• TABLE OF CONTENTS
HIDE
 Title Page
 Acknowledgement
 Table of Contents
 List of Tables
 List of Figures
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Appendix A: Emergy Terminology...
 Appendix B: Emergy Evaluations...
 List of References
 Biographical Sketch
 Committee Signature Page















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EMERGY EVALUATION OF ECOSYSTEMS: A BASIS FOR MITIGATION POLICY By ELIANA BARDI A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULLFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2002

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ii ACKNOWLEDGMENTS I wish to present my gratitude to my advisor, Mark Brown, for believing in me and giving me the opportunity to challenge myself and think outside the box. Special thanks go also to the supporting faculty memb ers, Clay Montague and Clyde Kiker, for the knowledge they shared in their classes a nd their invaluable input to this work. I would not be here if it were not for the support and love of my many dear friends here in Gainesville. I thank Matt and Leah, Chuck and Venessa, Jim and Chris, Annie, and my ultimate divas for helping me keep my sanity (or whatever is left of it) through the years. Matt was es pecially helpful on numerous occasions with simulation modeling and emergy theory. Todd, Kelly, Susan, Sharlynn, Ben, Mark, Joel, and the rest of the gang at the Center for Wetlands have been incredibly supportive and helpful whenever I was in need. Finally, I would like to thank my families: first, my Italian family, for believing in me from day one, helping me along the wa y, allowing me to pursue my dreams away from home, and inspiring me to always pers evere; and second, my American family, for welcoming me and opening their doors and hearts to me. They have made my staying in the United States so fulfilling. And lastly, I thank my husband B.J for showing me a new world, always encouraging me, pushing me to ach ieve great things, and helping me in so many ways to accomplish this. I also thank his family for all the love and support they have given me.

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TABLE OF CONTENTS page ACKNOWLEDGMENTS .iii LIST OF TABLES..vi LIST OF FIGURES .viii ABSTRACT..xii INTRODUCTION...1 Statement of the Problem Review of the Literature..3 Ecosystem Valuations.. Compensatory Mitigation and Mitigation Banking ....6 Systems Modeling. ..8 Plan of Study .8 METHODS....10 Description of Ecosystem Types ..10 Emergy Evaluation of Ecosystems15 System Boundaries and Evaluated Parameters...... Mass and Energy Flows.20 Calculation of Transformities....23 Emdollar Evaluation.. Emergy Evaluation of a Constructed Forested Wetland....30 Simulation Models.....33 Forested Wetland Simulation Model. Model Parameters and Calibration.....33 Constructed Wetland Cost Recovery Model..34 RESULTS Emergy Evaluation of Ecosystems35 Energy, Emergy, and Transformity of Ecosystems...35 Emdollar Values of Ecosystems Replacement Values of Ecosystems..50 Emergy Evaluation of a Constructed Forested Wetland iii

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Simulation Models.56 Forested Wetland Simulation Model. Energy, Emergy and Transformity of Forested Wetland Model...58 Constructed Wetland Cost Recovery Model ....68 DISCUSSION Ecosystem Services and Natural Capital...74 Mitigation Ratios...75 Static Replacement Ratios Cost Recovery Mitigation Ratios.. Simulation Model... Limitations and Suggestions for Further Research Conclusions....90 APPENDICES A SYSTEMS ECOLOGY SYMBOLS AND DEFINITIONS B EMERGY EVALUATIONS OF SIX FLORIDA ECOSYSTEMS..... LITERATURE CITED BIOGRAPHICAL SKETCH...126 iv

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v LIST OF TABLES Table page 1. Summary of emdollar values of environmental services of six Florida ecosystems……………………………………………………………….47 2. Summary of emdollar values of natural capital (live biomass, organic matter, soil water, and geologic structure) of six Florida ecosystems……………………………………………………………….49 3. Summary of replacement values of wetland and upland ecosystems assuming complete elimination…………………………………………………..51 4. Emergy evaluation of the inputs to construct a forested wetland in Florida (J/ha).……….………………...……………………………………….52 5. Storage and internal flow equati ons for the forested wetland simulation model…………………………………………………………………59 6. Steady-state values of the storages and calibrated coefficients for the forested wetland simulation model………………………………….……62 7. Static replacement ratios for the six ecosystems using values from Table 3…………………….……………….……………………………….78 8. Mitigation ratios of forested wetlands at 10 year intervals (from 60 to 100 years after constr uction) resulting from varying initial organic matter storage to 1%, 25%, 50%, and 90% of its steady state value………………………………………………………………...86 9. Definitions of emergy terminology and indices used in this study………………94 10. Emergy evaluation of annual drivi ng energies and environmental services of forested wetlands in north central Florida…………...………………96 11. Emergy evaluation of natural capi tal in forested wetlands………….…………...98 12. Emergy evaluation of annual drivi ng energies and environmental services of shrub/scrub wetlands in north central Florida……….……………..100 13. Emergy evaluation of natural ca pital in shrub/scrub wetlands……..…….…….102

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vi 14. Emergy evaluation of annual drivi ng energies and environmental services of marsh wetlands in north central Florida……….…………….……..104 15. Emergy evaluation of natural capital in marsh wetlands…….……..…….…….106 16. Emergy evaluation of annual drivi ng energies and environmental services of riparian wetlands in north central Florida……….………….………108 17. Emergy evaluation of natural capital in riparian wetlands …………………….110 18. Emergy evaluation of annual drivi ng energies and environmental services of mesic hardwood forest s in north central Florida…..……….………112 19. Emergy evaluation of natural capi tal in mesic hardwood forests………......…..114 20. Emergy evaluation of annual drivi ng energies and environmental services of pine flatwoods in north central Florida…………….………….……116 21. Emergy evaluation of natural capital in pine flatwoods..………………………118

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vii LIST OF FIGURES Figure page 1. System boundary of a depressional wetland……………………………………..16 2. System diagram of a depressional wetland. GPP = gross primary production; ES = saturation deficit……..……………………………....17 3. System diagram of a floodplain forest. GPP = gross primary production; O.M. = organic matter; SED = sediment; ES = saturation deficit ………………………………………………………...…18 4. System diagram of an upland ecosystem. The upland ecosystems included mesic hardwood forests and pine flatwoods………………………………………………………………………....19 5. Boundary of a floodplain ecosystem (A), with cross-sectional dimensions of channel and levees (B), and calculations of mass displacement (C) ...………………………………………...24 6. Schematic of floodplain ecosystem structure showing the 1 hectare area evaluated (A). The turnover time of the floodplain is illustrated in (B), where each box represents a 200 year migration of the stream channel, completing the entire cycle across the floodplain and back again in an estimated 1000 years.………………………………………………..……………………...25 7. Diagram of transformity calculati ons for water stored, infiltration, and transpiration………………………………………………………………….27 8. Emergy per dollar (se j/$) of the United States from 1980-2000. Values from 1980-1993 taken from Odum (1996), while from 1994-2000 calculated using data from the U.S. Statistical Abstract (2001)and the same methods employed by Odum (1996)…….…………………29 9. System diagram of a constructed forested wetland showing the renewable energies and the economic inputs to the system as well as the loss of soil orga nic matter and biomass resulting from excavation………………………………………………………………….32

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viii 10. Emergy signature of six Flor ida ecosystems showing the environmental inputs to the system. S = sun; W = wind; R = rain; RI = run-in; G = geologic input; RG = river geopotential. All values expressed in 1.0E+15 sej/ha/yr. No te the different scale on each graph. …..…………………………………………………………..……………36 11. Annual driving emergy of six Florida ecosystems (sum of transpiration, geologic input, and river geopotential for the floodplain forest; sum of transpira tion and geologic input for all other ecosystems). Calculated from data in Appendix B, Tables 10-21…………………………………………………..…………...….…38 12. Transpiration and infiltration valu es of six Florida ecosystems. (A) Power Density; (B) Solar Transfor mity; (C) Empower Density. See Appendix B, Tables 10-21..………………………………….……………...39 13. GPP values of six Florida ecosystems. (A) Power Density; (B) Solar Transformity; (C) Emer gy. See Appendix B, Tables 10-21……..……41 14. Biomass values of six Florida ecosystems. (A) Energy; (B) Transformity; (C) Emergy. See Appendix B, Tables 10-21…...……….…...42 15. Organic matter values of six Fl orida ecosystems. (A) Energy; (B) Transformity; (C) Emergy. See Appendix B, Tables 10-21……...………....43 16. Soil water values of six Flor ida ecosystems. (A) Energy; (B) Transformity; (C) Emergy. See Appendix B, Tables 10-21……….…..…....45 17. Geologic structure of four we tland ecosystems. (A) Energy; (B) Transformity; (C) Emergy. See Appendix B, Tables 10-21……………...…46 18. System diagram of forested we tland simulation model showing energy flows and storages evaluated……………………………………………..57 19. Diagram showing calculations of emergy and transformity of biomass in the forested wetland simulation model…………….……..………….63 20. Diagram showing calculations of emergy and transformity of organic matter in the forest ed wetland simulation model………….…………….64 21. Simulation results of the forested wetland model showing time series of forest biomass and organic matter storages…………….………………65 22. Emergy and transformity of forest biomass storage in forested wetland model……………………………………………………………………66

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ix 23. Emergy and transformity of organic matter storage in forested wetland model……………………………………………………………………67 24. Simulation results of biomass en ergy storage after increasing initial organic matter storage to 25%, 50%, and 90% of its steady state value showing increased grow th rates as the initial organic matter value increases……….…………………………………………………...69 25. Simulation results of organic matte r energy storage after increasing initial organic matter storage to 25% and 50% of its steady state value, showing increased grow th rates of organic matter………….…….….…...70 26. Simulation results of (A) GPP emdo llar value, and (B) recovery time needed to payback construc tions costs (calculated by adding yearly GPP to initial debt)………………………..………………………………71 27. Simulation results of GPP and r ecovery time under different initial organic matter storage values, showing an increase in GPP (A) and a decrease in re covery time (B) as the initial organic matter storage is in creased by 25%, 50%, and 90% of its steady state value……………………………………………….………….73 28. Graph of transpiration accrual in mature forested wetland and constructed ecosystem. The ratio of these two lines at any point in time constitutes the mitigation ratio necessary to recover losses due to construction within that time frame ……….………………………81 29. Simulated mitigation ratios for forested wetland from 54 to 100 years after construction showing decrease in mitigation ratios as the time frame allowed to offset losses increases….………………………….82 30. Simulated mitigation for forested wetlands from 60 to 120 years after construction showing decrease in mitigation ratios as the initial storage of or ganic matter is increased by 25%, 50%, and 90% of its steady state value……………………………………………………..85 31. Select energy systems symbols and definitions (after Odum 1996)………………………………………………………………………..……93

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x Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science EMERGY EVALUATION OF ECOSYSTEMS: A BASIS FOR MITIGATION POLICY By Eliana Bardi August 2002 Chair: Mark Brown Major Department: Environmental Engineering Sciences This thesis focuses on quantifying ecosys tems’ value to society both in terms of the environmental services and the natural cap ital they contribute. The research has concentrated on the ecosystem services of transpiration, infiltration, and gross primary production, and the natural capital of biomass, soil organic matter, water, and geologic structure. Six Florida ecosystems, four wetlands and two uplands, were studied. A constructed forested wetland was evaluated to explore costs and benefits of mitigation. A computer model was developed to simulate the energy, emergy and transformity of forested wetlands biomass and organic ma tter. A cost recovery model was also developed to shed light on the time frame needed to recover losses from mitigation. Results of this research can be summarized in four main points. First, ecosystems in general, and wetland communities in particular, are extremely valuable to human society. On an annual basis wetla nds provide between 2,295 and 6,430 em$/ha/yr

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x of value to regional human economies, compar ed to two upland ecosystems values of 727 and 911 em$/ha/yr. The natural capital (value stored in biomass, organic matter, and soil water) of wetlands ranges from 283,286 to 1,018,641 em$/ha, compared to the upland ecosystems, whose values range from 49,819 to 70,909 em$/ha. Replacement values of wetlands range between 301,645 and 1,081,230em$/ha, while replacement values of uplands range between 64,362 and 93,677 em$/ha. Second, mature ecosystems are the work of decades of ecosystem services and natural capital accrual. When a forested wetland is cut down and replaced by a created one, the created wetlands are usually monitored for only a few years. However, the ecosystem needs 165 years to reach 90% of its steady state biomass, and 386 years to accumulate 90% of its steady state storage of soil organic matter. Third, constructed wetlands are characterized by large in itial investments (costs) of construction. Construction costs of forested wetlands are approximately 103,000 em$/ha, with an additional 2,108 em$/ha sp ent for monitoring during the following three years. Approximately 54 years are required fo r the services (represented by GPP) of the newly constructed ecosystem to offs et the losses due to construction. Fourth, mitigation ratios (the ratio of constructed wetland required to replace wetland destroyed) are more properly determ ined using dynamic analysis of ecosystem value, since the ratios decrease as the time to offset losses increases. For instance, mitigation ratios for forested wetlands are 5.48:1 if the time frame allowed to offset losses is 70 years and decrease to 2.66:1 if the time frame is 100 years. Adding organic matter to created sites decreases construction costs, recovery times, and mitigation ratios.

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INTRODUCTION Statement of the Problem With increasing demand for lands by all types of development in support of growing human populations, there has been an increasing pressure to develop marginally developable lands. In Florida, where estimates suggest that approximately 30% of the landscape is wetlands (Frayer and Hefner 1991), this pressure translates into potentially significant impacts to wetland ecosystems. In the past century much of Floridas developed landscape was constructed on the most usable land, leaving wetlands and poorly drained flatwoods. Now, with developable land becoming more and more scarce, especially near rapidly growing urban centers, attention is shifting toward more marginal land. This shift in the direction of development is resulting in an increased pressure on wetlands. There are many state and federal regulations that limit direct impacts to wetlands. However, as a result of increased demand for developable lands, agencies responsible for protecting wetlands are under pressure to permit development in and around wetlands. To offset losses of wetlands, state and federal agencies have instituted systems of mitigation. Mitigation in this context generally means the act of offsetting losses that result from the elimination of wetlands through development actions. While at times mitigation has included such practices as restoration of impaired wetlands or preservation, in this thesis mitigation has been more narrowly defined as construction of wetlands as replacement for those destroyed. 1

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2 Early regulations associated with mitigati on required that it take place on the site where the impacts occurred. However, as agencies have gained more experience, there has been a shift away from onsite and type for type mitigation to off site and, most recently, toward the creation of regional mitigation banks. Today, compensatory mitigation and mitigation banking are relativel y common practices, yet there is no clear understanding of the environmen tal benefits and losses to society that result from these practices. In addition, regulat ions pertaining to mitigation are hindered by the lack of a clear and objective means of quantitatively determining appropriate mitigation ratios. As a result of those concerns, several questions arise. (1) How might the various properties and functions of wetlands be evaluated? (2) What are the relative va lues of wetlands? (3) What functions of wetlands are the most valuab le? (4) What are the costs and benefits of wetland mitigation? (5) What is the best scheme for determining appropriate mitigation ratios? All in all, what is needed is an assessment method that can determine the environmental values of whole systems. With such an eval uation, society could judge the costs, benefits, and trade-offs associat ed with wetland impacts and mitigation. Furthermore, by using the relative values of ecosystems more appropriate mitigation ratios might be determined. In this thesis, the structural propertie s and main processes of several wetland and upland ecosystems were evaluated using emer gy analysis techniques. The goal of the research was to determine relative values of wetland and upland ecosystem components and processes, and then to develop insight by comparative analysis related to costs and benefits of mitigation.

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3 Review of the Literature Ecosystems Valuations Ecosystems have been conventionally valued on the basis of their monetary contribution to human society. For instance, salt marshes may be given a monetary value dependent upon the perceived profit fr om fisheries production, tourism, and recreation use. Forested wetlands may be evaluated on the basis of their marketable timber. These types of evaluations focus on eco system functions and storages that have a marketable value and can thus be sold as comm odities such as fish or timber (Bell 1997). However, other non-marketable attributes of ecosystems remain igno red by these types of evaluations, such as water purif ication or wildlife habitat. In the literature, there are several approaches to valuating wetlands. These methodologies can be grouped into two main categories: (1) economic valuations from perceived monetary gains, (2) energetic valuations from ecosystem pr ocesses and pathways. The most common type of economic va luation of non-marketable ecosystems services and natural capital is to assess an individuals willingness-to-pay for those services. This approach relies on human preferences and perceived gains from ecosystems to establish a price for non-market able attributes (Cos tanza et al. 1997). While it is a widely employed method of estimating value of non-marketable goods and services, its shortcomings are also wide ly recognized (Ludwig 2000, Starrett 2000, Odum and Odum 2000). In fact, the willingnessto-pay method fails to accurately quantify ecosystem value from a scientific perspect ive, since it is based solely on peoples preferences, not on the ecosystems struct ural and functional components (Brown and Ulgiati, 1999). Bell (1997) identifies ot her methodologies, including the land-price

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4 analysis method, which estimates wetland values on the basis of the highest economic use that can be derived from the land, and the replacement or substitution model, which assesses wetland values by cal culating how much it costs to restore destroyed or developed wetlands to their orig inal state. The latter simply adds up costs for machinery, products, and human labor to carry out the pr oject, and again ignores other valuable natural services provided by wetlands. A somewhat more simplistic methodology is the opportunity cost of preservation model, in which preservation of natural resources that cannot be monetarily evaluated is favored unl ess the value of the forgone development is unacceptably large (Batie and Mabbs-Zeno 1985). However, this method fails to provide any quantitative guideli nes for what is considered unacceptably large, and while it considers in depth the economic valu es of the possible development scenarios, it fails to account for the ecosystem values lo st from wetland destruction. All of these economic valuations are only appropriate for recognizing services from ecosystems that have a market, (i.e. fish or timber sold on th e market) and result in subjective estimations of the many other services ecosystems provide to society, such as infiltration, water storage, increased water quality, and wildlife value. The importance of integrating ecological and economic values of ecosystems was recognized by Odum (Odum 1996). Energetic ev aluations of ecosystem processes and pathways emphasize energy networks and proce sses within ecosystems. Gosselink et al. (1974) employed such a methodology in estimating the value of one acre of tidal marsh wetland. Their calculations involved estim ating the economic value of the wetland products and services (fisheri es, aquaculture potential, and waste treatment), as well as the life support value as a function of energy flow (gross primary production times

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5 energy/money conversion ratio). The Gosselink et al. (1974) study resulted in a value of $82,000/ acre of tidal marsh. This value can be compared to a more traditional economic value for a saltmarsh calculated by Bell (1997) that ranged between $981 and $6,471. The huge difference in the reported values is probably due to the fact that Bell (1997) attempted to place an economic value on the contribution of wetlands to recreational fishing alone, without taking in to account other important serv ices of saltmarshes, such as gross primary production. Energetic valuations and emergy. Odum developed a method of valuation that was based on the total amount of energy of one kind used directly or indirectly (and through all pathways) to make a product or service (Odum and Odum 2000). The concept was later termed emergy, signify ing energy memory (Odum, 1996). The emergy accumulated in an ecosystem increases as it matures and it is calculated by multiplying the energy storages by their transf ormity. Transformity, or the solar emergy required to make one joule of a service or product (Odum 1996), is calculated by dividing a products solar emergy by its energy. Transformity increases as processes become more refined, and it thus can be a measure of maturity and efficiency. For example, the biomass of a mature, old growth forest will ha ve a higher transformity than the one of a younger forest, since its emergy has been accumulating for a longer time. Compensatory Mitigation and Mitigation Banking Wetland mitigation has become an indispen sable tool in the implementation of the no-net-loss policy for wetlands, which stem med from Section 404 of the Federal Clean Water Act. In its broadest definition, mitig ation refers to the avoidance, minimization, and elimination of negative impacts to wetlands, or compensation by replacement or

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6 substitution of equivalent wetland value in order to achieve no-net-loss of wetland function. However, equivalent wetland value and wetland function are not explicitly defined and are thus subject to personal interpretation. Much of the literature on wetland mitigation reports on the success or failure of mitigation sites (Zedler 1996,Brown and Lant 1999, Brinson and Rheinhardt 1996), while th ere are very few studies that address the issue of how to quantify a wetlands cont ribution to society (Bardi and Brown 2001). Compensatory mitigation, which is the replacement of impacted wetlands by creating new ones, has had limited success due to difficulties in implementing regulations, monitoring, and assessing the l ong-term viability of the numerous and smallscale mitigation sites. To address this c oncern, there has been a move in recent years towards the use of mitigation banks as an alternative to the postage-stamp wetland creation. Mitigation banks are often largescale projects that incorporate wetland creation, restoration, enhancement or preserva tion within regionally significant lands. Unlike compensatory mitigation, which occurs simultaneously or after wetland impacts have already taken place, mitigation banks ar e established in advance by a third party (mitigation banker), who then sells the wetland credits to future developers whose projects impact wetlands. Wetland mitigation banks offer several advantages and disadvantages: first, they consolidate small-scale projects into larger tracts of land, thus reducing permitting and monitoring requirements by federal, state, a nd local agencies. Second, they create the wetland credits in advance of impacts, thus ensuring the achievement of no-net-loss, and are required to invest in l ong-term financially secured management plans, usually by donating the banks to nature preserves or stat e agencies once they sell out. Finally, such

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7 large-scale projects can be more economically cost effective, thus reducing overall waste of human and material resour ces. On the other hand, the money-making enterprise of mitigation banking has attracted a lot of skepticism as well, and critics of mitigation banks question whether it is ecologically s ound to shape the landscape by concentrating wetlands in one location at the expense of smaller, isolated wetlands that dot the landscape. Mitigation ratios Whether compensation occurs through compensatory mitigation or mitigation banks, a mitigation ratio is used to calculate how many acres of compensation are required for a specific wetland impact. This mitigation ratio represents the value of acres compensated per acres conv erted of a particular ecosystem (Brown and Lant,1999). Because the current system lack s clearly defined functional methodologies for assessing wetland value, mitigation ratios are assessed qualitatively and are dependent on several criteria: the percei ved value of the ecosystem to be impacted, the ease of replacement, and the perceived recovery time needed for the constructed ecosystem to reach predefined success criteria (Zedle r, 1996). The acres co mpensated must not necessarily be in the form of newly cons tructed ecosystems, but can also extend to restoration, preservation and enhancement of already existing ecosystems. Typical mitigation ratios range between 2:1 for restoration, 3:1 for creation, 4:1 for enhancement, and 10:1 for preservation, that is, for 1 acr e of wetland impacted, 2 acres have to be restored while if the new ecosystems are cr eated, for each acre impacted 3 acres would have to be constructed. However, because each wetland is assessed on a case by case basis, there is much variab ility in their use.

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8 Systems Modeling Simulation models of ecosystems are useful tools to make predictions of ecosystem behavior from data collected in the field. Most models have focused on the dynamics of succession (Odum 1967, Burns 1970, Regan 1977), or prey-predator relationships and competition for scarce resources (Wiegert 1974). Tilley (1999) explored new theories in computer simulation by modeling the energy, emergy, and transformity of forest biom ass, organic matter, and saprolite in the Coweeta watershed. Until then, energy quality had been analyzed using emergy analysis at a particular point in time. Tilley s simulation showed that energy, emergy and transformity all increased over time, with the physical components (energy storages) reaching their maximum value at a faster rate than both emergy and transformity. Emergy accumulation and transformity, in other words, the quality of ecosystems, is not only a function of the energy storages, but also of the time it takes to accumulate value. Plan of Study This thesis focuses on quantifying ecosystem value and calculating mitigation ratios among different ecosystems. First, emergy evaluations were conducted for six major Florida ecosystems and their component s: depressional cypre ss dome, shrub/scrub wetland, freshwater marsh, floodplain forest, mesi c hardwood forest, and pine flatwoods. Comparisons between systems and th eir components were then made. Second, the energy costs of constructi ng a forested wetland were evaluated. Third, a dynamic simulation model of an aggreg ated ecosystem was used to evaluate the energy, emergy, and transformity of biomass and organic matter in forested wetlands. Results from the simulation model were used to investigate the time needed to recover

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9 the initial investment of wetland construction/ creation to explore the question of whether created wetlands are sound investments for the future of Florida. Finally, these analyses and the resulting data were used to study mitigation options and overall policy with recommendations for mitigation ratios and timing.

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METHODS The following methods are divided into several sections, beginning with a description of the ecosystem types that were evaluated. The second and third sections, Emergy Evaluation of Ecosystems and Emergy Evaluation of a Constructed Forested Wetland, provide details of methods used to evaluate data gathered from the literature on Florida ecosystems and a constructed wetland. The fourth section, Simulation Modeling, presents the methodology applied to the computer simulation models. Descriptions of Ecosystem Types Six Florida ecosystems were evaluated: four wetland ecosystems (cypress dome, shrub/scrub wetland, freshwater depressional marsh, and floodplain forest), and two upland ecosystems (a mesic hardwood forest and pine flatwoods). These ecosystems make up approximately 97% of the freshwater wetland area and 87% of the forested upland area in the current landscape of Florida (Florida Geographic Data Library 2000). Descriptions of each ecosystem, summarized from Brown et al. (1990) and Brown and Schaefer (1988), follow: Cypress domes--Cypress domes are found throughout Florida as small depressions most often within pine flatwoods. These small depressions are called cypress domes due to the domed shape of the trees when viewed from the side. Cypress domes are one of the most common forested wetlands in north central Florida. Standing water occurs in cypress domes from 50%-90% of the time. Pond cypress (Taxodium ascendens) is the dominant canopy species. Other canopy species include black gum 10

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11 ( Nyssa sylvatica ), pond pine ( Pinus serotina ), slash pine ( P. elliotti i), red maple ( Acer rubrum ), and one or more of the bay species, such as red bay ( Persea borbonia ), sweet bay ( Magnolia virginiana ), and loblolly bay (Gordonia lasianthus ). The understory of these ecosystems is often diverse. Dominant understory species in cypress domes include fetterbush ( Lyonia lucida ), wax myrtle ( Myrica cerifera ), dahoon holly ( Ilex cassine ), buttonbush ( Cephalanthus occidentalis ), Virginia willow ( Itea virginica ), and myrtle-leaf holly ( Ilex myrtifolia ). Vegetation at ground level is ofte n sparse and is a function of the wetland hydroperiod. The most frequent herbaceous species are lemon bacopa ( Bacopa caroliniana ), Virginia chain fern ( Woodwardia virginiana ), coinwort ( Centella asiatica ), redroot ( Lachnanthes caroliniana ), and various graminoids (e.g. Panicum spp.). The ecotone consists of transitional species such as wax myrtle, gallberry ( Ilex glabra ), highbush blueberry ( Vaccinium spp), fetterbush ( Lyonia lucida), greenbriar (Smilax spp.), blackberry ( Rubus spp.), muscadine grape (V itus rotundifolia ), and yellow jessamine ( Gelsemium semprevirens ). Shrubscrub wetland-The shrub-scrub wetland can be relatively diverse or dominated by only a few species depending on h ydrology and fire regime. When diverse, these ecosystems are dominated by both woody shrubs and herbaceous wetland vegetation. Common woody shrub speci es include: Carolina willow ( Salix caroliana ), fetterbush, wax myrtle, dahoon holly, buttonbush, and Virginia willow, all occurring at varying dominance depending on the hydroperiod. Many of the same herbaceous species found in marshes are also found in the shrubscrub wetland, but at much lower densities. Common herbaceous species include lemon bacopa, sawgrass ( Cladium jamaicense ), bullrush ( Scirpus spp.), Virginia chain fern, coinwort, and panicum. In some instances,

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12 the scrub-shrub wetland is dominated by only one or two woody species and has higher densities of herbaceous vegeta tion. The ecotone consists of transitional species such as such as wax myrtle, stagger-bush ( Lyonia ferruginea), gallberry, fetterbush, and vines such as greenbriar, blackberry, muscadine grape, and yellow jessamine (Brown and Schaefer, 1988; Brown et al. 1990). Depressional herbaceous marsh --Shallow marshes occupy low topographical areas and are common throughout central Florid a as interspersed ecosystems in pine flatwoods matrix. Shallow marshes are typica lly circular in shape and vary from small (less than one half acre) to large (tens of acr es). Depth of standi ng water during the rainy season is typically 25 to 55 centimeters. Most flatwoods marshes are relatively oligotrophic, with the main source of nutrien ts being rainfall and su rface drainage from surrounding watersheds. The ecotone of thes e systems often consists of mesic oak communities, pine flatwoods, or cypress domes. Shallow marshes are common where inundation is frequent and depths of i nundation are less than 0.5 meters. Marsh vegetation consists of a diversity of species. In the gra ssy shallow marshes, species that consistently occur and are often dominant include panicum, St. John's Wort ( Hypericum spp.) yellow-eyed grass ( Xyris spp), marsh fleabane ( Pluchea spp), redroot, and pickerelweed ( Pontedaria cordata ). Also common occurring spec ies are sawgrass, spikerush ( Eleocharis spp. ), soft rushes ( Juncus spp.) Broad-leaved marshes, often referred to as flag ponds, are marsh communities that exhibit deeper inundation, longer hydroperiods, and deep accumulations of organic matter. Dominant species include pickerelweed, arrowhead ( Sagittaria spp.), fire flag (Thalia geniculata ), bulrush ( Scirpus spp.), and cattail ( Typha spp.) (Brown and Schaefer 1988; Brown et al. 1990).

