Jan. Apr Area. m"2 1.36E+ll 1.36E+ll Eddy Diffilsion. m"21s = 1.38 3.33 Vertical Gradient,mlslm = 0.0104 0,(>069 Eddy Diffusion and Vertical Gradient from Swaney, 1978. July 1.36E+ll 3.25 0.0025 Oct 1.36E+ll LIS 0.0037

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.19S Footnotes to Table 3-9 (emergy evaluation of North Carolina) Energy/Qtr. (1) = (lOOO m)(l.23 kg/m"3)(Eddy diffusion m"21s)(7,S84,OOO seclQtr-yr)(Velocity Grad m/slm)2(area m"2) Energy/Qtr. (1)= 1.%E+17 2.09E+17 2.60E+l6 2.0SE+16 Energy, Total (1)= 4.5IE+17 JIyr WIND ENERGY ACCORDING TO "PROFILE METHOD" (see Table D-4) Energy, Total (1)= 5.4IE+ IS JIyr 5 SATURATION DEFICIT Volume ofair passing thm a lOOOm tall prism over NC (see Table D-4) Air flux. m3/y = 6.55E+ IS Water evapotranspired (see Rain, Chemical energy above) Mass of water, g/y = l.15E+17 Increase in e (vapor pressure) is therefore (mass of water)/(air fln.x) Assume that increase in e corresponds to commensurate decrease in vapor saturation deficit (d = es -e) Decrease in d, g/m3 = 0.02 Energy of d, J/kg-air = (S.33 J/mol/K)x(300 IQ/(lSg/molwater)x(lOOOglkg)x[log..(lOOO-eJ/(lOOO-eI) -Energy of d, J/kg-air 2.05 t;, glkg = 16.50 -LNIOOO-C135)/(lOOO-C136+(C1321l.2))) eh glkg = 13.40 Energy used., J/y = energy of d. Jlkg)x(1.2kg/m3)x(air flux, m3/y) Energy used. J/y= 1.61E+l9 6 HURRICANES One hurricane every 4 yrs (NOAA. 1989); energy per hnrricane = 9.6E15kcalIday (Hughes, 1952), 3% kinetic, 10% delivered to surface system; mean dmation = one day. Energylyr = (9.6e15 kcalld) x (0.03) x (0.10) x ( 4186 JIkcal) x (1/4) x (I d) Energy(J)= 3.0IE+16 7 WAVEENERGY: Shore lmIgth = velocity = 5.07E+05 m NCDEHNR, 1992. [(gravity)(gauge depth)]" 112 velocity, m1s = 1.4 estimated Energy(J)=(shorelength., m) x 118 x (seawater density, kg/m"3) x (gravity, Energy(J)= 1.80E+16 8 TIDAL ENERGY: Cont Shlf Area = Avg Tide Range = Density = Tideslyear = Percent absorbed = 2.50E+IO m"2 150 m, (est from Goode's World Atlas, 1990). 1.10 m USGS, 1985. 1,025 kg/ml\3 706 (estimated 2 tides/24.83 hr in one year) 100/0 estimated

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-9 (emergy evaluation of North Carolina) Energy (J) on Shelf=(sheIf)(O.S)(tidesly)(mean tidal range)2(density of Energy (J) on Shelf = Lm"2)*(0.5)*LIyr)*Lm)"2*L-kglm"3)L%)*(9.8 m/s"2) Energy (J) on Shelf= L07E+16 Estuarine area = 7. 99E+09 (NCDEHNR, 1992.) Percent absorbed = 75% estimated Estuarine Tidal Range = 0.15 m USGS, 1985. Energy (J) in Estuary = (estuarine area,m2)(O.5)(tidesly)(mean tidal range)2(density of Energy (J), Estuary = 4. 78E+ 14 Total tide energy = L 12E+ 16 9 DEEPHEAT Land Area (m"2) = L36E+ll Heat flow I Area = L58E+06 J/m"2/y, averaged from data in Pollock et aI., 199L Energy, J/y = 2. 16E+17 Land Area ofMtn (m"2) = L73E+I0 EnergyofMtn,J/y= 2.73E+16 10 HISTORIC LOSS OF SEDIMENTS VIA RIVERS Historic loss was estimated based on a t( Mean rate of sediment yield from forested basins in NC = 10.1 glm"2/y Historic loss = 1.38E+ 12 gIy INDIGENOUS RENEWABLE ENERGY 11 HYDROELECTRICITY: KilowattHrslyr= 5.81E+09 kWlll (1992, US Statistical Abstract, 1995) Energy(J) = ( _kWblyr)*(3606e3 JIkWh) Energy(J) = 2.09E+16 12 AGRICULTURAL PRODUCTION: Ag. Prod 5.73E+06 MT (1992 Census of Agriculture, NC.) Energy(J) = ( MT)*(IE06 g!MT)*(3.5 KcaUg)*(4186 IICal) Energy(J) = 8.40E+I6 13 LIVESTOCK. PRODUCTION: L'stock: Prod = 2,577,000 MT (1992 Census of Agriculture, NC.) Energy(J) = L MT)*(1 E6 g!MT)*(0.22 meatllive wt)(4.0 Cal/g)*(4186 IICal) 199

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-9 (emergy evaluation of North Carolina) 9.49E+15 Caloric content used is average oft>eet: porle,. poultry. 14 FISHERIES PRODUCTION: Fish Catch = 74.8E+3 MT 1993, (National Marine Fisheries Service, 1995) Energy(J) = 15 FOREST GROWTH L MT)*(1 E6 gfMT)*(O.22 meatJlive wt)(4.0 CalIg)*(4186 J/Cal) 2.50E+14 200 4.95E+07 m"3 1983-89. Forest statistics of North Carolina, 1990 USFS. Energy(J) = <-m"3)(1E+06 glm"3)(0.5 g dry wt/g green wt)(l9,200 Jig dry wt) 4.75E+l7 Transformity: (see Table 3-12) 16 FOREST EXTRACTION Harvest 3.87E+07 m"3 1983-89. Forest statistics of North Carolina, 1990. USFS Energy(J) = <-m"3)(1E+% glm"3)(0.5 g dry wt/g green wt)(l9,200 Jig dry wt) 3.72E+17 Transformity from Table 3-1 17 FUELWOOD USE: Use Energy(J) = 3.03E+06 m"3 Avg. 1984-89. US Forest Service, 1990. <-m"3)(lE+% glm"3)(O.5 g dry wt/g green wt)(19,200 Jig dry wt) 2.91E+16 18 DIRECTWATERUSE Tot Cons., MGD = Energy (J1y) = Energy (J1y) = 390 US Stat Abstract 1995 MGDx(365d1y)x(3.785E-3m"3/gal)x(5e6J/m"3) 2.69E+15 NONRENEWABLE RESOURCE USE WITHIN NORTH CAROLINA 19 PHOSPHATE ROCK Production 5.50E+06 MT (U.S.Bureau of Mines. 1992) Mass(g) ( MfIy)*(lE6 gIM1) 5.50E+12 20 PRESENT LOSS OF SEDIMENTS VIA RIVERS Actual loss was estimated based on integration of Simmons (1993) work. (see Table G-3.) Mean rate of sediment yield from basins in NC = 37 glm"2/y Historic loss = 5.05E+l2 gIy 21 TOTAL ELECTRICITY USE: Kilowatt Hrs/yr= 9.55E+l0 kWblyr(1992) EIA. 1992. State Energy Data Report. Energy(J) = ( _kWhlyr)*(3606e3 JIkWh)

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.201 Footnotes to Table 3-9 (emergy evaluation of North Carolina) Energy(J) = 3.44E+17 22 NON-FUEL MINERALS (clays, feldspar, sand & gravel. stone) Production = 5.61E+07 MTI} Sikich, S.W., P.A. Carpenter IIL & L.S. Wiener. 1992 Mass (g) = ( MTIy)*(IE6 gIMT) 5.61E+13 23 TOPSOIL: Soil loss on Ag. land,g/y = Soil gain on Forest Iand,g/y = Net soil gain. g/y 4.30E+13 4. 79E+ 13 4.91E+12 Energy. JIy = ( gIyr)*(0.03 organic)*(5.4 KcalIg)(4186 JlKcal) = Soil loss on Ag. land, JIy = Soil gain on Forest land. J/y = 2.92E+16 3.25E+16 IMPORTS and OUTSIDE ENERGY SOURCES: 24 Oil Deriv. Prods. imports = 1.4OE+08 (bbI/yr) (1992. US Statistical Abstract. 1995) Energy(J) = ( _bbllyr)*(6.28e9 J/bbl) 8.81E+17 25 NATURAL GAS Imports 1.81E+ll (cu. ft./yr) (1992. US Statistical Abstract. 1995) Energy(J) = ( __ cu. ft.1yr)*(1.10e6 J/cu. ft.) 1.99E+17 26 COAL: Imports 24.1 E+6 (short tonslyr) (1992. US Statistical Abstract. 1995) Energy(J) = ( _sa tonslyr)*(3.18e1O J/sh ton) 7.66E+17 27 NUCLEAR Kilowatt HrsIyr = 2.26E+ 10 kWh/yr (1992. US Statistical Abstract. 1995) Energy(J) = ( _kWhlyr)*(3606e3 JIkWh) Energy(J) = 8. 16E+16 28 LIVESTOCK Imports 64313 MTI} U.S. Census Bureau. 1998. Energy(J) = <-MfIyr)*(IE6 gIMl)*(4 KcalIg)*(4186 J/Kcal) 1.08E+15

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-9 (emergy evaluation of North Carolina) 29 AGRICULTURAL PRODUcrS Imports = 2.96E+06 Mrly Energy(J) = ( M1)*(IE06 gIMT)*(3.5 KcaJJg)*(4186 J/Cal) Energy(J) = 4.34E+16 30 NETIMMIGRATION Immigration = 6.40E+04 people1yr. avg. 1990-94. (US Statistical Abstract. 1995) 202 Energy/person = 3.S2E+09 JIy. energy expended per individual per day = 2500 CalId Energy(J) = CalId)*(41S6 J/Cal)*(365 days/}T) 2.44E+14 31 METALS U.S. Consumption. 1992. (US Statistical Abstract. 1996) Item Quantity. tE12 gIy Iron Ore and Steel Scrap 13S.9 Copper 2.S Aluminum 7.3 1.5 Sum total 150.5 N.C. consumption assumed proportional to population. i.e 2.68"/0 of US Consumption. N.C. consumption = 2.6S% of ISO.SEI2 gIy = 4.03E+ 12 32 WOOD (logs) Imports Energy(J) = 2.69E+06 ml\3 Johnson. T.G 1994. L-mJ\3)(lE+06 glmJ\3)(0.5 g dry wt/g green wt)(l9.200 Jig dry wt) 2.58E+l6 33 MACHINERY. TRANSPORTATION. EQUIPMENT Total value of U.S. shipments of machinery. transportation. electronics. and instrumentation equipment = LOSe12 Sly (US Census Bureau. 1992) Total production hours used in these industries for U.S. = 7.66E9 hrsIy. Therefore. value shipped per prod. hr = S137Ilabor-br. NC had LSIE6 surplus labor-hr in these industries based on having a consumption rate = to US average. NC import, Sly = SI371lab-hr x LSIE6 Iab-hr = 2.48E+OS 34 SERVICE IN OTHER IMPORTS Gross State Product = 160E+9 GSP/mA2 = L 17 Total DollarValueofimports = L47E+1O Dollar Value of other imports = (total value) less (value of machinery. etc) L45E+lO Imports are proportional to income density. M. T. Brown. 1980. 35 TOURISM: Dollar Value = Dollar Value = 2.13E+09 US Travel Data Center. 1996 8.51E+09 Total travel expenditures in NC. 1994. 2.BE+09 Assnme influx = 25% of state total expend.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-9 (emergy evaluation of North Carolina) 36 FEDERAL GOVERNMENT Dollar Value = 2.89E+l0 in 1994. (U.S. Statistical Abstract. 1995.) EXPORTS OF ENERGY, MATERIALS AND SERVICES 37 TOBACCO NC export = NC production less (US per capita consumption)x(NC population) Tobacco 2.60E+05 Mfl) (NC Census of Ag., 1992) Energy(J) = ( MfIy)*(IE+06 gIMf)*(3.5 CalIg)* (4186 I/Cal) 3.82E+15 38 FISHERY PRODUCTION: Exports 12.6E+3 Mf 1993, (National Marine Fisheries Service, 1995) 203 Energy(J) = ( Mf)*(lE+06 gIMf)*(4 CalIg)*(4186 IICal)(0.2 g dry/fresh) 39 LIVESTOCK: Exports: Energy(J) = 40 PHOSPHATE ROCK 4.23E+13 4.45E+05 Mfly see Table G-4 L MT/yr)(IE6 gIMf)(4.0 KcalIg)(4186 IICal) 7.46E+l5 Phosphate fertilizer use in NC Agriculture is S.10E+ 11 g Prod. Cons. = S.45E+06 Mfly S.45E+12 gIy With Ag. use = 1%, then ofproduction is exported. 41 COTTON NC export = NC production less (US per capita consumption)x(NC population) Cotton export, MTIy = 3.S5E+04 Energy(J) = ( MTIy)*(IE+06 gIMT)*(3.5 CalIg)* (4186 I/Cal) 42 CRUSHED STONE Exports Energy (g) = S.2IE+l4 Assume export = Prod -Cons.; Cons. = 2.6% orus total prod. 2.58E+07 MTIy <-MT)*(lE6 gIMf) 2.S8E+13 43 LUMBER, FURNITURE, PAPER Lambcr. funIilare .t apart baed .. sarpIIa IIbar-IIn ... ill praIucIioa ill NC. Surplus labor-hrs = Labor-hrs used in NC production less (Labor-hrs per citizen x NC pop.) Surplus labor-hrs = 220E6lab.-hrs (11.2 LHIpers)x(7E6 people); (US Census Bureau. 1992.) Surplus labor-hrsIy = 1.42E+08

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-9 (emergy evaluation of North Carolina) Emergy per labor-hour (l3E12 sejlLH), used as the "transformity," was the fuel+electricity emergy used in the U.S. wood products divided by the number of production hours woriced, thus it excluded services($). 44 SERVICES IN EXPORTS: Net Export of manufactured goods, Sly : 5.54E+IO 45 FEDERAL GOVERNMENT Assume the $ of federal outlays equaIs income (see #36) 204

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-10 (emergy evaluation of N.C. storages) 1 PHOSPHATE ROCK Phosphate Rock Reserves (MT) = %P= Reserves of phosphate (MT) = Reserves of phosphate (g) = 2 GROUNDWATER 1.00E+o9 (U.S.Bureau of Mines, 1992) 100/0 100.0E+6 1.00E+14 Area of Coastal Plain (mI\2) = 6.8E+1O 50% of State area Avg. depth of Aquifers (m) = 75 est. based on Clay et aI., 1975. Est. mean porosity = 0.1 estimated. Storage (mI\3) = 5.lE+1l Energy (1) = <--mI\3)(lE+06 gfmI\3)(4.94 JIg) Energy (1) = 2.52E+18 Transformity based on analysis by A. Buenfil (UF dissertation forth coming) 3 WOOD BIOMASS Growing Stock 9.29E+08 ml\3 205 Avg. 1983-89. Forest statistics of North Carolina, 1990. US Forest Service. Energy(1) = <--mI\3)(lE+06 gfmI\3)(0.5 g dry wt/g green wt)(l9.200 Jig dry wt) = 8.92E+18 Transformity based on analysis of Coweeta WS 18 4 TOPSOIL Forested Agriculture Area, mA2 6.5OE+10 3.20E+10 Topsoil (kg-orgJmA2) 15 (based on Coweeta soils) 7.5 (assumed 50% of forest soils) Organic Matter = Area, mA2 x __ kg/mA2 x 1000glkg x 5.4 kcaVg x 4186 Jlkcal Organic Matter,J = 2.75E+19 Transformity based on analysis of Coweeta WS 18 5 ECONOMIC ASSETS Gross State Prod. = 5o/oly depreciation Economic Assets = Economic Assets = 6 POPULATION Population = Mean age (y) = People-years = People-years = 7 SURFACE WATER 1.60E+ll $ 20 years gross state product x 20 yrs 3.2E+12 $ 7.00E+06 1994, U.S. Bureau of the Census 31 U.S. Average Population x mean age 2.17E+08 Reservoir storage (mA 3) = 7.48E+09 NCDEHNR, 1992. Energy (J) = <--mI\3)(lE+06 gfmI\3)(4.94 JIg) Energy (J) = 3.7E+16

