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Areal Empower Density and Landscape De velopment Intensity (LDI) Indices for Wetlands of the Bayou Meto Watershed, Arkansas Report Submitted to the Arkansas Soil and Water Conservation Commission Under the Sub-grant Agreement SGA 104 by M. Benjamin Vivas and Mark T. Brown Howard T. Odum Center for Wetlands University of Florida Gainesville, Florida 32611-6350 October 2006

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ii ACKNOWLEDGMENTS This study was supported through a sub-gr ant agreement (SGA 104) between the Arkansas Soil and Water Conservation Co mmission (ASWCC) and the University of Florida’s Howard T. Odum Center fo r Wetlands (UF-CFW). The ASWCC was the recipient of a grant from the United States Environmental Protection Agency (Grant # AW9761901) used in the implementation of the project. Dr. Mark T. Brown was principal investigator. Staff from the Arkansas Multi Agency Wetland Planning Team (MAWPT) provided support for this resear ch; particularly Elizabeth O. Murray, Coordinator of the MAWPT, w ho provided technical and logi stical support in the field, reviewed partial results, ma de recommendations to improve project performance, and supplied spatial and field data that were critical for the completion of the project. Acknowledgment is due to Tom Foti from the Arkansas Natural Heritage Commission (ANHC) for his assistance in se lecting the wetland study sites. Hans Haustein, GIS Planner from Metroplan provided zoning data for three urban areas in the study area. Mauricio Arias from the UF-C FW provided assistance in GIS analysis.

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iii TABLE OF CONTENTS Page ACKNOWLEDGEMENTS................................................................................................ii LIST OF TABLES...............................................................................................................v LIST OF FIGURES...........................................................................................................vi EXECUTIVE SUMMARY..............................................................................................vii CHAPTER 1 INTRODUCTION AND OVERVIEW................................................................1 Previous Studies Using Landscape Development Intensity...............................3 Project Overview...............................................................................................5 2 METHODS...........................................................................................................8 Study Area.........................................................................................................8 The State of Arkansas..................................................................................8 The Bayou Meto Watershed........................................................................8 Emergy Evaluations of Arkansas and Land Uses in the Bayou Meto Watershed........................................................................................................10 Land Use Areal Empower Densities................................................................10 Land Use / Land Cover (LU/LC) Data......................................................10 Definition of Land Use Categories: aggregations and disaggregations.....11 Areal Empower Densities..........................................................................14 LDI Index for Study Wetlands at Four Spatial Scales.....................................16 Selection of Wetlands Sites.......................................................................16 Spatial Areas of Influence..........................................................................16 Delineation of Drainage Basins.................................................................17 Landscape Development Intensity Index...................................................20 Analysis of Relationships between the LDI and Wetland Condition........21 3 RESULTS...........................................................................................................23 Land Use / Land Cover of the Bayou Meto Watershed...................................23 Emergy Evaluation of Selected Land Uses......................................................23 LDI and Wetland Condition.............................................................................27

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iv LDI Scores for Study Wetlands.................................................................27 Wetland Condition Indices for Wetland Study Sites.................................31 Relationships between the LDI and Measurements of Wetland Condition.....31 4 SUMMARY AND DISCUSSION.....................................................................40 Land Use Land Cover Data Sources................................................................42 Areal Empower Densities for Land Uses ........................................................44 A Landscape Assessment of Wetland Ecological Condition...........................45 Conclusions......................................................................................................46 LIST OF REFERENCES...................................................................................................48 APPENDIX EMERGY EVALUATIONS OF THE STATE OF ARKANSAS AND LAND USES OF THE BAYOU METO WATERSHED.................................................A-1 Introduction...................................................................................................A-1 Emergy and Emergy Analysis .....................................................................A-1 Background of Previous Studies using Emergy.................................................A-6 Methods.........................................................................................................A-7 Energy System Diagramming............................................................................A-7 Emergy Tables...................................................................................................A-8 Data Sources....................................................................................................A-10 Results.........................................................................................................A-11 Emergy Evaluation of Arkansas.................................................................A-11 Emergy Evaluation of Resource Basi s for the State of Arkansas...........A-28 Emergy Evaluation of Land Uses of the Bayou Meto Watershed .........A-30 List of References.......................................................................................A-94

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v LIST OF TABLES Table Page 2-1 Level 2 category codes and labels for the 1999 AR-LU/LC coverage .................12 2-2 Development intensity land use categories and definitions...................................15 2-3 Summary information for the Bayou Meto Wa tershed forested wetlands study.......................................................................................................................18 3-1 Areal empower density for land use classes in the Bayou Meto Watershed.........25 3-2 Non-renewable and purchased areal em power density and LDI index scores for 29 forested floodplain wetlands.......................................................................29 3-3 Summary of LDIs and wetland condition indices for a priori classes..................31 3-4 Final scores for three measuremen ts of wetland condition for the sample floodplain wetlands................................................................................................33 3-5 Spearmans correlations (r) between the LDI and measurements of wetland condition for the sample floodplain wetlands ca lculated at four different spatial scales...........................................................................................................34

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vi LIST OF FIGURES Figure Page 2-1 Location of the Bayou Me to Watershed, Arkansas.................................................9 2-2 Approximate location of the Bayou Meto watershed forested wetland study sites...............................................................................................................17 2-3 Landscape scales used to calculate LDI values for the study wetlands.................19 3-1 Base map of LU/LC classes for the BMW used to identify functional LDI-LU/LC classes................................................................................................24 3-2 Non-renewable and purchased areal empower density for the Bayou Meto Watershed..............................................................................................................26 3-3 Scatter plots of study wetland LD I indices at various scales ................................30 3-4 Scatterplots showing the relationship between the LDI a nd the WRAP for four different spatial scales....................................................................................35 3-5a Scatterplots showing the relati onship between the LDI and the HGM hydrological category for four different spatial scales..........................................36 3-5b Scatterplots showing the relati onship between the LDI and the HGM biogeochemical category for four different spatial scales.....................................37 3-5c Scatterplots showing the rela tionship between the LDI and the HGM biogeochemical category for four different spatial scales.....................................38 3-6 Scatterplots showing the relationship between the LDI a nd the UMAM for four different spatial scales....................................................................................39

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vii Areal Empower Density and Landscape De velopment Intensity (LDI) Indices for Wetlands of the Bayou Meto Watershed, Arkansas EXECUTIVE SUMMARY A primary goal of United States Envi ronmental Protection Agency’s National Wetland Program is to report on the ecologica l condition of the wetlands in the nation (USEPA 2003). A successful wetland monitori ng program might include landscape-level assessments (Level 1), rapid assessments th rough on-the-ground surveys (Level 2), and intensive field surveys (Brooks et al. 2004, Fenessy et al. 2004). Level 1 assessment methods are designed to provide informati on on the condition of wetlands relying on remote-sensing imagery and Geographic Inform ation Systems (GIS). These may include information from the National Wetlands Inventory (NWI), synoptic assessments (Brooks et al. 2004), and various indi ces of landscape disturbance. The Landscape Development Intensity (LDI) index (Brown and Vivas 2005) is an example of a Level 1 assessment method. It is a measure of human activity based on a development intensity measure that is derived from non-renewable energy use in the surrounding landscape. The LDI index has been used to predict ecosystem condition based on the intensity of human activities in the surrounding landscape and under the premise that ecological communities are affected by the direct, secondary, and cumu lative impacts in th e surrounding landscape (Brown and Vivas 2005). The first objective of this research was to compute areal empower densities for land use classes of the Bayou Meto Watershed (BMW) in Arkansas, using existing land

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viii use/land cover (LU/LC) data. Areal empower de nsity was computed for a total of 20 land use types using a modified version of th e method originally proposed by Brown and Vivas (2005). Values for the non-renewable a nd purchased areal empower density varied for land use types between 5.75 E15 sej/ha/ yr for open space/recreational lands and 6289.55 E15 sej/ha/yr for high-density multiple residential areas. The average areal empower density for the BMW was 61.47 E15 sej/ha/yr. The largest areal empower densities occurred in the urban areas in the northern portion of the watershed. The middle and southern portions of the BMW were dominated by intermediate areal empower densities that characterize ag ricultural lands. In general, non-renewable and purchased areal empower density values for land uses in Arkansas were in agreement with those reported elsewhere (Odum et al. 1998) and Florida (Brandt-Williams 2001, Brown and Vivas 2005). A second objective of this study was to calcu late LDI scores for floodplain forested wetlands in the BMW. A total of 29 wetlands we re investigated, and were selected from within various landscape setti ngs including natural, agricult ural, and urban land uses. The a priori selection of wetlands provided a range of landscapes that represented a gradient from undeveloped to highly developed lands Wetlands within natu ral landscapes (n = 12), generally exhibit non-renewable and purchased areal empower densities of 0.00 sej/ha/yr to 3.00 E15 sej/ha/yr, which are characteristic of natural lands. For wetlands within agricultural landscapes (n = 9), em power density values ranged between 7.40 E15 sej/ha /yr and 26.71 E15 sej/ha /yr. Wetlands within ur ban landscapes (n = 8) were characterized by areal empower density values between 342.80 E15 sej/ha /yr and 1910.85 E15 sej/ha /yr.

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ix The final objective was to correlate th e LDI scores with three independent measures of wetlands condition: the Wetland Rapid Assessment Procedure (WRAP) used in South Florida, Hydrogeomorphic Functiona l Capacity Indices (HGM), and the Florida Department of Environmental Regulati on’s Uniform Mitigation Assessment Method (UMAM). Correlation between the LDI and the WRAP was highly signif icant, especially when the LDI was estimated for an area of 300 meters around the wetland study plots (Spearman’s r = -0.81). The strongest corr elation between the LDI and the HGM was reported for the habitat index and also fo r the 300-meter area immediately surrounding the study plots (Spearman’s r = -0.73). The UM AM had the weakest co rrelation with the LDI (Spearman’s r = -0.50), with very simila r results for all four landscape scales considered. The main findings of this research, which constitute a contribution to the development of a landscape procedure for the assessment of we tland ecologic condition in the BMW, can be summarized in three main points: 1. Since the existing LU/LC coverages for the BMW (and for the state of Arkansas) were developed with different goals in mind than those for this research, identifying a set of LU/LC classes that satisfies the requirements for the calculation of areal empower densiti es may require extensive spatial data manipulation to identify func tional LDI classes. To that end, we are providing a set of 20 LDI classes with their co rresponding non-renewable and purchased areal empower density values that ma y be used in other regions within Arkansas for similar studies.

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x 2. The LDI index showed fair to good co rrelations with three multivariate independent measures of ecosystem condition for wetlands, confirming the validity and usefulness of the LDI. 3. Correlations between the LDI and the WRAP and between the hydrological and habitat categories of the HGM were hi ghest when the LDI was calculated for the area immediately surrounding wetland study plots, initially suggesting that a landscape assessment of wetlands conditi on using the LDI may only need to consider the impact caused by the neares t land uses over other more distant land uses.

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1 CHAPTER 1 INTRODUCTION AND OVERVIEW The United States Environmental Protect ion Agency (USEPA) has recognized three categories of wetland assessment pro cedures that can be used to assess the ecological condition of wetlands. The criteria fo r the three different assessment levels are determined based on the scale and intens ity of the assessment method, ranging from landscape-scale computer-based analyses to intensive field samp ling of biological, physical, and chemical measures. The three pr ocedures are describe d as Landscape Scale Assessment (Level 1), Rapid Field Methods (Level 2), and Intensive Biological and Physico-Chemical Measures (Level 3) (Fennessy et al. 2004). The assessment of the ecological conditi on of wetlands based on the landscape approach is usually carried out using a Geogr aphic Information System (GIS) and remote sensing data. It may also include the use of various indices of landscape composition and configuration and indices of landscape development intensity. The Landscape Development Intensity (LDI) index (Brown a nd Vivas 2005) is an example of a Level 1 assessment method. The LDI index (referred to as “LDI”) is a measure of human activity based on a development intensity measure that is derived from non -renewable energy use in the surrounding landscape. The LDI has b een used to predict ecosystem condition based on the intensity of human activities in the su rrounding landscape and under the premise that ecological communities are affected by the direct, secondary, and cumulative impacts in the surrounding landscap e (Brown and Vivas 2005). Examples of

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2 the application of the LDI are Lane (2003), Fore (2004; 2005), Reiss (2004; 2006), Reiss and Brown (2005), Surdick (2005), and Mack (2006). The metric used in the LDI to quantify human activity is emergy use per unit area per time (or areal empower density). Emergy is an expression of all of the energy used in the work processes that generate a product or service, in units of one type of energy. The solar emergy of a product is the emergy of the product expressed in equivalent solar energy required to generate it (Odum 1996). The units of emergy are emjoules (for emergy joules) and the units of solar emergy are solar emjoules (abbreviated sej). Areal empower density (usually expressed as solar emergy per hectare per year [sej/ha/yr]) is calculated as average values for land use cate gories. Since the LDI is a measure of human activity, non-renewable energies are the primar y source of areal empower density used in the calculation of the index. The LDI scale encompasses a gradient from undeveloped to highly developed land use intensity. Landscapes dominated by more intense activities such as commercial, industrial, and multi-fam ily residential land uses receive higher LDI scores. Less developed lands and rural areas dominated by areas of forests, wetlands, and open lands receive a lower LDI score. The LD I score does not account for any individual causal agents directly, but instead represen ts the combined actions of air and water pollutants, physical damage, changes in the suite of environm ental conditions (e.g., groundwater levels and increased flooding), or a combination of such factors, all of which enter the natural ecol ogical system from the su rrounding developed landscape (Brown and Vivas 2005).

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3 Previous Studies Using Landscape Development Intensity Emergy flows are organized hierarchically into spatial patterns with emergy flows per area more concentrated in hierarchical centers such as cities (Brown 1980; Odum 1996). Based on this observation, Brown and Viva s (2005) suggested that the impacts of human activities might be related spatially to the intensity of ener gy use and that areal empower density might serve as a measure of the level of human-induced impacts on ecological systems. Using land use data a nd areal empower density for land uses in Florida, Brown and Vivas (2005) computed LD I indices for watersheds and related them to water quality data and measures of wetland condition. Parker (1998) used preliminary versions of the LDI based on physical and emergy measurements to correlate them with model results from a spatial pollutant model for total phosphorus (TP) for sub-watersheds of the St. Marks Watershed in Northern Florida. The LDIs showed a good amount of association with the TP loads above background levels, particularly an impervi ousness LDI and the empower density LDIs. This study showed that despite the fact th at predicting TP loads at low-development intensities are difficult, at higher levels of human development the LDI in its various forms may be a good predictor of nutrients accumulation that can result from more intense human activities. Cohen et al. (2004) used the LDI cal culated by Brown and Vivas (2005) as a measure against which an expert-based flor istic quality assessment index (FQAI) could be compared and provide evidence of its im portance in the assessment of the ecological condition of small isolated herbaceous wetland systems. Strong associations between the LDI and the FQAI provided evidence of the rele vance of the floristic index for biological assessment studies and the LDI as a meas ure of the human disturbance gradient.

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4 Using the LDI, Lane (2003) developed thre e indices as quantit ative measures of biological integrity based on measurable attributes of diatoms, macrophytes, and macroinvertebrates for isolated herbaceous de pressional wetlands in Florida. Similarly, Reiss (2004) developed a Wetland Condition I ndex (WCI) using measurable metrics for the same groups of organisms for isolated fo rested wetlands in Flor ida; Reiss and Brown (2005) developed a Florida Wetland Conditi on Index (FWCI) for forested strand and floodplain wetlands. In all three cases the LDI was used as the human disturbance gradient along which the change in the composition of biological communities of wetlands were evaluated. Fore (2004, 2005) used modified versions of the LDI to assess the biological condition of str eams and lakes in Florida. Surdick (2005) analyzed how human land uses of varying intensities surrounding isolated forested wetlands in Florida a ffect the species composition of birds and amphibians. A strong relationship between la nd use intensity and amphibian and avian species composition was found. Differences between species composition in less developed landscapes and highly developed landscapes were significant, following a gradient of increasing dissimilarity from unde veloped lands to silviculture, agriculture, and urban land uses, respectively. Surdick (2005) pointed out the relevance of the LDI for ecological studies involving change s along a disturbance gradient. Mack (2006) tested the robustness of the LDI as a wetland condition assessment procedure using a large reference wetland data set in Ohio. The LDI was significantly correlated with the Ohio Rapid Assess ment Method for Wetlands (ORAM), an independent measure of the human disturba nce gradient. The LDI was also correlated with Ohio’s Vegetation Index of Biotic Inte grity (VIBI), a multi-m etric index of wetland

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5 integrity. The most significant relationship s were found between the LDI and metrics from emergent wetlands, followed by fore sted wetlands, and shrub wetlands. Mack (2006) emphasized the robustness of the LD I as a measure of the human disturbance gradient given its theoretical f oundations and quantitative nature. Project Overview Overall, there were three inter-related objectives of this st udy: 1) develop areal empower density values for land use classes based on existing LU/LC coverages of the BMW; 2) compute LDI values at four differe nt spatial scales fo r 29 floodplain forested wetlands chosen by the Arkansas Soil and Water Conservation Commission for which three field based measures of “ecosystem integrity” or wetland condition had been quantified; and 3) statistically determine if the LDI can be used as a predictor of wetland condition. Energy systems diagrams, and concepts and methods of the environmental accounting methodology developed by H. T. Odum and colleagues at the University of Florida’s Center for Environmental Policy (U F-CEP) were used to satisfy the first objective as the basis for calculating the areal empower density for land use types. To accomplish this objective it was first necessary to evaluate the emergy flows for Arkansas in order to apportion emergy to individual land use types. An emergy evaluation of Arkansas developed earlier by Odum et al. (1998) for 1990 was updated, and the resulting energy resource basis for the state was described (this analysis is presented in an appendix to this report). Next, LU/LC classi fication schemes of existing coverages were reviewed to determine their utility fo r calculating areal empower densities and recommendations were made for aggregati ng and disaggregating LU/LC categories to

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6 improve the functionality of classes. On ce LU/LC classes were determined, systems diagrams were developed for 20 LU/LC classe s. These classes served as an inventory guide for collecting material and energy flow data from a variety of sources including federal, state, and local agencies. Data on en ergy and material flow were used to develop emergy tables to compute areal empower dens ity. The areal empower density of the nonrenewable and purchased inputs was then us ed to derive LDI sc ores for individual wetland study plots. The second objective was to compute LDI valu es at four landscape scales for a set of study wetlands in the BMW (n = 29). The four scales are called Levels of analysis and correspond to the following: Level 1the enti re upstream watershed of the study wetland plot, Level 2a a 300-meter buffer of c ontiguous upstream wetlands, Level 2b a 100meter buffer of contiguous upstream wetla nds, and Level 3 a 300-meter buffer around the wetland study plot. To accomplish this obj ective, wetland study sites were sought in three a priori landscape settings: natural, agricultura l, and urban. This selection allowed a range of landscapes that re presented a gradient from undeve loped to highly developed land use intensity. Final LDI values for each wetland were computed using a GIS and based on the average areal empower density for land uses within each of the three landscape scales. To accomplish the final objective, correla tions between the LDI computed for wetland study plots and indepe ndent measures of wetlands condition were explored. The indices used were: a Wetland Rapid Assessmen t Procedure (WRAP) developed and used in South Florida, the Florida Department of Environmental Regulation’s Uniform Mitigation Assessment Method (UMAM), and the Hydrogeomorphic Functional

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7 Capacity Index (HGM). The indices were fi eld-calculated by a re search team of the Arkansas Multi Agency Wetland Planning Team (MAWPT) and scores were supplied to the UF team.

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8 CHAPTER 2 METHODS This chapter presents the steps followed in the computation of areal empower density for the different land use types and th en LDI scores for each of the study wetlands of the Bayou Meto Watershed (BMW), Arkansas First a brief descri ption of the study area is given, followed by detailed methods for evaluation of land uses, computation of areal empower density for land uses, applicatio n of LDI values to the study wetlands, and finally analysis of relationships between LDI and wetland condition. Study Area The State of Arkansas Arkansas is located in the southern/c entral U.S. and includes as its major geographic features the Ozark mountain hi ghlands to the northw est, the Ouachita Mountains to the south, and the Mississippi River alluvial pl ain to the east. The latter includes the floodplain and old ch annels of the Missi ssippi River, as well as a complex web of streams, tributaries, and artificial drainage ditches and canals. The Mississippi River valley is a fertile agricultural area and is home to most of the crop agriculture in the state. The Bayou Meto Watershed The BMW is located in eastern Arkansas between the Arkansas River and the White River (Figure 2-1) and almost wholly within the Mississippi Alluvial Plain. The BMW flows southeast and is part of the Arkansas River watershed. The land forms within the BMW include backswamps, natura l levees and meander belts, oxbow lakes or

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9 cutoffs, and terraces (MAWPT, unpublished report available at http://www.mawpt.org/products.asp). Except for the northern portion of the BMW that lies within the Ouachita Mountains ecoregi on (Level III, according to Omermik’s classification1), most of the BMW is contained w ithin the Mississippi Alluvial Plain ecoregion (Level III) with a rather flat t opography. The eastern portion of the BMW is within the Grand Prairie sub-ecoregion (Level IV), which lies between 6 to 12 meters above the Bayou Meto floodplains. Most of the wetlands under investig ation in this study were located within the Grand Prairie sub-ecoregion. #Bayou Meto Watershed State of ArkansasWhite River Arkansas RiverLittle RockM i s s i s s i p p i R i v e r Kilometers 100 0N Figure 2-1. Location of the Ba you Meto Watershed, Arkansas. 1 Omernik, J.M. 1987. Ecoregions of the conterminous United States. Map (scale 1:7,500,000). Annals of the Association of American Geographers 77(1):118-125.

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10 Once rich in forests and wetlands, agricultu re is currently the predominant land use within the BMW. Only 25% of the BMW is fore sted and it is estimated that from 1950 to 1990 approximately 50% of the natural wetlands present in the BMW were lost to land development (Arkansas MAWPT, unpublished report available at http://www.mawpt.org/products.asp). Urban la nd uses account for only 3% of the total landscape. Emergy Evaluations of Arkansas and La nd Uses in the Bayou Meto Watershed The emergy evaluations of th e state of Arkansas and of land use types within the BMW were performed following the principles and procedures of the emergy analysis methodology. The emergy analysis methodology c onsists of three general steps: (1) development of energy systems diagrams for th e system of interest, (2) development of emergy tables, and (3) calculation of emergy indices that describe the system and its potential. Detailed methods for the ev aluations are given in the Appendix. Land Use Areal Empower Densities Land Use / Land Cover (LU/LC) Data A 1999 Arkansas LU/LC: Summer (1999 AR -LU/LC) GIS coverage, developed by the Center for Advance Spatial Technologies (2001) was used to identify the main land uses present in the BMW. The 1999 AR-LU/LC coverage is available through GeoStor, a web-based database containing all publicly av ailable geodata for th e state of Arkansas and available at http://www.cast .uark.edu/cast/geostor/. This c overage is the most recent state-wide LU/LC data set available for Arka nsas and the study area. It was derived from Landsat TM 5 scenes and ground-truth informa tion with a 30 x 30-me ter cell resolution.

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11 The 1999 AR-LU/LC coverage has a hierarch ical system of categories with two levels ranging from general to specific. Level 1 consists of six classes (urban, barren, water, forests, agricultural, and herbaceous lands) which are further subdivided into finer detail (Level 2) with a total of 46 classes. Level 2 categorie s were used as the basis for identifying the land uses for which areal empow er densities coefficien ts were calculated, and were included in the development of LD I values for the watersheds of the study wetlands. Level 2 category codes and labe ls for the 1999 AR-LU/LC coverage are summarized in Table 2-1. Definition of Land Use Categories: aggregations and disaggregations The 1999 AR-LU/LC coverage emphasizes agricultural land uses and forest classes, with only general descriptions pr ovided for urban land uses and surface water cover. As a result of the uneven description of land uses in the coverage, it was necessary to aggregate some categories and disaggregate others to fit the requirements needed for LDI calculations. Aggregation was easily accomplished; however, disaggregation required the use of aerial phot o interpretation and the cons truction of new coverages. New coverages were then merged to th e 1999 AR-LU/LC to obtain a final LU/LC coverage that allowed describing LD I-LU/LC categories and performing LDI calculations. The 1999 AR-LU/LC focuses primarily on ag ricultural land uses. It also includes forest categories that were initially developed by the 1992 Arkansas Gap Project, which had among its objectives mapping th e distribution of vegetation types in the state. Water systems and urban lands were only generally classified in the 1999 AR-LU/LC. Since this research emphasized defining human disturban ce as measured by areal empower density

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12 Table 2-1. Level 2 category codes and labe ls for the 1999 AR-LU/LC coverage (after CAST 2001). LULC Code LULC Label LULC Code LULC Label 11 Urban Level 1 114 Forest 14 12 Urban Level 2 115 Forest 15 13 Urban Level 3 116 Forest 16 14 Urban Other (Park, Golf Course, Cemetery, etc.) 117 Forest 17 21 Major Roads 118 Forest 18 22 Railroads 119 Forest 19 23 Airports/Landing Strips 120 Forest 20 31 Barren Land (Sand Bars/Mining Operations/Exposed Rock) 121 Forest 21 41 Perennial Water 122 Forest 22 42 Flooded 123 Forest 23 101* Forest 1 124 Forest 24 102 Forest 2 125 Forest 25 103 Forest 3 126 Forest 26 104 Forest 4 127 Forest 27 105 Forest 5 128 Forest 28 106 Forest 6 201 Soybeans 107 Forest 7 202 Rice 108 Forest 8 203 Cotton 109 Forest 9 204 Wheat/Oats 110 Forest 10 205 Sorghum/Corn 111 Forest 11 208 Bare Soil/Seedbed/Fallow 112 Forest 12 209 Warm Season Pasture 113 Forest 13 210 Cool Season Pasture Forest categories (101-128) were origina lly labeled with the name of specific species given after the 1992 Arkansas Gap Project. primarily from urban and agricu ltural land uses, all of the forest classes on the 1999 ARLU/LC coverage were aggregated into tw o categories: upland fo rests and wetlands.

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13 The 1999 AR-LU/LC coverage had only tw o categories for describing the surface waters in the BMW: Perennial Waters a nd Flooded with codes 41 and 42, respectively. These were disaggregated to distinguish be tween the different freshwater ecosystems present in the study area, a nd to identify land uses such as managed ponds and dike/impounded waters systems. A new spatial layer, available through Geostor, was created based on spatial data fo r rivers/streams, lakes, and we tlands, and merged with the 1999 AR-LU/LC coverage to provide more deta il regarding the surface waters within the BMW. After these changes, undefined water ar eas remained. A visual identification of these areas using aerial photographs showed that these areas most likely correspond to rice fields and managed ponds (aquaculture). As a result, a new land use category was created that combined aspects of both land uses. Urban land use categories from the 1999 AR -LU/LC coverage were disaggregated by photo interpretation of aerial photographs in combination with v ector GIS coverages for selected urban areas in the BMW provide d by Metroplan, Arkansas. Urban lands were defined in the 1999 Arkansas LU/LC: Summer da ta set as three gene ral classes labeled Urban 1, Urban 2, and Urban 3. These were recla ssified to eight classe s that dis tinguished between residential, commercial, and i ndustrial areas. Reside ntial areas were disaggregated into five categories that acc ount for the different housing densities that might be present in an urban landscape. To determine housing densities for residential areas, houses were counted within one-hectar e plots laid on aerial photos. This was done only for delineated sub-basins within the BMW. Commercial areas were disaggregated into two categories that distinguish between commercial strips and community shopping centers. Industrial areas were included in onl y one category. Institutional land uses such

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14 as public buildings, schools, and churches were assumed to be equivalent to commercial strips in terms of their level of energy us age and were assigned to the same land use category. Urban areas such as city parks, pl aygrounds, golf courses, and urban lands that have been cleared and prepared for construc tion and/or development were assigned to a unique category. Urban areas we re completed by adding a data layer for roads (interstates and U.S. highways) and obtained from Geostor. The resulting LU/LC categories were r eclassified using functional LDI-LU/LC classes. The land use category 208 (bare so il/seedbed/fallow) from the 1999 AR-LU/LC coverage was not considered since it was onl y present in the northern portion of the BMW and only accounted for approximately 24.3 hectares. Land use categories 23 (airports/landing strips) and 204 (wheat/oats) were also not considered since the 1999 ArLU/LC: Summer coverage reported no such la nd use for the BMW. Definitions for the LDI-LU/LC classes are given in Table 2-2. Areal Empower Densities Detailed analyses for each LU/LC categor y were undertaken using data from the literature and the evaluation of the state of Arkansas (see Appendi x). A look-up table was developed for each LU/LC category then the LDI-LU/LC coverage was reclassified assigning areal empower densities to each land use type. The result was an LDI-emPower coverage where each land use category wa s assigned its appropriate areal empower density.

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15 Table 2-2. Development intensity land use categories and definitions. Land Use LULC* Code Definition Forests 101-128 Upland forests with low manipulations. Wetlands 101-128 Forested wetlands with low manipulations. Open Water 41, 42 Lakes, ponds, and streams with low manipulations. Hay Crop 209-210 Areas devoted to the production of hay. Also applies to pasture lands (without livestock), which are defined as areas where the natural vegetation has been altered by drainage, irrigation, etc., for the grazing of domestic animals. Soybeans 201 Areas devoted to the production of soybeans. Rice 202 Areas devoted to the production rice. Cotton 203 Areas devoted to the production cotton. Sorghum/Corn 205 Areas devoted to the production of sorghum/corn. Aquaculture 41 Fish farms. Can also apply to high-intensity agriculture land uses such as dairy farms and large-scale cattle feed lots, chicken farms, and hog farms, if present. Rice/Aquaculture 41, 202 Undefined agricultural areas. Average of rice and aquaculture. Open Space/Recreational 14, 31, 41 Areas with grassy lawns in urban landscapes including recreational lands such as playgrounds, ball fields, and golf courses. Also applies to land that has been cleared and prepared for construction and/or development, dirt roads, barren land, and open areas surrounding by paved roads and power lines. Includes humancreated water bodies (retention p onds, canals, reservoirs, etc.) other than for aquaculture. Low Intensity Single Family Residential 11 Areas that are predominantly residential units with a density less than 5 units/ha. Medium Intensity Single Family Residential 11 Areas that are predominantly residential units with a density between 5 and 10 units/ha. High Intensity Single Family Residential 11 Areas that are predominantly residential units with a density of more than 10 units/ha. Low Intensity Multi-family Residential 11 Areas that are predominantly multi-family residential units such as condominiums and apartment buildings up to 2 stories. High Intensity Multi-family Residential 11 Areas that are predominantly multi-family residential units such as condominiums and apartment buildings with 3 or more stories. Low Intensity Commercial/Institutional 12-13 Commercial strips with associated storage buildings and parking lots. Schools, universities, religious, military, medical and professional facilities, and government buildings. High Intensity Commercial 12-13 Community shopping center with associated storage buildings and parking lots. Industrial 12,13, 31 Land uses include manufacturing, assembly or processing of materials/products and associated buildings and grounds. Also includes extractive areas and mining operations, water supply plants, and solid waste disposal. Low Intensity Transportation 21-22 Paved road with no more than 2 lanes, and railroads. High Intensity Transportation 21 Paved road with more than 2 lanes, railroad terminals, bus and truck terminals, and large auto parking facilities when not directly related to other land uses. Level 2 category codes for the 1999 Arkansas Land-use/Land-cover: Summer.

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16 LDI Index for Study Wetlands at Four Spatial Scales Selection of Wetlands Sites Study sites were selected with the aid of aerial photography and through a joint field visit made by the UF team and the Arkansas MAWPT in August 2005. The locations of the wetland study plots were determined in the field by the MAWPT staff using a Global Positioning System (GPS). Th e location of the wetland sites (n = 29) is shown in Figure 2-2 and is indicated by generalized a priori land use categories (reference, rural, and urban). Hereafter wetlands embedded in primarily undeveloped landscapes are called reference wetlands; wetlands embedded in primarily agricultural land uses are called rural wetla nds; and wetlands embedded in primarily urban land uses are called urban wetlands. Information on each site is summarized in Table 2-3. Spatial Areas of Influence LDI indices for each study wetland were comput ed at four different spatial areas of influence (see Figure 2-3): 1) the drainage basin or total watershed upstream from the wetland study plots, 2) a 300-meter buffer ar ound the riparian zone immediately upstream of the study wetland, 3) a 100-meter buffer around the riparian zone immediately upstream of the study wetland, and 4) a 300-meter buffe r surrounding and immediately adjacent to the study wetland. Upstream riparian systems that were connected to the study wetlands were delineated using aerial pho tographs and GIS coverages. The buffer areas for riparian systems and buffer areas around each study wetlan d were delineated using buffer command in ArcView GIS 3.2 (Environmental System s Research Institute, Inc. 1999).

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17 Figure 2-2. Approximate location of the Ba you Meto watershed fo rested wetland study sites. Delineation of Drainage Basins The areas draining to the locations where fo rested wetlands of the flood zone of the BMW and its tributaries were sampled, as well as the stream networks within the drainage areas, were determined using the Better Assessment Science Integrating Point and Nonpoint Sources 3.0 (BASINS 3.0) envi ronmental analysis system. The BASINS computer program was developed by the O ffice of Water of the USEPA to support

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18 Table 2-3. Summary information for the Ba you Meto Watershed forested wetlands study. Site Number Site Name Type* Size of Watershed (ha) # of Sampling Plots 1 Fina Woods Urban 437.1 1 2 Old Highway 69 Woods Reference 3284.3 2 3 Church Woods Urban 14.5 1 4 Strip Mall Woods Urban 49.2 2 5 Cabot Park Woods Urban 45.7 1 6 Gander Mtn. Sporting Goods Urban 1721.7 2 7 Manson Rd. Woods Urban 66.5 1 8 Harvest Foods Woods Urban 45.0 1 9 Jacksonville Ball Field Urban 221.7 3 10 Gentry Rd West Rural 188.7 2 11 Gentry Rd East Rural 530.1 1 12 Fairview Rural 400.7 2 13 Winrock Hwy 13 West Rural 154.2 1 14 Winrock Hwy 13 East Rural 109.7 1 15 Winrock CR 923 East Reference 2790.1 2 16 Winrock CR 923 West Rural 2728.0 2 17 Merlin Mission Rural 46.3 3 18 Winrock CR 915 East B Reference 41.8 1 19 Winrock CR 915 East C (beaver) Reference 105.2 1 20 Winrock CR 915 West Rural 910.0 3 21 I-40 Woods Reference 1386.2 3 22 North Holland Bottoms 1 Reference 28.3 2 23 North Holland Bottoms 2 Reference 8.0 4 24 North Holland Bottoms 3 Reference 5.9 1 25 Prairie Bayou WMA 1 Rural 21.8 1 26 Prairie Bayou WMA 2 Reference 30.2 2 27 Prairie Bayou WMA 3 Reference 171.4 1 28 Lower Holland Bottoms 1 Reference 109.1 2 29 Lower Holland Bottoms 2 Reference 39.2 2 *Wetlands were classified as reference, rural, or urban if they were embedded in primarily undeveloped landscapes, embedded in primarily agricultural land uses, or embedded in primarily urban land uses, respectively. environmental and ecological studies at the watershe d level (USEPA 2001). The assessment tools used in the BASINS system are integrated into the GIS software ArcView 3.2 (ESRI 1992-1999), the computer program used for the spatial analyses performed during this study.

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19 Figure 2-3. Landscape scales used to calcu late LDI values for the study wetlands. LEVEL 1: watershed upstream of wetla nd study plot; LEVEL 2a: a 300-meter buffer around the riparian zone immedi ately upstream of the study wetland; LEVEL 2b: a meter buffer ar ound the riparian zone im mediately upstream of the study wetland; and LEVEL 3: a 300-meter buffer surrounding and immediately adjacent to the study wetland.

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20 The delineation of drainage basins and th e stream networks required the use of a digital terrain model (DTM), a grid map that masks the DTM, and a pre-digitized stream network. A state-wide digital elevation model (DEM) available through Geostor was used as the preferred DTM. The DEM has a 30 x 30-meter cell resolution and was developed by the United States Geological Survey (USGS) as part of the National Elevation Dataset (USGS 1999).The DEM for each drainage basi n was masked using state-wide watershed boundaries coverage. The pre-digi tized stream network used was a state-wide coverage also available through Geostor. Where data for streams were missing, the streams were delineated on-screen with the aid of aerial photography and the elevation terrain model. The final calculation of the drainage ba sin boundary was done using a stream outlet closest to the wetlands’ sampling locations. Landscape Development Intensity Index The land uses within each of the four areas of spatial influence were clipped from the LDI-emPower coverage and the LDI i ndex value was calculated for each study wetland as: LDI = 10 log (empPDTotal/emPDRef) (Eq. 1) where LDI is the Landscape Development In tensity index for a given landscape unit; empPDTotal is the total areal empower density (including the background environment) within the buffer; and emPDRef is the areal empower density of the background environment (2.20 E15 sej/ha-yr; average areal empower density for natural systems in the BMW). The total areal empower density (empPDTotal) was calculated as: emPDtotal = emPDRef + ( %LUi emPDi ) (Eq. 2)

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21 where %LUi is the percent of the area of influence in land use i; and emPDi is the nonrenewable areal empower dens ity for land use i. This is a modification of the LDI published by Brown and Vivas (2005) and used by Vivas (2006). Analysis of Relationships between the LDI and Wetland Condition Spearman’s rank order correlation, the non-parametric measure of correlation (Dytham 1999), was used to assess the rela tionship between the LDI and three different measures of wetland condition: WRAP (Miller and Boyd 1999), UMAM (62-345.100(6), Florida Administrative C ode [F.A.C.]), and HGM procedure (Brinson 1993). The WRAP (Miller and Boyd 1999), is a rapid assessment procedure consisting of a rating index that can be used to evalua te wetland condition ba sed on six variables: wildlife utilization, wetland overstory/shrub canopy, wetla nd vegetative ground cover, adjacent upland support/wetland buffer, field indicators of wetland hydrology, and water quality input and treatment systems. Each variable is scored from 0.0 to 3.0, in increments of 0.5. The final index score is expressed on a scale ranging from 0.0 to 1.0. A score of 1.0 indicates an undi sturbed wetland, whereas a scor e of 0.0 indicates a wetland with a reduced functional cap acity. The WRAP was original ly developed by the South Florida Water Management District (SFWMD) to assist in the re gulatory evaluation of mitigation sites. The variable for adjacent land support and wetland buffer was not included in the calculation final WRAP score. The Florida Department of Environmen tal Regulation (FDEP) developed the UMAM to assess impacts and mitigation requirements for wetlands and other protected waters (F.A.C 62-345.100(6)). UMAM provides a standardized procedure for assessing the functions provided by wetlands and other waters of the state, the amount those functions are reduced by proposed impacts, a nd the amount of mitigation necessary to off

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22 set that loss. Bardi et al. (2005) provided a summary of th e method as follows: the area of study is evaluated based on both a qualitative description a nd quantitative evaluation of the assessment area. For the qua ntitative section, site s are evaluated according to three variables: location and landscap e support, which examines the ecological context within which the system operates; water environm ent, a rapid assessment of hydrologic alteration and water quality impairment; a nd community structure, more specifically vegetation and structural habitat. Each indica tor is scored numerica lly on a scale from 0 to 10 (where 10 indicates a minimally impaired system).The final UMAM score is determined by summing the scores of each of the three variables assessed and dividing that value by 30 to yield a number betw een 0 and 1. The variable on location and landscape support was not included in the calcul ation of the final UMAM scores in this study. The HGM (Brinson 1993) is a procedur e for measuring wetland functional capacity. The procedure was designed to satisfy the technical and programmatic requirements of the Clean Water Act Secti on 404 (Section 404). The HGM is based on three fundamental factors that influence we tland function: the position of the wetland in the landscape (geomorphic setting), the water source (hydrology), and the flow and fluctuation of the water w ithin the wetland (hydrodynamics). Only three of the HGM categories were evaluated and used in this study: (a) hydrological category, (b) biogeochemical category, a nd (c) habitat category.

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23 CHAPTER 3 RESULTS Land Use / Land Cover of the Bayou Meto Watershed Figure 3-1 is a map produced from the LU/LC coverage of the BMW showing the extent of coverage by the va rious land uses. The vast ma jority of the watershed is dominated by agricultural uses with the northern portions of the watershed dominated by urban uses. Based on the LU/LC classes s hown in Figure 3-1, 20 functional land use categories for LDI calculations were defined for the BMW. Emergy Evaluation of Selected Land Uses A summary of areal empower densities for land use classes in the BMW is given in Table 3-1 and shown in Figure 3-2. The av erage areal empower density for the BMW was 61.47 E 15 sej/ha/yr. The largest areal empo wer densities (darker areas) occurred in the urban areas in the northe rn portion of the watershed (Figure 3-2). The middle and southern portions of the BMW were dominate d by intermediate areal empower densities that characterize agricu ltural lands. Details of individua l land use classes beginning with forested ecosystems are given in the following paragraphs. Emergy evaluations of upland forest and forested wetlands ecosystems (see Appendix) revealed that the total solar emergy flow for a hectare of mixed hardwood forest was 1.82 E15 sej/yr, while that of a bottomland hardwood forest was 2.58 E15 sej/yr. Six crops that constitute the most common agricultural crops grown in the BMW were also evaluated. Total solar emergy valu es for a hectare of crop ranged between

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24 Lulc_3vector_c.shpBare Soil/Seedbed/Fallow Barren Land Commercial Cool Season Pasture Cotton Diked Wetlands Excavated Wetlands Forests Industrial Interstate Lakes Other Urban Other Waters Reservoirs Residential Rice Rivers and Streams Sloughs Sorghum/Corn Soybeans US Highway Warm Season Pasture Wetlands Land Use/Land Cover N 010Kilometers Figure 3-1. Base map of LU/LC classes for the BMW used to identify functional LDILU/LC classes.

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25 7.87 E15sej/yr (sorghum) and 19.5 E15 sej/yr (cott on). Intermediate va lues included 9.61 E15 sej/yr (soybeans), 10.5 E15 sej/yr (hay), 11.7 E15 sej/yr (rice), and 12.3 E15 sej/yr (corn). Also common on the land scape of the BMW are fish ponds for raising catfish and baitfish. On a per hectare basis, the emer gy evaluation of six 2acre ponds for catfish resulted in a total solar emergy flow of 109.4 E15 sej/yr. A general energy systems Table 3-1. Areal empower density for land us e classes in the Ba you Meto Watershed. Notes Land Use Classes Total Areal empower Density (E15 sej/ha/yr) NR + PI* Areal empower Density wo/services (E15 sej/ha/yr) 1 Forests 1.820.00 2 Background Environment 2.170.00 3 Wetlands 2.580.00 4 Open Space/Recreational 7.915.75 5 Sorghum 7.876.16 6 Hay Crop 10.466.95 7 Soybeans 9.617.73 8 Corn 12.339.34 9 Rice 11.669.40 10 Cotton 19.5215.84 11 Rice/Aquaculture 60.5549.33 12 Aquaculture 109.4489.25 13 LI-Single Family Residential 218.18162.48 14 MI-Single Family Residential 610.91454.94 15 LI-Transportation 494.50494.50 16 HI-Single Family Residential 872.73649.92 17 LI-Multi Family Residential 2815.272096.52 18 LI-Commercial/Institu tional 5174.312444.43 19 HI-Transportation 2533.692533.69 20 Industrial 5235.023654.73 21 HI-Commercial 8372.424103.62 22 HI-Multi Family Resi dential 8445.806289.55 Non-renewable and purchased inputs (wo = with out services) Notes: 2 Weighted average of 1 and 3 Based on the proportion of each in the BMW. 11 Average of 9 and 12.

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26 diagram and the emergy evaluation tables for each agriculture system and for catfish production are included in the Appendix. Non Renewable Empower Density (E+15 sej/ha/yr) 0 0 7 7 10 10 90 90 580 580 2532 2532 3655 10 0Kilometers N Figure 3-2. Non-renewable and purchased ar eal empower density for the Bayou Meto Watershed. The range of the areal empow er density values are based on the LU/LC classes from Figure 3-1. The baseline emergy evaluation for resi dential land uses wa s a single-family residential area with a density of 2.5 houses per hectare with an annual emergy flow of

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27 2.18 E17 sej/ha/yr, and classified as low-in tensity single-family residential. Other housing densities used were 7, 10, 32, and 97 uni ts per hectare and were classified as medium-intensity single-family residential, hi gh-intensity single-family residential, lowintensity multi-family residential, and hi gh-intensity single-family residential, respectively. A general energy systems diag ram for a residential area and the emergy evaluation tables for each residential dens ity are included in the Appendix. The emergy evaluation of an urban lawn was also deve loped and used as a measurement for urban open spaces and urban recreationa l facilities after “dispersing” the energy usage over the landscape based on Robbins and Birkenholtz (20 03)’s estimate of 23% coverage of lawns in the urban landscape. The annual emergy flow for a hectare of urban lawn was calculated as 7.91 E15 sej/ha/yr; this emer gy evaluation is included in the Appendix. Other urban land uses that were evaluated were commer cial and industrial areas and transportation corridors (highways). The energy system diagrams and emergy evaluation tables for these urban land uses are provided in the Appendix. Commercial land uses had annual solar emergy flows of 5.17 E18 sej/ha/yr and 8.37 E18 sej/ha/yr for low-intensity and high-intensity areas, respec tively. The annual solar emergy flows for an industrial area were calculated as 5.24 E18 sej/ha/yr. A hectare of an interstate highway (I-40) had an annual solar emergy flow of 2.53 E18 sej/ha/yr, while a less intense highway (U.S. Highway 70) had an annual solar emergy flow of 4.94 E17 sej/ha/yr. LDI and Wetland Condition LDI Scores for Study Wetlands Table 3-2 lists each of th e wetland study sites, their a priori classes, and the areal empower density and computed LDI for each of the four spatial scales. Urban sites had

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28 higher areal empower densities and LDI scor es than rural and reference sites. The purpose of computing four different LDI scor es for each wetland was to test which scale is most appropriate within watersheds. The Le vel 3 scale is the smallest scale consisting of a 300-meter buffer around each of the wetla nd study sites, while Level 1 is the largest scale consisting of the entire upstream waters hed. There was general agreement between LDI scores for the four scales in urba n and rural study sites. However, three a priori reference sites had unusual areal empower dens ity values. Sites # 2 and 27 had Level 1, 2a, and 2b areal empower densit ies that were not indicative of reference conditions, while their Level 3 scores were well within refe rence conditions. Site # 21 had areal empower densities that were not indicat ive of reference conditions at all scales considered. This was due primarily to the fact that these study sites were embedded in watersheds that had relatively intense upstream urbanization. LDI scores for the different scales were compared across each study site to determine if there were significant differen ces from one scale to the next. A KruskalWallis non-parametric statistical test used to compare the computed LDI values at the four spatial scales showed no significant diffe rences between the different scales (H = 2.70, p = 0.439). A comparison of LDI scores of the four spatial scales, as shown in Figure 3-3, suggests that ther e are relatively strong corre lations between LDIs for wetland study plots computed for Levels 1, 2a, and 2b (r2 = 0.98). LDI indices for Level 3 differ slightly from those calculated for Le vels 1, 2a, and 2b but still have relatively strong correlations (r2 = 0.88). It is obvious from the sc atter plots in Figure 3-3 that wetland study sites with intermediate LDI values are absent from the data set.