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13 Floodplain forests-Floodplain forests make up a pproximately one-third of Floridas swamps and are found predominantly in north Florida. They occur along creeks, rivers, and sloughs and are often re ferred to as bottomland hardwood forests. Although there are six types of river swamps in Florida, depending on the rivers energy, water quality, and location in th e landscape (Wharton et al. 1 977), this analysis focuses on Blackwater floodplain forests. Blackwater rivers and creeks exhibit much slower flow rates than alluvial rivers and thus carry little alluvi um to the surrounding floodplain. Occasionally an impermeable soil layer beneath the floodpl ain also contributes to standing water (Ewel 1990). Ca nopy species include white ash ( Fraxinus caroliniana ), bald cypress, red maple, swamp blackgum ( Nyssa sylvatica var. biflora ), water hickory ( Carya glabra ), and hornbean ( Carpinus caroliniana ), to name a few. Understory shrubs include dahoon holly, wax myrtle and buttonbush. The herbaceous layer is often diverse with cinnamon fern ( Osmunda cinnamomea ), Virginia chain fern, pickerelweed, lizards tail ( Saururus cernuus ), and many others. Floodplain wetlands are often bordered by mesic hardwoods and flatwoods in slightly higher elevations. Mesic hardwood forests-This community is found throughout most of the Southeastern Coastal Plain but coverage is rest ricted to areas shielded from fire. These forests therefore do not occur extensively, but rather as narrow bands of vegetation bounded by sandhills and flatwoods on upgradie nt slope and bottomland forests down gradient. This community is a diverse and complex ecosystem characterized by large evergreen trees such as live oak ( Quercus virginiana ), Southern magnolia ( Magnolia grandiflora ), loblolly bay ( Gordonia lasianthus ), intermixed with deciduous tree species such as sweet gum ( Liquidambar styraciflua), red maple, water oak ( Quercus nigra ) and

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14 laurel oak ( Quercus laurifolia ) (Odum and Brown 1975). Pines such as slash ( Pinus elliottii ) and loblolly ( Pinus taeda ) are often present at low densities. A variety of factors influence the vegetation compos ition of mesic hardwood forests, such as organic matter, exchangeable cations, pH, and nutrient availa bility. For example, evergreen species occur more often on nutrient poor sites as they have a more closed nutrient cycle compared to deciduous species. Mesic hardwood forests are characte rized by greater diversity, vegetation layering, and greater accumulation of organi c matter than the adjacent pinelands (Platt and Schwartz 1990). Pine flatwoods-Pine Flatwoods cover as much as 50% of the Florida peninsula (Edmisten 1963). Flatwoods, as the name indicates are generally located in areas of little relief in somewhat poorly drained to very poorly drained soils (Edmisten 1963). They are characterized by open canopies composed of one or more pine species such as pond pine ( Pinus palustris ), slash pine, and loblolly pine. U nderstory species include a variety of shrubs, graminoids, and herbaceous plants such as wax myrtle, saw palmetto ( Serenoa repens ), gallberry, staggerbush, fetter bush, blueberry, and wiregrass ( Aristida beyrichiana). Vegetation composition is influenced by factors such as soils, drainage, and hydroperiod. Wet flatwoods are seasonally inundated, occur on sandy soils, and are composed of slash pine, pond pine, and cabbage palm with a hydrophytic understory that includes wax myrtle and fetterbus h. Mesic flatwoods are preval ent in drier sites and have canopies of slash and longleaf pine, with an understory of gallberry, rusty lyonia, and wiregrass (Abrahmson and Hartnett 1990). Pine flatwoods have been described as the matrix tying together different types of vegetation, such as wet prairies, marshes,

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15 swamps, sandhills, and scrubs (Edmisten 1963). Pine flatwoods are fire maintained ecosystems. Emergy Evaluation of Ecosystems Emergy evaluations were conducted using emergy terminology and symbols as introduced by Odum (1996). Appendix A summarizes emergy terminology (Table 9) and symbols (Figure 31) used throughout the study. System Boundaries and Evaluated Parameters Figure 1 illustrates the system boundary for the depressional wetland evaluations and depicts the various parameters included in the evaluations. The underlying geologic structure was included within the system boundary. For illustrative purposes, half the wetland is shown as a forested wetland and th e other half as a marsh. The evaluations were done for 1 hectare (approximate ly 2.5 acres) of typical wetland. Figures 2, 3 and 4 are generalized system s diagrams of a depressional wetland, a riparian forest, and an upland ecosystem, respectively. Figures 2, 3 and 4 show the main driving energies, environmental services, a nd storages (natural capital) that were evaluated for each of the ecosystems. The dominant driving energies of the ecosystems are: sunlight, wind, rainfall, run-in (surface water runoff from the surrounding watershed), and the emergy contribution from geologic processes. Mesic hardwood forests and pine flatwoods ar e not net sinks of run-in (S un 1995), and therefore it does not appear as an input in Figure 4. The main material storages of biomass, peat, water, and geomorphic structure were evaluated fo r the four wetland ecosystems, while only biomass, organic matter, and water were evaluated for the two upland ecosystems.

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16 TOP OFHAWTHORNE FORMATION SYSTEM BOUNDARY CLAYEY LENSES 2'-3" ~ 10 m DOLOMITE Area = 1 hectare Infiltration Figure 1. System boundary of a depressional wetland.

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17 WIND ES SUNRAINRUN-INDEPRESSIONALSTRUCTUREHAWTHORNEFORMATIONPEATWATERBIOMASSSURFACERUNOFF VEGETATION GEOLOGICINPUT GPP InfiltrationTranspirationEvapotranspirationEvaporation Figure 2. System diagram of a depressional wetland. GPP = gross primary production; ES = saturation deficit.

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18 FLOODPLAINSTRUCTURE SUN RAIN RIVERWATER GEOLOGICINPUTOMBIOMASSVEGETATION WIND ES SED. Infiltration and runof f OMSED GPP EvapotranspirationEvaporationTranspiration Figure 3. System diagram of a floodplain forest. GPP = gross primary production; O.M. = organic matter; SED = sediment; ES = saturation deficit.

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19 SUNRAINWATERBIOMASSSurfaceRunoffVEGETATIONGEOLOGICINPUTLANDSUPPORT WIND ES OM SOIL GPP InfiltrationEvaporationTranspirationEvapotranspiration Figure 4. System diagram of an upland ecosystem. The upland ecosystems included mesic hardwood forests and pine flatwoods.

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20 Driving energies and ecosystem storages interact in several processes that generate ecosystem services. Three services (ecosystem functions) of these ecosystems were evaluated: (1) transpiration of water, (2) gross primary production (GPP), and (3) water recharge (infiltration). Mass and Energy Flows Data from the literature were used to evaluate the mass and energy flows for each of the ecosystems. Sunlight, wind, and rainfall were taken as average conditions for the North Central Florida location. Runin (sur face runoff into the wetland) for forested and scrub/shrub wetlands was cited from Heimburg (1984) and Schwartz (1989) respectively. A runoff coefficient of 0.35 and a 1:1 watershe d to wetland ratio was assumed for run-in to the marsh. Stream overbank flow, which represents the major portion of run-in water for the floodplain forest, was calculated from estimates of Brown (1978), and water budget equations. Mesic hardwood forests and pine flatwoods are not net sinks of run-in (Sun 1995). The geologic input to the forested wetland was estimated as 0.275 mm of limestone erosion per year (Odum 1984). The amount of limestone eroded from the interaction of acidic waters leaching th rough the underlying limestone creates and maintains the wetland depression. The geologi c input to shrub-scrub and marsh wetlands was assumed to be proportional to infiltration rates compared to the forested wetland: 78% and 9% less than the estimated value of the forested wetland for the shrub-scrub and marsh wetlands respectively. The geologic input to the floodplain ecosystem and the mesic hardwood forest and pine flatwoods eco systems was assumed to be equal to the average limestone erosion of Florida, or 10 mm every 1000 years as estimated from

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21 Odum (2000). The floodplain structure is also maintained by the constant work of the stream channel and overbank flow, and the shap e of stream channels and their floodplains is related to stream power (Gordon et al. 1992) For this reason, the stream geopotential, which describes a streams erosive capacity, was also used to quantify the geomorphic input to the floodplain ecosystem and was a dded to the geologic input necessary to maintain the land support. While five driving energies were evaluated, (sun, wind, rain, run-in and geologic processes), these flows are all co-products of the world process. Therefore, globally the emergy required for each is the same (Odum 1996). Adding the five driving energies would erroneously result in double counting the emergy required to supp ort the system. In order to determine the driving emergy of a particular system, Odum (1996) suggests using the largest of the geobiospheric inputs. Therefore, total driving emergy for the six ecosystems was calculated to be the sum of tr anspiration (water use, rather than water input) and geologic input, and river geopotential was also ad ded to the floodplain forest. Transpiration is the use of water for biological pr oduction while geologic inputs result from the erosion of limestone built hist orically. Similarly, for the floodplainforest, the work of stream geopotential over time contri butes to the structure of the floodplain. Geologic input of emergy can be added to present day annual emergy use without double counting since the limestone that is erode d is geologic contribution from a geologic storage built long ago. Ecosystem Services. GPP was estimated from the literature by summing net primary production (NPP) and community re spiration. The annual emergy driving GPP was taken as the sum of transpiration and geologic input (and river geopotential for the

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22 floodplain forest). Rates of transpiration and in filtration were taken or estimated from the literature and transformities were calculated as the weighted average of the transformities of rainfall and run-in for all ecosystems. Ecosystem Storages. Main storages evaluated included: biomass, peat or soil organic matter, water, and geomorphic structur e. The emergy of ecosystem storages was calculated by multiplying the annual emergy required to make the storage by its turnover time. Energy and/or mass values for each storage were obtained from the literature. Geomorphic structure, the basin structure found in depressional wetlands and the floodplain channels in riparian wetlands, is constantly maintained by the limestone erosion beneath the depressions or by the consta nt work of the stream This structure is unique to the different types of wetlands, and indirectly supports wetland vegetation by concentrating run-off into the depressional wetlands or the floodplain landform. Basin structure was calculated based on the amount of eroded material in the underlying limestone. Odum (1984) calculated that 1818 years are required to generate a 50 cm deep depression beneath cypress wetla nds based on a 0.275 mm/year erosion rate of limestone. The emergy of the basin st ructure, then, is th e annual driving emergy multiplied by 1818 years. Similarly, the em ergy of shrub-scrub and marsh wetland basin structure was calculated based on the amount of material eroded and the number of years required. Floodplain structure was calcu lated by estimating the mass of channel and levee displaced (Figure 5). This was calculated by multiplying the volume of displaced sediments by the bulk density of the sediments, or 1.2 g/cm 3 Turnover time of the floodplain was estimated as the time required fo r the stream channel to move across the

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23 floodplain (Figure 6). This was estimated to be approximately 1000 years. The emergy of this structure is therefore the annual driving emergy multiplied by the time required to create the structure. Mesic hardwood forests and pine flatw oods are not characterized by unique structures such as basins or floodplain channels. The la nd support (structure) beneath upland ecosystems is replenished yearly by equa l rates of erosion and uplift. The same land support exists beneath depressional wetl ands and floodplain ecosystems, however its contributions are negligible compared to th e emergy needed to create wetland basin or floodplain morphology. Therefore, the storage of land support was not calculated for the upland ecosystems since the structure is not unique to those systems. Calculation of Transformities Transformities for driving energies of sunlight, wind, chemical potential energy of rain, and geologic input were ta ken from Odum (1996). The transformity of stream water (chemical potential) was taken from Buenfil (2000). The one remaining source, chemical potential of run-in, was calculated by mu ltiplying the transformity of rain by the appropriate rain:run-in ratio for each ecosystem. Transformities for ecosystems services of transpiration, infiltration, and gross primary production (GPP) were calculated from the annual driving emergies. A weighted average of rainfall and run-in was used to calculate the transformities for transpiration, infiltration, and water storage, using the rati onale that these flows are a mixture of the two water inputs (Figure 7). The emergy driving GPP was the sum of wa ter used (transpiration) and geologic input (as well as stream geopotential for the floodplain forest). The rationale of using

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24 10 m2 m 100 m2 m (B)(C)( A )2 m2 m Channel Mass = Width Depth Length Sinuosity = 10 m 2 m 100 m 1.2 = 2400 m 3 Levee Mass = 2 levees height *width length sinuosity = 2 0.3 m 2 m 100 m 1.2 = 144 m 3 Total Mass = 2544 m 3 Bulk Density = 1.2 g/cm 3 Mass = 3.05 E+9 g Total driving emergy = Sum of transpiration, geologic input and river geopotential = 3.97 E+15 sej/yr Emergy/gram = (3.97 E+15 sej/yr *1000) 3.05 E+9 = 1.29 E+09 sej/g Figure 5. Boundary of Floodplain Ecosystem (A), with cross-sectional dimensions of channel and levees (B), and calculations of mass displacement (C).

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25 1 hectare ofFloodplain ForestFLOODPLAINStreamChannelUPLANDUPLAND 0 yrs2004006008001000 yrsTime ( A )(B) Figure 6. Schematic of floodplain ecosystem structure showing the 1 hectare area evaluated (A). The turnover time of the floodplain is illustrated in (B), where each box represents a 200 year migration of the stream channel, completing the entire c y cle across the flood p lain and back a g ain in an estimated 1000 y ears.

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26 both is that transpiration is re quired to drive biological pro cesses and the limestone that is eroded is geologic contribution from a geologi c storage built long ago. Both the biologic and geologic processes are coupled and are required for GPP. The transformity was calculated as the sum of th e annual water use and contribution from geologic input divided by the energy of annual GPP. Transformities for storages of the six ecosystems were calculated using the emergy driving the systems, except for the transformity of water storage, which was assumed to be a weighted average of rainfall and run-in (Figure 7). Live biomass was the sum of all live above ground biomass includi ng trees, shrubs and understory vegetation. The transformity for biomass was calculat ed by multiplying annual emergy inputs (sum of transpiration and geologic input) by the turnover time of the biomass, and subsequently dividing by the energy of standing stock.. Soil organic matter results from the accumulation of un-decomposed plant matter. Turnover time was calculated by dividing the organic matter storage by the accumulation rate, which was derived by subtracting d ecomposition from litterfall (Dighe 1977). Emergy of the peat storage was calculated as the annual emergy input to the ecosystem multiplied by turnover time of the peat storag e. Dividing the result by the energy content of the soil storage yielded the transformity. Transformity of basin structure in the cypress dome, shrub/scrub, and marsh was calculated by dividing the emergy required to create the depression (annual emergy inflow multiplied by time for development) by the mass of the displaced limestone. The transformity of the floodplain structure was ca lculated using the same rationale, thus,

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27 Rain Run-inWater StoredSunlightWater UsedTranspiration Transformity (Twt)=(E n e r g y o f W a t e r U s e d ) ( T w s ) J of waterInfiltration Transformity (Twi) =( E n e r g y o f W a t e r ) ( T w s ) J of water Transformity (Tws) = (Rain TRain) + (Run-in TRun-in) J of water Figure 7. Diagram of transformity calculations for water stored, infiltration, and transpiration.

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28 Emdollar Evaluation For comparative purposes and to provide units more familiar to the public, emergy values were expressed as emdollars. Emdollars were calcu lated by dividing the emergy value of environmental services and natural capital by the emergy/money conversion ratio for the USA economy in 2000, which was equal to 0.96E+12 sej/$. The emergy/money ratio for 2000 was obtaine d using methodology employed by Odum (1996), and data from the U.S. Statistical Abstract (2001). The emergy money ratio is calculated by dividing the to tal emergy used in driving the U.S. economy by the Gross National Product (GNP) of the United States. Figure 8 shows emergy money ratios from 1980 to 2000. This ratio expresses the am ount of emergy required per dollar of circulation. By dividing em ergy flows and storages of the ecosystems by the emergy money ratio, the flows and storages are equate d with the amount of currency they could drive in circulation. Emergy Evaluation of a Co nstructed Forested Wetland Constructed wetland projects ca n be divided into three main stages: first, a wetland ecologist with a cons ulting firm performs a preliminary site selection. Elevations of the property and surrounding wetla nds are surveyed to use as template for the creation and design of the constructed wetland. Second, upon completion of the necessary surveys and permitting paperwork, construction begins. The site is cleared of the existing vegetation, excavated, contoure d, and when the time and/or hydrology are favorable, planted with desired vegetation. La stly, several success criteria stipulated in the permit application are monitored for an average of 3 years. Ecological data is collected annually to ascertain complian ce with the success criteria, and annual

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29 0.600.901.201.501.802.102.402.703.003.30198019811982198319841985198619871988198919901991199219931994199519961997199819992000YearSolar emergy/$ (1.0E+12 sej/ $ Figure 8. Emergy per dollar (sej/$) of the United States from 1980-2000. Values from 1980-1993 taken from Odum (1996), while from 1994-2000 calculated using data from the U.S. Statistical Abstract (2001) and the smethods employed by Odum (1996). ame

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30 monitoring reports are submitted to the appr opriate agencies. Exotic and nuisance species are manually removed or sprayed when needed. The mitigation site is considered successful when the following parameters have been achieved: 1) 80% survival of planted trees 2) At least 80% cover of herbaceous species 3) Less than 10% cover of e xotic and nuisance species 4) Hydrologic conditions that conform to those observed in adjacent natural wetlands. Data from a newly constructed forested wetland in North Florida were used to evaluate the inputs necessary to create a wetland in order to calculate environmental costs and benefits of wetland creation. The entire mitigation consisted of 5.26 ha of constructed forested wetland and 2.4 ha of fr eshwater marsh. Only the forested wetland was used for the evaluation since the marsh wa s not completed. Costs were prorated to eliminate costs associated with marsh construction. Extensive groundwork was done on site. Though the area was already several feet below grade, elevation surveys revealed th at even lower elevations were necessary to support wetland vegetation with longer hydroperiods. Approximately 100,000 cubic meters of fill were removed from the site and stock piled on a mound next to the created wetland. No donor topsoil was laid in the fo rested wetland area. Instead, raised beds were constructed to provide more aeration fo r the seedling root zone. Construction costs for the forested wetland were approximately $122,000. Vegetation planting occurred on January 21, 2002. The site was partially flooded and soils were saturated. Sixteen people participated in the planting. Over 8,800

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31 seedlings of eight different species were plan ted. Seedlings averaged 25 cm in height. Fifty-six percent of seedlings were pond cypr ess, while the remaining 44% was shared by blackgum, red maple, dahoon holly, white ash (Fraxinus pennsylvanica), silver bay (Magnolia virginiana), sweetbay, and river birch (Betula nigra) Total plant costs were approximately $4,600. Figure 9 is a generalized systems diag ram of a constructed wetland ecosystem showing the main driving energies and purch ased inputs from the economy that were evaluated. Sunlight, wind, and rainfall were again taken as average values for North Central Florida. Inputs from the econo my included construction costs, imported vegetation, fertilizer, and human labor. Additionally, environmental losses of natural capital, such as biomass from the cleared vegetation and organic matter, were also added to the costs of construction. Monitoring e fforts extend approximately 3 years after construction and planting, and include labor (monitoring and spraying) and material (herbicide). Since this site was only recently completed, monitoring efforts were estimated from other mitigation sites th at have already been released. Simulation Models Forested Wetland Simulation Model A simulation model was developed to an alyze energy, emergy and transformity values of a mature forested wetland. The model simulates successional trends in a forested wetland, with particular emphasis on forest biomass and organic matter. In addition to simulating energy flows, emergy and transformity values of biomass and organic matter storages we re also calculated.

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32 Seedlings ConstructionServices Fertilizer Labor Herbicides WIND ES Transpiration SUNVEGETATION BasinStructure Rain Biomass OMSOIL Soil ExportedO.M.BiomassInvestment Figure 9. Systems diagram of a constructed forested wetland showing the renewable energies and the economic inputs to the system as well as the loss of soil organic matter and biomass resulting from excavation.

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33 Tilley (1999) identified three rules for simulating emergy dynamics of ecosystem storages. When the energy storage is incr easing, the net accumulation of emergy is the sum of all inputs minus the exports of u sed emergy. Unlike depreciation, which was defined as a process necessary for the mainte nance of the storage w ithout subtraction of emergy, exports carry away emergy with a transformity equal to that of the storage. When the energy storage is decreasing, the em ergy lost is equal to the energy exported times its transformity. When energy stored is in steady-state, the accumulated emergy remains the same. Model Parameters and Calibration Data from the literature were used to calibrate the model. Coefficient values were calculated for the mature steady-state conditi ons, i.e. storage values are constants and therefore inflows to a storage equal outflows from the storage at steady state. The energy model simulates 400 years of forest growth. Emergy and transformity simulations of biomass were run for 200 years, while the emergy and transformity of organic matter were simulated for 2000 years. In the baseline simulation initial biomass and organic matter values were set at 1% of their steady state values, while the nut rient storage was set at 10% of its steady state value. Multiple simulations were run by setting the organic matter initial storage at 25%, 50%, and 90% of its steady state value. Constructed Wetland Cost Recovery Model A simple linear, cost recovery model was simulated for a newly constructed wetland to calculate the time required for the ecosystem to recover the costs of construction. Simulated GPP flows from the forested wetland model were converted to

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34 emdollar flows and added to the negative valu es (costs) of constr uction and monitoring. At time step 0, the simulation began with a negative value of 103,111 em$/ha, the equivalent of construction costs. At ti me step 1, the first year GPP value from the forested wetland model was added to the co sts of construction, and the first year operational costs of maintenance, 703 em$/ ha, subtracted. The same methodology was employed for years 2 and 3, while at year 4 only the GPP emdollars were added. Yearly GPP values were taken from the simulati on model so that beginning values were relatively small and increasing with time to the steady-state values. The simulation was run for 150 years.

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RESULTS Emergy Evaluation of Ecosystems Energy, Emergy, and Transformity of Ecosystems The emergy evaluation tables for the six ecosystems are given in Appendix B, Tables 10 through 21. Details of calculations and data sources are given as footnotes to each table. Emergy signatures for each ecosystem are shown in Figure 10. The emergy signature of an ecosystem depicts the set of environmental energy flows on which its processes and storages depend. The main driving emergy of the depressional wetland ecosystems was geologic input. Geologic input to forested wetlands (Figure 10) is nearly 5 times the driving emergy of rain or run-in (5.5E+15 sej/ha/yr versus 1.17E+15 sej/ha/yr respectively). Geologic input in the shrub/scrub wetland was only slightly higher than rain or run-in (1.21E+15 sej/ha/yr versus 1.17E+15 sej/ha/yr and 1.18E+15 sej/ha/yr respectively). Similar to the forested wetland, geologic input to the herbaceous marsh is 4.2 times the driving emergy of rain or run-in (4.95E+15 sej/ha/yr versus 1.17E+15 sej/ha/yr). River geopotential was the main driving emergy of the floodplain forest, contributing nearly twice and 1.5 times the emergy of rain and run-in (2.2E+15 sej/ha/yr versus 1.17E+15 and 1.49E+15 sej/ha/yr respectively). Geologic input to the floodplain forest was very small (0.2E+15 sej/ha/yr) compared to the other wetland ecosystems. The main driving emergy of the upland ecosystems was rain, which contributed nearly 6 times the emergy of geologic input in both the mesic hardwood forest and pine flatwoods 35

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Figure 10. Emergy signature of six Florida ecosystems showing the environmental inputs to the system. S = sun; W = wind; R = rain; RI = runin; G = geologic input; RG = river geopotential. Note the different scale on each graph. Calculated from data in Appendix B, Tables 10-21. 0.04 0.00 1.17 1.17 5.500 1 2 3 4 5 6 7SWR RIGFORESTED WETLAND 0.04 0.00 1.17 1.18 1.210.0 0.3 0.6 0.9 1.2 1.5SWR RIGSHRUB/SCRUB WETLAND 0.04 0.00 1.17 1.17 4.95 0 1 2 3 4 5 6SWR RIGHERBACEOUS MARSH 0.04 0.00 1.17 1.49 2.20 0.20 0.0 0.5 1.0 1.5 2.0 2.5SWR RIRGGFLOODPLAIN FOREST 0.04 0.00 1.17 0.00 0.20 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4SWR RIGMESIC HARDWOOD FOREST 0.04 0.00 1.17 0.00 0.20 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4SWR RIGPINE FLATWOODS Empower Density, 1.0 E+15 sej/ha/y r Empower Density, 1.0 E+15 sej/ha/y r Empower Density, 1.0 E+15 sej/ha/y r Empower Density, 1.0 E+15 sej/ha/y r Empower Density, 1.0 E+15 sej/ha/y r Empower Density, 1.0 E+15 sej/ha/y r

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37 (1.17E+15 sej/ha/yr versus 0.2E+15 sej/ha/yr respectively). A comparison across ecosystems showed th at run-in and geologic input varied considerably between wetland and upland ecosystems. R un-in was highest in the floodplain forest (1.49E+15 sej/ha/yr), which re ceives its input from the adjacent stream, while the upland ecosystems had no run-in. Geologic input was highe st in the cypress dome and herbaceous marsh ecosystems (5.5E+15 and 4.95E+15 sej/ha/yr respectively); both had nearly 5 times the emergy than th e shrub/scrub ecosystem (1.21E+15 sej/ha/yr) and 25 times more than the floodplain forest and the terrestrial ecosystems (0.2E+15 sej/ha/yr). Annual driving emergy of the six ecosystems is shown in Figure 11. Annual driving emergy for the floodplain forest was th e sum of transpirati on, geologic input and river geopotential, while for the other ecosystems it was the sum of transpiration and geologic input. In all, the wetland ecosy stems had between 3 and 9 times (range of 2.2E+15 and 6.17E+15 sej/ha/yr) the annual driv ing emergy of the terrestrial ecosystems (range of 6.98E+14 and 8.74E+14 sej/ha/yr). A majority of this difference resulted from differences in geologic inputs. Ecosystem services of tran spiration and infiltration ar e shown in Figure 12. The emergy of transpiration for the floodplain fo rest (1.58E+15 sej/ha/yr) was approximately twice the value of all other ecosystems. Infiltration was similar in the forested wetland (0.76E+15 sej/ha/yr), herbaceous marsh (0.72E+15 sej/ha/yr), floodplain forest (0.81E+15 sej/ha/yr), and mesic forest ( 0.46E+15 sej/ha/yr). However, it was considerably lower for the shrub/scrub (0.17E+15 sej/ha/yr) and pine flatwoods

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Figure 11. Annual driving emergy of six Florida ecosystems (sum of transpiration, geologic input, and river geopotential for the floodplain forest; sum of transpiration and geologic input for all other ecosystems). Calculated from data in Appendix B, Tables 10-21. 6.98 8.74 3.97 5.80 2.20 6.17 0.00E+00 1.00E+15 2.00E+15 3.00E+15 4.00E+15 5.00E+15 6.00E+15 7.00E+15Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEmpower Density Annual driving emergy, sej/ha/yr