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-13 (emergyoflogging) 1 Services Value of log shipments, $/y = 13.8E+9 (US Census Bureau 1992) Value of log shipments, $/m3 = (value ofshipments,S/y)/(log output,m3/y) Value of log shipments, $/m3 = 23.78 2 Total Wages Bureau of the Census: 1992 Economic Census:Census of Manufactures 3 Non-labor wages Non-labor wages = Total wages less production workers wages. Production workers wages = L31E+09 Non-labor wages = 3.86E+08 4 Laborhrs Hrs= L31E+08 Bureau of the Census: 1992 Economic Census:Census of Manufactures Number of Prod. Workers = 69400 40 hrs/wk x 52wk x 100kca1lhr x 4186 J/kcal Joules = 6.0426E+13 5 Capital Expenditures New expenditures = 3.76E+08 $ @ 20 year life (5%) = L88E+07 Bureau of the Census: 1992 Economic Census:Census of Manufactures 6 Biomass Harvest = 6.47E+08 m"3, 1991. 206 US Forest Service, 1994. GTR-NC-169 Energy(J) = (,-__ mJ\3)(lE+06 glm"3)(0.5 g dry wt/g green wt)(19,200 JIg dry wt) = 6.21E+18 Transformity of forest growth in NC (Table NC-forest). 7 Electricity Electricity consumed, kWh = 435.0E+6 Census Bureau, 1992. Electricity consumed, J/y = <--kWh)x(3.61E6 JIkWh) Electricity consumed, J/y = L6E+15 8 Petroleum Fuels Fuel used, Sly = Fuel used, J/y = 152.0E+6 Census Bureau, 1992. L S/y)x( 19a11S)x( Ibb1l42ga1)x( 6.28E9 Jlbbl) 22.7E+15

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.207 Footnotes to Table 3-13 (emergy of logging) 9 TlDlber Output Output of logs = Total Trees harvested x recovery rate recoverty rate = 90% assumed 10 Timber Output, transformity Transfonnity of logs = sum of 1,6-10 divided by output energy of logs. 11 Emergy/$ ratio for logs = sum of 1,6-10 divided by $ value of log shipments.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-14 (emergyofpulpwood) 1 Services Value of lumber shipments, $/y = 5.47E+9 (US Census Bureau 1992) $ value of logs, $1m3 = 23.78 (Table wood-log) $ value of logs used for lumber, $Iy = (logs for lumber, m3)x($Im3) $ value of logs used, $IY = 3.76E+09 Services = $ value of lumber sales less $ value of logs Services, $IY = 1.71 E+09 Value of pulp shipments, $IMT = (value of shipments,$Iy)/(pulp output, MT/y) $ value of pulp, $IMT = 94.41 2 Total Wages Bureau of the Census: 1992 Economic Census:Census of Manufactures 3 Non-labor wages Non-labor wages = Total wages less production workers wages. Production workers wages = 501.6E+6 $ Non-labor wages = 187.5E+6 $ Bureau of the Census: 1992 Economic Census:Census of Manufactures 4 Laborhrs Hrs = 26.3E+6 Number of Prod. Workers 12100 208 Joules = # of workers x 40 hrs/wk x 52wk x 1 OOkcallhr x 4186 Jlkcal Joules = 10.5E+12 Bureau of the Census: 1992 Economic Census:Census of Manufactures 5 Capital Expenditures New expenditures = 772.3E+6 $ @ 20 year life (5%) = 38.6E+6 Bureau of the Census: 1992 Economic Census:Census of Manufactures 6 Biomass Roundwood used for pulp = 1S8.2E+6 m"3, 1988. Ulrich, A.H., 1990. Energy(J) = ( m"3)(1 E+06 g/m"3)(0.5 g dry wt/g green wt)(19,200 JIg dry wt) = 1.52E+18 7 Electricity Kilowatt Hrs/yr = Energy(J) = Energy(J) = 8 Petroleum Petroleum use = Energy(J) = = 9 Coal Coal use = Energy(J) = = 2.54E+09 kWh/yr, 1991. EIA, 1991. ( __ kWh/yr)*(3606e3 JIkWh) 9.15E+15 4.80E+06 (bbVyr) 1991. EIA, 1991. ( __ bbVyr)*(S.28e9 Jlbbl) 3.02E+16 3.31E+OS sh. tons, 1991. EIA,1991. ( __ sh. tOnslyr)*(3.18e10 J/sh ton) 1.0SE+16

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-14 (emergy ofpuIpwood) 10 Natural Gas Natural gas use = Energy(J) = = 11 Wateruse Water use estimates from Springer, 198? (liters per M.T. produced) = Mix of production processes % of total produced, 1988 (API, 1989) 3.20E+10 cu. ft.,1991. EIA, 1991. < __ cu. ftJyr)*(1.10e6 J/cu. ft.) 3.52E+16 241,000 Kraft-dissolve pulp 53,000 Kraft-unbleached pulp 113,000 groundwood, chemimechanical pulp 99,000 groundwood, thermomechanical pulp 40,000 semichemical pulp 244,000 sulfite pulp 42.5% Kraft-dissolve pulp 34.9% Kraft-unbleached pulp 4.7% groundwood, thermomechanical pulp 5.0% groundwood, chemimechanical pulp 7.1 % semichemical pulp 2.6% sulfite pulp 3.2% other Mean = (water use of i) x (fraction of production as i) Mean water use = 144,889 litersIM.T. Water use (J) = L-MT>xLliterslMT)x(0.001 m"3I1iter)x(1 E6g/m"3)x(4940J/g) Water use (J) = 41.4E+15 12 Woodpulp output Woodpulp production = 63.8E+6 short tons, 1988. Ulrich, A.H., 1990. 209 Energy(J) = (_sh. tons/yr)x(1.0 MTI1.1 02 sh tons)x(1 E6g/MT)x(3.5kcaUg)x(4186J/kcal) = 8.4BE+17 J 13 Woodpulp output, transformity Transformity of woodpulp = sum of 1,6-11 divided by output energy of woodpulp.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.210 Footnotes to Table 3-15 (emergy of paperboard) 1 Services Value of paperboard shipments, $/y = 16.14E+9 (US Census Bureau 1992) $ value of pulp, $IMT = 94.41 (Table wood-pulp) $ value of pulp used for paperbd, $Iy = (pulp, M"Dx($IMT) $ value of pulp used, $Iy = 3.26E+09 Services = $ value of paperboard sales less $ value of pulp Services, $Iy = 1.29E+10 2 Total Wages Bureau of the Census: 1992 Economic Census:Census of Manufactures 3 Non-labor wages Non-labor wages = Total wages less production workers wages. Production workers wages = 1.5E+9 $ Non-labor wages = S01.4E+6 $ Bureau of the Census: 1992 Economic Census:Census of Manufactures 4 Laborhrs Hrs = 88.4E+6 Number of Prod. Workers 39400 employees Joules = # of workers x 40 hrslwk x 52wk x 1 OOkcallhr x 4186 Jlkcal Joules = 34.3E+12 Bureau of the Census: 1992 Economic Census:Census of Manufactures 5 capital Expenditures New expenditures = 2.0E+9 $ @ 20 year life (5%) = 102.0E+6 $ Bureau of the Census: 1992 Economic Census:Census of Manufactures S Woodpulp Woodpulp for paperbd = 31.3E+6 short tons, 1988. Ulrich, 1990. Energy(J) = (_sh. tons/yr)x(1.0 MT/1.1 02 sh tons)x(1 E6gIMT)x(3.5kcaVg)x(4186Jlkcal) = 4.1SE+17 J Transformity from Table WOod-pulp. 7 Recycled paper Waste paper recycled = 8.6E+6 short tons, 1988. Ulrich, 1990. Energy(J) = (_sh. tons/yr)x(1.0 MT/1.1 02 sh tons)x(1 E6gIMT)x(3.5kcaV9)x(4186Jlkcal) = 1.14E+17 J Assume Transformity of recycled paper is same as virgin woodpulp. 8 Electricity Kilowatt Hrs/yr = Energy(J) = Energy(J) = 1.D4E+10 kWhlyr, 1991. EIA,1991. (_kWh/yr)*(3606e3 JIkWh) 3.75E+16

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.211 Footnotes to Table 3-15 (ernergy of paperboard) 9 Petroleum Petroleum use = (paperboard Mill use of elect. per Paper Mill use of electricity, kWh) x (petroleum use by Paper Mills, bbls) Petroleum use = 4.47E+06 (bbl/yr) 1991. Est. derived from EIA, 1991 Energy(J) = ( __ bbVyr)*(6.28e9 Jlbbl) = 2.81E+16 10 Coal Coal use = (Paperboard Mill use of electricity per Paper Mill use of electricity, kWh) x (Coal use by Paper Mills, sh. tons) Coal use = Energy(J) = = 11 Natural Gas 2.74E+06 sh. tons, 1991. Est. derived from EIA, 1991. ( __ sh. tonslyr)*(3.18e10 J/sh ton) 8.72E+16 Natural gas use = (Paperboard Mill use of elect. per Paper Mill use of electricity, kWh) x (natural gas use by Paper Mills, cu. ft.) Natural gas use = 8.00E+10 cu. ft.,1991. Est. derived from EIA, 1991 Energy(J) = ( __ cu. ft.Iyr)*(1.1 0e6 J/cu. ft.) = 8.80E+16 12 Water use Water use estimates from Springer, 198? Oiters per M.T. produced) = Mix of production processes % oftotal produced, 1988 (API,1989) 53,000 Kraft-unbleached 40,000 semichemical 151,000 Kraft-bleached 30,000 recycled 47.9% Kraft-unbleached 15.9% semichemical 11.1 % Kraft-bleached 24.9% recycled Mean = (water use of i) x (fraction of production as i) Mean water use = 55,978 liters/M.T. Water use (J) = L-MT)xLliters/MT)x(0.001mA3I1iter)x(1E6glmA3)x(4940J/g) Water use (J) = 9.6E+15 12 Paperboard output Paperboard production = 38.2E+6 short tons, 1988. Ulrich, 1990. Energy(J) = (_sh. tonslyr)x(1.0 MT/1.1 02 sh tons)x(1 E6glMT)x(3.5kcaVg)x(4186Jlkcal) = 5.08E+17 J 13 Paperboard output. transformity Transformity of paperboard = sum of 1,6-12 divided by output energy of paperboard.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-16 (emergy of paper) 1 Services Value of shipments, $Iy = 32.8E+9 (US Census Bureau 1992) $ value of pulp, $JMT = 94.41 (Table wood-pulp) $ value of pulp used for paperbd, $Iy = (pulp, MT)x($lMT) $ value of pulp used, $/y = 3.26E+09 Services = $ value of paper sales less $ value of pulp Services, $/y = 2.9SE+10 2 Total Wages Bureau of the Census: 1992 Economic Census:Census of Manufactures 3 Non-labor wages Non-labor wages = Total wages less production workers wages. Production workers wages = 3.9E+9 $ Non-labor wages = 1.SE+9 $ Bureau ofthe Census: 1992 Economic Census:Census of Manufactures 4 Labor hrs Hrs= 21S.2E+6 100,400 number 212 Number of Prod. Workers Joules = Joules = # of workers x 40 hrs/wk x 52wk x 1 OOkcaUhr x 4186 J/kcal 87.4E+12 Bureau ofthe Census: 1992 Economic Census:Census of Manufactures S capital Expenditures New expenditures = 2.9E+9 $ @ 20 year life (S%) = 14S.SE+6 $ Bureau of the Census: 1992 Economic Census:Census of Manufactures 6 Woodpulp Woodpulp for paper = 31.3E+6 short tons, 1988. Ulrich, 1990. Energy(J) = (_sh. tons/yr)x(1.0 MT/1.1 02 sh tons)x(1 E6g/MT)x(3.SkcaVg)x(4186J/kcal) = 4.16E+17 J Transformity from Table wood-pulp. 7 Recycled paper Waste paper recycled = 8.SE+6 short tons, 1988. Ulrich,199O. Energy(J) = (_sh. tonslyr)x(1.0 MT/1.1 02 sh tons)x(1 E6g/MT)x(3.SkcaVg)x(4186J/kcal) = 1.14E+17 J Assume transformity of recycted paper is same as virgin woodpulp. 8 Electricity Kilowatt Hrslyr = Energy(J) = Energy(J) = 9 Petroleum Petroleum use = Energy(J) = = 3.27E+10 kWhlyr, 1991. EIA, 1991. (_kWhlyr)*(3606e3 JIkWh) 1.18E+17 1.41 E+07 (bbllyr) 1991. EIA, 1991. (_bbllyr)*(S.28e9 JlbbQ 8.8SE+16

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-16 (emergy of paper) 10 Coal Coat use = Energy(J) = = 11 Natural Gas Natural gas use = Energy(J) = = 12 Water use Water use estimates from Springer, 198? (liters per M. T. produced) = 8.63E+06 sh. tons, 1991. EtA, 1991. ( __ sh. tonslyr)*(3.18e1 0 J/sh ton) 2.7SE+17 2.S2E+11 cu. ft.,1991. EIA, 1991. ( __ cu. ftJyr)*(1.1 oeS J/cu. ft.) 2.nE+17 133,000 Kraft-bleached fine papers 91,000 groundwood-fine papers 220,000 sulfite-paper 30,000 nonintegrated-fine paper Mean = arithmetic average of above water use rates Mean water use = 118,SOO liters/M.T. Water use (J) = L-MT>xLliters/MT)x(0.OO1 mA3I1iter)x(1 E6glmA3)x(4940J/g) Water use (J):: 20.7E+1S 13 Paper output Paper production = 38.9E+6 short tons. 1988. Ulrich,1990. 213 Energy(J) :: (_sh. tons/yr)x(1.0 MT/1.1 02 sh tons)x(1 E6gIMT)x(3.Skcallg)x(4186Jlkcat) = S.17E+17 J 14 Paper output, transformity Transfonnity of paper:: sum of 1,6-12 divided by output energy of paper.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.214 Footnotes to Table 3-17 (emergyofplywood) 1 Services Hardwood veneer & plywood (SIC-2435) shipments, $ = 2.2E+09 (US Census 1992) Softwood veneer & plywood (SIC-2436) shipments, $ = 5.4E+09 $ value of logs, $1m3 = 23.78 (Table wood-log) $ value of logs used for plywood, $ly = (logs for plywood, m3)x($Im3) $ value of logs used, $IY = 1.14E+09 Services = $ value of veneer & plywood sales less $ value of logs Services, $Iy = 6.55E+09 2 Total Wages Hardwood veneer & plywood (SIC-2435) tot. wages, $ = 3.9E+08 Softwood veneer & plywood (SIC-2436) total wages, $ = 8.3E+08 Bureau of the Census: 1992 Economic Census:Census of Manufactures 3 Non-labor wages Non-labor wages = Total wages less production wol1cers wages. Hardwood V&P production wol1cers wages, $ = 285 E+6 Softwood V&P production wol1cers wages, $ = 705 E+6 Total Non-labor wages, $ = 232 E+6 Bureau of the Census: 1992 Economic Census:Census of Manufactures 4 Laborhrs Total production Hrs = 98.6E+6 Number of Prod. Workers, Hardwood V&P = 17,000 Number of Prod. Workers, Softwood V&P = 28,000 Joules = # of wol1cers x 40 hrsfwk x 52wk x 1 OOkcallhr x 4186 Jlkcal Joules = 39.2E+12 Bureau of the Census: 1992 Economic Census:Census of Manufactures 5 capital Expenditures New expenditures = 145.7E+6 $ @ 20 year life (5%) = 7.3E+6 Bureau of the Census: 1992 Economic Census:Census of Manufactures 6 Biomass Roundwood used for lumber 4.80E+07 mA3, 1988. CRB, 1993. Energy(J) = ( m"3)(1 E+06 g/mA3)(0.5 g dry wtlg green wt)(19.200 Jig dry wt) = 4.61E+17