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29 Table 3-2. Non-renewable and purchased areal empower density a nd LDI index scores for 29 fore sted floodplain wetlands. Developm ent intensity measurements were completed for four spatial scales. Level1:Watershed Level 2a: 300-m Stream Buffer Level 2b: 100-m Stream Buffer Level 3: 300-m Adjacent to Wetland NR+P EmpDen LDI NR+P EmpDen LDI NR+P EmpDen LDI NR+P EmpDen LDI Site No. Site Name Type* (E+15 sej/ha/yr) (E+1 5 sej/ha/yr) (E+15 sej/ha/yr) (E+15 sej/ha/yr) 1 Fina Woods Urb 603.38 24.40 1255.01 27.57 1335.57 27.84 1498.96 28.34 2 Old Highway 69 Woods Ref 28.24 11.41 25.27 10.96 22.41 10.49 0.07 0.14 3 Church Woods Urb 1312.54 27.76 1315.36 27.77 1374.84 27.97 1211.80 27.42 4 Strip Mall Woods Urb 1910.85 29.39 1711.64 28.92 704.81 25.07 1844.90 29.24 5 Cabot Park Urb 634.64 24.62 623.25 24.54 221.56 20.07 820.07 25.73 6 Gander Mtn. Sporting Goods Urb 342.80 21.95 307.78 21.49 248.83 20.57 2566.80 30.67 7 Manson Rd. Woods Urb 1470.33 28.26 1547.29 28.48 2108.05 29.82 2380.05 30.35 8 Harvest Foods Woods Urb 1501.21 28.35 1871.77 29.30 1491.62 28.32 1588.39 28.59 9 Jacksonville Ball Field Urb 789.90 25.56 665.24 24.82 428.26 22.92 231.04 20.25 10 Gentry Rd West Rur 16.20 9.22 7.34 6.37 6.10 5.77 4.67 4.94 11 Gentry Rd East Rur 26.71 11.19 9.02 7.07 8.01 6.67 5.59 5.49 12 Fareview Rur 9.81 7.37 8.41 6.83 7.04 6.23 7.61 6.49 13 Winrock Hwy 13 West Rur 8.78 6.98 8.73 6.96 7.94 6.64 9.25 7.16 14 Winrock Hwy 13 East Rur 8.49 6.87 8.59 6.90 7.95 6.64 6.19 5.81 15 Winrock CR 923 East Ref 9.42 7.23 9.05 7.09 8.62 6.92 5.51 5.45 16 Winrock CR 923 West Rur 9.45 7.24 9.12 7.11 8.69 6.95 8.19 6.74 17 Merlin Mission Rur 8.86 7.01 7.72 6.54 6.25 5.84 5.84 5.63 18 Winrock CR 915 East A Ref 5.89 5.66 4.90 5.09 0.75 1.27 0.31 0.58 19 Winrock CR 915 East B&C Ref 8.02 6.67 7.41 6.40 6.66 6.05 0.52 0.92 20 Winrock CR 915 West Rur 9.46 7.24 9.10 7.11 8.44 6.85 3.43 4.08 21 I-40 Woods Ref 13.25 8.46 14.19 8.72 13.35 8.49 98.66 16.61 22 North Holland Bottoms 1 Ref 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 23 North Holland Bottoms 2 Ref 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 24 North Holland Bottoms 3 Ref 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 25 Prairie Bayou WMA 1 Rur 7.40 6.40 6.71 6.07 2.26 3.07 2.56 3.35 26 Prairie Bayou WMA 2 Ref 6.47 5.95 6.35 5.90 2.71 3.49 0.31 0.58 27 Prairie Bayou WMA 3 Ref 38.72 12.70 25.02 10.92 13.97 8.66 1.75 2.54 28 Lower Holland Bottoms 1 Ref 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 29 Lower Holland Bottoms 2 Ref 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Urb = Urban; Ref = Reference; Rur = Rural

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30 (a) (b)(c) (d) (e) (f) Level 1 vs Level 2b R2 = 0.96150 5 10 15 20 25 30 35 05101520253035LDI Level 2bLDI Level 1 Level 1 vs Level 3 R2 = 0.86570 5 10 15 20 25 30 35 05101520253035LDI Level 3LDI Level 1 Level 1 vs Level 2a R2 = 0.9870 5 10 15 20 25 30 35 05101520253035LDI Level 2aLDI Level 1 Level 3 vs Level 2b R2 = 0.89670 5 10 15 20 25 30 35 05101520253035LDI Level 2bLDI Level 3 Level 3 vs Level 2a R2 = 0.89050 5 10 15 20 25 30 35 05101520253035LDI Level 2aLDI Level 3 Level 2b vs Level 2a R2 = 0.98130 5 10 15 20 25 30 35 05101520253035LDI Level 2aLDI Level 2b Figure 3.3 Scatter plots of study wetland LDI in dices at various scales. a). Level 1 vs. Level 2a; b) Level 1 vs. Level 2b; c) level 1 vs. Level 3; d) Level 3 vs. Level 2a ; e) Level 3 vs. Level 2b; and f) Level 2b vs. Level 2a. See text for explanations of the spatial scales corresponding to ea ch of the levels of analysis.

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31 Wetland Condition Indices for Wetland Study Sites Table 3-3 lists each of th e wetland study sites, their a priori classes, and their wetland condition index scores. Each of the three compone nts of the HGM score is listed separately. Table 3-3 is a summary of the data for the a priori classes of wetland s ites showing the mean LDI values for each of the four spatial scales and the corresponding mean wetland condition indices. The small sample size for each a priori class of wetland sites makes statistical comparisons among LDI groups and among groups of the wetland condition indices not relevant. However, the inspection of the data su ggests that there are important differences in LDI scores and wetland conditi on indices scores among the a priori classes. Table 3-3 Summary of LDIs and Wetland c ondition indices for a priori classes. A priori Class Level 1 LDI Level 2a LDI Level 2b LDI Level 3 LDI WRAPUMAM HGMHydrological HGMBiogeochemical HGMHabitat Reference Sites 4.84 4.59 3.78 2.24 0.98 0.96 0.90 0.87 0.92 Rural Sites 7.72 6.77 6.07 5.52 0.84 0.81 0.89 0.83 0.87 Urban Sites 26.29 26.61 25.32 27.57 0.72 0.81 0.71 0.67 0.82 In general, mean LDI scores decreased as th e spatial scale decreased. This held true for reference and rural site s; however, urban sites did not follo w this trend. The Level 3 mean LDI scores for reference sites (n = 12) were less than half those of the Level 1 score, while the Level 3 mean LDI score for rural sites was a bout 30% lower than the Level 1 score. Relationships between the LDI and Measurements of Wetland Condition The LDI was correlated with three indepe ndent measurements of anthropogenic disturbance: WRAP, UMAM, and HGM. The scores for each of these indices for each wetland study plot are presented in Table 3-4; the co rrelation results are shown in Table 3-5. All correlations were statistically significant (p-level of 0.05). WRAP had the strongest correlations

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32 with LDI at all scales of an alysis, followed by the HGM. The habitat component of the HGM had the highest correlations with LDI at all scales of analysis. The strongest correlation was found between the LDI and the WRAP at the Level 3 spatial scale (Spearman’s r = -0.81, p < 0.001). The habitat component of HGM correlated strongest with the LDI at the Level 3 spatia l scale. The hydrological component of the HGM also showed the strongest association with the LDI at the same scale (Level 3). The biogeochemical component of HGM showed the strongest association with the LDI at the Level 2a and Level 2b scales (100-meter buffer and 300-meter buffer around the stream, respectively). Correlations between the UMAM a nd the LDI were very similar among the four spatial scales considered. Graphs showing th e relationship between the LDI and the WRAP, HGM, and UMAM are shown in Figures 3-4, 35, and 3-6, respectively. Variables were graphed in rank order form. Level of impairment, evaluated by means of the WRAP, increased as the development intensity of the surrounding landscap e increased. The results seem to suggest that, for all scales, the levels of disturbance for the wetland study sites were influenced by their surrounding (or upstream) landscape and that areal empower density was a measure of the disturbance gradient (see Figure 3-4). Differences between the Spearman’ s correlations for the four scales (see Table 3-5), suggest that the landscape immediately ad jacent to the wetlands (Level 3) may be more important in determining wetland condition than lager scale areas (i.e., Levels 1, 2a, and 2b).

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33 Table 3-4. Final scores for three measurements of wetland condition for the sample floodplain wetlands. WRAP UMAM HGM Site No. Site Name Type* Hydrological Category Biogeochemical Category Habitat Category 1 Fina Woods Urb 0.75 0.86 0.54 0.42 0.76 2 Old Highway 69 Woods Ref 1.00 0.99 0.86 0.81 0.86 3 Church Woods Urb 0.54 0.72 0.78 0.71 0.79 4 Strip Mall Woods Urb 0.65 0.87 0.61 0.57 0.80 5 Cabot Park Woods Urb 0.75 0.81 0.73 0.64 0.88 6 Gander Mtn Sporting Goods Urb 0.61 0.78 0.78 0.90 0.76 7 Manson Rd. Woods Urb 0.85 0.84 0.78 0.76 0.90 8 Harvest Foods Woods Urb 0.88 0.83 0.74 0.78 0.81 9 Jacksonville Ball Field Urb 0.69 0.78 0.69 0.58 0.82 10 Gentry Rd West Rur 0.61 0.68 0.96 0.89 0.83 11 Gentry Rd East Rur 0.84 0.85 0.94 0.83 0.91 12 Fairview Rur 0.90 0.84 0.88 0.83 0.91 13 Winrock Hwy 13 West Rur 0.83 0.78 0.97 0.86 0.92 14 Winrock Hwy 13 East Rur 0.83 0.78 0.76 0.75 0.82 15 Winrock CR 923 East Ref 0.88 0.81 0.94 0.87 0.95 16 Winrock CR 923 West Rur 0.75 0.63 0.84 0.78 0.81 17 Merlin Mission Rur 0.89 0.82 0.84 0.82 0.85 18 Winrock CR 915 East A Ref 0.94 0.90 0.88 0.88 0.92 19 Winrock CR 915 East B&C Ref 0.92 0.89 0.85 0.79 0.87 20 Winrock CR 915 West Rur 0.93 0.92 0.92 0.85 0.88 21 I-40 Woods Ref 0.99 0.96 0.90 0.83 0.87 22 North Holland Bottoms 1 Ref 1.00 0.99 0.89 0.86 0.92 23 North Holland Bottoms 2 Ref 1.00 0.99 0.91 0.91 0.92 24 North Holland Bottoms 3 Ref 1.00 1.00 0.92 0.97 0.95 25 Prairie Bayou WMA 1 Rur 1.00 0.98 0.94 0.87 0.92 26 Prairie Bayou WMA 2 Ref 1.00 0.96 0.91 0.89 0.96 27 Prairie Bayou WMA 3 Ref 1.00 0.97 0.98 0.92 0.98 28 Lower Holland Bottoms 1 Ref 1.00 1.00 0.94 0.86 0.96 29 Lower Holland Bottoms 2 Ref 1.00 1.00 0.84 0.85 0.92

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34 Table 3-5. Spearman’s correlations (r) between the LDI and meas urements of wetland condition for the sample floodplain wetlands calculated at four diffe rent spatial scales. WRAP UMAM HGM LDI Hydrological Component Biogeochemical Component Habitat Component r p-value r p-value r p-value r p-value r p-value Level 1: Watershed -0.68<0.001-0.500.005 -0.490.007-0.600.001-0.67 <0.001 Level 2a: 300-m surrounding stream -0.64<0.001-0.480.009 -0.540.002-0.65<0.001-0.67 <0.001 Level 2b: 100-m surrounding stream -0.64<0.001-0.490.008 -0.540.002-0.64<0.001-0.67 <0.001 Level 3: 300-m adjacent to study wetland -0.81<0.001-0.500.006 -0.570.001-0.600.001-0.73 <0.001

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35 LDIWRAP 30 25 20 15 10 5 0 25 20 15 10 5 0 LEVEL 1: Watershed LDIWRAP 30 25 20 15 10 5 0 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 2a: 300-m Buffer Surrounding Stream LDIWRAP 30 25 20 15 10 5 0 25 20 15 10 5 0 LEVEL 2b: 100-m Buffer Surrounding Stream LDIWRAP 30 25 20 15 10 5 0 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 3: 300-m Buffer Adj acent to St udy Wetland Figure 3-4. Scatterplots show ing the relationship between the LDI and the WRAP for four different spatial scales. Data on both axes are shown as ranked scores.

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36 LDIHGM (Hydrological Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 LEVEL 1: Watershed LDIHGM (Hydrological Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 2a: 300-m Buffer Surrounding Stream LDIHGM (Hydrological Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 LEVEL 2b: 100-m Buffer Surrounding Stream LDIHGM (Hydrological Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 3: 300-m Buffer Adjacent ot Study Wetland (a) Figure 3-5a. Scatterplots showing the re lationship between the LDI and the HGM hydrological category for four different spatial scales. Data on both axes are shown as ranked scores.

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37 LDIHGM (Biogeochemical Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 LEVEL 1: Watershed LDIHGM (Biogeochemical Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 2a: 300-m Buffer Surrounding Stream LDIHGM (Biogeochemical Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 LEVEL 2b: 100-m Buffer Surrounding Stream LDIHGM (Biogeochemical Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 3: 300-m Buffer Adjacent to Study Wetland (b) Figure 3-5b. Scatterplots showing the relationship between the LDI and the HGM biogeochemical category for four diffe rent spatial scales. Data on both axes are shown as ranked scores.

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38 LDIHGM (Habitat Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 LEVEL 1: Watershed LDIHGM (Habitat Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 2a: 300-m Buffer Surrounding Stream LDIHGM (Habitat Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 LEVEL 2b: 100-m Buffer Surrounding Stream LDIHGM (Habitat Category) 30 25 20 15 10 5 0 30 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 3: 300-m Buffer Adj acent to Study Wetland (c) Figure 3-5c Scatterplots showing the relationship be tween the LDI and the HGM habitat category for four different spatial scales. Data on both axes are shown as ranked scores.

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39 LDIUMAM 30 25 20 15 10 5 0 30 25 20 15 10 5 0 LEVEL 1: Watershed LDIUMAM 30 25 20 15 10 5 0 30 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 2a: 300-m Buffer Surrounding Stream LDIUMAM 30 25 20 15 10 5 0 30 25 20 15 10 5 0 LEVEL 2b: 100-m Buffer Surrounding Stream LDIUMAM 30 25 20 15 10 5 0 30 25 20 15 10 5 0 Groups Reference Rural UrbanLEVEL 3: 300-m Buffer Adjacent to Study Wetland Figure 3-6. Scatterplots showing the relationship between the LDI and the UMAM for four different spatial s cales. Data on both axes are shown as ranked scores.

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40 CHAPTER 4 SUMMARY AND DISCUSSION This study consisted of the following three inter-related objective s: 1) develop areal empower density values for land use classes based on existing LU/LC coverages of the BMW; 2) compute LDI values for floodplain forested wetlands for which three field based measures of wetland condition had been qu antified; and 3) statis tically determine if the LDI can be used as a predictor of wetland condition. The first objective required three tasks: 1) a detailed evaluatio n of the emergy use of Arkansas to develop multipliers of emergy use for land uses, 2) integration of LU/LC coverages into a usable set of land uses classes for which de tailed emergy flow data could be reasonably collected, and 3) detailed em ergy evaluations of the land uses to compute areal empower density for each. The analysis of the state of Arkansas and the detailed analyses of individual land use t ypes are presented in the Appendix. The primary spatial data source for development of the land use classes was the 1999 Arkansas LU/LC: Summer (CAST 2001), re ferred to hereafter as 1999 AR-LC/LU coverage. The coverage consisted of 46 LU /LC classes, from which 20 LU/LC classes were defined and their areal empower dens ity calculated. Systems diagrams were developed and used as an inve ntory guide for collecting materi al and energy flow data for each land use class. These data were used to develop emergy tables from which areal empower density was computed. The second objective of this study was to calculate LDI scores for floodplain forested wetlands in the BMW. A total of 29 wetlands were selected from within various

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41 landscape settings including natural, agricultural, and urban land uses. The a priori selection of wetlands provided a range of la ndscapes that represented a gradient from undeveloped to highly developed lands, although intermediate disturbances were lacking in the data set. The method of calculating LDI scores for wetlands differed somewhat from previous studies in Florida; LDIs are not calculated for individual land use and then averaged, but instead the areal empower dens ity was computed for the entire area of influence of each wetland and then an LDI was calculated using a deci-log formula that included a reference state. The result is a more robust LDI score since it does not result from the averages of LDIs but instead from the average of the area l empower densities. To test the appropriate spatial scale ove r which the LDI score should be calculated, LDI scores for each wetland study plot were co mputed for four different spatial scales. There were strong correlations between all four scales; however, the smallest scale (Level 3; 300-meter buffer surround the wetland study plot ) seems to be a better predictor of wetland condition. LDI scores computed at the la rger spatial scales had higher LDI scores than the Level 3 scores, reflecting the intense development in the large watershed. However, it appears that wetland condition resp onds to localized impacts more strongly than to conditions in upstream watersheds. This was also found in the earlier work on LDI in Florida (Brown and Vivas 2005; Lane et al. 2003; Reiss and Brown 2005; Reiss 2006). The final objective was to correlate the LD I scores of the wetland study plots with several indices of wetland condition. Strong co rrelations between the LDI scores and the WRAP were found, especially at the Level 3 spatial scale. Correlations between the LDI

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42 scores and the HGM were also relatively hi gh, particularly when the LDI scores were related to the habitat component of the HGM at the Leve l 3 spatial scale. Of the HGM categories, the habitat component had the st rongest correlations with LDI scores. The relationship between the LDI and the UMAM was not as strong. Land Use Land Cover Data Sources The 1999 AR-LU/LC coverage emphasized agri cultural land uses and forest classes providing only general descriptions for urba n land uses and surface water cover. Because of the general description of urban land uses and water c over provided by the Arkansas LU/LC map, these categories had to be aggregated or disaggregated to fit the requirements needed for LDI calculations ba sed on functional land us e categories. This was done using partial coverages for urban centers in the BMW provided by Metroplan, Arkansas, through the MAWPT, and aerial photography. To determine housing densities for residential areas, houses were counted with in one hectare plots laid on aerial photos. Aquatic systems, both natural and constructe d, were determined using a combination of thematic coverages availabl e through Geostor, a web-ba sed database containing all publicly available geodata for the state of Arkansas (http://www.cast.uark.edu/cast/geostor/), and identification of land uses using aerial photography. Integrating all of these coverages using GIS allowed obtaining a working LU/LC coverage for the BMW. The steps followed here to identify f unctional LDI land use classes can be replicated for other regions where similar LDI studies may be intended. In the absence of more detailed and recent data, the 1999 Ar kansas LU/LC: Summer map provides detailed information on agricultural la nd uses. Information on forest classes can be easily aggregated with enough knowledge of the forest types used in the map into two classes,

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43 uplands and wetlands. For the purpose of ar eal empower density calculation these two forest categories may provide the level of detail needed. For urban areas, if more complete urban converges exist for other regi ons a more accurate representation of urban land uses will be possible. However, even w ith general spatial data for a given area as was the case for the BMW, LU/LC classes will be able to be identified that will fit LDI calculation needs. Baseline housing densities estimates from aerial photos can be easily determined, especially for urban areas with low tree cover. Finally, Geostor provides data that complements the 1999 Arkansas LU/LC: Summer map with coverages for aquatic (e.g., rivers, lakes, reservoirs canals) and transportation sy stems (e.g., roads, railroads). Only a small set of land uses presented so me difficulty for its accurate representation. The 1999 Arkansas LU/LC: Summer map presents a category for no data that was partially identified using aerial photography. After merging the 1999 Arkansas LU/LC: Summer map with the existing maps for aqua tic systems from the Geostor database and those determined using remote data, some unde fined water areas still remained. A visual identification of these areas using aerial photographs showed that these areas most probably corresponded to rice fi elds (wet stage) and mana ged ponds (aquaculture). These areas were incorporated in the final LU/L C map as a separate land use category. To accurately identify undefined land use areas, fi eld visits to these areas are suggested. However, if the unidentified areas are re latively small and thei r identification though aerial photography suggests that these may belong to a well-defined land cover (e.g., agriculture), the areal empower density for a similar land use type (or a combination of land use types) may serve as a good approximati on of energy flows within these areas.

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44 Areal Empower Densities for Land Uses Emergy evaluation results for each land use showed no major departures from similar studies in Arkansas and Florida. For Arkansas, Odum et al. (1998) developed emergy evaluations for land uses for the C ache River watershed in the northeastern portion of the state. These included an emergy evaluation of the Black Swamp and emergy evaluations for rice, soybeans, sorghum and corn. Our results were similar to those reported by Odum and colleagues (1998) Where some differences were noted for the results of the study of the Cache Rive r watershed and this study, they can be attributed to differences in data sources and number of inputs considered in the emergy evaluations. However, results for both studies were within the ra nge of emergy values usually reported for agricultu ral crops for industrialized re gions. In Florida, BrandtWilliams (2001) calculated the areal empower de nsity of a variety of agricultural land uses. The results for the Flor ida study and for this research were very similar. The areal empower densities computed fo r urban land uses were higher in this study than those reported by Brown and Vivas (2005) in the state of Florida. Among the residential land uses differences can be partially attributed to different housing densities used in the two studies and partially to diffe rences in data sources. For non-residential land uses (i.e., commercial, in stitutional, industrial, and transportation) more complete data sources may account for most of the di fferences. The previous studies of Florida urban land uses were primarily comple ted in the 1980s and 1990s. Data sources nowadays are more completed and our methods of analysis have matured. So it is not unexpected that the more complete data a nd improved methods of analysis would result in slightly different emergy flow data for urban land uses. However, the areal empower

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45 densities computed in this st udy were within the range of values reported for urban land uses for developed regions. A Landscape Assessment of Wetland Ecological Condition Correlations between the LDI and indi ces of ecosystem condition, including wetland condition indices (Lane et al. 2003; Reiss and Brown 2005; Reiss 2006), the Stream Condition Index for Florida (Fore 2004) the Lake Vegetation Index (Fore 2005), rapid wetland assessment methods (Reiss 2004; Brown and Vivas 2005), and measures of the human disturbance gradient (Reiss 2004; Fore 2004; Mack 2006) suggest that the LDI may capture in one index the combined action of various factors th at result from human activity that influence ecosys tem structure and functioning. In this study the LDI was correlated with three rapid field procedures for wetland condition: the WRAP, the HGM, and the UMAM to test the usefulness of the LDI as a Level 1 assessment method. The LDI was calcula ted for four areas of different sizes surrounding 29 floodplain wetlands in th e BMW. The WRAP, UMAM, and HGM indices were computed for these wetlands by the MAWPT staff based on their field visits conducted in the Fall of 2005. The wetland condition scores (see Table 3-3) when compared to the four LDI scores exhibited intermixing of reference wetlands and rural we tlands along the LDI disturbance gradient. Since there were very few natural areas within the BMW from which reference wetlands (low human-impacted s ites) could be selected this result is not unexpected, as some of the reference sites had to be chosen from within agricultural landscapes and wetland study plots were located within local buffers of forested lands. This selection resulted in similar non-renewable and purch ased areal empower density

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46 values for some of the reference and rural si tes. This outcome was more evident at the broader landscape scales. Correlations between the UMAM and LDI scores were the weakest correlation among the variables analyzed. In general, UMAM scores for the rural sites and the urban sites were approximately within the same range of values an d did not show an alignment along the disturbance gradient. Inspection of the UMAN scores related to WRAP and HGM reveals that consistently, the UMAM scores were higher for urban wetland study plots and tended to be somewhat lower for refe rence and rural sites. The reason for this is not entirely clear. In this study, the functional component of the UMAM that assesses location and landscape support was not scored to avoid redundancy with the LDI, and only the water environment and community st ructure categories of the UMAM were measured. It should be noted that the HGM hydrological component also had the lowest correlation with LDI scor es (see Table 3-4). Among the different scales of landscapes considered in the calculation of LDI values for the wetland study plots, the Level 3 300 meters adjacent to the study plots, exhibited the strongest correlations with the WRAP and with the habitat and hydrological categories of the HGM. These results agree with Brown and Vivas (2005), who found that LDIs computed for 100-meter buffer areas surrounding small wetlands (< 2 hectares) had stronger correlations with wetla nd condition than larger areas. Conclusions Using existing LU/LC data for the BMW a group of 20 land use classes were identified for which the emergy use per uni t area per time or areal empower density (units: sej/ha/yr) was calculated. The areal em power density values of the non-renewable and purchased energies for the 20 land use classes were comparable to those reported for

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47 similar land uses in Arkansas (Odum et al. 1998) and Florida (Brandt-Williams 2001; Brown and Vivas 2005). Thus, the areal empower densities calculated here can be used in other regions within Arkansas and possi bly in other regions of the country. LDI scores were computed from areal em power densities of land uses for four different scale landscape regions surroundi ng 29 floodplain wetlands in the BMW. LDI scores were correlated with three indepe ndent measures of wetlands condition: the WRAP, HGM, and the UMAM. The LDI showed fair to good correlations with these indices with the highest correla tions reported with the WRAP and the habitat category of the HGM. Since the LDI has been developed a nd applied mostly in Florida, it has been suggested that it should be test ed in other regions to further assess its validity and utility as an assessment tool (Mack 2006). Results from the use of the LDI in the BMW provide additional supportive evidence of the usefulness of the LD I as a Level 1 assessment procedure for the estima tion of wetland condition.

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48 LIST OF REFERENCES Bardi, E., M.T. Brown, K.C. Reiss, and M. J. Cohen. 2005. UMAM: Uniform Mitigation Assessment Method training manual. Webbased training manual for Chapter 62345, FAC for wetlands permitting. Howard T. Odum Center for Wetlands and Center for Environmental Policy, University of Florida, Gainesville. Brinson, M.M. 1993. A hydrogeomorphic classifi cation for wetlands. Wetland Research Program Technical Report WRP-DE-4. U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS. Brandt-Williams, S. 2001. Handbook of emergy ev aluation: a compendium of data for emergy evaluation. Folio # 4 Emergy of Florida Agriculture. Center for Environmental Policy, Environmental Engine ering Sciences, University of Florida. Gainesville. Brooks, R. P., D. Heller-Wardrop, and J. A. Bishop. 2004. Assessing wetland condition on a watershed basis in the Mid-Atlantic region using synoptic land cover maps. Environmental Monitoring and Assessment. 94:9–22. Brown, M. T. 1980. Energy basis for hierarchie s in urban and regional landscapes. Ph. D. Dissertation, University of Flor ida, Gainesville, Florida, USA. Brown, M.T., and M.B. Vivas. 2005. Landscape development intensity index. Environmental Monitoring and Assessment 101:289-309. Center for Advanced Spatial Technologi es. 2001. 1999 Arkansas land-use/land-cover: summer. University of Arkansas, Fayetteville, AR. Cohen, M. J., S. Carstenn, and C.R. Lane 2004. Floristic quality indices for biotic assessment of depressional marsh condition in Florida. Ecological Applications 14:784–794. Dytham, C. 1999. Choosing and using statistics : a biologist’s guide. Blackwell Science, Oxford, UK. Fennessy, M.S., A.D. Jacobs, and M.F. Ke ntula. 2004. Review of rapid assessment methods for assessing the wetland condition. EPA/620/R-04/009. U.S. Environmental Protection Ag ency, Washington D.C.

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49 Fore, L.S. 2004. Development and testing of biomonitoring tools for macroinvertebrates in Florida streams. Statistical Design, S eattle, Washington. A report for the Florida Department of Environmental Protecti on, Tallahassee, Florida, USA. 62 p. Fore, L.S. 2005. Assessing the biological conditi on of Florida lakes: development of the lake vegetation index (LDV). Statistical Design, Seattle, Washington. A report for the Florida Department of Environmental Protection, Tallahassee, Florida, USA. 29 pp. & Appendixes. Lane, C.R. 2003. Biological indicators of we tland condition for isolated depressional herbaceous wetlands in Florida. Ph.D. Dissertation, University of Florida, Gainesville, Florida, USA. Lane, C.R., M.T. Brown, M. Murray-Hudson, and M.B. Vivas. 2003. The Wetland Condition Index (WCI): biol ogical indicators of wetla nd condition for isolated depressional herbaceous wetlands in Florida. Report submitted to the Florida Department of Environmental Protection (Contract #WM-683). H.T. Odum Center for Wetlands, University of Florid a, Gainesville, Florida, USA. Mack, J.J. 2006. Landscape as a predictor of wetland condition: an evaluation of the landscape development index (LDI) with a large reference wetland dataset from Ohio. Environmental Monitoring and Assessment DOI: 10.1007/s10661-0059058-8. Miller, R.E., Jr. and B.E. Boyd. 1999. Wetland ra pid assessment procedure. South Florida Water Management District, Technical Publication REG-001. West Palm Beach, Florida, USA. Odum, H.T. 1996. Environmental Accountin g: emergy and environmental decision making. John Wiley & Sons, Inc., New York. Odum, H.T., S. Romitelli, and R. Tighe. 1998. Evaluation overview of the Cache River and the Black Swamp in Arkansas. Fina l Report on Contract #DACW39-94-K0300 Energy Systems Perspectives for Cumulative Impacts Assessment between Waterways Experiment Station, U.S. De pt. of the Army, Vicksburg, Miss. and University of Florida. Center fo r Environmental Policy, Environmental Engineering Sciences, University of Florida, Gainesville. 128 p. Parker, N.M. 1998. Spatial models of to tal phosphorus loading and landscape development intensity in a North Florida watershed. Masters Thesis, University of Florida, Gainesville. Reiss, K.C. 2004. Developing biol ogical indicators for isol ated forested wetlands in Florida. Ph.D. Dissertation, University of Florida, Gainesville, Florida, USA. Reiss, K.C. 2006. Florida Wetland Condition In dex for depressional forested wetlands. Ecological Indicators 6:337-352.

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50 Reiss, K.C., and M.T. Brown. 2005. The Florida Wetland Condition Index (FWCI): preliminary development of biological in dicators for forested strand and floodplain wetlands. Report submitted to the Florida Department of Envi ronmental Protection under contract #WM-683. Howard T. Odum Center for Wetlands, University of Florida, Gainesville, Florida, USA. 94 p. Robbins, P., and T. Birkenholtz. 2003. Turfgra ss revolution: measuri ng the expansion of the American lawn. Land Use Policy 20:181-194. Surdick, A.J. 2005. Amphibian and avian spec ies composition of forested depressional wetlands and circumjacent habitat: the in fluence of land use type and intensity. Ph.D. Dissertation, University of Flor ida, Gainesville, Florida, USA. United States Environmental Protection Agency. 2001. Better assessment science integrating point and nonpoint sources: BASINS 3.0 User’s manual. EPA-823-B01-001. U.S. Environmental Protec tion Agency, Office of Water. Unite States Environmenta l Protection Agency. 2003. Elem ents of a State Water Monitoring and Assessment Program EPA 841-B-03-003. Washington D.C. Available at http://www.epa.gov/owow /monitoring/repguid.html. Accessed 08/2006. United States Geological Survey. 1999. Elevati on, National Elevation Database (USGS). U.S. Geological Survey, EROS Data Center. Vivas, M.B. 2006. An assessment of the qual ity of surface waters in Florida using emergy-based landscape indices and landscap e pattern indices. Ph.D. Dissertation, University of Florida, Gainesville, Florida, USA.

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A-1 APPENDIX A EMERGY EVALUATION OF THE STATE OF ARKANSAS A ND LAND USES OF THE BAYOU METO WATERSHED Introduction Emergy and Emergy Analysis Emergy analysis is an environmental acc ounting procedure for estimating the work required for a product or process in units of one kind of energ y, and allows the relation of economic development with environmental ch ange. It measures the contributions of nature to the regional economy. In this secti on a brief explanation of the emergy concepts and measures used in this project is provided. Emergy-related definitions are summarized in Table A-1. Table A-1. Summary of emergy de finitions (from Odum 1996). Available Energy = Potential energy capab le of doing work and being degraded in the process (units: kilocalories, joules, British thermal units) Useful Energy = Available energy used to increase system production and efficiency Power = Useful energy flow per unit time Emergy = Available energy of one ki nd previously required directly and indirectly to make a produc t or service (units: emjoules) Empower = Emergy flow per unit time (units: emjoules per time) Transformity = The emergy of one type required to make a unit of energy of another type. A measure of en ergy quality (units: emjoule per joule) Emdollar Value = The dollars of gross economic product equivalent to the wealth measured in emergy Wealth = Usable products a nd services however produced

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A-2 Emergy and energy hierarchy Emergy is a measure of the available ener gy that was used in transformations and work to make a product or service (Odum 1996). It is cal culated from data on energy flows that go into the product or process; its unit of measure is the solar emergy joule or emjoule (abbreviated sej). Because of the second energy law, all of the processes of nature and the economy can be arranged in a series, representi ng the hierarchy of energy. In addition, all processes use up some of the available energy to do work, dispersing that energy as heat (degraded energy) and resulting in less available energy in its output than its inputs. Thus, processes may be arranged in an energy tr ansformation series as shown in Figure A-1. Total energy flow (power) decreases from le ft to right, but become s more concentrated. Also shown is how in each step of the hierarchy some of the available energy is dispersed. Food chains, stages in the hydrol ogical cycle, and steps in the production sectors of the economy are examples with such an organization (Odum et al 1998). Transformity Transformity is a measure of the hierarchy of energy. Transformity is defined as the energy per unit energy and is a measur e of energy quality (O dum 1996). Unlike the energy flow, which decreases through an en ergy transformation series, the emergy flow remains the same or increases if more inputs are added. Transformities are used to calculate emergy from data on energy (i.e., solar emergy = energy solar transformity; refer to Figure A-1).

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A-3 Solar Energy 1000100101 1 10 910818 Transformity=SolarEmergy/Energy 1000 1000 =1 1000 100 =10 1000 10 =100 1000 1 =1000 Figure A-1. A series of energy transformations forming an energy hierarchy from left to right with their corresponding transformities. Energy flow is measured as calories per time (modified fr om Odum et al. 1998). Areal empower density Power is defined as the rate of flow of energy into useful work (Odum 1994). When work is performed in a unit area we can speak of the energy flow as areal power density with units of power divided by area (e.g., watt/m2). Similarly, a flow of emergy is empower (measured in solar emjoule per time); when it is applied in a unit area it is referred to as areal empower density and can be interpreted as a measure of work per area per time (units: sej/ha-yr) (Odum 1996). An area with high energy use, such as a city, will have a higher areal empower density than areas using less energy, such as rural areas. Since self-organizing systems develop cen ters of energy processing, a city is a hierarchical center with high concen trations of empower (Odum 1996). Emdollars and real wealth The emdollar is defined as the emergy di vided by the emergy/money ratio for an economy for a given year (Odum 1996). Emdollars allow the combination of environmental resource contributions on a co mmon basis with contri butions purchased by the economy. Since money is paid only to people for their c ontribution, money and market values cannot be used to evaluate the contribution of the environment to a

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A-4 process. The real wealth of an area or pr ocess includes inputs free from the environment and those purchased and transpor ted in (Odum 1996). Emergy is a measure of real wealth since it allows evaluating the contributi ons from nature and those by humans on a common basis. As summarized in Figure A-2, dividing the annual emergy use by the gross economic product provides a useful measur ement for relating real wealth to money. Emergy indices Emergy indices are useful for evaluati ng systems and their potential. Two commonly used ratios of emergy flows in e nvironmental accounting are defined in Figure A-3. The emergy yield ratio is calculated by di viding the emergy of the yield (Y) flowing into the economy on the right by the emergy of all of the f eedbacks (F) from the economy (e.g., fuels, fertilizers, serv ices). The emergy yield ratio is a measure of the net contribution of a system to the economy (O dum 1996). A system with a large net emergy ratio contributes much more real wealth than is required for th e process. Examples of this are rich mineral deposits and abundant fresh waters (Odum et al. 1998). The emergy investment ratio allows the qua ntification of the intensity of regional economic development and the use of the environment. The emergy investment ratio is defined as the ratio of emergy purchased fr om the economy (F) to the emergy used free from the local environment (E). Less develope d areas have lower ratio values than more developed ones. The U.S. has an investment ratio of 7, while Ecuador, which is a less developed country, has an investment ratio of less than 1 (Odum 1996).

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A-5 Fuels, Materials, Fertilizers, Goods&Serv. Elec.Power Markets Gross Economic Product $ $ Sun,Wind, Rain,Rivers, EarthHeat EmpowerUse GrossEconomicProduct =Emergy/moneyratio State ResourcesPurchased OutofState SalesOutofState Figure A-2. Empower (emergy flow) and money circulation in a state. The emergy-tomoney ratio allows evaluating emdol lar of environmental contribution (modified from Odum et al. 1998). System Feedback(F) Yield(Y) Indigenous(I) Sources Main Economy EmergyInvestmentRatio= F I EmergyYieldRatio= Y F Figure A-3. Emergy indices used to evaluate environmental development (modified from Odum et al. 1998).

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A-6 Background of Previous Studies using Emergy Emergy accounting has allowed the rela tion of economic development with environmental change for a great variety of products and processes around the world. Most of this work is summarized in Odum ( 1996), and more recently in a series of folios published by the H.T. Odum Center for E nvironmental Policy of the University of Florida (Odum 2000; Odum et al. 2000; Br own and Bardi 2001; Brandt-Williams 2001; Kangas 2002), and in the proceedings of th e biennial Emergy Synthesis Research Conferences initiated in 1999 (i.e., Brown 2000; Brown 2003, Brown 2005). The scientific basis of the emergy methodology is de scribed in greater deta il in Odum (1994). The study of watersheds using emergy wa s begun more than 20 years ago. These studies have been directed to describe pr operties of watersheds, their patterns of development, and to propose management alte rnatives. Most of the earliest studies are summarized in Odum (1996). The work done by Odum et al. (1998) for the Cache River watershed in northeastern Arka nsas is of particular rele vance for the present study and seems to be the only reported case of simila r studies for this stat e. Odum and colleagues (1998) found that environmental contributions within that system accounted for approximately half of the watersheds’ wealth (measured in emergy units) while the other half was from inputs purchased from outsi de the system. The Cache River watershed, which is mostly an agricultural area based on indigenous soils and waters, proved to be a net emergy exporter. This study included an emergy evaluation of the Black Swamp and emergy evaluation of six production systems with in the watershed: rice, soybeans, wheat, sorghum, corn, and poultry broiler production. Odum et al. (1998) also evaluated the st ate of Arkansas using emergy and based on data for 1990. Arkansas was found to be 58% se lf-sufficient. With an emergy investment

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A-7 ratio of 0.73, Arkansas had a higher percentage of its economic basis supplied from the environmental emergy than more developed st ates like Florida or Texas. The emergy-tomoney ratio was 3.45 E12 sej/$, compared to th e same ratio of 1.55 E12 sej/$ for the U.S. for 1990 (Odum 1996). For the Mississippi River Watershed, Di amond (1984) and Odum et al. (1987) evaluated the propertie s of stream orders based on their environmental and economic empower. These studies revealed that the ge opotential energy fluxe s were greatest at intermediateto high-o rder levels while the delta and floodplain regions were found to be regions of emergy convergence. Methods Emergy evaluations are data intensiv e operations, requiring collection and cataloging of a variety of materi al and energy flows. The opera tion is organized into three related task; 1) drawing of system diagrams that capture the main flows of energy and materials supporting the system under study, 2) listing of data in an emergy evaluation table and 3) summary of data through the us e of indices of energy and material use that describe the system and its processes. The fo llowing provides details of each step in the methodology. Energy System Diagramming Energy system diagrams are useful since they allow the summarization of energy inputs and flows of a system and provide an overview of the main components, processes, problems, and contributing f actors to a system (Odum 1996). An emergy evaluation starts with the drawing of a diagra m of the system of in terest. After defining the physical boundary, important outside so urces are listed and drawn around the

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A-8 boundary from left to right in order of incr easing transformity, which marks their position in the energy hierarchy (i.e., sun, wind, ra in, geology, fuel, chemicals, goods, services, market, etc.). The main internal components and processes in the system are identified and drawn inside the system frame using en ergy system symbols. The system symbols that are commonly used are presented in Table A-2. In the diagramming process these symbols represent system components such as forests, agriculture and industrial producers, urban areas, and water and soil stor ages. The final step in the diagramming process is to connect pathways, interactio ns, and money transactions using arrows. A detailed discussion on the construction and ma thematical description of energy systems diagrams and symbols is provided in Odum (1994). Energy system diagrams showing primar y components, sources, and flows were drawn for each of 20 different land uses within BMW. Diagrams were used as the basis for creating an inventory of the energy and material flows needed in emergy evaluations. Emergy Tables The second step in the emergy evaluation proced ure is to develop emergy analysis tables. The main components of the emergy table are sh own in Table A-3. A table consists of six columns: (1) the number of the line item and its footnote; (2) the name of the item to be estimated; (3) data in units of energy mass, or cost; (4 ) emergy per unit (or transformities); (5) solar emergy; and (6) emdollars. Each input and output from the system were included in the table as a line item The solar emergy of each line item was estimated by multiplying the energy, mass, or money data in column 3 by the solar emergy per unit from column 4. Transformities were obtained from previous emergy studies and were referenced accordingly.

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A-9 Table A-2. Primary symbols of the energy circuit diagramming. Symbol Name Description System boundary Defines the system being di agrammed. Lines that cross the system boundary indicate inflows and outflows of the system. Energy circuit A pathway with a flow proportional to the quantity in the storage or source upstream. Source A forcing function or out side source of energy delivering forces according to a program controlled from outside. Flow limited source Outside source of energy with a flow that is externally controlled. Storage tank A compartment of energy storage within the system storing a quantity as th e balance of inflows and outflows. Sensor The sensor (small square box on storage) suggests the storage tank controls some other flow but does not supply the main energy for it. Producer Unit that collects and transforms low-quality energy under the control of hi gh-quality flows. Consumer Unit that transforms energy qua lity, stores it, and feeds it back autocatalytically to improve inflow. Box Miscellaneous symbol to use for whatever unit or function is needed. Heat sink Dispersion of potential energy into heat that accompanies all real transformation processes and storages. Dispersed energy is no longer available to the system. Separate emergy evaluation tables were prepared for each of the 20 different land uses in the BMW. Each land use was evaluate d based on a spatial area of one hectare, therefore the areal empower density was deri ved directly from the table by summing the solar emergy for each line item.

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A-10 Table A-3. Tabular format for an emergy evaluation. Notesa Itemb Data Units (J, g or $) Solar Emergy/unit (sej/unit) Solar Emergy (sej/yr) Em$ ($/yr) 1 1 2 2 … … n n a Footnotes for each row of the table are placed here. b One row for each source, proce ss, or storage of interest. Data Sources The material flows, energy requirements, and economic data required for emergy evaluations were obtained from a variety of sources. Government sources were the first choice when the data were available, since these data are usually more reliable. As a result, a variety of federal a nd state publications and databa ses were consulted via library and electronic research. Academic sources were also widely consulte d, particularly in the development of the emergy evaluations of ag ricultural land uses. Information provided by the agricultural extension servic es of different universities in Southern U.S., including the University of Arkansas, was used on multiple occasions. Published and unpublished academic documents were also widely used. Among these, a variety of documents such as reports, academic dissertations, and thes es from the University of Florida were frequently used as sources for emergy-related data such as transformities, and to compare results with previous emer gy evaluations and work. When required, data were transformed to meaningful emergy units, usually mass, that can be easily converted to energy units. In all cases, data usag e and conversions were reported in the footnotes for Column l of the emergy tables (see Table A-2). When required, assumptions about the data were made and also reported in the footnotes. Each

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A-11 source that was consulted was a ppropriately referenced in the footnotes secti on. All of the data were reported using the metric system since it is universally used and is the most convenient when data are obtained from many different sources. Results Emergy Evaluation of Arkansas Energy systems diagram The overview model of the state of Arka nsas is shown in Figure A-4. The main outside environmental and purchase inputs ar e shown, as well as the main internal components and processes in the state. On th e left of the diagram are the environmental and rural systems with their main energy s ources (sun, wind, rain, ri vers, and geological processes). These are production areas incl uding forests, grasslands, wetlands, and agricultural crops. On the right side of the diagram are the consumer sectors. These are mainly located in towns and cities. Energy inpu ts purchased from outside including fuels, food, fertilizers, machinery, goods and services, t ogether with inputs from within the state constitute the non-renewable resources basi s used to power the economy. Arkansas exports include agricultural crops, machin ery, chemicals, and meat. Additional energy flows outside the state include waste products. Summary diag rams with the aggregated pathways for evaluating the overall energy use in the state are presented in Figure A-5.

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A-12 Hydro power Population Industry, Commerce Grasslands Ozark Uplands Earth cycle Rain Water Storages Goods & Services AgricultureSoybeans &Rice Sorghum &Cotton Corn& Hay Wind Rivers Fuel Oil Gas Coal Forests& wetlands Livestock, Poultry, Fish Wastes $ Ag. products& food Chemicals & Fertilizers Metals (Fe,Cu, Al,Zn) Mach. &transp. equip. Rivers Sun ET Utilities Nut. Sed. H 2 O People & Tourism Soils& Nutrients Gov’t, Institutions Figure A-4. Energy systems diagram for the state of Arkansas with main inputs, internal components, and pathways.

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A-13 Goods Services &other goods Markets Rural systems Renewable resources Non Renewable Exports UrbanUse RuralUse $ $F G P2I I P2 R N2 N0 N1 N2 P1E E x $9.65E+10E20solaremjoules/yrE10$/yr (a) Arkansas Imports(F) F+G+P2I Exports(Y) N2+P1E Indigenous(I) sources R+N0+N1 ( b ) Fuels, minerals &metals 436.79 404.16 68.08 249.27 759.22 230.30 648.90 1247.36 $3.89E+10 68.08 $3.91E+10 1093.28 1638.42 1315.26 Figure A-5. Summary diagrams of emergy flows in the state of Arkansas in 2001. (a) aggregated diagram; (b) three-arm diag ram aggregated further into threee flows: indigenous resources (I), imports (F), and exports (Y).

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A-14 Emergy evaluation table The emergy evaluation of the environmental inputs, imports, and exports for Arkansas are presented in Table A-4. Fo r 2001 the total emergy used by the state’s economy was 2.73 E23 sej. Contributions to the state’s real wealth are shown in graph form in Figure A-6. The contributions are orga nized from left to right according to their position in the energy hierarchy. The major environmental contribution to the state came from the rain’s chemical potential energy, which accounts for 58% of the total renewable inputs into the system. Agriculture and livestock production (inc luding poultry) accounted for 94% of the indigenous renewable energies. Soil losses were high, and together with electricity and natural gas, they were the most importan t non-renewable resources from within the system. Among the purchased inputs, fossil fuels (gas, coal, oil and its derivates) were the major inputs driving the economy together with the services of imports. Fuels represented 44% of the state’s imports and services accoun t for 38% of the total imports. Fuel imports reflect the increasing depende ncy on outside sources of fo ssil fuels, as the state’s production of coal and oil has decreased over the last two decades. Organic chemicals and meat were the top export products from th e state; machinery and transportation equipment as well as agricultural products followed. The services associated with the state’s exports account ed for 88% of the total exported emergy. Emergy indices The indices derived from the emergy evalua tion table for Arkansas are presented in Table A-5 and Table A-6. Imported fuels a nd minerals accounted were the highest emergy imports in the state while the emer gy value of goods and services was highest among exports (Table A-5). The solar em ergy-to-money ratio was 2.83 E12 sej/$.