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Figure 12. Transpiration and infiltration values of six Florida ecosystems. (A) Power Density; (B) Solar Transformity; (C) Empower Density. See A pp endix B, Tables 10-21. 0.0E+00 1.0E+10 2.0E+10 3.0E+10 4.0E+10 5.0E+10 6.0E+10Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsPower Density, J/ha/yr Transpiration Infiltration 0.0E+00 5.0E+03 1.0E+04 1.5E+04 2.0E+04 2.5E+04 3.0E+04Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsSolar Transformity, sej/J Transpiration Infiltration 0.0E+00 3.0E+14 6.0E+14 9.0E+14 1.2E+15 1.5E+15 1.8E+15Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEmpower Density, sej/ha/yr Transpiration Infiltration

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40 ecosystem (0.02E+15 sej/ha/yr). Transformity of transpiration and infiltration were higher in the wetland ecosystems (mean of 26,887 sej/J) than in the terrestrial ecosystems (18,199 sej/J), due to their lack of run-in. GPP varied for the 6 ecosystems (Figur e 13). The floodplain forest (3.21E+12 J/ha/yr) was twice as produc tive as the forested wetland (1.54E+12 J/ha/yr), and these two ecosystems had considerably higher energy values than a ll other ecosystems (average of 5.46E+11 J/ha). Transformity of GPP va ried between 0.96E+3 and 14.4E+3 sej/J, and it was 7 times higher in the wetland ecosystem s than upland ecosystems (mean of 7.0E+3 and 1.0E+3 sej/J respectively). The fore sted wetland had the highest GPP emergy (6.17E+15 sej/ha/yr). Emergy storages of biomass (Figure 14) we re nearly an order of magnitude higher in forested wetlands (cypress and floodplain fore st) than in forested uplands (average of 23.4E+16 sej/ha in wetlands and 2.6E+16 sej/ha in uplands). While the floodplain forest had slightly higher biomass energy storage (3.3E+12 J/ha) than the forested wetland (2.9E+12 J/ha), once the energy storages were multiplied by their respective transformity, the forested wetland had approximately twice as much stored emergy than the floodplain forest (3.09E+17 versus 1.59E+17 sej/ha resp ectively). The herbaceous marsh had the lowest emergy storage of biomass (8.7E+15 sej/ha). Transformity of biomass ranged from a high of 10.7E+4 sej/J in the forested wetland to a low of 9.9E +3 sej/J in the pine flatwoods. Organic matter storage (Figure 15) was greatest in the herbaceous marsh (9680 E15 sej/ha) and smallest in the pine flatw oods (27 E15 sej/ha). Storages of organic matter were over fifteen times larger in the wetland ecosystems (49E+1 6 sej/ha) than in

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Figure 13. GPP values of six Florida ecosystems. (A) Power Density; (B) Solar Transformity; (C) Empower Density. See Appendix B, Tables 10-21. 0.00E+00 1.00E+12 2.00E+12 3.00E+12 4.00E+12Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsPower Density, J/ha/yr 0.00E+00 5.00E+03 1.00E+04 1.50E+04 2.00E+04Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsSolar Transformity, sej/J (B) 0.00E+00 2.00E+15 4.00E+15 6.00E+15 8.00E+15Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEmpower Density, sej/ha/yr (C)

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Figure 14. Biomass values of six Florida ecosystems. (A) Energy; (B) Transformity; (C) Emergy. See Appendix B, Tables 10-21. 0.0E+00 5.0E+11 1.0E+12 1.5E+12 2.0E+12 2.5E+12 3.0E+12 3.5E+12Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEnergy, J/ha 0.0E+00 2.0E+04 4.0E+04 6.0E+04 8.0E+04 1.0E+05 1.2E+05Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsTransformity, sej/J (B) 0.0E+00 5.0E+16 1.0E+17 1.5E+17 2.0E+17 2.5E+17 3.0E+17 3.5E+17Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEmergy, sej/ha (C)

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Figure 15. Organic matter values of six Florida ecosystems. (A) Energy; (B) Transformity; (C) Emergy. See Appendix B, Tables 10-21. 0.0E+00 2.0E+12 4.0E+12 6.0E+12 8.0E+12 1.0E+13 1.2E+13Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEnergy, J/ha (A) 0.0E+00 2.0E+04 4.0E+04 6.0E+04 8.0E+04 1.0E+05 1.2E+05 1.4E+05Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsTransformity, sej/J (B) 0.0E+00 2.0E+17 4.0E+17 6.0E+17 8.0E+17 1.0E+18 1.2E+18Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEmergy, sej/ha

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44 the terrestrial ones (3.2E+16 sej/ha). Transf ormity of organic matter ranged from a high of 12.3E+4 sej/J in the forested wetland to a low of 1.91E+4 se j/J in the mesic forest. Soil water is a function of the amount of organic matter in the system. The storage of water in the wetland ecosystems wa s assumed to be the water content of the peat soil plus the average standing water in the wetland (estimated as half the wetland depth). Differences of more than two orders of magnitude exist in emergy values of water storages (Figure 16) between the wetland and terrestrial ecosystems (5.9E+14 sej/ha and 4.4E+12 sej/ha resp ectively). Transformity of water storage and flows (transpiration and infiltration) in the wetland ecosystems was calculated as the weighted average of the inputs of rainfall (1.82E+4 sej/ J) and run-in (from 4.6E+4 to 5.2E+4 sej/J). Geologic structure (Figure 17), the result of thousands of years of geologic work, was the highest emergy storage in each of the wetland systems, and ranged from 11.2 E18 sej/ha in forested wetlands to 3.97E18 sej/h a in floodplain forests. Transformity of geologic structure (emergy per gram of materi al eroded to create the basin or channel) ranged from 1.12E+9 sej/g for forested wetla nds to 1.8E+9 sej/g for the shrub/scrub ecosystem. Emdollar Values of Ecosystems Representative emdollar values of ecosys tem services and natural capital for each ecosystem are given in the last column of each of the evaluation tables (Appendix B, Tables 10-21) and summarized in Tables 1 and 2. Ecosystem services of tran spiration, infiltration, and GPP are given in Table 1. Total ecosystem services, represented by GPP only to avoid double counting, ranged

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Figure 16. Soil water values of six Florida ecosystems. (A) Energy; (B) Transformity; (C) Emergy. See Appendix B, Tables 10-21. 0.00E+00 8.00E+09 1.60E+10 2.40E+10 3.20E+10 4.00E+10 4.80E+10Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEnergy, J/ha(A) 0.0E+00 5.0E+03 1.0E+04 1.5E+04 2.0E+04 2.5E+04 3.0E+04Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsTransformity, sej/J 0.0E+00 2.0E+14 4.0E+14 6.0E+14 8.0E+14 1.0E+15 1.2E+15Forested Wetland Shrub/Scrub Marsh Floodplain Forest Mesic Forest Pine FlatwoodsEmergy, sej/ha (C)

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Figure 17. Geologic structure of four wetland ecosystems. (A) Energy; (B) Transformity; (C) Emergy. See Appendix B, Tables 10-21. 0.0E+00 2.0E+09 4.0E+09 6.0E+09 8.0E+09 1.0E+10 1.2E+10 Forested WetlandShrub/scrubMarshFloodplain forestMass, g/ha(A) 0.0E+00 4.0E+08 8.0E+08 1.2E+09 1.6E+09 2.0E+09 Forested WetlandShrub/scrubMarshFloodplain forestTransformity, sej/g (B) 0.0E+00 2.0E+18 4.0E+18 6.0E+18 8.0E+18 1.0E+19 1.2E+19 Forested WetlandShrub/scrubMarshFloodplain forestEmergy, sej/ha

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47 Table 1. Summary of emdollar values of environmental services of six Florida ecosystems. Ecosystem Type Transpiration Infiltration GPP (em$/ha/yr) Forested Wetland $701 $787 $6,430 Shrub/Scrub Wetland $1,034 $177 $2,295 Freshwater Marsh $887 $754 $6,043 Floodplain Forest $1,642 $841 $4,140 Mesic Hardwood Forest $702 $479 $911 Pine Flatwoods $519 $18 $727 (See Appendix B, Tables 10-21)

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48 from 6,430 em$/ha/yr in forested wetlands to 727 em$/ha/yr in pine flatwoods. Wetland ecosystems contribute almost six times the en vironmental services of upland ecosystems (averages of 4,727 and 819 em$/ha/yr, respectively). Emdollar values of ecosystem storag es (Table 2) ranged from 12.6 million em$/ha/yr for forested wetlands to 49,819 em$/ha /yr for pine flatwoods. This significant difference in value is due to the large contribution of geologic st ructure to the wetland ecosystems. Geologic structure accounted for as much as 93% of total emdollar values. Without the geologic structure, herbaceous marshes had the highest emdollar value of 1,018,641 em$/ha. After subtracting geologic stru cture, organic matter (peat) accounted for nearly 99% of herbaceous marsh value. Organic matter had the second largest emdollar value in the four wetland ecosystems, and it was the highest contribu tion of upland ecosystems. Organic matter ranged from over 1,000,000 em$/ha in herba ceous marshes to 28,000 em$/ha in pine flatwoods. Organic matter accounted for, on aver age, 56% of total stored value in pine flatwoods and mesic forests. The range of emdollar values for live bi omass was relatively large. The emdollar value of forested wetland biomass was about 35 times as large as that of a typical marsh wetland (321,510 and 9,065 em$/ha/yr respectively). The floodplain forest biomass storage value was the second highest at 165,582 em$/ha, with shrub/scrub, mesic forest and pine flatwoods following at 45,896, 27,321, and 18,698 em$/ha/yr respectively. Finally, the emdollar values of stored wate r were the lowest of the four storages evaluated, accounting for less than 1% of total stored values.

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Ecosystem TypeLive BiomassOrganic MatterWaterGeologic StructureTotalWithout Structure Forested Wetland$321,510$566,304$511$11,690,095$12,578,420$888,325 Shrub/Scrub Wetland$45,896$237,184$206$11,379,949$11,663,235$283,286 Freshwater Marsh$9,065$1,008,438$1,139$6,104,113$7,122,754$1,018,641 Floodplain Forest$165,582$240,376$618$4,139,553$4,546,129$406,576 Mesic Forest$31,875$39,030$5$0$70,909$70,909 Pine Flatwoods$21,814$28,000$4$0$49,819$49,819 (See Appendix B, Tables 10-21). Table 2. Summary of emdollar values of natural capital (above ground biomass, organic matter, soil water and geologic structur e) of 6 Florida ecosystems. (em$/ha)

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50 Replacement Values of Ecosystems Table 3 summarizes the estimated re placement values of each ecosystem assuming complete elimination. The environmen tal services lost ar e calculated as the annual services (GPP) times ha lf the recovery time of th e newly constructed ecosystem (assuming construction of new wetlands to re place those destroyed). This was done to reflect that as a newly cons tructed wetland matures some services are replaced annually until a mature system has developed. Recovery times were estimated to be 60 years for forested wetland and floodplain forest, 50 years for mesic forest, 40 years for pine flatwoods, and 16 and 4 years for shrub/sc rub and marsh wetlands, respectively. The value of ecosystem structure (natural capital) that is destroyed is equal to the sum of biomass, peat and water, as shown in Table 3. The storage value of geologic structure was not included in the totals for natural ca pital since elimination of a wetland does not eliminate the underlying geologic structur e (see Figure 1). Th e total calculated replacement values ranged between 1,081,230 and 64,362 em$/ha. Emergy Evaluation of a Co nstructed Forested Wetland Emdollar costs of one hectar e of constructed wetland are shown in Table 4. The table is divided into four sections: renewable energy sources, purchased goods and services, environmental losses, and longterm monitoring efforts. Footnotes to each item appear in the following pages. Items 1-3 are the renewable en ergies that contribute to the system. These are also called free inputs as no money (dollars) ci rculates to pay for those services, and they are the same cont ributions evaluated in the six Florida ecosystems (Tables 10-21). Items 4-11 are the economic cont ributions to the

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51 Table 3. Summary of replacement values pe r hectare assuming complete elimination of wetland ecosystem. Ecosystem Type Environmental Services (a) Natural Capital (b) Total value (c) (Em$/ha) Forested Wetland $192,906 $888,325 $1,081,230 Shrub/Scrub Wetland $18,358 $283,286 $301,645 Freshwater Marsh $12,086 $1,018,641 $1,030,727 Floodplain Forest $124,187 $406,576 $530,763 Mesic Forest $22,768 $70,909 $93,677 Pine Flatwoods $14,543 $49,819 $64,362 (a) Replacement value of environmental services is the emdollar value of GPP over 1/2 recovery time. Estimate 60 years for both cypress and floodplain forest, 16, and 4 years for shrub/scrub, and marsh systems respectively, 50 years for mesic hardw ood forest and 40 years for pine flatwoods. (b) Replacement values of natural capital are the sum of storages in each ecosystem. The loss of basin structure was not considered. c) Total replacement value is the sum of environmental services and natural capital.

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52 Table 4. Emergy evaluation of the inputs to cons truct a forested wetland in Florida (J/ha). Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej) (2000 em$) Renewable Energy Sources 1 Sun 4.19E+13 J/yr 1 0.04 $44 2 Wind 2.96E+09 J/yr 1496 0.004 $5 3 Rain, chemical potential 6.42E+10 J/yr 18199 1.17 $1,217 Total Renewable Energy (taken as largest to avoid double counting) $1,217 Purchased Goods and Services 4 Construction services 2.33E+04 $ 1.12E+12 26.08 $27,170 Vegetation Planting 5 Biomass 8.39E+07 J 40000 0.00 $3 6 Cost $870 $ 1.E+12 0.83 $870 Fertilizer 7 Active ingredients 6.68E+03 g 2.80E+09 0.02 $19 8 Cost $102 $ 9.60E+11 0.10 $102 Labor 9 Planting 3.06E+07 J 2.5E+07 0.75 $783 10 Planning and permitting 5.54E+07 J 7.3E+07 4.06 $4,229 11 Costs $4,125 $ 9.6E+11 3.96 $4,125 Environmental losses 12 Biomass 2.53E+12 J 1.2E+04 30.60 $31,875 13 Organic Matter 1.96E+12 J 1.9E+04 37.47 $39,030 Total Goods and Services and Environmental Losses (Items 4, 6, 8, 9, 10, 12, 13) $103,111 Longterm monitoring efforts 14 Chemicals (Herbicides) $64 $ 9.60E+11 0.06 $64 Labor 15 Spraying 1.15E+07 J 2.5E+07 0.28 $294 16 Monitoring 2.29E+07 J 7.3E+07 1.68 $1,750 Total $2,108 Per year $703 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000.

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53 Notes to Table 4. RENEWABLE ENERGY SOURCES 1 SOLAR INSOLATION (assume 1 year of sunlight) Area of wetland = 1.00 ha Mean Net Radiation = 274 Ly (Henning 1989) = (1.0E+04 m 2 /ha)(274 Ly)(10 Cal/m 2 /Ly)(4186 J/Cal)(365 days) = 4.19E+13 J/ha/yr Transformity = defined as 1 (Odum 1996) 2 WIND (assume 1 year of wind) Area = 1.00E+04 m 2 Density = 1.3 Kg/m 3 Drag. Coefficient = 1.00E-03 (Odum 1996) Av. Annual Velocity = 1.16 mps (Jones et al.1984) Geostrophic wind = 1.93 (observed winds are about 0.6 of geostrophic wind) = (area)(density)(Drag Coeff.)(velocity) 3 (3.15E7 sec/yr) = 2.96E+09 J/ha/yr Transformity = 1,496 sej/J (Odum 1996) 3 RAIN, CHEMICAL POTENTIAL (assume 1 year of rain) Area = 1.00E+00 ha Rainfall = 1.3 m/yr (NOAA 1985) Gibbs Free Energy = 4.94 J/g2 = (1.00E+04 m 2 /ha)(1.3 m)(4.94 J/g)(1.00E+06 g/m 3 ) = 6.42E+10 J/ha/yr Transformity = 18,199 (Odum 1996) PURCHASED GOODS AND SERVICES 4 CONSTRUCTION SERVICES Six weeks of earthwork for entire site (7.66 ha: 5.26 ha of forested wetland and 2.4 ha of freshwater marsh) using the following equipment: 5 pans, 3 dozers, 1 backhoe, 2 trucks, and 1 motor grader. Total cost of construction (including labor) was approximately $175,000. Cost for forested area (70% of total area) approximately $122,500, or $23,289/ha. Cost = 23,289 $/ha Transformity = 9.60E+11 sej/$ 5 VEGETATION BIOMASS Planting for forested wetlands occurs on 7-10 foot ce nters. 8 tree species were planted at this site: Taxodium ascendens, Nyssa aquatica, Acer Rubrum, Persea palustris, Magnolia virginiana, Betula nigra, Ilex cassine, and Fraxinus americanus. Total number of tree seedlings was 8790. Number of seedlings = 8790 seedlings Average dry weight/seedling = 3 g Biomass = (3 g/seedling)(8790 seedlings)(4 kcal/g)(4186 J/kcal)/5.26 ha = 8.39E+07 J/ha Transformity = 4.00E+04 sej/J (estimate)

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54 Notes to Table 4 continued. 6 VEGETATION COST Cost of seedlings only was $4574. Cost = 870 $/ha Transformity = 9.60E+11 sej/$ (Odum 1996) 7 FERTILIZER, ACTIVE INGREDIENTS The slow release fertilizer "Agriform" was applied to each hole in which a seedling was planted. One 10 g tablet for each seedling. Main ingredients are: 20% Total N, 10% Phosphoric Acid (P2O5), 5% soluble Potash (K2O), 2.8% Ca, 2% Na, .5% Fe, .5% Mg, and binding agents. Fertilizer = (10 g/seedling)* 8790 seedlings/5.26ha = 16711 g Active Ingredients = 6684 g (40% of mass) Transformity = 2.80E+09 sej/g (weighted ave., Lagerberg and Brown 1999) 8 FERTILIZER, COST Agriform: 1 box (1000, 10g tablets) = $61. No. of boxes for this site: 8.8. Total cost $537, or $102/ha. Cost = 102 $/ha Transformity = 9.60E+11 sej/$ (Odum 1996) HUMAN LABOR 9 HUMAN LABOR, PLANTING: 16 people for 1 day (8 hours). Combined days of work= 16 days Human Input= (16 days)(2,400 kcal/day)(4186 J/kcal)/5.26ha = 3.06E+07 J/ha Transformity = 2.46E+07 sej/J (Odum 1996) 10 HUMAN LABOR, PLANNING AND PERMITTING: Surveying, Planning, Permitting and Monitoring. Pre-construction = 6 days; design = 8 days; construction oversight = 15 days. Combined days of work= 29 days Human Input= (29 days)(2,400 kcal/day)(4186 J/kcal) = 2.91E+08 J/5.26 ha = 5.54E+07 J/ha Transformity = 7.33E+07 sej/J (Odum 1996) 11 HUMAN LABOR, COSTS Total Costs for forested wetland = $21,700 $/5.26 ha Per hectare = $4,125 $/ha Transformity = 9.6E+11 sej/$ (Odum 1996)

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55 Notes to Table 4 continued. ENVIRONMENTAL LOSSES 12 BIOMASS Assume construction site was historically a mesic hardwood forest. Biomass structure taken from Table 19 in this study. 13 ORGANIC MATTER Assume construction site was historically a mesic hardwood forest. Organic matter structure taken from Table 19 in this study. LONGTERM MONITORING EFFORTS 14 CHEMICALS Rodeo herbicide for aquatic conditions is used to spray exotic species. Based on 2 spray events/year for 3 years of monitoring for a total of 6 events. 2.5 gallons at $337. Chemicals= 64 $/ha (Forestry Suppliers catalog) Transformity = 9.60E+11 sej/$ (Odum 1996) LABOR 15 One person spraying for 1 day for each event. Two spray events per year for 3 years. Combined work days= 6 days Labor= (6 days)(2,400 kcal/day)(4186 J/kcal)/5.26 ha = 1.15E+07 J/ha Transformity = 2.46E+07 sej/J (Odum 1996) 16 Monitoring: 2 person 2 days/year for 3 years. Work days = 12 days Labor = (12 days)(2,400 kcal/day)(4186 J/kcal)/5.26 ha = 2.29E+07 J/ha Transformity = 7.33E+07 sej/J (Odum 1996)

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56 construction of a wetland. C onstruction services make up approximately 84% of total purchased goods and services. Emdollar valu es of the other economic inputs (vegetation, fertilizer and labor) were cal culated both on the basis of th e dollar spent and the energy contributed. In the case of vegetation and fertilizer, the em ergy contributed by the actual products was much smaller than the price paid for it. Items 12 and 13 represent the loss of natural capital (biomass and or ganic matter) of the ecosystem previously present on the constructed site. Wetlands are usually built on degraded uplands, therefore the values of biomass and organic matter for the mesic hardwood forest ecosystem were used to quantify those losses. When tabulating total emdo llar costs, only items 4, 6, 8, 9, and 10, 12, and 13 were added to avoid double countin g. Total construction costs were 103,111 em$/ha/yr. Environmental losses were almo st 70% of total costs, with construction services accounting for 26%. Labor costs were about 4% of total co sts, while vegetation and fertilizer accounted for the remainder. Following construction, the created wetla nd is monitored for approximately 3 years. Total longterm monitoring efforts were equal to 2,108 em$/ha, or 703 em$/ha/yr. Labor accounts for 96% of those costs, while herbicides account for the remainder. Simulation Models Forested Wetland Simulation Model Figure 18 is a system diagram of the ecosy stem flows and storages included in the simulation model. The system boundary of the model is one hectare of forested wetland. Main driving energies of this ecosystem ar e sun, rain, run-in, and geologic input. Main ecosystem storages are soil water, biomass, organic matter, and nutrients. Nutrients are modeled as a storage rather than a flow through the system since in forested wetlands

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ORGANIC MATTER WATER BIOMASS WIND ES SUN RUN-IN GEOLOGIC INPUT RAIN NUTRIENTS Runoff+infiltration ExportedN ExportedBiomass ExportedOM J15 Rain Run-inGJ14J1 J0 R J7 J9 J8J2J12 J16J3 J6 J4 J10 J11 J5J17 N N Figure18.Systemsdiagramoftheforestedwetlandsimula tionmodelshowingenergyflowsandstoragesevaluated.

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58 nutrient turnover is tightly linked to biomass and organic matter turnover. Table 5 presents the mathematical equations and flow values used in the model, as well as the notes to those calculations. Table 6 provides the values used for each storage and the calibrated coefficients. Emergy and transfor mity of biomass and organic matter were calculated using formulas in Figure 19 and 20. Energy, Emergy and Transformity of Forested Wetland Model Figure 21 shows the simulation results of biomass and organic matter storages in the forested wetland model. Biomass grew at a faster rate than organic matter and reached 90% (2.61E+12 J/ha) of its maximu m (2.9E+12 J/ha) after 165 years. Organic matter had much slower growth and reach ed 90% (3.98E+12 J/ha) of its maximum (4.42E+12 J/ha) by year 386. Simulated emergy and transformity of biomass are given in Figure 22. While emergy values increase steadily from time 0, tr ansformity values st art out extremely high (1.9E+5 sej/J) and keep increasing for the firs t 11 years to a maximum of 1.14E+6. At year 12 they begin decreasing steadily until th ey reach steady state by year 924 at 4.3E+4 sej/J. Emergy of biomass storage reached st eady state of 1.25E+17 sej/ha by 421 years. Organic matter emergy and transformity va lues peaked around year 1700 (Figure 23). Transformity of organic matter rapidly increased until year 29 to a value of 3.15E+5 sej/J. Between year 29 and year 164, transfor mity decreased slightly to 7.88E+4 sej/J, and then began ascending until it leveled off by 1700 years at a value of 1.3E+5 sej/J. Emergy of organic matter reached a maximum value of 5.77E+17 by 1880. Increasing the organic matter storage to 25%, 50%, and 90% of its steady state value had a considerable effect on biomass st orage growth (Figure 24), but did not result

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59 Table 5. Storage and internal flow equa tions for the forested wetland simulation model. Note Symbol Equation Value Definition Storage Equations dB = J 1 J 2 J 3 J 4 dOM = J 5 J 6 J 7 dN = J 8 +J 9 + J 10 + J 11 J 12 J 13 dSW = Rain + Run-in J 14 J 15 J 16 Item Internal Flows 1 R I/(1+K 0 *SW*B*N*G) 4.19E+12 Remaining Sunlight 2 J 0 k0*SW*B*N*G*R 4.19 E+13 Sunlight Received by Trees 3 J 1 k 1 *SW*B*N*G*R 2.05E+11 Net Primary Production 4 J 2 k 2 *B 7.72E+10 Litterfall 5 J 3 k 3 *B 6.63E+10 Exported Biomass 6 J 4 k 4 *B 6.15E+10 Biomass depreciation 7 J 5 k 5 *B 3.86E+10 Litter Accumulation 8 J 6 k 6 *OM 1.27E+10 Exported OM 9 J 7 k 7 *OM 2.59E+10 OM Depreciation 10 J 8 k 8 *B 7.44E+05 Nutrients from Litter Decomposition 11 J 9 k 9 *OM 3.84E+05 Nutrients from OM depreciation 12 J 10 k 10 *Rain 3.99E+05 Nutrients in Rain 13 J 11 k 11 *Run-in 4.70E+05 Nutrients in Run-in 14 J 12 k 12 *N 4.99E+05 Exported Nutrients 15 J 13 k 13 *SW*B*N*G*R 1.50E+06 Nutrient uptake by Trees 16 J 14 k 14 *SW*B*N*G*R 2.57E+10 Transpiration 17 J 15 k 15 *SW 3.49E+10 Evaporation 18 J 16 k 16 *SW 2.88E+10 Runoff & Infiltration 19 J 17 k 17 *SW*B*N*G*R 1.34E+12 Respiration Item Constant Flows 20 Rain 6.42E+10 Rain input to the system 21 Run-in 2.52E+10 Run-in input to the system 22 G 5.50E+06 Geologic Input

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60 Notes and calculations to flow values in Table 5. 1 Remaining Sunlight Estimated as 10% of Sunlight 2 Sunlight Received by Trees Table 10 3 Net Primary Production Table 10 4 Litterfall Litterfall = 461 g/m 2 /yr (Deghi 1977) Energy = (461 g/m 2 /yr)(1.0E+04 m 2 /ha)(4 Cal/g)(4186 J/Cal) = 7.72E+10 J/ha/yr 5 Exported Biomass Calculated as NPP Litterfall Biomass depreciation Exports = 6.63E+10 J/ha/yr 6 Biomass depreciation Approximately 30% of NPP 7 Litter Accumulation Organic matter from litterfall 50% of litterfall (Deghi 1977) 8 Exported OM OM in percolating waters = 100 g/m 3 (Odum 1984) = (100 g/m 3 )*(.584 m)*(1E+4 m 2 /ha)(5.2 Cal/g)(4186 J/Cal) = 1.27E+10 J/ha/yr 9 OM Depreciation Calculated as OM from litter Exported OM 10 Nutrients from Litterfall Decomposition P in litter = 0.84 mg/g dry weight (Brown 1978) = (.84 mg/g)(461 g/m 2 /yr)*(50% decomp.)*(1E+4 m 2 /ha) *(1E-3 g/mg)*(384 J/g) = 7.44E+05 J/ha/yr 11 Nutrients from OM depreciation P from OM = P concentration in depreciation OM OM Depreciation = 2.59E+10 J/ha/yr = 1.19E+06 g/ha/yr P in OM = 0.84 mg/g dry weight (assume same as litterfall) P from OM = 3.84E+05 J/ha/yr 12 Nutrients in Rain P in rain = 0.08 g/m 3 (Brown 1978) Rain = (1.3 m)(1E+4 m 2 /ha)(0.08 g/m 3 ) 1040 g/ha/yr P in rain = (1040 g P)(384 J/g) = 3.99E+05 J/ha/yr

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61 Notes and calculations to flow values in Table 5 continued. 13 Nutrients in Run-in P in run-in= 0.24 g/m 3 (Brown 1978) Run-in = (.51 m)(1E+4 m 2 /ha)(.24 g/m 3 ) P in run-in = 1224 g/yr = (1224 g P)(384 J/g) = 4.70E+05 J/ha/yr 14 Exported Nutrients EXPORTED P = Balance J 8 + J 9 + J 10 + J 11 J 13 15 Nutrient uptake by Trees P uptake by Biomass = 0.39 g P/m 2 /yr (Brown 1978) = 1.50E+06 J/ha/yr 16 Transpiration Table109 17 Evaporation From water balance Rain + Run-in = Transpiratio n + Evaporation + Runoff&Infil = 3.49E+10 J/ha/yr 18 Runoff&Infil Table 10 19 Respiration Table 10 20 Rain input to the system Table 10 21 Run-in input to the system Table 10 22 Geologic input Table 10

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62 Table 6. Steady-state values of the stor ages and calibrated coefficients for the forested wetland simulation model. Symbol Value Storages B = 2.90E+12 OM = 4.42E+12 N = 6.37E+07 SW = 1.87E+10 Coefficients k0 = 4.73E-37 k 1 = 2.57E-39 k 2 = 2.66E-02 k 3 = 2.29E-02 k 4 = 2.12E-02 k 5 = 1.33E-02 k 6 = 2.88E-03 k 7 = 5.86E-03 k 8 = 2.56E-07 k 9 = 8.68E-08 k 10 = 6.22E-06 k 11 = 1.87E-05 k 12 = 7.83E-03 k 13 = 1.88E-44 k 14 = 3.23E-40 k 15 = 1.87E+00 k 16 = 1.54E+00 k 17 = 1.52E-38

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63 GeologicInput Sunlight Emergy in Exported Biomass =(Energy of Biomass Exported)(TB)Emergy in Litterfall =(Energy of Litterfall)(TB)+BiomassEmergyTranspiration Emergy (Transpem) =(Energy of Transpiration)(Tws) Emergy of Biomass (Bem) = J6 Tws) + (G Tgeo) (J2 TB) (J3 TB) = [(k6*SW*B*N*G*R Tws)] + [(G Tgeo)] [(k2 B) TB][(k3 B) TB]Geologic Input Emergy (Geoem) =(Mass of Geo input)(Tgeo)Tws = 26202 sej/J Tgeo = 1.00E+9 sej/gTransformity of Biomass (TB) = E m e r g y o f B i o m a s s Ene r g y ofBiomass RainUsedRain used =(Transpiration)(Tws) J6GJ2J3 Figure 19. Emergy system diagram showing calculations of emergy and transformity of biomass in the forested wetland simulation model.