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.215 Footnotes to Table 3-17 (emergy of plywood) 7 Electricity The use of electricity and fuels in the plywood industry is assumed to have the same distribution of use in the wood products industry. Fuel + electricity emergy of SIC-2435 & SIC-2436 = [$ value shipped (SIC-2435,-36)] x [sej (fuel+electricity) per $ shipped (SIC-24)] sej Fuel + elect. emergy used in Veneer & Plywood (SIC-2435,-36) = 1.3E+21 Distribution of fuel used in SIC-24 (lumber & wood prod'> Electricity Petroleum Coal Natural Gas Total % 74.3% 9.9% 0.8% 14.9% 100.0% sej/y 1.03E+22 1.36E+21 1.16E+20 2.06E+21 1.38E+22 Electricity use = Fuel+elect. emergy of SIC-2435,-36 x % of total SIC-24 as elect. Electricity use = 74.3% of 1.3 E21 sej Electricity use = 964.6E+18 sej 8 Petroleum Petroleum use = Fuel+elect. emergy of SIC-2435,-36 x % of total SIC-24 as petrol. Petroleum used = 9.9% of 1.3 E21 sej. Petroleum used = 128.3E+18 sej 9 Coal Coal use = Fuel + electricity emergy of SIC-2435,-36 x % of total SIC-24 as coal Coal use = 0.8% of 1.3 E21 sej Coal use = 11.0E+18 sej 10 Natural Gas Natural gas use = Fuel + electricity emergy of SIC-2435,-36 x % of total SIC-24 as N.G. Natural gas use = 14.9% of 1.3 E21 sej Natural gas use = 193.8E+18 sej 11 Plywood output Plywood production = 2.21 E+07 mA3, 1993. CRB, 1996. Energy(J) = (1.... __ mA3)(1 E+06 g/mA3)(0.5 g dry wtlg green wt}(19,200 JIg dry wt) 212.2E+15 12 Plywood output, transfonnity Transformity of plywood = sum of 1,6-10 divided by output energy of plywood.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-18 (emergy of lumber) 1 Services Value of lumber shipments, $Iy = 2.11 E+1 0 (US Census Bureau 1992) $ value of logs, $1m3 = 23.78 (Table 3-13) $ value of logs used for lumber, $Iy = (logs for lumber, m3)x($Im3) $ value of logs used, $Iy = S.67E+09 Services = $ value of lumber sales less $ value of logs Services, $Iy = 1.54E+10 2 Total Wages Bureau of the Census: 1992 Economic Census:Census of Manufactures 3 Non-labor wages Non-labor wages = Total wages less production workers wages. Production workers wages = 2.4E+9 $ Non-labor wages = 646.2E+6 $ Bureau of the Census: 1992 Economic Census:Census of Manufactures 4 Laborhrs Hrs= Number of Prod. Workers 249.1E+6 118000 216 Joules = # of workers x 40 hrs/wk x 52wk x 1 OOkcaUhr x 4186 Jlkcal Joules = 102.7E+12 Bureau of the Census: 1992 Economic Census:Census of Manufactures 5 Capital Expenditures New expenditures = 457.1 E+6 $ @ 20 year life (5%) = 22.9E+6 Bureau of the Census: 1992 Economic Census:Census of Manufactures 6 Biomass Roundwood used for lumber 2.39E+08 mA3, 1988. CRB, 1993. Energy(J) = ( mA3)(1 E+06 g/mA3)(0.S 9 dry wtlg green wt)(19,200 JIg dry wt) = 2.29E+18

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Footnotes to Table 3-18 (emergyoflwnber) 7 Electricity The use of electricity and fuels in the sawmill industry is assumed to have the same distribution of use in the wood products industry. Fuel + electricity (F&EL) of SIC-2421. sejly = [$ value lumber sales (SIC-2421)] x [sejl$ of (F&EL of SIC-24)] F&EL used in sawmills (SIC-2421). sejly = 3.6E+21 Distribution of fuel used in SIC-24 (Lumber & wood prod'> Electricity Petroleum Coal Natural Gas Total % sej/y 74.3% 1.03E+22 9.9% 1.36E+21 0.8% 1.16E+20 14.9% 2.06E+21 100.00'{' 1.38E+22 Electricity use = F&EL of SIC-2421 (Sawmills) x % of total SIC-24 as electricity Electricity use = 74.3% of 3.6 E21 sej Electricity use = 2.6E+21 sej 8 Petroleum Petroleum use = F&EL of SIC-2421 (sawmills) x % of total SIC-24 as petrol. Petroleum used = 9.9% of 3.55 E21 sej. Petroleum used = 351.2E+18 sej 9 Coal Coal use = F&EL of SIC-2421 x % of total SIC-24 as coal Coal use = 0.8% of 3.55 E21 sej Coal use = 30.0E+18 sej 10 Natural Gas Natural gas use = F&EL of SIC-2421x % of total SIC-24 as N.G. Natural gas use = 14.9% of 3.55 E21 sej Natural gas use = 530.5E+18 sej 11 Lumber output Lumber production = 1.18E+08 m"3. 1993. CRS, 1996. 217 Energy(J) = ( ..... __ m"3)(1 E+06 g/m"3)(0.5 g dry wtlg green wt)(19,200 JIg dry wt) 1.1E+18 12 Lumber output, transfonnity Transfonnity of lumber = sum of 1 ,6-10 divided by output energy of lumber.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.APPENDIXB CALIBRATION OF EMERGYDYN AND EMSPECIES This appendix contains tables with footnotes documenting the calibration of EMERGYDYN for simulating wood (Table B-1), total organic matter (Table B-2), and saprolite (Table B-3) for the Coweeta watershed (ws18). Table B-4 documents the calibration ofEMSPECIES for simulating tree species abundance and emergy values. 218

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table B-1. Calibration ofEMERGYDYN for simulating biomass, emergy, and transformity of wood in Coweeta watershed. Calibration Note Description Variable Equation Value Units k-value I Rainfall R constant 100 Ixl09Jlhaly nJa 2 Deep heat 0 constant 14 IxlO9 J/haly nJa 3 Transformity of Rain TR constant 18000 sej/J nJa 4 Transfonnity of deep heat TO constant 34000 sej/J nJa 5 Wood biomass Q 250 MT/ha nJa 6 Runoff Rr ;;;R/( I + k I"Q*G) 55 I x I 09 J/haly 7 Transpiration Jl ;;;kl*Rr*O*Q 45 Ix I 09 J/haly 2.34E-04 8 Deepheat used J5 ;;;k5*Rr*O*Q 14 I x I 09 J/ha/y 7.27E-05 9 Wood feedback J4 zero 0 10 Gross wood production 12 =k2*Rr*G*Q 17 MT/haly 8.83E-05 II Wood export J6 =k6*Q 2.5 MT/ha/y 1.00E-02 12 Wood depreciation J3 =k3*Q 15 MT/ha/y 6.00E-02 13 Empower of rain MR =TR*R 1800 IxlO12 sej/haly nJa 14 Empower of deep heat MO =TO*O 476 1 x 10 12 sejlha/y nJa 15 Empower of wood production MJ2 =MR+MG 2276 IxlO12 sejlha/y nJa N -\0

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-1 1 Rainfall RainfulJ averaged 2 mfy for Coweeta (Swift et aI 1988) Energy of rain. JIhaIy = (2 mfy)x(10,00OmJ\2Iha)x(IE6 glmJ\3)x(5 Jig) Energy of rain. J!haIy = IE + 11 2 Deep heat Land Area (m"2) = 1.00E+04 Heat flow I Area = L4E+06 J/mJ\21y, @ Bryson City, NC (Smith et aI., 1981; in Pollack et al., 1991). Energy (Jlbaly) = (land area, mJ\2)x(heat flow/area, J/mJ\21y) Energy (J!haIy) = 1.4E+1O 3 Transformity of rain Transformity of rain taken from Odum 1996 4 Transformity of dee,p heat Transformity of heat flux through continents (Odum, 1996). 5 Wood biomass 220 Wood biomass in 1972, at least 50 years after heavy logging was 134 MTIha. Monk and Day, 1988. Assume by age 100 y, wood biomass would be 250 MTIha. 6 Runoff Runoff was 1.0 m/y from rainfall of 1.9 mfy, or -55%. 55%of2m1y= 1.1 mfy. Energy of runoff: J!haIy = 1.Im/y x 1 E4 mJ\21ha x 5E6 J/mJ\ 3 = 55 E9 7 Transpiration Difference between rainfall and runoff = 2 1.1 = 0.9 m/y Energy of transpiration, Ilhaly = O.9mJy x IE4 mJ\2/ha x 5E6 J/m"3 = 45 E9 8 DeqJ heat used Deep heat used, was a proxy for geologic input (I.e., rock weathering, and land uplift) Assume all of deep heat flux was used 9 Wood feedback Gross production of wood was an autocatalytic function. The energy flow of the feedback, although not zero in reality, was assumed negligIole here. Also, for convenience in calculating emergy flow on a circular pathway, feedback emergy was assumed to be zero. 10 Gross production of wood Net production of wood in 1972, at least 50 Y after heavy logging was 4.2 MT lhaIy (Monk and Day, 1988) Estimate that gross wood production was 17 MTlhaly when wood storage was 250 MTIha II Wood export Assume that wood export was 1% of wood biomass, or 2.5 MTlhaly

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-1 1 Rainfall Rainfall averaged 2 mfy for Coweeta (Swift et aI 1988) Energy ofraiD, JIhaIy = (2 mfy)x(l0,00Om"2/ba)x(lE6 glmJ\3)x(5 Jig) Energy of rain, JIhaIy = 1 E + 11 2 Deep heat LOOE+04 Land Area (mJ\2) = Heat flow I Area = 1.4E+06 J/mJ\21y, @ Bryson City, NC (Smith et aI., 1981; in Pollack et aI., 1991). Energy (JIbaIy) = (land area, mJ\2)x(heat flow/area, J/mJ\21y) Energy (Jlhaly) = 1.4E+I0 3 Transformity of rain Transfonnity of rain taken from Odum 1996 4 Transformity of deep heat Transfonnity ofheat flux through continents (Odum, 1996). 5 Wood biomass 221 Wood biomass in 1972, at least 50 years after heavy logging was 134 MT/ha. Monk and Day, 1988. Assume by age 100 y, wood biomass would be 250 MTIba. 6 Runoff Runoff was 1.0 mfy from rainfall of 1.9 mfy, or -55%. 55% of2m/y = 1.1 mfy. Energy of runoff, J/ha/y = 1.1mfyx IE4 mJ\2Iba x 5E6 J/mJ\3 = 55 E9 7 Transpiration Difference between rainfuIl and runoff = 2 1.1 = 0.9 m/y Energy of transpiration, Jlha/y = O.9m/y x lE4 mJ\2Iba x 5E6 J/m"3 = 45 E9 8 Deep heat used Deep heat used, was a proxy for geologic input (I.e., rock weathering, and land uplift) Assume all of deep heat flux was used 9 Wood feedback Gross production of wood was an autocatalytic function. The energy flow of the feedback, although not zero in reality, was assumed negligible here. Also, for convenience in calculating emergy flow on a circular pathway, feedback emergy was assumed to be zero. 10 Gross production of wood Net production of wood in 1972, at least 50 y after heavy logging was 4.2 MTlbaly (Monk and Day, 1988) Estimate that gross wood production was 17 MTlbaly when wood storage was 250 MT/ha 11 Wood export Assume that wood export was 1 % of wood biomass, or 2.5 MTlbaly

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.222 Notes to Table 8-1 12 Wood depreciation (respiration) Assume that when wood biomass was 250 MTIha, respiration was 90% of gross wood prod., or -15 MTIbaIy. 13 Empower of rain Empower of rain = Transfonnity of rain x energy of rainfall 14 Empower of deep heat Empower of deep heat = Transfonnity of deep heat x energy of deep heat 15 Empower of gross wood production Sum of rain and deep heat empower

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table B-2. Calibration ofEMEROYDYN for simulating biomass, emergy, and transformity of total organic matter in Coweeta watershed. Calibration Note Description Variable Equation Value Units k-value 1 Rainfall R constant 100 lx109 J/ha/y nla 2 Deep heat 0 constant 14 lxlO9 J/ha/y nJa 3 Transfonnity of Rain TR constant 18000 sej/J nJa 4 Transfonnity of deep heat TG constant 34000 sej/J nla 5 Total organic matter (TOM) Q 350 MT/ha nJa 6 Runoff Rr =RI( I + k I*Q*G) 55 1 x 1 09 J/ha/y 7 Transpiration Jl =kl*Rr*G*Q 45 1 x 109 J/ha/y 1.67E-04 g Deephcat used J5 =k5"'Rr"'G"'Q 14 lx109 J/ha/y 5. 19E-05 9 TOM feedback J4 zero 0 10 Gross TOM production J2 =k2*Rr"'G"'Q 2S MTlhaly 9.28E-05 11 TOM export J6 =k6"'Q 2 MTlhaly 5.7IE-03 12 TOM depreciation 13 =k3*Q 8 MT/ha/Y 2.29E-02 13 Empower of rain MR =TR*R 1800 lx1012 sej/ha/y nla 14 Empower of deep heat MG =TO*O 476 IxlOI2 sej/ha/y nla 15 Empower of TOM production MJ2 =MR+MG 2276 I x 10 12 sej/ha/y nla N N w

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-2 1 Rainfull Rainfull averaged 2 mfy for Coweeta (Swift et al 1988) Energy of raiD, J/haly = (2 m1y)x(10,OOOmI\2Iha)x(IE6 glmI\3)x(5 JIg) Energy of rain, J/haly = 1 E + 11 2 Deep heat Land Area (m"2) = 1.00E+04 Heat flow I Area = 1.4E+06 J/ml\21y, @ Bryson City, NC (Smith et al., 1981; in Pollack et al., 1991). Energy (JIhaIy) = (land area, m"2)x(heat flow/area, J/m l\2/y) Energy (J/haIy) = 1.4E+1O 3 Transfonnity of rain Transfonnity of rain taken from Odum 1996 4 Transfonnity of deep heat Transfonnity of heat flux through continents (Odum., 1996). 5 Total organic matter (TOM) 224 TOM (wood, roots, soil organic matter) in 1972, at least 50 years after heavy logging was 330 MT/ha. Monk and Day, 1988. Round up to 350 MTIha. 6 Runoff Runoffwas 1.0 mfy from rainfall of 1.9 mfy, or -55%. 55% of2mfy = 1.1 mfy. Energy of runo( J/haly = 1.lmfy x lE4 ml\2Iha x 5E6 J/ml\3 = 55 E9 7 Transpiration Difference between rainfiill and runoff = 2 -1.1 = 0.9 mfy Energy of transpiration, J/haly = 0.9mIy x lE4 ml\2Iha x 5E6 J/ml\3 = 45 E9 8 Deep heat used Deep heat used, was a proxy for geologic input (I.e., rock weathering, and land uplift) Assume all of deep heat flux was used 9 TOM feedback Gross production of TOM was an autocatalytic function. Energy flow of the feedback, although not zero in reality, was assumed negligible here. Also, for convenience in calculating ernergy flow on a circular pathway, feedback emergy was assumed to be zero. 10 Gross production of TOM Net production of TOM in 1972, at least 50 y after heavy logging was 15 MT/haly (Monk and Day, 1988) Based on observation estimate that gross production was 25 MTIbaIy when TOM storage was 350 MT/ha

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-2 II TOM export Assume that TOM export was less than 1% of TOM, -2 Mf/haly 12 TOM depreciation
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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table B-3. Calibration ofEMERGYDYN for simulating saprolite, emergy, and emergy per mass of saprolite (regolith) in Coweeta watershed. Calibration Note Description Variable Equation Value Units k-value 1 Rainfall R constant 100 9 IxlO J/ha/y nla 2 Deep heat G constant 14 9 lxlO J/ha/y nla 3 Transformity of Rain TR constant 18000 sej/J nla 4 Transfonnity of deep heat TG constant 34000 sej/J nla 5 Saprolite Q 91.5 Ix 109 g/ha nla 6 Rain not used in saprolite fonnation Rr =RI( I + k 1 "'Q"'G) 1 9 lxlO J/ha/y 7 Rain used in saprolite formation Jl =kl*Rr*G*Q 99 9 IxlO J/haly 7.73E-02 8 Deepheat used J5 =k5"'Rr*G*Q 14 lxlO9 J/ha/y 1.09E-02 9 Saprolite feedback J4 zero 0 10 Gross saprolite production J2 =k2*Rr*G*Q 0.57 9 IxlO g/haIy 4.4SE-04 II Saprolite export J6 =k6*Q 0.285 1 x 109 g/haly 3.IIE-03 12 Saprolite depreciation J3 =k3*Q 0.285 1 x 1 09 glha/y 3.lIE-03 13 Empower of rain MR =TR*R 1800 IxlO12 sej/ha/y nla 14 Empower of deep heat MG =TG*G 476 Ixl012 sej/ha/y nla IS Empower of saprolite production MJ2 =MR+MG 2276 IxlO12 sejlha/y nla N N 0\