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A-15 Table A-4. Emergy evaluation of resource basis for the state of Arkansas for 2001. Note Item Raw Units Transformity (sej/unit)* Solar Emergy (E20 sej) EmDollars (E9 US$) RENEWABLE RESOURCES: 1 Sunlight 6.48E+20J 1.00E+00 6.50.2 2 Rain, Chemical 8.08E+17J 3.05E+04 246.49.0 3 Rain, Geopotential 6.03E+15J 4.70E+04 2.80.1 4 Wind, Kinetic Energy 1.38E+18J 2.45E+03 33.91.2 5 Inflow River Geopotential 1.06E+17J 4.70E+04 49.81.8 6 Inflow River Chemical Potential 6.44E+15J 8.14E+04 5.20.2 7 Earth Cycle 1.38E+17J 5.80E+04 79.92.9 INDIGENOUS RENEWABLE ENERGY: 8 Hydroelectricity 9.17E+15J 3.36E+05 30.81.1 9 Agriculture Production 1.34E+17J 3.36E+05 448.816.3 10 Livestock Production 1.27E+16J 3.36E+06 426.415.5 11 Fisheries Production 1.88E+14J 3.36E+06 6.30.2 12 Fuelwood Production 0.00E+00J 2.21E+04 0.00.0 13 Forest Extraction 9.09E+16J 2.21E+04 20.10.7 0.0 NONRENEWABLE SOURCES FROM WITHIN SYSTEM: 14 Natural Gas 1.84E+17J 8.06E+04 148.35.2 15 Oil 4.63E+16J 8.90E+04 41.21.5 16 Coal 5.08E+14J 6.69E+04 0.30.0 17 Minerals (Bromine) 1.75E+11g 2.20E+10 38.51.4 18 Soil Losses 1.94E+13g 1.68E+09 325.711.8 19 Topsoil Losses 1.31E+16J 7.40E+04 9.70.4 20 Groundwater 4.69E+16J 1.60E+05 75.02.7 21 Electricity 5.32E+16J 3.36E+05 178.86.3

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A-16 Table A-3. Continued. Note Item Raw Units Transformity (sej/unit)* Solar Emergy (E20 sej) EmDollars (E9 US$) IMPORTS AND OUTSIDE SOURCES: 22 Fuels 8.79E+17J 8.55E+04 751.326.5 23 Metals 1.02E+11g 7.75E+09 7.90.3 24 Fertilizers 2.32E+11g 2.19E+10 50.81.8 25 Agricultural Products 2.27E+15J 3.36E+05 7.60.3 26 Meat, Fish & Related Foods 1.57E+14J 3.36E+06 5.30.2 27 Plastics & Rubber 2.56E+15J 1.11E+05 2.80.1 28 Chemicals (incl. pesticides) 1.92E+11g 2.49E+10 47.61.7 29 Finished Materials 4.32E+11g 1.89E+09 8.10.3 30 Machinery & Transportation Equipment 1.61E+12g 6.70E+09 108.03.9 31 Services in Imports 3.91E+10$ 1.66E+12 648.923.6 32 Tourism 3.81E+09$ 1.66E+12 63.32.3 EXPORTS: 33 Agricultural Products 3.92E+15J 3.36E+05 13.20.5 34 Meat 1.06E+15J 3.36E+06 35.61.3 35 Paper/Paperboard 2.16E+11g 3.69E+09 8.00.3 36 Fuels 0.00E+00J 0.00E+00 0.00.0 37 Metals 1.88E+11g 6.13E+09 11.50.4 38 Minerals (bromine) 3.08E+10g 2.20E+10 6.80.2 39 Organic Chemicals 2.00E+11g 2.49E+10 49.81.8 40 Machinery & Transportation Equipment 2.91E+11g 6.70E+09 19.50.7 41 Plastics 7.76E+14J 1.11E+05 0.90.0 42 Services in Exports 3.89E+10$ 2.75E+12 1071.438.9 Transformity based on a global renewable emer gy flow of 15.83E24 sej/yr (Odum et al. 2000).

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A-17 Table A-3. Continued Footnotes: RENEWABLE RESOURCES: References: 1 SOLAR ENERGY: Cont Shelf Area = 0.00E+00 m2 Land Area = 1.38E+11 m2 (AGC; www.state.ar.us/agc) Insolation = 1.41E+02 Kcal/cm2/yr (Odum et al. 1998) Albedo = 0.20 (% given as decimal) (After www.nasa.gov) Energy(J) = (area incl. shelf)(avg. insolation)(1-albedo) = (__m2)(__Cal/cm2/y)(E+04cm2/m2)(1-albedo)(4186J/kcal) = 6.48E+20 J/yr Transformity = 1.00+00 sej/J (Odum 1996) 2 RAIN, CHEMICAL POTENTIAL ENERGY: Land Area = 1.38E+11 m2 Cont Shelf Area = 0.00E+00 m2 Rain (land) = 1.21 m/yr (www.noaa.gov) Rain (shelf) = 0.00 m/yr Evapotranspiration rate = 1.19 m/yr (Odum et al. 1998) Energy (land) (J) = (area)(Evapotranspiration)(Gibbs no.) = (__m2)(__m)(1000kg/m3)(4.94E3J/kg) = 8.08E+17 J/yr Energy (shelf) (J) = (area of shelf)(Rainfall)(Gibbs no.) = 0.00E+00 J/yr Total energy (J) = 8.08E+17 J/yr Transformity = 3.05E+04 sej/J (Odum et al. 2000) 3 RAIN, GEOPOTENTIAL ENERGY: Area = 1.38E+11 m2 Rainfall = 1.21 m Avg. Elev. = 198.12 m (650 feet) (Carpenter & Provorse 1998) Runoff rate = 0.02 % (percent, given as a decimal ) Energy(J) = (area)(rainfall)(% runoff)(avg. elevation)(gravity) = (__m2)(__m)(__%)(1000kg/m3)(_m)(9.8m/s2) = 6.03E+15 J/yr Transformity = 4.70E+04 sej/J (Odum 2000) 4 WIND ENERGY: Area = 1.38E+11 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2000; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air density)(drag coefficient)(velocity3) = (__m2)(1.3 kg/ m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Energy(J) = 1.38E+18 J/yr Transformity = 2.45E+03 sej/J (Odum et al. 2000) 5 RIVER GEOPOTENTIAL: Major inflowing rivers: Arkansas and Mississippi rivers Flow in Arkansas River = 1.02E+03 m3/s (At Dardanelle, AR, data for 2001; www.usgs.gov) Elevation in = 2.10E+02 m (Odum et al. 1998) Elevation out = 3.05E+01 m Energy (J) = (volume)(density)(height in-height out)(gravity) = (__m3)(1.0E3kg/m3)(__m __m)(9.8 m/sec2) Energy (J) = 5.66E+16 J/yr Flow in Mississippi River = 1.33E+04 m3/s (Odum et al. 1998) Elevation in = 4.50E+01 m (Odum et al. 1998)

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A-18 Elevation out = 2.10E+01 m Energy (J) = (volume)(density)(height in-height out)(gravity) = (__m3)(1.0E3kg/m3)(__m __m)(9.8 m/sec2) Energy = 9.86E+16 J/yr Energy used in the State = 4.93E+16 J/yr (Assumed 1/2 used after Odum et al. 1998) Total energy = 1.06E+17 J/yr Transformity = 4.70E+04 sej/J (Odum et al. 2000) 6 RIVER CHEMICAL POTENTIAL: Gibbs free energy = [(8.3143 J/mol/deg)(288 K)/(18 g/mol)] ln [(1e6 Solutes)ppm)/965000] Dissolved solids in = 2.00E+02 ppm (Odum et al. 1998) Dissolved solids out = 4.00E+02 ppm (Odum et al. 1998) Gibbs free energy in = 4.71E+00 J/g Gibbs free energy out = 4.69E+00 J/g Flow in Arkansas River = 1.02E+03 m3/s Energy (J) = (volume)(density)(Gibbs free energy) = (__m3/s)(1.0E3 kg/ m3)(__J/g) Energy in = 1.52E+17 J/yr Energy out = 1.51E+17 J/yr InOut = 8.57E+14 J/yr Flow in Mississippi River = 1.33E+04 m3/s Energy in = 1.98E+18 J/yr Energy out = 1.97E+18 J/yr InOut = 1.12E+16 J/yr Energy Used in the State = 5.58E+15 J/yr (Assumed 1/2 used) Total Energy = 6.44E+15 J/yr Transformity = 8.14E+04 sej/J (Odum 1996) 7 EARTH CYCLE: Land area = 1.38E+11 m2 Heat flow = 1.00E+06 J/ m2 (Odum et al. 1998) Energy (J) = (area)(Heat flow) Energy (J) = (__m2)(1.00E6 J/ m2) = 1.38E+17 J/yr Transformity = 5.80E+04 sej/J (Odum 2000) INDIGENOUS RENEWABLE ENERGY 8 HYDROELECTRICITY: Kilowatt Hrs/yr = 2.55E+09 KwH/yr (APSC, 2001 data; www.arkansas.gov/psc) Energy (J) = (Energy production)(energy content) Energy (J) = (__KwH/yr)(3.6 E6 J/KwH) = 9.17E+15 J/yr Transformity = 3.36E+05 sej/J (Odum 1996) 9 AGRICULTURAL PRODUCTION: Rice = 4.67E+06 MT/yr (USDA, 2001data; www.nass.usda.gov/ar) Sorghum = 3.71E+05 MT/yr Cotton = 3.99E+05 MT/yr Soybeans = 2.48E+06 MT/yr Corn = 6.81E+05 MT/yr Wheat = 1.37E+06 MT/yr Total production = 9.97E+06 MT/yr (dry mass, 20% humidity) Energy (J) = (Total production)(energy content) Energy (J) = (__ MT/yr)(1E06 g/MT)(80%)(4.0 kcal/g)(4186 J/kcal) = 1.34E+17 J/yr Transformity = 3.36E+05 se j/J (Brown & McClanaham 1996)

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A-1910 LIVESTOCK PRODUCTION: Cattle = 3.36E+05 MT/yr (USDA, 2001data; www.nass.usda.gov/ar) Pigs = 5.13E+04 MT/yr Poultry = 2.64E+06 MT/yr Livestock production = 3.03E+06 MT/yr (80% humidity) Energy (J) = (Total production)(energy content) Energy(J) = (__MT/yr)(1E+06 g/MT)(20%)(5.0 KCal/g)(4186 J/KCal) = 1.27E+16 J/yr Transformity = 3.36E+06 sej/ J (Brown & McClanaham 1996) 11 FISHERIES PRODUCTION: Fish Catch = 4.49E+04 MT/yr (80% humidity) (USDA, 2001data; www.nass.usda.gov/ar) Energy (J) = (Total production)(energy content) Energy (J) = (__MT)(1E+06 g/MT)(5.0 KCal/g)(20%)(4186 J/KCal) = 1.88E+14 J/yr Transformity = 3.36E+06 sej/ J (Brown & McClanaham 1996) 12 FUELWOOD PRODUCTION: Fuelwood Prod = 0.00E+00 m3 Energy (J) = (Total production)(energy content) Energy (J) = (__m3)(0.5E6g/ m3)(3.6 kcal/g)(80%)(4186 J/kcal) = 0.00E+00 J/yr Transformity = 2.21E+04 sej/J (Romitelli 2000) 13 FOREST EXTRACTION: Harvest = 1.51E+07 m3 (After Mehmood & Pelkki 2005) Energy (J) = (Total production)(energy content) Energy (J) = (__m3)(0.5E+06 g/ m3)(80%)(3.6 kcal/g)(4186 J/kcal) = 9.09E+16 J/yr Transformity = 2.21E+04 sej/J (Romitelli 2000) NONRENEWABLE RESOURCE USE FROM WITHIN THE STATE 14 NATURAL GAS: Consumption = 4.90E+06 m3/yr (ADED 2003) Energy (J) = (__m3/yr)(energy content) Energy (J) = (__m3/yr)(8966 kcal/ m3)(4186 J/kcal) = 1.84E+14 J/yr Transformity = 4.80E+04 sej/J (Odum 1996) 15 OIL: Consumption = 7.59E+06 barrels (ADED 2003) Energy (J) = (__barrel/yr)(energy content) Energy (J) = (__barrel/yr)(6.1E9 Joules/barrel) = 4.63E+16 J/yr Transformity = 8.90E+04 sej/J (Odum 1996) 16 COAL: Consumption = 1.75E+04 MT/yr (AGC; www.state.ar.us/agc) Energy (J) = (__MT/yr)(energy content) Energy (J) = (__MT/yr)(2.9E+10 J/MT) = 5.08E+14 J/yr Transformity = 6.69E+04 sej/J (Odum 1996) 17 MINERALS (Bromine): Consumption = 1.75E+05 MT/yr (AGC; www.state.ar.us/agc) Mass (g) = (__E5 MT)(1E6 g/MT) = 1.75E+11 g/yr Transformity (weighed) = 2.20E+10 sej/g (Odum et al. 1998)

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A-2018/19 TOPSOIL AND SOM: Harvested cropland = 3.88E+10 m2 (www.ers.usda.gov) Soil loss = 5.00E+02 g/m2/yr (Odum et al. 1998) Average organic content (%) = 3 % Energy (J) = (__ g/ m2/yr)( __ m2)(% organic)(5.4 K cal/g)(4186 J/Kcal) = 1.31E+16 J/yr Mass (g) = 1.94E+13 g/yr Transformity Soil = 1.68E+09 sej/g (Odum 1996) Transformity SOM = 7.40E+04 sej/J (Brown & Bardi 2001) 20 GROUNDWATER: Groundwater consumption = 6.92E+03 Mgal/d ay (http://water.usgs.gov, data for 2000) = 9.57E+09 m3/yr Energy (J) = chemical potential of groundwater Energy (J) = (volume)(density)(Gibbs no.) = (__m3/yr)(1.0E6 g/ m3)(4.94J/g) = 4.69E+16 J/yr Transformity = 1.60E+05 sej/J (Odum et al. 1998) 21 ELECTRICITY: Kilowatt Hrs/yr = 1.48E+10 KwH/yr (EAI, 2001 data; www.arkansas.gov/psc) Energy (J) = (Energy production)(energy content) Energy (J) = (__KwH/yr)(3.6 E6 J/KwH) = 5.32E+16 J/yr Transformity = 1.60E+05 sej/J (Odum 1996) IMPORTS OF OUTSID E ENERGY SOURCES: 22 FUELS: (EIA, State Energy Data 2001; www.eia.doe.gov) Total natural gas used = 7.11E+09 m3/yr Used-produced = 7.10E+09 m3/yr Energy (J) = (__m3/yr)(8966 kcal/m3)(4186 J/kcal) Total oil used = 7.10E+07 barrels Used-produced = 6.34E+07 barrels Energy (J) = (__ barrel/yr)(6.1E9 Joules/barrel) Total coal used = 1.41E+07 MT/yr Used-produced = 1.41E+07 MT/yr Energy (J) = (_ MT/yr)(2.9E10 J/Mt) Transformity Natural gas = 2.67E+17 J/yr 5.88E+04 sej/J (Romitelli 2000) Oil derived fuels = 3.87E+17 J/yr 1.11E+05 sej/J (Odum 1996) Coal = 4.09E+17 J/yr 6.69E+04 sej/J (Odum 1996) = 1.06E+18 J/yr Transformity (weighed) = 8.09E+04 sej/J 23 METALS: Estimates as fraction of US imports of metals in 2001. (Data from UN Statistics Division; http://unstats.un.org) Transformity Aluminum unwrought = 2.68E+06 MT/yr 1.43E+09 sej/g (Odum 1996) Aluminum worked = 8.77E+05 MT/yr 1.25E+10 sej/g (Brown & Buranakam 2000) Iron ore = 4.68E+06 MT/yr 1.44E+09 sej/g (Odum 1996) Steel = 2.18E+06 MT/yr 4.13E+09 sej/g (Brown & Buranakam 2000) Copper wire = 3.16E+05 MT/yr 1.66E+11 sej/g (Odum 1996) US imports = 1.07E+07 MT/yr 7.75E+09 sej/g Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) State imports = 1.02E+05 MT/yr Mass (g) = (__MT/yr)(1E6 g/MT) = 1.02E+11 g/yr Transformity (weighed) = 7.75E+09 sej/g

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A-21 24 FERTILIZERS: Estimates were done considering the use of fertilizer per crop and the area planted by crop in the State. Fertilizer used/ha N P2O5 K2O Area Kg/ha Kg/ha Kg/ha ha Sorghum 37.8 3.4 0.9 7.08E+04 (Odum et al. 1998) Wheat 89.7 1.12 0 4.45E+05 Rice 134.5 0 33.6 6.60E+05 (www.nass.usda.gov/ar) Cotton 40 16 17 4.37E+05 Soybeans 5.61 0 33.6 1.17E+06 Consumption Transformity Phosphorus = 7.73E+03 MT/yr 2.99E+10 sej/g (Odum 1996) Potash = 6.91E+04 MT/yr 2.92E+09 sej/g (Odum 1996) Nitrogen = 1.55E+05 MT/yr 7.73E+09 sej/g (Odum 1996) Total consumption = 2.32E+05 MT/yr 2.19E+10 sej/g Mass (g) = (__E6 MT/yr)(1E6 g/MT) = 2.32E+11 g/yr Transformity (weighed) = 2.19E+10 sej/g 25 AGRICULTURAL PRODUCTS: Estimates were done as fraction of US imports of agricultural products in 2001. US imports = 2.04E+07 MT/yr (UN Statistics Division; http://unstats.un.org) Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) State imports = 1.94E+05 MT/yr Energy (J) = (__ MT/yr)(1E6g/MT)(3.5 Kcal/g)(4186 J/Kcal)(80%) = 2.27E+15 J/yr Transformity = 3.36E+05 sej/ J (Brown & McClanaham 1996) 26 MEAT, FISH & RELATED FOODS: Estimates were done as fraction of US imports of meat and fish products in 2001. US imports = 3.58E+06 MT/yr (UN Statistics Division; http://unstats.un.org) Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) State imports = 3.41E+04 MT/yr Energy (J) = (__MT/yr)(1E6 g/MT)(5 Kcal/g)(4186 J/Kcal)(0.22 protein) = 1.57E+14 J/yr Transformity = 3.36E+06 sej/ J (Brown & McClanaham 1996) 27 PLASTICS & RUBBER: Estimates were done as fraction of US imports in 2001. Imports = 3.01E+10 $/yr (UN Statistics Division; http://unstats.un.org) Average price = 3.34E+03 $/MT Imports = 8.99E+06 MT/yr Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) State imports = 8.54E+04 MT/yr Energy (J) = (__ MT/yr)(1000 Kg/MT)(30.0E6J/kg) = 2.56E+15 J/yr Transformity = 1.11E+05 sej/J (Odum 1996) 28 CHEMICALS: Estimates were done as fraction of US imports in 2001. Imports = 2.02E+07 MT/yr (UN Statistics Division; http://unstats.un.org) Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) State imports = 1.92E+05 MT/yr

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A-22 Mass (g) = (__MT/ yr)(1E6g/MT) = 1.92E+11 g/yr Transformity = 2.49E+10 sej/g (as pesticides) (Brown and Arding 1991, in Brandt-Williams 2001 ) 29 FINISHED MATERIALS (lumber, pape r, textiles, glass, others): Estimates were done as fraction of US imports in 2001. Imports (lumber) = 2.92E+07 MT/yr (UN Statistics Division; http://unstats.un.org) Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) State imports = 2.77E+05 MT/yr Imports (paper) = 1.57E+10 $/yr Price = 9.62E+02 $/MT Imports (paper) = 1.63E+07 MT/yr Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) State imports = 1.55E+05 MT/yr Transformity Lumber = 2.77E+05 MT/yr 8.80E+08 sej/g (Brown & Buranakam 2000) Paper = 1.55E+05 MT/yr 3.69E+09 sej/g (Luchi & Ulgiati 2000) Others = 0.0 MT/yr 5.85E+09 sej/g (Brown & Buranakam 2000) Imports = 4.32E+05 MT/yr 1.89E+09 sej/g Energy (J) = (__ MT/yr)(1E6g/MT) = 4.32E+11 g/yr Transformity (weighed) = 1.89E+09 sej/g 30 MACHINERY, TRANSPORTATION, EQUIPMENT: Estimates were done as fraction of US imports in 2001. Imports = 5.09E+11 $/yr (UN Statistics Division; http://unstats.un.org) Price = 3.00E+03 $/MT (Assumed) Imports = 1.70E+08 MT/yr Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) State Imports = 1.61E+06 MT/yr Mass (g) = (___E4 MT/yr)(1E6g/MT) = 1.61E+12 g/yr Transformity = 6.70E+09 sej/g (Brown & Bardi 2001) 31 IMPORTED SERVICES: Estimates were done as fraction of US imports in 2001. Dollar value (US ) = 1.18E+12 $/yr (UN Statistics Division; http://unstats.un.org) Fraction = 9.50E-03 (Based on Population: State/US; US Census Bureau; http://quickfacts.census.gov) Foreign state imports = 1.12E+10 $/yr Relative imports from other states = 1.12E+10 $/yr (Estimated based on a 2.51 times increase between 1992 and 2001. Data for 1992 from Odum et al (1998)) Federal spending received = 1.67E+ 10 $/yr (Tax Foundation 2004; http://www.taxfoundation.org/taxdata/) Total $ value of imports = 3.91E+10 $/yr World Emergy/$ ratio = 1.66E+12 sej/$ 32 TOURISM : Dollar Value = 3.81E+09 $US (ADPT; http://www.arkansas.com) World Emergy/$ ratio = 1.66E+12 sej/$

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A-23EXPORTS OF ENERGY, MATERIALS AND SERVICES 33 AGRICULTURAL PRODUCTS: Average price for US exports (2001) = 2.74E+02 $/MT (Estimated as raw cereals after UNSD; http://unstats.un.org) State exports = 9.17E+07 $/yr (ADED 2003) State exports = 3.35E+05 MT/yr Energy (J) = (__MT)(1E+06 g/MT)(80%)(3.5 Cal/g)(4186 J/Cal) = 3.92E+15 J/yr Transformity = 3.36E+05 sej/ J (Brown & McClanaham 1996) 34 MEAT: Average price for US exports (2001) = 2.08E+03 $/MT (Estimated after UN Statistics Division; http://unstats.un.org) State exports = 4.78E+08 $ (ADED 2003) State exports = 2.30E+05 MT/yr Energy (J) = (__MT)(1E+06 g/MT)(5 Cal/g)(4187 J/Cal)(0.22 protein) = 1.06E+15 J/yr Transformity = 3.36E+06 sej/ J (Brown & McClanaham 1996) 35 PAPER & PAPERBOARD: Average price for US exports (2001) = 9.62E+02 $/MT (UN Statistics Division; http://unstats.un.org) State exports = 2.08E+08 $ (ADED 2003) State exports = 2.16E+05 MT/yr Energy (J) = (__MT)(1.0E+06 g/MT) = 2.16E+11 g/yr Transformity = 3.69E+09 sej/g (Luchi & Ulgiati 2000) 36 FUELS: Natural gas = 0.00E+00 m3/yr Energy (J) = (__ m3/yr)(8966 kcal/m3)(4186 J/kcal) Oil derived fuels = 0.00E+00 L/yr Energy (J) = (__L/yr)(1.14E4kcal/L)(4186 J/kcal) Coal = 0.00E+00 MT/yr Energy (J) = (__MT/yr)(2.9E10 J/MT) Transformity Natural gas = 0.00E+00 J/yr 5.88E+04 sej/J (Romitelli 2000) Oil derived fuels = 0.00E+00 J/yr 1.11E+05 sej/J (Odum 1996) Coal = 0.00E+00 J/yr 6.69E+04 sej/J (Odum 1996) = 0.00E+00 J/yr Transformity = 0.00E+00 sej/J 37 METALS: Price US exports aluminum (2001) = 6.15E+02 $/MT (Aluminum hydroxide) (UN Statistics Division; http://unstats.un.org) State exports = 3.97E+07 $/yr (ADED 2003) State exports = 6.46E+04 MT/yr Price US exports Iron (2001) = 5.74E+02 $/MT (Primary form of iron) (UN Statistics Division; http://unstats.un.org) State exports = 3.54E+07 $/yr (Assumed 50% of State's exports; ADED 2003) State exports = 6.17E+04 MT/y r (Reported for iron and steel) Price US exports steel (2001) = 5.74E+02 $/MT (Primary form of steel) (UN Statistics Division; http://unstats.un.org) State exports = 3.54E+07 $/yr (Assumed 50% of State's exports; ADED 2003) State exports = 6.17E+04 MT/y r (Reported for iron and steel) Transformity Aluminum ore (Bauxite) = 0.00E+00 MT/yr 1.43E+09 sej/g (Odum 1996) Aluminum = 6.46E+04 MT/yr 1.25E+10 sej/g (Brown & Buranakam 2000) Iron = 6.17E+04 MT/yr 1.44E+09 sej/g (Odum 1996) Steel = 6.17E+04 MT/yr 4.13E+09 sej/g (Brown & Buranakam 2000) Copper wire = 0.00E+00 MT/yr 1.66E+11 sej/g (Odum 1996)

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A-24 Others = 0.00E+00 MT/yr 1.68E+09 sej/g (Odum 1996) Exports = 1.88E+05 MT/yr 6.13E+09 sej/g Mass (g) = (__MT)(1E6 g/MT) = 1.88E+11 g/yr Transformity (weighed) = 6.13E+09 sej/g 38 MINERALS (Bromine): Exports = 3.08E+04 MT/yr (15% of production) (AGC; www.state.ar.us/agc) Mass (g) = (__E5 MT)(1E6 g/MT) = 3.08E+10 g/yr Transformity = 2.20E+10 sej/g (Odum et al. 1998) 39 CHEMICALS (ORGANIC): Average price for US exports (2001) = 8.92E+02 $/MT (Estimated after UN Statistics Division; http://unstats.un.org) State exports = 1.79E+08 $/yr (ADED 2003) State exports = 2.00E+05 MT/yr Mass (g) = (__MT)(1E6 g/MT) = 2.00E+11 g/yr Transformity = 2.49E+10 sej/g (as pesticides) (Brown and Arding 1991, in Brandt-Williams 2001 ) 40 MACHINERY, TRANSPORTATION, EQUIPMENT: Average price = 3.00E+03 $/MT (Assumed) State exports = 8.72E+08 $/yr (Machinery, aircrafts, vehicles, 2001; ADED 2003) State exports = 2.91E+05 MT/yr Mass (g) = (__MT/yr)(1E6g/MT) = 2.91E+11 g/yr Transformity = 6.70E+09 sej/g (Doherty 1995 in Brown and Bardi 2001) 41 PLASTICS: Average price for US exports (2001) = 3.34E+03 $/MT (UN Statistics Division; http://unstats.un.org) State exports = 8.65E+07 $ (ADED 2003) State exports = 2.59E+04 MT/yr Energy (J) = (__MT/yr)(1000 Kg/MT)(30.0E6J/kg) = 7.76E+14 Transformity = 1.11E+05 sej/J (Odum 1996) 42 SERVICES IN EXPORTS: Foreign exports = 2.91E+09 $/yr (ADED 2003) Relative exports to other states = 3.60E+10 $/yr (Estimated based on a 2.21 times increase between 1992 and 2001. Data for 1992 from Odum et al [1998]) Federal tax paid = 1.24E+10 $/yr (Tax Foundation 2004; http://www.taxfoundation.org/taxdata/) Total $ value of exports = 3.89E+10 $/yr

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A-25 0 100 200 300 400 500 600 700Sunli g ht W i nd, k in et i c en er gy Ra i n, c he m i c al Rain, geopotenti a l Infl o w Ri ve r G eopotential Eart h Cycle Na tur al ga s Coa l Inflo w Rive r Ch e mi c a l Pot e nt i al Oil & Derivates G ro undw ate r E l ec t ri c it y Topsoil losses Che m i c al s (in c l. pe st ic i de s ) Fert i li z e rs Metal s Goods (i mpo rt ed) Servi c e i n i m port sEmergy/yr (E20 sej/yr)Figure A-6. Emergy signature of the environmen t and the economy of Arkansas in 2001. The same ratio for the U.S. for 2001 was estimated at about 1.00 E12 sej/$. Since the U.S. as a whole is more developed than the state of Arkansas alone the differences in values reflect this distinction. The emergy used from home sources index showed that Arkansas is only 40% sufficient depending mostly on imported emer gy (Table A-5).The emergy use per person is a measure of the standard of living in emergy terms. A person living in a rural environment may have a higher emergy use than a person living in a city. For Arkansas this ratio was 1.01 E17 sej/person, which is higher than for the average person for the entire U.S. in the year 20001. Again, since th e U.S. as a whole is more developed than the state of Arkansas alone, the different valu es reflect this difference. On a per area basis, the emergy use for th e state was 1.98 E16 sej/ha. 1 Unpublished data, H.T. Odum Center for Envi ronmental Policy, University of Florida.

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A-26 Table A-5. Summary of fl ows for Arkansas, 2001. Variable Item Solar Emergy (E20 sej/yr) Dollars R Renewable sources (rain, tide, earth cycle) 249.27 N Non-renewable resources from within State 264.50 N0 Dispersed Rural Source 436.79 N1 Concentrated Use 407.16 N2 Exported without Use 68.08 F Imported Fuels and Minerals 759.22 G Imported Goods 230.30 I Dollars Paid for Imports 3.91E+10 P2I Emergy of Services in Imported Goods & Fuels 648.90 E Dollars Received for Exports 3.89E+10 P1E Emergy Value of Goods and Service Exports 1247.36 X Gross State Product 9.65E+10 P2 World emergy/$ ratio, used in imports 1.66E+12 P1 State Emergy/$ ratio 2.83E+12 The emergy yield ratio (Y/F) was calculate d as 0.80 (see Figure A-4[b]), which indicates that Arkansas uses much more re sources from the economy than it contributes to it; Arkansas is a net importer of emer gy. The emergy investment ratio (F/I) was 1.50. This index measures the intensity of the economic development and the loading of the environment. The reference value usually used for comparison is the investment ratio for the U.S., which tends to be 7 or higher. Hi gh values suggest a more developed economy and a high level of environmental stress. A ccordingly, and since the loading ratio for Arkansas is relatively low, the free contribu tions from the environment to the state’s

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A-27 economy are relatively large. A more deve loped state like Flor ida has an emergy investment ratio of about 7. Table A-6. Emergy indices for Arkansas. Item Name of Index Expression Quantity 1 Renewable emergy flow R 2.49E+22 2 Flow from indigenous non-renewable reserves N 2.64E+22 3 Flow of imported emergy F+G+P2I 1.64E+23 4 Total emergy inflows R+N+F+G+P2I 2.15E+23 5 Total emergy used, U N0+N1+R+F+G+P2I 2.73E+23 6 Total exported emergy P1E 1.25E+23 7 Fraction emergy use derived from home sources (NO+N1+R)/U 0.40 8 Imports minus exports (F+G+P2I)-(N2+B+P1E) 3.23E+22 9 Export to Imports (N2+P1E)/(F+G+P2I) 0.80 10 Fraction used, locally renewable R/U 0.09 11 Fraction of use purchased (F+G+P2I)/U 0.60 12 Fraction imported service P2I/U 0.24 13 Fraction of use that is free (R+N0)/U 0.25 14 Ratio of concentrated to rural (F+G+P2I+N1)/(R+N0) 2.98 15 Use per unit area, Empower Density U/(area ha) 1.98E+16 16 Use per person U/population 1.01E+17 17 Renewable carrying capacity at present living standard STATE POPULATION = (R/U) (population) 2.70E+06 2.46E+05 18 Developed carrying capacity at same living standard 8(R/U)(population) 1.97E+06 19 Ratio of use to GSP, emergy/dollar ratio P1=U/GSP 2.83E+12 20 Ratio of electricity to use (el)/U 1% 21 Fuel use per person fuel/population 2.78E+16

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A-28 Emergy Evaluation of Resource Ba sis for the State of Arkansas With an annual rainfall of 1.21 meters in 2001, the rain-chemical potential energy was the highest source of natura l renewable energy in Arkansas. Odum et al. (1998) also pointed out the significance of this source of energy to the state’s economy and noted the high rates of evapotranspiration during the summer and early fall months due to the abundant rain usually present in the state. The relative richness in non-renewable re sources of Arkansas was also noted by Odum et al. (1998) and was confirmed by this study. The results showed that even though Arkansas has a significant amount of resource s, there were no marked changes in the quantities of indigenous renewable and non-rene wable resources used in the state over a period of 10 years. Both agri cultural and livestock products (including poultry) remained the most important components of the annua l indigenous renewable emergy flow in the state. Fossil fuels and electricity from with in the state had total annual emergy flows of 189.9 E20 sej and 232.68 E20 sej, respectively. Thes e values are similar to those reported by Odum et al. (1998). The agricultural cost in terms of so il erosion continued to be high. This study reported a total of 325.7 E20 sej in soil losses, wh ich is more than twice that reported in Odum et al. (1998). The difference might be the result of on increase in croplands between the two time periods. Overall, in 2001 soil losses represen ted 40% of all the non-renewable emergy used from within the stat e, suggesting that Arkansas agricultural production and its contribution to its economic growth comes at the expense of this important natural stock. The Arkansas gross state product increased from 39 billion dollars in 1990 to 96.5 billion dollars in 2001. Since th ere was little change to the resources basis of the

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A-29 Arkansas economy from within the state during these years, the growth of the state’s economy was possibly mostly due to an in crease in the imports of non-renewable resources, particularly of fossil fuels that accounted for 44% of all the emergy brought in to the system in 2001. The ratio of exports to imports for 2001 was 0.80. The emergy used from state sources was 40% of the to tal emergy used and the emergy used from home sources index showed that Arkansas was only 39% sufficient in 2001, depending mostly on imported emergy. Together these figu res show that Arkansas is a net emergy importer state. This is a significant change from that reported by Odum et al. (1998). Using 1990 data, Odum et al.’s study showed that Arkansas was a net emergy exporter state. The results for exported emergy that were reported by Odum et al. (1998) and the results of this study show some difference in the number of items included in the analysis and in the way total energy values were calc ulated. This study included more items. We used the exports dollar value of each product fr om state-level data and the average price for U.S. exports for each item in 2001 to obtain data on quantities exported. As such, emergy exports accounted only for the emer gy in the internati onal trade, excluding exports to other states. However, when calcula ting the emergy of the services in exports, a relative dollar value of the exports to other states was considered. The total emergy reported as exports in the Odum et al. ( 1998) study was 1231 E20 sej, while the total emergy exported according to this study wa s 1247.18 E20 sej. The services in exports accounted for 77% and 88% of total exports, respectively. The emergy investment ratio for 1990 was 0.73. In 2001 this ratio was 1.50. The ratio value for the state is still lower th an that for the U.S., which has an emergy

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A-30 investment ratio of around 7.0 and the state may still be considered a mostly rural or less developed state. However, the difference in the ratio value between the two time periods suggest that Arkansas is rece iving less of their emergy as free contributions from the environment and that the state is slowly moving towards a more developed economy. In 2001 the economic system invested more emer gy from sources outside the state. The changes in the fraction of emergy used wh ich is locally renewable was 0.15 in 1990 and 0.09 in 2001, also seem to support this trend. The solar emergy-to-money ratio for Ar kansas in 1990 was 3.45 E12 sej/$ and 2.83 E12 sej/$ in 2001. Despite the nor mal decrease in its value2, the emergy-to-money ratio of Arkansas was still higher than the rati o for the U.S. in 2001, which was estimated as about 1.00 E12 sej/$. Once again this value confirms the rather ru ral nature of the state of Arkansas. This ratio is an indication of the r eal wealth (in emergy terms) that a dollar can buy. In summary, Arkansas has a diversif ied economy and is in creasingly becoming more dependent on imported emergy. The emergy evaluation for Arkansas suggests that the state is slowly moving to wards a more developed economy. Emergy Evaluation of Land Uses of the Bayou Meto Watershed In the following pages systems diagrams, a nd emergy evaluation tables of land uses and land cover systems of the Bayou Meto Watershed are presented. 2 Generally, emergy-to-money ratios decrease over time due to inflation, the increase in money circulation year to year, and to the increasing efficiency in resource use (Odum 1996).

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A-31 Mixed hardwood forest Figure A-7. Energy systems diagram of a mixed hardwood forest.

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A-32 Table A-7. Emergy evaluation table of a mi xed hardwood forest, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 4.72E+13 J 1.00E+00 5 2 Wind 5.02E+10 J 2.45E+03 12 3 Rain chemical potential 5.98E+10 J 3.05E+04 182 4 Run-in chemical potential 0.00E+00 J 8.24E+04 0 5 Water use (Transpiration) 2.62E+10 J 4.38E+04 115 Flows 6 Gross primary production 7.80E+11 J 1.47E+03 115 7 Total EMERGY 182 Calculated ratios 8 Empower Density 1.82E+15 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (____m2)*(____Cal/cm2/y)*(E+04cm2/m2)* (1-albedo)*(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 0.2 (After www.nasa.gov) Annual energy = 4.72E+13 J Emergy per unit input = 1 sej/J (Odum 1996) 2 Wind, J Annual energy = (area)(air dens ity)(drag coefficient)(velocity3) = (_____m2)(1.3 kg/m3)(1.00 E-3)(______mps)(3.14 E7 s/yr) Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (observed winds are about 0.6 of geostrophic wind) Drag coeff. = 1.00E-03 (Garrat 1977) Annual energy = 5.02E+10 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 3 Rain chemical potential, J Annual energy = (Avg. precip.)*(Area)*(1 E6 g/m2)*(4.94J/g) Avg. precipitation = 1.21 m Area = 1.00E+04 m2 Annual energy = 5.98E+10 Emergy per unit input = 3.05E+04 sej/J (Odum 2000) 4 Run-in chemical potential, J Annual energy = 0 (Southern mixed hardwood forest complex is not net sink for run-in; Orrell 1998) Emergy per unit input = 8.24E+ 04 sej/J (Bardi and Brown 2001) 5 Water use (Transpiration), J Annual energy = (Transpiration)*(area)*(1E6 g/m3)*(4.94 J/g)) Transpiration = 5.30E-01 m/yr (Orrell 1998) Annual energy = 2.62E+10 J/yr

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A-33 Emergy per unit input = 4.38E+ 04 sej/J (Bardi and Brown 2001) 6 Gross primary production, J Annual energy = (GPP)*(1E6 g/ton)*(8 kcal/g)*(4186 J/kcal) Gross primary production = 2.33E+01 ton C/ha-yr (Orrell 1998) Annual energy = 7.80E+11 J/yr Emergy per unit input = 1.47E+03 sej/J (S olar emergy of item # 6/Annual energy) 7 Total Emergy Highest renewable input 8 Empower Density emergy per hectare per year

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A-34 Bottomland hardwood forest Figure A-8. Energy systems diagram of a bottomland hardwood forest.

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A-35 Table A-8. Emergy evaluation table of a bottomla nd hardwood forest, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 4.72E+13 J 1.00E+00 5 2 Wind 5.02E+10 J 2.45E+03 12 3 Rain chemical potential 5.98E+10 J 3.05E+04 182 4 River geopotential 5.95E+08 J 4.70E+04 3 5 River chemical potential 1.51E+10 J 8.14E+04 123 6 Water use (Transpiration) 5.88E+10 J 4.38E+04 258 Flows 7 Gross primary production 6.28E+10 J 4.15E+04 261 8 Total EMERGY 258 Calculated ratios 9 Empower Density 2.58E+15 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total Annua l Insolation J/yr)(Area)(1-albedo) = (____m2)*(____Cal/cm2/y)*(E+04cm2/m2)* (1-albedo)*(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 0.2 (After www.nasa.gov) Annual energy = 4.72E+13 J Emergy per unit input = 1 sej/J (Odum 1996) 2 Wind, J Annual energy = (area)(air dens ity)(drag coefficient)(velocity3) = (_____m2)(1.3 kg/m3)(1.00 E-3)(______mps)(3.14 E7 s/yr) Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mp s (data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (observed winds are about 0.6 of geostrophic wind) Drag coeff. = 1.00E-03 (Garrat 1977) Annual energy = 5.02E+10 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 3 Rain chemical potential, J Annual energy = (Avg. precip.)*(Area)*(1 E6 g/m2)*(4.94J/g) Avg. precipitation = 1.21 m Area = 1.00E+04 m2 Annual energy = 5.98E+10 Emergy per unit input = 3.05E+04 sej/J (Odum 2000) 4 River geopotential, J Annual energy = (volume)*(1.0E3 kg/m3)*(height in-height out)*(gravity) Mean annual river flow = 6.99E+00 m3/sec (Estimated from daily data for 2000-2001 from USGS; available at http://nwis.waterdata.usgs.gov) Mean annual river flow = 2.20E+08 m3/yr Average elevation change = 1.07E+02 m (www.mawpt.org; Bayo u Meto WPA Report) Area Bayou Meto Watershed = 3.88E+05 ha (www.mawpt.org; Bayou Meto WPA Report)

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A-36 Annual energy = 5.95E+08 J/yr Emergy per unit input = 4.70E+ 04 sej/J (Odum et al. 2000) 5 River chemical potential, J Gibbs free energy = [(8.3143 J/mol/deg)(288 K)/(18 g/mol)]*ln[(1e6 Solutes)ppm)/965000] (Campbell et al. 2005) Dissolved Solids in = 2.00E+02 ppm (Odum et al. 1998) Dissolved Solids out = 4.00E+02 ppm (Odum et al. 1998) Gibbs Free Energy in = 4.71E+00 J/g Gibbs Free Energy out = 4.69E+00 J/g Mean annual river flow = 2.20E+08 m3/yr Energy(J) = (volume)(density)(Gibbs free energy) = (____m3/s)*(1.0E3 kg/m3)(__J/g) Energy in = 1.04E+18 J/yr Energy out = 1.03E+18 J/yr Annual energy (InOut) = 1.51E+10 J/yr Emergy per unit input = 8.14E+04 sej/J (Odum, 1996) 6 Water use (Transpiration), J Annual energy = (Transpiration)*(area)*(1E6 g/m3)*(4.94 J/g) Transpiration = 1.19E+00 m/yr (Odum et al. 1998) Annual energy = 5.88E+10 J/yr Emergy per unit input = 4.38E+ 04 sej/J (Bardi and Brown 2001) 7 Gross primary production, J Annual energy = (GPP)*(1E6 g/ton)*(4 kcal/g)*(4186 J/kcal) Gross primary production = 3.75E+00 ton/yr (Dat a for the Black Swamp, AR; Odum et al. 1998) Annual energy = 6.28E+10 J/yr Emergy per unit input = 4.15E+04 sej/J (Sum of solar emergy for item #4 and #6/Annual energy) 8 Total Emergy Highest renewable input 9 Empower Density emergy per hectare per year

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A-37 Agricultural land uses Figure A-9. Energy systems diagram of ag riculture in the Bayou Meto Watershed.