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64 Biomass Sunlight Emergy in Litterfall =(Energy of Litterfall)(TB) OrganicMatter Emergy in Exported OM =(Energy of ExportedOM)(TOM)Emergy in Accumulation =Emergy in Litterfall DecompositionEmergy of Organic Matter (OMem) = Accumulationem ExOMem= (J5 TB) (J6 TOM)= [(k5* B) TB] [(k5 OM) TOM]Transformity of Organic Matter (TOM) = E m e r g y o f O r g a n i c M a t t e r ( s e j / J ) Ene r g y o f OM ( J ) Decomposition = 50% of Litterfall J5J6 Figure 20. Energy diagram showing calculations of emergy and transformity of organic matter in the forested wetland simulation model.

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Figure 21. Simulation results of the forested wetland model showing time series of forest biomass and organic matter storages. 0.E+00 1.E+12 2.E+12 3.E+12 4.E+12 5.E+12 0 100 200 300 400Time, yrOrganic Matter, J/ha0.0E+00 6.0E+11 1.2E+12 1.8E+12 2.4E+12 3.0E+12 3.6E+12 4.2E+12 4.8E+12Biomass, J/haOrganic MatterBiomass

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Figure 22. Emergy and transformity of forest biomass storage in forested wetland model. 0.E+00 3.E+16 6.E+16 9.E+16 1.E+17 2.E+17 0 50 100 150 200Time, yrEmergy, sej/ha0.0E+00 2.0E+05 4.0E+05 6.0E+05 8.0E+05 1.0E+06 1.2E+06Solar Transformity, sej/JEmergy Transformity

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Figure 23. Emergy and transformity of organic matter storage in forested wetland model. 0.E+00 1.E+17 2.E+17 3.E+17 4.E+17 5.E+17 6.E+17 0300600900120015001800Time, yrEmergy, sej/ha0.0E+00 4.0E+04 8.0E+04 1.2E+05 1.6E+05 2.0E+05Solar Transformity, sej/JEmergy Transformity

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68 in any changes to emergy and transformity of biomass. The 25%, 50%, and 90% increase resulted in biomass reaching 90% of its steady state within 141,119, and 98 years, respectively, instead of the 165 years require d in the baseline simulation. Setting organic matter to 25% and 50% of its steady state value enabled th e organic matter storage to reach 90% of its steady state value in 360 and 328 years, respectively, instead of the 386 years necessary in the baselin e simulation (Figure 25). Constructed Wetland Cost Recovery Model Emdollar GPP flows for the forested wetla nd model are shown in Figure 26. GPP was calculated by adding NPP (J 1 ), and respiration (J 17 ). In the forested wetland model, GPP grows rapidly until year 50, after which growth is much slower and it begins to level off around 6.0E+3 em$/ha/yr at 214 years. Figur e 26 depicts the recovery time of a constructed wetland ecosystem. At time 0, th e ecosystem has a negative balance of 103,111em$/ha. Though the ecosystem begins to recover some of its initial costs with the addition of GPP, its balance is lower by year one because of the monitoring costs. The lowest balance occurs at year 3 (105,000 em$/ha) with the la st installment of monitoring costs. Then, the ecosystem begi ns to recover and as it matures more GPP services are added each year. The value of eco system services of GPP equals the costs of construction by year 54. At this time the eco system has paid off its debt and begins accruing positive value. Increasing the baseline organic matter storage to 25%, 50% and 90% of its maximum had considerable effects on GPP ra tes and thus recovery time (Figure 27). Additionally, increasing the baselin e organic matter storage also translated into decreased environmental losses, and thus decrease d construction costs. Mesic hardwood

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Figure 24. Simulation results of biomass energy storage after increasing initial organic matter storage to 25%, 50% and 90% of its steady state value, showing increased growth rates as the initial organic matter value increases. 0.0E+00 5.0E+11 1.0E+12 1.5E+12 2.0E+12 2.5E+12 3.0E+120 20 40 60 80 100 120 140 160 180Time, yearBiomass, J/ha Baseline, OM=1% OM=25% OM=50% OM=90%

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Figure 25. Simulation results of organic matter energy storage after increasing initial organic matter storage to 25% and 50% of its steady state value, showing increased growth rates of organic matter. 0.0E+00 5.0E+11 1.0E+12 1.5E+12 2.0E+12 2.5E+12 3.0E+12 3.5E+12 4.0E+12 4.5E+12 050100150200250300350Time, yearOrganic Matter, J/ha Baseline, OM=1% OM=25% OM=50%

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Figure 26. Simulation of (A) GPP emdollar value and (B) recovery time needed to payback construction costs (calculated by adding yearly GPP to initial debt). 0.0E+00 1.0E+03 2.0E+03 3.0E+03 4.0E+03 5.0E+03 6.0E+03 7.0E+030 10 20 30 40 50 60 70 80 90 100 110 120 130 140Time, yearGPP, em$/ha/yr -2.0E+05 -1.0E+05 0.0E+00 1.0E+05 2.0E+05 3.0E+05 4.0E+05 5.0E+05 6.0E+050 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150Time, yearEm$/ha

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72 forests have approximately half of the orga nic matter of forested wetland (Appendix B, Table 11 and 19). Therefore, if the organic matter starts off at 25% of its steady state value in the simulation model, then initia l construction costs amounted to 83,600 em$/ha (the original 103,111em$/ha minus 19,115 em$/ha or 50% of organic matter of mesic hardwood forests). In this scenario, ecosys tem services of GPP equal construction costs by year 48 (Figure 27). Similarly, increasing the organic matter st orage to 50% in the simulation model resulted in construc tion costs of 64,081 em$/ha (original 103,111 em$/ha minus 39,030 em$/ha, or approximately 100% of organic matter value of mesic hardwood forests) and a recovery time of 42 years (Figure 27). Finally, if additional organic matter is imported from other sources to equal 90% of the forested wetland steady state value, constructi on costs remain at 64,081 em$/ha, but GPP slightly increases to yield a recovery time of 40 years (Figure 27).

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Figure 27. Simulation results of GPP and recovery time under different initial organic matter storage values, showing an increase in GPP (A) and a decrease in recovery time (B) as the initial organic matter storage is increased by 25%, 50% and 90% of its steady state value. -2.E+05 -1.E+05 0.E+00 1.E+05 2.E+05 3.E+05 4.E+050 10 20 30 40 50 60 70 80 90 100Time, year Baseline, OM=1% OM=25% OM=50% OM=90%(B)Em$/ha 0.E+00 1.E+03 2.E+03 3.E+03 4.E+03 5.E+03 6.E+03 7.E+030 10 20 30 40 50 60 70 80 90Time, yearGPP, em$/ha/yr Baseline, OM=1% OM=25% OM=50% OM=90%(A)

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DISCUSSION Ecosystem Services and Natural Capital This study calculated emergy and emdollar values for services and natural capital of six Florida ecosystems. Wetlands in Florida are protected by laws and regulations that prevent their uncompensated destruction. These policies are justified since this research showed that from an energetic analysis, wetland ecosystems are much more valuable than uplands both in terms of the yearly services they provide to society and in the natural capital (structure) they store. However, current policy that values wetlands between $45,000 and $75,000 per acre ($112,500 to $187,500 per hectare) seriously undervalues them. The emdollar values of structure and environmental services (Tables 1 and 2) can be used to determine an approximate monetary value for wetlands and their environmental services. These values are appropriate for deriving fair mitigation ratios among different ecosystems and should not be confused with market values of wetlands. On an annual basis wetlands provide between 2,295 and 6,430 em$/ha/yr of value to regional human economies, compared to the two upland ecosystems values of 727 and 911 em$/ha/yr (Table 1). The natural capital of wetlands (without including geologic structure) ranges from approximately 283,000 to over 1,000,000 em$/ha (Table 2). Compared to the upland ecosystems, whose emdollar values ranges from approximately 74

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75 50,000 to 71,000 em$/ha, wetlands, on the average, have almost 11 times as much value in their natural capital. These values can be used to determine th e monetary costs for replacing services and natural capital lost as a result of development. Whenever a price is placed on wetlands, it usually reflects the costs of building wetlands, which includes land acquisition, planning, construction, and monitoring. These values are costs in economic terms based on actual (or maybe perceived) cost s to construct wetlands in Florida, but in reality they do not reflect the value of environmental services or structure that is lost when a wetland is destroyed. A better measure of what society loses with each hectare of wetland conversion is suggested by the replacemen t values (Table 3) calculated in this study. For instance, if a forested wetland were cut, the appropriate loss value could be calculated from the biomass storage and GPP loss. The current price for wetlands in Florida ranges between $112,500 and $187,500 per hect are. Even at the highest range, $187,500 per hectare is only about 17% to 62%, depending on the type of wetlands, of the value of ecosystem services and natural capital that is lost with the elimination of wetlands (Table 3). Mitigation Ratios The current trend in public policy con cerning wetland losses associated with development is no net loss. It is be lieved that no net loss can be achieved by constructing wetlands to repla ce those that are eliminated, or by enhancing degraded wetlands to replace functions and values lost from impacted ones. In most cases a wetland is built on-site, but in mitigation banks, it may be built somewhere within the watershed (service area).

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76 Under current regulations, a mitigation ratio is calculated by subjectively quantifying ecosystem value of the proposed im pacted site, as well as accounting for the perceived ease of replacement and recove ry time needed. Representatives of government agencies and consulting companie s visit the proposed impacted site and score the wetlands using rapid assessment procedures. The wetland value achieved by this methodology is a result of perceived valu es by the scorers. Since no quantitative studies are required, mitigation ratios are thus affected by individual preferences rather than actual contributions. Problems aris e when wetland scoring is done by hundreds of professionals throughout the state, each one evaluating wetlands according to their individual preferences. For this reason, mitig ation ratios across the state and in different years may be highly variable. This met hodology is even more questionable when mitigation ratios have to be calculated for wetlands that are not replaced type for type, as may occur with the onset of mitigation banks. Static Replacement Ratios One option to calculate mitigation ratios among different ecosystems is to use static replacement ratios of wetland value. Replacement values are based on several assumptions from the following rationale: when a wetland is eliminated, vegetation is cut, peat is removed, water is drained, and the depression might be filled and covered with impervious surface (roads or buildings). C onsequently, annual ecosystem services are lost since the wetland no longer exists. A wetland that is eliminated and not replaced, cannot contribute environmental services a nd therefore, the lo ss of environmental services accumulates indefinitely. Conversel y, if the wetland is replaced, eventually, the created wetland will provide th e services that were provided by the original wetland,

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77 assuming the new ecosystem is similar to the destroyed one. Since a constructed wetland is a growing system, each year there is an incr emental replacement of th e lost services. If we assume that ecosystem services increas e linearly, that is, approximately half the environmental services are gained over the replacement time of an ecosystem, then the replacement value is the emdollar value of stru cture plus half the environmental services multiplied by the recovery time (Table 3). Examples of ratios calculated for the six Florida ecosystems using replacement values are given in Table 7. For instance, for every one hectare of forested wetland destroyed, 3.6 hectares of shrub/scrub are needed to replace the value lost. Similarly, 1.0 ha of herbaceous marsh is equivalent to 1 ha of forested wetland, and 2.0 ha of floodplain forest replace 1 ha of forested wetland. If the wetland is mitigated by an upland ecosystem, 11.5 ha of mesic forest and 16.8 ha of pine flatwoods are needed to replace 1 ha of forested wetland. These static calculations, however, do not take into account the investment costs needed to construct a wetland and the fact that the natural capital is later replaced. While biomass and organic matter may be complete ly replaced if the constructed wetland is successful, the services of the mature ecosyst em lost during the period of replacement are never recovered. A static calculation, howev er, yields a 1:1 ratio for type-for-type wetland replacement (Table 7), and thus, it does not account for the services lost. Cost Recovery Mitigation Ratios Results of the cost recovery model summar ized in Figure 26 show that 54 years are required to pay back construction costs of a typical constructed forested wetland. GPP em$ of mature ecosystems accumula ted over the recovery time can be

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With Replace Forested Wetland Shrub Scrub Herbaceous Wetland Floodplain Forest Mesic Forest Pine Flatwoods Forested Wetland 13.61.02.011.516.8 Shrub Scrub 0.310.30.63.24.7 Herbaceous Wetland 1.03.411.911.016.0 Floodplain Forest 0.51.80.515.78.2 Mesic Forest 0.10.30.10.211.5 Pine Flatwoods 0.10.20.10.10.71 Table 7. Static replacement ratios for the six Florida ecosystems using values from Table 3.

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79 calculated by multiplying yearly GPP values from Table 1 (6430 em$/ha/yr for the forested wetland ecosystem) by 54 years. T hus, after 54 years tota l em$ from GPP of a mature system equals 347,220 em$/ha. A growing system, on the other hand, will have lower initial GPP values, and as it matures, yearly GPP will approach that of a mature forested wetland. Using emdollar GPP valu es shown in Figure 26 and adding them for 54 years, yields 108,000 em$/ha. This results in a loss of ecosystem services equal to 239,220 em$/ha over 54 years. This loss is never recovered if the type for type mitigation ratio is 1:1. In other words, in order for a constructed wetland to reach 347,220 em$ of accumulated GPP, 100 years of growth are required. By that time, the mature ecosystem would have accrued 643,000 em$ (6430 em$/yr 100 years), so the constructed wetland would always fall short of the original ecosystem. Therefore, a higher mitigation ratio is needed to recover those losses. Dividing accumulated GPP em$ values of the mature ecosystem by the GPP valu es of the created site at year 54 yields a 1.9:1 ratio for type-for-type mitigation. When costs of construction are subtracted from GPP em$ of constructed wetlands, it takes 54 years for the new ecosy stem to pay back its initial investment (Figure 26). So while a mature forested wetland would ha ve accrued 347,220 em$ in 54 years, the constructed ecosystem is just beginning to provide a net benefit to society and its accrued value is merely 3000 em$. In this scenari o, for the constructed wetland to accrue 347,220 em$, 119 years from the time of construction are required. By that time, a mature ecosystem would have accrued 765,000 em$/ha. This pattern is shown in Figure 28. If t=54 years is used to calculate the mitiga tion ratio, it would yield a value of 116:1. Clearly, this ratio is unreasonable considering that mitigation is a result of land scarcity

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Figure 28. Graph of GPP accrual in mature forested wetland and constructed ecosystem. The ratio of these two lines at any point in time constitutes the mitigation ratio necessary to recover losses due to construction within that time frame. -2.00E+05 0.00E+00 2.00E+05 4.00E+05 6.00E+05 8.00E+05 1.00E+060 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150Time, yearGPP accrual em$/ha

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80 and competition for this limited resource. Wh en mitigation ratios are computed yearly, it is apparent that the ratios are decreasing, and though the two lines will never meet, by year 100 the ratio is reduced to 2.7:1 (Figure 29) and it will be as low as 1.2:1 by year 500. This decrease in mitigation ratios begs the question: what is the appropriate time frame in which to calculate mitigation ratios? If mitigation sites are successful and protected in perpetuity, then long term trends in ecosystem services accrual show that, given enough time, constructed ecosystems rec over close to 100% of the initial losses. Therefore, type-for-type mitigation ratios cal culated over thousands of years can be as low as 1.05:1. However, when decisions are made to maximize contributions to society, this time frame is not appropriate. A more reasonable time frame would be 70-100 years, or the equivalent of one generation of human life. Mitigation ratios at year 70 and 100 are 5.5:1 and 2.7:1, respectively. That is, if society wants to recover the ecosystem services lost to impacts within 70 years of wetland creation, 5.5 hectar es will have to be constructed for each hectare impacted. Similarly, if ecosystem services are to be recovered within 100 years of impacts, then 2.7 hectares of wetlands will have to be constructed for each hectare of impact. Thus, mitigation ratios decrease as the time frame allowed to recover ecosystem losses increases (Figure 29). Simulation Model Mature ecosystems are the work of decad es of ecosystem services and natural capital accrual. When a forested wetland is cut down and replaced by a created one, a huge investment is needed from the economy to mitigate the wetland losses. While the created wetlands are usually monitored for only a few years, at least 165 years are

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Figure 29. Simulated mitigation ratios for forested wetlands from 54 to 100 years after construction showing decrease in mitigation ratios as the time frame allowed to offset losses increases. 0 10 20 30 40 50 60 70 80 90 100 110 120 130 5460667278849096Time, yearMitigation ratio of forested wetland

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83 required for the ecosystem to reach 90% of its steady state biomass, and 386 years to achieve 90% of organic matter (Figure 21). Some wetland scientists involved in wetland creation ha ve been trying to jump start created sites by adding or ganic matter from the impacted sites or saving the on-site organic pool. The effects of jump star ting constructed wetlands by adding organic matter prior to planting was illustrated in th e simulation results by increasing the initial organic matter storage. The simulation model of a forested wetland showed that increasing the organic matter pool by 25% 50%, and 90% of its maximum value increased biomass growth and decreased ecosyst em recovery time by as much as 11% to 26%. A 25% increase in organic matter stor age resulted in biomass reaching 90% of steady state value in 140 years, 35 years faster than with the baseline simulation (Figure 24). A 50% increase in organic matter st orage resulted in biomass reaching 90% of steady state values in 119 year s (Figure 24), 46 years faster th an without the organic pool. Similarly, increasing the organic matter storag e to 90% of its steady state value resulted in biomass reaching 90% of its steady state va lue by 98 years, 67 years faster (Figure 24). GPP rates were also positively affected, and translated into faster recovery times of constructed wetlands. While 54 years are required to recove r costs of construction when no organic matter is added, this time frame is reduced to 48 years with a 25% increase of organic matter, 42 years with a 50% addition and 40 years with a 90% addition of organic matter (Figure 27). Saving the on-site organic matter pool not only increases growth rates, but it also decreases cost s associated with construction.

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84 Consequently, dynamic mitigation ratios al so decrease as greater percentages of organic matter are added to the constructed wetland (Figure 30). For example, without organic matter, a mitigation ratio of 5.5:1 is ne cessary to recover losses within 70 years of wetland construction (Figur e 30). Increasing the initia l organic matter pool to 25%, 50%, and 90% of its steady state value yields mitigation ratios of 3.9:1, 3.1:1 and 2.7:1, respectively, for the 70 year time frame (Table 8). Similarly, in order to recover losses within 100 years of construction, mitigation ratios of 2.3:1, 2.0:1, and 1.9:1 are necessary with a 25%, 50%, and a 90% increase in organi c matter, compared to the ratio of 2.7:1 calculated from the baseline simulation. The simulated emergy and transformity values of biomass of forested wetlands (Figure 22) are slightly lowe r than the ones given in the emergy evaluation table (Table 11). This could be due to the fact that th e tabulated value tends to overestimate total emergy inputs since the same steady state value (6.17E+15 sej/ha/yr) is multiplied by the turnover time. In reality, when an ecosystem is in early su ccessional stages transpiration rates are lower and therefore total driving em ergy contributed from the process is also lower. On the other hand, organic matter emergy and transformity values (Figure 23) resulting from the simulation model are sli ghtly higher than the tabulated ones (Table 10). This could be due to the slightly different calculation methodology employed in tabulating emergy and transformity, as explained in Table 11 and Figure 20. Transformity values of GPP, biomass, and organic matter for the six Florida ecosystems (Appendix B, Tables 10 through 21) in this study are s ubstantially higher

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Figure 30. Simulated mitigation ratios for forested wetlands from 60 to 120 years after construction showing decrease in mitigation ratios as the initial storage of organic matter is increased by 25%, 50% and 90% of its steady state value. 0 2 4 6 8 10 12 1460 70 80 90 100 110 120Time, yearMitigation ratios of forested wetland Baseline, OM=1% OM=25% OM=50% OM=90%

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1%25%50%90% 6012.16.24.23.6 705.53.93.12.7 803.83.12.62.3 903.12.62.22.1 1002.72.32.01.9 Initial organic matter storage Table 8. Mitigation ratios of forested wetlands at 10 year intervals (from 60 to 100 years after construction) resulting from varying initial organic matter storage to 1%, 25%, 50%, and 90% of its steady state value. Time

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87 compared to previous studies (Orrell 1998; Tilley 1999). This is primarily a result of calculations of annual driving emergy inputs, particularly the add ition of geologic input to total driving emergy. Moreover, the simu lated transformity values of biomass and organic matter storages in this study yield a different pattern than the one presented by Tilley (2000). Tilley found that transformity values increase as a function of time. In this study, transformity of biomass and, to a smaller extent, organic matter had higher initial values than steady state values (Figures 22 and 23). This is al so a result of adding geologic input to the annual driving emergy of the ecosystem; in fact, annual driving emergy in the early stages of ecosystem growth is primarily in the form of geologic input. When this value is divided by the ecosystem energy storage to derive its transformity, it results in extremely high transformity valu es since the amount of biomass and organic matter energy present is still small. As th e ecosystem matures, transpiration increases and begins contributing to annual driving emergy, but the ecosystem storages also increase, thus resulting in lower transformities. Limitations and Suggestions for Further Research This study relied on already published data for the ecosystem evaluations and the forested wetland model. While literature da ta were cross-referenced, sometimes the lack of published data resulted in educated estimat es in order to carry out the evaluations. This problem was especially true for the floodplain forest and the upland ecosystems. For example, while I was able to gather data for the biota of the riparian wetland, understanding the processes and scale of floodplain formation posed several challenges. First, the system analyzed in this study was a lake-fed, black water, low flow stream for which there is virtually no data relating to floodplain formation and structure. Most of

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88 the stream studies focus on large, alluvial systems that usually pose a flooding threat to human development. Extrapolating structur e and turnover times fr om those studies, and applying those values to this research yields approximations at best. Thus, the value of floodplain structure is re ported with caution. Similarly, the upland ecosystems lacked complete reports on organic matter storages, litterfall, and decomposition rates. While published decomposition rates in pine flatwoods appeared low compared to other upland and wetland systems, pine flatwoods experience frequent fires that arrest litter accumulation. Ho wever, published data on pine flatwoods decomposition rates largely ignored the effects of fire on this ecosystem. As a result of relying on data specific to only a few sites within Florida, the ecosystems evaluations reflect conditions found at those sites, and average values for Florida should be derived with caution. Th e ecosystem tables can also be used as templates to generate values for other site s throughout Florida by inserting site specific data collected at those locations if available. Ideally, the constructed wetland model that was developed to explore the benefits, costs, and recovery time of wetland creation should have been calibrated using actual GPP values from a mitigation site. In reality, mature constructed wetlands are rare and since developers are only required to monitor them until compliance, the fate of those wetlands post compliance is largely unknown. Th e mitigation ratios calculated in this study depend on GPP values from the literature and thus are specific to the sites sampled in those studies.

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89 Further Research This research focused on quantifying the value of ecosystem se rvices and natural capital of six Florida ecosystems to invest igate differences among various ecosystems. Results from this study have shown that we tlands on average contribute more wealth to society than upland ecosystems. However, it is important to stress the fact that wetland mitigation should not be at the expense of a ll uplands in Florida. Mitigation ratios between ecosystems should vary as the relativ e abundance of upland ecosystems change. As certain ecosystems become scarce, for in stance longleaf pine savannahs or maritime forests, their value should increase to refl ect their rarity in the landscape. Abundance of ecosystems could be determined by reviewing Geographic Information Systems land use coverages of Florida over time. Based on results from these analyses, statewide policies could be implemented that valued ecosystems on the basis of their relative abundance as well as their contributions to society. This study demonstrated that created fore sted wetlands require 54 years before the benefits (in the form of ecosystem services of GPP) from the created ecosystem outweigh the costs of construction (the sum of economic inputs to constructed wetlands as well as the environmental losses from the destruction of the pre-existing ecosystem). Mitigation ratios derived from the model have used data pertaining to constructe d forested wetlands. Future research is needed to explore the concept of mitigation further and include calculations of mitigation ratios for different ecosystems, as well as for different mitigation alternatives, such as restoration, en hancement, and preservation. What are the appropriate ratios if we constr uct a freshwater marsh to repl ace a forested wetland? What range of mitigation ratios should we use for restored, enhanced, or preserved wetlands?

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90 Under what conditions would restoration and enhancement be more appropriate than creation? Long-term studies of mitigation sites should also be developed to ensure that the ecosystems survive beyond the first few years of monitoring. Do created wetlands ever become successful ecosystems? How much time does the created wetland require to achieve the structure and productivity of th e forgone ecosystem? How can one accelerate growth and productivity of creat ed sites in order to recover costs more quickly? What is the appropriate investment in terms of economic inputs into creating wetlands? Finally, as regulatory agencies drift towards the use of mitigation banks, the costs and benefits of on-site and type-for-type m itigation versus mitigation banking should also be compared. Since mitigation banks are large-scale projects, the economic inputs to one hectare of ecosystem within a mitigation bank may be smaller than constructing one hectare of isolated wetland. Do economies of scale exist in wetland creation and are mitigation banks thus cheaper to build? Conclusions As long as there are competing interests in the use of a limited resource such as land, understanding the costs and be nefits of decisions about appropriate use of the land is critical in ensuring society and ecosyst em long-term success. Emergy analysis was used to evaluate the contributions of ecosyst ems services and natura l capital to social welfare. This research provided several t ools to appropriately value ecosystems and derive fair mitigation ratios. Four main conclusions were generated fr om this study. First, wetland ecosystems are extremely valuable to our societies, with replacement values ranging from over

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91 300,000 to 1,000,000 em$/ha. Their replacement is very costly (103,000 em$/ha) to society, due to the economic inputs required as well as the environmental losses of the pre-existing ecosystem. Second, ecosystem dyna mics can be modeled in terms of energy, emergy and transformity and results of dynami c simulations can be incorporated into decision-making processes, as in the case of the constructed wetland model. For instance, the model showed that applying orga nic matter to growing ecosystems results in increased productivity, which translates into de creased recovery times by as much as 1126%. Third, with an initial investment of 103,111 em$/ha, approximately 54 years are required for ecosystem services to offset costs of construction. Th erefore, losses due to impacts alone cannot be mitigated in fewer th an 54 years if we take construction costs into account. Recovery times can be d ecreased to 48, 42, and 40 years by adding up to 25%, 50% and 90% of the steady state value of organic matter to constructed sites; thus, the organic matter should be applied to constr ucted sites whenever available to increase productivity and decrease construction costs. Fourth, mitigation ratios cannot be calculated from static valuations, but re quire dynamic simulations of growth and ecosystem value accrual. In fact, mitigation ra tios themselves are flexible rather than set values, and vary according to the time frame soci ety decides to offset losses. In order to offset losses due to impacts in the shortest amount of time possibl e, higher ratios are required. Examples of type for type mitigation ratios for forested wetlands are 5.5:1 or 2.7:1 to offset losses within 70 and 100 years of wetland construction, respectively. These ratios are affected by init ial construction costs as well as GPP rates. Therefore, adding organic matter to constructed sites provides a twofold benefit: 1) it decreases construction costs by alleviating environmental losses, and 2) it positively affects GPP

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92 rates. Mitigation ratios re sulting from a 25%, 50%, and 90% addition of organic matter decrease to 3.9:1, 3.1:1 and 2.7:1, respectively, for a 70 year time frame, and are as low as 2.3:1, 2.0:1 and 1.9:1, respectively, for losses to be recovered within 100 years of construction.