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-3 1 Rainfall Rainfull averaged 2 mly for Coweeta (Swift et aI 1988) Energy of raiD, Jlbafy = (2 mly)x(l0,000m1\21ha)x(lE6 g/mI\3)x(5 Jig) Energy of raiD, JIbaf) IE+II 2 Deep heat Land Area (mI\2) = LOOE+04 Heat flow I Area = L4E+06 J/ml\2!y, @ Bryson City, NC (Smith et aI., 1981; in Pollack et aI., 1991). Energy (J/ha/y) = (land area, m"2)x(heat flow/area, J/ml\2/y) Energy (J/ha/y) = L4E+ 10 3 Transfonnity of rain Transformity of rain taken from Odum 1996 Transfonnity of 4 deep heat Transformity of heat flux through continents (Odum, 1996). 5 Saprolite (regolith) Saprolite depth in Coweeta basin averaged 6.1 m. Douglass and Swank, 1975. At a density of 1.5 g/cmI\3, that depth was the equivalent of 91.5 E9 gIha 6 Rain not used in saprolite formation Assume that nearly 100% of rainfall was used in saprolite formation. 227 Rain was either used as transpiration in production which accelerated rock weathering, or was runoff which carried acids and removed saprolite. 7 Rain used in saprolite formation Assume that nearly 100% of rainfall (see above) 8 Deep heat used Deep heat used, was a proxy for geologic input (i.e., rock weathering, and land uplift) Assume all of deep heat flux was used 9 Saprolite feedback Gross production of saprolite was an autocatalytic function. Energy flow of the feedback, although not zero in reality, was assumed negligible here. Also, for convenience in calculating emergy flow on a circular pathway, feedback emergy was assumed to be zero. 10 Gross production of saprolite Velbel (1984) calculated that the rate of saprolite formation was 3.8 cmllOOOy Based on this observation and a density of 1.5 g/cmI\3, saprolite was being fonned at 570,000 g!ha/y II Saprolite export WIthout better data, assume that saprolite export was 50% of gross production

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-3 12 Saprolite dq!reciation Assume that saprolite depreciation (dispersal) 'was 50% of gross production. 13 Empower of rain Empower of rain = Transformity of rain x energy of rainfall 14 Empower of deep heat Empower of deep heat = Transformity of deep heat x energy of deep heat 15 Empower of gross saprolite production Sum of rain and deep heat empower 228

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table B-4. Calibration of EM SPECIES for simulating species abundance, stored emergy, and emergy per species in the WSC watershed. Calibration Note Description Variable Equation Value Units k-value 1 Rainfall per area r constant 100 1 x I 09 Jlhaly nla 2 Deep heat G constant 14 nla 3 Seed availability C constant 1 arbitrary units 4 Transformity of Rain TR constant 18000 sej/J nla 5 Transformity of deep heat TG constant 34000 nla 6 Empower per species TC constant I.OE+20 sej/y per tree species nla 7 Area A constant 0.08 ha nla 8 Biomass V state variable 28 MT per 0.08 ha nla 9 Tree species S state variable 9 species per 0.08 ha 10 Rainfall R r'" area 8 II Runoff Rr =RI(1 + k I"'S) 5 lx109 J per 0.08 ha per y 12 Transpiration Jl =kl"'RrS 3 6.67E-02 13 Deep heat used J5 =k5"'V"'O*C 1.1 7.47E-02 14 Gross primary production 12 =k2*RrS 2 1\ 4.44E-02 15 Species feedback J4 negligible 0 16 Unit respiration J3 =k3*V 1.5 5.36E-02 17 Connectivity respiration J6 =k6*V*S2 0.4 1. 76E-04 N N 18 Recruitment respiration J7 =k7*V*O*C 0.1 2.55E-04 \0

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table B-4. continued. Calibration Note Description Variable Equation Value Units k-value 19 Species recruitment (gross) JS =kS*V*O*C 0.24 species per O.OS ha 6. 12E-04 pery 20 Species loss (l st order) J9 =k9*S 0.225 2.50E-02 21 Species loss (2nd order) Jl3 =k13*S2 0.015 l.S5E-04 22 Empower of rain MR =TRR 1800 lxl012 sej/haly n/a 23 Empower of deep heat MO =TOO 476 n/a 24 Empower of new species MC =TC*C 1.0E+08 II n/a 25 Empower of primary production MJ2 =MR 1800 n/a Empower contribution to tree MJ7 26 fr b' specIes om IOmass =TV*J7 variable n/a 27 Empower of species recruitment MJ8 =MJ7+MG+MC variable nJa o

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-4 1 Rainfall per area Rainfall averaged 2 rn/y for Coweeta (Swift et al 1988) Energy of rain, J/haly = (2 rn/y)x(lO,000mI\21ha)x(lE6 glmI\3)x(5 J/g) Energy of rain, J/haly = 1 E + 11 2 Deep heat Land Area (mI\2) = 1.00E+04 Heat flow / Area = 1.4E+06 J/mI\2/y, @ Bryson City, NC (Smith et aI., 1981; in Pollack et aI .. 1991) Energy (J/haIy) = (land area, mI\2)x(heat flow/area, J/mI\2/y) Energy (Jlhaly) = l.4E+ 1 0 3 Seed availability Availability was assumed constant 4 Transformity of rain Transformity of rain taken from Odum 1996 5 Transformity of deep heat Transformity of heat flux through continents (Odum, 1996). 6 Empower per species Used Orrell's (1998) calculation of the annual empower per tree species in north central Florida. 7 Area Calibration values were based on an area of 0.08 ha. 8 Biomass 28 MT per 0.08 ha is equivalent to 350 MTIha, which was rounded up from Monk and Day's (1988) estimate of total organic matter for Coweeta WSl8 9 Number of tree species Calculated from Eliott and Hewitt's (1998) data. 10 Rainfall Rainfall = rainfall per area x area N W '""'

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-4 11 Runoff Runoffwas 1.0 mly from rainfall of 1.9 m/y, or -55%, 55%of2m1y= 1.1 m/y, Energy of runoff, J/haly = 1, Im/y x I E4 m"21ha x 5E6 J/m"3 = 55 E9 Energy of runoff, J per 0,08 ha per y = 55 E9 JlhaJy 0,08= -5 E9 J 12 Transpiration Difference between rainfall and runoff = 2 -J, 1 = 0,9 m/y Energy of transpiration, J/ha/y = 0,9m1y x lE4 ml\21ha x 5E6 J/m"3 = 45 E9 Energy of transpiration, J per 0,08 ha per y = 45 E9 J/ha/y 0,08= -3 E9 J 13 Deep heat used Deep heat used, was a proxy for geologic input (Le" rock weathering, and land uplift) Energy of deep heat, J per O,OS ha per y = 14 E9 J/ha/y. O,OS= -1.1 E9 J 14 Gross production of biomass Net production of TOM in 1972, at least 50 y after heavy logging, was 15 MT/ha/y (Monk and Day. 1988) Based on the observation, gross production was estimated to be 25 MT/haJy (2 MT/O,OShaly) when TOM storage was 350 MTIha 15 Species feedback Gross production of biomass was a function of rain energy and tree species, The energy flow of the feedback, although not zero in reality, was assumed negligible here, Also, for convenience in calculating emergy flow on a circular pathway, feedback emergy was assumed to be zero. 16 Unit respiration Unit respiration represented the energetic expense of the units as if in isolation, and was a function of biomass only Total respiration was calibrated equal to gross production, unit respiration was assumed to be 75% of total respiration, 17 Connectivity respiration fj N

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Notes to Table B-4 Connectivity respiration was the energetic expense of maintaining the interactions between tree species. It was assumed to be 20% of total respiration at steady state 18 Recruitment respiration Recruitment respiration was the energetic expense to recruit new tree species It was assumed to be 5% of total respiration at steady state 19 Species recruitment Gross tree species recruitment was assumed to equal 3 species per ha per year (0.24 per 0.08 hal 20 Species loss Ost orderl Species exit the ecosystem as a 1st order (linear) function of the species present. Total species loss balanced species recruitment. Ist order loss was assumed to equal-95% of total species loss 21 Species loss (2nd orderl Species exit the ecosystem as a 2nd order (quadratic) function of the species present (a "crowding effect"), Equaled 5% of total species loss. 22 Empower of rain Empower of rain = Transfonnity of rain x energy of rainfall 23 Empower of deep heat Empower of deep heat = Transfonnity of deep heat x energy of deep heat 24 EmpOwer of new species Empower of new species = Empower per tree species (north central Florida) x species recruitment 25 Empower of primary production Empower of rain only 26 Empower contribution to tree species from biomasS Empower from biomass to tree species was transfonnity of biomass x recruitment respiration 27 Empower of species recruitment Sum of empower from recruitment respiration, deep heat, and new species N w w

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.APPENDIXC W ATER VAPOR SATURATION DEFICIT OF THE ATMOSPHERE OVERL YING LAND The mean solar transfonnity of the water vapor saturation deficit was calculated to be 590 sej/J. The following sections explain how the transformity was derived. Introduction The water vapor saturation deficit is well known to be a major factor in forest transpiration and has been strongly correlated with gross primary prodUctivity of forest ecosystems (Odum 1970). Prior to this study, the solar transformity of had not been calculated, and therefore, the emergy contnoution of es
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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.235 The vapor saturation pressure, the maximum amount of vapor a parcel of air will hold, is a function of temperature T as given by the Clausius-Clapeyron equation (Schneider 1996) deJdT = Cs L MwIR T2 (2) where L = latent heat of phase transition, Mw = 18.0 is average molecular weight of water, R = 8.33xl03 Joules per Kelvin per mole is the ideal-gas constant, and T is absolute temperature. The equation can be integrated and simplified to an approximate fonn (Chow et al. 1988) Cs = 6.11 exp[(17.27. T)/(237.3 + T)] (3) where Cs is in millibars, T is in degrees Celsius, and exp means raise the base of the natural logarithm (2.718) by the bracketed expression. Energy at the Surface (1000 mb) The mean annual value of the saturation deficit over the continents at the surface (1000 mb) was estimated based on the mean monthly temperature and vapor pressure presented in a 0.50 latitude by 0.50 longitude resolution climatology for land areas, excluding Antarctica, for the period 1961-1990. The 'Global Climate Dataset' was compiled by the Climate Research Unit of the United Nations Intergovernmental Panel on Climate Change and distributed by their Data Distribution Centre (New et al. 1998). Mean monthly water vapor saturation pressure for each grid was approximated with Eq. (3), which was then used in Eq. (1) to figure the water vapor saturation deficit. The mean zonal value (Le., per latitude) for the saturation deficit over land was figured by summing the monthly values at each latitude and dividing by the total area of

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.236 land at that latitude. The mean saturation deficit for all land was found by summing the monthly sums across all latitudes and dividing by the total area of land represented in the dataset. Meridional Profiles of the Vertical Distribution of the Saturation Deficit For each 10 degree interval oflatitude an equation was developed for figuring the saturation deficit at a given altitude. The estimates for the surface (1000mb) and 850 mb were combined with the minimum values (Le., those found at the highest altitudes) to develop a linear regression modeL The saturation deficit at the surface (1000 mb) was determined as previously described. At the 850 mb level, the saturation deficit was based on the meridional profile of relative humidity (peixoto and Oort 1996) and temperature (Haurwitz and Austin 1944) over land. The relative humidity U is The minimum saturation deficit occurs at the highest altitudes. For the analysis the minimum vapor saturation deficit for each latitude was estimated based on the cross section of the saturation mixing ratio given for the whole globe (ocean plus land) (peixoto and Oort 1996). The saturation vapor pressure deficit can be approximated from the difference between saturation mixing ratio (qs) and the mixing ratio (q) by em = p/622. (qs -q) (5) Where p = atmospheric pressure in millibars, qs is saturation mixing ratio in glkg, and q is mixing ratio in g/kg.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.237 Results Systems Diagram of the Global Water Vapor Saturation Deficit Figure C-I shows the systems diagram highlighting the role of the water vapor saturation deficit in controlling the hydrologic cycle between sea, atmosphere, and land. The storages of heat (T M, T d and water vapor er.) in the global atmosphere were separated into marine (M) and continental (L) components due to their distinctly different attributes. Marine air is generally more moist than continental air. In the sea, the sun, ocean water, tide, and the deep heat of the earth interact with the marine atmosphere to produce more atmospheric vapor and heat. In the atmosphere, the marine and continental air masses interact, accelerated by the deep heat of earth driving the land cycle, to produce rain over land and sea. On land, plant transpiration is driven by water availability, the water vapor saturation deficit (a function of the difference between T L and er.), and the land cycle. Water not used in transpiration or evaporated is discharged to the sea. Energy at the Surface (1000 mb) The seasonal distribution of the saturation deficit esd for the globe can be seen in the world maps (Figures C-2a and C-2b). In June, the saturation deficit was greatest in the deserts of North Africa, northern and southwestern North America. (Note: data was missing between meridians 45E-80oE and 105E-120oE for June, Figure C-2a). In December, esd was greatest in North Africa, AustraIia, south central South America, the Arabian peninsula, southern Africa, and western India. The vapor saturation deficit generally was greatest near the equator and decreased poleward.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.The mean annual saturation deficit for the Northern Hemisphere (7.31 mb) was less than the 8.89 mb mean for the Southern Hemisphere. However, the mean annual meridional distribution for the Northern Hemisphere had a much higher peak (-20 mb near Figure C-3) than any latitude in the Southern Hemisphere. For the JuneAugust period (JJA), the global distribution was much more uneven between the Southern and Northern hemispheres. 238 In Figure C-4 the annual cycle of mean monthly vapor saturation deficit is shown for the Southern Hemisphere (SH), Northern Hemisphere (NH), and the globe. The cycles for the hemispheres were out of phase with the SH peaking in November-January and the NH doing so in June-July. Globally, the period of maximum vapor deficit was June-July. Vertical Distribution of the Saturation Deficit Figure C-5 is a graph of the data presented in Table C-l. Figure C-5 shows the meridional profiles of the vapor saturation deficit (esc!) for altitudes from ground surface (1000 mb) up to 350 mb. The esc! decreased with altitude at all latitudes, but at varying rates. Above 350 mb the Csd was less than 1 mb. Figure C-6 presents a graph of the data shown in the final column of Table C-2. Figure C-6 shows the meridional distribution of the vertically integrated, mean annual energy of the saturation deficit. Globally, it was greatest at but had a local maximum at 20S. The Csd dipped to a local minimum at the equator.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.239 Figure C-7 shows the vertical distribution of the vapor saturation deficit (esd) over the continents. The esd declined with altitude from 7.8 mb at the surface (1000 mb) to near zero at 350 mb. This was an average of 0.74 mb per 1000 m of altitude. Transformity of the Saturation Deficit over Land The solar transformity of the earth's mean water vapor saturation deficit over land was 590 sejlJ (Table C-3). The mean annual energy of the saturation deficit of the atmosphere overlying the continents was 361 E18 J. On average, the water vapor of the atmosphere is replaced every 8.2 days (UNESCO 1978), hence, the annual flow of energy necessary to support this storage is (361 E18 1)/(8.2 d) x (365 d) = 16 E21 J/y. Supposing that the total emergy budget of the globe was required to maintain this energy flow, the global transformity of the saturation deficit over land was estimated as (9.44 E24 sej/y)/(l6 E21 J/y) = 590 sej/J.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.N Figure C-I. Systems diagram of the hydrologic cycle overlayed with the heat budget of the atmosphere highlighting the role of the water vapor saturation deficit over land.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.-.. .. "". .' .. ". '. .. .. :.1 .: Missing Dat )! .. Mean vapor saturation deficit (mb x 100) at surface (1000 mb) for June (1961-90) 0-150 150 400 400 600 600 1500 -_ 1500 5000 Figure C-2a. Avemge annual atmospheric water vapor saturation deifict for 1000 mb for period 1961-1990. '1\ I!. / -