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A-38 Table A-9. Emergy evaluation table of sorghum, per ha per year Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 1.56E+13 J 1 2 2 Rain transpired 1.98E+10 J 2.59E+04 51 3 Wind 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 9.04E+09 J 1.24E+05 112 5 Groundwater 3.55E+09 2.69E+05 96 Purchased Inputs 6 Fuel 4.92E+09 J 1.11E+05 55 7 Phosphorus 7.74E+04 g 1.45E+10 112 8 Nitrogen 1.29E+05 g 1.59E+10 205 9 Potassium 1.01E+05 g 1.85E+09 19 10 Pesticides 6.44E+03 g 2.52E+10 16 11 Labor 4.21E+06 J 4.45E+06 2 12 Services 4.23E+02 $ 2.83E+12 120 13 Total EMERGY 2.8E+12 787 Yields 14 Total Yield, dry weight 5.40E+06 g 15 Total Yield, energy 7.91E+10 J Calculated ratios 16 Emergy per mass 1.46E+09 sej/g 17 Transformity w/services 9.95E+04 sej/J 18 Transformity wo/services 8.43E+04 sej/J 19 Empower Density 7.87E+15 sej/ha/yr 20 NR + PI Empower Density w/services 7.36E+15 sej/ha/yr 21 NR + PI Empower Density wo/services 6.16E+15 sej/ha/yr Notes: Grain Sorghum, Flood Irrigated, Loamy Soils References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Growing season = 3.30E-01 yr (www.uaex.edu) Area = 1.00E+04 m2 Albedo = 2.00E-01 (After www.nasa.gov) Annual energy = 1.56E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Evapotranspiration, J Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Evapotranspiration = 1.20E+00 m3/m2/yr (Odum et al. 1998) Volume/year = 1.20E+04 m3/yr Volume (4 months) = 4.00E+03 m3/yr Annual energy = 1.98E+10 J Emergy per unit input = 1.54E+04 sej/J (Odum 1996)

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A-393 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (__m2)(1.3 kg/m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Annual energy = 1.00E+11 J Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.00E+03 g/m2/yr (After Odum et al. 1998) Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) OM in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 9.04E+09 J Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Ground water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater irrigation = 7.00E+00 acre inch/yr (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Groundwater irrigation = 7.20E+02 m3/yr Annual energy = 3.55E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al 1998) 6 Fuel, J Annual energy = (Gallons fuel)(1.32E8 J/gal) Gallons/acre = 1.51E+01 (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Gallons/ha = 3.73E+01 Annual energy = 4.92E+09 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Phosphorus, g Annual consumption = 6.90E+01 lb /acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption = 7.74E+04 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 8 Nitrogen, g Annual consumption (as Urea 46%) = 1.15E+02 lb/acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption (as Urea) = 1.29E+05 g/ha Emergy per unit input = 1.59E+10 sej/g (Brandt-Williams 2001) 9 Potassium, g Annual consumption = 9.00E+01 lb /acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption = 1.01E+05 g/ha Emergy per unit input = 1.10E+09 sej/g (Odum 1996) 10 Pesticides, g (fungicides and herbicides) Annual consumption = 5.74E+00 lb/acre (Assu med one pint of pesticide = 1.0375 lbs) Annual consumption = 6.44E+03 g/ ha (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets)

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A-40 Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001) 11 Labor, J (operation and irrigation) Annual energy = (pers-hours/ha/yr)(2500 kcal/day)(4186J/Cal) / (8 pershrs/day) Labor = 1.30E+00 hr/acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Labor = 3.21E+00 hr/ha Annual energy = 4.21E+06 J Emergy per unit input = 4.45E+06 sej/J (Migrant labor, Brandt-Williams 2001) 12 Services, $ Value = 3.56E+00 $/CWT (www.nass.usda.gov/ar/) Value = 3.56E-02 $/lb Value = 4.23E+02 $/ha Annual emergy = ($ /yr)(sej/$) Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 13 Total Emergy Sum of inputs 2 through 12 14 Yield, g Yield = 8.60E+01 Bushel/acre (www.auex.edu) 5.60E+01 lb/bushel (www.muextension.missouri.edu) Yield = 5.40E+06 g/ha 15 Product in Joules Energy = (__g)(3.5 kcal/g)( 4186J/kcal) (Odum et al.1998) Energy content = 7.91E+10 J 16 Emergy per mass Total emergy divided by yield in grams 17 Transformity w/services Total emergy yield divided by yield in joules 18 Transformity wo/services Total emergy yield minus servic es divided by yield in joules 19 Empower Density sum of emergy per hectare per year 20 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 21 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-41 Table A-10. Emergy evaluation table of ha y (Bermuda grass), per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 1.56E+13 J 1 2 2 Rain transpired 1.98E+10 J 2.59E+04 51 3 Wind 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 6.33E+07 J 1.24E+05 1 5 Groundwater 6.12E+09 J 2.69E+05 164 Purchased Inputs 6 Fuel 8.81E+09 J 1.11E+05 98 7 Phosphorus 6.73E+04 g 5.67E+09 38 8 Nitrogen 2.35E+05 g 1.59E+10 374 9 Potassium 6.73E+04 g 1.85E+09 12 10 Labor 1.49E+07 J 4.45E+06 7 11 Services 1.06E+03 $ 2.83E+12 301 12 Total EMERGY 1046 Yields 13 Total Yield, dry weight 1.70E+07 g 14 Total Yield, energy 1.85E+11 J Calculated ratios 15 Emergy per mass 6.16E+08 sej/g 16 Transformity w/services 5.66E+04 sej/J 17 Transformity wo/services 4.03E+04 sej/J 18 Empower Density 1.05E+16 sej/ha/yr 19 NR + PI Empower Density w/services 9.95E+15 sej/ha/yr 20 NR + PI Empower Density wo/services 6.95E+15 sej/ha/yr Notes: Northwest Arkansas Bermuda Round Bales References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Growing season = 3.30E-01 yr (www.uaex.edu) Area = 1.00E+04 m2 Albedo = 2.00E-01 (After www.nasa.gov) Annual energy = 1.56E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Evapotranspiration, J Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Evapotranspiration = 1.20E+00 m3/m2/yr (Odum et al. 1998) Volume/year = 1.20E+04 m3/yr Volume (4 months) = 4.00E+03 m3/yr Annual energy = 1.98E+10 J Emergy per unit input = 1.54E+04 sej/J (Odum 1996)

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A-42 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mp s (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (__m2)(1.3 kg/m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Annual energy = 1.00E+11 J Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 7.00E+00 g/m2/yr (After Pimentel et al. 1995) Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) OM in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 6.33E+07 J Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Ground water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater irrigation = 1.20E+01 acre inch /yr (After Duble, R.L.; http://aggiehorticulture.tamu.edu/) Groundwater irrigation = 1.24E+03 m3/yr Annual energy = 6.12E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al 1998) 6 Fuel, J Annual energy = (Gallons fuel)(1.32E8 J/gal) Gallons/acre = 2.70E+01 (Rainey et al. 2005; www.aragriculture.org/famplanning/budgets) Gallons/ha = 6.68E+01 Annual energy = 8.81E+09 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Phosphorus, g (P2O5) Annual consumption = 6.00E+01 lb/acre (Sa ndage & Chapman 1999; http://www.uaex.edu) Annual consumption = 6.73E+04 g/ha Emergy per unit input = 5.67E+09 sej/g (Brandt-Williams 2001) 8 Nitrogen, g Annual consumption = 2.10E+02 lb/acre (Sa ndage & Chapman 1999; http://www.uaex.edu) Annual consumption = 2.35E+05 g/ha Emergy per unit input = 1.59E+10 sej/g (Brandt-Williams 2001) Annual consumption = 6.00E+01 lb/acre (Sa ndage & Chapman 1999; http://www.uaex.edu) Annual consumption = 6.73E+04 g/ha Emergy per unit input = 1.10E+09 sej/g (Odum 1996) 10 Labor, J (operation and irrigation) Annual energy = (pers-hours/ha/yr)(2500 kcal/day)(4186J/Cal) / (8 pershrs/day) Labor = 4.60E+00 hr/acre (Rainey et al. 2004; www.aragriculture.org/famplanning/budgets) Labor = 1.14E+01 hr/ha Annual energy = 1.49E+07 J Emergy per unit input = 4.45E+06 sej/J (Migrant labor, Brandt-Williams 2001)

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A-43 11 Services, $ Value = 6.25E+01 $/ton (www.nass.usda.gov/ar/) Value = 1.06E+03 $/ha Annual emergy = ($ /yr)(sej/$) Emergy per unit input = 2.83E+12 se j/$, 2001 (This study, see Table A-5) 12 Total Emergy Sum of inputs 2 through 11 13 Yield, g (Midland 99, Tifton 44, Midland, Greenfield) Average Yield = 6.88E+00 ton/ acre (Sandage & Cassida 2001; http://www.uaex.edu) Yield = 1.70E+07 g/ha 14 Product in Joules Energy = (__g)(2.6 kcal /g)(4186J/kcal) (Pimentel 1980) Energy content = 1.85E+11 J 15 Emergy per mass Total emergy divided by yield in grams 16 Transformity w/services Total emergy yield divided by yield in joules 17 Transformity wo/services Total emergy yield minus servic es divided by yield in joules 18 Empower Density sum of emergy per hectare per year 19 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 20 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-44 Table A-11. Emergy evaluation table of soybeans, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 1.56E+13 J 1 2 2 Rain transpired 1.98E+10 J 2.59E+04 51 3 Wind 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.26E+10 J 1.24E+05 404 5 Groundwater 6.60E+09 J 2.69E+05 177 Purchased Inputs 6 Fuel 8.67E+09 J 1.11E+05 96 7 Phosphorus 4.04E+04 g 1.45E+10 59 8 Potassium 8.07E+04 g 1.85E+09 15 9 Pesticides 7.48E+03 g 2.52E+10 19 10 Labor 6.88E+06 J 4.45E+06 3 11 Services 4.86E+02 $ 2.83E+12 137 12 Total EMERGY 961 Yields 13 Total Yield, dry weight 3.03E+06 g 14 Total Yield, energy 5.11E+10 J Calculated ratios 15 Emergy per mass 3.17E+09 sej/g 16 Transformity w/services 1.88E+05 sej/J 17 Transformity wo/services 1.61E+05 sej/J 18 Empower Density 9.61E+15 sej/ha/yr 19 NR + PI Empower Density w/services 9.10E+15 sej/ha/yr 20 NR + PI Empower Density wo/services 7.73E+15 sej/ha/yr Notes: Soybeans, Flood Irrigated Following Rice, Loamy Soils References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Growing season = 3.30E-01 yr (www.uaex.edu) Area = 1.00E+04 m2 Albedo = 2.00E-01 (After www.nasa.gov) Annual energy = 1.56E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Evapotranspiration, J Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Evapotranspiration = 1.20E+00 m3/m2/yr (Odum et al. 1998) Volume/year = 1.20E+04 m3/yr Volume (4 months) = 4.00E+03 m3/yr Annual energy = 1.98E+10 J Emergy per unit input = 1.54E+04 sej/J (Odum 1996)

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A-45 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (__m2)(1.3 kg/m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Annual energy = 1.00E+11 J Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 3.60E+03 g/m2/yr (After Pimentel et al. 1995) Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) OM in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.26E+10 J Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Ground water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater irrigation = 1.30E+01 acre inch/yr (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Groundwater irrigation = 1.34E+03 m3/yr Annual energy = 6.60E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al 1998) 6 Fuel, J Annual energy = (Gallons fuel)(1.32E8 J/gal) Gallons/acre = 2.66E+01 (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Gallons/ha = 6.57E+01 Annual energy = 8.67E+09 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Phosphorus, g Annual consumption = 3.60E+01 lb /acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption = 4.04E+04 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 8 Potassium, g Annual consumption = 7.20E+01 lb /acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption = 8.07E+04 g/ha Emergy per unit input = 1.10E+09 sej/g (Odum 1996) 9 Pesticides, g (herbicides) Annual consumption = 6.67E+00 lb/acre (A ssumed one pint of pesticide = 1.0375 lbs) Annual consumption = 7.48E+03 g/ ha (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001 )

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A-46 10 Labor, J (operation and irrigation) Annual energy = (pers-hours/ha/yr)(2500 kcal/day)(4186J/Cal) / (8 pershrs/day) Labor = 2.13E+00 hr/acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Labor = 5.26E+00 hr/ha Annual energy = 6.88E+06 J Emergy per unit input = 4.45E+06 sej/J (Migrant labor, Brandt-Williams 2001) 11 Services, $ Value = 4.37E+00 $/bushel (www.nass.usda.gov/ar/) Value = 4.86E+02 $/ha Annual emergy = ($ /yr)(sej/$) Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 12 Total Emergy Sum of inputs 2 through 11 13 Yield, g Yield = 4.50E+01 Bushel/acre (www.auex.edu) 6.00E+01 lb/bushel (www.muextension.missouri.edu) Yield = 3.03E+06 g/ha 14 Product in Joules Energy = (__g)(4.03 kcal/g)(4186 J/kcal) (Odum et al.1998) Energy content = 5.11E+10 J 15 Emergy per mass Total emergy divided by yield in grams 16 Transformity w/services Total emergy yield divided by yield in joules 17 Transformity wo/services Total emergy yield minus servic es divided by yield in joules 18 Empower Density sum of emergy per hectare per year 19 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 20 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-47 Table A-12. Emergy evaluation tabl e of corn, per ha per year Data Emergy/unit Solar EMERGY Notes Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 1.56E+13 J 1 2 2 Rain transpired 1.98E+10 J 2.59E+04 51 3 Wind 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 1.81E+10 J 1.24E+05 224 5 Groundwater 5.08E+09 J 2.69E+05 137 Purchased Inputs 6 Fuel 6.95E+09 J 1.11E+05 77 7 Phosphorus 9.03E+04 g 1.45E+10 131 8 Nitrogen 1.97E+05 g 1.59E+10 314 9 Potassium 1.18E+05 g 1.85E+09 22 10 Pesticides 1.10E+04 g 2.52E+10 28 11 Labor 4.88E+06 J 4.45E+06 2 12 Services 8.73E+02 $ 2.83E+12 247 13 Total EMERGY 1233 Yields 14 Total Yield, dry weight 9.11E+06 g 15 Total Yield, energy 1.33E+11 J Calculated ratios 16 Emergy per mass 1.35E+09 sej/g 17 Transformity w/services 9.24E+04 sej/J 18 Transformity wo/services 7.39E+04 sej/J 19 Empower Density 1.23E+16 sej/ha/yr 20 NR + PI Empower Density w/services 1.18E+16 sej/ha/yr 21 NR + PI Empower Density wo/services 9.34E+15 sej/ha/yr Notes: Corn, Flood Irrigated, Loamy Soils References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Growing season = 3.30E-01 yr (www.uaex.edu) Area = 1.00E+04 m2 Albedo = 2.00E-01 (After www.nasa.gov) Annual energy = 1.56E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Evapotranspiration, J Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Evapotranspiration = 1.20E+00 m3/m2/yr (Odum et al. 1998) Volume/year = 1.20E+04 m3/yr Volume (4 months) = 4.00E+03 m3/yr Annual energy = 1.98E+10 J Emergy per unit input = 1.54E+04 sej/J (Odum 1996)

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A-48 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (__m2)(1.3 kg/m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Annual energy = 1.00E+11 J Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 2.00E+03 g/m2/yr (Pimentel et al. 1995) Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) OM in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 1.81E+10 J Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Ground water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater irrigation = 1.00E+01 acre inch/yr (Windham & Marshall 2005; www.aragriculture.org/famplanning/budgets) Groundwater irrigation = 1.03E+03 m3/yr Annual energy = 5.08E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al 1998) 6 Fuel, J Annual energy = (Gallons fuel)(1.32E8 J/gal) Gallons/acre = 2.13E+01 (Windha m & Marshall 2004; www.aragri culture.org/famplanning/budgets) Gallons/ha = 5.27E+01 Annual energy = 6.95E+09 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Phosphorus, g Annual consumption = 8.05E+01 lb /acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption = 9.03E+04 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 8 Nitrogen, g Annual consumption (Liquid 32%) = 1.76E+02 lb/acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption (Liquid 32%) = 1.97E+05 g/ha Emergy per unit input = 1.59E+10 sej/g (Brandt-Williams 2001) 9 Potassium, g Annual consumption = 1.05E+02 lb /acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption = 1.18E+05 g/ha Emergy per unit input = 1.10E+09 sej/g (Odum 1996) 10 Pesticides, g (insecticides and herbicides) Annual consumption = 9.85E+00 lb/acre (Assu med one pint of pesticide = 1.0375 lbs) Annual consumption = 1.10E+04 g/ ha (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001 )

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A-49 11 Labor, J (operation and irrigation) Annual energy = (pers-hours/ha/yr)(2500 kcal/day)(4186J/Cal) / (8 pershrs/day) Labor = 1.51E+00 hr/acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Labor = 3.73E+00 hr/ha Annual energy = 4.88E+06 J Emergy per unit input = 4.45E+06 sej/J (Migrant labor, Brandt-Williams 2001) 12 Services, $ Value = 2.02E+00 $/bushel (www.nass.usda.gov/ar/) Value = 8.73E+02 $/ha Annual emergy = ($ /yr)(sej/$) Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 13 Total Emergy Sum of inputs 2 through 12 14 Yield Yield = 1.45E+02 Bu/acre (www.auex.edu) 5.60E+01 lb/bu (www.muextension.missouri.edu) Yield = 9.11E+06 g/ha 15 Product in Joules Energy = (__g)(3.5 kcal/g)( 4186J/kcal) (Odum et al.1998) Energy content = 1.33E+11 J 16 Emergy per mass Total emergy divided by yield in grams 17 Transformity w/services Total emergy yield divided by yield in joules 18 Transformity wo/services Total emergy yield minus servic es divided by yield in joules 19 Empower Density sum of emergy per hectare per year 20 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 21 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-50 Table A-13. Emergy evaluation tabl e for rice, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 1.56E+13 J 1 2 2 Rain transpired 1.98E+10 J 2.59E+04 51 3 Wind 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 9.04E+09 J 1.24E+05 112 5 Groundwater 1.22E+10 J 2.69E+05 328 Purchased Inputs 6 Fuel 1.19E+10 J 1.11E+05 132 7 Phosphorus 4.04E+04 g 1.45E+10 59 8 Nitrogen 1.70E+05 g 1.59E+10 271 9 Potassium 8.07E+04 g 1.85E+09 15 10 Pesticides 8.63E+03 g 2.52E+10 22 11 Labor 6.33E+06 J 4.45E+06 3 12 Services 6.16E+02 $ 2.83E+12 174 13 Total EMERGY 1166 Yields 14 Total Yield 7.12E+06 g 15 Total Yield, energy 1.04E+11 J Calculated ratios 16 Emergy per mass 1.64E+09 sej/g 17 Transformity w/services 1.12E+05 sej/J 18 Transformity wo/services 9.50E+04 sej/J 19 Empower Density 1.17E+16 sej/ha/yr 20 NR + PI Empower Density w/services 1.11E+16 sej/ha/yr 21 NR + PI Empower Density wo/services 9.40E+15 sej/ha/yr Notes: Rice, Silt Loam Soils, Eastern Arkansas References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Growing season = 3.30E-01 yr (www.uaex.edu) Area = 1.00E+04 m2 Albedo = 2.00E-01 (After www.nasa.gov) Annual energy = 1.56E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Evapotranspiration, J Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Evapotranspiration = 1.20E+00 m3/m2/yr (Odum et al. 1998) Volume/year = 1.20E+04 m3/yr Volume (4 months) = 4.00E+03 m3/yr Annual energy = 1.98E+10 J Emergy per unit input = 1.54E+04 sej/J (Odum 1996)

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A-51 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (__m2)(1.3 kg/m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Annual energy = 1.00E+11 J Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.00E+03 g/m2/yr (Odum et al. 1998) Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) OM in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 9.04E+09 J Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Groundwater, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater irrigation = 2.40E+01 acre inch/yr (Windham & Marshall 2005; www.aragriculture.org/famplanning/budgets) Groundwater irrigation = 2.47E+03 m3/yr Annual energy = 1.22E+10 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al 1998) 6 Fuel, J Annual energy = (Gallons fuel)(1.32E8 J/gal) Gallons/acre = 3.65E+01 (W indham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Gallons/ha = 9.02E+01 Annual energy = 1.19E+10 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Phosphorus, g Annual consumption = 3.60E+01 lb /acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption = 4.04E+04 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 8 Nitrogen, g Consumption (as Urea 46%) = 1.52E+02 lb/acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Consumption (as Urea) = 1.70E+05 g/ha Emergy per unit input = 1.59E+10 sej/g (Brandt-Williams 2001) 9 Potassium, g Annual consumption = 7.20E+01 lb /acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Annual consumption = 8.07E+04 g/ha Emergy per unit input = 1.10E+09 sej/g (Odum 1996) 10 Pesticides, g (includes fungicides and herbicides) Annual consumption = 7.70E+00 lb/acre (Assu med one pint of pesticide = 1.0375 lbs)

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A-52 Annual consumption = 8.63E+03 g/ ha (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Emergy per unit input = 1.50E+10 sej/g (Brown and Arding 1991) 11 Labor, J (operation and irrigation) Annual energy = (pers-hours/ha/yr)(2500 kcal/day)(4186J/Cal) / (8 pershrs/day) Labor = 1.96E+00 hr/acre (Windham & Marshall 2004; www.aragriculture.org/famplanning/budgets) Labor = 4.84E+00 hr/ha Annual energy = 6.33E+06 J Emergy per unit input = 4.45E+06 sej/J (Migrant labor, Brandt-Williams 2001) 12 Services, $ Value = 3.93E+00 $/CWT (www.nass.usda.gov/ar/) Value = 6.16E+02 $/ha Annual emergy = ($ /yr)(sej/$) Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 13 Total Emergy Sum of inputs 2 through 12 14 Yield, g Yield = 6.35E+03 lb/acre (www.nass.usda.gov/ar/) Yield = 7.12E+06 g/ha 15 Product in Joules Energy = (__g)(3.5 kcal/g)(4186 J/kcal) (Odum et al.1998) Energy content = 1.04E+11 J 16 Emergy per mass Total emergy divided by yield in grams 17 Transformity w/services Total emergy yield divided by yield in joules 18 Transformity wo/services Total emergy yield minus servic es divided by yield in joules 19 Empower Density sum of emergy per hectare per year 20 NR + PI Empower Density w/services s um of non renewable and purchased in puts emergy per hectare per year 21 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-53 Table A-14. Emergy Evaluation of cotton, per ha per year Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 1.56E+13 J 1 2 2 Rain transpired 1.98E+10 J 2.59E+04 51 3 Wind 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 8.23E+10 J 1.24E+05 1020 5 Groundwater 6.09E+09 J 2.69E+05 164 Purchased Inputs 6 Fuel 8.86E+09 J 1.11E+05 98 7 Phosphorus 3.36E+04 g 1.45E+10 49 8 Nitrogen 1.12E+05 g 1.59E+10 178 9 Potassium 1.01E+05 g 1.85E+09 19 10 Pesticides 2.13E+04 g 2.52E+10 54 11 Labor 6.79E+06 J 4.45E+06 3 12 Services 1.12E+03 $ 2.83E+12 316 13 Total EMERGY 1952 Yields 14 Total Yield 1.81E+06 g 15 Total Yield, energy 3.03E+10 J Calculated ratios 16 Emergy per mass 1.08E+10 sej/g 17 Transformity w/services 6.44E+05 sej/J 18 Transformity wo/services 5.39E+05 sej/J 19 Empower Density 1.95E+16 sej/ha/yr 20 NR + PI Empower Density w/services 1.90E+16 sej/ha/yr 21 NR + PI Empower Density wo/services 1.58E+16 sej/ha/yr Notes: Cotton, Conventional till, furrow irrigation, 8 row equipment References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Growing season = 3.30E-01 yr (www.uaex.edu) Area = 1.00E+04 m2 Albedo = 2.00E-01 (After www.nasa.gov) Annual energy = 1.56E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Evapotranspiration, J Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Evapotranspiration = 1.20E+00 m3/m2/yr (Odum et al. 1998) Volume/year = 1.20E+04 m3/yr Volume (4 months) = 4.00E+03 m3/yr Annual energy = 1.98E+10 J Emergy per unit input = 1.54E+04 sej/J (Odum 1996)

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A-54 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (__m2)(1.3 kg/m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Annual energy = 1.00E+11 J Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 9.10E+03 g/m2/yr (After Pimentel et al. 1995) Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) OM in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 8.23E+10 J Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Ground water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) (Hogan et al. 2005); www.aragriculture.org/famplanning/budgets Groundwater irrigation = 1.20E+01 acre inch/yr Groundwater irrigation = 1.23E+03 m3/yr Annual energy = 6.09E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al 1998) 6 Fuel, J Annual energy = (Gallons fuel)(1.32E8 J/gal) Gallons/acre = 2.72E+01 (Hogan et al. 2005) ; www.aragriculture.org/famplanning/budgets Gallons/ha = 6.71E+01 Annual energy = 8.86E+09 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Phosphorus, g Annual consumption = 3.00E+01 lb/acr e (Bourland et al. 2003; data for the Southeast Branch Experime nt Station at Rohwer) Annual consumption = 3.36E+04 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 8 Nitrogen, g Annual consumption (Liquid 32%) = 9.98E+01 lb/acre (Hogan et al. 2005; www.aragriculture.org/famplanning/budgets) Annual consumption = 1.12E+05 g/ha Emergy per unit input = 1.59E+ 10 sej/g (Brandt-Williams, 2001) 9 Potassium, g Annual consumption = 9.00E+01 lb/acr e (Bourland et al. 2003; data for the Southeast Branch Experime nt Station at Rohwer) Annual consumption = 1.01E+05 g/ha Emergy per unit input = 1.10E+09 sej/g (Odum 1996) 10 Pesticides, g (fungicides, insecticides and herbicides) Annual consumption = 1.90E+01 lb/acre (Assu med one pint of pesticide = 1.0375 lbs) Annual consumption = 2.13E+04 g/ ha (Hogan et al. 2005); www.aragriculture.org/famplanning/budgets Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001 )

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A-55 11 Labor, J (operation, irrigation, and hand labor) Annual energy = (pers-hours/ha/yr)(2500 kcal/day)(4186J/Cal) / (8 pershrs/day) Labor = 2.10E+00 hr/acre (Hogan et al. 2005; www.aragriculture.org/famplanning/budgets) Labor = 5.19E+00 hr/ha Annual energy = 6.79E+06 J Emergy per unit input = 4.45E+06 sej/J (Migrant labor, Brandt-Williams 2001) 12 Services, $ Value = 2.80E-01 $/lb (www.nass.usda.gov/ar/) Value = 1.12E+03 $/ha Annual emergy = ($ /yr)(sej/$) Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 13 Total Emergy Sum of inputs 2 through 12 14 Yield, g Yield = 1.62E+03 lb/acre (Bourland et al. 2003; data for the Southeast Branch Experime nt Station at Rohwer) Yield = 1.81E+06 g/ha 15 Product in Joules Energy = (__g)(4.0 kcal/g)( 4186J/kcal) (Odum et al.1998) Energy content = 3.03E+10 J 16 Emergy per mass Total emergy divided by yield in grams 17 Transformity w/services Total emergy yield divided by yield in joules 18 Transformity wo/services Total emergy yield minus servic es divided by yield in joules 19 Empower Density sum of emergy per hectare per year 20 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 21 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-56 Aquaculture Figure A-10. Energy systems diagram of a catfish farm.

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A-57 Table A-15. Emergy evaluation table for a catfish farm, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.31E+13 J 1 5 2 Rain 5.98E+10 J 3.02E+04 181 3 Wind 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Groundwater 2.49E+10 J 2.69E+05 669 Purchased Inputs 5 Fish Fingerlings 5.82E+09 3.36E+06 1954 6 Fuel 1.34E+09 J 1.11E+05 15 7 Electricity 4.64E+09 J 2.69E+05 125 8 Feed 1.50E+11 J 3.36E+05 5056 9 Clay (pond construction) 1.52E+06 g 1.71E+09 260 10 Gravel (pond construction) 2.49E+06 g 1.71E+09 426 11 Machinery 1.32E+03 $ 2.83E+12 374 12 Labor 2.79E+08 J 4.45E+06 124 13 Services 6.22E+03 $ 2.83E+12 1762 14 Total EMERGY 10944 Yields 15 Total Yield 3.92E+06 g 16 Total Yield, energy 1.94E+10 J Calculated ratios 17 Emergy per mass 2.79E+10 sej/g 18 Transformity w/services 5.65E+06 sej/J 19 Transformity wo/services 4.74E+06 sej/J 20 Empower Density 1.09E+17 sej/ha/yr 21 NR + PI Empower Density w/services 1.08E+17 sej/ha/yr 22 NR + PI Empower Density wo/services 9.00E+16 sej/ha/yr Notes: Small-scale Catfish Pr oduction (Six 2-acre ponds) References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area (pond) = 1.00E+04 m2 Albedo = 1.00E-01 (Assumed) Annual energy = 5.31E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain, J Annual energy = (__m/yr)(__m2)(1E6g/m3)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area (pond) = 1.00E+04 m2 Annual energy = 5.98E+10 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996)

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A-58 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag Coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (__m2)(1.3 kg/m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Annual energy = 1.00E+11 J Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Groundwater, J Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Used = 1.67E+00 acre-ft Used = 5.08E+03 m3/yr Annual energy = 2.49E+10 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al. 1998) 5 Fish Fingerlings, J Annual energy = (grams fish)(5 kcal/gr)(4186 J/kcal) Stock = 3.75E+03 fish/acre Stock = 9.26E+03 fish/ha Average weight = 3.00E+01 g/fish (C hapman 2000; http://e dis.ifas.ufl.edu) Total weight = 2.78E+05 g Annual energy = 5.82E+09 J Emergy per unit input = 2.00E+06 sej/J (Brown et al. 1992) 6 Fuel, J (fuel/oil/lube) Annual energy = (Gallons fuel)(1.32E8 J/gal) Tractor = 4.12E+01 h/yr (Engle & Stone 2002; http://srac.tamu.edu) Tractor fuel consumption = 4.20E-02 gal/h (Grisso et al. 2003) Total tractor fuel consumption = 1.73E+00 gal/yr Tractor annual energy = 2.28E+08 J ATV = 9.37E+01 h/yr ATV fuel consumption = 8.97E-02 gal/h (Assumed based on 2.3 L/100 km, 15 km/h) Total ATV fuel consumpti on = 8.40E+00 gal/yr ATV annual energy = 1.11E+09 J Total annual energy = 1.34E+09 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Electricity, J Based on usage of a 1.5 HP/acre electric aerator 1 HP = 2.69E+06 J/h Usage/yr = 7.00E+02 h/acre (Engle & Stone 2002; http://srac.tamu.edu) Usage/yr = 1.73E+03 h/ha Annual energy = 4.64E+09 J Emergy per unit input = 1.60E+05 sej/J (Odum 1996) 8 Feed, J Annual energy = (__grams)(__Kcal/g)(4186 J/kcal) Weight = 4.95E+00 ton/acre (Engl e & Stone 2002; http://srac.tamu.edu) Weight = 1.22E+07 g/ha (30% protein; 6% fat; 30% carbohydrates) (Robinson & Li 1996; http://msucares.com/ pubs/bulletins/b1041.htm) (protein = 4.0 kcal/g; fat = 9.0 kcal/g ; carbohydrates = 4.0 kcal/g ) (FAO 2003) Annual energy = 1.50E+11 J

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A-59 Emergy per unit input = 2.00E+ 05 sej/J (Ortega et al. 2000) 9 Clay, g (pond construction, 20 yr useful life) (Volume clay 50%, volume gravel 50%) (Assumed) Volume clay = 1.38E+01 cu yd/acre (www.uaex.edu/aquaculture2/FSA/FSA9077.htm) Weight(dry) clay = 7.25E+ 01 lb/cu ft (www.sodsoluti ons.com/turfmgt/metric.html) Weight clay = 1.52E+06 g/ha Emergy per unit input = 1.71E+09 (Odum 1996) 10 Gravel, g (pond construction, 20 yr useful life) Volume gravel = 1.38E+01 cu yd/acre (www.uaex.edu/aquaculture2/FSA/FSA9077.htm) Weight (dry) gravel = 1.19E+02 lb/cu ft (www.epa.gov/ttn/chief/ap42/appendix/appa.pdf) Weight gravel = 2.49E+06 g/ha Emergy per unit input = 1.71E+09 (Odum 1996) 11 Machinery, $ (Average useful life 7 yrs) (Assumed after Engle & Stone 2002; www.srac.tamu.edu) Total Investment = 3.74E+03 $/acre (Engle & Stone 2002; www.srac.tamu.edu) Total Investment = 1.32E+03 $/ha-yr Emergy per unit input = 2.29E+12 sej/$ 2001 (This study, see Table A-5) 12 Labor, J Annual energy = (pers-hours/ha/yr)(2500 kcal/day)(4186J/Cal) / (8 pershrs/day) Labor = 8.63E+01 h/acre (Engle & Stone 2002; http://srac.tamu.edu) Labor = 2.13E+02 h/ha Annual energy = 2.79E+08 J Emergy per unit input = 4.45E+06 sej/J (Migrant labor, Brandt-Williams 2001) 13 Services, $ Value = 7.20E-01 $/lb (Engle & Stone 2002; http://srac.tamu.edu) Value = 6.22E+03 $/yr Annual emergy = ($ /yr)(sej/$) Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 14 Total Emergy Sum of inputs 3 through 13 15 Yield, g Total Yield = 3.50E+03 lb/acre (Cha pman 2000: http://e dis.ifas.ufl.edu) Total Yield = 3.92E+06 g/ha 16 Product in Joules Energy = (__grams)(__Kcal/g)(4186 J/kcal) Energy content = 1.18E+02 kcal/100g (raw tissue) (Robinson et al. 2001) Energy content = 1.94E+10 J 17 Emergy per mass Total emergy divided by yield in grams 18 Transformity w/services Total emergy yield divided by yield in joules 19 Transformity wo/services Total emergy yield minus servic es divided by yield in joules 20 Empower Density sum of emergy per hectare per year 21 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 22 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-60 Residential land uses Figure A-11. Energy systems diagram of a single-family residential land use.

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A-61 Table A-16. Emergy evaluation table for a low-density single-family residential land use, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.08E+13 J 1 5 2 Rain (chemical potential) 2.99E+10 J 3.02E+04 90 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Water 3.07E+09 J 2.69E+05 82 6 Fuel 1.01E+10 J 1.11E+05 112 7 Natural Gas 3.68E+10 J 8.06E+04 297 8 Electricity 4.54E+10 J 2.69E+05 1222 9 Pesticides 5.10E+03 g 2.52E+10 13 10 Nitrogen 2.27E+04 g 1.59E+10 36 11 Phosphate 8.43E+03 g 1.45E+10 12 12 Food 2.62E+07 J 3.36E+06 9 13 Construction Materials 3.04E+07 g 1.55E+09 4712 14 Goods & Services 7.55E+03 $ 2.83E+12 2138 15 Total EMERGY 8727 Units/ha = 2.5 21818 Calculated ratios 16 Empower Density 8.73E+16 sej/ha/yr 17 NR + PI Empower Density w/services 8.64E+16 sej/ha/yr 18 Empower Density (2.5 units/ha) 2.18E+17 sej/ha/yr 19 NR + PI Empower Density w/services (2.5 units/ha) 2.16E+17 sej/ha/yr 20 NR + PI Empower Density wo/services (2.5 units/ha) 1.62E+17 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.40E-01 (Odum 1987, refe renced by Brown and Vivas 2005) Annual energy = 5.08E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Percent transpiration = 5.00E-01 (Parker 1998) Annual energy = 2.99E+10 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996)

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A-62 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.00E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater consumption = 1.11E+02 Mgal/day (Data fo r Arkansas, Faulkner, Jeff erson, Lonoke, Prairie, and Lulaski counties, Y 2000: www.water.usg.gov) Groundwater consumption = 1.53E+08 m3/yr Population = 6.15E+05 (Data for Arkansas Faulkner, Jeffers on, Lonoke, Prairie, and Lulaski counties, Y 2000; www.usg.gov) Per capita groundwater consumption = 2.48E+02 m3/yr Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Groundwater consumption = 6.21E+02 m3/unit Annual energy = 3.07E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al. 1998) 6 Fuel, J (Kerosene and LPG) Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E+06 (Estim ated based on 1% increase for Y2000; ADED 2003) Total residential fuel use (Y 2001) = 1.03E+13 Btu (www.eia.gov) Per capita fuel consumption = 3.81E+06 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Fuel consumption = 9.54E+06 Btu/ha Annual energy = 1.01E+10 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Natural Gas, J Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E+06 (Estim ated based on 1% increase for Y2000; ADED 2003) Total residential gas use (Y2001) = 3.77E+13 Btu (www.eia.gov) Per capita gas consumption = 1.40E+07 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Gas consumption = 3.49E+07 Btu Annual energy = 3.68E+10 Emergy per unit input = 4.80E+04 sej/J (Odum 1996)

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A-63 8 Electricity, J Annual Energy = (___KwH/yr)(3.6 E6 J/KwH) Electricity consumption = 1.26E+04 KwH/ yr (Entergy Arkansas, Inc. 2001) Annual energy = 4.54E+10 Btu Emergy per unit input = 1.60E+05 sej/J (Odum 1996) 9 Pesticides, g (includes herbicides, insecticides, fungicides) Annual consumption = 5.10E+03 g/ha (Robbins and Birkenholtz 2003) Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001 ) 10 Nitrogen, g of N (g fertilizer active ingredie nt)(28 gmol P/132 gmol DAP) g = 1.07E+05 (Brown and Vivas 2005) Annual consumption = 2.27E+04 g/ha Emergy per unit input = 1.59E+ 10 sej/g (Brandt-Williams, 2001) 11 Phosphate, g of P (g fertilizer active ingredie nt)(31 gmol P/132 gmol DAP) g = 3.59E+04 (Brown and Vivas 2005) Annual consumption = 8.43E+03 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 12 Food, J Annual consumption = (2500 Cal/day)(4186 J/Cal) Persons/household (Y2000)= 2. 50E+00 (www.census.gov) Annual energy = 2.62E+07 J Emergy per unit input = 3.36E+06 sej/J (After Brown & Vivas 2005) 13 Construction Materials, g Mass (g) = (Total weight)/(50 yrs) Total weight = 1.52E+09 g (Haukoos 1995) Mass = 3.04E+07 g Emergy per unit input = 1.55E+09 sej/g (After Brown & Vivas 2005) 14 Goods, $ Per capita income Y2001 = 2.29E+ 04 $ (ADED, www.1800arkansas.com) Fraction of income into goods= 3.30E-01 (ACCRA Cost of Living Index – Misc. in ADED 2005) Annual consumption = 7.55E+03 $ Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 15 Total Emergy Sum of inputs 2 through 14 16 Empower Density sum of emergy per hectare per year 17 NR + PI Empower Density sum of non renewable and purchased inputs emergy per hectare per year 18 Empower Density (2.5 units/ha) sum of emergy per hectare per year 19 NR + PI Empower Density w/services (2.5 units/ha) sum of non renewable and purchased inputs emergy per hectare per year 20 NR + PI Empower Density wo /services (2.5 units/ha) sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-64 Table A-17. Emergy evaluation table for a medium-d ensity single-family residential land use, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.08E+13 J 1 5 2 Rain (chemical potential) 2.99E+10 J 3.02E+04 90 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Water 3.07E+09 J 2.69E+05 82 6 Fuel 1.01E+10 J 1.11E+05 112 7 Natural Gas 3.68E+10 J 8.06E+04 297 8 Electricity 4.54E+10 J 2.69E+05 1222 9 Pesticides 5.10E+03 g 2.52E+10 13 10 Nitrogen 2.27E+04 g 1.59E+10 36 11 Phosphate 8.43E+03 g 1.45E+10 12 12 Food 2.62E+07 J 3.36E+06 9 13 Construction Materials 3.04E+07 g 1.55E+09 4712 14 Goods & Services 7.55E+03 $ 2.83E+12 2138 15 Total EMERGY 8727 Units/ha = 7 61091 Calculated ratios 16 Empower Density 8.73E+16 sej/ha/yr 17 NR + PI Empower Density 8.64E+16 sej/ha/yr 18 Empower Density (7 units/ha) 6.11E+17 sej/ha/yr 19 NR + PI Empower Density w/services (7 units/ha) 6.05E+17 sej/ha/yr 20 NR + PI Empower Density wo/services (7 units/ha) 4.55E+17 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.40E-01 (Odum 1987, refere nced by Brown and Vivas 2005) Annual energy = 5.08E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Percent transpiration = 5.00E-01 (Parker 1998) Annual energy = 2.99E+10 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996) 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998)

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A-65 Avg. annual wind velocity = 3.04E+00 mp s (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.00E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater consumption = 1.11E+02 Mgal/day (D ata for Arkansas, Faulkner, Jefferson, Lonoke, Prairie, and Lulaski count ies, Y 2000: www.usg.gov) Groundwater consumption = 1.53E+08 m3/yr Population = 6.15E+05 (Data for Ar kansas, Faulkner, Jefferson, Lonoke, Prairie, and Lulaski count ies, Y 2000; www.usg.gov) Per capita groundwater consumption = 2.48E+02 m3/yr Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Groundwater consumption = 6.21E+02 m3/unit Annual energy = 3.07E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al. 1998) 6 Fuel, J (Kerosene and LPG) Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E+06 (Est based on 1% increase for Y2000; ADED 2003) Total residential fuel use (Y 2001) = 1.03E+13 Btu (www.eia.gov) Per capita fuel consumption = 3.81E+06 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Fuel consumption = 9.54E+06 Btu/ha Annual energy = 1.01E+10 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Natural Gas, J Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E+06 (Est based on 1% increase for Y2000; ADED 2003) Total residential gas use (Y2001) = 3.77E+13 Btu (www.eia.gov) Per capita gas consumption = 1.40E+07 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Gas consumption = 3.49E+07 Btu Annual energy = 3.68E+10 Emergy per unit input = 4.80E+04 sej/J (Odum 1996) 8 Electricity, J Annual Energy = (___KwH/yr)(3.6 E6 J/KwH) Electricity consumption = 1.26E+04 KwH/ yr (Entergy Arkansas, Inc. 2001) Annual energy = 4.54E+10 Btu

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A-66 Emergy per unit input = 1.60E+05 sej/J (Odum 1996) 9 Pesticides, g (includes herbicides, insecticides, fungicides) Annual consumption = 5.10E+03 g/ha (Robbins and Birkenholtz 2003) Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001 ) 10 Nitrogen, g of N (g fertilizer active ingredie nt)(28 gmol P/132 gmol DAP) g = 1.07E+05 (Brown and Vivas 2005) Annual consumption = 2.27E+04 g/ha Emergy per unit input = 1.59E+ 10 sej/g (Brandt-Williams, 2001) 11 Phosphate, g of P (g fertilizer active ingredie nt)(31 gmol P/132 gmol DAP) g = 3.59E+04 (Brown and Vivas 2005) Annual consumption = 8.43E+03 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 12 Food, J Annual consumption = (2500 Cal/day)(4186 J/Cal) Persons/household (Y2000)= 2. 50E+00 (www.census.gov) Annual energy = 2.62E+07 J Emergy per unit input = 3.36E+06 sej/J (After Brown & Vivas 2005) 13 Construction Materials, g Mass (g) = (Total weight)/(50 yrs) Total weight = 1.52E+09 g (Haukoos 1995) Mass = 3.04E+07 g Emergy per unit input = 1.55E+09 sej/g (After Brown & Vivas 2005) 14 Goods, $ Per capita income Y2001 = 2.29E+04 $ ( ADED, available at www.1800arkansas.com) Fraction of income into goods= 3.30E-01 (ACCRA Cost of Living Index – Misc., ADED 2005) Annual consumption = 7.55E+03 $ Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 15 Total Emergy Sum of inputs 2 through 14 16 Empower Density sum of emergy per hectare per year 17 NR + PI Empower Density sum of non renewable and purchased inputs emergy per hectare per year 18 Empower Density (7 units/ha) sum of emergy per hectare per year 19 NR + PI Empower Density w/services (7 units/ha) sum of non renewable and purchased inputs emergy per hectare per year 20 NR + PI Empower Density wo/services (7 units/ha) sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-67 Table A-18. Emergy evaluation table fo r a high-density single-family residential land use, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.08E+13 J 1 5 2 Rain (chemical potential) 2.99E+10 J 3.02E+04 90 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Water 3.07E+09 J 2.69E+05 82 6 Fuel 1.01E+10 J 1.11E+05 112 7 Natural Gas 3.68E+10 J 8.06E+04 297 8 Electricity 4.54E+10 J 2.69E+05 1222 9 Pesticides 5.10E+03 g 2.52E+10 13 10 Nitrogen 2.27E+04 g 1.59E+10 36 11 Phosphate 8.43E+03 g 1.45E+10 12 12 Food 2.62E+07 J 3.36E+06 9 13 Construction Materials 3.04E+07 g 1.55E+09 4712 14 Goods & Services 7.55E+03 $ 2.83E+12 2138 15 Total EMERGY 8727 Units/ha = 10 87273 Calculated ratios 16 Empower Density 8.73E+16 sej/ha/yr 17 NR + PI Empower Density 8.64E+16 sej/ha/yr 18 Empower Density (10 units/ha) 8.73E+17 sej/ha/yr 19 NR + PI Empower Density w/services (10 units/ha) 8.64E+17 sej/ha/yr 20 NR + PI Empower Density wo/services (10 units/ha) 6.50E+17 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.40E-01 (Odum 1987, refe renced by Brown and Vivas 2005) Annual energy = 5.08E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Percent transpiration = 5.00E-01 (Parker 1998) Annual energy = 2.99E+10 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996)

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A-68 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observe d winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.00E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater consumption = 1.11E+02 Mgal/day (Data fo r Arkansas, Faulkner, Jeff erson, Lonoke, Prairie, and Lulaski counties, Y 2000: www.water.usg.gov) Groundwater consumption = 1.53E+08 m3/yr Population = 6.15E+05 (Data for Arkansas Faulkner, Jeffers on, Lonoke, Prairie, and Lulaski counties, Y 2000; www.usg.gov) Per capita groundwater consumption = 2.48E+02 m3/yr Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Groundwater consumption = 6.21E+02 m3/unit Annual energy = 3.07E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al. 1998) 6 Fuel, J (Kerosene and LPG) Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E+06 (Estim ated based on 1% increase for Y2000; ADED 2003) Total residential fuel use (Y 2001) = 1.03E+13 Btu (www.eia.gov) Per capita fuel consumption = 3.81E+06 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Fuel consumption = 9.54E+06 Btu/ha Annual energy = 1.01E+10 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Natural Gas, J Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E+06 (Estim ated based on 1% increase for Y2000; ADED 2003) Total residential gas use (Y2001) = 3.77E+13 Btu (www.eia.gov) Per capita gas consumption = 1.40E+07 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Gas consumption = 3.49E+07 Btu Annual energy = 3.68E+10 Emergy per unit input = 4.80E+04 sej/J (Odum 1996)

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A-69 8 Electricity, J Annual Energy = (___KwH/yr)(3.6 E6 J/KwH) Electricity consumption = 1.26E+04 KwH/ yr (Entergy Arkansas, Inc. 2001) Annual energy = 4.54E+10 Btu Emergy per unit input = 1.60E+05 sej/J (Odum 1996) 9 Pesticides, g (includes herbicides, insecticides, fungicides) Annual consumption = 5.10E+03 g/ha (Robbins and Birkenholtz 2003) Emergy per unit input = 1.50E+10 sej/g (B rown and Arding 1991, in Brandt-Williams 2001 ) 10 Nitrogen, g of N (g fertilizer active ingredie nt)(28 gmol P/132 gmol DAP) g = 1.07E+05 (Brown and Vivas 2005) Annual consumption = 2.27E+04 g/ha Emergy per unit input = 1.59E+ 10 sej/g (Brandt-Williams, 2001) 11 Phosphate, g of P (g fertilizer active ingredie nt)(31 gmol P/132 gmol DAP) g = 3.59E+04 (Brown and Vivas 2005) Annual consumption = 8.43E+03 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 12 Food, J Annual consumption = (2500 Cal/day)(4186 J/Cal) Persons/household (Y2000) = 2.50E+00 (www.census.gov) Annual energy = 2.62E+07 J Emergy per unit input = 3.36E+06 sej/J (After Brown & Vivas 2005) 13 Construction Materials, g Mass (g) = (Total weight)/(50 yrs) Total weight = 1.52E+09 g (Haukoos 1995) Mass = 3.04E+07 g Emergy per unit input = 1.55E+09 sej/g (After Brown & Vivas 2005) 14 Goods, $ Per capita income Y2001 = 2.29E+04 $ ( ADED, available at www.1800arkansas.com) Fraction of income into goods = 3.30E-01 (ACCRA Co st of Living Index Miscellaneous in ADED 2005) Annual consumption = 7.55E+03 $ Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 15 Total Emergy Sum of inputs 2 through 14 16 Empower Density sum of emergy per hectare per year 17 NR + PI Empower Density sum of non renewable and purchased inputs emergy per hectare per year 18 Empower Density (10 units/ha) sum of emergy per hectare per year 19 NR + PI Empower Density w/services (10 units/ha) sum of non renewable and purchased inputs emergy per hectare per year 20 NR + PI Empower Density wo/services (10 units/ha) sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-70 Table A-19. Emergy evaluation table for a low-rise (1 story) multi-family residential land use, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.08E+13 J 1 5 2 Rain (chemical potential) 2.99E+10 J 3.02E+04 90 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Water 3.07E+09 J 2.69E+05 82 6 Fuel 1.01E+10 J 1.11E+05 112 7 Natural Gas 3.68E+10 J 8.06E+04 297 8 Electricity 4.54E+10 J 2.69E+05 1222 9 Pesticides 5.10E+03 g 2.52E+10 13 10 Nitrogen 2.27E+04 g 1.59E+10 36 11 Phosphate 8.43E+03 g 1.45E+10 12 12 Food 2.62E+07 J 3.36E+06 9 13 Construction Materials 3.04E+07 g 1.55E+09 4712 14 Goods & Services 7.55E+03 $ 2.83E+12 2138 15 Total EMERGY 8727 Units/ha = 32 281527 Calculated ratios 16 Empower Density 8.73E+16 sej/ha/yr 17 NR + PI Empower Density 8.64E+16 sej/ha/yr 18 Empower Density (32 units/ha) 2.82E+18 sej/ha/yr 19 NR + PI Empower Density w/services (32 units/ha) 2.79E+18 sej/ha/yr 20 NR + PI Empower Density wo/services (32 units/ha) 2.10E+18 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.40E-01 (Odum 1987, refe renced by Brown and Vivas 2005) Annual energy = 5.08E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Percent transpiration = 5.00E-01 (Parker 1998) Annual energy = 2.99E+10 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996)