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APPENDIX A EMERGY TERMINOLOGY AND SYSTEMS ECOLOGY SYMBOLS.

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94 E ne r g y C i r cui t :Ap a t h w a y w h ose f lo w isp r opo r t io n a l t o t h e q u a n t i t y in the storage or source upstream.Source: Outside source of energy delivering forces according to a program controlled from outside; a forcing function.Tank: A compartment of energy storage within the system storing a quantity as the balance of inflows and outflows; a state variableHeat sink: Degradation of potential energy into heat that accompanies all real transformation processes and storages; loss of potential energy from further use by the system.Interaction: Interactive intersection of two pathways coupled to produce an outflow proportional to a function of both; control action of one flow on another; limiting factor action; work gate.Producer: Unit that collects and transforms low-quality energy under control interactions of high-quality flows.Consumer: Unit that transforms energy quality, stores it, and feeds it back autocatalytically to improve inflows.Swithching action: A symbol that indicates one or more switching actions. Figure 31. Select energy systems symbols and definitions (after Odum, 1996).

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95 ItemDefinitionUnits EmergyAvailable energy of one kind required directly and indirectly to produce a product or service Emjoules Solar emergySolar energy required directly and indirectly to produce a product or service Solar emjoules (sej) TransformityEmergy used per unit available energy produced calculated as emergy/energy Emjoule/joule Solar transformitySolar emergy used per unit energy available sej / J Power DensityUseful energy flow per area per unit timeJ/ha/yr Empower DensityEmergy flow per area per unit timeSej/ha/yr Em$ value Macro-economic value Annual total emergy used in the United States, divided by its Gross National Product in 2000. Em$, 2000 Table 9. Definitions of emergy terminology and indices used in this study (Odum 1996)

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APPENDIX B EMERGY EVALUATIONS OF SIX FLORIDA ECOSYSTEMS.

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Table 10. Emergy Evaluation of annual driving energies and environmental services of forested wetlands. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej/yr) (2000 em$/yr) Energy Sources 1 Sun 4.19E+13 J/ha/yr 1 0.04 $44 2 Wind 2.96E+09 J/ha/yr 1496 0.004 $5 3 Rain, chemical potential 6.42E+10 J/ha/yr 18199 1.17 $1,217 4 Run-in, chemical potential 2.52E+10 J/ha/yr 46589 1.17 $1,223 5 Geologic input 5.50E+06 g/ha/yr 1.00E+09 5.50 $5,729 Functions (Env. Services) 6 Transpiration (water use ) 2.57E+10 J/ha/yr 26199 0.67 $701 7 GPP 1.54E+12 J/ha/yr 3999 6.17 $6,430 8 Infiltration 2.88E+10 J/ha/yr 26199 0.76 $787 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 10. 1 SOLAR INSOLATION Area of wetland = 1.00E+04 m 2 Mean Net Radiation = 274 Ly (Henning 1989) = (1.00 E4 m 2 )(274 Ly)(10 Cal/m 2 /Ly)(4186 J/Cal)(365 days) = 4.19E+13 J/ha/yr Transformity = defined as 1 (Odum, 1996) 2 WIND Area = 1.00E+04 m 2 Density = 1.3 Kg/m 3 Drag. Coefficient = 1.00E-03 (Odum 1996) Av. Annual Velocity = 1.16 mps (Jones et al.1984) Geostrophic wind = 1.93 (observed winds are about 0.6 of geostrophic wind) = (area)(density)(Drag Coeff.)(velocity) 3 (3.15E7 sec/yr) = 2.96E+09 J/ha/yr Transformity = 1,496 sej/J (Odum 1996) 3 RAIN, CHEMICAL POTENTIAL Area = 1.00E+04 m 2 /ha Rainfall = 1.3 m/yr (NOAA 2002) Gibbs Free Energy = 4.94 J/g = (1.00E+04 m 2 /ha)(1.3 m)(4.94 J/g)(1.00E+06 g/m 3 ) = 6.42E+10 J/ha/yr Transformity = 18,199 (Odum 1996) 4 RUN IN, CHEMICAL POTENTIAL Run-in = 0.51 m/yr (Heimberg 1984) Area = 1.00E+04 m 2 /ha Gibbs Free Energy = 4.94 J/g = (0.51 m/yr)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 2.52E+10 J/ha/yr Transformity:46,589 (calculated as 2.56 transformity of rain assuming total rainfall is required to generate 39% avg. run-off) 97

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98 5 GEOLOGIC INPUT Limestone Eroded = 0.02750 cm/yr (Odum 1984) Density of Limestone = 2 g/cm 3 = (0.0275 cm/yr)(1.00E+08 cm 2 /ha)(2 g/cm 3 ) = 5.50E+06 g/ha/yr Transformity = 1.00E+09 Sej/g (Odum 1996) 6 WATER USE (TRANSPIRATION) cal culated as daily summer transpiration rates times 240 days. Transpiration = 0.52 m/yr (Liu 1996) Gibbs Free Energy = 4.94 J/g = (0.52 m)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 2.57E+10 J/ha/yr Transformity = 26,199 (Calculated as weighted average of rain and run-in) 7 GROSS PRIMARY PRODUCTION Net Primary Production = 6.13 tn C/ha/yr (Brown 1978) = (6.13 tn/ha/yr) (1,000,000 g/tn) (8 Cal/g) (4186 J/kcal) = 2.05E+11 J//ha/yr Plant respiration = 39.96 tn C/ha/yr (Brown 1978) = (39.96 tn/ha) (1,000,000 g/tn) (8 kcal/g) (4186 J/Cal) = 1.34E+12 J/ha/yr Gross Production = 1.54E+12 J/ha/yr Total annual emergy = Sum of tr anspiration and geologic input = 6.17E+15 Sej/ha/yr Transformity = (6.17E+15 Sej/ha/y r / 1.54E+12 J/ha/yr ) = 3,999 sej/J 8 INFILTRATION Infiltration Rate = 0.0016 m/day (Heimburg 1984) = 0.584 m/yr Gibbs free energy = 4.94 J/g = (0.584 m/yr)(4.94 J/g)(1.00E+06 g/m 3 )(1.00E+04 m 2 /ha) = 2.88E+10 J/ha/yr Transformity = 26,199 (Calculated as wei ghted average of rainfall and run-in)

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99 Table 11. Emergy evaluation of storages of natural capital in forested wetlands. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej) (2000 em$/yr) Structure (Natural Capital) 1 Live Biomass 2.90E+12 J/ha 106613 309 $321,510 2 Organic Matter 4.42E+12 J/ha 123033 544 $566,304 3 Water 1.87E+10 J/ha 26199 0.5 $511 4 Basin Structure 1.00E+10 g/ha 1.12E+09 11222 $11,690,095 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 11. 1 LIVE BIOMASS Biomass = 266 tn/ha green biomass (Brown 1978) Water weight = 35 % (estimate) Energy = (266 tn/ha)(.65 dry weight) (1,000,000 g/tn) (4 Cal/g) (4186 J/Cal) = 2.90E+12 J/ha Time to maturity = 50 yrs Total annual emergy = sum transp iration, and geologic input = 6.17E+15 Sej/ha/yr Transformity = (6.17E+15 sej/ha/y r 50 yrs) / 2.90E+12 J/ha = 106,613 sej/J 2 ORGANIC MATTER Organic Matter = 20.3 kg/m2 depth of 20 cm (Dierberg and Ewel 1984) Heat Content = 5.20 Cal/g Peat = (20 kg/m2)(1.00 E+04 m2/ha)(1000 g/kg)(5.2 Cal/g)(4186 J/Cal) = 4.42E+12 J/ha Accumulation = Litterfall Decomposition Litterfall = 4.61E+02 g dry weight/m 2 /yr (average, Deghi 1977) Decomposition = 2.31E+02 g dry weight/m 2 /yr (50% of litt erfall, Deghi 1977) Turnover Time = Storage of Peat (g) / accumulation (g/yr) Time to develop peat = 88 yrs Total annual emergy = Sum of transpiration and geologic input = 6.17E+15 Sej/ha/yr Transformity = (6.17E+15 Sej/ha /yr 87 yrs) / 4.42E+12 J/ha = 123,033 sej/J 3 WATER Volume of water taken as 89.6% moisture content of the volume of peat plus avg. standing water Volume of Peat = 2.00E+03 m 3 depth of 20 cm (Dierberg and Ewel 1984) Peat water = 1.79E+03 m 3 Standing water volume = 2.00E+03 m 3 Gibbs Free Energy = 4.94 J/g = (3.79E+03 m 3 )(1.00E+06 g/m 3 )(4.94 J/g) = 1.87E+10 J/ha Transformity: 26,199 (Calculated as weighted average of rain and run-in)

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100 4 BASIN STRUCTURE Mass Displaced of Basin = (density)(volume displaced) Density = 2 g/cm 3 (Odum 1984) Volume displaced = 5.00E+09 cm 3 = 1.00E+10 g/ha Time = 1818 yrs (Odum 1984) total annual emergy = Sum of transpiration and geologic input = 6.17E+15 Sej/yr Transformity = (6.17E+15 sej/yr 1818) / 1.00E+10 J/ha = 1.12E+09 sej/g

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101 Table 12. Emergy evaluation of annual driving energies and environm ental services of scrub-shrub wetlands. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej/yr) (2000 em$/yr) Energy Sources 1 Sun 4.19E+13 J/ha/yr 1 0.04 $44 2 Wind 2.96E+09 J/ha/yr 1496 0.004 $5 3 Rain, chemical potential 6.42E+10 J/ha/yr 18199 1.17 $1,217 4 Run-in, chemical potential 2.47E+10 J/ha/yr 47863 1.18 $1,231 5 Geologic input 1.21E+06 g/ha/yr 1.0E+09 1.21 $1,260 Functions (Env. Services) 5 Transpiration (water use ) 3.76E+10 J/ha/yr 26439 0.99 $1,034 6 GPP 2.57E+11 J/ha/yr 8577 2.20 $2,295 7 Infiltration 6.42E+09 J/ha/yr 26439 0.17 $177 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 12. 1 SOLAR INSOLATION Area of wetland = 1.00E+04 m 2 Mean Net Radiation = 274 Ly (Henning 1989) = (1.00 E4 m 2 )(274 Ly)(10 Cal/m 2 /Ly)(4186 J/Cal)(365 days) = 4.19E+13 J/ha/yr Transformity = defined as 1 (Odum 1996) 2 WIND Area = 1.00E+04 m 2 Density = 1.3 Kg/m 3 Drag. Coefficient = 1.00E-03 (Odum 1996) Av. Annual Velocity = 1.16 mps (Jones et al.1984) Geostrophic wind = 1.93 (observed winds are about 0.6 of geostrophic wind) = (area)(density)(Drag Coeff.)(velocity) 3 (3.15E7 sec/yr) = 3.0E+09 J/ha/yr Transformity = 1,496 sej/J (Odum 1996) 3 RAIN, CHEMICAL POTENTIAL Area = 1.00E+04 m 2 /ha Rainfall = 1.3 m/yr (NOAA 2002) Gibbs Free Energy = 4.94 J/g2 = (1.00E+04 m 2 /ha)(1.3 m)(4.94 J/g)(1.00E+06 g/m 3 ) = 6.42E+10 J/ha/yr Transformity = 18,199 (Odum 1996) 4 RUN IN, CHEMICAL POTENTIAL Run-in = 0.5 m/yr (Schwartz 1989) Area = 1.00E+04 m 2 /ha Gibbs Free Energy = 4.94 J/g = (0.5 m/yr)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g)

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102 = 2.47E+10 J/ha/yr Transformity: 47,863 (calculated as 2.63 transformity of rain assuming total rainfall is required to generate 38% runo-off) 5 GEOLOGIC INPUT Limestone Eroded = 0.00605 cm/yr (78% less than Cypress based on infiltration) Density of Limestone = 2 g/cm 3 = (0.00605 cm/yr)(1.00E+08 cm 2 /ha)(2 g/cm 3 ) = 1.21E+06 g/ha/yr Transformity = 1.00E+09 Sej/g (Odum 1996) 6 WATER USE (TRANSPIRATION) Transpiration = 2083 g H 2 O/m 2 /day (Schwartz 1989) Gibbs Free Energy = 4.94 J/g = (2083g H 2 O/m 2 /day)(365 days)(1.00E+04 m 2 /ha)(4.94 J/g) = 3.76E+10 J/ha/yr Transformity = 26439 (Calculated as we ighted average of rain and run-in) 7 GROSS PRIMARY PRODUCTION Net Primary Production = 164 g C/m 2 /yr (estimate from Flohrschutz, 1978) = (164 g C/m 2 /yr)(8 Cal/g) (4186 J/C)(1E+4 m 2 /ha) = 5.49E+10 J//ha/yr Plant respiration = 603 g C/m 2 /yr (estimate from Flohrschutz, 1978) = (603 g C/m 2 /yr)(8 Cal/g) (4186 J/Cal)(1E+4 m 2 /ha) = 2.02E+11 J/ha/yr Gross Production = 2.57E+11 J/ha/yr Total annual emergy = Sum of transpiration and geologic input = 2.20E+15 Sej/ha/yr Transformity = (2.20 E+15 Sej/h a/yr / 2.57E+11 J/ha/yr ) = 8577 sej/J 8 INFILTRATION Infiltration Rate = 0.13 m/yr (Schwartz 1989) Gibbs free energy = 4.94 J/g = (0.13 m/yr)(4.94 J/g)(1.00E+06 g/m 3 )(1.00E+04 m 2 /ha) = 6.42E+09 J/ha/yr Transformity: 26439 (Calculated as weighted average of water and run-in)

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103 Table 13. Emergy evaluation of storages of natural capital in scrub-shrub wetlands. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej) (2000 em$/yr) Structure (Natural Capital) 1 Live Biomass 1.41E+12 J/ha 31324 44 $45,896 2 Organic Matter 4.46E+12 J/ha 51089 228 $237,184 3 Water 7.48E+09 J/ha 26439 0.20 $206 4 Basin Structure 6.00E+09 g/ha 1.82E+09 10925 $11,379,949 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 13. 1 LIVE BIOMASS Biomass = 8400.5 g/m 2 (Schwartz 1989) = (8400.5 g/m 2 ) (1.00E+04 m 2 /ha) (4 Cal/g) (4186 J/Cal) = 1.41E+12 J/ha Total ann. emergy = Sum of transpiration and geologic input = 2.20E+15 Sej/ha/yr Time = 20 yrs (Schwartz 1989) Transformity = (2.20 E+15 sej/ha/yr 20 yrs) / 1.41 E+12 J/ha = 31324 Sej/J 2 PEAT Peat Depth = 15.00 cm (Schwartz 1989) Bulk Density = 1.05 g/cm 3 (Schwartz 1989) % organic matter = 0.13 as decimal (Schwartz 1989) Organic Matter = (% OM)(bulk density)(depth)(1.0 E+4 cm2/m2)(1.0 E-3 kg/g) = 20.48 kg/m 2 Heat Content = 5.20 Cal/g = 4.46E+12 J/ha Accumulation = Litterfall Decomposition Litterfall = 2.83E+02 g dry weight/m 2 /yr (Schwartz 1989) Decomposition = 8.49E+01 g dry weight/m 2 /yr (30% of litterfall, Schwartz 1989 ) Turnover Time = Storage of Peat (g) / accumulation (g/yr) Time to dev. peat = 103 yrs Total ann. emergy = Sum of transpiration and geologic input = 2.20E+15 Sej/ha/yr Transformity = (2.20 E+15 Sej/ha/yr 103) / 4.46E+10 J/ha/yr = 51089 Sej/J 3 WATER Volume of water taken as 89.6% moisture content of volume of peat plus avg. standing water Peat Volume = 1500 m 3 Peat water = 1.34E+01 m 3 Avg. standing water Volume= 1.50E+03 m 3 Gibbs Free Energy = 4.94 J/g = (2.84E+03 m 3 )(1.00E+06 g/m 3 )(4.94 J/g) = 7.48E+09 J/ha/yr

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104 Transformity: 26,439 (Calculated as weighted average of rain and run-in) 4 BASIN STRUCTURE Mass Displaced of Basin = ( density)(volume displaced) Density = 2 g/cm 3 (Odum 1984) Volume displaced = 3.00E+09 cm 3 depth of 30 cm = 6.00E+09 g/ha Time = 4959 yrs (30 cm/0.00605 cm/yr) (estimate from Odum 1984) total annual emergy = Sum of transpiration and geologic input = 2.20E+15 Sej/yr Transformity = (2.20E+15 sej/yr 4959) / 6.00E+9 J/ha = 1.82E+09

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105 Table 14. Emergy Evaluation of annual driving energies and environmental services of herbaceous wetlands. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej/yr) (2000 em$/yr) Energy Sources 1 Sun 4.19E+13 J/ha/yr 1 0.04 $44 2 Wind 2.96E+09 J/ha/yr 1496 0.004 $5 3 Rain, chemical potential 6.42E+10 J/ha/yr 18199 1.17 $1,217 4 Run-in, chemical potential 2.25E+10 J/ha/yr 51867 1.17 $1,214 5 Geologic input 4.95E+06 g/ha/yr 1.00E+09 4.95 $5,156 Functions (Env. Services) 5 Transpiration (water use ) 3.16E+10 J/ha/yr 26928 0.85 $887 6 GPP 4.02E+11 J/ha/yr 14436 5.80 $6,043 7 Infiltration 2.69E+10 J/ha/yr 26928 0.72 $754 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 14. 1 SOLAR INSOLATION Area of wetland = 1.00E+04 m 2 Mean Net Radiation = 274 Ly (Henning 1989) = (1.00 E4 m 2 )(274 Ly)(10 Cal/m 2 /Ly)(4186 J/Cal)(365 days) = 4.19E+13 J/ha/yr Transformity = defined as 1 2 WIND Area = 1.00E+04 m 2 Density = 1.3 Kg/m 3 Drag. Coefficient = 1.00E-03 (Odum 1996) Av. Annual Velocity = 1.16 mps (Jones et al.1984) Geostrophic wind = 1.93 (observed winds are about 0.6 of geostrophic wind) = (area)(density)(Drag Coeff.)(velocity) 3 (3.15E7 sec/yr) = 3.0E+09 J/ha/yr Transformity = 1,496 sej/J (Odum 1996) 3 RAIN, CHEMICAL POTENTIAL Area = 1.00E+04 m 2 /ha Rainfall = 1.3 m/yr (NOAA 2002) Gibbs Free Energy = 4.94 J/g2 = (1.00E+04 m 2 /ha)(1.3 m)(4.94 J/g)(1.00E+06 g/m 3 ) = 6.42E+10 J/ha/yr Transformity = 18,199 (Odum 1996) 4 RUN IN, CHEMICAL POTENTIAL Assume 1 to 1 watershed to wetland ratio and run-off coefficient of 0.35 Run-in = 0.455 m/yr Area = 1.00E+04 m 2 /ha Gibbs Free Energy = 4.94 J/g = (0.455 m/yr)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 2.25E+10 J/ha/yr

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106 Transformity: 51,867 (calculated as 2.85 transformity of rain assuming total rainfall is required to generate 35% runo-off) 5 GEOLOGIC INPUT Limestone Eroded = 0.02475 cm/yr (9% less than Cypress based on infiltration) Density of Limestone = 2 g/cm 3 = (0.02475 cm/yr)(1.00E+08 cm 2 /ha)(2 g/cm 3 ) = 4.95E+06 g/ha/yr Transformity = 1.00E+09 Sej/g (Odum 1996) 5 WATER USE (TRANSPIRATION) (estimate from Zolteck, 1979; Abtew, 1996; Rushton, 1996) Transpiration = 0.64 m/yr Gibbs Free Energy = 4.94 J/g = (0.64 m)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 3.16E+10 J/ha/yr Transformity = 26928 (Calculated as we ighted average of water and run-in) 6 GROSS PRIMARY PRODUCTION Net Primary Production + Respiration Net Primary Production = 600 g/m 2 /yr (estimate from Zolteck et al., 1979) = (600 g/m 2 /yr)(4 Cal/g) (4186 J/Cal)(1.00E+04 m 2 /ha) = 1.00E+11 J//ha/yr Plant respiration = 1800 g/m 2 /yr (based on 75% of GPP) = (1800 g/m 2 /yr)(4 Cal/g) (4186 J/Cal)(1.00E+04 m 2 /ha) = 3.01E+11 J/ha/yr Gross Production = 4.02E+11 J/ha/yr Total annual emergy = Sum of transpiration and geologic input = 5.80E+15 Sej/ha/yr Transformity = (5.80 E+15 Sej/ha/yr / 5.69E+11 J/ha/yr) = 14436 sej/J 7 INFILTRATION Estimate from Rushton, 1996; 31% of water loss in marsh due to seepage. Infiltration Rate = 0.54 m/yr Gibbs free energy = 4.94 J/g = (0.54 m/yr)(4.94 J/g)(1.00E+06 g/m 3 )(1.00E+04 m 2 /ha) = 2.69E+10 J/ha/yr Transformity: 26928 (Calculated as weighted average of rain and run-in)

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107 Table 15. Emergy evaluation of storages of natural capital in herbaceous wetlands Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej) (2000 em$/yr) Structure (Natural Capital) 1 Live Biomass 1.17E+11 J/ha 74244 9 $9,065 2 Organic Matter 1.02E+13 J/ha 95185 968 $1,008,438 3 Water 4.06E+10 J/ha 26928 1 $1,139 4 Basin Structure 5.00E+09 g/ha 1.17E+09 5860 $6,104,113 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 15. 1 LIVE BIOMASS Biomass = 700 g dry weight/m 2 (estimate from Zolteck et al., 1979) = (700 g/m 2 /yr) (4 Cal/g) (4186 J/kcal)(1.00E+04 m 2 /ha) = 1.17E+11 J/ha Total ann. emergy = Sum of transpiration and geologic input = 5.80E+15 Sej/ha/yr Time = 1.5 yrs (estimate) Transformity = (5.80 E+15 sej/ha/yr 1.5 yrs)/ 1.17E+11 J/ha/yr = 74244 sej/J 2 PEAT Peat Depth = 75.00 cm p. 49 (Zolteck et al. 1979) Bulk Density = 0.07 g/cm 3 p. 49 (Zolteck et al. 1979) % organic matter = 0.89 as decima l p. 49 (Zolteck et al. 1979) Organic Matter = (% OM)(bulk density)(depth)(1.0 E+4 cm2/m2)(1.0 E-3 kg/g) = 46.73 kg/m 2 Heat Content = 5.20 Cal/g = 1.02E+13 J/ha Accumulation = Litterfall Decomposition Litterfall = 5.60E+02 g dry weight/m 2 /yr (estimate, 80% of biomass dieback) Decomposition = 2.80E+02 g dry weight/m 2 /yr (50 % of litterfall, Zolteck et al. 1979) Turnover Time = Storage of Peat (g) / accumulation (g/yr) Time to dev. peat = 167 yrs Total ann. emergy = Sum of transpiration and geologic input = 5.80E+15 Sej/ha/yr Transformity = (5.80 E+15 Sej/ha/yr 173) / 1.02E+13 J/ha/yr = 95185 3 WATER Volume of water taken as 89.6% moisture content of volume of peat plus avg. standing water Peat Volume = 7.50E+03 m3/ha Peat water = 6.72E+03 m 3 /ha Standing water volume = 1.50E+03 m 3 /ha Gibbs Free Energy = 4.94 J/g = (8.22E+03 m 3 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 4.06E+10 J/ha/yr Transformity: 26,928 (Calculated as we ighted average of rain and run-in)

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108 4 BASIN STRUCTURE Mass in Basin = (dens ity)(volume displaced) Density = 2 g/cm 3 (Odum 1984) Volume displaced = 2.50E+09 cm3/ha = 5.00E+09 Time = 1010 yrs (25cm/.02530cm/yr) Total ann. emergy = Sum of transpiration and geologic input = 5.80E+15 Sej/yr Transformity = (5.80E+15 sej/yr 1010yrs) / 5.0E+09 J/ha = 1.17E+09 sej/g

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109 Table 16. Emergy evaluation of annual drivi ng energies and envir onmental services of floodplain forests. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej/yr) (2000 em$/yr) Energy Sources 1 Sun 4.19E+13 J/ha/yr 1 0.04 $44 2 Wind 2.96E+09 J/ha/yr 1496 0.004 $5 3 Rain, chemical potential 6.42E+10 J/ha/yr 18199 1.17 $1,217 4 Run-in, chemical potential 3.06E+10 J/ha/yr 48500 1.49 $1,547 5 River, geopotential 7.92E+10 J/ha/yr 27764 2.20 $2,290 6 Geologic Input 2.00E+05 J/ha/yr 1.00E+09 0.20 $208 Functions (Env. Services) 7 Transpiration (water use ) 5.63E+10 J/ha/yr 27984 1.58 $1,642 8 GPP 3.21E+12 J/ha/yr 1236 3.97 $4,140 9 Infiltration 2.88E+10 J/ha/yr 27984 0.81 $841 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 16. 1 SOLAR INSOLATION Area of wetland = 1.00E+04 m 2 Mean Net Radiation = 274 Ly (Henning 1989) = (1.00 E4 m 2 )(274 Ly)(10 Cal/m 2 /Ly)(4186 J/Cal)(365 days) = 4.19E+13 J/ha/yr Transformity = defined as 1 (Odum, 1996) 2 WIND Area = 1.00E+04 m 2 Density = 1.3 Kg/m 3 Drag. Coefficient = 1.00E-03 (Odum 1996) Av. Annual Velocity = 1.16 mps (Jones et al.1984) Geostrophic wind = 1.93 (observed winds are about 0.6 of geostrophic wind) = (area)(density)(Drag Coeff.)(velocity) 3 (3.15E7 sec/yr) = 3.0E+09 J/ha/yr Transformity = 1,496 sej/J (Odum 1996) 3 RAIN, CHEMICAL POTENTIAL Area = 1.00E+04 m 2 /ha Rainfall = 1.3 m/yr (NOAA 2002) Gibbs Free Energy = 4.94 J/g = (1.00E+04 m 2 /ha)(1.3 m)(4.94 J/g)(1.00E+06 g/m 3 ) = 6.42E+10 J/ha/yr Transformity = 18,199 (Odum 1996) 4 RUN-IN, CHEMICAL POTENTIAL That portion of River overflow that contributes to transpiration From Water Balance = Rain + Run-in = Tr anspiration + Infiltration + Evaporation 1.3 + x = 1.25 + .58 + .09 (Brown 1978) Rin-in = 0.62 m/yr Area = 1.00E+04 m 2 /ha Gibbs Free Energy = 4.94 J/g = (0.62 m/yr)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 3.06E+10 J/ha/yr