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.'I. ," "". r '"" .. :.. .1 ,.. Mean vapor saturation deficit (100 x mb) at surface for December for period 1961-1990, 0-100 100 200 200 600 600 900 600 3400 Figure C-2, continued. ._ .... "':f\':':'" .. .' \ / N

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission...c E 30 25 20 gf 15 10 5 o -90 -60 -30 o 30 60 Figure C-3. Annual and seasonal meridional profiles of the mean zonal water vapor saturation deficit (mb) at the surface of the continents. (DJFDec, Jan, Feb; JJA-Jun,July, Aug). 243 90

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.244 12 10 Southern Hemis here '-...".. .-.. -. -. I 8 .0 E IV 6 CD I III Q) 41 Northern Hemishpere 21 0 J F M A M J J A S 0 N 0 Figure C-4. Mean monthly (1961-90) water vapor saturation deficit at the surface (1000 mb) of the continents for the globe, Northern Hemisphere and Southern Hemisphere.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.20 1000mb 18 ---850mb ..0 16 .. .. 700mb E_ 14 A 550mb ..... ;g 12 400mb Q) "0 10 c e 350mb 0 8 ::J 6 ..... Cl1 (/) 4 2 0 -90 -BO -30 0 30 60 90 Latitude Figure C-5. Meridional profiles of the mean zonal water vapor saturation deficit at altitudes ranging from the surface (1000 mb) to 350 mb. VI

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table C-1. Derivation of the vertical profile of the annual vapor saturation deficit (mb) by latituc Altitude, mb Mid-saturation deficit (sd) for latitude 1000 8 850b 700 550 400 350 elevations (h) > 850 mb 80 0.5 0.1 70 0.8 0.4 sd = 0.003h -2.1179 60 1.6 0.9 0.56 sd = 0.0033h -1.8121 50 2.6 2.1 1.56 0.96 sd = 0.0038h -1.0952 40 5.5 5.2 2.84 1.00 sd = 0.0106h -4.5787 30 11.1 8.3 6.23 3.73 0.64 0.39 sd = 0.0167h -5.4635 20 18.2 11.9 9.34 5.42 1.51 0.50 sd = 0.0261h -8.9334 10 13.0 11.0 7.50 4.58 1.65 0.56 sd = 0.0195h -6.1467 0 6.6 5.9 4.02 2.58 1.14 0.56 sd = O.0096h -2.7089 -10 7.9 7.1 4.78 3.03 1.27 0.56 sd = 0.0117h -3.4164 -20 11.6 8.3 6.23 3.73 1.22 0.50 sd = 0.0167h -5.4635 -30 9.9 5.7 4.68 2.52 0.64 sd = 0.0144h -5.403 -40 5.5 4.0 2.96 1.78 0.64 sd = 0.0079h -2.5734 -50 3.9 2.0 1.62 0.88 sd = 0.0063h -2.7962 a from global map (this dissertation) b based on meridional profiles of relative humidity for land (Peixoto & Oort, 1996) and temperature (Haurwitz & Austin, 1944) The sat. def. at the highest altitude for each latitude was interpolated from zonal mean cross sections given for whole globe (I.e., ocean and land) (Peixoto & Dort, 1996) All other sat. def. were based on regression equations (shown) developed from points at 1000 N mb, 850 mb, and highest altitude for each latitude.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table C-2. Energy (J) of the water vapor saturation deficit by latitude and altitude. Total energy (J) at given altitude (mb) Latitude Area, km2 1000 mb 850mb 700mb 550mb 400mb 350mb Total 80 1685687 6.69E+16 3.69E+16 0 0 0 0 1.04E+17 70 7817518 5.03E+17 4.63E+17 0 0 0 0 9.66E+17 60 12101767 1.44E+18 1.65E+18 1.10E+18 8.12E+15 0 0 4.20E+18 50 13786047 2.79E+18 4.40E+18 3.51E+18 2.96E+18 0 0 1.37E+19 40 12830910 5.42E+18 1.00E+19 5.93E+18 2.87E+18 0 0 2.42E+19 30 12359376 1.05E+19 1.54E+19 1.25E+19 1.03E+19 2.02E+18 5.02E+17 5.13E+19 20 11576940 1.61 E+19 2.06E+19 1.76E+19 1.40E+19 4.46E+18 6.11E+17 7.34E+19 10 10022407 9.94E+18 1.64E+19 1.22E+19 1.03E+19 4.24E+18 5.92E+17 5.37E+19 0 11051876 5.57E+18 9.73E+18 7.23E+18 6.38E+18 3.22E+18 6.53E+17 3.28E+19 -10 10283746 6.21E+18 1.09E+19 8.00E+18 6.96E+18 3.34E+18 6.08E+17 3.60E+19 -20 10067917 8.96E+18 1.24E+19 1.02E+19 8.39E+18 3.14E+18 5.31E+17 4.36E+19 -30 7030558 5.30E+18 5.94E+18 5.35E+18 3.96E+18 1.15E+18 0 2.17E+19 -40 2025638 8.50E+17 1.21E+18 9.75E+17 8.04E+17 3.31E+17 0 4.17E+18 -50 731799 2.20E+17 2.1SE+17 1.93E+17 1.44E+17 0 0 7.72E+17 Total 7.39E+19 1.09E+20 8.48E+19 6.71E+19 2.19E+19 3.50E+18 3.61E+20 Density, g/m3 1.23 1.06 0.91 0.75 0.57 0.39 Altitude,m 0 1500 3000 4750 7200 10500 Equation: Energy of saturation deficit at latitude Y and altitude Z, J = sat def, mb x _J/kg per mb x area per Y, km2 x 1 E6 m2/km2 x density, g/m3 x mid-interval height, m "-> .....

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission..0 E oi "'0 ::s -i2 o o es ea(3}, mb I xqs -q, g/kg 250 soor OX xo 750 x 0 I 0.0 2.0 4.0 6.0 8.0 Saturation deficit 248 Figure C-7. Vertical profiles of water vapor saturation deficit (mb) and difference in vapor mixing ratios for the atmosphere above the continents.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.10 I 9 f 8 f\ 7 6 r E .ii 5 L CD I '" 4 CD 3 2 -. 1 a 90 Memphis, TN v ,--. -. 87.5 85 Southern Appalachians 82.5 Longitude .... _-----.--80 77.5 249 r j Nov I Jan 75 Morehead City, NC Figure C-S. Seasonal mean monthly saturation deficit across the Southern Appalachiaru along the 35th paraIIel from eastern North Carolina to western Tennessee.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.250 Table C-3. Solar transformity of the water vapor saturation deficit overlying the continents. Description Mean annual energy of saturation deficit of atmosphere overlying the continents, J = Mean turnover time of atmospheric moisture, days = Annual supply of saturation deficit to atmosphere (3.61 E20 J x 365 days per year 18.2 days), J = Global emergy input to maintain saturation deficit of atmosphere, sej/y = Global mean transformity of saturation deficit, sejlJ = Value Source 3.61E+20 Table C-2 8.2 UNESCO, 1978. 1.60E+22 9.44E+24 Odum 1996 588

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.APPENDIX 0 CALCULATING ENERGY ABSORBED FROM WIND A new methodology was developed and used for estimating the energy conttibuted from wind. First, wind speeds aloft (100Om) were approximated based on the general observation that, over land, near-surface speeds are 60010 of speeds aloft (Barry and Chorley, 1992). Next, a vertical profile of wind speed was fitted to the two endpoints based on the curve-shape typically observed (Figure 0-1). The total energy absorbed was found by numerically integrating the vertical change in wind velocity in a spreadsheet (explanation to follow). Only near-surface data on wind speed-typically reported at weather stations-were required, making the task of estimating energy absorption easier. Table 0-1 shows the data and equations used to calculate the wind energy absorbed in one (1) hectare of the Coweeta watershed. Columns 1-3 give the velocity profile over the 1000 m height. Wind speed increased with altitude. Column 4 gives the wind energy absorbed per unit of air between consecutive layers of the atmosphere. The last column, number 7, gives the rate of air exchange between height layers. Column 5 gives the annual wind energy absorbed between intervals of height, which was column 4 times column 7. The total wind energy absorbed over the control volume of lE7 mA3 (1 ha x 1000 m) was the sum of column 5 (188 E9 J/ha/y). 251

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 0-1. Equations and data used to calculate annual wind energy absorbed in the Coweeta watershed. ezucuz profile Wind energy Annual wind (fractional Height Wmd Wind absorbed energy change in above speed, speed, over interval absorbed speed with Air exchange, ground, m mph mls (EJ, J/m3 (EJ, J/y elevation) m3/y 1000 7.13 3.19 900 7.07 3.16 0.11 1.02E+09 0.0091 9.06E+09 800 6.96 3.11 0.18 2.76E+09 0.0153 1.50E+I0 700 6.86 3.06 0.18 2.71E+09 0.0155 1.50E+1O 550 6.71 3.00 0.25 5. 16E+09 0.0221 2.09E+I0 400 6.48 2.90 0.37 1.21E+I0 0.0355 3.24E+IO 300 6.27 2.80 0.33 9.71E+09 0.0334 2.96E+I0 200 5.98 2.67 0.44 1.78E+1O 0.0484 4.08E+IO 100 5.30 2.37 0.94 8.91E+I0 0.1273 9.52E+1O 50 4.90 2.19 0.51 2.94E+1O 0.0833 5.75E+1O 20 4.58 2.05 0.36 1.60E+I0 0.0682 4.41E+I0 0.1 4.47 2.00 0.12 1. 87E+09 0.0244 1.54E+1O Total wind energy absorbed
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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.253 1000 900 800 700 E 600 -.c 500 0> CD 400 :I: 300 200 100 a 0.0 1.0 2.0 3.0 4.0 speed,m1s Figure D-l. Wmd speed profile used for the Coweeta watershed.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table D-2. Equations and data used to calculate allIl'.ml wind energy absorbed in the Wme Spring Creek watershed. Wind Vertical profile Height Wind Wmd energy Annual wind (fractional above speed, speed, absorbed, energy increase in speed ground, m mph mls J/m3 absorbed, J/y with elevation) 1000 7.13 3.19 900 7.07 3.16 0.11 1.02E+09 0.0091 800 6.96 3.11 0.18 2. 76E+09 0.0153 700 6.86 3.06 0.18 2.71E+09 0.0155 550 6.71 3.00 0.25 5. 16E+09 0.0221 400 6.48 2.90 0.37 1.21E+I0 0.0355 300 6.27 2.80 0.33 9.71E+09 0.0334 200 5.98 2.67 0.44 1.78E+I0 0.0484 100 5.30 2.37 0.94 8.91E+1O 0.1273 50 4.90 2.19 0.51 2.94E+1O 0.0833 20 4.58 2.05 0.36 1.60E+I0 0.0682 0.1 4.47 2.00 0.12 1.81+09 0.0244 Total kinetic energy absorbed = 187.61E+9 Air exchange, m3/y 9.06E+09 1. 5 OE+ 10 1.50E+1O 2.09E+I0 3.24E+I0 2.96E+I0 4.08E+I0 9.52E+I0 5.75E+1O 4.41E+1O 1.54E+I0 Volume of air exchanged, m3/y = 374.9E+9 Footnotes to Table D-2 Surface wind speed, mph = 4.47 Surface wind speed, mls = 2.00 wind speed from climate station CS30 It; 1213m; mid-elev ofWSC Area of Wine Spring Cr. basin, m"2 = 10000 Annual wind speed @ surface averages 60% oftbat @ 1000m. (assumed) Shape of the wind profile was approximated based on Barry & Chorley 1996. Equations: Ell = Energy absorbed at each height interval, lly E3 = [{(wind speed@h, m/s)"-(wind speed @ hI, m/s),,}x(1.23 kglm:>12)x{(wind speed @ h, mls)-(wind speed@ hI, mls)}x(surface area, m2)x(3.154E7 s/y)1 Etotal = Total energy absorbed over control volume. J/y. EtwI = Sum Ell over entire height 254

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table D-3. Equations and data used to calculate annual wind energy absorbed within a 1000 m prism overlying Macon County. N.C. Wind energy Annual wind Vertical profile Height Wind Wmd absorbed energy (fractional above speed, speed. over interval absorbed change in speed Air exchange. ground, m mph mls . J/m3 (EJ. J/y with elevation) m3/y 1000 7.17 3.21 900 7.11 3.18 0.11 1.38E+14 0.0091 1.22E+15 800 7.00 3.13 0.19 3.75E+14 0.0153 2.02E+15 700 6.89 3.08 0.18 3.70E+14 0.0155 2.02E+15 550 6.75 3.02 0.25 7.02E+14 0.0221 2.81E+15 400 6.51 2.91 0.38 I.64E+15 0.0355 4.31E+15 300 6.30 2.82 0.33 1.32E+15 0.0334 3.98E+15 200 6.01 2.69 0.44 2.42E+15 0.0484 5.50E+15 100 5.33 2.38 0.95 1.21E+16 0.1273 1.28E+16 50 4.92 2.20 0.52 4.01E+15 0.0833 7.75E+15 20 4.61 2.06 0.37 2. 18E+15 0.0682 5.94E+15 0.1 4.50 2.01 0.12 2.55E+14 0.0244 2.01E+15 Total wind energy absorbed . J/y = 25.56E+15 50.5E+15 Footnotes to Table D-3 Surface wind speed. mph = 4.50 NOAA website Surface wind speed, mls = 2.01 Area of Macon Co ml\2 = 1.34E+09 Annual wind speed@ surface averages 60% of that @ 100Om. (assumed) Shape of vertical wind profile was approximated based on Barry & Chorley 1996. Egyations: h = height of top of interval; h' = height of bottom of interval Eh = Energy absorbed over each height interval.. J/m3 Eh = [{(wind speed@ h. mls)2-(wind speed@ h'. mls)2}x(1.23 kglm3/2) Ea = Energy absorbed over each height interval, J/y Ea = (EIuJ/m3) x {(wind speed @ h. mls)-(wind speed @ h', mls)} x (surface area,m 2 ) x (seconds per time) Etout = Total energy absorbed over control volume. J/y. = Swn of Ea for each height interval 255

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table 04. Equations and data used to calculate annual wind energy absorbed within a 1000 m prism overlying North Carolina. Wind energy Annual wind Vertical profile Height Wind Wind absorbed energy (fractional above speed, speed, over interval absorbed change in speed Air exchange, ground,m mph mls (EJ, J/m3 (EJ, J/y with elevation) m3/y 1000 9.17 4.10 900 9.08 4.06 0.19 2.93E+16 0.0091 1.58E+17 800 8.95 4.00 0.30 7.95E+16 0.0153 2.62E+17 700 8.81 3.94 0.30 7.83E+16 0.0155 2.62E+17 550 8.62 3.85 0.41 1.49E+17 0.0221 3.65E+17 400 8.32 3.72 0.61 3.4SE+17 0.0355 5.66E+17 300 8.06 3.60 0.54 2.S0E+17 0.0334 5.16E+17 200 7.68 3.43 0.72 5.13E+17 0.0484 7.14E+17 100 6.82 3.05 1.55 2.57E+lS 0.1273 1.66E+18 50 6.29 2.S1 0.84 8.48E+17 0.0833 1.01E+18 20 5.89 2.63 0.60 4.63E+17 0.0682 7.70E+17 0.1 5.75 2.57 0.20 5.39E+16 0.0244 2.69E+17 Total wind energy absorbed
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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.APPENDIXE SOLAR TRANSFORMITY OF MOUNTAIN DEEP HEAT AND EROSION Introduction Mountains are hierarchical centers of the landscape which require the work of all lower land for creation and maintenance (Figure E-l). Thus, the transformity of geologic processes (e.g., erosion, weathering, heat flow) and mountain structure increase with elevation. Since the mountain operates as an energy chain with higher levels having less heat flow, but the same supporting earth empower, the transformity of deep heat increased with elevation. Similarly, erosion rates increased with altitude (Choriey et al. 1984), but earth empower was assumed constant, leading to a higher ratio of empower to mass eroded with elevation. Systems theories of energy hierarchy indicate that the higher transformity of mountains results in a greater ability to effect global systems and control other more abundant forms of energy. Here, a series of altitude dependent solar transformities were calculated for deep heat emanating from the surface of the continents and for the mass of material eroded from mountains. The new transformities and emergy per mass ratios will be useful for examining the spatial configurations of empower in mountain landscapes. 257