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A-71 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.00E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater consumption = 1.11E+02 Mgal/day (Data for Arkansas, Faulkner, Jeffer son, Lonoke, Prairie, and Lulaski counties, Y 2000: www.water.usg.gov) Groundwater consumption = 1.53E+08 m3/yr Population = 6.15E+05 (Data for Arkansas, Faulkner, Jefferson, Lonoke, Prairie, and Lulaski counties, Y 2000; www.usg.gov) Per capita groundwater consumption = 2.48E+02 m3/yr Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Groundwater consumption = 6.21E+02 m3/unit Annual energy = 3.07E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al. 1998) 6 Fuel, J (Kerosene and LPG) Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E+06 (Estim ated based on 1% increase for Y2000; ADED 2003) Total residential fuel use (Y2001) = 1.03E+13 Btu (www.eia.gov) Per capita fuel consumption = 3.81E+06 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Fuel consumption = 9.54E+06 Btu/ha Annual energy = 1.01E+10 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Natural Gas, J Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E +06 (Estimated based on 1% increase for data for Y2000; ADED 2003) Total residential gas use (Y2001) = 3.77E+13 Btu (www.eia.gov) Per capita gas consumption = 1.40E+07 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Gas consumption = 3.49E+07 Btu Annual energy = 3.68E+10

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A-72 Emergy per unit input = 4.80E+04 sej/J (Odum 1996) 8 Electricity, J Annual Energy = (___KwH/yr)(3.6 E6 J/KwH) Electricity consumption = 1.26E+04 KwH/ yr (Entergy Arkansas, Inc. 2001) Annual energy = 4.54E+10 Btu Emergy per unit input = 1.60E+05 sej/J (Odum 1996) 9 Pesticides, g (includes herbicides, insecticides, fungicides) Annual consumption = 5.10E+03 g/ha (Robbins and Birkenholtz 2003) Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001 ) 10 Nitrogen, g of N (g fertilizer active ingredie nt)(28 gmol P/132 gmol DAP) g = 1.07E+05 (Brown and Vivas 2005) Annual consumption = 2.27E+04 g/ha Emergy per unit input = 1.59E+ 10 sej/g (Brandt-Williams, 2001) 11 Phosphate, g of P (g fertilizer active ingredie nt)(31 gmol P/132 gmol DAP) g = 3.59E+04 (Brown and Vivas 2005) Annual consumption = 8.43E+03 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 12 Food, J Annual consumption = (2500 Cal/day)(4186 J/Cal) Persons/household (Y2000)= 2. 50E+00 (www.census.gov) Annual energy = 2.62E+07 J Emergy per unit input = 3.36E+06 sej/J (After Brown & Vivas 2005) 13 Construction Materials, g Mass (g) = (Total weight)/(50 yrs) Total weight = 1.52E+09 g (Haukoos 1995) Mass = 3.04E+07 g Emergy per unit input = 1.55E+09 sej/g (After Brown & Vivas 2005) 14 Goods, $ Per capita income Y2001 = 2.29E+04 $ ( ADED, available at www.1800arkansas.com) Fraction of income into goods= 3.30E-01 (ACCRA Cost of Living Index Miscellaneous in ADED 2005) Annual consumption = 7.55E+03 $ Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 15 Total Emergy Sum of inputs 2 through 14 16 Empower Density sum of emergy per hectare per year 17 NR + PI Empower Density sum of non renewable and purchased inputs emergy per hectare per year 18 Empower Density (32 units/ha) sum of emergy per hectare per year 19 NR + PI Empower Density w/services (32 units/ha) sum of non renewable and purchased inputs emergy per hectare per year 20 NR + PI Empower Density wo/services (32 units/ha) sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-73 Table A-20. Emergy evaluation table fo r a high rise (3 story) multi-family residential land use, per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.08E+13 J 1 5 2 Rain (chemical potential) 2.99E+10 J 3.02E+04 90 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Water 3.07E+09 J 2.69E+05 82 6 Fuel 1.01E+10 J 1.11E+05 112 7 Natural Gas 3.68E+10 J 8.06E+04 297 8 Electricity 4.54E+10 J 2.69E+05 1222 9 Pesticides 5.10E+03 g 2.52E+10 13 10 Nitrogen 2.27E+04 g 1.59E+10 36 11 Phosphate 8.43E+03 g 1.45E+10 12 12 Food 2.62E+07 J 3.36E+06 9 13 Construction Materials 3.04E+07 g 1.55E+09 4712 14 Goods & Services 7.55E+03 $ 2.83E+12 2138 15 Total EMERGY 8727 Units/ha = 97 844580 Calculated ratios 16 Empower Density 8.73E+16 sej/ha/yr 17 NR + PI Empower Density 8.64E+16 sej/ha/yr 18 Empower Density (97 units/ha) 8.45E+18 sej/ha/yr 19 NR + PI Empower Density w/services (97 units/ha) 8.36E+18 sej/ha/yr 20 NR + PI Empower Density wo/services (97 units/ha) 6.29E+18 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.40E-01 (Odum 1987, refe renced by Brown and Vivas 2005) Annual energy = 5.08E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Percent transpiration = 5.00E-01 (Parker 1998) Annual energy = 2.99E+10 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996)

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A-74 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+ 00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.00E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume)(1E6 g/m3)(4.94 J/g) Groundwater consumption = 1.11E+02 Mgal/day (Data fo r Arkansas, Faulkner, Jeff erson, Lonoke, Prairie, and Lulaski counties, Y 2000: www.water.usg.gov) Groundwater consumption = 1.53E+08 m3/yr Population = 6.15E+05 (Data for Arkansas Faulkner, Jeffers on, Lonoke, Prairie, and Lulaski counties, Y 2000; www.usg.gov) Per capita groundwater consumption = 2.48E+02 m3/yr Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Groundwater consumption = 6.21E+02 m3/unit Annual energy = 3.07E+09 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al. 1998) 6 Fuel, J (Kerosene and LPG) Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2.70E+06 (Es timated based on 1% increase for Y2000; ADED 2003) Total residential fuel use (Y2001) = 1.03E+13 Btu (www.eia.gov) Per capita fuel consumption = 3.81E+06 Btu Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Fuel consumption = 9.54E+06 Btu/ha Annual energy = 1.01E+10 J Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Natural Gas, J Annual energy = (Btu)(1055 J/Btu) Population Arkansas (Y2001) = 2. 70E+06 (Estimated based on 1% increase for Y2000; ADED 2003) Total residential gas use (Y2001) = 3.77E+13 Btu (www.eia.gov) Per capita gas consumption = 1.40E+07 Btu

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A-75 Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Gas consumption = 3.49E+07 Btu Annual energy = 3.68E+10 Emergy per unit input = 4.80E+04 sej/J (Odum 1996) 8 Electricity, J Annual Energy = (___KwH/yr)(3.6 E6 J/KwH) Electricity consumption = 1.26E+04 KwH/ yr (Entergy Arkansas, Inc. 2001) Annual energy = 4.54E+10 Btu Emergy per unit input = 1.60E+05 sej/J (Odum 1996) 9 Pesticides, g (includes herbicides, insecticides, fungicides) Annual consumption = 5.10E+03 g/ ha (Robbins and Birkenholtz 2003) Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001 ) 10 Nitrogen, g of N (g fertilizer active ingredie nt)(28 gmol P/132 gmol DAP) g = 1.07E+05 (Brown and Vivas 2005) Annual consumption = 2.27E+04 g/ha Emergy per unit input = 1.59E+ 10 sej/g (Brandt-Williams, 2001) 11 Phosphate, g of P (g fertilizer active ingredie nt)(31 gmol P/132 gmol DAP) g = 3.59E+04 (Brown and Vivas 2005) Annual consumption = 8.43E+03 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 12 Food, J Annual consumption = (2500 Cal/day)(4186 J/Cal) Persons/household (Y2000)= 2. 50E+00 (www.census.gov) Annual energy = 2.62E+07 J Emergy per unit input = 3.36E+06 sej/J (After Brown & Vivas 2005) 13 Construction Materials, g Mass (g) = (Total weight)/(50 yrs) Total weight = 1.52E+09 g (Haukoos 1995) Mass = 3.04E+07 g Emergy per unit input = 1.55E+09 sej/g (After Brown & Vivas 2005) 14 Goods, $ Per capita income Y2001 = 2.29E+04 $ (ADED, available at www.1800arkansas.com) Fraction of income into goods= 3.30E-01 (ACCRA Cost of Living Index Miscellaneous in ADED 2005) Annual consumption = 7.55E+03 $ Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 15 Total Emergy Sum of inputs 2 through 14 16 Empower Density sum of emergy per hectare per year 17 NR + PI Empower Density sum of non renewable and purchased inputs emergy per hectare per year 18 Empower Density (97 units/ha) sum of emergy per hectare per year 19 NR + PI Empower Density w/services (97 units/ha) sum of non renewable and purchased inputs emergy per hectare per year 20 NR + PI Empower Density wo/services (97 units/ha) sum of non renewable and purchased inputs emergy per hectare per year minus services

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A-76 Table A-21. Emergy evaluation table for a tu rf grass house lawn, per ha per year Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.08E+13 J 1 5 2 Rain (chemical potential) 2.99E+10 J 3.02E+04 90 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 4 Water use (Transpiration) 7.16E+10 J 3.02E+04 217 Nonrenewable Storages Used 5 Net Topsoil Loss 6.33E+07 J 1.24E+05 1 Purchased Inputs 6 Water (irrigation) 1.91E+10 J 2.69E+05 513 7 Pesticides 5.10E+03 g 2.52E+10 13 8 Nitrogen 2.27E+04 g 1.59E+10 36 9 Phosphate 8.43E+03 g 1.45E+10 12 10 Total EMERGY 791 Calculated ratios 11 Empower Density 7.91E+15 sej/ha/yr 12 NR + PI Empower Density 5.75E+15 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (____m2)(____Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.40E-01 (Odum 1987, refe renced by Brown and Vivas 2005) Annual energy = 5.08E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Percent transpiration = 5.00E-01 (Parker 1998) Annual energy = 2.99E+10 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996) 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mp s (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (__m2)(1.3 kg/m3)(1.00 E-3)(__mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Water use (Transpiration), J Annual energy = (Transpiration)(area)(1E6 g/m3)(4.94 J/g)) Transpiration = 1.45E+00 m/yr (R.L. D uble, Texas Cooperative Extension; http://aggie-horticulture.tamu.edu)

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A-77 Annual energy = 7.16E+10 J/yr Emergy per unit input = 1.50E+05 sej/J (Ave rage transformities for rain and groundwater) 5 Net Topsoil Loss, J Erosion rate = 7.00E+00 g/m2/yr (Pimentel et al. 1995) Organic fraction in soil = 0.04 (Pimentel et al. 1995) Energy cont./g organic = 5.40 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 6.33E+07 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 6 Water, J Annual energy = Chemical potential of groundwater Annual energy = ( Volume) (1E6 g/m3) (4.94 J/g) Groundwater consumption = 1.11E+02 Mgal/day (Data for Arkansas, Faulkner, Jeffer son, Lonoke, Prairie, and Lulaski counties, Y 2000: www.water.usg.gov) Groundwater consumption = 1.53E+08 m3/yr Population = 6.15E+05 (Data for Arkansas, Faul kner, Jefferson, Lonoke, Prairie, and Lulaski counties, Y 2000; www.usg.gov) Per capita groundwater consumption = 2.48E+02 m3/yr Persons/household (Y2000) = 2. 50E+00 ( www.census.gov) Groundwater consumption = 6.21E+02 m3/unit Fraction of groundwater used for irrigation = 5.80E-01 (After AWWARF 2000; www.awwarf.org) Ground water used for irrigation = 3.60E+02 m3/unit Number of units = 1.07E+01 unit/ha (Assumed 65% of residential unit as lawn, and 23% of landscape as lawn after Robbins and Birkenholtz 2003) Annual energy = 1.91E+10 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al 1998) 7 Pesticides, g (includes herbicides, insecticides, fungicides) Annual consumption = 5.10E+03 g/ha (Robbins and Birkenholtz 2003) Emergy per unit input = 1.50E+10 sej/g (Bro wn and Arding 1991, in Brandt-Williams 2001 ) 8 Nitrogen, g of N (g fertilizer active ingredie nt)(28 gmol P/132 gmol DAP) g = 1.07E+05 (Brown and Vivas 2005) Annual consumption = 2.27E+04 g/ha Emergy per unit input = 1.59E+ 10 sej/g (Brandt-Williams 2001) 9 Phosphate, g of P (g fertilizer active ingredie nt)(31 gmol P/132 gmol DAP) g = 3.59E+04 (Brown and Vivas 2005) Annual consumption = 8.43E+03 g/ha Emergy per unit input = 1.45E+10 sej/g (Brandt-Williams 2001) 10 Total Emergy Sum of inputs 4 through 9 11 Empower Density sum of emergy per hectare per year 12 NR Empower Density sum of non renewable emergy per hectare per year

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A-78 Commercial land uses Figure A-12. Energy systems diagra m of a commercial land use.

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A-79 Table A-22. Emergy evaluation table for a low-intensity commercial land use (commercial strip), per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.19E+13 J 1 5 2 Rain (chemical potential) 2.99E+09 J 3.02E+04 9 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Fuel 3.26E+11 J 1.11E+05 3610 6 Natural Gas 1.92E+12 J 8.06E+04 15513 7 Electricity 2.01E+12 J 2.69E+05 53906 8 Construction Materials 1.50E+08 g 2.25E+09 33769 9 Labor 3.33E+10 J 4.13E+07 137642 10 Services 9.64E+05 $ 2.83E+12 272963 11 Total EMERGY 517431 Calculated ratios 12 Empower Density 5.17E+18 sej/ha/yr 13 NR + PI Empower Density w/services 5.17E+18 sej/ha/yr 14 NR + PI Empower Density wo/services 2.44E+18 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.20E-01 (Assumed) Annual energy = 5.19E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Fraction transpired = 5.00E-02 (Parker 1998) Annual energy = 2.99E+09 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996) 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mp s (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr

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A-80 Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.50E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Fuel, J Annual energy = (Btu)*(1055 J/Btu) Total area commercial/industrial LU in AR = 3.56E+08 m2 (Calculated using a GIS based on the 1999 AR LU/LC: Summer; available at www.cast.uark.edu/cast/geostor/) Total area commercial LU in AR = 1.78E+08 m2 (Assumed 1/2 of total area fo r commercial/industrial land use) Fuel used in AR (2001) = 5.50E+12 Btu (www.eia.gov) Annual energy = 3.26E+11 J/ha Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 6 Natural Gas, J Annual energy = (Btu)*(1055 J/Btu) Total area commercial LU in AR = 1.78E+08 m2 Natural gas used in AR (2001) = 3.25E+13 Btu (www.eia.gov) Annual energy = 1.92E+12 J/yr Emergy per unit input = 4.80E+04 sej/J (Odum 1996) 7 Electricity, J Annual energy = (Btu)*(1055 J/Btu) Total area commercial LU in AR = 1.78E+08 m2 Electricity used in AR (2001) = 3.39E+13 Btu (www.eia.gov) Annual energy = 2.01E+12 J/yr Emergy per unit input = 1.60E+05 sej/J (Odum 1996) 8 Construction Materials, g Construction volume calculations based on municipal code specifica tions for North Little Ro ck, 2004 (www.municode.com) Calculations based for 11 units/h a and 50% shared materials. Commercial lot area = 1.00E+04 sq. ft. (City Council, North Little Rock, Arkansas 2004; www.municode.com) Concrete and wood, assumed 50% each in construction volume Mass (g) = (Total weight)/(50 yrs) Building structure (concrete) = 2.70E+03 m3 Weight (concrete) = 2.40E+03 kg/m3 Mass = 1.30E+08 g Emergy per unit input = 1.28E+09 sej/g (Haukoos 1995) Building structure (wood) = 2.70E+03 m3 Weight (wood) = 3.80E+02 kg/m3 Mass = 2.05E+07 g Emergy per unit input = 1.40E+09 sej/g (Haukoos 1995) Total mass = (concrete) + (wood) Total mass = 1.50E+08 g Emergy per unit input = 1.34E+09 sej/g (Avera ge of transformities for concrete and wood)

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A-81 9 Labor, J Annual energy = (pers/ha/yr)*(2500 kcal/day)*(41 86J/Cal)*(250 days/person-yr)*(fraction day worked) # persons employed by sector (2001) = 3.69E +05 person/yr (AESD 2001; www.arkansas.gov) # persons employed non-shopping centers (2001) = 6.74E+05 person/yr (Estimated base d on employment data for shopping centers in Arkansas for 2004; ICSC 2005) Total area non-shopping center LU in AR = 1.75E+08 m2 (Estimated based on data for sh opping centers in Arkansas for 2004; ICSC 2005) # persons employed per ar ea = 3.86E+01 person/ha Total annual energy = 3.33E+10 J Emergy per unit input = 2.46E+07 sej/J (Transformity of education through high school, Odum 1996) 10 Services (labor), $/ha Annual emergy = ($ /yr)*(sej/$) Per capita income for sector (2001) = 2.50E+04 $/yr (Estimated from AE SD 2001; www.arkansas.gov) # persons employed non-shopping centers (2001) = 3.86E+01 person/ha Dollar value = 9.64E+05 $/ha Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 11 Total Emergy Sum of inputs 3 through 10 12 Empower Density sum of emergy per hectare per year 13 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 14 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emer gy per hectare per year minus services

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A-82 Table A-23. Emergy evaluation table for a high intensity commercial land use (shopping center), per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.19E+13 J 1 5 2 Rain (chemical potential) 2.99E+09 J 3.02E+04 9 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Fuel 3.26E+11 J 1.11E+05 3610 6 Natural Gas 1.92E+12 J 8.06E+04 15513 7 Electricity 2.01E+12 J 2.69E+05 53906 8 Construction Materials 2.82E+08 g 3.40E+09 95871 9 Labor 5.84E+10 J 4.13E+07 241459 10 Services 1.51E+06 $ 2.83E+12 426856 11 Total EMERGY 837242 Calculated ratios 12 Empower Density 8.37E+18 sej/ha/yr 13 NR + PI Empower Density w/services 8.37E+18 sej/ha/yr 14 NR + PI Empower Density wo/services 4.10E+18 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.20E-01 (Assumed) Annual energy = 5.19E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Fraction Transpired = 5.00E-02 (Parker 1998) Annual energy = 2.99E+09 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996) 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mp s (Data for Little Rock,2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr

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A-83 Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.50E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Fuel, J Annual energy = (Btu)*(1055 J/Btu) Total area comm./indust. LU in AR = 3.56E+08 m2 (Calculated with a GIS based on the 1999 AR LU/LC: Summer; available at www.ca st.uark.edu/cast/geostor/) Total area commercial LU in AR = 1.78E+08 m2 (Assumed 1/2 of total area for comm./industrial land use) Fuel used in AR (2001) = 5.50E+12 Btu (www.eia.gov) Annual energy = 3.26E+11 J/ha Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 6 Natural Gas, J Annual energy = (Btu)*(1055 J/Btu) Total area commercial LU in AR = 1.78E+08 m2 Natural gas used in AR (2001) = 3.25E+13 Btu (www.eia.gov) Annual energy = 1.92E+12 J/yr Emergy per unit input = 4.80E+04 sej/J (Odum 1996) 7 Electricity, J Annual energy = (Btu)*(1055 J/Btu) Total area commercial LU in AR = 1.78E+08 m2 Electricity used in AR (2001) = 3.39E+13 Btu (www.eia.gov) Annual energy = 2.01E+12 J/yr Emergy per unit input = 1.60E+05 sej/J (Odum 1996) 8 Construction Materials, g Construction volume calculations based on municipal code specificati ons for North Little Rock 2004 (www.municode.com) Concrete and steel, assumed 50% each in construction volume. Mass (g) = (Total weight)/(50 yrs) Building structure (concrete) = 5.06E+03 m3 Weight (concrete) = 2.40E+03 kg/m3 Mass = 2.43E+08 g Emergy per unit input = 2.15E+09 sej/g (Haukoos 1995) Building structure (steel) = 5.06E+03 m3 Weight (steel) = 3.80E+02 kg/m3 Mass = 3.85E+07 g Emergy per unit input = 4.65E+09 sej/g (Haukoos 1995) Total mass = 2.82E+08 g Emergy per unit input = 3.40E+09 sej/g (Average of transformities for concrete and steel) 9 Labor, J Annual energy = (pers/ha/yr)*(2500 kcal/day)*(41 86J/Cal)*(250 days/person-yr)*(fraction day worked) # persons employed = 8.06E+04 pe rson/yr (Data for 2004; ICSC 2005) Total leasable retail area = 3.57E+06 m2 (Data for 2004; ICSC 2005) # persons employed per ar ea = 6.77E+01 person/ha Annual energy = 5.84E+10 J

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A-84 Emergy per unit input = 2.46E+07 sej/J (Transformity of education through high school, Odum 1996) 10 Services (labor), $/ha Annual emergy = ($ /yr)(sej/$) Per capita income for sector (2001) = 2.23E+04 $/yr (Estimated from AESD 2001; www.arkansas.gov) # Persons employed per area = 6.77E+01 person/ha Dollar value = 1.51E+06 $/ha Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 11 Total Emergy Sum of inputs 3 through 10 12 Empower Density sum of emergy per hectare per year 13 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 14 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emer gy per hectare per year minus services

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A-85 Industrial land use Figure A-13. Energy systems diagra m of an industrial land use.

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A-86 Table A-24. Emergy evaluation table for an industrial land use, per ha per year Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.19E+13 J 1 5 2 Rain (chemical potential) 2.99E+09 J 3.02E+04 9 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 5 Groundwater 1.45E+10 J 2.69E+05 390 Purchased Inputs 6 Coal 6.45E+11 J 1.11E+05 7154 7 Fuel 5.03E+12 J 6.69E+04 33640 8 Natural Gas 7.43E+12 J 8.06E+04 59903 9 Electricity 3.38E+12 J 2.69E+05 90848 10 Construction Materials 3.18E+08 g 3.40E+09 108264 11 Labor 1.58E+10 J 4.13E+07 65269 12 Services 5.58E+05 $ 2.83E+12 158004 13 Total EMERGY 523502 Calculated ratios 14 Empower Density 5.24E+18 sej/ha/yr 15 NR + PI Empower Density w/services 5.23E+18 sej/ha/yr 16 NR + PI Empower Density wo/services 3.65E+18 sej/ha/yr Notes: References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.20E-01 (Assumed) Annual energy = 5.19E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Fraction transpired = 5.00E-02 (Parker 1998) Annual energy = 2.99E+09 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996) 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mp s (Data for Little Rock,2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3)

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A-87 = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.50E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Water, J (groundwater) Annual energy = Chemical potential of groundwater Annual energy = ( Volume) (1E6 g/m3) (4.94 J/g) Total area comm./indust. LU in AR = 3.56E+08 m2 (Calculated with a GIS based on the 1999 AR LU/LC: Summer; available at www.ca st.uark.edu/cast/geostor/) Total area industrial LU in AR = 1.78E+08 m2 (Assumed 1/2 of total area fo r commercial/industrial land use) Groundwater consumption = 3.79E+01 Mgal/day (Data for Arkansas, Faulkner, Jeffer son, Lonoke, Prairie, and Lulaski counties, Y 2000: www.water.usg.gov) Groundwater consumption = 5.24E+07 m3/yr Groundwater Consumption = 2.94E+03 m3/ha Annual energy = 1.45E+10 J Emergy per unit input = 1.60E+ 05 sej/J (Odum et al 1998) 6 Coal, J Annual energy = (Btu)*(1055 J/Btu) Total area industrial LU in AR = 1.78E+08 m2 Coal used in AR (2001) = 1.09E+13 Btu (www.eia.gov) Annual energy = 6.45E+11 J/ha Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 7 Fuel, J Annual energy = (Btu)*(1055 J/Btu) Total area industrial LU in AR = 1.78E+08 m2 Fuel used in AR (2001) = 8.50E+13 Btu (www.eia.gov) Annual energy = 5.03E+12 J/ha Emergy per unit input = 3.98E+04 sej/J (Odum 1996) 8 Natural Gas, J Annual energy = (Btu)*(1055 J/Btu) Total Area Commercial LU in AR = 1.78E+08 m2 Natural gas used in AR (2001) = 1.26E+14 Btu (www.eia.gov) Annual energy = 7.43E+12 J/yr Emergy per unit input = 4.80E+04 sej/J (Odum 1996) 9 Electricity, J Annual energy = (Btu)*(1055 J/Btu) Total area of industrial LU in AR = 1.78E+08 m2 Electricity used in AR (2001) = 5.71E+13 Btu (www.eia.gov) Annual energy = 3.38E+12 J/yr Emergy per unit input = 1.60E+05 sej/J (Odum 1996)

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A-88 10 Construction Materials, g Construction volume calculations based on municipal code specificati ons for North Little Rock, 2004 (www.municode.com). Concrete and steel, assumed 50% each in construction volume. Mass (g) = (Total weight)/(50 yrs) Building structure (concrete) = 5.72E+03 m3 Weight (concrete) = 2.40E+03 kg/m3 Mass = 2.75E+08 g Emergy per unit input = 2.15E+09 sej/g (Haukoos 1995) Building structure (steel) = 5.72E+03 m3 Weight (steel) = 3.80E+02 kg/m3 Mass = 4.35E+07 g Emergy per unit input = 4.65E+09 sej/g (Haukoos 1995) Total mass = 3.18E+08 g Emergy per unit input = 3.40E+09 sej/g (Average of transformities for concrete and steel) 11 Labor, J Annual energy = (pers/ha/yr)*(2500 kcal/day)*(41 86J/Cal)*(250 days/person-yr)*(fraction day worked) # persons employed = 3.26E+05 person/yr (Estimated from AESD 2001; www.arkansas.gov) # persons employed per area = 1.83E+01 person/ha Annual energy = 1.58E+10 J Emergy per unit input = 2.46E+07 sej/J (Transformity of education through high school, Odum 1996) 12 Services (labor), $/ha Annual emergy = ($ /yr)(sej/$) Per capita income for sector (2001) = 3.05E+04 $/yr (Estimated fro m AESD 2001; www.arkansas.gov) # persons employed per area = person/ha Dollar value = 5.58E+05 $/ha Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 13 Total Emergy Sum of inputs 3 through 12 14 Empower Density sum of emergy per hectare per year 15 NR + PI Empower Density w/services sum of non renewable and purchased inputs emergy per hectare per year 16 NR + PI Empower Density wo/services sum of non renewable and purchased inputs emer gy per hectare per year minus services

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A-89 Transportation land uses Figure A-14. Energy systems diagram of a transportation corridor (highway).

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A-90 Table A-25: Emergy evaluation table fo r a low-intensity transportation co rridor (2 lane road), per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.19E+13 J 1 5 2 Rain (chemical potential) 2.99E+09 J 3.02E+04 9 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Fuel 4.31E+12 J 1.11E+05 47844 6 Vehicles 1.75E+05 g 4.28E+10 749 7 Construction Materials 3.03E+02 $ 2.83E+12 86 8 Maintenance & Operation 2.62E+03 $ 2.83E+12 742 9 Total EMERGY 49450 Calculated ratios 10 Empower Density 4.94E+17 sej/ha/yr 11 NR + PI Empower Density 4.94E+17 sej/ha/yr Notes: Data on purchased inputs for US Highway 70; assumed 2 lanes. References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.20E-01 (www.epa.gov) Annual energy = 5.19E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Fraction transpired = 5.00E-02 (Parker 1998) Annual energy = 2.99E+09 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996) 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observe d winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.50E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr

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A-91 Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Fuel, J (Data for US Highway 70) Annual energy = (Gallons fuel)*(1.32E8 J/gal) Average number of cars = 3.28E+03 vehicl es/day (AHTD 1999; www.ahtd.state.ar.us) Average number of cars = 1.20E+06 vehicles/yr Average KPG = 4.03E+01 km/gal (Assumed) US H-70 length in the BMW = 3.61E+01 km (Calculated using a GIS) Total fuel use = 1.07E+06 gal/yr Total annual energy = 1.42E+14 J/yr Total annual energy/1111m length = 4.31E+12 J/yr (Lane width = 15 feet/4.6m; 2 lanes) Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 6 Vehicles, g Average number of cars = 1.20E+06 vehicles/yr Average speed = 8.86E+01 km/hr (Assumed) Time spent on road segment = 1.25E-02 hr Average useful life of a vehi cle = 8.76E+04 hr (Assumed) Fraction of life spent on road segment = 1.43E-07 Average weight of a vehicle = 1. 02E+03 kg/vehicle (McGrane 1994) Vehicle use on road segment = 1.46E-04 kg/vehicle Total vehicle use on road segment = 1.75E+05 g/yr Emergy per unit input = 4.28E+10 sej/g (After McGrane 1994) 7 Construction Materials, $ Cost ($) = (Cost of 1111m length)/(50 yrs) Cost/mile = 2.20E+04 $/yr (Assumed as 1/2 th e cost of Interstate mile, see Table A-26) Cost/1111m length = 3.03E+02 $/yr Emergy per unit input = 2.83E+12 sej/$, 2001 8 Maintenance & Operation, $ Cost/mile = 3.81E+03 $/yr (Assumed as 1/2 th e cost of Interstate mile, see Table A-26) Cost/1111m length = 2.62E+03 $/yr Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 9 Total Emergy Sum of inputs 3 through 8 10 Empower Density sum of emergy per hectare per year 11 NR + PI Empower Density sum of non renewable and purchased inputs emergy per hectare per year

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A-92 Table A-26: Emergy evaluation table for a high-intensity transportation corridor (4 lane road), per ha per year. Data Emergy/unit Solar EMERGY Note Description (per ha-1 yr-1) (sej/unit) (E13 sej/yr) Renewable Inputs 1 Sunlight 5.19E+13 J 1 5 2 Rain (chemical potential) 2.99E+09 J 3.02E+04 9 3 Wind (kinetic energy) 1.00E+11 J 2.45E+03 25 Nonrenewable Storages Used 4 Net Topsoil Loss 3.70E+08 J 1.24E+05 5 Purchased Inputs 5 Fuel 2.25E+13 J 1.11E+05 249672 6 Vehicles 6.64E+05 g 4.28E+10 2840 7 Construction Materials 3.03E+02 $ 2.83E+12 86 8 Maintenance & Operation 2.62E+03 $ 2.83E+12 743 9 Total EMERGY 253369 Calculated ratios 10 Empower Density 2.53E+18 sej/ha/yr 11 NR + PI Empower Density 2.53E+18 sej/ha/yr Notes: Data on purchased inputs for Interstate-40 (4 lanes). References: 1 Sunlight, J Annual energy (J) = (Avg. Total A nnual Insolation J/yr)(Area)(1-albedo) = (__m2)(__Cal/cm2/y)(1E+04cm2/m2)(1-albedo)(4186J/kcal) Insolation = 1.41E+02 kcal/cm2/yr (Odum et al. 1998) Area = 1.00E+04 m2 Albedo = 1.20E-01 (www.epa.gov) Annual energy = 5.19E+13 J Emergy per unit input = 1.00E+00 sej/J (Odum 1996) 2 Rain (chemical potential), J Annual energy = (__m/yr)(__m2)(1E6g/m3)(% Transpiration)(4.94J/g) Annual rainfall = 1.21E +00 m/yr (www.noaa.gov) Area = 1.00E+04 m2 Fraction transpired = 5.00E-02 (Parker 1998) Annual energy = 2.99E+09 J Emergy per unit input = 1.80E+04 sej/J (Odum 1996) 3 Wind (kinetic energy), J Area = 1.00E+04 m2 Density of air = 1.23E+00 kg/m3 (Odum et al. 1998) Avg. annual wind velocity = 3.04E+00 mps (Data for Little Rock, 2001; www.noaa.gov) Geostrophic wind = 5.07E+00 mps (Observed winds are about 0.6 of geostrophic wind) Drag coeff. = 2.00E-03 (Garrat 1977) Energy (J) = (area)(air dens ity)(drag coefficient)(velocity3) = (___m2)(1.3 kg/m3)(1.00 E-3)(___mps)(3.14 E7 s/yr) Energy (J) = 1.00E+11 J/yr Emergy per unit input = 2.45E+ 03 sej/J (Odum et al. 2000) 4 Net Topsoil Loss, J Erosion rate = 1.50E+00 lb/acre/day (Corbitt 1990) Erosion rate = 4.09E+01 g/m2/yr

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A-93 Organic fraction in soil = 4. 00E-02 (Pimentel et al. 1995) Energy cont./g organic = 5.40E+00 kcal/g Net loss of topsoil = (farmed area)(erosion rate) Organic matter in topsoil used up = (total mass of topsoil)(% organic) Energy loss = (loss of organic matter)(5.4 kcal/g)(4186 J/kcal) Annual energy = 3.70E+08 Emergy per unit input = 7.38E+04 sej/J (Odum 1996) 5 Fuel, J Annual energy = (Gallons fuel)*(1.32E8 J/gal) Average number of cars = 3.38E+04 vehicl es/day (AHTD 1999; www.ahtd.state.ar.us) Average number of cars = 1.23E+07 vehicles/yr Average KPG = 4.03E+01 km/gal (Assumed) I-40 length in the BMW = 6.17E+01 km (Calculated using a GIS) Total fuel use = 1.89E+07 gal/yr Total annual energy = 2.50E+15 J/yr Total annual energy/556m length = 2.25E+ 13 J/yr (Lane width = 15 feet/4.6m) Emergy per unit input = 6.60E+04 sej/J (Odum 1996) 6 Vehicles, g Average number of cars = 1.23E+07 vehicles/yr Average speed = 1.21E+02 km/hr (Assumed) Time spent on road segment = 4.60E-03 hr Average useful life of a vehi cle = 8.76E+04 hr (Assumed) Fraction of life spent on road segment = 5.26E-08 Average weight of a vehicle = 1.02E+03 kg/vehicle (McGrane 1994) Vehicle use on road segment = 5.38E-05 kg/vehicle Total vehicles use on road segment = 6.64E+05 g/yr Emergy per unit input = 4.28E+10 sej/g (After McGrane 1994) 7 Construction Materials, $ Cost ($) = (Cost of 556m length)/(50 yrs) Cost/mile = 4.39E+04 $/yr (AHC 2002; www.ahtd.state.ar.us) Cost/556m length = 3.03E+02 $/yr Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 8 Maintenance & Operation, $ Cost/mile = 7.61E+03 $/yr (AHC 2002; www.ahtd.state.ar.us) Cost/556m length = 2.62E+03 $/yr Emergy per unit input = 2.83E+12 sej/$ 2001 (This study, see Table A-5) 9 Total Emergy Sum of inputs 3 through 8 10 Empower Density sum of emergy per hectare per year 11 NR + PI Empower Density sum of non renewable and purchased inputs emergy per hectare per year

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A-98 Odum, H.T., M.T. Brown, and S. Brandt-Williams. 2000. Handbook of emergy evaluation: a compendium of data fo r emergy evaluation. Folio # 1 Introduction and Global Budget. Center for Environm ental Policy, Environm ental Engineering Sciences, University of Florida, Gainesville. Odum, H.T., C. Diamond, and M.T. Brown. 1987. Energy systems overview of the Mississippi River Basin. Re port to the Cousteau Soci ety, CFW Publication #87-1. Center for Wetlands, University of Florid a, Gainesville, Florida, USA. 107 p. Odum, H.T., S. Romitelli, and R. Tighe. 1998. Evaluation overview of the Cache River and the Black Swamp in Arkansas. Fina l Report on Contract #DACW39-94-K0300 Energy Systems Perspectives for Cumulative Impacts Assessment between Waterways Experiment Station, U.S. De pt. of the Army, Vicksburg, Miss. and University of Florida. Center fo r Environmental Policy, Environmental Engineering Sciences, University of Florida, Gainesville. 128 p. Orrell, J.J. 1998. Cross scale comparison of plant production a nd diversity. Masters Thesis, University of Florida, Gainesville. Ortega, E., J.F. Queiroz, C.E. Boyd, and J.M.G. Ferraz. 2000. Emergy analysis of channel catfish farming in Alabama, US A. Pages 171-180 in M. T. Brown (Ed.). Emergy synthesis: theory and applications of the emergy methodology. The Center for Environmental Policy, Department of Environmental Engineering Sciences, University of Florida, Gainesville. Pimentel, D.C. 1980. Handbook of energy utiliza tion in agriculture. CRC Press, Boca Raton, FL. Pimentel, D.C. Harvey, P. Resosudarmo, K. Si nclair, D. Kurz, M. McNair, S. Crist, L. Shpritz, L. Fitton, R. Saffouri, and R. Blair. 1995. Environmental and economic costs of soil erosion and conser vation benefits. Science 267:1117-1123. Rainey, R.L., H. Hauk, and J.D. Speight 2005. Estimating 2005 Costs of production: Northwest Arkansas Bermuda round bales. AG-847. Cooperative Extension Service, Division of Agriculture, Univ ersity of Arkansas. Available at http://www.uaex.edu/Other_Areas/pub lications/HTML/FSA-2013.asp. Accessed 07/2005. Robbins, P., and T. Birkenholtz. 2003. Turfgra ss revolution: measuri ng the expansion of the American lawn. Land Use Policy 20:181-194. Robinson, E.H., and M.H. Li. 1996. A practical guide to nutrition, feed s, and feeding of catfish. Bulletin 1041, Mississippi Agricultur al and Forestry Experiment Station, Mississippi State University. Available at http://msucares.com/pubs/bulletins/b1041.htm. Accessed 06/05.

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Areal Empower Density and Landscape Development Intensity (LDI) Indices for Wetlands of the Bayou Meto Watershed, Arkansas
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Permanent Link: http://ufdc.ufl.edu/AA00004016/00001
 Material Information
Title: Areal Empower Density and Landscape Development Intensity (LDI) Indices for Wetlands of the Bayou Meto Watershed, Arkansas
Physical Description: Report
Language: English
Creator: Vivas, Manuel Benjamin
Brown, Mark T.
Publisher: Center for Wetlands
Publication Date: 2006
 Subjects
Subjects / Keywords: landscape development intensity (LDI)
emergy
disturbance
land use
watersheds
spatial modeling
Spatial Coverage: United States -- Arkansas -- Arkansas -- Bayou Meto -- Bayou Meto Watershed
Coordinates: 34.22 x -91.52
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General Note: 160 Pages
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Areal Empower Density and Landscape Development Intensity (LDI) Indices
for Wetlands of the Bayou Meto Watershed, Arkansas











Report Submitted to
the Arkansas Soil and Water Conservation Commission
Under the Sub-grant Agreement SGA 104









by

M. Benjamin Vivas
and
Mark T. Brown


Howard T. Odum Center for Wetlands
University of Florida
Gainesville, Florida 32611-6350


October 2006















ACKNOWLEDGMENTS

This study was supported through a sub-grant agreement (SGA 104) between the

Arkansas Soil and Water Conservation Commission (ASWCC) and the University of

Florida's Howard T. Odum Center for Wetlands (UF-CFW). The ASWCC was the

recipient of a grant from the United States Environmental Protection Agency (Grant #

AW9761901) used in the implementation of the project. Dr. Mark T. Brown was

principal investigator. Staff from the Arkansas Multi Agency Wetland Planning Team

(MAWPT) provided support for this research; particularly Elizabeth 0. Murray,

Coordinator of the MAWPT, who provided technical and logistical support in the field,

reviewed partial results, made recommendations to improve project performance, and

supplied spatial and field data that were critical for the completion of the project.

Acknowledgment is due to Tom Foti from the Arkansas Natural Heritage

Commission (ANHC) for his assistance in selecting the wetland study sites. Hans

Haustein, GIS Planner from Metroplan provided zoning data for three urban areas in the

study area. Mauricio Arias from the UF-CFW provided assistance in GIS analysis.
















TABLE OF CONTENTS

Page

A C K N O W L E D G E M E N T S ................................................................................................ ii

L IST O F T A B L E S .............. ................................................... ............... v...... .. .... .v

LIST OF FIGURES .................................................. ............................ vi

EXECU TIVE SUM M ARY ... ................................................................. .............. vii

CHAPTER

1 INTRODUCTION AND OVERVIEW..........................................................1...

Previous Studies Using Landscape Development Intensity.............................. 3
P project O verview ................ . .............. .............................................. . 5

2 M E T H O D S ........................................................................... .. . . . . . .. ...............8

Stu dy A rea .............. ................................................ ................... . . . . . .... 8
T he State of A rkansas ..................................... ..................... ...............8...
The B ayou M eto W atershed ................................................... ...............8...
Emergy Evaluations of Arkansas and Land Uses in the Bayou Meto
W atershed ........................................ ................... ... ... ............... 10
Land U se A real Em pow er D ensities........................................... ............... 10
Land Use / Land Cover (LU/LC) Data................................. ............... 10
Definition of Land Use Categories: aggregations and disaggregations.....11
A real E m pow er D ensities ..................................................... ............... 14
LDI Index for Study Wetlands at Four Spatial Scales............................... 16
Selection of W wetlands Sites .................................................. ............... 16
Spatial A reas of Influence..................................................... ............... 16
D elineation of D rainage B asins .................................................. 17
Landscape Development Intensity Index........................... ................... 20
Analysis of Relationships between the LDI and Wetland Condition ........21

3 R E S U L T S ........................................................................................................... 2 3

Land Use / Land Cover of the Bayou Meto Watershed...............................23
Emergy Evaluation of Selected Land Uses................................. ................ 23
LD I and W etland C ondition........................................................ ................ 27









LD I Scores for Study W wetlands ............................................ ................ 27
Wetland Condition Indices for Wetland Study Sites...............................31
Relationships between the LDI and Measurements of Wetland Condition..... 31

4 SUMMARY AND DISCUSSION ................................................................40

Land U se Land Cover D ata Sources........................................... ................ 42
Areal Empower Densities for Land Uses ...................................................44
A Landscape Assessment of Wetland Ecological Condition........................45
C o n c lu sio n s ..................................................................................................... . 4 6

L IST O F R E FE R E N C E S ...................................................................................... 48

APPENDIX

EMERGY EVALUATIONS OF THE STATE OF ARKANSAS AND LAND
USES OF THE BAYOU METO WATERSHED........................................... A-i

Introduction ..................................................... . ..... .............. A-i
Em ergy and Em ergy A analysis ............................................... ................. A -1
Background of Previous Studies using Emergy..................... ................... A-6
M e th o d s...................................................................................................... ... A -7
Energy System Diagramming ....... ........ ...................... A-7
Em ergy Tables ............................................................................. ................ A -8
D ata S o u rce s .................................................. ............................ ................ A -10
R results ................................................................................................... A -11
Em ergy Evaluation of Arkansas ............................................................ A-11
Emergy Evaluation of Resource Basis for the State of Arkansas ........ A-28
Emergy Evaluation of Land Uses of the Bayou Meto Watershed ......... A-30

List of R eferences . ............................................................ .............. A -94















LIST OF TABLES


Table Page

2-1 Level 2 category codes and labels for the 1999 AR-LU/LC coverage ..............12
2-2 Development intensity land use categories and definitions............................... 15
2-3 Summary information for the Bayou Meto Watershed forested wetlands
stu d y ................. ..... .... . .. .. ........................ .... ... ........................................ .... 1 8
3-1 Areal empower density for land use classes in the Bayou Meto Watershed .........25
3-2 Non-renewable and purchased areal empower density and LDI index scores
for 29 forested floodplain wetlands. .................... ...... ................ 29
3-3 Summary of LDIs and wetland condition indices for a priori classes ...............31
3-4 Final scores for three measurements of wetland condition for the sample
fl oodplain w wetlands ............................................. ........... .. .. .. .. .... .... ................ 33
3-5 Spearman's correlations (r) between the LDI and measurements of wetland
condition for the sample floodplain wetlands calculated at four different
sp atia l sc ale s........................................................................................................... 3 4














LIST OF FIGURES
Figure Page

2-1 Location of the Bayou Meto Watershed, Arkansas ...........................................9...
2-2 Approximate location of the Bayou Meto watershed forested wetland
stu d y site s............... ......... ................. . ...... . ...... ... ...... ............ ........... . . . . 17
2-3 Landscape scales used to calculate LDI values for the study wetlands.............. 19
3-1 Base map of LU/LC classes for the BMW used to identify functional
L D I-L U /L C classes ........................ . ...... .... .... .. .... .... .... ....................... 24
3-2 Non-renewable and purchased areal empower density for the Bayou Meto
Watershed ................ .. ........ . ........................................ 26
3-3 Scatter plots of study wetland LDI indices at various scales ................................30
3-4 Scatterplots showing the relationship between the LDI and the WRAP for
four different spatial scales ................... ........................................................... 35
3-5a Scatterplots showing the relationship between the LDI and the HGM
hydrological category for four different spatial scales ..........................................36
3-5b Scatterplots showing the relationship between the LDI and the HGM
biogeochemical category for four different spatial scales ...................................37
3-5c Scatterplots showing the relationship between the LDI and the HGM
biogeochemical category for four different spatial scales .....................................38
3-6 Scatterplots showing the relationship between the LDI and the UMAM for
four different spatial scales ....................................................................................39














Areal Empower Density and Landscape Development Intensity (LDI) Indices
for Wetlands of the Bayou Meto Watershed, Arkansas

EXECUTIVE SUMMARY


A primary goal of United States Environmental Protection Agency's National

Wetland Program is to report on the ecological condition of the wetlands in the nation

(USEPA 2003). A successful wetland monitoring program might include landscape-level

assessments (Level 1), rapid assessments through on-the-ground surveys (Level 2), and

intensive field surveys (Brooks et al. 2004, Fenessy et al. 2004). Level 1 assessment

methods are designed to provide information on the condition of wetlands relying on

remote-sensing imagery and Geographic Information Systems (GIS). These may include

information from the National Wetlands Inventory (NWI), synoptic assessments (Brooks

et al. 2004), and various indices of landscape disturbance. The Landscape Development

Intensity (LDI) index (Brown and Vivas 2005) is an example of a Level 1 assessment

method. It is a measure of human activity based on a development intensity measure that

is derived from non-renewable energy use in the surrounding landscape. The LDI index

has been used to predict ecosystem condition based on the intensity of human activities in

the surrounding landscape and under the premise that ecological communities are

affected by the direct, secondary, and cumulative impacts in the surrounding landscape

(Brown and Vivas 2005).

The first objective of this research was to compute areal empower densities for land

use classes of the Bayou Meto Watershed (BMW) in Arkansas, using existing land









use/land cover (LU/LC) data. Areal empower density was computed for a total of 20 land

use types using a modified version of the method originally proposed by Brown and

Vivas (2005). Values for the non-renewable and purchased areal empower density varied

for land use types between 5.75 E15 sej/ha/yr for open space/recreational lands and

6289.55 E15 sej/ha/yr for high-density multiple residential areas. The average areal

empower density for the BMW was 61.47 E15 sej/ha/yr. The largest areal empower

densities occurred in the urban areas in the northern portion of the watershed. The middle

and southern portions of the BMW were dominated by intermediate areal empower

densities that characterize agricultural lands. In general, non-renewable and purchased

areal empower density values for land uses in Arkansas were in agreement with those

reported elsewhere (Odum et al. 1998) and Florida (Brandt-Williams 2001, Brown and

Vivas 2005).