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110 Transformity:4 8,500 (Buenfil 2000) 5 RIVER, GEOPOTENTIAL River channel maintenance Total River Discharge Average POR 1978-2000 = 64.61 ft3/s (USGS) or 1.83 m3/s River Discharge = 5.77E+07 m 3 /yr (USGS 2002) Change in height = 1.4E-01 m over 100 m (boundary) Density = 1000.00 Kg/m3 Gravity accelleration = 9.80E+00 m2/s Power = 7.92E+10 J/yr Transformity = 2.78E+04 sej/J (Odum 1996) 6 GEOLOGIC INPUT Limestone Eroded = 1.00E-05 m/yr (Odum 2000) Density of Limestone = 2.00E+06 g/m 3 = (1E-05 m/yr )(2E+06 g/m 3 )(1E+04 m 2 /ha) = 2.00E+05 g/ha/yr Transformity = 1.00E+09 Sej/g (Odum 1996) 7 WATER USE (TRANSPIRATION): calculated as daily summer transpiration rates times 220 days. Transpiration = 1.14 m/yr ( estimate from Brown 1978) Gibbs Free Energy = 4.94 J/g = (1.14 m)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 5.63E+10 J/ha/yr Transformity = 27,984 (Calculated as we ighted average of rain and run-in) 8 GROSS PRIMARY PRODUCTION Net Primary Production = 11.30 tn C/ha/yr (Brown 1978) = (11.30 tn/ha/yr) (1,000,000 g/tn) (8 kcal/g) (4186 J/kcal) = 3.78E+11 J//ha/yr Plant respiration = 84.68 tn C/ha/yr (Brown 1978) = (84.68 tn/ha) (1,000,000 g/tn) (8 kcal/g) (4186 J/kcal) = 2.84E+12 J/ha/yr Gross Production = 3.21E+12 J/ha/yr Total annual emergy = Sum of transpiratio n, river geopotential, and geologic input = 3.97E+15 Sej/ha/yr Transformity = (3.97E+15 Sej/ha/yr / 3.18E+12 J/ha/yr ) = 1,236 sej/J 9 INFILTRATION Infiltration Rate = 0.0016 m/day (estimate) Gibbs free energy = 4.94 J/g = (0.0016 m/d)(365 d/yr)(4.94 J/g)(1.00E+06 g/m 3 )(1.00E+04 m 2 /ha) = 2.88E+10 J/ha/yr Transformity = 27,984 (Calculated as weighted average of rainfall and run-in)

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111 Table 17. Emergy evaluation of storages of natural capital in floodplain forests. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej) (2000 em$/yr) Structure (Natural Capital) 1 Live Biomass 3.33E+12 J/ha 47754 158.96 $165,582 2 Organic Matter 2.26E+12 J/ha 101936 230.76 $240,376 3 Water 2.12E+10 J/ha 27984 0.59 $618 4 Geomorphic Structure 3.05E+09 g/ha 1.30E+09 3973.97 $4,139,553 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 17. 1 LIVE BIOMASS Biomass = 284 tn/ha green biomass (Brown 1978) Water weight (%) = 0.3 as decimal (estimate) Energy = (284 tn/ha)(.70 dry weight) (1,000,000 g/tn) (4 Cal/g) (4186 J/Cal) = 3.33E+12 J/ha Time to maturity = 40 yrs (estimate) Total annual emergy = Sum of transpiration, river geopotential, and geologic input = 3.97E+15 Sej/ha/yr Transformity = (3.97E+15 sej/ha/yr 40 yrs) / 3.33E+12 J/ha = 47,754 sej/J 2 ORGANIC MATTER Organic Matter = 10.4 kg/m 2 (depth of 20 cm) (Brown 1978) Heat Content = 5.20 Cal/g Peat = (10.4 kg/m2)(1.00 E+04 m2/ha)(1000 g/kg)(5.2 Cal/g)(4186 J/Cal) = 2.26E+12 J/ha Accumulation = Litterfall Decomposition Litterfall = 5.97E+02 g dry weight/m 2 /yr (Brown 1978) Decomposition = 4.18E+02 g dry weight/m 2 /yr (50% of litterfall, estimate, Deghi 1977 Turnover Time = Storage of Peat (g) / accumulation (g/yr) Time to develop peat = 58 yrs Total annual emergy = Sum of transpiration, river geopotential, and geologic input = 3.97E+15 Sej/ha/yr Transformity = (3.97E+15 Sej/ha/yr 35 yrs) / 2.26E+12 J/ha = 101,936 sej/J 3 WATER Volume of water taken as 89.6% moisture content of the volume of peat plus avg. standing water Peat Volume = 2.00E+03 m 3 Peat water = 1.79E+03 m 3 Standing water volume = 2.50E+03 m 3 (Brown 1978) Gibbs Free Energy = 4.94 J/g = (3.79E+03 m 3 )(1.00E+06 g/m 3 )(4.94 J/g) = 2.12E+10 J/ha Transformity: 27,984 (Calculated as weighted average of rain and run-in)

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112 4 GEOMORPHIC STRUCTURE Mass of channel + levee displaced Mass of channel = (Width)(length)(height)(Sinuosity) Channel Width = 1.00E+01 m Channel length = 1.00E+02 m Sinuosity = 1.2 (estimate) Channel Height = 2 m Channel Mass = 2.40E+03 m 3 Levee Mass = (2 levees)(.3 m high)( 2 m long)(120 m length of channel) = 144 m 3 Total Mass Displaced = 2.54E+03 m 3 Bulk density = 1.2 g/cm 3 = 3.05E+09 g Turnover Time = 1000 yrs Total annual emergy = Sum of transpira tion, river geopotential, and geologic input = 3.97E+15 Sej/yr Transformity = (3.97E+15 sej/yr 1000) / 3.05E+09 J/ha = 1.30E+09 sej/g

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113 Table 18. Emergy evaluation of annual drivi ng energies and envir onmental services of mesic hardwood forest. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej/yr) (2000 em$/yr) Energy Sources 1 Sun 4.19E+13 J/ha/yr 1 0.04 $44 2 Wind 2.96E+09 J/ha/yr 1496 0.004 $5 3 Rain, chemical potential 6.42E+10 J/ha/yr 18199 1.17 $1,217 4 Run-in, chemical potential 0 J/ha/yr 18199 0 $0 5 Geologic input 2.00E+05 g/ha/yr 1.00E+09 0.20 $208 Functions (Env. Services) 6 Transpiration (water use ) 3.71E+10 J/ha/yr 18199 0.67 $702 7 GPP 8.04E+11 J/ha/yr 1088 0.87 $911 8 Infiltration 2.52E+10 J/ha/yr 18199 0.46 $479 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 18. 1 SOLAR INSOLATION Area of wetland = 1.00E+04 m 2 Mean Net Radiation = 274 Ly (Henning 1989) = (1.00 E4 m 2 )(274 Ly)(10 Cal/m 2 /Ly)(4186 J/Cal)(365 days) = 4.19E+13 J/ha/yr Transformity = defined as 1 (Odum, 1996) 2 WIND Area = 1.00E+04 m 2 Density = 1.3 Kg/m 3 Drag. Coefficient = 1.00E-03 (Odum 1996) Av. Annual Velocity = 1.16 mps (Jones et al.1984) Geostrophic wind = 1.93 (observed winds are about 0.6 of geostrophic wind) = (area)(density)(Drag Coeff.)(velocity) 3 (3.15E7 sec/yr) = 3.0E+09 J/ha/yr Transformity = 1,496 sej/J (Odum 1996) 3 RAIN, CHEMICAL POTENTIAL Area = 1.00E+04 m 2 /ha Rainfall = 1.3 m/yr (NOAA 2002) Gibbs Free Energy = 4.94 J/g = (1.00E+04 m 2 /ha)(1.3 m)(4.94 J/g)(1.00E+06 g/m 3 ) = 6.42E+10 J/ha/yr Transformity = 18,199 (Odum 1996) 4 RUN IN, CHEMICAL POTENTIAL Run-in = 0 m/yr Mesic Hardwood Forests are not net sinks of run-in. 5 GEOLOGIC INPUT Limestone Eroded = 1.00E-05 m/yr (Odum 2000) Density of Limestone = 2.00E+06 g/m 3

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114 = (1E-05 m/yr )(2E+06 g/m 3 )(1E+04 m 2 /ha) = 2.00E+05 g/ha/yr Transformity = 1.00E+09 Sej/g (Odum 1996) 6 WATER USE (TRANSPIRATION) Transpiration = 0.75 m/yr (estimate, Liu 1996, Odum and Brown 1975) Gibbs Free Energy = 4.94 J/g = (0.75 m)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 3.71E+10 J/ha/yr Transformity = 18,199 (Calculated as we ighted average of rain and run-in) 7 GROSS PRIMARY PRODUCTION Net Primary Production = 10 tn C/ha/yr (estimate, Joyce 1995)) = (9.3 tn/ha/yr) (1,000,000 g/tn) (8 kcal/g) (4186 J/kcal) = 3.35E+11 J//ha/yr Plant respiration = 14 tn C/ha/yr (estimate, 60% of GPP) = (14 tn/ha) (1,000,000 g/tn) (8 kcal/g) (4186 J/kcal) = 4.69E+11 J/ha/yr Gross Production = 8.04E+11 J/ha/yr Total annual emergy = Sum of transpiration and geologic input = 8.74E+14 Sej/ha/yr Transformity = (8.74E+14 Sej/ha/yr / 8.04E+11 J/ha/yr ) = 1,088 sej/J 8 INFILTRATION Infiltration Rate = 1.40E-03 m/day (estimate from water b alance) Gibbs free energy = 4.94 J/g = (1.4E-3 m/d)(365 d/yr)(4.94 J/g)(1.00E+06 g/m 3 )(1.00E+04 m 2 /ha) = 2.52E+10 J/ha/yr Transformity = 18,199 (Calculated as weighted average of rainfall and run-in)

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115 Table 19. Emergy evaluation of storages of natural capital in mesi c hardwood forests. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej) (2000 em$/yr) Structure (Natural Capital) 1 Live Biomass 2.53E+12 J/ha 12087 30.60 $31,875 2 Organic Matter 1.96E+12 J/ha 19126 37.47 $39,030 3 Water 2.59E+08 J/ha 18199 0.00 $5 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 19. 1 LIVE BIOMASS Biomass = 216 tn/ha green biomass (Cost and McClure 1982) Water weight= 30 % (estimate) Energy = (216tn/ha) (0.70 dry weight)(1,000,000 g/tn) (4 Cal/g) (4186 J/kcal) = 2.53E+12 J/ha Time to maturity = 35 yrs Total annual emergy = sum transpiration, and geologic input = 8.74E+14 Sej/ha/yr Transformity = (8.74E+14 sej/ha/yr 35 yrs) / 2.53E+12 J/ha = 12,087 sej/J 2 ORGANIC MATTER Organic matter depth = 1.50E+01 cm (estimate) Bulk density = 1.50 g/m 3 (est., USDA 1985, ave. Millhopper-BonneauArredondo) % organic matter = 0.040 as decimal (estimate, USDA 1985) Organic matter = (% OM)(bulk density)(depth)(1.0 E+4 cm2/m2)(1.0 E-3 kg/g) = 9.0 kg/m 2 Heat Content = 5.20 Cal/g = 1.96E+12 J/ha Accumulation = Litterfall Decomposition Litterfall = 7.00E+02 g dry weight/m 2 /yr (estimate, Lugo et al. 1980) Decomposition = 4.90E+02 g dry weight/m 2 /yr (estimate 70% of litterfall, Lugo et al. 1980) Turnover Time = Storage of Peat (g) / accumulation (g/yr) Time to dev. OM = 43 yrs Total annual emergy = Sum of transpiration and geologic input = 8.74E+14 Sej/ha/yr Transformity = (8.74E+14 Sej/ha/yr 43 yrs) / 1.96E+12 J/ha = 19,126 sej/J

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116 3 WATER Assume same moisture holding capacity as pine flatwoods (3.5%) Soil Volume = 1500 m 3 Soil water = 5.25E+01 m 3 Avg. water depth = 0.00E+00 m Gibbs Free Energy = 4.94 J/g = (5.25E+01 m 3 )(1.00E+06 g/m 3 )(4.94 J/g) = 2.59E+08 J/ha Transformity: 18,199 (Calculated as weighted average of rain and run-in)

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117 Table 20. Emergy evaluation of annual drivi ng energies and envir onmental services of pine flatwoods. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej/yr) (2000 em$/yr) Energy Sources 1 Sun 4.19E+13 J/ha/yr 1 0.04 $44 2 Wind 2.96E+09 J/ha/yr 1496 0.004 $5 3 Rain, chemical potential 6.42E+10 J/ha/yr 18199 1.17 $1,217 4 Run-in, chemical potential 0.00E+00 J/ha/yr 0 0.00 $0 5 Geologic input 2.00E+05 g/ha/yr 1.00E+09 0.20 $208 Functions (Env. Services) 6 Transpiration (water use ) 2.74E+10 J/ha/yr 18199 0.50 $519 7 GPP 7.23E+11 J/ha/yr 965 0.70 $727 8 Infiltration 9.38E+08 J/ha/yr 18199 0.02 $18 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 20. 1 SOLAR INSOLATION Area of wetland = 1.00E+04 m 2 Mean Net Radiation = 274 Ly (Henning 1989) = (1.00 E4 m 2 )(274 Ly)(10 Cal/m 2 /Ly)(4186 J/Cal)(365 days) = 4.19E+13 J/ha/yr Transformity = defined as 1 (Odum, 1996) 2 WIND Area = 1.00E+04 m 2 Density = 1.3 Kg/m 3 Drag. Coefficient = 1.00E-03 (Odum 1996) Av. Annual Velocity = 1.16 mps (Jones et al.1984) Geostrophic wind = 1.93 (observed winds are about 0.6 of geostrophic wind) = (area)(density)(Drag Coeff.)(velocity) 3 (3.15E7 sec/yr) = 3.0E+09 J/ha/yr Transformity = 1,496 sej/J (Odum 1996) 3 RAIN, CHEMICAL POTENTIAL Area = 1.00E+04 m 2 /ha Rainfall = 1.3 m/yr (NOAA 2002) Gibbs Free Energy = 4.94 J/g = (1.00E+04 m 2 /ha)(1.3 m)(4.94 J/g)(1.00E+06 g/m 3 ) = 6.42E+10 J/ha/yr Transformity = 18,199 (Odum 1996) 4 RUN IN, CHEMICAL POTENTIAL Run-in = 0 m/yr Pine Flatwoods are not net sinks of run-in. (Sun 1995)

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118 5 GEOLOGIC INPUT Limestone Eroded = 1.00E-05 m/yr (Odum 2000) Density of Limestone = 2.00E+06 g/m 3 = (1E-05 m/yr )(2E+06 g/m 3 )(1E+04 m 2 /ha) = 2.00E+05 g/ha/yr Transformity = 1.00E+09 Sej/g (Odum 1996) 6 WATER USE (TRANSPIRATION) Transpiration = 0.554 m/yr (average from Liu 1996) Gibbs Free Energy = 4.94 J/g = (0.554 m)(1.00E+04 m 2 /ha)(1.00E+06 g/m 3 )(4.94 J/g) = 2.74E+10 J/ha/yr Transformity = 18,199 (Calculated as we ighted average of rain and run-in) 7 GROSS PRIMARY PRODUCTION Net Primary Production = 8.6 tn C/ha/yr (Golkin and Ewel 1984) = (8.6 tn/ha/yr) (1,000,000 g/tn) (8 kcal/g) (4186 J/kcal) = 2.88E+11 J//ha/yr Plant respiration = 13 tn C/ha/yr (Golkin and Ewel 1984) = (13 tn/ha) (1,000,000 g/tn) (8 kcal/g) (4186 J/kcal) = 4.35E+11 J/ha/yr Gross Production = 7.23E+11 J/ha/yr Total annual emergy = Sum of transpiration and geologic input = 6.98E+14 Sej/ha/yr Transformity = (6.98E+14 Sej/ha/yr / 7.23E+11 J/ha/yr ) = 965 sej/J 8 INFILTRATION Infiltration Rate = 5.20E-05 m/day (Golkin and Ewel 1984) Gibbs free energy = 4.94 J/g = (5.2E-05 m/d)(365 d/yr)(4.94 J/g)(1.00E+06 g/m 3 )(1.00E+04 m 2 /ha) = 9.38E+08 J/ha/yr Transformity = 18,199 (Calculated as weighted average of rainfall and run-in)

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119 Table 21. Emergy evaluation of storages of natural capital in pine flatwoods. Note Item Data Units Transformity Solar Emergy Em$ Value* (sej/unit) (E+15 sej) (2000 em$/yr) Structure (Natural Capital) 1 Live Biomass 2.11E+12 J/ha 9926 20.94 $21,814 2 Organic Matter 1.06E+12 J/ha 25331 27 $28,000 3 Water 2.25E+08 J/ha 18199 0.004 $4 em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000. Notes to Table 21. 1 LIVE BIOMASS Biomass = 180 tons/ha green biomass (Cost and McClure 1982) Water weight = 30 % (estimate) Biomass (dry weight)= 126 tons/ha Energy = (126 tn/ha) (1,000,000 g/tn) (4 Cal/g) (4186 J/Call) = 2.11E+12 J/ha Time to maturity = 30 yrs (estimate, Gholz and Fisher 1982) Total annual emergy = sum transpiration, and geologic input = 6.98E+14 Sej/ha/yr Transformity = (6.98E+14 sej/ha/yr 30 yrs) / 2.11E+12 J/ha = 9,926 sej/J 2 ORGANIC MATTER Organic Matter Depth = 1.30E+01 cm (Gholz and Fisher 1982) Bulk density = 1.25 g/m 3 (Gholz and Fisher 1982) % organic matter = 0.03 as decimal (Gholz and Fisher 1982, Edmisten 1963) Organic matter = (% OM)(bulk density)(depth)(1.0 E+4 cm2/m2)(1.0 E-3 kg/g) = 4.88 kg/m 2 Heat Content = 5.20 Cal/g = 1.06E+12 J/ha Accumulation = Litterfall Decomposition Litterfall = 4.22E+02 g dry weight/m 2 /yr (Gholz et al. 1991) Decomposition = 2.95E+02 g dry weight/m 2 /yr (70% litterfall, estimate) Turnover Time = Storage of Peat (g) / accumulation (g/yr) Time to dev. OM = 38.51 yrs Total annual emergy = Sum of transpiration and geologic input = 6.98E+14 Sej/ha/yr Transformity = (6.98E+14 Sej/ha/yr 38.51 yrs) / 1.06E+12 J/ha = 25,331 sej/J

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120 3 WATER Moisture Holding capacity of sandy soils ranging from 3-12 % depending on fire regimes (Edmisten 1963). An average of 7% was used in this calculation. Assume 1/2 year soil saturated, 1/2 moist, therefore 50% of saturation = 3.5% moisture holding capacity. Soil Volume = 1300 m 3 Soil water = 4.55E+01 m 3 Avg. water depth = 0.00E+00 m 3 Gibbs Free Energy = 4.94 J/g = (1.16E+03 m 3 )(1.00E+06 g/m 3 )(4.94 J/g) = 2.25E+08 J/ha Transformity: 18,199 (Calculated as weighted average of rain and run-in)

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LIST OF REFERENCES Abrahmson, W.G. and D.C. Hartnett. 1990. Pine flatwoods and dry prairies. In: Ecosystems of Florida, R.L. Myers and J. J. Ewel, eds. University of Central Florida Press, Orlando, Florida, USA. Abtew,W. 1996. Evapotranspiration measur ements and modeling for three wetland systems in South Florida. Wate r Resources Bulletin 32(3): 465-473. Bardi, E. and M.T. Brown. 2001. Emergy evaluation of ecosystems: a basis for environmental decision making. In: Emergy synthesis: Theory and application of the emergy methodology, M.T. Brown, ed. Center for Environmental Policy, University of Florida, Gainesville, Florida, USA. Batie, S.S. and C.C. Mabbs-Zeno. 1985. Opportunity costs of preserving coastal wetlands: a case of a recreat ional housing development. Land Economics 61(1): 1-9. Bell, F.W. 1997. The economic valuati on of saltwater marsh supporting marine recreational fishing in the southeastern United States. Ecological Economics 21: 243-254. Brinson, M.M. and R. Rheinhardt. 1996. Th e role of reference wetlands in functional assessment and mitigation. Ecologi cal Applications 6(1): 69-76. Brown, M.T. and J. Schaefer. 1988. Buffer zone s for water, wetlands, and wildlife. Final Report to the St. Johns River Water Mana gement District. Center for Wetlands, University of Florida, Gainesville, Florida, USA. Brown, M.T., J. Schaefer, and K. Brandt. 1990. Buffer zones for water, wetlands and wildlife in East Central Florida. Final Report to the East Central Florida Regional Planning Council, Winter Park, Florida. Center for Wetlands, University of Florida, Gainesville, Florida, USA. Brown, M.T., and S. Ulgiati. 1999. Emergy ev aluation of the biosphere and natural capital. AMBIO 28(6): 486-492. Brown, P.H. and C.L. Lant. 1999. The e ffects of wetland mitigation banking on the achievement of no-net-loss. Environmental Management 23(3): 333-345. 121

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122 Brown, S.L. 1978. A comparison of cypress ecos ystems in the landscape of Florida. dissertation, University of Florid a, Gainesville, Florida, USA. Buenfil, A.A. 2000. The value of water in Fl orida: a quantitative st udy of the importance of water for humans and the rest of nature Dissertation. University of Florida, Gainesville, Florida, USA. Burns, L. 1970. Analog simulation of a reain forest with high-low pass filters and a programmatic spring pulse. Appendix p. I284. In: A tropical rainforest, H.T. Odum and R.F. Pigeon, eds. Division of Technical Information, United States Atomic Energy Commission. Oak Ridge, Tennessee, USA. Cost, N.D., and J.P. McClure. 1982. Mu ltiresource inventories—forest biomass in florida. US Department of Agriculture, Southeastern Forest Experiment Station. Forest Service Research Paper S.E. – 235. Costanza, R., R. D’Arge, R. DeGroot, S. Fa rber, M. Grasso, B. Hannon, K. Limburg, S. Naeem, R. O’Neill, J. Paruelo, R.G. Rask in, P. Sutton, and M. van den Belt. 1997. The value of the world’s ecosystem servic es and natural capit al. Nature 387: 25360. Deghi, G.S. 1977. Effect of sewage effluent application on phosphorus cycling in cypress domes. Master’s thesis. University of Florida, Gainesville, Florida, USA. Dierberg, F.E. and K.C. Ewel. 1984. The e ffects of wastewater on decomposition and organic matter accumulation in cypress dom es. In: Cypress Swamps, K.C. Ewel and H.T. Odum, eds. University of Fl orida Press, Gainesville, Florida, USA. Edmisten, J.A. 1963. The ecology of the Flor ida pine flatwoods. Dissertation, University of Florida, Gainesville, Florida, USA. Ewel, K.C. 1990. Swamps. In: Ecosystems of Fl orida, R.L. Myers and J.J. Ewel, eds. University of Central Florida Press, Orlando, Florida, USA. FGDL. 2000. Florida Geographic Data Library. Geoplan Center, University of Florida. Version 2.0 (June 2000). Flohrschutz, E.W. 1978. Dwarf cypress in the Big Cypress Swamp of south-western Florida. Master’s Thesis. University of Florida, Gainesville, Florida, USA. Frayer, W.E. and J.M. Hefner. 1991. Flor ida wetlands: status and trends, 1970’s to 1980’s. U.S. Fish and Wildlife Servi ce, Southeast Region, Atlanta, Georgia. Gholz, H.L., and R.F. Fisher. 1982. Organic matter production and distribution in Slash Pine ( Pinus elliottii ) plantations. Ecology 42: 1827-1839.

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123 Gholz, H.L., R.F. Fisher, and W.L. Pritchet t. 1985. Nutrient dynamics in slash pine plantation ecosystems. Ecology 66: 648-659. Gholz, H.L, S.A. Vogel, W.P. Cropper, K. McKelvey, K.C. Ewel, R.O. Teskey and P.J. Curran. 1991. Dynamics of canopy st ructure and light interception in Pinus elliottii stands, North Florida. Ecol ogical Monographs 61 (1): 33-51. Golkin, K.R., and K.C. Ewel. 1984. A com puter simulation of the carbon, phosphorus, and hydrologic cycles of a pine flatw oods ecosystem. Ecological Modelling 24: 113-116. Gordon, N.D., T.A. McMahon, and B.L. Fi nlayson. 1992. Stream hydrology: an introduction for ecologists. John Wiley & Sons, New York, USA. Gosselink, J.G., E.P. Odum, and R.M. Pope. 1974. The value of the tidal marsh. Center for Wetland Resources, Louisiana State University, Baton Rouge, Louisiana, USA. Heimburg, K. 1984. Hydrology of north-cen tral Florida cypress domes. In: Cypress Swamps K.C. Ewel and H.T. Odum, eds. University of Florida Press, Gainesville, Florida, USA. Henning, D.1989. Atlas of the su rface heat balance of the continents: components and parameters estimated from climatologi cal data. Gebruder Borntraeger. Berlin, Stuttgart. Jones, J.W., L.H. Allen, S.F. Shih, J.S. Rogers, L.C. Hammond, A.G. Smajstrala, and J.D. Martsolf. 1984. Estimated and measured evapotranspiration for Florida climate, crops, and soils. Bulletin 840. Agricultural Experiment Station, Institute of Food and Agricultural Science, Univers ity of Florida, Gainesville, Florida, USA. Joyce, L.A. 1995. Productivity of america’ s forests and climate change. USDA, Forest Service. Genera l Technical Report RM-271. Rocky Mountain Forest and Range Experiment Station, Fort Collins, Colorado, USA. Liu, S. 1996. Evapotranspiration from cypre ss wetlands and slash pine uplands in north-central Florida. Dissertation, Univer sity of Florida, Gainesville, Florida, USA. Ludwig, D. 2000. Limitations of economic valu ation of ecosystems. Ecosystems 3: 3135.

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124 Nessel, J.K. and S.E. Bayley. 1984. Dist ribution and dynamics of organic matter and phospohorus in a sewage-enriched cypress swamp. In: Cypress Swamps K.C. Ewel and H.T. Odum, eds. University of Florida Press, Gainesville, Florida, USA. NOAA, National Oceanographic and Atmosp eric Administration. 2002. Climatological Data, Florida. Found at: http://www.no aa.gov. Accessed on 4/21/02. Maintained by the NOAA. Odum, E.P. 1969. The strategy of ecosys tem development. Science 164: 262-270. Odum, H.T. 1984. Summary: cypress sw amps and their regional role. In: Cypress Swamps K.C. Ewel and H.T. Odum, eds. University of Florida Press, Gainesville, Florida, USA. Odum H.T. 1996. Environmental accoun ting. emergy and environmental decision making. John Wiley & Sons, N.Y., USA. Odum, H.T. 2000. Emergy-emdollar evaluation and the Everglades. Center for Environmental Policy, University of Fl orida, Gainesville, Florida, USA. Odum, H.T. and M.T. Brown (eds.). 1975. Ca rrying capacity for man and nature in South Florida. Final Report to the U.S. Department of the Interior and Florida Division of State Planning. Center fo r Wetlands, University of Florida, Gainesville, Florida, USA. Odum, H.T. and E.P. Odum. 2000. The ener getic basis for valuation of ecosystem services. Ecosystems 3: 21-23. Odum, H.T., Wang, F.C., Alexander, J.F., Gilli land, M., Miller, M., and Sendzimer, J. 1987. Energy Analysis of Environmental Value Center for Wetlands, University of Florida, Gainesville, Florida, USA. Orrell, J.J. 1998. Cross scale comparison of plant production and di versity. Master’s Thesis. University of Florida, Gainesville, Florida, USA. Platt, W.J. and M.W. Schwartz. 1990. Temperate hardwood forests. In: Ecosystems of Florida R.L. Myers and J.J. Ewel, eds. Un iversity of Central Florida Press, Orlando, Florida, USA. Regan, E.J. 1977. The natural energy basis for soils and urban growth in Florida. Master’s Thesis. University of Fl orida, Gainesville, Florida, USA. Rushton, B. 1996. Hydrologic budget for a freshwater marsh in Florida. Water Resources Bulletin 32(1): 13-21.