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.258 Methods Deep heat The transformity of deep heat flow at varying altitudes was calculated by dividing the total heat flow at elevation into the total empower supporting the world's geobiospheric processes (9.44 E24 sej y-l). The total heat flow at an elevation was found by multiplying the deep heat flux per area by the area of the globe above the given elevation. The area above an elevation was determined from the earth's hypsographic curve. A world hypsographic curve was interpolated from a graph in Duxbury and Duxbury (1991). The elevation gradient of deep heat flux was derived from the global heat flow database compiled by Pollack et al. (1991). The change in deep heat flux per change in elevation was found by pooling the 7200+ data points of the global heat flow database (pollack et al. 1991) into 500 m intervals from 0 to 4000 m. Pooling was necessary since the number of measurements at lower elevations drastically outnumbered the high elevation measurements. The arithmetic average of the observations made within each 500 m interval were plotted against the mid-elevation to develop a graph of deep heat flow as a function of altitude. Mountain Erosion The emergy per mass of mountain erosion was calculated for various altitudes by dividing the total empower supporting the world's geobiospheric processes (9.44 E24 sej y-l) by the total erosion above a given elevation (see Table E-2).). The total mountain erosion above an elevation was found by mUltiplying the erosion rate (mass/area/time) by

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.259 the area of the globe above the given elevation. The same area-elevation relationship was used for mountain erosion, as used for deep heat (see explanation in previous section). Results Deep heat The deep heat generated per unit area was found to increase 26.5 mW m-2 per km of elevation (Figure E-2). Elevation explained the majority (64%) of the variation in heat flow. The transformity of deep heat flow near sea level was 2.9 E4 sej/J, while at elevations of 1000 m it was twice that amount, 5.9 E4 sej/I (Table E-1). The highest peaks on earth (> 8000 m) had transformities on the order of 3 E7 sej/J. By comparison, Odum (1996) estimated that the mean transformity for continental deep heat was 3.4 E4 sej/J. The mean empower density of deep heat also increased with elevation (Table E-1). Mountain Erosion The emergy per mass of mountain erosion increased with altitude at an exponential rate (Figure E-3). For example, at an altitude of 1000 In, mountain erosion had a emergy per mass ratio of 1.9 E9 sej/g (Table E-2), while at 4000 In, the ratio was 14.2 E9 sej/g. The mean elevation of the Wme Spring Creek (WSC) watershed (1320m) was above the global mean (840m). The altitude-dependent solar transformity of deep heat at the mean elevation ofWSC was 7.5 E4 sej/I, double the 3.4 E4 sej/I used in the emergy evaluations. The empower density of the geologic work, calculated with the altitude-

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.dependent transformity, was 1020 E12 sej/haly. This was double the empower density estimated with the mean global transformity ofland deep heat. 260

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.t CD "0 ::l -1 Mountain ----------------------........ ---------......... .... -...... Earth Empower Heat Flux per year -....... '" ........ '-" \ ...... \ \ \ "-" \ \ \ \ \ \ \ + Transformity Increasing Mountain Energy Chain 261 Figure E-l. Diagram illustrating how total heat flow of the earth decreased with altitude. (Heat release per unit area increased slightly with altitude, see Figure E-2). The same solar empower was supporting heat flux at each thus the transformity of heat release increased with altitude.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.262 300 I 8.00 E I 200 I 6.00 <:-t N E < E --, 4.00 <0 ;;:: W -100 (tJ I CD t J: 2.00 0 I -0 1000 2000 3000 4000 5000 Elevation, m Figure E-2. Mean (+/-SEM; variable n) flow of deep heat versus elevation averaged over the globe. Heat flow, mW m-2 = 67.4 + O.0265*elevation (m).

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table E-I. Solar transformity and empower density of deep heat as a function of altitude. Transfonnity Area above Total heat of deep heat Empower given flow, at given density, elevation, Heat flow, 1x1012 elevation, 1x1012 Elev,m 1x109 m2 mW/m2 mW sej/J sej/ha/y A B C 0 E 0 149,984 69 10,349 28,924 629 100 135,049 72 9,676 30,936 699 500 88,733 82 7,298 41,015 1,064 1000 52,491 96 5,013 59,715 1,799 1500 31,051 109 3,3n 88,646 3,041 2000 18,368 122 2,241 133,5n 5,140 3000 6,428 149 955 313,599 14,688 4000 2,249 175 394 760,454 41,973 5000 787 202 159 1,887,318 119,945 6000 275 228 63 4,766,444 342,761 7000 96 255 25 12,202,555 979,491 8000 34 281 9 31,582.133 2,799,042 Footnotes to Table E-1 A Hypsographic curve of worfd estimated from figure given in Duxbury & Duxbury (1991). B Deep heat at elevation = 69 +(0.00265 x height,m) (see Figure E-2) C Total heat flow = Area x heat flow per area D Transfonnity of deep heat at given elevation = (Global emergy input,9.44x1024 sej/y) I (total heat flow, J/y) E Empower at given elevation = (Transfonnity, sej/J) x (heat flow, J/ha/y) Empower density = 62gexp(0.00105H); H is height in meters. 263

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.264 Table E-2. Solar emergy per gram of mountain erosion as a function of altitude. Area above Emergyper given Total gram above elevation, Denudation erosion, given elevation, Elev, m Ixl09 m2 rate, emllOOO Y Ixl01S g Ixl09 sej/g A B C D 0 149,984 1.1 4.3 2.2 1000 52,491 3.7 5.0 l.9 2000 18,368 6.2 3.0 3.2 3000 6,428 8.8 1.5 6.4 4000 2,249 11.3 0.7 14.2 5000 787 13.9 0.3 33.2 6000 275 16.4 0.1 80.1 7000 96 19.0 0.0 198.2 8000 34 Footnotes to Table E-2 A --Hypsographic curve of world estimated from figure given in Duxbury & Duxbury (1991). B --Denudation rate = (0.0001535 (mid-altitude) + 0.01088)/6. The equation, taken from Ahnert cited in Chorley et al. (1984) was divided by six (6) so that the total erosion of the earth would equal 9.5 EI5 gly, the total earth cycle. C Total erosion = (area, m"2) x (denudation rate, emlI000 y)/(lOOO y) x (2.6 E6 glm"3) x (1 m/100cm) D --Solar emergy per gram above given elevation = (Global emergy input,9.44xl024 sej/y) / (total erosion above given elevation, gly)

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.1000 F C 0 w 0 L-a> 100 -0 (/) (/) Ol m:::::,. E a> L-en 10 a>(J) a.w e> a> E 1 I t t a> I t I L-m 0 2000 4000 6000 8000 15 en Altitude m Figure E-3. Solar ernergy per gram of mountain erosion as a function of altitude. See Table E-2 for calculations. Solar emergy per mass (sej/g) = [O.694exp(7 E4)*A]*lE9; where A is altitude in meters, exp is base of natural logarithm. 265

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.APPENDIXF PROGRAM CODE FOR EXTEND BLOCKS USED IN SIMULATION MODELS This appendix contains the programming code for the Extend blocks (graphical user interface icons) used to simulate the models developed in this dissertation. 266

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Deep heat: (G) R4infall (R) I CONVERTER 1 \ "" :if <: I Export: lDeprecia" Figure F-1. Extend representation of model EMERGYDYN used for simulating the emergy and transformity of wood biomass for the Cow watershed (compare to systems diagram in Figure 3-7). 267

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Constant Code is 0; *. Array definition Constant Force is 1; Constant Flow is 2; Constant Transformity is 3; Real 0, dO, EM, clEM. km, kd, Variables for storage Inflowl, Infl0w2, Inflow3, Inflow4, InflowS, STI, ST2, STI, ST4, ST5, *. Variables for inflow Outflowl, Outflow2, Outflow3, Outflow4, ST,ST40, Variables for outflow Matteroutflow, STm.EC; Real ConlinarrayO, Con2inarray[), ConJinarray[J, Con4inarIayO, ConSinarray[J, Receivedlinarray[J, Received2inarray[], Received3inarray[], Received4inanay[J, Received5inarrayO, ConloutarrayO, Con2outanayO. ConJontamly[], Con4Oo1arrayO, Receivedloutarray[], Received2outanay[), Received3outarray[],Received40utarray[],Received5outarray[], Matteroutanay{], Sensoroutarray[]; .* Set initial values for the dialog on Createblock { } Fract = 0.01; Cahbstore = 100; Cahlxlrain = 5; Initstore = l; Inittransformity = 10000; Materialftaction = .01; emergyconserv = 0; *. Initialize any simulation variables. on Initsim { Q = Initstore; ST = Initttansformity; kd = Cahlxlrain I Cahbstore; km = Materialfraction kef; EM=ST*Q; Makearray(Conlinarray, 4); Conlinarray[Code] = -1; Conlinanay[Force1 = 0.0; Conlinanay[Flow] = 0.0; Conlinarray[Transformity1 = 0.0; Makearray(Con2inarray, 4); Con2inanay[Code] = -1; Con2inarray[Force] = 0.0; Con2inarray[FlowJ = 0.0; Con2inanay[Trnnsformity] = 0.0; Makeanay(ConJinarray,4); ConJinarray(Code] = -I; ConJinarray[Force] = 0.0; ConJinarray[FlowJ = 0.0; 268

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.} Con3inarray[Transformity] = 0.0; Makeanay(Con4inanay,4); Con4inarray[Code] = -1; Con4inanay{Force] = 0.0; Con4inarray[FIow) = 0.0; Con4inarray[Transformity) = 0.0; Makeanay(ConSinarray,4); ConSinarray[Code] = -1; ConSinarray[Force] = 0.0; ConSinanay[Flow) = 0.0; ConSinarray[Transformity) = 0.0; Makeanay(Conloutarray, 4); Con1outarray[Code] = -1; Conloutarray[Force] = 0.0; Conloutarray[FIow] = 0.0; Conloutarray[Transformity) = 0.0; Makeanay(Con2outarray, 4); Con2outarray[Code) = -1; Con2outarray[Force] = 0.0; Con2outarray[FIow1 = 0.0; Con2outarray[Transformity) = 0.0; Makeanay(Con3outarray,4); Con3outarray[Code] = -1; Con3outarray[Force) = 0.0; Con3outarray[FIow] = 0.0; Con3outarray[Transformity) = 0.0; Makeanay(Con4outarray, 4); Con40utarray[Code) = -1; Con40utarray[Force] = 0.0; Con4outarray[FIow1 = 0.0; Con40utarray[Transformity] = 0.0; Makeanay(Matteroutarray,4); Matteroutarray[Code) = -1; Matteroutanay[Force] = 0.0; Matteroutanay[FIow1 = 0.0; Matteroutanay[Transformity) = 0.0; Makearray(Sensoroutarray, 4); Sensoroutarray[Code) = -1; Sensoroutanay[Force) = 0.0; Sensoroutanay[Flow) = 0.0; Sensoroutanay[Transformity] = 0.0; Start simulation on Simulate { If (Getpassedarray(Conlin, Received 1 inanay) ) { 269

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.} Conlinanay[Code] = Receivedlinarray[Code]; Conlinarray[Flow] = Receivedlinarray[Flow]; Conlinarray[Transformity] = Receivedlinanay[Transfonnity]; If(Conlinarray[Code] = 1) OpendialogboxO; .* Code 1 is force. but should be Code 2 for flow If (Getpassedarray(Conlin, Received2inarray { } Con2inarray[Code] = Received2inarray[Code]; Con2inarray[Flow] = Received2inanay[Flow]; Conlinanay[Transformity] = Received2inarray[Transfonnity]; If(Con2inarray[Code] = 1) OpendialogboxO; ** code 1 is force but should be code 2 for flow If (Getpassedarray(Co03in, Received3inarray { } Con3inarray[Code] = Received3inarray[Code]; Co03inarray[Flow] = Received3inarray[Flow]; Con3inanay[Transformity] = Received3inarray[Transfulllrily]; If(Con3inanay[Code] = 1) OpendialogboxO; code 1 is force but should be code 2 for flow If (Getpassedarray(Con4in, Received4inarray { } Con4inarray[Code] = Received4inarray[Code]; Con4inarray[Flow] = Received4inarray[Flow]; Con4inarray[Transformity} = Received4inarray[Transformity]; If (Con4inarray[Code] = I) OpendialogboxO; code 1 is force but should be code 2 for flow If (Getpassedarray(ConSin, Received5inarray { } conSinarray[Code] = Received5inarray[Code]; ConSinarray[Flow) = Received5inanay[Flow]; ConSinarray[Transformity] = Received5inarray[Transformity]; If(ConSinarray[Code] = 1) OpendialogboxO; .* code 1 is force but should be code 2 for flow If (Getpassedarray(Conlout, Receivedloutanay Conloutarray[Flow] = Receivedloutarray[Flow]; If (Getpassedarray(Conlout. Received2outarray Conloutarray[FIow1 = Received2outaIIay[FIow); If (Getpassedarray(Con3out, Received3outarray 270

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.**Con3outarray[Code] = Received3outanay[Code]; Con3outarray[Flow1 = Received3outarray(Flow]; **Con3outarray[Trnnsformity1 = Received3outarmy[Transformity]; If (Getpassedarray(Con4out, Received4outanay { Con4outarray[F1ow] = Received4outarray[F1ow); Con4outarra:y[Transformity1 = Received4outanay[Transformity1; } If (Getpassedanay(Matterout, Received5outarray { Matteroutarray[F1ow] = Received5outarray[F1ow]; } If (Currentstep = 0) { } Conlinarray[Force] = Q; Conlinanay[Force] = Q; Con3inarray[Force] = Q; Con4inarray[Force] = Q; ConSinarray[Force1 = Q; Conloutan'ay[Code] = I; ** Code 1 is force out Conloutarray[Force] = Q; Conloutanay[Transformity] = ST; Con2outarray[Code] = 1; ** Code 1 is force out C0n2outarray{Force1 = Q; Con2outarray[Transformity] = ST; Con3outanay[Code] = 1; ** Code 1 is force out Con3outarray[Force] = Q; Con3outarray[Transformity] = ST; Con40utarray[Code] = 1; ** Code 1 is force out Con4outarra:y[Force] = Q; Con4outarray[Transformity] = ST; Matteroutarray(Code] = 1; ** Code 2 for flow out Matteroutarray[Force1 = Q; Matteroutarray[Transformity) = 0.0; Sensoroutarray(Code) = 1; Sensoroutarray[Force] = Q; Sensoroutarray[Transformity] = ST; Else { Inflowl = Conlinarray[Flow]; Inflow2 = Con2inarray[Flow]; Inflow3 = Con3iDarray[Flow]; Inflow4 = Con4iDarray[Flow); InflowS = ConSiDarray[F1ow]; Outflowl = Q*Conloutarray[F1ow]; 271

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.emtflow2 = emtflow3 = Outtlow4 = Matteroutflow = kd*Q; **MatteroutaIIaytflowJ; STm = EM I (Materialfraction Q); 212 dQ = Inflowl + Infl0w2 + Inflow3 + Inflow4 + InflowS -kd Q -Outflowl -0utfl0w2 -OutfIow3 -Outflow4-;*-MatterontfloW; Q = Q + dQ DeltaTune; If(Q<=O) { Q=O; } STI = Conlinarray[Transformity]; sn = Con2inarraytyransformityl; ST3 = ConJinarray[Transformityl; ST4 = Con4inarray(Transformity]; ST5 = ConSinarray[Transformity]; ST40 =Con4outarray(Transformity]; { ST40= ST; } If( emergyconserv) { EC=l; } If ( (dQ > 0) AND (dQ/Q> &act dEM= STlInflowl + ST2*Inflow2 + STI*Inf1ow3 + ST4*InfIow4 + STS*InflowS ST*OutfIowl ST*Outflow2 ST*Outtlow3 -EC*sr Outflow4: *. ST*matteroutfIow; elseif(dQ=O) dEM=O; else if dQ > 0) AND (dQ/Q < fract) ) dEM=O; else if dQ is negative dEM=ST*dQ; EM = EM + clEM Deltatime; If(EM<=O) EM=O.I; ST=EM/Q; EC=O; Conlinarray[Force1 = Q; Con2inarray[Force] = Q; Con3inarray[Force] = Q; Con4inarray[Force] = Q; ConSinarray[Force] = Q; Conloutarray[Code] = I; .* Code 1 is force out