A second objective of this study was to calculate LDI scores for floodplain forested

wetlands in the BMW. A total of 29 wetlands were investigated, and were selected from

within various landscape settings including natural, agricultural, and urban land uses. The

a priori selection of wetlands provided a range of landscapes that represented a gradient

from undeveloped to highly developed lands. Wetlands within natural landscapes (n =

12), generally exhibit non-renewable and purchased areal empower densities of 0.00

sej/ha/yr to 3.00 E15 sej/ha/yr, which are characteristic of natural lands. For wetlands

within agricultural landscapes (n = 9), empower density values ranged between 7.40 E15

sej/ha /yr and 26.71 E15 sej/ha /yr. Wetlands within urban landscapes (n = 8) were

characterized by areal empower density values between 342.80 E15 sej/ha /yr and

1910.85 E15 sej/ha/yr.









The final objective was to correlate the LDI scores with three independent

measures of wetlands condition: the Wetland Rapid Assessment Procedure (WRAP) used

in South Florida, Hydrogeomorphic Functional Capacity Indices (HGM), and the Florida

Department of Environmental Regulation's Uniform Mitigation Assessment Method

(UMAM). Correlation between the LDI and the WRAP was highly significant, especially

when the LDI was estimated for an area of 300 meters around the wetland study plots

(Spearman's r = -0.81). The strongest correlation between the LDI and the HGM was

reported for the habitat index and also for the 300-meter area immediately surrounding

the study plots (Spearman's r = -0.73). The UMAM had the weakest correlation with the

LDI (Spearman's r = -0.50), with very similar results for all four landscape scales

considered.

The main findings of this research, which constitute a contribution to the

development of a landscape procedure for the assessment of wetland ecologic condition

in the BMW, can be summarized in three main points:

1. Since the existing LU/LC coverages for the BMW (and for the state of

Arkansas) were developed with different goals in mind than those for this

research, identifying a set of LU/LC classes that satisfies the requirements for

the calculation of areal empower densities may require extensive spatial data

manipulation to identify functional LDI classes. To that end, we are providing a

set of 20 LDI classes with their corresponding non-renewable and purchased

areal empower density values that may be used in other regions within

Arkansas for similar studies.









2. The LDI index showed fair to good correlations with three multivariate

independent measures of ecosystem condition for wetlands, confirming the

validity and usefulness of the LDI.

3. Correlations between the LDI and the WRAP and between the hydrological and

habitat categories of the HGM were highest when the LDI was calculated for

the area immediately surrounding wetland study plots, initially suggesting that a

landscape assessment of wetlands condition using the LDI may only need to

consider the impact caused by the nearest land uses over other more distant land

uses.














CHAPTER 1
INTRODUCTION AND OVERVIEW

The United States Environmental Protection Agency (USEPA) has recognized

three categories of wetland assessment procedures that can be used to assess the

ecological condition of wetlands. The criteria for the three different assessment levels are

determined based on the scale and intensity of the assessment method, ranging from

landscape-scale computer-based analyses to intensive field sampling of biological,

physical, and chemical measures. The three procedures are described as Landscape Scale

Assessment (Level 1), Rapid Field Methods (Level 2), and Intensive Biological and

Physico-Chemical Measures (Level 3) (Fennessy et al. 2004).

The assessment of the ecological condition of wetlands based on the landscape

approach is usually carried out using a Geographic Information System (GIS) and remote

sensing data. It may also include the use of various indices of landscape composition and

configuration and indices of landscape development intensity. The Landscape

Development Intensity (LDI) index (Brown and Vivas 2005) is an example of a Level 1

assessment method. The LDI index (referred to as "LDI") is a measure of human activity

based on a development intensity measure that is derived from non-renewable energy use

in the surrounding landscape. The LDI has been used to predict ecosystem condition

based on the intensity of human activities in the surrounding landscape and under the

premise that ecological communities are affected by the direct, secondary, and

cumulative impacts in the surrounding landscape (Brown and Vivas 2005). Examples of









the application of the LDI are Lane (2003), Fore (2004; 2005), Reiss (2004; 2006), Reiss

and Brown (2005), Surdick (2005), and Mack (2006).

The metric used in the LDI to quantify human activity is emergy use per unit area

per time (or areal empower density). Emergy is an expression of all of the energy used in

the work processes that generate a product or service, in units of one type of energy. The

solar emergy of a product is the emergy of the product expressed in equivalent solar

energy required to generate it (Odum 1996). The units of emergy are emjoules (for

emergy joules) and the units of solar emergy are solar emjoules (abbreviated sej). Areal

empower density (usually expressed as solar emergy per hectare per year [sej/ha/yr]) is

calculated as average values for land use categories. Since the LDI is a measure of human

activity, non-renewable energies are the primary source of areal empower density used in

the calculation of the index. The LDI scale encompasses a gradient from undeveloped to

highly developed land use intensity. Landscapes dominated by more intense activities

such as commercial, industrial, and multi-family residential land uses receive higher LDI

scores. Less developed lands and rural areas dominated by areas of forests, wetlands, and

open lands receive a lower LDI score. The LDI score does not account for any individual

causal agents directly, but instead represents the combined actions of air and water

pollutants, physical damage, changes in the suite of environmental conditions (e.g.,

groundwater levels and increased flooding), or a combination of such factors, all of

which enter the natural ecological system from the surrounding developed landscape

(Brown and Vivas 2005).









Previous Studies Using Landscape Development Intensity

Emergy flows are organized hierarchically into spatial patterns with emergy flows

per area more concentrated in hierarchical centers such as cities (Brown 1980; Odum

1996). Based on this observation, Brown and Vivas (2005) suggested that the impacts of

human activities might be related spatially to the intensity of energy use and that areal

empower density might serve as a measure of the level of human-induced impacts on

ecological systems. Using land use data and areal empower density for land uses in

Florida, Brown and Vivas (2005) computed LDI indices for watersheds and related them

to water quality data and measures of wetland condition.

Parker (1998) used preliminary versions of the LDI based on physical and emergy

measurements to correlate them with model results from a spatial pollutant model for

total phosphorus (TP) for sub-watersheds of the St. Marks Watershed in Northern

Florida. The LDIs showed a good amount of association with the TP loads above

background levels, particularly an imperviousness LDI and the empower density LDIs.

This study showed that despite the fact that predicting TP loads at low-development

intensities are difficult, at higher levels of human development the LDI in its various

forms may be a good predictor of nutrients accumulation that can result from more

intense human activities.

Cohen et al. (2004) used the LDI calculated by Brown and Vivas (2005) as a

measure against which an expert-based floristic quality assessment index (FQAI) could

be compared and provide evidence of its importance in the assessment of the ecological

condition of small isolated herbaceous wetland systems. Strong associations between the

LDI and the FQAI provided evidence of the relevance of the floristic index for biological

assessment studies and the LDI as a measure of the human disturbance gradient.









Using the LDI, Lane (2003) developed three indices as quantitative measures of

biological integrity based on measurable attributes of diatoms, macrophytes, and

macroinvertebrates for isolated herbaceous depressional wetlands in Florida. Similarly,

Reiss (2004) developed a Wetland Condition Index (WCI) using measurable metrics for

the same groups of organisms for isolated forested wetlands in Florida; Reiss and Brown

(2005) developed a Florida Wetland Condition Index (FWCI) for forested strand and

floodplain wetlands. In all three cases the LDI was used as the human disturbance

gradient along which the change in the composition of biological communities of

wetlands were evaluated. Fore (2004, 2005) used modified versions of the LDI to assess

the biological condition of streams and lakes in Florida.

Surdick (2005) analyzed how human land uses of varying intensities surrounding

isolated forested wetlands in Florida affect the species composition of birds and

amphibians. A strong relationship between land use intensity and amphibian and avian

species composition was found. Differences between species composition in less

developed landscapes and highly developed landscapes were significant, following a

gradient of increasing dissimilarity from undeveloped lands to silviculture, agriculture,

and urban land uses, respectively. Surdick (2005) pointed out the relevance of the LDI for

ecological studies involving changes along a disturbance gradient.

Mack (2006) tested the robustness of the LDI as a wetland condition assessment

procedure using a large reference wetland data set in Ohio. The LDI was significantly

correlated with the Ohio Rapid Assessment Method for Wetlands (ORAM), an

independent measure of the human disturbance gradient. The LDI was also correlated

with Ohio's Vegetation Index of Biotic Integrity (VIBI), a multi-metric index of wetland









integrity. The most significant relationships were found between the LDI and metrics

from emergent wetlands, followed by forested wetlands, and shrub wetlands. Mack

(2006) emphasized the robustness of the LDI as a measure of the human disturbance

gradient given its theoretical foundations and quantitative nature.


Project Overview

Overall, there were three inter-related objectives of this study: 1) develop areal

empower density values for land use classes based on existing LU/LC coverages of the

BMW; 2) compute LDI values at four different spatial scales for 29 floodplain forested

wetlands chosen by the Arkansas Soil and Water Conservation Commission for which

three field based measures of "ecosystem integrity" or wetland condition had been

quantified; and 3) statistically determine if the LDI can be used as a predictor of wetland

condition.

Energy systems diagrams, and concepts and methods of the environmental

accounting methodology developed by H. T. Odum and colleagues at the University of

Florida's Center for Environmental Policy (UF-CEP) were used to satisfy the first

objective as the basis for calculating the areal empower density for land use types. To

accomplish this objective it was first necessary to evaluate the emergy flows for Arkansas

in order to apportion emergy to individual land use types. An emergy evaluation of

Arkansas developed earlier by Odum et al. (1998) for 1990 was updated, and the

resulting energy resource basis for the state was described (this analysis is presented in an

appendix to this report). Next, LU/LC classification schemes of existing coverages were

reviewed to determine their utility for calculating areal empower densities and

recommendations were made for aggregating and disaggregating LU/LC categories to









improve the functionality of classes. Once LU/LC classes were determined, systems

diagrams were developed for 20 LU/LC classes. These classes served as an inventory

guide for collecting material and energy flow data from a variety of sources including

federal, state, and local agencies. Data on energy and material flow were used to develop

emergy tables to compute areal empower density. The areal empower density of the non-

renewable and purchased inputs was then used to derive LDI scores for individual

wetland study plots.

The second objective was to compute LDI values at four landscape scales for a set

of study wetlands in the BMW (n = 29). The four scales are called Levels of analysis and

correspond to the following: Level 1- the entire upstream watershed of the study wetland

plot, Level 2a - a 300-meter buffer of contiguous upstream wetlands, Level 2b - a 100-

meter buffer of contiguous upstream wetlands, and Level 3 - a 300-meter buffer around

the wetland study plot. To accomplish this objective, wetland study sites were sought in

three a priori landscape settings: natural, agricultural, and urban. This selection allowed a

range of landscapes that represented a gradient from undeveloped to highly developed

land use intensity. Final LDI values for each wetland were computed using a GIS and

based on the average areal empower density for land uses within each of the three

landscape scales.

To accomplish the final objective, correlations between the LDI computed for

wetland study plots and independent measures of wetlands condition were explored. The

indices used were: a Wetland Rapid Assessment Procedure (WRAP) developed and used

in South Florida, the Florida Department of Environmental Regulation's Uniform

Mitigation Assessment Method (UMAM), and the Hydrogeomorphic Functional






7


Capacity Index (HGM). The indices were field-calculated by a research team of the

Arkansas Multi Agency Wetland Planning Team (MAWPT) and scores were supplied to

the UF team.














CHAPTER 2
METHODS

This chapter presents the steps followed in the computation of areal empower

density for the different land use types and then LDI scores for each of the study wetlands

of the Bayou Meto Watershed (BMW), Arkansas. First a brief description of the study

area is given, followed by detailed methods for evaluation of land uses, computation of

areal empower density for land uses, application of LDI values to the study wetlands, and

finally analysis of relationships between LDI and wetland condition.


Study Area

The State of Arkansas

Arkansas is located in the southern/central U.S. and includes as its major

geographic features the Ozark mountain highlands to the northwest, the Ouachita

Mountains to the south, and the Mississippi River alluvial plain to the east. The latter

includes the floodplain and old channels of the Mississippi River, as well as a complex

web of streams, tributaries, and artificial drainage ditches and canals. The Mississippi

River valley is a fertile agricultural area and is home to most of the crop agriculture in the

state.

The Bayou Meto Watershed

The BMW is located in eastern Arkansas between the Arkansas River and the

White River (Figure 2-1) and almost wholly within the Mississippi Alluvial Plain. The

BMW flows southeast and is part of the Arkansas River watershed. The land forms

within the BMW include backswamps, natural levees and meander belts, oxbow lakes or









cutoffs, and terraces (MAWPT, unpublished report available at

http://www.mawpt.org/products.asp). Except for the northern portion of the BMW that

lies within the Ouachita Mountains ecoregion (Level III, according to Omermik's

classification1), most of the BMW is contained within the Mississippi Alluvial Plain

ecoregion (Level III) with a rather flat topography. The eastern portion of the BMW is

within the Grand Prairie sub-ecoregion (Level IV), which lies between 6 to 12 meters

above the Bayou Meto floodplains. Most of the wetlands under investigation in this study

were located within the Grand Prairie sub-ecoregion.


Figure 2-1. Location of the Bayou Meto Watershed, Arkansas.


1 Omernik, J.M. 1987. Ecoregions of the conterminous United States. Map (scale
1:7,500,000). Annals of the Association of American Geographers 77(1): 118-125.









Once rich in forests and wetlands, agriculture is currently the predominant land use

within the BMW. Only 25% of the BMW is forested and it is estimated that from 1950 to

1990 approximately 50% of the natural wetlands present in the BMW were lost to land

development (Arkansas MAWPT, unpublished report available at

http://www.mawpt.org/products.asp). Urban land uses account for only 3% of the total

landscape.


Emergy Evaluations of Arkansas and Land Uses in the Bayou Meto Watershed

The emergy evaluations of the state of Arkansas and of land use types within the

BMW were performed following the principles and procedures of the emergy analysis

methodology. The emergy analysis methodology consists of three general steps: (1)

development of energy systems diagrams for the system of interest, (2) development of

emergy tables, and (3) calculation of emergy indices that describe the system and its

potential. Detailed methods for the evaluations are given in the Appendix.


Land Use Areal Empower Densities

Land Use / Land Cover (LU/LC) Data

A 1999 Arkansas LU/LC: Summer (1999 AR-LU/LC) GIS coverage, developed by

the Center for Advance Spatial Technologies (2001) was used to identify the main land

uses present in the BMW. The 1999 AR-LU/LC coverage is available through GeoStor, a

web-based database containing all publicly available geodata for the state of Arkansas

and available at http://www.cast.uark.edu/cast/geostor/. This coverage is the most recent

state-wide LU/LC data set available for Arkansas and the study area. It was derived from

Landsat TM 5 scenes and ground-truth information with a 30 x 30-meter cell resolution.









The 1999 AR-LU/LC coverage has a hierarchical system of categories with two

levels ranging from general to specific. Level 1 consists of six classes (urban, barren,

water, forests, agricultural, and herbaceous lands) which are further subdivided into finer

detail (Level 2) with a total of 46 classes. Level 2 categories were used as the basis for

identifying the land uses for which areal empower densities coefficients were calculated,

and were included in the development of LDI values for the watersheds of the study

wetlands. Level 2 category codes and labels for the 1999 AR-LU/LC coverage are

summarized in Table 2-1.

Definition of Land Use Categories: aggregations and disaggregations

The 1999 AR-LU/LC coverage emphasizes agricultural land uses and forest

classes, with only general descriptions provided for urban land uses and surface water

cover. As a result of the uneven description of land uses in the coverage, it was necessary

to aggregate some categories and disaggregate others to fit the requirements needed for

LDI calculations. Aggregation was easily accomplished; however, disaggregation

required the use of aerial photo interpretation and the construction of new coverages.

New coverages were then merged to the 1999 AR-LU/LC to obtain a final LU/LC

coverage that allowed describing LDI-LU/LC categories and performing LDI

calculations.

The 1999 AR-LU/LC focuses primarily on agricultural land uses. It also includes

forest categories that were initially developed by the 1992 Arkansas Gap Project, which

had among its objectives mapping the distribution of vegetation types in the state. Water

systems and urban lands were only generally classified in the 1999 AR-LU/LC. Since this

research emphasized defining human disturbance as measured by areal empower density













Table 2-1. Level 2 category codes and labels for the
CAST 2001).


1999 AR-LU/LC coverage (after


LULC LULC Label LULC LULC Label
Code Code


Urban Level 1
Urban Level 2
Urban Level 3
Urban Other (Park, Golf Course,
Cemetery, etc.)
Major Roads
Railroads
Airports/Landing Strips
Barren Land (Sand Bars/Mining
Operations/Exposed Rock)
Perennial Water
Flooded
Forest 1
Forest 2
Forest 3
Forest 4
Forest 5
Forest 6
Forest 7
Forest 8
Forest 9
Forest 10
Forest 11
Forest 12
Forest 13


Forest 14
Forest 15
Forest 16
Forest 17


Forest 18
Forest 19
Forest 20
Forest 21


Forest 22
Forest 23
Forest 24
Forest 25
Forest 26
Forest 27
Forest 28
Soybeans
Rice
Cotton
Wheat/Oats
Sorghum/Corn
Bare Soil/Seedbed/Fallow
Warm Season Pasture
Cool Season Pasture


* Forest categories (101-128) were originally labeled with the name of specific
species given after the 1992 Arkansas Gap Project.



primarily from urban and agricultural land uses, all of the forest classes on the 1999 AR-

LU/LC coverage were aggregated into two categories: upland forests and wetlands.


41
42
101*
102
103
104
105
106
107
108
109
110
111
112
113









The 1999 AR-LU/LC coverage had only two categories for describing the surface

waters in the BMW: Perennial Waters and Flooded with codes 41 and 42, respectively.

These were disaggregated to distinguish between the different freshwater ecosystems

present in the study area, and to identify land uses such as managed ponds and

dike/impounded waters systems. A new spatial layer, available through Geostor, was

created based on spatial data for rivers/streams, lakes, and wetlands, and merged with the

1999 AR-LU/LC coverage to provide more detail regarding the surface waters within the

BMW. After these changes, undefined water areas remained. A visual identification of

these areas using aerial photographs showed that these areas most likely correspond to

rice fields and managed ponds (aquaculture). As a result, a new land use category was

created that combined aspects of both land uses.

Urban land use categories from the 1999 AR-LU/LC coverage were disaggregated

by photo interpretation of aerial photographs in combination with vector GIS coverages

for selected urban areas in the BMW provided by Metroplan, Arkansas. Urban lands were

defined in the 1999 Arkansas LU/LC: Summer data set as three general classes labeled

Urban 1, Urban 2, and Urban 3. These were reclassified to eight classes that distinguished

between residential, commercial, and industrial areas. Residential areas were

disaggregated into five categories that account for the different housing densities that

might be present in an urban landscape. To determine housing densities for residential

areas, houses were counted within one-hectare plots laid on aerial photos. This was done

only for delineated sub-basins within the BMW. Commercial areas were disaggregated

into two categories that distinguish between commercial strips and community shopping

centers. Industrial areas were included in only one category. Institutional land uses such









as public buildings, schools, and churches were assumed to be equivalent to commercial

strips in terms of their level of energy usage and were assigned to the same land use

category. Urban areas such as city parks, playgrounds, golf courses, and urban lands that

have been cleared and prepared for construction and/or development were assigned to a

unique category. Urban areas were completed by adding a data layer for roads (interstates

and U.S. highways) and obtained from Geostor.

The resulting LU/LC categories were reclassified using functional LDI-LU/LC

classes. The land use category 208 (bare soil/seedbed/fallow) from the 1999 AR-LU/LC

coverage was not considered since it was only present in the northern portion of the

BMW and only accounted for approximately 24.3 hectares. Land use categories 23

(airports/landing strips) and 204 (wheat/oats) were also not considered since the 1999 Ar-

LU/LC: Summer coverage reported no such land use for the BMW. Definitions for the

LDI-LU/LC classes are given in Table 2-2.

Areal Empower Densities

Detailed analyses for each LU/LC category were undertaken using data from the

literature and the evaluation of the state of Arkansas (see Appendix). A look-up table was

developed for each LU/LC category then the LDI-LU/LC coverage was reclassified

assigning areal empower densities to each land use type. The result was an LDI-emPower

coverage where each land use category was assigned its appropriate areal empower

density.










Table 2-2. Development intensity land use categories and definitions.
Land Use LULC* Definition


Forests
Wetlands
Open Water
Hay Crop



Soybeans
Rice
Cotton
Sorghum/Corn
Aquaculture


Rice/Aquaculture
Open Space/Recreational







Low Intensity Single Family
Residential
Medium Intensity Single
Family Residential
High Intensity Single Family
Residential
Low Intensity Multi-family
Residential
High Intensity Multi-family
Residential
Low Intensity
Commercial/Institutional

High Intensity Commercial

Industrial



Low Intensity Transportation
High Intensity Transportation


Code
101-128 Upland forests with low manipulations.
101-128 Forested wetlands with low manipulations.
41, 42 Lakes, ponds, and streams with low manipulations.
209-210 Areas devoted to the production of hay. Also applies to pasture
lands (without livestock), which are defined as areas where the
natural vegetation has been altered by drainage, irrigation, etc., for
the grazing of domestic animals.
201 Areas devoted to the production of soybeans.
202 Areas devoted to the production rice.
203 Areas devoted to the production cotton.
205 Areas devoted to the production of sorghum/corn.
41 Fish farms. Can also apply to high-intensity agriculture land uses
such as dairy farms and large-scale cattle feed lots, chicken farms,
and hog farms, if present.
41, 202 Undefined agricultural areas. Average of rice and aquaculture.
14, 31, 41 Areas with grassy lawns in urban landscapes including recreational
lands such as playgrounds, ball fields, and golf courses. Also
applies to land that has been cleared and prepared for construction
and/or development, dirt roads, barren land, and open areas
surrounding by paved roads and power lines. Includes human-
created water bodies (retention ponds, canals, reservoirs, etc.)
other than for aquaculture.
11 Areas that are predominantly residential units with a density less
than 5 units/ha.
11 Areas that are predominantly residential units with a density
between 5 and 10 units/ha.
11 Areas that are predominantly residential units with a density of
more than 10 units/ha.
11 Areas that are predominantly multi-family residential units such as
condominiums and apartment buildings up to 2 stories.
11 Areas that are predominantly multi-family residential units such as
condominiums and apartment buildings with 3 or more stories.
12-13 Commercial strips with associated storage buildings and parking
lots. Schools, universities, religious, military, medical and
professional facilities, and government buildings.
12-13 Community shopping center with associated storage buildings and
parking lots.
12,13, 31 Land uses include manufacturing, assembly or processing of
materials/products and associated buildings and grounds. Also
includes extractive areas and mining operations, water supply
plants, and solid waste disposal.
21-22 Paved road with no more than 2 lanes, and railroads.
21 Paved road with more than 2 lanes, railroad terminals, bus and
truck terminals, and large auto parking facilities when not directly
related to other land uses.


* Level 2 category codes for the 1999 Arkansas Land-use/Land-cover: Summer.









LDI Index for Study Wetlands at Four Spatial Scales

Selection of Wetlands Sites

Study sites were selected with the aid of aerial photography and through a joint

field visit made by the UF team and the Arkansas MAWPT in August 2005. The

locations of the wetland study plots were determined in the field by the MAWPT staff

using a Global Positioning System (GPS). The location of the wetland sites (n = 29) is

shown in Figure 2-2 and is indicated by generalized a priori land use categories

(reference, rural, and urban). Hereafter wetlands embedded in primarily undeveloped

landscapes are called reference wetlands; wetlands embedded in primarily agricultural

land uses are called rural wetlands; and wetlands embedded in primarily urban land uses

are called urban wetlands. Information on each site is summarized in Table 2-3.

Spatial Areas of Influence

LDI indices for each study wetland were computed at four different spatial areas of

influence (see Figure 2-3): 1) the drainage basin or total watershed upstream from the

wetland study plots, 2) a 300-meter buffer around the riparian zone immediately upstream

of the study wetland, 3) a 100-meter buffer around the riparian zone immediately upstream

of the study wetland, and 4) a 300-meter buffer surrounding and immediately adjacent to

the study wetland. Upstream riparian systems that were connected to the study wetlands

were delineated using aerial photographs and GIS coverages. The buffer areas for riparian

systems and buffer areas around each study wetland were delineated using buffer command

in ArcView GIS 3.2 (Environmental Systems Research Institute, Inc. 1999).















Bayou Meto Watershed


Location of Sample Wetlands

0 Reference

A Rural
* Urban

Ecoregions

Arkans as/Outchita River B ack swamps

Arkans as/Outchita River H oloc ene Meander B elt

Fourche Mountains

Grand Prairie


N
0 6 12 Kilometers
E!!�� A


Figure 2-2. Approximate location of the Bayou Meto watershed forested wetland study
sites.

Delineation of Drainage Basins

The areas draining to the locations where forested wetlands of the flood zone of the

BMW and its tributaries were sampled, as well as the stream networks within the

drainage areas, were determined using the Better Assessment Science Integrating Point

and Nonpoint Sources 3.0 (BASINS 3.0) environmental analysis system. The BASINS

computer program was developed by the Office of Water of the USEPA to support


0










Table 2-3. Summary information for the Bayou Meto Watershed forested wetlands study.
Site Size of Watershed # of Sampling
Number Site Name Type* (ha) Plots

1 Fina Woods Urban 437.1 1
2 Old Highway 69 Woods Reference 3284.3 2
3 Church Woods Urban 14.5 1
4 Strip Mall Woods Urban 49.2 2
5 Cabot Park Woods Urban 45.7 1
6 Gander Mtn. Sporting Goods Urban 1721.7 2
7 Manson Rd. Woods Urban 66.5 1
8 Harvest Foods Woods Urban 45.0 1
9 Jacksonville Ball Field Urban 221.7 3
10 Gentry Rd West Rural 188.7 2
11 Gentry Rd East Rural 530.1 1
12 Fairview Rural 400.7 2
13 Winrock Hwy 13 West Rural 154.2 1
14 Winrock Hwy 13 East Rural 109.7 1
15 Winrock CR 923 East Reference 2790.1 2
16 Winrock CR 923 West Rural 2728.0 2
17 Merlin Mission Rural 46.3 3
18 Winrock CR 915 East B Reference 41.8 1
19 Winrock CR 915 East C (beaver) Reference 105.2 1
20 Winrock CR 915 West Rural 910.0 3
21 1-40 Woods Reference 1386.2 3
22 North Holland Bottoms 1 Reference 28.3 2
23 North Holland Bottoms 2 Reference 8.0 4
24 North Holland Bottoms 3 Reference 5.9 1
25 Prairie Bayou WMA 1 Rural 21.8 1
26 Prairie Bayou WMA 2 Reference 30.2 2
27 Prairie Bayou WMA 3 Reference 171.4 1
28 Lower Holland Bottoms 1 Reference 109.1 2
29 Lower Holland Bottoms 2 Reference 39.2 2
*Wetlands were classified as reference, rural, or urban if they were embedded in primarily undeveloped
landscapes, embedded in primarily agricultural land uses, or embedded in primarily urban land uses, respectively.



environmental and ecological studies at the watershed level (USEPA 2001). The

assessment tools used in the BASINS system are integrated into the GIS software

ArcView 3.2 (ESRI �1992-1999), the computer program used for the spatial analyses


performed during this study.






19



Watershed Boundary\ --



Riparian Wetlands /



Stream A








/ Wetland Study Plot



Contiguous Wetland /' -





LEVEL 2a


\ y x LEVEL 2b

LEVEL 3

Wetland Study Plot



Figure 2-3. Landscape scales used to calculate LDI values for the study wetlands.
LEVEL 1: watershed upstream of wetland study plot; LEVEL 2a: a 300-meter
buffer around the riparian zone immediately upstream of the study wetland;
LEVEL 2b: a meter buffer around the riparian zone immediately upstream of
the study wetland; and LEVEL 3: a 300-meter buffer surrounding and
immediately adjacent to the study wetland.









The delineation of drainage basins and the stream networks required the use of a

digital terrain model (DTM), a grid map that masks the DTM, and a pre-digitized stream

network. A state-wide digital elevation model (DEM) available through Geostor was used

as the preferred DTM. The DEM has a 30 x 30-meter cell resolution and was developed

by the United States Geological Survey (USGS) as part of the National Elevation Dataset

(USGS 1999).The DEM for each drainage basin was masked using state-wide watershed

boundaries coverage. The pre-digitized stream network used was a state-wide coverage

also available through Geostor. Where data for streams were missing, the streams were

delineated on-screen with the aid of aerial photography and the elevation terrain model.

The final calculation of the drainage basin boundary was done using a stream outlet

closest to the wetlands' sampling locations.

Landscape Development Intensity Index

The land uses within each of the four areas of spatial influence were clipped from

the LDI-emPower coverage and the LDI index value was calculated for each study

wetland as:

LDI = 10 * log (empPDTotal/emPDRef) (Eq. 1)

where LDI is the Landscape Development Intensity index for a given landscape unit;

empPDTotal is the total areal empower density (including the background environment)

within the buffer; and emPDRef is the areal empower density of the background

environment (2.20 E15 sej/ha-yr; average areal empower density for natural systems in

the BMW). The total areal empower density (empPDTotal) was calculated as:

emPDtota = emPDRef + Z( %LUi * emPDi) (Eq. 2)









where %LUi is the percent of the area of influence in land use i; and emPDi is the non-

renewable areal empower density for land use i. This is a modification of the LDI

published by Brown and Vivas (2005) and used by Vivas (2006).

Analysis of Relationships between the LDI and Wetland Condition

Spearman's rank order correlation, the non-parametric measure of correlation

(Dytham 1999), was used to assess the relationship between the LDI and three different

measures of wetland condition: WRAP (Miller and Boyd 1999), UMAM (62-345.100(6),

Florida Administrative Code [F.A.C.]), and HGM procedure (Brinson 1993).

The WRAP (Miller and Boyd 1999), is a rapid assessment procedure consisting of

a rating index that can be used to evaluate wetland condition based on six variables:

wildlife utilization, wetland overstory/shrub canopy, wetland vegetative ground cover,

adjacent upland support/wetland buffer, field indicators of wetland hydrology, and water

quality input and treatment systems. Each variable is scored from 0.0 to 3.0, in

increments of 0.5. The final index score is expressed on a scale ranging from 0.0 to 1.0. A

score of 1.0 indicates an undisturbed wetland, whereas a score of 0.0 indicates a wetland

with a reduced functional capacity. The WRAP was originally developed by the South

Florida Water Management District (SFWMD) to assist in the regulatory evaluation of

mitigation sites. The variable for adjacent land support and wetland buffer was not

included in the calculation final WRAP score.

The Florida Department of Environmental Regulation (FDEP) developed the

UMAM to assess impacts and mitigation requirements for wetlands and other protected

waters (F.A.C 62-345.100(6)). UMAM provides a standardized procedure for assessing

the functions provided by wetlands and other waters of the state, the amount those

functions are reduced by proposed impacts, and the amount of mitigation necessary to off









set that loss. Bardi et al. (2005) provided a summary of the method as follows: the area of

study is evaluated based on both a qualitative description and quantitative evaluation of

the assessment area. For the quantitative section, sites are evaluated according to three

variables: location and landscape support, which examines the ecological context within

which the system operates; water environment, a rapid assessment of hydrologic

alteration and water quality impairment; and community structure, more specifically

vegetation and structural habitat. Each indicator is scored numerically on a scale from 0

to 10 (where 10 indicates a minimally impaired system).The final UMAM score is

determined by summing the scores of each of the three variables assessed and dividing

that value by 30 to yield a number between 0 and 1. The variable on location and

landscape support was not included in the calculation of the final UMAM scores in this

study.

The HGM (Brinson 1993) is a procedure for measuring wetland functional

capacity. The procedure was designed to satisfy the technical and programmatic

requirements of the Clean Water Act Section 404 (Section 404). The HGM is based on

three fundamental factors that influence wetland function: the position of the wetland in

the landscape (geomorphic setting), the water source (hydrology), and the flow and

fluctuation of the water within the wetland (hydrodynamics). Only three of the HGM

categories were evaluated and used in this study: (a) hydrological category, (b)

biogeochemical category, and (c) habitat category.














CHAPTER 3
RESULTS

Land Use / Land Cover of the Bayou Meto Watershed

Figure 3-1 is a map produced from the LU/LC coverage of the BMW showing the

extent of coverage by the various land uses. The vast majority of the watershed is

dominated by agricultural uses with the northern portions of the watershed dominated by

urban uses. Based on the LU/LC classes shown in Figure 3-1, 20 functional land use

categories for LDI calculations were defined for the BMW.


Emergy Evaluation of Selected Land Uses

A summary of areal empower densities for land use classes in the BMW is given in

Table 3-1 and shown in Figure 3-2. The average areal empower density for the BMW

was 61.47 E 15 sej/ha/yr. The largest areal empower densities (darker areas) occurred in

the urban areas in the northern portion of the watershed (Figure 3-2). The middle and

southern portions of the BMW were dominated by intermediate areal empower densities

that characterize agricultural lands. Details of individual land use classes beginning with

forested ecosystems are given in the following paragraphs.

Emergy evaluations of upland forest and forested wetlands ecosystems (see

Appendix) revealed that the total solar emergy flow for a hectare of mixed hardwood

forest was 1.82 E15 sej/yr, while that of a bottomland hardwood forest was 2.58 E15

sej/yr. Six crops that constitute the most common agricultural crops grown in the BMW

were also evaluated. Total solar emergy values for a hectare of crop ranged between
















Y'T . .......
flv


'V

& r


i-i�I,


ResidenTIial


U r--r Ndireifi


Figure 3-1. Base map of LU/LC classes for the BMW used to identify functional LDI-
LU/LC classes.










7.87 E15sej/yr (sorghum) and 19.5 E15 sej/yr (cotton). Intermediate values included 9.61

E15 sej/yr (soybeans), 10.5 E15 sej/yr (hay), 11.7 E15 sej/yr (rice), and 12.3 E15 sej/yr

(corn). Also common on the landscape of the BMW are fish ponds for raising catfish and

baitfish. On a per hectare basis, the emergy evaluation of six 2-acre ponds for catfish

resulted in a total solar emergy flow of 109.4 E15 sej/yr. A general energy systems


Table 3-1. Areal empower density for land use classes in the Bayou Meto Watershed.
Total NR + PI*
Areal empower Areal empower Density
Density wo/services
Notes Land Use Classes (E15 sej/ha/yr) (E15 sej/ha/yr)
1 Forests 1.82 0.00
2 Background Environment 2.17 0.00
3 Wetlands 2.58 0.00
4 Open Space/Recreational 7.91 5.75
5 Sorghum 7.87 6.16
6 Hay Crop 10.46 6.95
7 Soybeans 9.61 7.73
8 Corn 12.33 9.34
9 Rice 11.66 9.40
10 Cotton 19.52 15.84
11 Rice/Aquaculture 60.55 49.33
12 Aquaculture 109.44 89.25
13 LI-Single Family Residential 218.18 162.48
14 MI-Single Family Residential 610.91 454.94
15 LI-Transportation 494.50 494.50
16 HI-Single Family Residential 872.73 649.92
17 LI-Multi Family Residential 2815.27 2096.52
18 LI-Commercial/Institutional 5174.31 2444.43
19 HI-Transportation 2533.69 2533.69
20 Industrial 5235.02 3654.73
21 HI-Commercial 8372.42 4103.62
22 HI-Multi Family Residential 8445.80 6289.55
* Non-renewable and purchased inputs (wo = with out services)
Notes:
2 Weighted average of 1 and 3 - Based on the proportion of each in the BMW.
11 Average of 9 and 12.










diagram and the emergy evaluation tables for each agriculture system and for catfish

production are included in the Appendix.


J.A.:


Non Renewable Empower Density
(E+ 15 sej/ha/yr)
0
0-7





N
0 10 Kilometers A


Figure 3-2. Non-renewable and purchased areal empower density for the Bayou Meto
Watershed. The range of the areal empower density values are based on the
LU/LC classes from Figure 3-1.

The baseline emergy evaluation for residential land uses was a single-family

residential area with a density of 2.5 houses per hectare with an annual emergy flow of


*^









2.18 E17 sej/ha/yr, and classified as low-intensity single-family residential. Other

housing densities used were 7, 10, 32, and 97 units per hectare and were classified as

medium-intensity single-family residential, high-intensity single-family residential, low-

intensity multi-family residential, and high-intensity single-family residential,

respectively. A general energy systems diagram for a residential area and the emergy

evaluation tables for each residential density are included in the Appendix. The emergy

evaluation of an urban lawn was also developed and used as a measurement for urban

open spaces and urban recreational facilities after "dispersing" the energy usage over the

landscape based on Robbins and Birkenholtz (2003)'s estimate of 23% coverage of lawns

in the urban landscape. The annual emergy flow for a hectare of urban lawn was

calculated as 7.91 E15 sej/ha/yr; this emergy evaluation is included in the Appendix.

Other urban land uses that were evaluated were commercial and industrial areas

and transportation corridors (highways). The energy system diagrams and emergy

evaluation tables for these urban land uses are provided in the Appendix. Commercial

land uses had annual solar emergy flows of 5.17 E18 sej/ha/yr and 8.37 E18 sej/ha/yr for

low-intensity and high-intensity areas, respectively. The annual solar emergy flows for an

industrial area were calculated as 5.24 E18 sej/ha/yr. A hectare of an interstate highway

(1-40) had an annual solar emergy flow of 2.53 E18 sej/ha/yr, while a less intense

highway (U.S. Highway 70) had an annual solar emergy flow of 4.94 E17 sej/ha/yr.


LDI and Wetland Condition

LDI Scores for Study Wetlands

Table 3-2 lists each of the wetland study sites, their a priori classes, and the areal

empower density and computed LDI for each of the four spatial scales. Urban sites had









higher areal empower densities and LDI scores than rural and reference sites. The

purpose of computing four different LDI scores for each wetland was to test which scale

is most appropriate within watersheds. The Level 3 scale is the smallest scale consisting

of a 300-meter buffer around each of the wetland study sites, while Level 1 is the largest

scale consisting of the entire upstream watershed. There was general agreement between

LDI scores for the four scales in urban and rural study sites. However, three a priori

reference sites had unusual areal empower density values. Sites # 2 and 27 had Level 1,

2a, and 2b areal empower densities that were not indicative of reference conditions, while

their Level 3 scores were well within reference conditions. Site # 21 had areal empower

densities that were not indicative of reference conditions at all scales considered. This

was due primarily to the fact that these study sites were embedded in watersheds that had

relatively intense upstream urbanization.

LDI scores for the different scales were compared across each study site to

determine if there were significant differences from one scale to the next. A Kruskal-

Wallis non-parametric statistical test used to compare the computed LDI values at the

four spatial scales showed no significant differences between the different scales (H=

2.70, p = 0.439). A comparison of LDI scores of the four spatial scales, as shown in

Figure 3-3, suggests that there are relatively strong correlations between LDIs for

wetland study plots computed for Levels 1, 2a, and 2b (r2 = 0.98). LDI indices for Level

3 differ slightly from those calculated for Levels 1, 2a, and 2b but still have relatively

strong correlations (r2 = 0.88). It is obvious from the scatter plots in Figure 3-3 that

wetland study sites with intermediate LDI values are absent from the data set.











Table 3-2. Non-renewable and purchased areal empower density and LDI index scores for 29 forested floodplain wetlands. Development
intensity measurements were completed for four spatial scales.
Levell:Watershed Level 2a: 300-m Stream Level 2b: 100-m Stream Level 3: 300-m Adjacent
Buffer Buffer to Wetland
NR+P EmpDen LDI NR+P EmpDen LDI NR+P EmpDen LDI NR+P EmpDen LDI


Site No.


Type* (E+15 sej/ha/yr): (E+15 sej/ha/yr): (E+15 sej/ha/yr): (E+15 sej/ha/yr)


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
* Urb =


Site Name
Fina Woods
Old Highway 69 Woods
Church Woods
Strip Mall Woods
Cabot Park
Gander Mtn. Sporting Goods
Manson Rd. Woods
Harvest Foods Woods
Jacksonville Ball Field
Gentry Rd West
Gentry Rd East
Fareview
Winrock Hwy 13 West
Winrock Hwy 13 East
Winrock CR 923 East
Winrock CR 923 West
Merlin Mission
Winrock CR 915 East A
Winrock CR 915 East B&C
Winrock CR 915 West
1-40 Woods
North Holland Bottoms 1
North Holland Bottoms 2
North Holland Bottoms 3
Prairie Bayou WMA 1
Prairie Bayou WMA 2
Prairie Bayou WMA 3
Lower Holland Bottoms 1
Lower Holland Bottoms 2


Urb
Ref
Urb
Urb
Urb
Urb
Urb
Urb
Urb
Rur
Rur
Rur
Rur
Rur
Ref
Rur
Rur
Ref
Ref
Rur
Ref
Ref
Ref
Ref
Rur
Ref
Ref
Ref
Ref


603.38
28.24
1312.54
1910.85
634.64
342.80
1470.33
1501.21
789.90
16.20
26.71
9.81
8.78
8.49
9.42
9.45
8.86
5.89
8.02
9.46
13.25
0.00
0.00
0.00
7.40
6.47
38.72
0.00
0.00


24.40
11.41
27.76
29.39
24.62
21.95
28.26
28.35
25.56
9.22
11.19
7.37
6.98
6.87
7.23
7.24
7.01
5.66
6.67
7.24
8.46
0.00
0.00
0.00
6.40
5.95
12.70
0.00
0.00


1255.01
25.27
1315.36
1711.64
623.25
307.78
1547.29
1871.77
665.24
7.34
9.02
8.41
8.73
8.59
9.05
9.12
7.72
4.90
7.41
9.10
14.19
0.00
0.00
0.00
6.71
6.35
25.02
0.00
0.00


1255.01
25.27
1315.36
1711.64
623.25
307.78
1547.29
1871.77
665.24
7.34
9.02
8.41
8.73
8.59
9.05
9.12
7.72
4.90
7.41
9.10
14.19
0.00
0.00
0.00
6.71
6.35
25.02
0.00
0.00


27.57
10.96
27.77
28.92
24.54
21.49
28.48
29.30
24.82
6.37
7.07
6.83
6.96
6.90
7.09
7.11
6.54
5.09
6.40
7.11
8.72
0.00
0.00
0.00
6.07
5.90
10.92
0.00
0.00


Urban- Ref = Reference: Rur = Rural


1335.57
22.41
1374.84
704.81
221.56
248.83
2108.05
1491.62
428.26
6.10
8.01
7.04
7.94
7.95
8.62
8.69
6.25
0.75
6.66
8.44
13.35
0.00
0.00
0.00
2.26
2.71
13.97
0.00
0.00


27.84
10.49
27.97
25.07
20.07
20.57
29.82
28.32
22.92
5.77
6.67
6.23
6.64
6.64
6.92
6.95
5.84
1.27
6.05
6.85
8.49
0.00
0.00
0.00
3.07
3.49
8.66
0.00
0.00


1498.96
0.07
1211.80
1844.90
820.07
2566.80
2380.05
1588.39
231.04
4.67
5.59
7.61
9.25
6.19
5.51
8.19
5.84
0.31
0.52
3.43
98.66
0.00
0.00
0.00
2.56
0.31
1.75
0.00
0.00


Urban; Ref = Reference; Rur = Rural


28.34
0.14
27.42
29.24
25.73
30.67
30.35
28.59
20.25
4.94
5.49
6.49
7.16
5.81
5.45
6.74
5.63
0.58
0.92
4.08
16.61
0.00
0.00
0.00
3.35
0.58
2.54
0.00
0.00















Level 1 vs Level 2a


0 5 10 15 20 25 30 35
LDI Level 2a


Level 3 vs Level 2a


0 5 10 15 20 25 30 35
LDI Level 2a

(d)


Level 1 vs Level 2b


R2 0.9615







0 5 10 15 20 25 30 35
LDI Level 2b


Level 3 vs Level 2b


0 5 10 15 20 25 30 35
LDI Level 2b

(e)


Level 1 vs Level 3


R2 = 0.8657 *






0 5 10 15 20 25 30
LDI Level 3


Level 2b vs Level 2a


R 2- 0.9813 0







0 5 10 15 20 25 30 35
LDI Level 2a


(f)


Figure 3.3 Scatter plots of study wetland LDI indices at various scales. a). Level 1 vs. Level 2a; b) Level 1 vs. Level 2b; c) level 1 vs.
Level 3; d) Level 3 vs. Level 2a; e) Level 3 vs. Level 2b; and f) Level 2b vs. Level 2a. See text for explanations of the
spatial scales corresponding to each of the levels of analysis.









Wetland Condition Indices for Wetland Study Sites

Table 3-3 lists each of the wetland study sites, their a priori classes, and their wetland

condition index scores. Each of the three components of the HGM score is listed separately.

Table 3-3 is a summary of the data for the a priori classes of wetland sites showing the mean

LDI values for each of the four spatial scales and the corresponding mean wetland condition

indices. The small sample size for each a prior class of wetland sites makes statistical

comparisons among LDI groups and among groups of the wetland condition indices not

relevant. However, the inspection of the data suggests that there are important differences in

LDI scores and wetland condition indices scores among the a priori classes.


Table 3-3 Summary of LDIs and Wetland condition indices for a priori classes.
Level 1 Level 2a Level 2b Level 3 HGM- HGM- HGM-
A priori Class LDI LDI LDI LDI WRAP UMAM Hydrological Biogeochemical Habitat
Reference Sites 4.84 4.59 3.78 2.24 0.98 0.96 0.90 0.87 0.92
Rural Sites 7.72 6.77 6.07 5.52 0.84 0.81 0.89 0.83 0.87
Urban Sites 26.29 26.61 25.32 27.57 0.72 0.81 0.71 0.67 0.82



In general, mean LDI scores decreased as the spatial scale decreased. This held true for

reference and rural sites; however, urban sites did not follow this trend. The Level 3 mean LDI

scores for reference sites (n = 12) were less than half those of the Level 1 score, while the Level

3 mean LDI score for rural sites was about 30% lower than the Level 1 score.


Relationships between the LDI and Measurements of Wetland Condition

The LDI was correlated with three independent measurements of anthropogenic

disturbance: WRAP, UMAM, and HGM. The scores for each of these indices for each wetland

study plot are presented in Table 3-4; the correlation results are shown in Table 3-5. All

correlations were statistically significant (p-level of 0.05). WRAP had the strongest correlations









with LDI at all scales of analysis, followed by the HGM. The habitat component of the HGM

had the highest correlations with LDI at all scales of analysis.

The strongest correlation was found between the LDI and the WRAP at the Level 3

spatial scale (Spearman's r = -0.81, p < 0.001). The habitat component of HGM correlated

strongest with the LDI at the Level 3 spatial scale. The hydrological component of the HGM

also showed the strongest association with the LDI at the same scale (Level 3). The

biogeochemical component of HGM showed the strongest association with the LDI at the

Level 2a and Level 2b scales (100-meter buffer and 300-meter buffer around the stream,

respectively). Correlations between the UMAM and the LDI were very similar among the four

spatial scales considered. Graphs showing the relationship between the LDI and the WRAP,

HGM, and UMAM are shown in Figures 3-4, 3-5, and 3-6, respectively. Variables were

graphed in rank order form.