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125 Schwartz, L.N. 1989. Nutrient, carbon, and water dynamics of a titi shrub ecosystem in Apalachicola, Florida. Mast er’s Thesis. University of Florida, Gainesville, Florida, USA. Starrett, D.A. 2000. Shadow pricing in economics. Ecosystems 3: 16-20. Sun, G. 1995. Measurement and modeling of the hydrology of cypr ess wetlands-pine uplands ecosystems in florida flatwoods. Dissertation, University of Florida, Gainesville, Florida, USA. Tilley, D.R. 1999. Emergy basis of forest system s. Dissertation. University of Florida, Gainesville, Florida, USA. USDA United States Department of Agricult ure. 1985. Soil Survey of Alachua County, Florida. U.S. Department of Commerce. 2001. Statis tical Abstract of th e United States: 2001. The Natianal Data Book. USGS United States Geological Surve y. Stream hydrology data. 2000. Found at: http://water.usgs.gov/. Accessed on 4/21/02. Maintained by the USGS. Weigert, R. G. 1974. A general mathema tical representation of ecological flux processes: description a nd use in ecosystem models. Proceedings of the 6th southeast systems symposium. Baton Rouge, Louisiana, USA. Wharton, C.H., H.T. Odum, K.C. Ewel, M.J. Duever, A.E. Lugo, R.Boyt, J. Bartholomew, E. DeBellevue, S.L. Brow n, M.T. Brown, and L.C. Duever. 1977. Forested wetlands: their management a nd use. Division of State Planning, Tallahassee, and Center for Wetlands, Univer sity of Florida, Ga inesville, Florida, USA. Zedler, J.B. 1996. Ecological i ssues in wetland mitigation: an introduction to the forum. Ecological Applicati ons 6(1): 33-37. Zolteck, J., S.E. Bayley, A.J. Hermann, L.R. Tortora, and T.J. Dolan. 1979. Removal of nutrients from treated municipal wastewat er by freshwater marshes. Final Report to the City of Clermont, Florida. Cent er for Wetlands, University of Florida, Gainesville, Florida, USA.

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126 BIOGRAPHICAL SKETCH Eliana Bardi was born on May 22, 1975 in Chieri, Italy. Having spent most of her early years living in the country side bordering Turin, she soon developed a love for travel and languages. At age sixteen she embarked into a journey to discover the “Americas” through an exchange student program. She then decided to remain in the United States and continue her education. After attending Central Florida Community College and the University of Central Florida, she transferred to the University of Florida in 1996. In 1998 she received a Bachelor of Arts in Economics, and immediat ely began pursuing a Mast er’s degree in the Environmental Engineering Sciences Depa rtment. While at UF, Eliana had the opportunity to teach an Envir onmental Science and Humanity Laboratory course as well as several Beginning Italian 1 courses. Thes e experiences instilled a love for teaching. After receiving a master of science degr ee in systems ecology and energy analysis in August 2002, Eliana plans to relocate to American Samo a and pursue a job with the Audubon Society working with mangrove wetlands.

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I certify that I have read this study an d that in my opinion it conforms to acceptable standards of scholarly presentation an d is fully adequate, in scope and quality, as a thesis for the degree of Master of Science. ______________________________ Mark T. Brown, Chairman Assistant Professor of Environmental Engineering Sciences I certify that I have read this study an d that in my opinion it conforms to acceptable standards of scholarly presentation an d is fully adequate, in scope and quality, as a thesis for the degree of Master of Science. ______________________________ Clay L. Montague Associate Professor of Environmental Engineering Sciences I certify that I have read this study an d that in my opinion it conforms to acceptable standards of scholarly presentation an d is fully adequate, in scope and quality, as a thesis for the degree of Master of Science. ______________________________ Clyde F. Kiker Professor of Food and Resource Economics This thesis was submitted to the Graduate Faculty of the College of Engineering and to the Graduate School and was accepted as partial fulfillment of the requirements for the degree of Master of Science. August, 2002 ______________________________ Pramod P. Khargonekar Dean, College of Engineering ______________________________ Winfred M. Phillips Dean, Graduate School


Emergy evaluation of ecosystems
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Title: Emergy evaluation of ecosystems a basis for mitigation policy
Physical Description: xi, 126 leaves : ill. ; 29 cm.
Language: English
Creator: Bardi, Eliana, 1975-
Publication Date: 2002
 Subjects
Subjects / Keywords: Environmental Engineering Sciences thesis, M.S   ( lcsh )
Dissertations, Academic -- Environmental Engineering Sciences -- UF   ( lcsh )
emergy
mitigation banking
Spatial Coverage: United States -- Florida
 Notes
Statement of Responsibility: by Eliana Bardi.
Thesis: Thesis (M.S.)--University of Florida, 2002.
Bibliography: Includes bibliographical references (leaves 121-125).
General Note: Printout.
General Note: Vita.
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Table of Contents
    Title Page
        Page i
    Acknowledgement
        Page ii
    Table of Contents
        Page iii
        Page iv
    List of Tables
        Page v
        Page vi
    List of Figures
        Page vii
        Page viii
        Page ix
    Abstract
        Page x
        Page xi
    Introduction
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        Page 2
        Page 3
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    Methods
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    Results
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    Discussion
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    Appendix A: Emergy Terminology and Systems Ecology Symbols
        Page 93
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    Appendix B: Emergy Evaluations of Six Florida Ecosystems
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    List of References
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    Biographical Sketch
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    Committee Signature Page
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Full Text











EMERGY EVALUATION OF ECOSYSTEMS:
A BASIS FOR MITIGATION POLICY

















By
ELIANA BARDI














A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE


UNIVERSITY OF FLORIDA


2002















ACKNOWLEDGMENTS


I wish to present my gratitude to my advisor, Mark Brown, for believing in me

and giving me the opportunity to challenge myself and think outside the box. Special

thanks go also to the supporting faculty members, Clay Montague and Clyde Kiker, for

the knowledge they shared in their classes and their invaluable input to this work.

I would not be here if it were not for the support and love of my many dear

friends here in Gainesville. I thank Matt and Leah, Chuck and Venessa, Jim and Chris,

Annie, and my ultimate divas for helping me keep my sanity (or whatever is left of it)

through the years. Matt was especially helpful on numerous occasions with simulation

modeling and emergy theory. Todd, Kelly, Susan, Sharlynn, Ben, Mark, Joel, and the

rest of the gang at the Center for Wetlands have been incredibly supportive and helpful

whenever I was in need.

Finally, I would like to thank my families: first, my Italian family, for believing in

me from day one, helping me along the way, allowing me to pursue my dreams away

from home, and inspiring me to always persevere; and second, my American family, for

welcoming me and opening their doors and hearts to me. They have made my staying in

the United States so fulfilling. And lastly, I thank my husband B.J for showing me a new

world, always encouraging me, pushing me to achieve great things, and helping me in so

many ways to accomplish this. I also thank his family for all the love and support they

have given me.













TABLE OF CONTENTS


ACKNOW LEDGM ENTS ..................................................................... iii

LIST OF TA BLES ........... .. .................. ...................... ... .. ...... vi

LIST OF FIGURES ................ ......................................... .. ...... viii

ABSTRACT.................................. .......................... xii

INTRODUCTION ................... ................... .... ............................

Statem ent of the Problem .............................................. ... .......... 1
Review of the Literature.................................................. ... ........ 3
Ecosystem Valuations................ ..............................3
Compensatory Mitigation and Mitigation Banking ........... ...............6
System s M odeling. ................................. ........... .... ...... ..8
Plan of Study ...................................... .................... .... ....... .. 8

M ETHODS............. ................. ................................................10

Description of Ecosystem Types ........... ..................... .................... 10
Emergy Evaluation of Ecosystems............... ..................... .............. 15
System Boundaries and Evaluated Parameters............................15
Mass and Energy Flows ................. ............. ............. 20
Calculation of Transformities................. ............ ..............23
Emdollar Evaluation .................................................................. 28
Emergy Evaluation of a Constructed Forested Wetland..........................30
Simulation Models.................... ................................ .......... 33
Forested W etland Simulation M odel....................................... 33
M odel Parameters and Calibration ............ ............... ... ......... 33
Constructed Wetland Cost Recovery Model ...............................34

RESULTS.............................................................. 35

Emergy Evaluation of Ecosystems........... .... ....... ......... ..... .............. 35
Energy, Emergy, and Transformity of Ecosystems.........................35
Emdollar Values of Ecosystems... .................. ............ ................44
Replacement Values of Ecosystems............... ...... ...........50
Emergy Evaluation of a Constructed Forested Wetland .......... ............50









Simulation M odels........... ...... .............. .............................. 56
Forested W etland Simulation M odel.................... ..................... 56
Energy, Emergy and Transformity of Forested Wetland Model............58
Constructed Wetland Cost Recovery Model .................. ............68

DISCU SSION .................................................................. .... ......... 74

Ecosystem Services and Natural Capital.................. .................. ..........74
M litigation R atios.....................................................................75
Static Replacem ent Ratios.................................. ......... ...... 76
Cost Recovery M litigation Ratios ............... ............. ..............79
Simulation M odel.................................. ......... ........ .. ........ 83
Limitations and Suggestions for Further Research................................87
Conclusions....................... .... ......... .. 90

APPENDICES

A SYSTEMS ECOLOGY SYMBOLS AND DEFINITIONS ...........................93

B EMERGY EVALUATIONS OF SIX FLORIDA ECOSYSTEMS.......................96


LITERATURE CITED ............ .... ........................................ .......... 121

BIOGRAPHICAL SKETCH ............... .............................. .......... ....126














LIST OF TABLES


Table pae

1. Summary of emdollar values of environmental services of six
Florida ecosystem s.................. .............. ................... .......... 47

2. Summary of emdollar values of natural capital (live biomass,
organic matter, soil water, and geologic structure) of six
Florida ecosystem s.................. .............. ................... .......... 49

3. Summary of replacement values of wetland and upland ecosystems
assume ing com plete elim ination......................................................... .51

4. Emergy evaluation of the inputs to construct a forested wetland
in Florida (J/ha)............ .................... ............. ............... ......... 52

5. Storage and internal flow equations for the forested wetland
sim ulation m odel ................. ................. ..................... ....... .. 59

6. Steady-state values of the storage and calibrated coefficients
for the forested wetland simulation model........... .............................. 62

7. Static replacement ratios for the six ecosystems using values
from Table 3 ................... ................... ........................ ........ 78

8. Mitigation ratios of forested wetlands at 10 year intervals
(from 60 to 100 years after construction) resulting from varying
initial organic matter storage to 1%, 25%, 50%, and 90% of its
steady state value................... ............................................86

9. Definitions of emergy terminology and indices used in this study .............. 94

10. Emergy evaluation of annual driving energies and environmental
services of forested wetlands in north central Florida.................. ..........96

11. Emergy evaluation of natural capital in forested wetlands..........................98

12. Emergy evaluation of annual driving energies and environmental
services of shrub/scrub wetlands in north central Florida............ .............100

13. Emergy evaluation of natural capital in shrub/scrub wetlands......................102










14. Emergy evaluation of annual driving energies and environmental
services of marsh wetlands in north central Florida.............. ............104

15. Emergy evaluation of natural capital in marsh wetlands............ ..............106

16. Emergy evaluation of annual driving energies and environmental
services of riparian wetlands in north central Florida.............. ........... 108

17. Emergy evaluation of natural capital in riparian wetlands .......................110

18. Emergy evaluation of annual driving energies and environmental
services of mesic hardwood forests in north central Florida....................... 112

19. Emergy evaluation of natural capital in mesic hardwood forests....................114

20. Emergy evaluation of annual driving energies and environmental
services of pine flatwoods in north central Florida ................................. 116

21. Emergy evaluation of natural capital in pine flatwoods............................118














LIST OF FIGURES


Figure pae

1. System boundary of a depressional wetland ............................. ............16

2. System diagram of a depressional wetland. GPP = gross
primary production; ES = saturation deficit ........... ......... ..........17

3. System diagram of a floodplain forest. GPP = gross primary
production; O.M. = organic matter; SED = sediment;
E S = saturation deficit ............ .. ....... ...... ................. .. ...... 18

4. System diagram of an upland ecosystem. The upland
ecosystems included mesic hardwood forests and pine
flatw oods...................... .............. ................... ... ........ 19

5. Boundary of a floodplain ecosystem (A), with
cross-sectional dimensions of channel and levees (B), and
calculations of mass displacement (C) ........... ............... ............... 24

6. Schematic of floodplain ecosystem structure showing the 1
hectare area evaluated (A). The turnover time of the floodplain
is illustrated in (B), where each box represents a 200 year
migration of the stream channel, completing the entire cycle
across the floodplain and back again in an estimated
1000 years ....................... ........ ................................. . . .... 25

7. Diagram of transformity calculations for water stored, infiltration,
and transpiration.................................. ............... ........ 27

8. Emergy per dollar (sej/$) of the United States from 1980-2000.
Values from 1980-1993 taken from Odum (1996), while from
1994-2000 calculated using data from the U.S. Statistical Abstract
(2001)and the same methods employed by Odum (1996)........................29

9. System diagram of a constructed forested wetland showing
the renewable energies and the economic inputs to the system
as well as the loss of soil organic matter and biomass resulting
from excavation.................................... ...................... ....... 32









10. Emergy signature of six Florida ecosystems showing the
environmental inputs to the system. S = sun; W = wind; R = rain;
RI = run-in; G = geologic input; RG = river geopotential. All values
expressed in 1.0E+15 sej/ha/yr. Note the different scale on each
graph. ........... .............................................. ...........36

11. Annual driving emergy of six Florida ecosystems (sum of
transpiration, geologic input, and river geopotential for the
floodplain forest; sum of transpiration and geologic input for all
other ecosystems). Calculated from data in Appendix B,
Tables 10-21 ............ ...................... ...................... ... . ..... 38

12. Transpiration and infiltration values of six Florida ecosystems.
(A)Power Density; (B) Solar Transformity; (C) Empower Density.
See A ppendix B Tables 10-21 ............................................. ............39

13. GPP values of six Florida ecosystems. (A) Power Density;
(B) Solar Transformity; (C) Emergy. See Appendix B, Tables 10-21............41

14. Biomass values of six Florida ecosystems. (A) Energy;
(B) Transformity; (C) Emergy. See Appendix B, Tables 10-21 ....................42

15. Organic matter values of six Florida ecosystems. (A) Energy;
(B) Transformity; (C) Emergy. See Appendix B, Tables 10-21 ......................43

16. Soil water values of six Florida ecosystems. (A) Energy;
(B) Transformity; (C) Emergy. See Appendix B, Tables 10-21 ......................45

17. Geologic structure of four wetland ecosystems. (A) Energy;
(B) Transformity; (C) Emergy. See Appendix B, Tables 10-21 ..................46

18. System diagram of forested wetland simulation model showing
energy flows and storage evaluated ...... ....................... .. ............. 57

19. Diagram showing calculations of emergy and transformity of
biomass in the forested wetland simulation model...................................63

20. Diagram showing calculations of emergy and transformity of
organic matter in the forested wetland simulation model............ ............64

21. Simulation results of the forested wetland model showing time
series of forest biomass and organic matter storages...............................65

22. Emergy and transformity of forest biomass storage in forested
wetland model ................................. ..................... ... ... 66









23. Emergy and transformity of organic matter storage in forested
w etland m odel .......................................................... ....... .. 67

24. Simulation results of biomass energy storage after increasing
initial organic matter storage to 25%, 50%, and 90% of its steady
state value showing increased growth rates as the initial organic
matter value increases ....................................... ............. 69

25. Simulation results of organic matter energy storage after increasing
initial organic matter storage to 25% and 50% of its steady state
value, showing increased growth rates of organic matter.........................70

26. Simulation results of (A) GPP emdollar value, and (B) recovery
time needed to payback constructions costs (calculated by adding
yearly G PP to initial debt) ............................................. ............. 7 1

27. Simulation results of GPP and recovery time under different
initial organic matter storage values, showing an increase
in GPP (A) and a decrease in recovery time (B) as the initial
organic matter storage is increased by 25%, 50%, and 90%
of its steady state value ....................... ..... ................ ............ 73

28. Graph of transpiration accrual in mature forested wetland and
constructed ecosystem. The ratio of these two lines at any point
in time constitutes the mitigation ratio necessary to recover
losses due to construction within that time frame ................................. 81

29. Simulated mitigation ratios for forested wetland from 54 to 100
years after construction showing decrease in mitigation ratios
as the time frame allowed to offset losses increases................................82

30. Simulated mitigation for forested wetlands from 60 to 120 years
after construction showing decrease in mitigation ratios as the
initial storage of organic matter is increased by 25%, 50%, and
90% of its steady state value.............................................................85

31. Select energy systems symbols and definitions (after Odum
1996) .................................... ............................ .......... 93















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

EMERGY EVALUATION OF ECOSYSTEMS:
A BASIS FOR MITIGATION POLICY

By

Eliana Bardi

August 2002


Chair: Mark Brown
Major Department: Environmental Engineering Sciences

This thesis focuses on quantifying ecosystems' value to society both in terms of

the environmental services and the natural capital they contribute. The research has

concentrated on the ecosystem services of transpiration, infiltration, and gross primary

production, and the natural capital of biomass, soil organic matter, water, and geologic

structure. Six Florida ecosystems, four wetlands and two uplands, were studied. A

constructed forested wetland was evaluated to explore costs and benefits of mitigation. A

computer model was developed to simulate the energy, emergy and transformity of

forested wetlands biomass and organic matter. A cost recovery model was also

developed to shed light on the time frame needed to recover losses from mitigation.

Results of this research can be summarized in four main points. First, ecosystems

in general, and wetland communities in particular, are extremely valuable to

human society. On an annual basis wetlands provide between 2,295 and 6,430 em$/ha/yr









of value to regional human economies, compared to two upland ecosystems values of 727

and 911 em$/ha/yr. The natural capital (value stored in biomass, organic matter, and soil

water) of wetlands ranges from 283,286 to 1,018,641 em$/ha, compared to the upland

ecosystems, whose values range from 49,819 to 70,909 em$/ha. Replacement values of

wetlands range between 301,645 and 1,081,230em$/ha, while replacement values of

uplands range between 64,362 and 93,677 em$/ha.

Second, mature ecosystems are the work of decades of ecosystem services and

natural capital accrual. When a forested wetland is cut down and replaced by a created

one, the created wetlands are usually monitored for only a few years. However, the

ecosystem needs 165 years to reach 90% of its steady state biomass, and 386 years to

accumulate 90% of its steady state storage of soil organic matter.

Third, constructed wetlands are characterized by large initial investments (costs)

of construction. Construction costs of forested wetlands are approximately 103,000

em$/ha, with an additional 2,108 em$/ha spent for monitoring during the following three

years. Approximately 54 years are required for the services (represented by GPP) of the

newly constructed ecosystem to offset the losses due to construction.

Fourth, mitigation ratios (the ratio of constructed wetland required to replace

wetland destroyed) are more properly determined using dynamic analysis of ecosystem

value, since the ratios decrease as the time to offset losses increases. For instance,

mitigation ratios for forested wetlands are 5.48:1 if the time frame allowed to offset

losses is 70 years and decrease to 2.66:1 if the time frame is 100 years. Adding organic

matter to created sites decreases construction costs, recovery times, and mitigation ratios.













INTRODUCTION


Statement of the Problem

With increasing demand for lands by all types of development in support of

growing human populations, there has been an increasing pressure to develop marginally

developable lands. In Florida, where estimates suggest that approximately 30% of the

landscape is wetlands (Frayer and Hefner 1991), this pressure translates into potentially

significant impacts to wetland ecosystems.

In the past century much of Florida's developed landscape was constructed on the

most usable land, leaving wetlands and poorly drained flatwoods. Now, with

developable land becoming more and more scarce, especially near rapidly growing urban

centers, attention is shifting toward more marginal land. This shift in the direction of

development is resulting in an increased pressure on wetlands.

There are many state and federal regulations that limit direct impacts to wetlands.

However, as a result of increased demand for developable lands, agencies responsible for

protecting wetlands are under pressure to permit development in and around wetlands. To

offset losses of wetlands, state and federal agencies have instituted systems of mitigation.

Mitigation in this context generally means the act of offsetting losses that result from the

elimination of wetlands through development actions. While at times mitigation has

included such practices as restoration of impaired wetlands or preservation, in this thesis

mitigation has been more narrowly defined as construction of wetlands as

replacement for those destroyed.







2

Early regulations associated with mitigation required that it take place on the site

where the impacts occurred. However, as agencies have gained more experience, there

has been a shift away from onsite and type for type mitigation to off site and, most

recently, toward the creation of regional mitigation banks. Today, compensatory

mitigation and mitigation banking are relatively common practices, yet there is no clear

understanding of the environmental benefits and losses to society that result from these

practices. In addition, regulations pertaining to mitigation are hindered by the lack of a

clear and objective means of quantitatively determining appropriate mitigation ratios. As

a result of those concerns, several questions arise. (1) How might the various properties

and functions of wetlands be evaluated? (2) What are the relative values of wetlands? (3)

What functions of wetlands are the most valuable? (4) What are the costs and benefits of

wetland mitigation? (5) What is the best scheme for determining appropriate mitigation

ratios?

All in all, what is needed is an assessment method that can determine the

environmental values of whole systems. With such an evaluation, society could judge the

costs, benefits, and trade-offs associated with wetland impacts and mitigation.

Furthermore, by using the relative values of ecosystems more appropriate mitigation

ratios might be determined.

In this thesis, the structural properties and main processes of several wetland and

upland ecosystems were evaluated using emergy analysis techniques. The goal of the

research was to determine relative values of wetland and upland ecosystem components

and processes, and then to develop insight by comparative analysis related to costs and

benefits of mitigation.







3

Review of the Literature

Ecosystems Valuations

Ecosystems have been conventionally valued on the basis of their monetary

contribution to human society. For instance, salt marshes may be given a monetary

value dependent upon the perceived profit from fisheries production, tourism, and

recreation use. Forested wetlands may be evaluated on the basis of their marketable

timber. These types of evaluations focus on ecosystem functions and storage that have a

marketable value and can thus be sold as commodities such as fish or timber (Bell 1997).

However, other non-marketable attributes of ecosystems remain ignored by these types of

evaluations, such as water purification or wildlife habitat. In the literature, there are

several approaches to valuating wetlands. These methodologies can be grouped into two

main categories: (1) economic valuations from perceived monetary gains, (2) energetic

valuations from ecosystem processes and pathways.

The most common type of economic valuation of non-marketable ecosystems

services and natural capital is to assess an individual's willingness-to-pay for those

services. This approach relies on human preferences and perceived gains from

ecosystems to establish a "price" for non-marketable attributes (Costanza et al. 1997).

While it is a widely employed method of estimating value of non-marketable goods and

services, its shortcomings are also widely recognized (Ludwig 2000, Starrett 2000, Odum

and Odum 2000). In fact, the willingness-to-pay method fails to accurately quantify

ecosystem value from a scientific perspective, since it is based solely on people's

preferences, not on the ecosystems' structural and functional components (Brown and

Ulgiati, 1999). Bell (1997) identifies other methodologies, including the "land-price"







4

analysis method, which estimates wetland values on the basis of the highest economic use

that can be derived from the land, and the "replacement or substitution model", which

assesses wetland values by calculating how much it costs to restore destroyed or

developed wetlands to their original state. The latter simply adds up costs for machinery,

products, and human labor to carry out the project, and again ignores other valuable

natural services provided by wetlands. A somewhat more simplistic methodology is the

"opportunity cost of preservation model," in which preservation of natural resources that

cannot be monetarily evaluated is favored unless the value of the forgone development is

"unacceptably" large (Batie and Mabbs-Zeno 1985). However, this method fails to

provide any quantitative guidelines for what is considered "unacceptably" large, and

while it considers in depth the economic values of the possible development scenarios, it

fails to account for the ecosystem values lost from wetland destruction. All of these

economic valuations are only appropriate for recognizing services from ecosystems that

have a market, (i.e. fish or timber sold on the market) and result in subjective estimations

of the many other services ecosystems provide to society, such as infiltration, water

storage, increased water quality, and wildlife value.

The importance of integrating ecological and economic values of ecosystems was

recognized by Odum (Odum 1996). Energetic evaluations of ecosystem processes and

pathways emphasize energy networks and processes within ecosystems. Gosselink et al.

(1974) employed such a methodology in estimating the value of one acre of tidal marsh

wetland. Their calculations involved estimating the economic value of the wetland

products and services (fisheries, aquaculture potential, and waste treatment), as well as

the life support value as a function of energy flow (gross primary production times







5

energy/money conversion ratio). The Gosselink et al. (1974) study resulted in a value of

$82,000/ acre of tidal marsh. This value can be compared to a more traditional economic

value for a saltmarsh calculated by Bell (1997) that ranged between $981 and $6,471.

The huge difference in the reported values is probably due to the fact that Bell (1997)

attempted to place an economic value on the contribution of wetlands to recreational

fishing alone, without taking into account other important services of saltmarshes, such as

gross primary production.

Energetic valuations and emergy. Odum developed a method of valuation that

was based on the total amount of energy of one kind used directly or indirectly (and

through all pathways) to make a product or service (Odum and Odum 2000). The

concept was later termed emergy, signifying "energy memory" (Odum, 1996). The

emergy accumulated in an ecosystem increases as it matures and it is calculated by

multiplying the energy storage by their transformity. Transformity, or the solar emergy

required to make one joule of a service or product (Odum 1996), is calculated by dividing

a product's solar emergy by its energy. Transformity increases as processes become

more refined, and it thus can be a measure of maturity and efficiency. For example, the

biomass of a mature, old growth forest will have a higher transformity than the one of a

younger forest, since its emergy has been accumulating for a longer time.

Compensatory Mitigation and Mitigation Banking

Wetland mitigation has become an indispensable tool in the implementation of the

"no-net-loss" policy for wetlands, which stemmed from Section 404 of the Federal Clean

Water Act. In its broadest definition, mitigation refers to the avoidance, minimization,

and elimination of negative impacts to wetlands, or compensation by replacement or







6

substitution of equivalent wetland value in order to achieve "no-net-loss" of wetland

function. However, "equivalent wetland value" and "wetland function" are not explicitly

defined and are thus subject to personal interpretation. Much of the literature on wetland

mitigation reports on the success or failure of mitigation sites (Zedler 1996,Brown and

Lant 1999, Brinson and Rheinhardt 1996), while there are very few studies that address

the issue of how to quantify a wetland's contribution to society (Bardi and Brown 2001).

Compensatory mitigation, which is the replacement of impacted wetlands by

creating new ones, has had limited success due to difficulties in implementing

regulations, monitoring, and assessing the long-term viability of the numerous and small-

scale mitigation sites. To address this concern, there has been a move in recent years

towards the use of mitigation banks as an alternative to the "postage-stamp" wetland

creation. Mitigation banks are often large-scale projects that incorporate wetland

creation, restoration, enhancement or preservation within regionally significant lands.

Unlike compensatory mitigation, which occurs simultaneously or after wetland impacts

have already taken place, mitigation banks are established in advance by a third party

(mitigation banker), who then sells the wetland credits to future developers whose

projects impact wetlands.

Wetland mitigation banks offer several advantages and disadvantages: first, they

consolidate small-scale projects into larger tracts of land, thus reducing permitting and

monitoring requirements by federal, state, and local agencies. Second, they create the

wetland credits in advance of impacts, thus ensuring the achievement of no-net-loss, and

are required to invest in long-term financially secured management plans, usually by

donating the banks to nature preserves or state agencies once they sell out. Finally, such







7

large-scale projects can be more economically cost effective, thus reducing overall waste

of human and material resources. On the other hand, the money-making enterprise of

mitigation banking has attracted a lot of skepticism as well, and critics of mitigation

banks question whether it is ecologically sound to shape the landscape by concentrating

wetlands in one location at the expense of smaller, isolated wetlands that dot the

landscape.