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.} Conloutarray[Force] = Q; Conlootanay[F1ow] = outflowl; Conloutarray[Transfonnity] = ST; Con2ou1anay[Code] = I; ** Code I is force out Con2outarray[Force] = Q; Con2outarray[Transformity] = ST; Con3outarray[Code] = I; ** Code 1 is force out Con3outarray[Force] = Q; Con3outarray[Transformity] = ST; Con4outarray[Code] = I; ** Code I is force out Con40utarray[Force] = Q; Con4ootarray[Transformity] = ST; Matteroutarray[Code) = 1; ** Code 1 for force out Matteroutarray[Flow] = MatteroutfloW; Matteroutarray[Force] = Q; Matteroutarray[Transfonnity] = ST; ** DRT changed from STm on 8123/95 Sensoroutanay(Code] = 1; Sensoroutarray[Force] = Q; Sensoroutarray[ransformity] = ST; Conlin = Passanay(Conlinarray); Con2in = Passanay(Con2inarray); Con3in = Passarray(Con3inarray); Con4in = Passarray(Con4inarray); ConSin = Passarray(ConSinarray); Conlout = Passarray(Conloutarray); Con2out = Passarray(Con2outarray); Con3out = Passanay(Con3outarray); Con40ut = Passarray(Con40utarray); Matterout = Passarray(Matteroutarray); Sensorout = Passarray(Sensoroutarray); } ** If the dialog data is inconsistent for simulation. abort. on Checkdata { } If (Novalue(lnitstore abort; ** User clicked the dialog HELP button. on Help { showHelp(); } 273

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.APPENDIXG MISCELLANEOUS DATA TABLES AND EMERGY EVALUATIONS This appendix contains data tables and miscellaneous emergy evaluation tables. 274

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Trees Infrastructure ,Universi!l of Florida ArJ29retl{rJl ........ _. i .. Tilley I 1998. Figure G-I. Systems diagram of the environmental--economic interface of the UF Arboretum, Gainesville, Florida. VI

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.276 Table G-l. Emergy evaluation of the University of Florida Arboretum (2 ha; ca. 1993) Trans-Solar Macroeconomic Note Item Raw Units formity Emergy Value (sej/unit) 1 E14 sej/y (1990 US$) 1 Sunlight 9.15E+13 J 1 0.9 61 2 Rain Transpired 7.56E+IO J 18,200 13.8 917 3 Soil formation (erosion) 3.66E+1O J 34400 12.6 839 4 Water from irrigation 2.99E+09 J 160,000 4.8 319 5 Mulch 4.27E+1O J 17,200 7.3 489 6 Fuel for mowing 3.09E+1O J 66,000 20.4 1,361 7 Fertilizer Nitrogen 5832 g 3.45E+09 0.2 13 Phosphorus 2592 g 3.90E+09 0.1 7 Potassium 3240 g 2.96E+09 0.1 6 8 Fertilizer, $ pd. 107 $ 1.50E+12 1.6 107 9 Electricity for irrigation 2.79E+09 J 160,000 4.5 298 10 Electricity, $ pd. 120 $ 1.50E+12 1.8 120 II Herbicide, $ pd. 140 $ 1.50E+12 2.1 140 12 Start-up costs 600 $ 1.50E+12 9.0 600 13 Labels for trees 32 $ 1.50E+12 0.5 32 14 Human service Pruning 1600 $ 1.50E+12 24.0 1,600 Planting, irrigation, star 900 $ 1.50E+12 13.5 900 Administration 13000 $ 1.50E+12 195.0 13,000 Mowing 975 $ 1.50E+12 14.6 975 Sum of all items except 1 326 21,724 Footnotes to Table G-I (UF Arboretum) 1 SOLAR ENERGY Area of tree unit, ha = 2.0E+O Insolation @ ground = 6.IE+9 J/m"21yr Area planted, % = 75% estimated Energy(J)= (area)*(avg insolation) = <-m"2)*L-.J/m"2/y) = 91.5E+12 Transfonnity, defined as I. 2 Rain Transpired Rainfall, mly = 1.36 mean for North central Florida % as transpiration = 0.75 estimated Rain chemical energy used by trees (1) = (area)(transpiration rate)(Gibbs no.) = <-m"2)*L-.m)*(lOOO kgIm"3)*(4940 JIkg)

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.= 7.56E+IO Tranformity of average global rainfall (Odum, 1996) 3 Soil formation (erosion) Use the average empower density ofland throughout the globe (629 E12 sejlhaly). Use transformity of deep heat to calculated energy flow. 4 Water from irrigation According to Dr. Dehgan: 277 Trees are irrigated twice a week in summer (6 months) at a rate of 7.5 gallons per tree. Water used, J/y=(21wk)x(26wk1y)x(7.5gaVtree)x(3.79 Ugal)x(1000gIL)x(5J/g)x(405 trees) Water used, J/y = 2.99E+09 Tranformity of municipal water supplied by Gainesville Regional Utilities (A. Buenfil, dissertation forthcoming) 5 Mulch According to Dr. Dehgan: Mulch is applied at the base of the trees at a rate of 20 cu. Yd. Per year for whole unit. Mulch used, J/y = = (20 ydI\3/y)x(9 ftI\3/ydI\3)x(0.0283 m3/ftI\3)x(0.5E6 glm"3)x(4 kcallg)x(4l86J/kcal) Mulch used, J/y = 4.21E+ 10 Transformity is that calculated for Coweeta (this study). 6 Fuel for mowing According to Dr. Dehgan: Tree unit is cut once weekly in summer, once per two weeks in winter Gasoline usage rate, ga1Ih = 2 Mowing rate, acIh = 2 Energy used to cut grass, J/y = = (2 ha)x(39 #/yr)x(O.5 hr/ac)x(2.5 ac/ha)x(2 galIhr)x(3790 glgal)x(lO kcallg)x(4186 kcal) Energy used to cut grass, J/y = 3.0931E+ 10 Transformity is average for petroleum products (Odum, 1996) 7 Fertilizer According to Dr. Dehgan: Each tree receives 80 grams of 18-8-10 slow release ($75 per 50 lb. Bag) Therefore, total fertilizer used equals (80 glyltree)x(405 trees), gly = 32,400 Nitrogen 18% of total as N, g/y = 5832 Phosphorus 8% of total as P, g/y = 2592 Potassium 10% of total as K, g/y = 3240 Emergy per gram from Odum, 1996.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.8 S paid for fertilizer (fertilizer used per year)x(S75 per 50 lb bag) S pd = (32,400 gly)x(0.0022Ib/g)x(S751501b-bag) S pd per year = S107 9 Electricity for irrigation According to Dr. Dehgan: 278 A 5 hp pump is used 2 days per week in summer (6 months) for 4 hrs each day used. Electrical energy used, J/y = = (5 hp)x(1 kW/1.341hp)x(l000 W/kW)x(U/slW)x(52 #/y)x(4 hI#)x(3600 sib) Electrical energy used, J/y = 2.79E+09 Transformity is mean for coal-fired power plants (Odum, 1996) 10 Electricity, S pd. According to Dr. Dehgan: S10/month (SI0/month)x(12 monthsly) = 11 Herbicide, S pd. S120 According to Dr. Dehgan: one gallon of Round-up (SI40/gal) is used per year. S paid for herbicide per y = (SI40/gal)x(l gaIly) S140 12 Start-up costs According to Dr. Dehgan: A S20,000 grant was used to buy saplings and install irrigation. S10,000 worth of trees were donated. Assume project life of 50 yrs. Ammortized cost for start-up = (S30,00015Oy) = S600 13 Labels for trees According to Dr. Dehgan: One label per species was bought (S12 ea) and attached Assume project life of 50 yrs. (SI21Iabel)x(l label/species)x(135 species)/(50 y) = S32 14 Total labor Pnming Requires 2 days per year to prune crop. Dr. Dehgan and Dr. Black perfonn pruning. Dollar rate, Sib = 50 estimatM Labor for pruning, Sly = (2 people)x(2 dly)x(8 hld)x(S501b) Labor for pruning, Sly = SI,600 Planting, install irrigation, start-up maintenance Half-time employee for first three years

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Dollar rate, Sib = IS estimated Ammortize over SO y life of project Labor required, Sly = (1 person)x(IOOO bly)x(SI51b)x(3 y)/(5Oy) Labor required, Sly = S900 Administration Dr. Dehgan devotes S blwk to overseeing operation. Dollar rate, Sib = SO estimated Labor required, Sly = (l person)x(S blwk)x(S2 wk/y)x(SSOIb) Labor required, Sly = S13,OOO Mowing see fuels for mowing above. Labor required, Sly = (2 ha)x(39 #/y)x(O.5 blac)x(2.5 ac/ha)x(SlOlb) Labor required, Sly = S97S Data was supplied by Professor Bijan Dehgan, creator and administrator of the UF Tree Unit. Tree unit was established in 1993. It is located on SW 23 St., Gainesville, Fl. There are 135 North Central Florida. trees on 2 ha. 279

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table G-2. Evaluation of the water, and sediment of the continents. Discharge of Empower per Water suspended Precipitation suspended Area, 1000 runoff, sediment, Precipitation, empower, sediment, I E9 Continent kml\2 kml\3/y IE6 MT/y kml\3/y IE24 sej/y sej/g (1) (2) (3) (4) (5) (6) Europe 9800 2850 439 7540 0.68 1.55 Asia 40775 13560 10500 25700 2.31 0.22 Africa 29530 4110 988 21400 1.93 1.95 N. America 20060 7840 1100 16200 1.46 1.33 S. America 17800 11700 2440 28400 2.S6 1.0S Australia 7615 2370 197 3470 0.31 1.59 All continents 125580 42430 15664 102710 9.24 0.59 Footnotes to Table G-2 (1), (2), (3), & (4) from UNESCO, 1978. (S) Empower of precipitation, sej/y = (precipitation, kmI\3/y)x(lElSglkmI\3)x(9E4 sejlg) (6) Empower per sediment, sej/g = (empower of precipitation, sejly)/(sediment discharge, gly) (7) Suspended sediment per water runoff, sej/g = (sediment discharge, gly)/(water runoff, mI\3/y) Suspended sediment per water runoff, glml\3 154 774 240 140 209 83 369 N

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.9oo,--------------------------------. 8001 A 700 ] _to ai (") 600 J .5 =5 E 500 iL-C;, I en -400 1 I 'O-CD 5i -= 200 Aust. 8 100 Europe N.A. Asia. Africa S.A. 00 c 0 c:: 0.0 8 0.5 1.5 2.0 1.0 2.5 Empower of precipitation. 1 E24 sejly to C (") 1 ""","' ----------------------------------5i CD < B .5 -, 750 x Asia '0 a 500 t c:: .-0 -rn =c 250 1 en c:: LCD CD Globe x Africax E >k uro. Aust. x N.A. x S.A. 00 0 .2: c:: L-a o o o 5 10 15 20 Empower density. 1e14 sej/haly 3.0 Figure G-2. Concentration of suspended sediment in continental river discharge as a function of (a) total empower of continental precipitation and (b) empower density of continental precipitation. 281

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table G-3. Sediment and emergy budgets for the main river basins of N.C. based on historic, agriculture, and present day sediment Historic Mean Yield Mean Yield of Actual (Forested) of Sediment Sediment Historic Sediment if Sediment Sediment Sediment from Export (Forested) 100% Exported Historic exported If Actual Export Agriculture Rate from Sediment Agriculture from sediment Agriculture Sediment Rate a basins a Basin a Export Landuse Basin exported 100% exported Basin name Area, ha 9 m2 t1 1000 MT t1 Million EM$ I!er Cape Fear 2,430,056 8.6 63.0 21.0 209 1,531 510 139 1,021 340 Chowan 344,792 1.8 4.0 4.0 6 14 14 4 9 9 Chowan 264,425 1.8 4.0 15.0 5 11 40 3 7 26 French Broad 746,009 15.4 56.0 67.0 115 418 500 77 279 333 Hiawassee 127,152 15.4 38.0 24.0 20 48 31 13 32 20 Little Tennessee 434,487 15.4 56.0 175.0 67 243 760 45 162 507 lumber 841,069 1.8 4.0 4.0 15 34 34 10 22 22 Neuse 1,375,677 8.6 42.0 11.0 118 578 151 79 385 101 New 304,440 1.8 4.0 4.2 5 12 13 4 8 9 Pasquatank 277,682 1.8 4.0 15.0 5 11 42 3 7 28 Roanoke 900,900 8.6 88.0 4.2 77 793 38 52 529 25 Savannah 49,503 15.4 67.0 66.7 8 33 33 5 22 22 Tar-Pamllco 1,096,543 8.6 40.0 15.0 94 439 164 63 292 110 Upper Broad 386,882 15.4 98.0 137.0 60 379 530 40 253 353 Upper Catawba 871,534 15.4 98.0 133.0 135 854 1,159 90 569 773 Upper New 203,068 15.4 49.0 130.0 31 100 264 21 66 176 Watuaga 40,283 15.4 49.0 49.0 6 20 20 4 13 13 Yadkin--Pee Dee 1,901,906 15.4 105.0 19.0 294 1,997 361 196 1,331 241 Total 12,596,408 10.1 59.6 37.0 1270 7513 4663 847 5,009 3,109 a -Sediment yield rates based on Simmons, 1993. 4.66E+21 N 00 N

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table G-4. EmeIgy evaluation of North Carolina leaf tobacco, 1987. Traos-Solar Emdo1Iar Note Item Raw Units formity Emergy Value (sej/unit) (E20 sej) E6 1990 US$ 1 Sun 1.47E+19 J 1 0.15 10 2 Rain 9.97E+15 J 1.82E+04 1.81 117 3 Soil used 2.36E+15 J 6.34E+04 1.50 97 4 Gasoline 2.37E+15 J 5.30E+04 1.26 81 5 Diesel 3.64E+15 J 5.30E+04 1.93 125 6 Natural Gas 6.21E+14 J 4.80E+04 0.30 19 7 Other Fuels 2.37E+07 $ 1.80E+12 0.43 28 8 Electricity 6.26E+14 J 1.59E+05 0.99 64 9 Nitrogen Fertilizer 1.45E+l1 g 3.45E+09 4.99 322 10 Phosphate Fertilizer 1.45E+11 g 6.88E+09 9.95 642 11 Potassium Fertilizer 1.45E+ll g 2.96E+09 4.28 276 12 Agricultural Chemicals 5.24E+09 g 1.48E+I0 0.78 50 13 Machinery, Trucks 8.48E+09 g 6.70E+09 0.57 37 14 Machinery, Tractors 7.89E+09 g 6.70E+09 0.53 34 15 Machinery, Other 7.89E+08 g 6.70E+09 0.05 3 16 Buildings 1.77E+07 $ 1.80E+12 0.32 21 17 Labor, unskilled 2.81E+13 J 8.90E+06 2.50 162 19 Labor, Skilled 3.43E+13 J 2.46E+07 8.44 544 20 Research 1. 17E+ll J 3.43E+08 0.40 26 Sumof2-19 less 17 38.11 2459 21 Tobacco Produced 22 Traosformity of tobacco Footnotes for Table G-4 1 Sun Annual Energy = 3.18E+15 J 1.20E+06 = (1.18e6 ac)(0.4071 ba/ac)(1.1e6 kcaVm2Iy)(1e4 m2Jha)(81l2 y)(4186J/kcal) 1.47E+19I/y 2 Evapotranspiration Annual Energy = = (1.18e6 ac)(0.4071 ba/ac)(Ie4 m21ba) x (0.84m1y) x (1/2 y) x 4.94 E6I/m3) 9.97E+15 I/y 3 Soil used Erosion rate from cropland, MTlhaly = 7.5 (USDA 1977) Soil used, J/y = (area, ac)x(1 ha/2.47ac)x(7.5 MTlbaly)x(1.5 E6 g/MT)x(3% OM)x(3.5 kcaVg)x(4186 I/kcal) Soil used, J/y = 2.36E+ 15 283