Level of impairment, evaluated by means of the WRAP, increased as the development

intensity of the surrounding landscape increased. The results seem to suggest that, for all scales,

the levels of disturbance for the wetland study sites were influenced by their surrounding (or

upstream) landscape and that areal empower density was a measure of the disturbance gradient

(see Figure 3-4). Differences between the Spearman's correlations for the four scales (see Table

3-5), suggest that the landscape immediately adjacent to the wetlands (Level 3) may be more

important in determining wetland condition than lager scale areas (i.e., Levels 1, 2a, and 2b).











Table 3-4. Final scores for three measurements of wetland condition for the sample floodplain
wetlands.


Site Name


Type*


Fina Woods
Old Highway 69 Woods
Church Woods
Strip Mall Woods
Cabot Park Woods
Gander Mtn Sporting Goods
Manson Rd. Woods
Harvest Foods Woods
Jacksonville Ball Field
Gentry Rd West
Gentry Rd East
Fairview
Winrock Hwy 13 West
Winrock Hwy 13 East
Winrock CR 923 East
Winrock CR 923 West
Merlin Mission
Winrock CR 915 East A
Winrock CR 915 East B&C
Winrock CR 915 West
1-40 Woods
North Holland Bottoms 1
North Holland Bottoms 2
North Holland Bottoms 3
Prairie Bayou WMA 1
Prairie Bayou WMA 2
Prairie Bayou WMA 3
Lower Holland Bottoms 1
Lower Holland Bottoms 2


WRAP UMAM
Hydrological
Category
0.75 0.86 0.54
1.00 0.99 0.86
0.54 0.72 0.78
0.65 0.87 0.61
0.75 0.81 0.73
0.61 0.78 0.78
0.85 0.84 0.78
0.88 0.83 0.74
0.69 0.78 0.69
0.61 0.68 0.96
0.84 0.85 0.94
0.90 0.84 0.88
0.83 0.78 0.97
0.83 0.78 0.76
0.88 0.81 0.94
0.75 0.63 0.84
0.89 0.82 0.84
0.94 0.90 0.88
0.92 0.89 0.85
0.93 0.92 0.92
0.99 0.96 0.90
1.00 0.99 0.89
1.00 0.99 0.91
1.00 1.00 0.92
1.00 0.98 0.94
1.00 0.96 0.91
1.00 0.97 0.98
1.00 1.00 0.94
1.00 1.00 0.84


HGM
Biogeochemical
Category
0.42
0.81
0.71
0.57
0.64
0.90
0.76
0.78
0.58
0.89
0.83
0.83
0.86
0.75
0.87
0.78
0.82
0.88
0.79
0.85
0.83
0.86
0.91
0.97
0.87
0.89
0.92
0.86
0.85


Habitat
Category
0.76
0.86
0.79
0.80
0.88
0.76
0.90
0.81
0.82
0.83
0.91
0.91
0.92
0.82
0.95
0.81
0.85
0.92
0.87
0.88
0.87
0.92
0.92
0.95
0.92
0.96
0.98
0.96
0.92













Table 3-5. Spearman's correlations (r) between the LDI and measurements of wetland condition for the sample floodplain wetlands
calculated at four different spatial scales.
WRAP UMAM HGM
Hydrological Biogeochemical Habitat
LDI Component Component Component
r p-value r p-value r p-value r p-value r p-value
Level 1: Watershed -0.68 <0.001 -0.50 0.005 -0.49 0.007 -0.60 0.001 -0.67 <0.001
Level 2a: 300-m surrounding stream -0.64 <0.001 -0.48 0.009 -0.54 0.002 -0.65 <0.001 -0.67 <0.001
Level 2b: 100-m surrounding stream -0.64 <0.001 -0.49 0.008 -0.54 0.002 -0.64 <0.001 -0.67 <0.001
Level 3: 300-m adjacent to study wetland -0.81 <0.001 -0.50 0.006 -0.57 0.001 -0.60 0.001 -0.73 <0.001



















LEVEL 1: Watershed


LEVEL 2a: 300-m Buffer Surrounding Stream


s* Groups
* Reference
A Rural
* Urban


S
*A
A


A A


A 0 U


0 5 10 15 20 25 30
LDI


0 5 10 15
LDI


20 25 30


LEVEL 2b: 100-m Buffer Surrounding Stream


*0


*


A 0 U


LEVEL 3: 300-m Buffer Adjacent to Study Wetland

46 0 * A Groups
* Reference
A Rural
* Urban


A A

A M U


0 5 10 15 20 25 30
LDI


0 5 10 15 20 25 30
LDI


Figure 3-4. Scatterplots showing the relationship between the LDI and the WRAP for

four different spatial scales. Data on both axes are shown as ranked scores.


. oA


*0


a g A


AA


m


A U


* Ag



S


















LEVEL 1: Watershed


A
A


30-


25-


I 20-
-




' 10-
- lo


a 5-


0-


0 5 10 15
LDI


20
I 20-


15


S10-

Sl 5-
* a 5-


20 25 30


LEVEL 2a: 300-m Buffer Surrounding Stream


A Groups
A A Reference
* A Rural
A U Urban


0 5 10 15
LDI


20 25 30

20 25 30


LEVEL 2b: 100-m Buffer Surrounding Stream


25-


20
I 20-


" 15-
~n~ -


S10-


a 5-


*
*


0 5 10 15
LDI


20 25 30


LEVEL 3: 300-m Buffer Adjacent ot Study Wetland

* A Groups
A A* Reference
* A Rural
U Urban


U
A



0 5 10 15 20 25 30


Figure 3-5a. Scatterplots showing the relationship between the LDI and the HGM

hydrological category for four different spatial scales. Data on both axes

are shown as ranked scores.


*
*
U


30-


25-
-)

20
I 20-


" 15-



5o
S10-
a 5-


0-


I I I I I I















LEVEL 2a: 300-m Buffer Surrounding Stream


*A
*


30-


25-
--

U 20-
- I5
-4 15-


*. 10-


5-


Groups
0 * Reference
A Rural
* Urban


0 5 10 15
LDI


20 25 30


0 5 10 15
LDI


20 25 30


LEVEL 2b: 100-m Buffer Surrounding Stream


0�


U
U


0 5 10 15
LDI


25-
on


U 20-


- 15-


.2 10"

S5


20 25 30


LEVEL 3:300-m Buffer Adjacent to Study Wetland
Groups
0 Reference
A Rural
A n Urban


A
*


0 5 10 15
LDI


20 25 30


Figure 3-5b. Scatterplots showing the relationship between the LDI and the HGM

biogeochemical category for four different spatial scales. Data on both

axes are shown as ranked scores.


U
U
U
U
U
U


A*A


S25-
&o

U 20-
-


- 15-


10-
5 -


U
U
*


30-


25-
-)

U 20-
-


15-
-n

S10-


5-


0-


I I I I I I I


LEVEL 1: Watershed














LEVEL 1: Watershed


A


20-
-


15-


� 10-


LEVEL 2a: 300-m Buffer Surrounding Stream

* Groups
* * Reference
* A Rural
A U Urban


* 0


0 5 10 15
LDI


20 25 30


0 5 10 15
LDI


20 25 30


LEVEL 2b: 100-mBuffer Surrounding Stream


o -
? 20-


. 15-


S10
a


10 15 20 25 30

0 5 10 15 20 25 30


LEVEL 3: 300-m Buffer Adjacent to Study Wetland

* Groups
* S Reference
* A Rural
A U Urban


0 5 10 15
LDI


20 25 30


Figure 3-5c. Scatterplots showing the relationship between the LDI and the HGM

habitat category for four different spatial scales. Data on both axes are
shown as ranked scores.


30-


25-


I 20-


I 15-


10-
-


* a A


30-


25-


20-


. 15-


10-
-a


















LEVEL 1: Watershed


U
-t
0


LEVEL 2a: 300-m Buffer Surrounding Stream

Groups
* Reference
* A Rural
A U� Urban
~R]


*
U


0 5 10 15
LDI


20 25 30


0 5 10 15
LDI


20 25 30


LEVEL 2b: 100-m Buffer Surrounding Stream


0


LEVEL 3: 300-m Buffer Adjacent to Study Wetland

Groups
S Reference
* A Rural
A U Urban


A


*
U


0 5 10 15
LDI


20 25 30


0 5 10 15
LDI


20 25 30


Scatterplots showing the relationship between the LDI and the

UMAM for four different spatial scales. Data on both axes are shown

as ranked scores.


Figure 3-6.


I I � I I I �


I I � I I I I














CHAPTER 4
SUMMARY AND DISCUSSION

This study consisted of the following three inter-related objectives: 1) develop areal

empower density values for land use classes based on existing LU/LC coverages of the

BMW; 2) compute LDI values for floodplain forested wetlands for which three field

based measures of wetland condition had been quantified; and 3) statistically determine if

the LDI can be used as a predictor of wetland condition.

The first objective required three tasks: 1) a detailed evaluation of the emergy use

of Arkansas to develop multipliers of emergy use for land uses, 2) integration of LU/LC

coverages into a usable set of land uses classes for which detailed emergy flow data could

be reasonably collected, and 3) detailed emergy evaluations of the land uses to compute

areal empower density for each. The analysis of the state of Arkansas and the detailed

analyses of individual land use types are presented in the Appendix.

The primary spatial data source for development of the land use classes was the

1999 Arkansas LU/LC: Summer (CAST 2001), referred to hereafter as 1999 AR-LC/LU

coverage. The coverage consisted of 46 LU/LC classes, from which 20 LU/LC classes

were defined and their areal empower density calculated. Systems diagrams were

developed and used as an inventory guide for collecting material and energy flow data for

each land use class. These data were used to develop emergy tables from which areal

empower density was computed.

The second objective of this study was to calculate LDI scores for floodplain

forested wetlands in the BMW. A total of 29 wetlands were selected from within various









landscape settings including natural, agricultural, and urban land uses. The a priori

selection of wetlands provided a range of landscapes that represented a gradient from

undeveloped to highly developed lands, although intermediate disturbances were lacking

in the data set.

The method of calculating LDI scores for wetlands differed somewhat from

previous studies in Florida; LDIs are not calculated for individual land use and then

averaged, but instead the areal empower density was computed for the entire area of

influence of each wetland and then an LDI was calculated using a deci-log formula that

included a reference state. The result is a more robust LDI score since it does not result

from the averages of LDIs but instead from the average of the areal empower densities.

To test the appropriate spatial scale over which the LDI score should be calculated,

LDI scores for each wetland study plot were computed for four different spatial scales.

There were strong correlations between all four scales; however, the smallest scale (Level

3; 300-meter buffer surround the wetland study plot) seems to be a better predictor of

wetland condition. LDI scores computed at the larger spatial scales had higher LDI scores

than the Level 3 scores, reflecting the intense development in the large watershed.

However, it appears that wetland condition responds to localized impacts more strongly

than to conditions in upstream watersheds. This was also found in the earlier work on

LDI in Florida (Brown and Vivas 2005; Lane et al. 2003; Reiss and Brown 2005; Reiss

2006).

The final objective was to correlate the LDI scores of the wetland study plots with

several indices of wetland condition. Strong correlations between the LDI scores and the

WRAP were found, especially at the Level 3 spatial scale. Correlations between the LDI









scores and the HGM were also relatively high, particularly when the LDI scores were

related to the habitat component of the HGM at the Level 3 spatial scale. Of the HGM

categories, the habitat component had the strongest correlations with LDI scores. The

relationship between the LDI and the UMAM was not as strong.

Land Use Land Cover Data Sources

The 1999 AR-LU/LC coverage emphasized agricultural land uses and forest classes

providing only general descriptions for urban land uses and surface water cover. Because

of the general description of urban land uses and water cover provided by the Arkansas

LU/LC map, these categories had to be aggregated or disaggregated to fit the

requirements needed for LDI calculations based on functional land use categories. This

was done using partial coverages for urban centers in the BMW provided by Metroplan,

Arkansas, through the MAWPT, and aerial photography. To determine housing densities

for residential areas, houses were counted within one hectare plots laid on aerial photos.

Aquatic systems, both natural and constructed, were determined using a combination of

thematic coverages available through Geostor, a web-based database containing all

publicly available geodata for the state of Arkansas

(http://www.cast.uark.edu/cast/geostor/), and identification of land uses using aerial

photography. Integrating all of these coverages using GIS allowed obtaining a working

LU/LC coverage for the BMW.

The steps followed here to identify functional LDI land use classes can be

replicated for other regions where similar LDI studies may be intended. In the absence of

more detailed and recent data, the 1999 Arkansas LU/LC: Summer map provides detailed

information on agricultural land uses. Information on forest classes can be easily

aggregated with enough knowledge of the forest types used in the map into two classes,









uplands and wetlands. For the purpose of areal empower density calculation these two

forest categories may provide the level of detail needed. For urban areas, if more

complete urban converges exist for other regions a more accurate representation of urban

land uses will be possible. However, even with general spatial data for a given area as

was the case for the BMW, LU/LC classes will be able to be identified that will fit LDI

calculation needs. Baseline housing densities estimates from aerial photos can be easily

determined, especially for urban areas with low tree cover. Finally, Geostor provides data

that complements the 1999 Arkansas LU/LC: Summer map with coverages for aquatic

(e.g., rivers, lakes, reservoirs, canals) and transportation systems (e.g., roads, railroads).

Only a small set of land uses presented some difficulty for its accurate representation.

The 1999 Arkansas LU/LC: Summer map presents a category for no data that was

partially identified using aerial photography. After merging the 1999 Arkansas LU/LC:

Summer map with the existing maps for aquatic systems from the Geostor database and

those determined using remote data, some undefined water areas still remained. A visual

identification of these areas using aerial photographs showed that these areas most

probably corresponded to rice fields (wet stage) and managed ponds (aquaculture). These

areas were incorporated in the final LU/LC map as a separate land use category. To

accurately identify undefined land use areas, field visits to these areas are suggested.

However, if the unidentified areas are relatively small and their identification though

aerial photography suggests that these may belong to a well-defined land cover (e.g.,

agriculture), the areal empower density for a similar land use type (or a combination of

land use types) may serve as a good approximation of energy flows within these areas.









Areal Empower Densities for Land Uses

Emergy evaluation results for each land use showed no major departures from

similar studies in Arkansas and Florida. For Arkansas, Odum et al. (1998) developed

emergy evaluations for land uses for the Cache River watershed in the northeastern

portion of the state. These included an emergy evaluation of the Black Swamp and

emergy evaluations for rice, soybeans, sorghum, and corn. Our results were similar to

those reported by Odum and colleagues (1998). Where some differences were noted for

the results of the study of the Cache River watershed and this study, they can be

attributed to differences in data sources and number of inputs considered in the emergy

evaluations. However, results for both studies were within the range of emergy values

usually reported for agricultural crops for industrialized regions. In Florida, Brandt-

Williams (2001) calculated the areal empower density of a variety of agricultural land

uses. The results for the Florida study and for this research were very similar.

The areal empower densities computed for urban land uses were higher in this

study than those reported by Brown and Vivas (2005) in the state of Florida. Among the

residential land uses differences can be partially attributed to different housing densities

used in the two studies and partially to differences in data sources. For non-residential

land uses (i.e., commercial, institutional, industrial, and transportation) more complete

data sources may account for most of the differences. The previous studies of Florida

urban land uses were primarily completed in the 1980s and 1990s. Data sources

nowadays are more completed and our methods of analysis have matured. So it is not

unexpected that the more complete data and improved methods of analysis would result

in slightly different emergy flow data for urban land uses. However, the areal empower









densities computed in this study were within the range of values reported for urban land

uses for developed regions.

A Landscape Assessment of Wetland Ecological Condition

Correlations between the LDI and indices of ecosystem condition, including

wetland condition indices (Lane et al. 2003; Reiss and Brown 2005; Reiss 2006), the

Stream Condition Index for Florida (Fore 2004), the Lake Vegetation Index (Fore 2005),

rapid wetland assessment methods (Reiss 2004; Brown and Vivas 2005), and measures of

the human disturbance gradient (Reiss 2004; Fore 2004; Mack 2006) suggest that the LDI

may capture in one index the combined action of various factors that result from human

activity that influence ecosystem structure and functioning.

In this study the LDI was correlated with three rapid field procedures for wetland

condition: the WRAP, the HGM, and the UMAM to test the usefulness of the LDI as a

Level 1 assessment method. The LDI was calculated for four areas of different sizes

surrounding 29 floodplain wetlands in the BMW. The WRAP, UMAM, and HGM

indices were computed for these wetlands by the MAWPT staff based on their field visits

conducted in the Fall of 2005.

The wetland condition scores (see Table 3-3) when compared to the four LDI

scores exhibited intermixing of reference wetlands and rural wetlands along the LDI

disturbance gradient. Since there were very few natural areas within the BMW from

which reference wetlands (low human-impacted sites) could be selected this result is not

unexpected, as some of the reference sites had to be chosen from within agricultural

landscapes and wetland study plots were located within local buffers of forested lands.

This selection resulted in similar non-renewable and purchased areal empower density









values for some of the reference and rural sites. This outcome was more evident at the

broader landscape scales.

Correlations between the UMAM and LDI scores were the weakest correlation

among the variables analyzed. In general, UMAM scores for the rural sites and the urban

sites were approximately within the same range of values and did not show an alignment

along the disturbance gradient. Inspection of the UMAN scores related to WRAP and

HGM reveals that consistently, the UMAM scores were higher for urban wetland study

plots and tended to be somewhat lower for reference and rural sites. The reason for this is

not entirely clear. In this study, the functional component of the UMAM that assesses

location and landscape support was not scored to avoid redundancy with the LDI, and

only the water environment and community structure categories of the UMAM were

measured. It should be noted that the HGM hydrological component also had the lowest

correlation with LDI scores (see Table 3-4).

Among the different scales of landscapes considered in the calculation of LDI

values for the wetland study plots, the Level 3 - 300 meters adjacent to the study plots,

exhibited the strongest correlations with the WRAP and with the habitat and hydrological

categories of the HGM. These results agree with Brown and Vivas (2005), who found

that LDIs computed for 100-meter buffer areas surrounding small wetlands (< 2 hectares)

had stronger correlations with wetland condition than larger areas.

Conclusions

Using existing LU/LC data for the BMW a group of 20 land use classes were

identified for which the emergy use per unit area per time or areal empower density

(units: sej/ha/yr) was calculated. The areal empower density values of the non-renewable

and purchased energies for the 20 land use classes were comparable to those reported for









similar land uses in Arkansas (Odum et al. 1998) and Florida (Brandt-Williams 2001;

Brown and Vivas 2005). Thus, the areal empower densities calculated here can be used in

other regions within Arkansas and possibly in other regions of the country.

LDI scores were computed from areal empower densities of land uses for four

different scale landscape regions surrounding 29 floodplain wetlands in the BMW. LDI

scores were correlated with three independent measures of wetlands condition: the

WRAP, HGM, and the UMAM. The LDI showed fair to good correlations with these

indices with the highest correlations reported with the WRAP and the habitat category of

the HGM. Since the LDI has been developed and applied mostly in Florida, it has been

suggested that it should be tested in other regions to further assess its validity and utility

as an assessment tool (Mack 2006). Results from the use of the LDI in the BMW provide

additional supportive evidence of the usefulness of the LDI as a Level 1 assessment

procedure for the estimation of wetland condition.














LIST OF REFERENCES


Bardi, E., M.T. Brown, K.C. Reiss, and M. J. Cohen. 2005. UMAM: Uniform Mitigation
Assessment Method training manual. Web-based training manual for Chapter 62-
345, FAC for wetlands permitting. Howard T. Odum Center for Wetlands and
Center for Environmental Policy, University of Florida, Gainesville.

Brinson, M.M. 1993. A hydrogeomorphic classification for wetlands. Wetland Research
Program Technical Report WRP-DE-4. U.S. Army Engineer Waterways
Experiment Station, Vicksburg, MS.

Brandt-Williams, S. 2001. Handbook of emergy evaluation: a compendium of data for
emergy evaluation. Folio # 4 Emergy of Florida Agriculture. Center for
Environmental Policy, Environmental Engineering Sciences, University of Florida.
Gainesville.

Brooks, R. P., D. Heller-Wardrop, and J.A. Bishop. 2004. Assessing wetland condition
on a watershed basis in the Mid-Atlantic region using synoptic land cover maps.
Environmental Monitoring and Assessment. 94:9-22.

Brown, M. T. 1980. Energy basis for hierarchies in urban and regional landscapes. Ph. D.
Dissertation, University of Florida, Gainesville, Florida, USA.

Brown, M.T., and M.B. Vivas. 2005. Landscape development intensity index.
Environmental Monitoring and Assessment 101:289-309.

Center for Advanced Spatial Technologies. 2001. 1999 Arkansas land-use/land-cover:
summer. University of Arkansas, Fayetteville, AR.

Cohen, M. J., S. Carstenn, and C.R. Lane. 2004. Floristic quality indices for biotic
assessment of depressional marsh condition in Florida. Ecological Applications
14:784-794.

Dytham, C. 1999. Choosing and using statistics: a biologist's guide. Blackwell Science,
Oxford, UK.

Fennessy, M.S., A.D. Jacobs, and M.F. Kentula. 2004. Review of rapid assessment
methods for assessing the wetland condition. EPA/620/R-04/009. U.S.
Environmental Protection Agency, Washington D.C.









Fore, L.S. 2004. Development and testing of biomonitoring tools for macroinvertebrates
in Florida streams. Statistical Design, Seattle, Washington. A report for the Florida
Department of Environmental Protection, Tallahassee, Florida, USA. 62 p.

Fore, L.S. 2005. Assessing the biological condition of Florida lakes: development of the
lake vegetation index (LDV). Statistical Design, Seattle, Washington. A report for
the Florida Department of Environmental Protection, Tallahassee, Florida, USA. 29
pp. & Appendixes.

Lane, C.R. 2003. Biological indicators of wetland condition for isolated depressional
herbaceous wetlands in Florida. Ph.D. Dissertation, University of Florida,
Gainesville, Florida, USA.

Lane, C.R., M.T. Brown, M. Murray-Hudson, and M.B. Vivas. 2003. The Wetland
Condition Index (WCI): biological indicators of wetland condition for isolated
depressional herbaceous wetlands in Florida. Report submitted to the Florida
Department of Environmental Protection (Contract #WM-683). H.T. Odum Center
for Wetlands, University of Florida, Gainesville, Florida, USA.

Mack, J.J. 2006. Landscape as a predictor of wetland condition: an evaluation of the
landscape development index (LDI) with a large reference wetland dataset from
Ohio. Environmental Monitoring and Assessment DOI: 10.1007/s 10661-005-
9058-8.

Miller, R.E., Jr. and B.E. Boyd. 1999. Wetland rapid assessment procedure. South Florida
Water Management District, Technical Publication REG-001. West Palm Beach,
Florida, USA.

Odum, H.T. 1996. Environmental Accounting: emergy and environmental decision
making. John Wiley & Sons, Inc., New York.

Odum, H.T., S. Romitelli, and R. Tighe. 1998. Evaluation overview of the Cache River
and the Black Swamp in Arkansas. Final Report on Contract #DACW39-94-K-
0300 Energy Systems Perspectives for Cumulative Impacts Assessment between
Waterways Experiment Station, U.S. Dept. of the Army, Vicksburg, Miss. and
University of Florida. Center for Environmental Policy, Environmental
Engineering Sciences, University of Florida, Gainesville. 128 p.

Parker, N.M. 1998. Spatial models of total phosphorus loading and landscape
development intensity in a North Florida watershed. Masters Thesis, University of
Florida, Gainesville.

Reiss, K.C. 2004. Developing biological indicators for isolated forested wetlands in
Florida. Ph.D. Dissertation, University of Florida, Gainesville, Florida, USA.

Reiss, K.C. 2006. Florida Wetland Condition Index for depressional forested wetlands.
Ecological Indicators 6:337-352.









Reiss, K.C., and M.T. Brown. 2005. The Florida Wetland Condition Index (FWCI):
preliminary development of biological indicators for forested strand and floodplain
wetlands. Report submitted to the Florida Department of Environmental Protection
under contract #WM-683. Howard T. Odum Center for Wetlands, University of
Florida, Gainesville, Florida, USA. 94 p.

Robbins, P., and T. Birkenholtz. 2003. Turfgrass revolution: measuring the expansion of
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Surdick, A.J. 2005. Amphibian and avian species composition of forested depressional
wetlands and circumjacent habitat: the influence of land use type and intensity.
Ph.D. Dissertation, University of Florida, Gainesville, Florida, USA.

United States Environmental Protection Agency. 2001. Better assessment science
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Unite States Environmental Protection Agency. 2003. Elements of a State Water
Monitoring and Assessment Program. EPA 841-B-03-003. Washington D.C.
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United States Geological Survey. 1999. Elevation, National Elevation Database (USGS).
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Vivas, M.B. 2006. An assessment of the quality of surface waters in Florida using
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University of Florida, Gainesville, Florida, USA.














APPENDIX A
ENERGY EVALUATION OF THE STATE OF ARKANSAS AND LAND USES
OF THE BAYOU METO WATERSHED



Introduction

Emergy and Emergy Analysis

Emergy analysis is an environmental accounting procedure for estimating the work

required for a product or process in units of one kind of energy, and allows the relation of

economic development with environmental change. It measures the contributions of

nature to the regional economy. In this section a brief explanation of the emergy concepts

and measures used in this project is provided. Emergy-related definitions are summarized

in Table A-1.

Table A-1. Summary of emergy definitions (from Odum 1996).
Available Energy = Potential energy capable of doing work and being degraded
in the process (units: kilocalories, joules, British thermal
units)
Useful Energy = Available energy used to increase system production and
efficiency
Power = Useful energy flow per unit time
Emergy = Available energy of one kind previously required directly
and indirectly to make a product or service (units: emjoules)
Empower = Emergy flow per unit time (units: emjoules per time)

Transformity = The emergy of one type required to make a unit of energy of
another type. A measure of energy quality (units: emjoule
per joule)
Emdollar Value = The dollars of gross economic product equivalent to the
wealth measured in emergy
Wealth = Usable products and services however produced






A-2


Emergy and energy hierarchy

Emergy is a measure of the available energy that was used in transformations and

work to make a product or service (Odum 1996). It is calculated from data on energy

flows that go into the product or process; its unit of measure is the solar emergy joule or

emjoule (abbreviated sej).

Because of the second energy law, all of the processes of nature and the economy

can be arranged in a series, representing the hierarchy of energy. In addition, all

processes use up some of the available energy to do work, dispersing that energy as heat

(degraded energy) and resulting in less available energy in its output than its inputs. Thus,

processes may be arranged in an energy transformation series as shown in Figure A-1.

Total energy flow (power) decreases from left to right, but becomes more concentrated.

Also shown is how in each step of the hierarchy some of the available energy is

dispersed. Food chains, stages in the hydrological cycle, and steps in the production

sectors of the economy are examples with such an organization (Odum et al 1998).

Transformity

Transformity is a measure of the hierarchy of energy. Transformity is defined as

the energy per unit energy and is a measure of energy quality (Odum 1996). Unlike the

energy flow, which decreases through an energy transformation series, the emergy flow

remains the same or increases if more inputs are added. Transformities are used to

calculate emergy from data on energy (i.e., solar emergy = energy * solar transformity;

refer to Figure A-1).









10 1

Solar 1000 100 10 1
Energy ---- - -0 4b

910 81 8

Transformity = Solar Emergy / Energy

1000_ 1 1000 = 10 1000 = 100 1000 1000
1000 100 10 1


Figure A-1. A series of energy transformations forming an energy hierarchy from left to
right with their corresponding transformities. Energy flow is measured as
calories per time (modified from Odum et al. 1998).

Areal empower density

Power is defined as the rate of flow of energy into useful work (Odum 1994).

When work is performed in a unit area we can speak of the energy flow as areal power

density with units of power divided by area (e.g., watt/m2). Similarly, a flow of emergy is

empower (measured in solar emjoule per time); when it is applied in a unit area it is

referred to as areal empower density and can be interpreted as a measure of work per area

per time (units: sej/ha-yr) (Odum 1996). An area with high energy use, such as a city,

will have a higher areal empower density than areas using less energy, such as rural

areas. Since self-organizing systems develop centers of energy processing, a city is a

hierarchical center with high concentrations of empower (Odum 1996).

Emdollars and real wealth

The emdollar is defined as the emergy divided by the emergy/money ratio for an

economy for a given year (Odum 1996). Emdollars allow the combination of

environmental resource contributions on a common basis with contributions purchased by

the economy. Since money is paid only to people for their contribution, money and

market values cannot be used to evaluate the contribution of the environment to a









process. The real wealth of an area or process includes inputs free from the environment

and those purchased and transported in (Odum 1996). Emergy is a measure of real wealth

since it allows evaluating the contributions from nature and those by humans on a

common basis. As summarized in Figure A-2, dividing the annual emergy use by the

gross economic product provides a useful measurement for relating real wealth to money.

Emergy indices

Emergy indices are useful for evaluating systems and their potential. Two

commonly used ratios of emergy flows in environmental accounting are defined in Figure

A-3. The emergy yield ratio is calculated by dividing the emergy of the yield (Y) flowing

into the economy on the right by the emergy of all of the feedbacks (F) from the economy

(e.g., fuels, fertilizers, services). The emergy yield ratio is a measure of the net

contribution of a system to the economy (Odum 1996). A system with a large net emergy

ratio contributes much more real wealth than is required for the process. Examples of this

are rich mineral deposits and abundant fresh waters (Odum et al. 1998).

The emergy investment ratio allows the quantification of the intensity of regional

economic development and the use of the environment. The emergy investment ratio is

defined as the ratio of emergy purchased from the economy (F) to the emergy used free

from the local environment (E). Less developed areas have lower ratio values than more

developed ones. The U.S. has an investment ratio of 7, while Ecuador, which is a less

developed country, has an investment ratio of less than 1 (Odum 1996).







A-5


Resources Purchased
Out of State -.


Sales Out of State


Empower Use


Emergy/money ratio


Gross Economic Product


Figure A-2. Empower (emergy flow) and money circulation in a state. The emergy-to-
money ratio allows evaluating emdollar of environmental contribution
(modified from Odum et al. 1998).


Emergy Investment Ratio


F
I


Emergy Yield Ratio


Figure A-3. Emergy indices used to evaluate environmental development (modified from
Odum et al. 1998).


Gross






A-6


Background of Previous Studies using Emergy

Emergy accounting has allowed the relation of economic development with

environmental change for a great variety of products and processes around the world.

Most of this work is summarized in Odum (1996), and more recently in a series of folios

published by the H.T. Odum Center for Environmental Policy of the University of

Florida (Odum 2000; Odum et al. 2000; Brown and Bardi 2001; Brandt-Williams 2001;

Kangas 2002), and in the proceedings of the biennial Emergy Synthesis Research

Conferences initiated in 1999 (i.e., Brown 2000; Brown 2003, Brown 2005). The

scientific basis of the emergy methodology is described in greater detail in Odum (1994).

The study of watersheds using emergy was begun more than 20 years ago. These

studies have been directed to describe properties of watersheds, their patterns of

development, and to propose management alternatives. Most of the earliest studies are

summarized in Odum (1996). The work done by Odum et al. (1998) for the Cache River

watershed in northeastern Arkansas is of particular relevance for the present study and

seems to be the only reported case of similar studies for this state. Odum and colleagues

(1998) found that environmental contributions within that system accounted for

approximately half of the watersheds' wealth (measured in emergy units) while the other

half was from inputs purchased from outside the system. The Cache River watershed,

which is mostly an agricultural area based on indigenous soils and waters, proved to be a

net emergy exporter. This study included an emergy evaluation of the Black Swamp and

emergy evaluation of six production systems within the watershed: rice, soybeans, wheat,

sorghum, corn, and poultry broiler production.

Odum et al. (1998) also evaluated the state of Arkansas using emergy and based on

data for 1990. Arkansas was found to be 58% self-sufficient. With an emergy investment






A-7


ratio of 0.73, Arkansas had a higher percentage of its economic basis supplied from the

environmental emergy than more developed states like Florida or Texas. The emergy-to-

money ratio was 3.45 E12 sej/$, compared to the same ratio of 1.55 E12 sej/$ for the U.S.

for 1990 (Odum 1996).

For the Mississippi River Watershed, Diamond (1984) and Odum et al. (1987)

evaluated the properties of stream orders based on their environmental and economic

empower. These studies revealed that the geopotential energy fluxes were greatest at

intermediate- to high-order levels while the delta and floodplain regions were found to be

regions of emergy convergence.


Methods

Emergy evaluations are data intensive operations, requiring collection and

cataloging of a variety of material and energy flows. The operation is organized into three

related task; 1) drawing of system diagrams that capture the main flows of energy and

materials supporting the system under study, 2) listing of data in an emergy evaluation

table, and 3) summary of data through the use of indices of energy and material use that

describe the system and its processes. The following provides details of each step in the

methodology.

Energy System Diagramming

Energy system diagrams are useful since they allow the summarization of energy

inputs and flows of a system and provide an overview of the main components,

processes, problems, and contributing factors to a system (Odum 1996). An emergy

evaluation starts with the drawing of a diagram of the system of interest. After defining

the physical boundary, important outside sources are listed and drawn around the






A-8


boundary from left to right in order of increasing transformity, which marks their position

in the energy hierarchy (i.e., sun, wind, rain, geology, fuel, chemicals, goods, services,

market, etc.). The main internal components and processes in the system are identified

and drawn inside the system frame using energy system symbols. The system symbols

that are commonly used are presented in Table A-2. In the diagramming process these

symbols represent system components such as forests, agriculture and industrial

producers, urban areas, and water and soil storage. The final step in the diagramming

process is to connect pathways, interactions, and money transactions using arrows. A

detailed discussion on the construction and mathematical description of energy systems

diagrams and symbols is provided in Odum (1994).

Energy system diagrams showing primary components, sources, and flows were

drawn for each of 20 different land uses within BMW. Diagrams were used as the basis

for creating an inventory of the energy and material flows needed in emergy evaluations.


Emergy Tables

The second step in the emergy evaluation procedure is to develop emergy analysis tables.

The main components of the emergy table are shown in Table A-3. A table consists of six

columns: (1) the number of the line item and its footnote; (2) the name of the item to be

estimated; (3) data in units of energy, mass, or cost; (4) emergy per unit (or

transformities); (5) solar emergy; and (6) emdollars. Each input and output from the

system were included in the table as a line item The solar emergy of each line item was

estimated by multiplying the energy, mass, or money data in column 3 by the solar

emergy per unit from column 4. Transformities were obtained from previous emergy

studies and were referenced accordingly.






A-9


Table A-2. Primary symbols of the energy circuit diagramming.
Symbol Name Description


System
boundary


Energy circuit


Source

Flow limited
source


Storage tank


Sensor


Producer


Consumer


Box


Heat sink


O


Separate emergy evaluation tables were prepared for each of the 20 different land

uses in the BMW. Each land use was evaluated based on a spatial area of one hectare,

therefore the areal empower density was derived directly from the table by summing the


solar emergy for each line item.


0


-4


&0_


C)2


Defines the system being diagrammed. Lines that cross
the system boundary indicate inflows and outflows of
the system.
A pathway with a flow proportional to the quantity in
the storage or source upstream.
A forcing function or outside source of energy
delivering forces according to a program controlled from
outside.
Outside source of energy with a flow that is externally
controlled.

A compartment of energy storage within the system
storing a quantity as the balance of inflows and
outflows.
The sensor (small square box on storage) suggests the
storage tank controls some other flow but does not
supply the main energy for it.
Unit that collects and transforms low-quality energy
under the control of high-quality flows.

Unit that transforms energy quality, stores it, and feeds
it back autocatalytically to improve inflow.

Miscellaneous symbol to use for whatever unit or
function is needed.
Dispersion of potential energy into heat that
accompanies all real transformation processes and
storage. Dispersed energy is no longer available to the
system.


Z)






A-10


Table A-3. Tabular format for an emergy evaluation.
Data Units Solar Emergy/unit Solar Emergy Em$
Notes Itemb (J, g or $) (sej/unit) (sej/yr) ($/yr)
1 1
2 2


n n
a Footnotes for each row of the table are placed here.
b One row for each source, process, or storage of interest.


Data Sources

The material flows, energy requirements, and economic data required for emergy

evaluations were obtained from a variety of sources. Government sources were the first

choice when the data were available, since these data are usually more reliable. As a

result, a variety of federal and state publications and databases were consulted via library

and electronic research. Academic sources were also widely consulted, particularly in the

development of the emergy evaluations of agricultural land uses. Information provided by

the agricultural extension services of different universities in Southern U.S., including the

University of Arkansas, was used on multiple occasions. Published and unpublished

academic documents were also widely used. Among these, a variety of documents such

as reports, academic dissertations, and theses from the University of Florida were

frequently used as sources for emergy-related data such as transformities, and to compare

results with previous emergy evaluations and work.

When required, data were transformed to meaningful emergy units, usually mass,

that can be easily converted to energy units. In all cases, data usage and conversions were

reported in the footnotes for Column 1 of the emergy tables (see Table A-2). When

required, assumptions about the data were made and also reported in the footnotes. Each






A-11


source that was consulted was appropriately referenced in the footnotes section. All of the

data were reported using the metric system since it is universally used and is the most

convenient when data are obtained from many different sources.


Results
Emergy Evaluation of Arkansas

Energy systems diagram

The overview model of the state of Arkansas is shown in Figure A-4. The main

outside environmental and purchase inputs are shown, as well as the main internal

components and processes in the state. On the left of the diagram are the environmental

and rural systems with their main energy sources (sun, wind, rain, rivers, and geological

processes). These are production areas including forests, grasslands, wetlands, and

agricultural crops. On the right side of the diagram are the consumer sectors. These are

mainly located in towns and cities. Energy inputs purchased from outside including fuels,

food, fertilizers, machinery, goods and services, together with inputs from within the state

constitute the non-renewable resources basis used to power the economy. Arkansas

exports include agricultural crops, machinery, chemicals, and meat. Additional energy

flows outside the state include waste products. Summary diagrams with the aggregated

pathways for evaluating the overall energy use in the state are presented in Figure A-5.












































Figure A-4. Energy systems diagram for the state of Arkansas with main inputs, internal components, and pathways.







A-13


Indigenous (I) 1093.28 1315.26
sources Arkansas exports (Y)
R+NO+N1 N2+P1E



(b)




Figure A-5. Summary diagrams of emergy flows in the state of Arkansas in 2001. (a)
aggregated diagram; (b) three-arm diagram aggregated further into three
flows: indigenous resources (I), imports (F), and exports (Y).






A-14


Emergy evaluation table

The emergy evaluation of the environmental inputs, imports, and exports for

Arkansas are presented in Table A-4. For 2001 the total emergy used by the state's

economy was 2.73 E23 sej. Contributions to the state's real wealth are shown in graph

form in Figure A-6. The contributions are organized from left to right according to their

position in the energy hierarchy.

The major environmental contribution to the state came from the rain's chemical

potential energy, which accounts for 58% of the total renewable inputs into the system.

Agriculture and livestock production (including poultry) accounted for 94% of the

indigenous renewable energies. Soil losses were high, and together with electricity and

natural gas, they were the most important non-renewable resources from within the

system. Among the purchased inputs, fossil fuels (gas, coal, oil and its derivates) were the

major inputs driving the economy together with the services of imports. Fuels represented

44% of the state's imports and services account for 38% of the total imports. Fuel imports

reflect the increasing dependency on outside sources of fossil fuels, as the state's

production of coal and oil has decreased over the last two decades.

Organic chemicals and meat were the top export products from the state; machinery

and transportation equipment as well as agricultural products followed. The services

associated with the state's exports accounted for 88% of the total exported emergy.

Emergy indices

The indices derived from the emergy evaluation table for Arkansas are presented in

Table A-5 and Table A-6. Imported fuels and minerals accounted were the highest

emergy imports in the state while the emergy value of goods and services was highest

among exports (Table A-5). The solar emergy-to-money ratio was 2.83 E12 sej/$.













Table A-4. Emergy evaluation of resource basis for the state of Arkansas for 2001.
Note Item Raw Units Transformity Solar Emergy EmDollars
(sej/unit)* (E20 sej) (E9 US$)


RENEWABLE RESOURCES:
1 Sunlight (
2 Rain, Chemical
3 Rain, Geopotential
4 Wind, Kinetic Energy
5 Inflow River Geopotential
6 Inflow River Chemical Potential
7 Earth Cycle

INDIGENOUS RENEWABLE ENERGY:
8 Hydroelectricity
9 Agriculture Production
10 Livestock Production
11 Fisheries Production
12 Fuelwood Production
13 Forest Extraction

NONRENEWABLE SOURCES FROM WITHIN
SYSTEM:
14 Natural Gas
15 Oil
16 Coal
17 Minerals (Bromine)
18 Soil Losses
19 Topsoil Losses
20 Groundwater
21 Electricity


6.48E+20
8.08E+17
6.03E+15
1.38E+18
1.06E+17
6.44E+15
1.38E+17


).17E+15
1.34E+17
1.27E+16
1.88E+14
).00E+00
).09E+16



1.84E+17
1.63E+16
5.08E+14
1.75E+11
1.94E+13
1.31E+16
1.69E+16
.32E+16


1.00E+00
3.05E+04
4.70E+04
2.45E+03
4.70E+04
8.14E+04
5.80E+04


3.36E+05
3.36E+05
3.36E+06
3.36E+06
2.21E+04
2.21E+04


8.06E+04
8.90E+04
6.69E+04
2.20E+10
1.68E+09
7.40E+04
1.60E+05
3.36E+05


6.5
246.4
2.8
33.9
49.8
5.2
79.9


30.8
448.8
426.4
6.3
0.0
20.1


1.1
16.3
15.5
0.2
0.0
0.7
0.0


5.2
1.5
0.0
1.4
11.8
0.4
2.7
6.3


148.3
41.2
0.3
38.5
325.7
9.7
75.0
178.8













Table A-3. Continued.
Note Item Raw Units Transformity Solar Emergy EmDollars
(sej/unit)* (E20 sej) (E9 US$)


IMPORTS AND OUTSIDE SOURCES:
22 Fuels
23 Metals
24 Fertilizers
25 Agricultural Products
26 Meat, Fish & Related Foods
27 Plastics & Rubber
28 Chemicals (incl. pesticides)
29 Finished Materials
30 Machinery & Transportation
Equipment
31 Services in Imports
32 Tourism

EXPORTS:
33 Agricultural Products
34 Meat
35 Paper/Paperboard
36 Fuels
37 Metals
38 Minerals (bromine)
39 Organic Chemicals
40 Machinery & Transportation
Equipment
41 Plastics
42 Services in Exports


* Transformity based on a global renel


8.79E+17
1.02E+11
2.32E+11
2.27E+15
1.57E+14
2.56E+15
1.92E+11
4.32E+11

1.61E+12
3.91E+10
3.81E+09


3.92E+15
1.06E+15
2.16E+11
0.00E+00
1.88E+11
3.08E+10
2.00E+1 1


8.55E+04
7.75E+09
2.19E+10
3.36E+05
3.36E+06
1.11E+05
2.49E+10
1.89E+09

6.70E+09
1.66E+12
1.66E+12


3.36E+05
3.36E+06
3.69E+09
0.00E+00
6.13E+09
2.20E+10
2.49E+10


751.3
7.9
50.8
7.6
5.3
2.8
47.6
8.1

108.0
648.9
63.3


26.5
0.3
1.8
0.3
0.2
0.1
1.7
0.3

3.9
23.6
2.3


13.2
35.6
8.0
0.0
11.5
6.8
49.8


2.91E+11 g 6.70E+09 19.5 0.7
7.76E+14 J 1.11E+05 0.9 0.0
3.89E+10 $ 2.75E+12 1071.4 38.9
able emergy flow of 15.83E24 sej/yr (Odum et al. 2000).







A-17


Table A-3. Continued
Footnotes:


References:


RENEWABLE RESOURCES:
1 SOLAR ENERGY:


Cont Shelf Area = 0.OOE+00 m2
Land Area = 1.38E+11 m2
Insolation = 1.41E+02 Kcal/cm2nr/yr
Albedo = 0.20 (% given as decimal)
Energy(J) = (area incl. shelf)(avg. insolation)(1-albedo)
= (_m2)(_Cal/cm2/y)(E+04cm2/m2)( 1 -albedo)(4186J/kcal)
6.48E+20 J/yr
Transformity = 1.00+00 sej/J
2 RAIN, CHEMICAL POTENTIAL ENERGY:
Land Area = 1.38E+11 m2
Cont Shelf Area = 0.OOE+00 m2
Rain (land) = 1.21 m/yr
Rain (shelf) = 0.00 m/yr
Evapotranspiration rate = 1.19 m/yr


Energy (land) (J)


(area)(E
( m2)(
8.