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.4 Gasoline Annual Energy = (SI7.9e6/yr) I (S1.00/gal) x (1.25e5 Btu/gal) x (1.06e3 JIBtu) 2.31E+I5 J/y 5 Diesel Fuel Annual Energy = (SI7.3e6/yr) I (SO.70/gal) x (1.3ge5 Btu/gal) x (1.06e3 JIBtu) 3.64E+I5 J/y 6 Natural Gas Annual Energy = (S3.Ie6/yr) I (So. I 925/m3) x (36.4e3 Btu/m3) x (1.06e3 JIBtu) 6.2IE+14 J/y 7 Other Fuels Annual Dollars = 23.7e6 2.31E+07 S 8 Electricity Annual Energy = (S13.9e6/y) / (SO.081kwh) x (3.6e6 Jlkwh) 6.26E+14 J/y 9 Nitrogen Fertilizer Annual Mass Flow = (S69.4e6) x (1/3) I (SI601MT) x (le6 g!MT) 1.45E+ 11 g/y 10 Phosphate Fertilizer Annual Mass Flow = (S69.4e6) x (1/3) I (SI601MT) x (1e6 gIMT) 1.45E+ 11 g/y 11 Potassium Fertilizer Annual Mass Flow = (S69.4e6) x (1/3) I (SI601MT) x (1e6 gIM1) 1.45E+ 11 g/y 12 Agricultural Chemicals Annual Mass Flow = ($41.5e6) I (S3.6/lb) x (454.5 glIb) 5.24E+09 g/y 13 Machinery, Trucks Annual Mass Flux = (31,096 trucks) x (6000 Ibltruck) x (454.5 glIb) x (1/10) Assume truck lifespan = 10 yrs 8.48E+09 g/y 284

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.14 Machinery, Tractors Annual Mass Flux = (43,404 tractors) x (8000 lbltract.) x (454.5 glIb) x (1120) Assume tractor lifespan = 20 yrs 7.89E+09 gly 15 Machinery, Other Annual Mass Flux = 16 Buildings 7.89E+OS g/y (Assume equals 10010 of Tractor mass) Assume buildings have lifespan of 30 years 1987 buidings = $5.3e8 1.71+07 $ 17 Labor, unskilled Annual Labor Costs = $94.0e6 Average Wage Rate = $8.001hr Assume Work Period = 5 months @ 40 hr/wk Number of Workers = ($94e6/yr) f ($S.OO/hr) 1800 hrfworker-year Number of Workers = 14,688 Annual Energy = (# of Workers) x (2500 kcaVd) x (4186 IIkca1) x (183 dly) Annual Energy, Ify = 2.81E+ 13 19 Labor. Skilled Skilled Labor Base on Owners Time # of Owners = 17911 Annual Energy = (# of Owners) x (2500 kcaVd) x (4186 Ilkcal) x (183 dly) 3.43E+13 I/y 20 Research Total Research for U.S. = 87.3 Scientist-yrs N.C. Tobacco Production = 35% of U.S. Total Annual Energy = (# of Scientists) x (2500 kcalld) x (4186 J/kcal) x (365 dIy) x (35%) 1.11+11 Ify 21 Tobacco Production Production, gly = 2.11+ 11 Energy, Ily = ( g/y)x(3.5kcaIlg)x(4I86IIkca1) Energy. Ily = 3.I8E+15 22 Transformity of N.C. Leaf Tobacco Total emergy inputs (sum of2 through 191ess 17) divided by tobacco production 285

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Table G-5. Computation of North Carolina trade in manufactured goods. U.S. per N.C. per US mean Standard U.S. N.C. capita capita N.C. exports value of Industrial Production Production production, production, (imports), shipment N.C. exports Classification labor-hours labor-hours labor-hours labor-hours 1000 labor-per prod. (imports), $ code DescriEtion (1000's) (lOOO's) per person per person hours per year hour, SIhr per year 20 Food and kindred products 2,245,400 76,400 8.8 11.2 16,170 181 2.93E+09 21 Tobacco Products 51,300 21,700 0.2 3.2 20,324 686 1.39E+1O 22&23 Textile Mill products & apparel 2,593,800 451,500 10.2 66.0 381,925 55 2.09E+l0 24,25,26 Lumber, furniture, paper 2,858,500 219,500 11.2 32.1 142,825 90 I. 29E+l 0 27 Printing & publishing 1,564,300 32,600 6.1 4.8 .9,360 107 -9.98E+08 28 Chemicals 1,007,700 49,200 4.0 7.2 22,170 303 6.72E+09 29 Petroleum & coal products 165,400 1,100 0.6 0.2 -3,337 907 -3.02E+09 30 Plastics 1,412,200 62,000 5.5 9.1 24,120 80 I. 94E+09 32 Stone, clay, glass 742,500 30,400 2.9 4.4 10,484 84 8.81E+08 33,34 Primary and fabricated metals 2,744,200 67,700 10.8 9.9 ,909 90 -5.31E+08 35,36,37,38,39 Machinery, Electronics, transport. Equipment, Instruments 7,657,700 203,600 30.0 29.8 -1,807 137 -2.47E+08 Total 23.0E+6 1,215,700 90.4 177.7 597,605 127 5.54E+1O N

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.REFERENCES API, 1989. American Paper Institute's annual report. Ashton, P.S., 1964. Ecological studies in the mixed dipetrocarp forest of Brunei State. Clarendon Press, Oxford. Baas, P., K. Kalkman, and R. Geesink, 1990. The plant diversity ofMalesia. Kluwer Academic, Dordecht. 420 pp. Barry, R.G. & R.I. Chorley, 1992. Atmosphere, weather and climate. 6th eel. Routledge, London. 392. pp. Beyer, F., 1991. North Carolina: the years before man, a geologic history. Carolina Academic Press, Durham, NC. 244 pp. Boggess, C.F., 1995. The biogeoeconomics of phosphorus in the Kissimmee Valley. Ph.D. dissertation, University of Florida, Gainesville. 234 pp. Boring, L.R., C.D. Monk, and W.T. Swank, 1981. Early regeneration ofa clear-cut southern Appalachian forest. Ecology 62(5):1244-1253. Boring, L.R., W.T. Swank, and C.D. Monk, 1988. Dynamics of early successional forest structure and processes in the Coweeta basin. In: Forest hydrology and Ecology at Coweeta, W.T. Swank and D.A Crossley, Ir. (eds). Springer-Verlag, New York, NY. Brown, M.I., 1990. North Carolina's Forests. USDA, Forest Service, Southeastern Forest Experiment Station, Asheville, NC. Resource Bulletin, SE-142. Brown, M.T. and R.A Herendeen, 1996. Embodied energy analysis and emergy analysis: a comparative view. Ecological Economics 19:219-235. Brown, M.T. and S. Ulgiati, 1999. Emergy evaluation of natural capital and biosphere services. Ambio (in press) Buranakarn, V., 1998. Evaluation fo recycling and reuse of building materials using the emergy analysis method. PhD. dissertation, University of Florida, Gainesville. 258pp. 287

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Odum, liT., C. Diamond, and M-T. Brown, 1987. Energy systems overview of the Mississippi River Basin. Center for Wetlands Publication #87-1, University of Florida. 107 pp. Odum, H.T., M.S. Romitelli, and R. Tighe, 1998. Evaluation overview of the Cache River and Black Swamp in Arkansas. Final report to Waterways Experiment Station, U.S. Dept. of Anny, Vicksburg, MS. 127 pp. 292 Orrell, J.J., 1998. Cross scale comparbon of plant and production diversity. M.S. thesis, University of Florida, Gainesville. 159 pp. Paces, T., 1986. Rates of weathering and erosion derived from mass balance in small drainage basins. In: Rates of Chemical Weathering of Rocks and Minerals, Colman, S.M.. and D.P. Dethier, eds. Academic Press, Orlando, FL 603 pp. Paijmans, K., 1970. An analysis offoUT tropical rain forest sites in New Guinea. J. EcoL 58(1):77-101. Parker, N. 1998. Spatial models of total phosphorus loading and landscape development intensity in a north Florida watershed. M..E. thesis, University of Florida, Gainesville. 123 pp. Peixoto, J.P. and AH. Oort, 1996. The climatology of relative humidity in the atmosphere. J. Clim. 9{l2):3443-3463. PoUack, H.N., S.l Hurter, and J.R Johnson, 1991. A new global heat flow compilation. Department of Geological Sciences, U. of Mich. Ann Arbor. Romitelli, M.S., 1997. Energy analysis of watersheds. Ph.D. dissertation, University of Florida, Gainesville. 292 pp. Romitelli, M.S. and Odum, H.T., 1996. Energy analysis of Coweeta River basin, N.C. Final report to the U.S. Dept. of Agriculture Coweeta Hydrologic Laboratory, Otto, NC. Rosen, RD., D.A. Salstein, J.P. Peixoto, 1979a. Variability in the annual fields of large scale atmospheric water vapor transport. Monthly Weather Review 107:26-37. Rosen, RD., D.A. Salstein, J.P. Peixoto, 1979b. Streamfunction analysis ofinterannuaI variablitliy in large-scale water vapor flux. Monthly Weather Review 107: 16821684. Scatena, F.N., 1995. The managenment ofLuquiIlo elfin cloud forest ecosytems: Irreversible decisions in a nonsubstitutable ecosytem, pp. 296-308. In: Tropical montane cloud forests. Hamiltion, LS., 10. Juvik, and F.N. Scatena (eds). Springer-Verlag, New York. 407 pp.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.293 Sclater, JG, C Jaupart, and D. Galson, 1980. The heat flow through oceanic and continental crust and the heat loss of the earth. Reviews of Geophysics and Space Physics, 18(1):269-311. Sheffield, RM. and H.A. Knight, 1986. North Carolina's forests. Resource bulletin SE88. US Department of Agriculture Forest Service, Southeastern Experiment Station. Asheville, NC. Sikich, S.W., P.A Carpenter IlL L.S. Wiener, 1992. Annual Report North Carolina. U.S. Dept. of Interior, Bureau of Mines. Simmons, C.E., 1993. Sediment characteristics of North Carolina Streams, 1910-19. USGS Water Supply Paper 2364. Singh, J.S., S.P.Singh, AK. Saxena and Y.S. Rawat, 1984. The forest vegetaion of Silent Valley, India, pp. 25-52. In: Tropical rain-forest: The Leeds symposium, A.C. Chadwick and SL Sutton (ed). Leeds. Smith, D.L., R.G. Gregory, and J.W. Emho( 1981. Geothennal measurements in the Southern Appalachian Mountains and Southeastern Coastal Plain. Amer. J. Sci., 281, 282-298. Smith, D.L., R.G. Gregory, and M.J. Garvey, 1918. A thermal reconnaissance of Georgia heat flow and radioactive heat generation. GeoL Surv. of Georgia Bull., 93, 93104. Southern Appalachian Assessement, 1996. Southern Appalachian Man and the Biosphere Program, Norris, TN. Springer, AM., 1986. Industrial environmental control: pulp and paper industry. John Wdey, New York. pp. 430 Steer, H.B., 1948. Lumber production in the U.S. 1199-1946. U.S. Department of Agriculture, Miscellaneous Publication #669. Swaney, D.P., 1918. Energy analysis of climatic inputs to agriculture. MS thesis, University of Florida, 198 pp. Swank, W.S., 1998. Wine Spring Creek ecosystem demonstration project. North American Forestry Research Conference. Raleigh, NC. Swank, W.S. and D.A Crossley, 1988. Forest hydrology and ecology at Coweeta. Springer-Verlag, New York. 469pp. Swift, L.W., G.B. Cunningham, and J.E. Douglass, 1988. Climatology and hydrology pp. 35-55. In: Forest hydrology and Ecology at Coweeta, W.T. Swank and D.A Crossley, Jr. (eds). Springer-Vedag, New York.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Swift, L.W. and W.T. Swank, 1981. Long term responses of streamflow following clearcutting and regrowth.. Hydrological Sciences Bulletin 26(3):245-256. 294 Tilley, D.R., 1996. Benefits ofecologicaIly engineered stormwater management systems in urban watersheds south of Miami, Florida. M.E. thesis, University of Florida, Gainesville. 206 pp. Timber Mart-South, 1997. Stumpage and F.O.B. Price mart. Daniel B. Warnell School of Forest Resources, University of Georgia. Athens. Ulrich, A.H., 1990. U.S. timber production, trade, consumption, and price statistics 196088. USDA Forest Service, Miscellaneous Publication No. 1486. Washington. 80 pp. Ulrich, L.L., 1989. Raw water treatment, pp. 1-6. In: Water supply and treatment, 2nd ed. J.G. Walters, ed. TAPPI, Atlanta, GA pp.87. UNESCO, 1978. World water balance and water resources of the earth, UNESCO studies and reports in hydrology 25,1978. United Nations. U.S. Bureau of Mines, 1992. Annual Report of North Carolina. U.S. Geologic Survey. U.S. Census Bureau, 1992. Economic Census:Census of Manufactures, Department of Commerce. Washington, DC. U.S. Department of Commerce, Burea of the Census. http://www.doc.gov/ USDA, 1996. Soil survey of Macon County, North Carolina. Natural Resources Conservation Service, Washington, DC. U.S. Forest Service, 1995. Wme Spring Creek Ecosystem Management Project: Summary of research results. Coweeta Hydrologic Laboratory, Otto, NC. U.S. Forest Service, 1999. Southern Research Station, Forest Inventory and Analysis. http://www.srfia.usfs.msstate.edu! U.S. Travel Data Center, 1996. Impact of travel on state economies, 1994. Research Dept. of Travel Industry Assoc. of America. Velbel, MA, 1985. Geochemical mass balances and weathering rates in forested watersheds of the southern Blue Ridge. Am. J. Sci. 285:904-930. Velbel, MA, 1988. Weathering and soil-forming processes. In: In: Forest hydrology and Ecology at Coweeta, W.T. Swank and D.A. Crossley, Jr. (eds). Springer-Vedag, New York. Vose, J.M., W.T. Swank, B.D. Clinton, J.D. Knoepp, L.W. Swift, 1999. Using stand replacement tires to restore southern Appalachian pine-hardwood ecosystems:

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.effects on mass, carbon. and nutrient pools. Forest Ecology and Management 114:2-3( 215-226) Whisnant, D .E., 1994. Modernizing the Mountaineer: people, power, and planning in Appalachia. Rev. ed. Univ. of Tennessee Press, Knoxville. 310 pp. 295 Whitmore, T.C. (ed), 1984. Tropical rain of the Far East (2 ed). Clarendon Press, Oxford, 352 pp. Whitmore, T.C. and K. Sidiyasa, 1986. Composition and structure ofa lowland rain forest at Toraut, northern Sulawesi. Kew Bulletin 41(3):747-756.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.BIOGRAPIDCAL SKETCH David Rogers Tilley was born in Greensboro, NC, the 31 st day of January, 1969. He attended Oak Ridge Elementary, Northwest Guilford Junior High and Northwest Guilford Senior High, all located in Guilford County, NC. In 1987, David entered the College of Engineering at North Carolina State University in Raleigh. While in school he participated in the cooperative education program, working as an industrial engineer first at Thomasville Furniture Industries in Thomasville, NC and then at Phillip Morris, U.S.A. in Richmond, VA. He received a B.S. in industrial engineering and a B.S. in furniture manufacturing and management in December 1992. David held a management engineering position with Cape Fear Valley Medical Center in Fayetteville, NC after graduating from NCSU. Exposure to systems engineering and computer simulation modelling during David's undergraduate education and his fascination with nature combined to inspire his interest in ecological and general systems. David received his M.E. in environmental engineering from the University of Florida with an emphasis in systems ecology in August 1996. From 1996 to 1999 David pursued his doctoral degree in the systems ecology program of the Department of Environmental Engineering Sciences at the University of Florida. After graduation, David took a position as an assistant professor of environmental engineering at Texas A&M Kingsville. 296

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.I certifY that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of PhilOSOPhy .. /-. Mark T. Brown, Chair Assistant Professor of Environmental Engineering Sciences I certifY that I have read this study and that in my opinion it confonns to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Howard T. Odum Graduate Research Professor Emeritus of Environmental Engineering Sciences I certifY that I have read this study and that in my opinion it confonns to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Clay L. ontague Associ te Professor of Engineering Sciences I certifY that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and Huality, as a dissertation fur the degree of Doctor U '= Clyde Kiker Professor of Food and Resource Economics I certifY that I have read this study and that in my opinion it confonns to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy.

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.This dissertation was submitted to the Graduate Faculty of the College of Engineering and to the Graduate School and was accepted as partial fulfillment of the requirements for the degree of Doctor of Philosophy. August, 1999 L o ___ WInfred M. Phillips Graduate School