Energy (shelf) (J) = (area of
0.
Total energy (J) = 8.'
Transformity = 3.
3 RAIN, GEOPOTENTIAL ENERGY:
Area = 1.
Rainfall =
Avg. Elev. =
Runoff rate =
Energy(J) = (area
= (_m
6.
Transformity = 4.
4 WIND ENERGY:
Area = 1.
Density of air = 1.
Avg. annual wind velocity = 3.
Geostrophic wind = 5.
Drag coeff. = 2
Energy (J) = (area
= (_m
Energy(J) = 1.
Transformity = 2.
5 RIVER GEOPOTENTIAL:


ivapotranspiration)(Gibbs no.)
_m)(1000kg/m3)(4.94E3J/kg)
08E+17 J/yr
* shelf)(Rainfall)(Gibbs no.)
OOE+00 J/yr
08E+17 J/yr
05E+04 sej/J

38E+11 m2


1.21 m
198.12 m (650 feet) (
0.02 % (percent, given as a decimal)
)(rainfall)(% runoff)(avg. elevation)(gravity)
)(_m)(_%)(1000kg/m3)(_m)(9 in
03E+15 J/yr
70E+04 sej/J

38E+11 m2
23E+00 kg/m3
04E+00 mps (Data for Little
07E+00 mps (Observed winds are ab
.OOE-03
)(air density)(drag coefficient)(velocity3)
)(1.3 kg/ m')(1.00 E-3)(_mps)(3.14 E7 s/yr)
38E+18 J/yr
45E+03 sej/J


Major inflowing rivers: Arkansas and Mississippi rivers
Flow in Arkansas River = 1.02E+03 m3/s
Elevation in = 2.10E+02 m
Elevation out = 3.05E+01 m
Energy (J) = (volume)(density)(hei4
= (_m3)(1.0E3kg/m3)(_
Energy (J) = 5.66E+16 J/yr
Flow in Mississippi River = 1.33E+04 m3/s
Elevation in = 4.50E+01 m


ht in-heig
m - m)


(At Dardanelle, AR, data for 2001; www.usgs.gov)
(Odum et al. 1998)

ght out)(gravity)
(9.8 in sc )

(Odum et al. 1998)
(Odum et al. 1998)


(AGC; www.state.ar.us/agc)
(Odum et al. 1998)
(After www.nasa.gov)



(Odum 1996)



(www.noaa.gov)

(Odum et al. 1998)






(Odum et al. 2000)



Carpenter & Provorse 1998)




(Odum 2000)


(Odum et al. 1998)
Rock, 2000; www.noaa.gov)
out 0.6 of geostrophic wind)
(Garrat 1977)



(Odum et al. 2000)







A-18


Elevation out =
Energy (J) = (vo
= (_
Energy =
Energy used in the State =
Total energy =
Transformity =
6 RIVER CHEMICAL POTENTIAL:
Gibbs free energy = [(8.
Dissolved solids in =
Dissolved solids out =
Gibbs free energy in =
Gibbs free energy out =
Flow in Arkansas River =
Energy (J) = (vol


Energy in
Energy out
In- Out
Flow in Mississippi River
Energy in
Energy out
In- Out
Energy Used in the State
Total Energy
Transformity
7 EARTH CYCLE:
Land area
Heat flow
Energy (J)
Energy (J)


Transformity


2.10E+01 m
lume)(density)(height in-height out)(
m3)(1.0E3kg/m3)(m - _m)(9.8 m/!
9.86E+16 J/yr
1.93E+16 J/yr
1.06E+17 J/yr
I.70E+04 sej/J

3143 J/mol/deg)(288 K)/(18 g/mol)]
2.00E+02 ppm
4.OOE+02 ppm
1.71E+00 J/g
1.69E+00 J/g
1.02E+03 m3/s
lume)(density)(Gibbs free energy)
n3/s)(1.0E3 kg/ m3)(_J/g)
1.52E+17 J/yr
1.51E+17 J/yr
8.57E+14 J/yr
1.33E+04 m3/s
1.98E+18 J/yr
1.97E+18 J/yr
1.12E+16 J/yr
5.58E+15 J/yr
6.44E+15 J/yr
8.14E+04 sej/J


(Assumed 1/2 used after Odum et al. 1998)

(Odum et al. 2000)

* In [(le6 - Solutes)ppm)/965000]
(Odum et al. 1998)
(Odum et al. 1998)













(Assumed 1/2 used)

(Odum 1996)


1.38E+11 m2
1.00E+06 J/m2
(area)(Heat flow)
(_m2)(1.00E6 J/m2)
1.38E+17 J/yr
5.80E+04 sej/J


(Odum et al. 1998)


(Odum 2000)


INDIGENOUS RENEWABLE ENERGY
8 HYDROELECTRICITY:
Kilowatt Hrs/yr =


2.55E+09 KwH/yr


Energy (J) = (Energy production)(energy content)
Energy (J) = (_KwH/yr)(3.6 E6 J/KwH)
9.17E+15 J/yr


Transformity =
9 AGRICULTURAL PRODUCTION:
Rice = z

Sorghum = 3
Cotton =
Soybeans =
Corn=
Wheat =
Total production =
Energy (J) = (To
Energy (J) = (_

Transformity =


3.36E+05 sej/J


I.67E+06 MT/yr

3.71E+05 MT/yr
3.99E+05 MT/yr
2.48E+06 MT/yr
6.81E+05 MT/yr
1.37E+06 MT/yr
).97E+06 MT/yr (dry mass, 20% humidity)
tal production)(energy content)
MT/yr)(1E06 g/MT)(80%)(4.0 kcal/g)(4186 J/kcal)
1.34E+17 J/yr
3.36E+05 sej/J


(APSC, 2001 data;
www.arkansas.gov/psc)



(Odum 1996)

(USDA, 2001data;
www.nass.usda.gov/ar)










(Brown & McClanaham
1996)







A-19


10 LIVESTOCK PRODUCTION:
Cattle =
Pigs =
Poultry =
Livestock production =
Energy (J) =
Energy(J) =

Transformity =
11 FISHERIES PRODUCTION:
Fish Catch =


3.36E+05 MT/yr
5.13E+04 MT/yr
2.64E+06 MT/yr
3.03E+06 MT/yr (80% humidity
(Total production)(energy content)
( MT/yr)(1E+06 g/MT)(20%)(5.0 KCa
1.27E+16 J/yr
3.36E+06 sej/J

4.49E+04 MT/yr (80% humidity


Energy (J) = (Total production)(energy content)
Energy (J) = ( MT)(1E+06 g/MT)(5.0 KCal/g i 2 "**..
1.88E+14 J/yr


Transformity =
12 FUELWOOD PRODUCTION:
Fuelwood Prod =
Energy (J) =
Energy (J) =

Transformity =
13 FOREST EXTRACTION:
Harvest =
Energy (J) =
Energy (J) =

Transformity =


3.36E+06 sej/J

0.OOE+00 m3
(Total production)(energy content)
( m3)(0.5E6g/ m3)(3.6 kcal/g)(80%)(41
0.OOE+00 J/yr
2.21E+04 sej/J

1.51E+07 m3
(Total production)(energy content)
( m3)(0.5E+06 g/ mi x, , ..i ..6 kcal/g)
9.09E+16 J/yr
2.21E+04 sej/J


(USDA, 2001data; www.nass.usda.gov/ar)


)

l/g)(4186 J/KCal)

(Brown & McClanaham 1996)

) (USDA, 2001data;
www.nass.usda.gov/ar)

i4186 J/KCal)

(Brown & McClanaham 1996)



86 J/kcal)

(Romitelli 2000)


(4186 J/k


(After Mehmood & Pelkki 2005)

cal)

(Romitelli 2000)


NONRENEWABLE RESOURCE USE FROM WITHIN THE STATE


14 NATURAL GAS:
Consumption
Energy (J)
Energy (J)


15 OIL:


16 COAL:


Transformity

Consumption
Energy (J)
Energy (J)

Transformity

Consumption
Energy (J)
Energy (J)


Transformity
17 MINERALS (Bromine):
Consumption


(ADED 2003)


4.90E+06 m3/yr
m3/yr)(energy content)
m3/yr)(8966 kcal/ m3)(4186 J/kcal)
1.84E+14 J/yr
4.80E+04 sej/J

7.59E+06 barrels
barrel/yr)(energy content)
barrel/yr)(6.1E9 Joules/barrel)
4.63E+16 J/yr
8.90E+04 sej/J


1.75E+04 MT/yr
_MT/yr)(energy content)
_MT/yr)(2.9E+10 J/MT)
5.08E+14 J/yr
6.69E+04 sej/J


1.75E+05 MT/yr


Mass (g) = ( E5 MT)(1E6 g/MT)
1.75E+11 g/yr
Transformity (weighed) = 2.20E+10 sej/g


(Odum 1996)

(ADED 2003)


(Odum 1996)


(AGC; www.state.ar.us/agc)


(Odum 1996)


(AGC;
www.state.ar.us/agc)


(Odum et al. 1998)







A-20


18/19 TOPSOIL AND SOM:
Harvested cropland
Soil loss
Average organic content (%)
Energy (J)

Mass (g)
Transformity Soil
Transformity SOM
20 GROUNDWATER:
Groundwater consumption


Tr


3.88E+10 m2
5.00E+02 g/m2/yr
3 %
(_ g/ m2/yr)( _i -".. organic)(5.4 Kcal/g)(4186 J/Kcal)
1.31E+16 J/yr
1.94E+13 g/yr
1.68E+09 sej/g
7.40E+04 sej/J


6.92E+03 Mgal/day


9.57E+09 m'/yr
Energy (J) = chemical potential of groundwater
Energy (J) = (volume)(density)(Gibbs no.)
= (_m3/yr)(1.0E6 g/ m3)(4.94J/g)
4.69E+16 J/yr
ansformity = 1.60E+05 sej/J


21 ELECTRICITY:
Kilowatt Hrs/yr
Energy (J)
Energy (J)

Transformity


1.48E+10 KwH/yr
(Energy production)(energy content)
(_KwH/yr)(3.6 E6 J/KwH)
5.32E+16 J/yr
1.60E+05 sej/J


IMPORTS OF OUTSIDE ENERGY SOURCES:
22 FUELS:


Total natural gas used:
Used-produced:
Energy (J):
Total oil used:
Used-produced:
Energy (J):
Total coal used:
Used-produced:
Energy (J):
Natural gas:
Oil derived fuels:
Coal:

Transformity (weighed):


(www.ers.usda.gov)
(Odum et al. 1998)


(Odum 1996)
(Brown & Bardi 2001)


(http://water.usgs.gov, data for 2000)





(Odum et al. 1998)

(EAI, 2001 data; www.arkansas.gov/psc)



(Odum 1996)


(EIA, State Energy Data 2001; www.eia.doe.gov)


7.11E+09 m3/yr
7.10E+09 m3/yr
(_m3/yr)(8966 kcal/m3)(4186 J/kcal)
7.10E+07 barrels
6.34E+07 barrels
(_ barrel/yr)(6.1E9 Joules/barrel)
1.41E+07 MT/yr
1.41E+07 MT/yr
(_ MT/yr)(2.9E10 J/Mt) Transformity
2.67E+17 J/yr 5.88E+04 sej/J
3.87E+17 J/yr 1.11E+05 sej/J
4.09E+17 J/yr 6.69E+04 sej/J
1.06E+18 J/yr
8.09E+04 sej/J


23 METALS:
Estimates as fraction of US imports of metals in 2001.


Aluminum unwrought:
Aluminum worked:
Iron ore :
Steel:
Copper wire:
US imports :
Fraction:

State imports :
Mass (g):

Transformity (weighed):


2.68E+06
8.77E+05
4.68E+06
2.18E+06
3.16E+05
1.07E+07
9.50E-03


MT/yr
MT/yr
MT/yr
MT/yr
MT/yr
MT/yr


(Romitelli 2000)
(Odum 1996)
(Odum 1996)


(Data from UN Statistics Division; http://unstats.un.org)
Transformity


1.43E+09 sej/g
1.25E+10 sej/g
1.44E+09 sej/g
4.13E+09 sej/g
1.66E+11 sej/g
7.75E+09 sej/g


(Odum 1996)
(Brown & Buranakam 2000)
(Odum 1996)
(Brown & Buranakam 2000)
(Odum 1996)


(Based on Population: State/US; US Census Bureau;
http://quickfacts.census.gov)


1.02E+05 MT/yr
(_MT/yr)(1E6 g/MT)
1.02E+11 g/yr
7.75E+09 sej/g







A-21


24 FERTILIZERS:
Estimates were done considering the use of fertilizer per crop and the area planted by crop in the State.
Fertilizer used/ha N P205 K20 Area
Kg/ha Kg/ha Kg/ha ha
Sorghum 37.8 3.4 0.9 7.08E+04 (Odi
Wheat 89.7 1.12 0 4.45E+05
Rice 134.5 0 33.6 6.60E+05 (www.na!
Cotton 40 16 17 4.37E+05
Soybeans 5.61 0 33.6 1.17E+06
Consumption Transformity
Phosphorus = 7.73E+03 MT/yr 2.99E+10 sej/g
Potash = 6.91E+04 MT/yr 2.92E+09 sej/g
Nitrogen = 1.55E+05 MT/yr 7.73E+09 sej/g
Total consumption = 2.32E+05 MT/yr 2.19E+10 sej/g


Mass (g):


metal. 1998)

ss.usda.gov/ar)



(Odum 1996)
(Odum 1996)
(Odum 1996)


(_E6 MT/yr)(1E6 g/MT)
2.32E+11 g/yr


Transformity (weighed) = 2.19E+10 sej/g
25 AGRICULTURAL PRODUCTS:
Estimates were done as fraction of US imports of agricultural products in 2001.
US imports = 2.04E+07 MT/yr


Fraction


9.50E-03


(UN Statistics Division;


http://unstats.un.org)
(Based on Population: State/US; US Census Bureau;
http://quickfacts.census.gov)


State imports = 1.94E+05 MT/yr
Energy (J) = (_ MT/yr)(lE6g/MT)(3.5 Kcal/g)(4186 J/Kcal)(80%)
2.27E+15 J/yr
Transformity = 3.36E+05 sej/J
26 MEAT, FISH & RELATED FOODS:
Estimates were done as fraction of US imports of meat and fish products in 2001.
US imports = 3.58E+06 MT/yr


Fraction

State imports
Energy (J)


9.50E-03


(Brown & McClanaham 1996)


(UN Statistics Division;


http://unstats.un.org)
(Based on Population: State/US; US Census Bureau;
http://quickfacts.census.gov)


3.41E+04 MT/yr
(_MT/yr)(1E6 g/MT)(5 Kcal/g)(4186 J/Kcal)(0.22 protein)
1.57E+14 J/yr


Transformity = 3.36E+06 sej/J
27 PLASTICS & RUBBER:
Estimates were done as fraction of US imports in 2001.
Imports = 3.01E+10 $/yr
Average price = 3.34E+03 $/MT
Imports = 8.99E+06 MT/yr
Fraction = 9.50E-03


State imports
Energy (J)


8.54E+04 MT/yr
(_ MT/yr)(1000 Kg/MT)(30.0E6J
2.56E+15 J/yr


Transformity = 1.11E+05 sej/J
28 CHEMICALS:
Estimates were done as fraction of US imports in 2001.
Imports = 2.02E+07 MT/yr


Fraction


9.50E-03


(Bri


own & McClanaham 1996)


(UN Statistics Division; http://unstats.un.org)


(Based on Population: State/US; US Census Bureau;
http://quickfacts.census.gov)

J/kg)

(Odum 1996)


(UN Statistics Division;
http://unstats.un.org)
(Based on Population: State/US; US Census Bureau;
http://quickfacts.census.gov)


1.92E+05 MT/yr


State imports







A-22


Mass (g)= (MT/ yr)(1E6g/MT)
1.92E+11 g/yr
Transformity = 2.49E+10 sej/g (as pesticides)

29 FINISHED MATERIALS (lumber, paper, textiles, glass, others):
Estimates were done as fraction of US imports in 2001.
Imports (lumber) = 2.92E+07 MT/yr


Fraction

State imports
Imports (paper)
Price
Imports (paper)
Fraction

State imports


9.50E-03

2.77E+05
1.57E+10
9.62E+02
1.63E+07
9.50E-03


MT/yr
$/yr
$/MT
MT/yr


(Brown and Arding 1991,
in Brandt-Williams 2001 )


(UN Statistics Division;


http://unstats.un.org)
(Based on Population: State/US; US Census Bureau;
http://quickfacts.census.gov)




(Based on Population: State/US; US Census Bureau;
http://quickfacts.census.gov)


1.55E+05 MT/yr


Lumber = 2.77E+05 MT/yr
Paper = 1.55E+05 MT/yr
Others = 0.0 MT/yr
Imports = 4.32E+05 MT/yr
Energy (J) = (_ MT/yr)(1E6g/MT)
4.32E+11 g/yr
Transformity (weighed) = 1.89E+09 sej/g
30 MACHINERY, TRANSPORTATION, EQUIPMENT:
Estimates were done as fraction of US imports in 2001.
Imports = 5.09E+11 $/yr
Price = 3.00E+03 $/MT
Imports = 1.70E+08 MT/yr
Fraction = 9.50E-03


State Imports =
Mass (g) =

Transformity
31 IMPORTED SERVICES:


1.61E+06 MT/yr
(_E4 MT/yr)(lE6g/MT)
1.61E+12 g/yr
6.70E+09 sej/g


Estimates were done as fraction of US imports in 2001.
Dollar value (US) = 1.18E+12 $/yr


Fraction =

Foreign state imports =
Relative imports from
other states =


Federal spending received

Total $ value of imports
World Emergy/$ ratio
32 TOURISM:
Dollar Value
World Emergy/$ ratio


9.50E-03

1.12E+10 $/yr

1.12E+10 $/yr

1.67E+10 $/yr

3.91E+10 $/yr
1.66E+12 sej/$

3.81E+09 $US
1.66E+12 sej/$


Transformity
8.80E+08 sej/g
3.69E+09 sej/g
5.85E+09 sej/g
1.89E+09 sej/g


(Brown & Buranakam 2000)
(Luchi & Ulgiati 2000)
(Brown & Buranakam 2000)


(UN Statistics Division; http://unstats.un.org)
(Assumed)

(Based on Population: State/US; US Census
Bureau; http://quickfacts.census.gov)



(Brown & Bardi 2001)


(UN Statistics Division;
http://unstats.un.org)
(Based on Population: State/US; US Census
Bureau; http://quickfacts.census.gov)


(Estimated based on a 2.51 times increase between 1992
and 2001. Data for 1992 from Odum et al (1998))


(Tax Foundation 2004;
http://www.taxfoundation.org/taxdata/)



(ADPT; hIp \ \ \ .arkansas.com)







A-23


EXPORTS OF ENERGY, MATERIALS AND SERVICES
33 AGRICULTURAL PRODUCTS:


Average price for US
exports (2001) =
State exports =
State exports =
Energy (J) =

Transformity =
34 MEAT:
Average price for US
exports (2001) =
State exports =
State exports =
Energy (J) =

Transformity =
35 PAPER & PAPERBOARD:
Average price for US
exports (2001) =
State exports =
State exports =
Energy (J) =

Transformity =
36 FUELS:
Natural gas =
Energy (J) =
Oil derived fuels =
Energy (J) =
Coal =
Energy (J) =
Natural gas =
Oil derived fuels =
Coal =

Transformity =
37 METALS:
Price US exports
aluminum (2001) =
State exports =
State exports =
Price US exports Iron
(2001) =
State exports =
State exports =
Price US exports steel
(2001) =
State exports =
State exports =

Aluminum ore (Bauxite) =
Aluminum =
Iron =
Steel =
Copper wire =


(Estimated as raw cereals after UNSD;
2.74E+02 $/MT http://unstats.un.org)
9.17E+07 $/yr (ADED 2003)
3.35E+05 MT/yr
(_MT)(1E+06 g/MT)(80%)(3.5 Cal/g)(4186 J/Cal)
3.92E+15 J/yr
3.36E+05 sej/J (Brown & McClanaham 1996)

(Estimated after UN Statistics Division;
2.08E+03 $/MT http://unstats.un.org)
4.78E+08 $ (ADED 2003)
2.30E+05 MT/yr
(_MT)(1E+06 g/MT)(5 Cal/g)(4187 J/Cal)(0.22 protein)
1.06E+15 J/yr
3.36E+06 sej/J (Brown & McClanaham 1996)


9.62E+02 $/MT
2.08E+08 $
2.16E+05 MT/yr
(_MT)(1.0E+06 g/MT)
2.16E+11 g/yr
3.69E+09 sej/g


(UN Statistics Division; http://unstats.un.org)
(ADED 2003)



(Luchi & Ulgiati 2000)


0.OOE+00 m3/yr
(_ m3/yr)(8966 kcal/m3)(4186 J/kcal)
0.OOE+00 L/yr
( L/yr)(1.14E4kcal/L)(4186 J/kcal)


0.00E+00 MT/yr
( MT/yr)(2.9E10 J/MT)


0.OOE+00
0.OOE+00
0.OOE+00
0.OOE+00
0.OOE+00


6.15E+02
3.97E+07
6.46E+04

5.74E+02
3.54E+07
6.17E+04

5.74E+02
3.54E+07
6.17E+04

0.OOE+00
6.46E+04
6.17E+04
6.17E+04
0.OOE+00


J/yr
J/yr
J/yr
J/yr
sej/J


$/MT
$/yr
MT/yr

$/MT
$/yr
MT/yr

$/MT
$/yr
MT/yr

MT/yr
MT/yr
MT/yr
MT/yr
MT/yr


Transformity
5.88E+04 sej/J
1.11E+05 sej/J
6.69E+04 sej/J


(Aluminum hydroxide)


(Romitelli 2000)
(Odum 1996)
(Odum 1996)


(UN Statistics Division;
http://unstats.un.org)
(ADED 2003)


(UN Statistics Division;
(Primary form of iron) http://unstats.un.org)
(Assumed 50% of State's exports; ADED 2003)
(Reported for iron and steel)
(UN Statistics Division;
(Primary form of steel) http://unstats.un.org)
(Assumed 50% of State's exports; ADED 2003)
(Reported for iron and steel)
Transformity
1.43E+09 sej/g (Odum 1996)
1.25E+10 sej/g (Brown & Buranakam 2000)
1.44E+09 sej/g (Odum 1996)
4.13E+09 sej/g (Brown & Buranakam 2000)
1.66E+11 sej/g (Odum 1996)







A-24


Others =
Exports =
Mass (g) =

Transformity (weighed) =
38 MINERALS (Bromine):
Exports =
Mass (g) =

Transformity =
39 CHEMICALS (ORGANIC):
Average price for US
exports (2001) =
State exports =
State exports =
Mass (g) =

Transformity =


0.OOE+00 MT/yr
1.88E+05 MT/yr
( MT)(1E6 g/MT)
1.88E+11 g/yr
6.13E+09 sej/g

3.08E+04 MT/yr
( E5 MT)(1E6 g/MT)
3.08E+10 g/yr
2.20E+10 sej/g

8.92E+02 $/MT

1.79E+08 $/yr
2.00E+05 MT/yr
( MT)(1E6 g/MT)
2.00E+11 g/yr
2.49E+10 sej/g


40 MACHINERY, TRANSPORTATION, EQUIPMENT:


Aver
Stat
Stat


Trai


age price = 3.00E+03 $/MT
e exports = 8.72E+08 $/yr
exports = 2.91E+05 MT/yr
Mass (g) = (MT/yr)(lE6g/MT)
2.91E+11 g/yr
isformity = 6.70E+09 sej/g


41 PLASTICS:
Average price for US
exports (2001) =
State exports =
State exports =
Energy (J) =

Transformity =
42 SERVICES IN EXPORTS:
Foreign exports =
Relative exports to other
states =
Federal tax paid =


1.68E+09 sej/g
6.13E+09 sej/g


(15% of production)


(Odum 1996)


(AGC; www.state.ar.us/agc)


(Odum et al. 1998)

(Estimated after UN Statistics Division;
http://unstats.un.org)
(ADED 2003)


(as pesticides)


3.34E+03 $/MT
8.65E+07 $
2.59E+04 MT/yr
(_MT/yr)(1000 Kg/MT)(30.0E6J/kg)
7.76E+14
1.11E+05 sej/J


2.91E+09 $/yr


3.60E+10
1.24E+10


(Brown and Arding 1991, in
Brandt-Williams 2001)


(Assumed)
(Machinery, aircraft, vehicles, 2001; ADED 2003)



(Doherty 1995 in Brown and Bardi 2001)


(UN Statistics Division; http://unstats.un.org)
(ADED 2003)


(Odum 1996)


(ADED 2003)
(Estimated based on a 2.21 times increase between 1992
and 2001. Data for 1992 from Odum et al [1998])
(Tax Foundation 2004;
http://www.taxfoundation.org/taxdata/)


Tota $ vlue f eport 3.8E+10 $/y


Total $value of exl~ort


3.89E+10 $/vr







A-25


700
z, 600
"3 500
I 400
300
8 200

0

, . .*-* o* o , , ,,, ,. 'o -" "" � , ' . "






Figure A-6. Emergy signature of the environment and the economy of Arkansas in 2001.


The same ratio for the U.S. for 2001 was estimated at about 1.00 E12 sej/$. Since the

U.S. as a whole is more developed than the state of Arkansas alone, the differences in

values reflect this distinction.

The emergy used from home sources index showed that Arkansas is only 40%

sufficient depending mostly on imported emergy (Table A-5).The emergy use per person

is a measure of the standard of living in emergy terms. A person living in a rural

environment may have a higher emergy use than a person living in a city. For Arkansas

this ratio was 1.01 E17 sej/person, which is higher than for the average person for the

entire U.S. in the year 20001. Again, since the U.S. as a whole is more developed than

the state of Arkansas alone, the different values reflect this difference. On a per area

basis, the emergy use for the state was 1.98 E16 sej/ha.


1 Unpublished data, H.T. Odum Center for Environmental Policy, University of Florida.







A-26


Table A-5.

Variable

R

N

NO

N1

N2

F

G

I

P2I

E

P1E

X

P2

P1


Summary of flows for Arkansas, 2001.

Item

Renewable sources (rain, tide, earth cycle)

Non-renewable resources from within State

Dispersed Rural Source

Concentrated Use

Exported without Use

Imported Fuels and Minerals

Imported Goods

Dollars Paid for Imports

Emergy of Services in Imported Goods & Fuels

Dollars Received for Exports

Emergy Value of Goods and Service Exports

Gross State Product

World emergy/$ ratio, used in imports

State Emergy/$ ratio


3.91E+10


648.90


3.89E+10


1247.36


9.65E+10


1.66E+12

2.83E+12


The emergy yield ratio (Y/F) was calculated as 0.80 (see Figure A-4[b]), which

indicates that Arkansas uses much more resources from the economy than it contributes

to it; Arkansas is a net importer of emergy. The emergy investment ratio (F/I) was 1.50.

This index measures the intensity of the economic development and the loading of the

environment. The reference value usually used for comparison is the investment ratio for

the U.S., which tends to be 7 or higher. High values suggest a more developed economy

and a high level of environmental stress. Accordingly, and since the loading ratio for

Arkansas is relatively low, the free contributions from the environment to the state's


Dollars


Solar Emergy
(E20 sej/yr)
249.27

264.50

436.79

407.16

68.08

759.22

230.30






A-27


economy are relatively large. A more developed state like Florida has an emergy

investment ratio of about 7.

Table A-6. Emergy indices for Arkansas.
Item Name of Index Expression Quantity

1 Renewable emergy flow R 2.49E+22
2 Flow from indigenous non-renewable N 2.64E+22
reserves
3 Flow of imported emergy F+G+P2I 1.64E+23

4 Total emergy inflows R+N+F+G+P2I 2.15E+23

5 Total emergy used, U NO+N1+R+F+G+P2I 2.73E+23

6 Total exported emergy PIE 1.25E+23
Fraction emergy use derived from (NO+NI+R)/U 0.40
home sources
8 Imports minus exports (F+G+P2I)-(N2+B+P1E) 3.23E+22

9 Export to Imports (N2+P1E)/(F+G+P2I) 0.80

10 Fraction used, locally renewable R/U 0.09

11 Fraction of use purchased (F+G+P2I)/U 0.60

12 Fraction imported service P2I/U 0.24

13 Fraction of use that is free (R+NO)/U 0.25

14 Ratio of concentrated to rural (F+G+P2I+N1)/(R+NO) 2.98

15 Use per unit area, Empower Density U/(area ha) 1.98E+16

16 Use per person U/population 1.01E+17

17 Renewable carrying capacity at STATE POPULATION= 2.70E+06
present living standard (R/U) (population) 2.46E+05
18 Developed carrying capacity at same 8(R/U)(population) 1.97E+06
living standard
19 Ratio of use to GSP, emergy/dollar PI=U/GSP 2.83E+12
ratio
20 Ratio of electricity to use (el)/U 1%

21 Fuel use per person fuel/population 2.78E+16






A-28


Emergy Evaluation of Resource Basis for the State of Arkansas

With an annual rainfall of 1.21 meters in 2001, the rain-chemical potential energy

was the highest source of natural renewable energy in Arkansas. Odum et al. (1998) also

pointed out the significance of this source of energy to the state's economy and noted the

high rates of evapotranspiration during the summer and early fall months due to the

abundant rain usually present in the state.

The relative richness in non-renewable resources of Arkansas was also noted by

Odum et al. (1998) and was confirmed by this study. The results showed that even though

Arkansas has a significant amount of resources, there were no marked changes in the

quantities of indigenous renewable and non-renewable resources used in the state over a

period of 10 years. Both agricultural and livestock products (including poultry) remained

the most important components of the annual indigenous renewable emergy flow in the

state. Fossil fuels and electricity from within the state had total annual emergy flows of

189.9 E20 sej and 232.68 E20 sej, respectively. These values are similar to those reported

by Odum et al. (1998).

The agricultural cost in terms of soil erosion continued to be high. This study

reported a total of 325.7 E20 sej in soil losses, which is more than twice that reported in

Odum et al. (1998). The difference might be the result of on increase in croplands

between the two time periods. Overall, in 2001 soil losses represented 40% of all the

non-renewable emergy used from within the state, suggesting that Arkansas agricultural

production and its contribution to its economic growth comes at the expense of this

important natural stock.

The Arkansas gross state product increased from 39 billion dollars in 1990 to 96.5

billion dollars in 2001. Since there was little change to the resources basis of the






A-29


Arkansas economy from within the state during these years, the growth of the state's

economy was possibly mostly due to an increase in the imports of non-renewable

resources, particularly of fossil fuels that accounted for 44% of all the emergy brought in

to the system in 2001. The ratio of exports to imports for 2001 was 0.80. The emergy

used from state sources was 40% of the total emergy used and the emergy used from

home sources index showed that Arkansas was only 39% sufficient in 2001, depending

mostly on imported emergy. Together these figures show that Arkansas is a net emergy

importer state. This is a significant change from that reported by Odum et al. (1998).

Using 1990 data, Odum et al.'s study showed that Arkansas was a net emergy exporter

state.

The results for exported emergy that were reported by Odum et al. (1998) and the

results of this study show some difference in the number of items included in the analysis

and in the way total energy values were calculated. This study included more items. We

used the exports dollar value of each product from state-level data and the average price

for U.S. exports for each item in 2001 to obtain data on quantities exported. As such,

emergy exports accounted only for the emergy in the international trade, excluding

exports to other states. However, when calculating the emergy of the services in exports,

a relative dollar value of the exports to other states was considered. The total emergy

reported as exports in the Odum et al. (1998) study was 1231 E20 sej, while the total

emergy exported according to this study was 1247.18 E20 sej. The services in exports

accounted for 77% and 88% of total exports, respectively.

The emergy investment ratio for 1990 was 0.73. In 2001 this ratio was 1.50. The

ratio value for the state is still lower than that for the U.S., which has an emergy






A-30


investment ratio of around 7.0 and the state may still be considered a mostly rural or less

developed state. However, the difference in the ratio value between the two time periods

suggest that Arkansas is receiving less of their emergy as free contributions from the

environment and that the state is slowly moving towards a more developed economy. In

2001 the economic system invested more emergy from sources outside the state. The

changes in the fraction of emergy used which is locally renewable was 0.15 in 1990 and

0.09 in 2001, also seem to support this trend.

The solar emergy-to-money ratio for Arkansas in 1990 was 3.45 E12 sej/$ and 2.83

E12 sej/$ in 2001. Despite the normal decrease in its value2, the emergy-to-money ratio

of Arkansas was still higher than the ratio for the U.S. in 2001, which was estimated as

about 1.00 E12 sej/$. Once again this value confirms the rather rural nature of the state of

Arkansas. This ratio is an indication of the real wealth (in emergy terms) that a dollar can

buy.

In summary, Arkansas has a diversified economy and is increasingly becoming

more dependent on imported emergy. The emergy evaluation for Arkansas suggests that

the state is slowly moving towards a more developed economy.

Emergy Evaluation of Land Uses of the Bayou Meto Watershed

In the following pages systems diagrams, and emergy evaluation tables of land uses

and land cover systems of the Bayou Meto Watershed are presented.








2 Generally, emergy-to-money ratios decrease over time due to inflation, the increase in
money circulation year to year, and to the increasing efficiency in resource use (Odum
1996).






A-31


Mixed hardwood forest


Figure A-7. Energy systems diagram of a mixed hardwood forest.







A-32


Table A-7. Emergy evaluation table of a mixed hardwood forest, per ha per year.
Data Emergy/unit Solar EMERGY
Note Description (per ha'1 yr 1) (sej/unit) (E13 sej/yr)


Renewable Inputs
1 Sunlight
2 Wind
3 Rain chemical potential
4 Run-in chemical potential
5 Water use (Transpiration)


Gross primary production


7 Total ENERGY

Calculated ratios
8 Empower Density


4.72E+13
5.02E+10
5.98E+10
O.OOE+00
2.62E+10


7.80E+11 J


1.82E+15 sej/ha/yr


Notes:
References:
1 Sunlight, J


Annual


energy (J) = (Avg. Total Annual Insolation J/yr)(Area)(1-albedo)
= ( m2)*(_ Cal/cm2/y)*(E+04cm2/m2)*
(1-albedo)*(4186J/kcal)
Insolation= 1.41E+02 kcal/cm2 /yr
Area= 1.00E+04 m2


Albedo
Annual energy
Emergy per unit input
2 Wind, J


Avg. annual
Geo



Emergy


0.2
4.72E+13 J
1 sej/J


Annual energy = (area)(air density)(drag coefficient)(velocity3)
= ( m2)(1.3 kg/m3)(1.00 E-3)( mps)(3.14 E7 s/yr)
Area= 1.OOE+04 m2
Density of air = 1.23E+00 kg/m3
wind velocity = 3.04E+00 mps (data
)strophic wind = 5.07E+00 mps (observed wii
Drag coeff.= 1.OOE-03
Annual energy = 5.02E+10 J/yr
per unit input = 2.45E+03 sej/J


3 Rain chemical potential, J
Annual energy = (
Avg. precipitation =
Area =
Annual energy =
Emergy per unit input =
4 Run-in chemical potential, J
Annual energy =
Emergy per unit input =
5 Water use (Transpiration), J
Annual energy =
Transpiration =


Annual energy


(Odum et al. 1998)

(After www.nasa.gov)

(Odum 1996)





(Odum et al. 1998)
for Little Rock, 2001; www.noaa.gov)
nds are about 0.6 of geostrophic wind)
(Garrat 1977)

(Odum et al. 2000)


Avg. precip.)*(Area)*(1 E6 g/m2)*(4.94J/g)
1.21 m
1.OOE+04 m2
5.98E+10
3.05E+04 sej/J


(Odum 2000)


0 (Southern mixed hardwood forest complex is not net sink for run-in; Orrell 1998)
8.24E+04 sej/J (Bardi and Brown 2001)


(Transpiration)*(area)*(1E6 g/m3)*(4.94 J/g))
5.30E-01 m/yr
2.62E+10 J/yr


(Orrell 1998)


Flows
6


1.OOE+00
2.45E+03
3.05E+04
8.24E+04
4.38E+04

1.47E+03


1







A-33


Emergy per unit input = 4.38E+04 sej/J
6 Gross primary production, J
Annual energy = (GPP)*(1E6 g/ton)*(8 kcal/g)*(4186 J/kcal)
Gross primary production = 2.33E+01 ton C/ha-yr
Annual energy = 7.80E+11 J/yr
Emergy per unit input = 1.47E+03 sej/J
7 Total Emergy - Highest renewable input
8 Empower Density - emergy per hectare per year


(Bardi and Brown 2001)



(Orrell 1998)

(Solar emergy of item # 6/Annual energy)






A-34


Bottomland hardwood forest


Figure A-8. Energy systems diagram of a bottomland hardwood forest.







A-35


Table A-8. Emergy evaluation table of a bottomland hardwood forest, per ha per year.
Data Emergy/unit Solar EMERGY
Note Description (per ha-'1 yr 1) (sej/unit) (El3 sej/yr)
Renewable Inputs
1 Sunlight 4.72E+13 J 1.OOE+00 5
2 Wind 5.02E+10 J 2.45E+03 12
3 Rain chemical potential 5.98E+10 J 3.05E+04 182
4 River geopotential 5.95E+08 J 4.70E+04 3
5 River chemical potential 1.51E+10 J 8.14E+04 123
6 Water use (Transpiration) 5.88E+10 J 4.38E+04 258
Flows
7 Gross primary production 6.28E+10 J 4.15E+04 261
8 Total EMERGY 258

Calculated ratios
9 Empower Density 2.58E+15 sej/ha/yr

Notes:
References:


1 Sunlight, J









Ei
2 Wind, J


Annual energy (J):



Insolation:
Area
Albedo :
Annual energy:
energy per unit input:


(Avg. Total Annual Insolation J/yr)(Area)(1-albedo)
(_ m2)*(_ Cal/cm2/y)*(E+04cm2/m2)*
(1-albedo)*(4186J/kcal)
1.41E+02 kcal/cm /yr
1.OOE+04 m2


(Odum et al. 1998)

(After www.nasa.gov)


4.72E+13 J
1 sej/J


(Odum 1996)


Annual energy:

Area
Density of air:
Avg. annual wind velocity:
Geostrophic wind:
Drag coeff. :
Annual energy:
Emergy per unit input:
3 Rain chemical potential, J
Annual energy:
Avg. precipitation:
Area
Annual energy:
Emergy per unit input:
4 River geopotential, J
Annual energy:
Mean annual river flow:

Mean annual river flow:
Average elevation change:
Area Bayou Meto Watershed:


(area)(air density)(drag coefficient)(velocity3)
( m2)(1.3 kg/m3)(1.00 E-3)( mps)(3.14 E7 s/yr)
1.OOE+04 m2
1.23E+00 kg/m3
3.04E+00 mps (data for Little
5.07E+00 mps (observed winds are ab
1.OOE-03
5.02E+10 J/yr
2.45E+03 sej/J


(Avg. precip.)*(Area)*(1 E6 g/m2)*(4.94J/g)
1.21 m
1.OOE+04 m2
5.98E+10
3.05E+04 sej/J


(Odum et al. 1998)
Rock, 2001; www.noaa.gov)
out 0.6 of geostrophic wind)
(Garrat 1977)

(Odum et al. 2000)


(Odum 2000)


(volume)*(1.0E3 kg/m3)*(height in-height out)*(gravity)
6.99E+00 m3/sec (Estimated from daily data for 2000-2001 from
USGS; available at http://nwis.waterdata.usgs.gov)


2.20E+08 m3yr
1.07E+02 m
3.88E+05 ha


(www.mawpt.org; Bayou Meto WPA Report)
(www.mawpt.org; Bayou Meto WPA Report)







A-36


Annual energy:
Emergy per unit input:
5 River chemical potential, J
Gibbs free energy:

Dissolved Solids in:
Dissolved Solids out:
Gibbs Free Energy in:
Gibbs Free Energy out:
Mean annual river flow:
Energy(J):

Energy in:
Energy out:
Annual energy (In- Out):
Emergy per unit input:
6 Water use (Transpiration), J
Annual energy:
Transpiration:
Annual energy:
Emergy per unit input:
7 Gross primary production, J
Annual energy:
Gross primary production:
Annual energy:
Emergy per unit input:


5.95E+08 J/yr
4.70E+04 sej/J


(Odum et al. 2000)


[(8.3143 J/mol/deg)(288 K)/(18 g/mol)]*ln[(le6 -
Solutes)ppm)/965000]
2.00E+02 ppm
4.00E+02 ppm
4.71E+00 J/g
4.69E+00 J/g
2.20E+08 m3/yr
(volume)(density)(Gibbs free energy)
( m3/s)*(1.0E3 kg/m3)(J/g)
1.04E+18 J/yr
1.03E+18 J/yr
1.51E+10 J/yr
8.14E+04 sej/J

(Transpiration)*(area)*(1E6 g/m3)*(4.94 J/g)
1.19E+00 m/yr
5.88E+10 J/yr
4.38E+04 sej/J


(Campbell et al. 2005)

(Odum et al. 1998)
(Odum et al. 1998)










(Odum, 1996)



(Odum et al. 1998)

(Bardi and Brown 2001)


(GPP)*(1E6 g/ton)*(4 kcal/g)*(4186 J/kcal)
3.75E+00 ton/yr (Data for the Black Swamp, AR; Odum et al. 1998)
6.28E+10 J/yr
4.15E+04 sej/J (Sum of solar emergy for item #4 and #6/Annual energy)


Total Emergy - Highest renewable input
Empower Density - emergy per hectare per year






A-37


Agricultural land uses


Figure A-9. Energy systems diagram of agriculture in the Bayou Meto Watershed.







A-38


Table A-9. Emergy evaluation table of sorghum,


per ha per year


Data Emergy/unit Solar EMERGY
Note Description (per ha'1 yr 1) (sej/unit) (E13 sej/yr)
Renewable Inputs
1 Sunlight 1.56E+13 J 1 2
2 Rain transpired 1.98E+10 J 2.59E+04 51
3 Wind 1.OOE+11 J 2.45E+03 25
Nonrenewable Storages Used
4 Net Topsoil Loss 9.04E+09 J 1.24E+05 112
5 Groundwater 3.55E+09 2.69E+05 96
Purchased Inputs
6 Fuel 4.92E+09 J 1.11E+05 55
7 Phosphorus 7.74E+04 g 1.45E+10 112
8 Nitrogen 1.29E+05 g 1.59E+10 205
9 Potassium 1.01E+05 g 1.85E+09 19
10 Pesticides 6.44E+03 g 2.52E+10 16
11 Labor 4.21E+06 J 4.45E+06 2
12 Services 4.23E+02 $ 2.83E+12 120
13 Total EMERGY 2.8E+12 787
Yields
14 Total Yield, dry weight 5.40E+06 g
15 Total Yield, energy 7.91E+10 J
Calculated ratios
16 Emergy per mass 1.46E+09 sej/g
17 Transformity w/services 9.95E+04 sej/J
18 Transformity wo/services 8.43E+04 sej/J
19 Empower Density 7.87E+15 sej/ha/yr
20 NR + PI Empower 7.36E+15 sej/ha/yr
Density w/services
21 NR + PI Empower 6.16E+15 sej/ha/yr
Density wo/services


Notes: Grain Sorghum, Flood Irrigated, Loamy Soils

1 Sunlight, J


References:


Annual energy (J)

Insolation
Growing season
Area
Albedo
Annual energy
Emergy per unit input
2 Evapotranspiration, J
Annual energy
Evapotranspiration
Volume/year
Volume (4 months)
Annual energy
Emergy per unit input


(Avg. Total Annual Insolation J/yr)(Area)(1-albedo)
( m2)(Cal/cm2/y)(1E+04cm2/m2)(1-albedo) 4 -i '- .j..,.1
1.41E+02 kcal/cm2/yr
3.30E-01 yr
1.OOE+04 m2
2.00E-01
1.56E+13 J
1.OOE+00 sej/J

(Volume)(1E6 g/m3)(4.94 J/g)
1.20E+00 m3/m2/yr
1.20E+04 m3/yr
4.00E+03 m3/yr
1.98E+10 J
1.54E+04 sej/J


(Odum et al. 1998)
(www.uaex.edu)

(After www.nasa.gov)

(Odum 1996)


(Odum et al. 1998)


(Odum 1996)







A-39


3 Wind (kinetic energy), J
Area =
Density of air =
Avg. annual wind velocity =
Geostrophic wind =
Drag coeff. =
Energy (J) =

Annual energy =
Emergy per unit input =
4 Net Topsoil Loss, J
Erosion rate =
Organic fraction in soil =
Energy cont./g organic =
Net loss of topsoil =
OM in topsoil used up =
Energy loss =
Annual energy =
Emergy per unit input =
5 Ground water, J
Annual energy =
Annual energy =
Groundwater irrigation =

Groundwater irrigation =
Annual energy =
Emergy per unit input =
6 Fuel, J
Annual energy =
Gallons/acre =

Gallons/ha =
Annual energy =
Emergy per unit input =
7 Phosphorus, g
Annual consumption =

Annual consumption =
Emergy per unit input =
8 Nitrogen, g
Annual consumption
(as Urea 46%) =
Annual consumption
(as Urea) =
Emergy per unit input =
9 Potassium, g
Annual consumption =


Annual consumption
Emergy per unit input


1.00E+04 m2
1.23E+00 kg/m3
3.04E+00 mps (E
5.07E+00 mps (Observe
2.00E-03
(area)(air density)(drag coefficient)(velocity3)
(m2)(1.3 kg/m3)(1.00 E-3)( :ip n 1 14 E7 s/yr)
1.00E+11 J
2.45E+03 sej/J

1.00E+03 g/m2/yr
4.00E-02
5.40E+00 kcal/g
(farmed area)(erosion rate)
(total mass of topsoil)(% organic)
(loss of organic matter)(5.4 kcal/g)(4186 J/kcal)
9.04E+09 J
7.38E+04 sej/J


Chemical potential of groundwater
(Volume)(1E6 g/m3)(4.94 J/g)
7.00E+00 acre inch/yr

7.20E+02 m3/yr
3.55E+09 J
1.60E+05 sej/J

(Gallons fuel)(1.32E8 J/gal)
1.5 1E+01


3.73E+01
4.92E+09
6.60E+04


(Odum et al. 1998)
)ata for Little Rock, 2001; www.noaa.gov)
d winds are about 0.6 of geostrophic wind)
(Garrat 1977)




(Odum et al. 2000)

(After Odum et al. 1998)
(Pimentel et al. 1995)







(Odum 1996)


(Windham & Marshall 2004;
www.aragriculture.org/famplanning/budgets)


(Odum et al 1998)



(Windham & Marshall 2004;
www.aragriculture.org/famplanning/budgets)


(Odum 1996)


(Windham & Marshall 2004;
www.aragriculture.org/famplanning/budgets)

(Brandt-Williams 2001)

(Windham & Marshall 2004;
www.aragriculture.org/famplanning/budgets)


6.90E+01 lb/acre

7.74E+04 g/ha
1.45E+10 sej/g


1.15E+02 lb/acre

1.29E+05 g/ha
1.59E+10 sej/g

9.00E+01 lb/acre

1.01E+05 g/ha
1.10E+09 sej/g


(Brandt-Williams 2001)


(Windham & Marshall 2004;
www.aragriculture.org/famplanning/budgets)


(Odum 1996)


10 Pesticides, g (fungicides and herbicides)
Annual consumption = 5.74E+00 lb/acre
Annual consumption = 6.44E+03 g/ha


(Assumed one pint of pesticide = 1.0375 lbs)
(Windham & Marshall 2004;
www.aragriculture.org/famplanning/budgets)







A-40


Emergy per unit input =
11 Labor, J (operation and irrigation)


Annual


Labor
Annual energy
Emergy per unit input
12 Services, $


1.50E+10 sej/g


energy = (pers-hours/ha/yr)(2500 kcal/day)(4186J/Cal) /(
Labor = 1.30E+00 hr/acre


3.21E+00 hr/ha
4.21E+06 J
4.45E+06 sej/J


Value = 3.56E+00 $/CWT
Value = 3.56E-02 $/lb
Value = 4.23E+02 $/ha
Annual emergy = ($ , i, cj 1')
Emergy per unit input = 2.83E+12 sej/$, 2001
13 Total Emergy - Sum of inputs 2 through 12
14 Yield, g
Yield = 8.60E+01 Bushel/acre
5.60E+01 lb/bushel
Yield = 5.40E+06 g/ha
15 Product in Joules


(Brown and Arding 1991, in Brandt-Williams 2001)


8 pers- hrs/day)
(Windham & Marshall 2004;
www.aragriculture.org/famplanning/budgets)


(Migrant labor, Brandt-Williams 2001)

(www.nass.usda.gov/ar/)




(This study, see Table A-5)



(www.auex.edu)
(www.muextension.missouri.edu)


Energy = (_g)(3.5 kcal/g)(4186J/kcal) (Odum et al.1998)
Energy content = 7.91E+10 J
Emergy per mass - Total emergy divided by yield in grams
Transformity w/services - Total emergy yield divided by yield in joules
Transformity wo/services - Total emergy yield minus services divided by yield in joules
Empower Density - sum of emergy per hectare per year
NR + PI Empower Density w/services - sum of non renewable and purchased inputs emergy per hectare per year
NR + PI Empower Density wo/services - sum of non renewable and purchased inputs emergy per hectare per year minus
services
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