Mitigation ratios. Whether compensation occurs through compensatory

mitigation or mitigation banks, a mitigation ratio is used to calculate how many acres of

compensation are required for a specific wetland impact. This mitigation ratio represents

the value of acres compensated per acres converted of a particular ecosystem (Brown and

Lant,1999). Because the current system lacks clearly defined functional methodologies

for assessing wetland value, mitigation ratios are assessed qualitatively and are dependent

on several criteria: the perceived value of the ecosystem to be impacted, the ease of

replacement, and the perceived recovery time needed for the constructed ecosystem to

reach predefined success criteria (Zedler, 1996). The acres compensated must not

necessarily be in the form of newly constructed ecosystems, but can also extend to

restoration, preservation and enhancement of already existing ecosystems. Typical

mitigation ratios range between 2:1 for restoration, 3:1 for creation, 4:1 for enhancement,

and 10:1 for preservation, that is, for 1 acre of wetland impacted, 2 acres have to be

restored while if the new ecosystems are created, for each acre impacted 3 acres would

have to be constructed. However, because each wetland is assessed on a case by case

basis, there is much variability in their use.









Systems Modeling

Simulation models of ecosystems are useful tools to make predictions of

ecosystem behavior from data collected in the field. Most models have focused on the

dynamics of succession (Odum 1967, Burns 1970, Regan 1977), or prey-predator

relationships and competition for scarce resources (Wiegert 1974).

Tilley (1999) explored new theories in computer simulation by modeling the

energy, emergy, and transformity of forest biomass, organic matter, and saprolite in the

Coweeta watershed. Until then, energy quality had been analyzed using emergy analysis

at a particular point in time. Tilley's simulation showed that energy, emergy and

transformity all increased over time, with the physical components (energy storage)

reaching their maximum value at a faster rate than both emergy and transformity.

Emergy accumulation and transformity, in other words, the quality of ecosystems, is not

only a function of the energy storage, but also of the time it takes to accumulate value.


Plan of Study

This thesis focuses on quantifying ecosystem value and calculating mitigation

ratios among different ecosystems. First, emergy evaluations were conducted for six

major Florida ecosystems and their components: depressional cypress dome, shrub/scrub

wetland, freshwater marsh, floodplain forest, mesic hardwood forest, and pine flatwoods.

Comparisons between systems and their components were then made.

Second, the energy costs of constructing a forested wetland were evaluated.

Third, a dynamic simulation model of an aggregated ecosystem was used to evaluate the

energy, emergy, and transformity of biomass and organic matter in forested wetlands.

Results from the simulation model were used to investigate the time needed to recover







9

the initial investment of wetland construction/creation to explore the question of whether

created wetlands are sound investments for the future of Florida. Finally, these analyses

and the resulting data were used to study mitigation options and overall policy with

recommendations for mitigation ratios and timing.













METHODS


The following methods are divided into several sections, beginning with a

description of the ecosystem types that were evaluated. The second and third sections,

"Emergy Evaluation of Ecosystems" and "Emergy Evaluation of a Constructed Forested

Wetland," provide details of methods used to evaluate data gathered from the literature

on Florida ecosystems and a constructed wetland. The fourth section, "Simulation

Modeling," presents the methodology applied to the computer simulation models.

Descriptions of Ecosystem Types

Six Florida ecosystems were evaluated: four wetland ecosystems (cypress dome,

shrub/scrub wetland, freshwater depressional marsh, and floodplain forest), and two

upland ecosystems (a mesic hardwood forest and pine flatwoods). These ecosystems

make up approximately 97% of the freshwater wetland area and 87% of the forested

upland area in the current landscape of Florida (Florida Geographic Data Library 2000).

Descriptions of each ecosystem, summarized from Brown et al. (1990) and Brown and

Schaefer (1988), follow:

Cypress domes--Cypress domes are found throughout Florida as small

depressions most often within pine flatwoods. These small depressions are called cypress

domes due to the domed shape of the trees when viewed from the side. Cypress domes

are one of the most common forested wetlands in north central Florida. Standing water

occurs in cypress domes from 50%-90% of the time. Pond cypress (Taxodium

ascendens) is the dominant canopy specit 10 other canopy species include black gum







11

(Nyssa sylvatica), pond pine (Pinus serotina), slash pine (P. elliottii), red maple (Acer

rubrum), and one or more of the bay species, such as red bay (Persea borbonia), sweet

bay (Magnolia virginiana), and loblolly bay (Gordonia lasianthus). The understory of

these ecosystems is often diverse. Dominant understory species in cypress domes include

fetterbush (Lyonia lucida), wax myrtle (Myrica cerifera), dahoon holly (Ilex cassine),

buttonbush (Cephalanthus occidentalis), Virginia willow (Itea virginica), and myrtle-leaf

holly (Ilex myrtifolia). Vegetation at ground level is often sparse and is a function of the

wetland hydroperiod. The most frequent herbaceous species are lemon bacopa (Bacopa

caroliniana), Virginia chain fern (Woodwardia virginiana), coinwort (Centella asiatica),

redroot (1,JIchu inhe,' caroliniana), and various graminoids (e.g. Panicum spp.). The

ecotone consists of transitional species such as wax myrtle, gallberry (Ilex glabra), high-

bush blueberry (Vaccinium spp), fetterbush (Lyonia lucida), greenbriar (Smilax spp.),

blackberry (Rubus spp.), muscadine grape (Vitus rotundifolia), and yellow jessamine

(Gelsemium semprevirens).

Shrub- scrub wetland--The shrub-scrub wetland can be relatively diverse or

dominated by only a few species depending on hydrology and fire regime. When diverse,

these ecosystems are dominated by both woody shrubs and herbaceous wetland

vegetation. Common woody shrub species include: Carolina willow (Salix caroliana),

fetterbush, wax myrtle, dahoon holly, buttonbush, and Virginia willow, all occurring at

varying dominance depending on the hydroperiod. Many of the same herbaceous species

found in marshes are also found in the shrub-scrub wetland, but at much lower densities.

Common herbaceous species include lemon bacopa, sawgrass (Cladiumjamaicense),

bullrush (Scirpus spp.), Virginia chain fern, coinwort, and panicum. In some instances,







12

the scrub-shrub wetland is dominated by only one or two woody species and has higher

densities of herbaceous vegetation. The ecotone consists of transitional species such as

such as wax myrtle, stagger-bush (Lyoniaferruginea), gallberry, fetterbush, and vines

such as greenbriar, blackberry, muscadine grape, and yellowjessamine (Brown and

Schaefer, 1988; Brown et al. 1990).

Depressional herbaceous marsh--Shallow marshes occupy low topographical

areas and are common throughout central Florida as interspersed ecosystems in pine

flatwoods matrix. Shallow marshes are typically circular in shape and vary from small

(less than one half acre) to large (tens of acres). Depth of standing water during the rainy

season is typically 25 to 55 centimeters. Most flatwoods marshes are relatively

oligotrophic, with the main source of nutrients being rainfall and surface drainage from

surrounding watersheds. The ecotone of these systems often consists of mesic oak

communities, pine flatwoods, or cypress domes. Shallow marshes are common where

inundation is frequent and depths of inundation are less than 0.5 meters. Marsh

vegetation consists of a diversity of species. In the grassy shallow marshes, species that

consistently occur and are often dominant include panicum, St. John's Wort (Hypericum

spp.), yellow-eyed grass (Xyris spp), marsh fleabane (Pluchea spp), redroot, and pickerel-

weed (Pontedaria cordata). Also common occurring species are sawgrass, spikerush

(Eleocharis spp.), soft rushes (Juncus spp.). Broad-leaved marshes, often referred to as

flag ponds, are marsh communities that exhibit deeper inundation, longer hydroperiods,

and deep accumulations of organic matter. Dominant species include pickerelweed,

arrowhead (Sagittaria spp.), fire flag (Thalia geniculata), bulrush (Scirpus spp.), and

cattail (Typha spp.) (Brown and Schaefer, 1988; Brown et al. 1990).







13

Floodplain forests--Floodplain forests make up approximately one-third of

Florida's swamps and are found predominantly in north Florida. They occur along

creeks, rivers, and sloughs and are often referred to as bottomland hardwood forests.

Although there are six types of river swamps in Florida, depending on the river's energy,

water quality, and location in the landscape (Wharton et al. 1977), this analysis focuses

on Blackwater floodplain forests. Blackwater rivers and creeks exhibit much slower flow

rates than alluvial rivers and thus carry little alluvium to the surrounding floodplain.

Occasionally an impermeable soil layer beneath the floodplain also contributes to

standing water (Ewel 1990). Canopy species include white ash (Fraxinus caroliniana),

bald cypress, red maple, swamp blackgum (Nyssa sylvatica var. biflora), water hickory

(Carya glabra), and hornbean (Carpinus caroliniana), to name a few. Understory shrubs

include dahoon holly, wax myrtle and buttonbush. The herbaceous layer is often diverse

with cinnamon fern (Osmunda cinnamomea), Virginia chain fern, pickerelweed, lizard's

tail (Saururus cernuus), and many others. Floodplain wetlands are often bordered by

mesic hardwoods and flatwoods in slightly higher elevations.

Mesic hardwood forests--This community is found throughout most of the

Southeastern Coastal Plain but coverage is restricted to areas shielded from fire. These

forests therefore do not occur extensively, but rather as narrow bands of vegetation

bounded by sandhills and flatwoods on upgradient slope and bottomland forests down

gradient. This community is a diverse and complex ecosystem characterized by large

evergreen trees such as live oak (Quercus virginiana), Southern magnolia (Magnolia

grandiflora), loblolly bay (Gordonia lasianthus), intermixed with deciduous tree species

such as sweet gum (Liquidambar styraciflua), red maple, water oak (Quercus nigra) and







14

laurel oak (Quercus laurifolia) (Odum and Brown 1975). Pines such as slash (Pinus

elliottii) and loblolly (Pinus taeda) are often present at low densities. A variety of factors

influence the vegetation composition of mesic hardwood forests, such as organic matter,

exchangeable cations, pH, and nutrient availability. For example, evergreen species

occur more often on nutrient poor sites as they have a more closed nutrient cycle

compared to deciduous species.

Mesic hardwood forests are characterized by greater diversity, vegetation

layering, and greater accumulation of organic matter than the adjacent pinelands (Platt

and Schwartz 1990).

Pine flatwoods--Pine Flatwoods cover as much as 50% of the Florida peninsula

(Edmisten 1963). Flatwoods, as the name indicates, are generally located in areas of little

relief in somewhat poorly drained to very poorly drained soils (Edmisten 1963). They

are characterized by open canopies composed of one or more pine species such as pond

pine (Pinuspalustris), slash pine, and loblolly pine. Understory species include a variety

of shrubs, graminoids, and herbaceous plants such as wax myrtle, saw palmetto (Serenoa

repens), gallberry, staggerbush, fetterbush, blueberry, and wiregrass (Aristida

beyrichiana). Vegetation composition is influenced by factors such as soils, drainage, and

hydroperiod. Wet flatwoods are seasonally inundated, occur on sandy soils, and are

composed of slash pine, pond pine, and cabbage palm with a hydrophytic understory that

includes wax myrtle and fetterbush. Mesic flatwoods are prevalent in drier sites and have

canopies of slash and longleaf pine, with an understory of gallberry, rusty lyonia, and

wiregrass (Abrahmson and Hartnett 1990). Pine flatwoods have been described as the

matrix tying together different types of vegetation, such as wet prairies, marshes,







15

swamps, sandhills, and scrubs (Edmisten 1963). Pine flatwoods are fire maintained

ecosystems.

Emergy Evaluation of Ecosystems

Emergy evaluations were conducted using emergy terminology and symbols as

introduced by Odum (1996). Appendix A summarizes emergy terminology (Table 9)

and symbols (Figure 31) used throughout the study.

System Boundaries and Evaluated Parameters

Figure 1 illustrates the system boundary for the depressional wetland evaluations

and depicts the various parameters included in the evaluations. The underlying geologic

structure was included within the system boundary. For illustrative purposes, half the

wetland is shown as a forested wetland and the other half as a marsh. The evaluations

were done for 1 hectare (approximately 2.5 acres) of typical wetland.

Figures 2, 3 and 4 are generalized systems diagrams of a depressional wetland, a

riparian forest, and an upland ecosystem, respectively. Figures 2, 3 and 4 show the main

driving energies, environmental services, and storage (natural capital) that were

evaluated for each of the ecosystems. The dominant driving energies of the ecosystems

are: sunlight, wind, rainfall, run-in (surface water runoff from the surrounding

watershed), and the emergy contribution from geologic processes. Mesic hardwood

forests and pine flatwoods are not net sinks of run-in (Sun 1995), and therefore it does

not appear as an input in Figure 4. The main material storage ofbiomass, peat, water,

and geomorphic structure were evaluated for the four wetland ecosystems, while only

biomass, organic matter, and water were evaluated for the two upland ecosystems.







16










Area = 1 hectare
- - - - - - - SYSTEM BOUNDARY




A h 1~


CLAYEY LENSES
/ Infiltration

10m \
Sl TOP OF
V HAIWTHORNE FORMATION


DOLOMIITE K
L - - -^ f_ ------ _


Figure 1. System boundary of a depressional wetland.












































Figure 2. System diagram of a depressional wetland. GPP = gross
primary production; ES = saturation deficit.








































Infiltration nd runoff

VEGETATION
GPP







Figure 3. System diagram of a floodplain forest. GPP = gross
primary production; O.M. = organic matter; SED = sediment;
ES = saturation deficit.













































Figure 4. System diagram of an upland ecosystem. The upland
ecosystems included mesic hardwood forests and pine flatwoods.







20

Driving energies and ecosystem storage interact in several processes that

generate ecosystem services. Three services (ecosystem functions) of these ecosystems

were evaluated: (1) transpiration of water, (2) gross primary production (GPP), and (3)

water recharge (infiltration).

Mass and Energy Flows

Data from the literature were used to evaluate the mass and energy flows for each

of the ecosystems. Sunlight, wind, and rainfall were taken as average conditions for the

North Central Florida location. Run-in (surface runoff into the wetland) for forested and

scrub/shrub wetlands was cited from Heimburg (1984) and Schwartz (1989) respectively.

A runoff coefficient of 0.35 and a 1:1 watershed to wetland ratio was assumed for run-in

to the marsh. Stream overbank flow, which represents the major portion of run-in water

for the floodplain forest, was calculated from estimates of Brown (1978), and water

budget equations. Mesic hardwood forests and pine flatwoods are not net sinks of run-in

(Sun 1995).

The geologic input to the forested wetland was estimated as 0.275 mm of

limestone erosion per year (Odum 1984). The amount of limestone eroded from the

interaction of acidic waters leaching through the underlying limestone creates and

maintains the wetland depression. The geologic input to shrub-scrub and marsh wetlands

was assumed to be proportional to infiltration rates compared to the forested wetland:

78% and 9% less than the estimated value of the forested wetland for the shrub-scrub and

marsh wetlands respectively. The geologic input to the floodplain ecosystem and the

mesic hardwood forest and pine flatwoods ecosystems was assumed to be equal to the

average limestone erosion of Florida, or 10 mm every 1000 years as estimated from







21

Odum (2000). The floodplain structure is also maintained by the constant work of the

stream channel and overbank flow, and the shape of stream channels and their floodplains

is related to stream power (Gordon et al. 1992). For this reason, the stream geopotential,

which describes a stream's erosive capacity, was also used to quantify the geomorphic

input to the floodplain ecosystem and was added to the geologic input necessary to

maintain the land support.

While five driving energies were evaluated, (sun, wind, rain, run-in and geologic

processes), these flows are all co-products of the world process. Therefore, globally the

emergy required for each is the same (Odum 1996). Adding the five driving energies

would erroneously result in double counting the emergy required to support the system.

In order to determine the driving emergy of a particular system, Odum (1996) suggests

using the largest of the geobiospheric inputs. Therefore, total driving emergy for the six

ecosystems was calculated to be the sum of transpiration (water use, rather than water

input) and geologic input, and river geopotential was also added to the floodplain forest.

Transpiration is the use of water for biological production while geologic inputs

result from the erosion of limestone built historically. Similarly, for the floodplainforest,

the work of stream geopotential over time contributes to the structure of the floodplain.

Geologic input of emergy can be added to present day annual emergy use without double

counting since the limestone that is eroded is geologic contribution from a geologic

storage built long ago.

Ecosystem Services. GPP was estimated from the literature by summing net

primary production (NPP) and community respiration. The annual emergy driving GPP

was taken as the sum of transpiration and geologic input (and river geopotential for the







22

floodplain forest). Rates of transpiration and infiltration were taken or estimated from the

literature and transformities were calculated as the weighted average of the transformities

of rainfall and run-in for all ecosystems.

Ecosystem Storages. Main storage evaluated included: biomass, peat or soil

organic matter, water, and geomorphic structure. The emergy of ecosystem storage was

calculated by multiplying the annual emergy required to make the storage by its turnover

time. Energy and/or mass values for each storage were obtained from the literature.

Geomorphic structure, the basin structure found in depressional wetlands and the

floodplain channels in riparian wetlands, is constantly maintained by the limestone

erosion beneath the depressions or by the constant work of the stream. This structure is

unique to the different types of wetlands, and indirectly supports wetland vegetation by

concentrating run-off into the depressional wetlands or the floodplain landform.

Basin structure was calculated based on the amount of eroded material in the

underlying limestone. Odum (1984) calculated that 1818 years are required to generate a

50 cm deep depression beneath cypress wetlands based on a 0.275 mm/year erosion rate

of limestone. The emergy of the basin structure, then, is the annual driving emergy

multiplied by 1818 years. Similarly, the emergy of shrub-scrub and marsh wetland basin

structure was calculated based on the amount of material eroded and the number of years

required.

Floodplain structure was calculated by estimating the mass of channel and levee

displaced (Figure 5). This was calculated by multiplying the volume of displaced

sediments by the bulk density of the sediments, or 1.2 g/cm3. Turnover time of the

floodplain was estimated as the time required for the stream channel to move across the







23

floodplain (Figure 6). This was estimated to be approximately 1000 years. The emergy

of this structure is therefore the annual driving emergy multiplied by the time required to

create the structure.

Mesic hardwood forests and pine flatwoods are not characterized by unique

structures such as basins or floodplain channels. The land support (structure) beneath

upland ecosystems is replenished yearly by equal rates of erosion and uplift. The same

land support exists beneath depressional wetlands and floodplain ecosystems, however its

contributions are negligible compared to the emergy needed to create wetland basin or

floodplain morphology. Therefore, the storage of land support was not calculated for the

upland ecosystems since the structure is not unique to those systems.

Calculation of Transformities

Transformities for driving energies of sunlight, wind, chemical potential energy of

rain, and geologic input were taken from Odum (1996). The transformity of stream water

(chemical potential) was taken from Buenfil (2000). The one remaining source, chemical

potential of run-in, was calculated by multiplying the transformity of rain by the

appropriate rain:run-in ratio for each ecosystem.

Transformities for ecosystems services of transpiration, infiltration, and gross

primary production (GPP) were calculated from the annual driving emergies. A weighted

average of rainfall and run-in was used to calculate the transformities for transpiration,

infiltration, and water storage, using the rationale that these flows are a mixture of the

two water inputs (Figure 7).

The emergy driving GPP was the sum of water used (transpiration) and geologic

input (as well as stream geopotential for the floodplain forest). The rationale of using
































10m


Channel Mass = Width Depth Length Sinuosity
= 10 m *2m* 100 m* 1.2
= 2400 m3
Levee Mass = 2 levees height *width length sinuosity
=2 0.3 m 2 m 100m 1.2
= 144 m3
Total Mass = 2544 m3
Bulk Density = 1.2 g/cm3
Mass = 3.05 E+9 g
Total driving emergy = Sum of transpiration, geologic input and river geopotential
= 3.97 E+15 sej/yr
Emergy/gram = (3.97 E+15 sei/vr *1000)
3.05 E+9
= 1.29 E+09 sej/g


Figure 5. Boundary of Floodplain Ecosystem (A), with cross-sectional dimensions
of channel and levees (B), and calculations of mass displacement (C).











(A)



FLOODPLAIN




I- - - - -~ --i
S1 he Atare of
U P Floodp ai Forest
UPLAND I



I UPLAND




Stream
Channel





(B)

Syrs 200 400 600 800 1000 yrs






Time >



Figure 6. Schematic of floodplain ecosystem structure showing the 1 hectare area
evaluated (A). The turnover time of the floodplain is illustrated in (B), where each
box represents a 200 year migration of the stream channel, completing the entire
cycle across the floodplain and back again in an estimated 1000 years.







26

both is that transpiration is required to drive biological processes and the limestone that is

eroded is geologic contribution from a geologic storage built long ago. Both the biologic

and geologic processes are coupled and are required for GPP. The transformity was

calculated as the sum of the annual water use and contribution from geologic input

divided by the energy of annual GPP.

Transformities for storage of the six ecosystems were calculated using the

emergy driving the systems, except for the transformity of water storage, which was

assumed to be a weighted average of rainfall and run-in (Figure 7). Live biomass was the

sum of all live above ground biomass including trees, shrubs and understory vegetation.

The transformity for biomass was calculated by multiplying annual emergy inputs (sum

of transpiration and geologic input) by the turnover time of the biomass, and

subsequently dividing by the energy of standing stock..

Soil organic matter results from the accumulation of un-decomposed plant matter.

Turnover time was calculated by dividing the organic matter storage by the accumulation

rate, which was derived by subtracting decomposition from litterfall (Dighe 1977).

Emergy of the peat storage was calculated as the annual emergy input to the ecosystem

multiplied by turnover time of the peat storage. Dividing the result by the energy content

of the soil storage yielded the transformity.

Transformity of basin structure in the cypress dome, shrub/scrub, and marsh was

calculated by dividing the emergy required to create the depression (annual emergy

inflow multiplied by time for development) by the mass of the displaced limestone. The

transformity of the floodplain structure was calculated using the same rationale, thus,
























= (Rain TRain) + (Run-in TRun-in)
J of water


Infiltration Transformity (Twi)
(Energy of Water)Tws)
J of water


-unlignt Transpiration Transformity (Twt)=
(Energy of Water Used )(Tws)
J of water








Figure 7. Diagram of transformity calculations for water stored, infiltration, and
transpiration.







28

Emdollar Evaluation

For comparative purposes and to provide units more familiar to the public,

emergy values were expressed as emdollars. Emdollars were calculated by dividing the

emergy value of environmental services and natural capital by the emergy/money

conversion ratio for the USA economy in 2000, which was equal to 0.96E+12 sej/$. The

emergy/money ratio for 2000 was obtained using methodology employed by Odum

(1996), and data from the U.S. Statistical Abstract (2001). The emergy money ratio is

calculated by dividing the total emergy used in driving the U.S. economy by the Gross

National Product (GNP) of the United States. Figure 8 shows emergy money ratios from

1980 to 2000. This ratio expresses the amount of emergy required per dollar of

circulation. By dividing emergy flows and storage of the ecosystems by the emergy

money ratio, the flows and storage are equated with the amount of currency they could

drive in circulation.

Emergy Evaluation of a Constructed Forested Wetland

Constructed wetland projects can be divided into three main stages: first, a

wetland ecologist with a consulting firm performs a preliminary site selection.

Elevations of the property and surrounding wetlands are surveyed to use as template for

the creation and design of the constructed wetland. Second, upon completion of the

necessary surveys and permitting paperwork, construction begins. The site is cleared of

the existing vegetation, excavated, contoured, and when the time and/or hydrology are

favorable, planted with desired vegetation. Lastly, several success criteria stipulated in

the permit application are monitored for an average of 3 years. Ecological data is

collected annually to ascertain compliance with the success criteria, and annual



















3.30

3.00

2.70

+ 2.40

2.10

S1.80

1.50

S 1.20

0.90

0.60


Year



Figure 8. Emergy per dollar (sej/$) of the United States from 1980-2000.
Values from 1980-1993 taken from Odum (1996), while from 1994-2000
calculated using data from the U.S. Statistical Abstract (2001) and the same
methods employed by Odum (1996).







30

monitoring reports are submitted to the appropriate agencies. Exotic and nuisance

species are manually removed or sprayed when needed. The mitigation site is considered

successful when the following parameters have been achieved:

1) 80% survival of planted trees

2) At least 80% cover of herbaceous species

3) Less than 10% cover of exotic and nuisance species

4) Hydrologic conditions that conform to those observed in adjacent natural

wetlands.

Data from a newly constructed forested wetland in North Florida were used to

evaluate the inputs necessary to create a wetland in order to calculate environmental costs

and benefits of wetland creation. The entire mitigation consisted of 5.26 ha of

constructed forested wetland and 2.4 ha of freshwater marsh. Only the forested wetland

was used for the evaluation since the marsh was not completed. Costs were prorated to

eliminate costs associated with marsh construction.

Extensive groundwork was done on site. Though the area was already several

feet below grade, elevation surveys revealed that even lower elevations were necessary to

support wetland vegetation with longer hydroperiods. Approximately 100,000 cubic

meters of fill were removed from the site and stock piled on a mound next to the created

wetland. No donor topsoil was laid in the forested wetland area. Instead, raised beds

were constructed to provide more aeration for the seedling root zone. Construction costs

for the forested wetland were approximately $122,000.

Vegetation planting occurred on January 21, 2002. The site was partially flooded

and soils were saturated. Sixteen people participated in the planting. Over 8,800







31

seedlings of eight different species were planted. Seedlings averaged 25 cm in height.

Fifty-six percent of seedlings were pond cypress, while the remaining 44% was shared by

blackgum, red maple, dahoon holly, white ash (Fraxinuspennsylvanica), silver bay

(Magnolia virginiana), sweetbay, and river birch (Betula nigra). Total plant costs were

approximately $4,600.

Figure 9 is a generalized systems diagram of a constructed wetland ecosystem

showing the main driving energies and purchased inputs from the economy that were

evaluated. Sunlight, wind, and rainfall were again taken as average values for North

Central Florida. Inputs from the economy included construction costs, imported

vegetation, fertilizer, and human labor. Additionally, environmental losses of natural

capital, such as biomass from the cleared vegetation and organic matter, were also added

to the costs of construction. Monitoring efforts extend approximately 3 years after

construction and planting, and include labor (monitoring and spraying) and material

(herbicide). Since this site was only recently completed, monitoring efforts were

estimated from other mitigation sites that have already been released.

Simulation Models

Forested Wetland Simulation Model

A simulation model was developed to analyze energy, emergy and transformity

values of a mature forested wetland. The model simulates successional trends in a

forested wetland, with particular emphasis on forest biomass and organic matter. In

addition to simulating energy flows, emergy and transformity values of biomass and

organic matter storage were also calculated.










































Figure 9. Systems diagram of a constructed forested wetland showing the
renewable energies and the economic inputs to the system as well as the loss of
soil organic matter and biomass resulting from excavation.







33

Tilley (1999) identified three rules for simulating emergy dynamics of ecosystem

storage. When the energy storage is increasing, the net accumulation of emergy is the

sum of all inputs minus the exports of "used" emergy. Unlike depreciation, which was

defined as a process necessary for the maintenance of the storage without subtraction of

emergy, exports carry away emergy with a transformity equal to that of the storage.

When the energy storage is decreasing, the emergy lost is equal to the energy exported

times its transformity. When energy stored is in steady-state, the accumulated emergy

remains the same.

Model Parameters and Calibration

Data from the literature were used to calibrate the model. Coefficient values were

calculated for the mature "steady-state" conditions, i.e. storage values are constants and

therefore inflows to a storage equal outflows from the storage at steady state. The energy

model simulates 400 years of forest growth. Emergy and transformity simulations of

biomass were run for 200 years, while the emergy and transformity of organic matter

were simulated for 2000 years.

In the baseline simulation initial biomass and organic matter values were set at

1% of their steady state values, while the nutrient storage was set at 10% of its steady

state value. Multiple simulations were run by setting the organic matter initial storage at

25%, 50%, and 90% of its steady state value.

Constructed Wetland Cost Recovery Model

A simple linear, cost recovery model was simulated for a newly constructed

wetland to calculate the time required for the ecosystem to recover the costs of

construction. Simulated GPP flows from the forested wetland model were converted to







34

emdollar flows and added to the negative values (costs) of construction and monitoring.

At time step 0, the simulation began with a negative value of 103,111 em$/ha, the

equivalent of construction costs. At time step 1, the first year GPP value from the

forested wetland model was added to the costs of construction, and the first year

operational costs of maintenance, 703 em$/ha, subtracted. The same methodology was

employed for years 2 and 3, while at year 4 only the GPP emdollars were added. Yearly

GPP values were taken from the simulation model so that beginning values were

relatively small and increasing with time to the steady-state values. The simulation was

run for 150 years.













RESULTS


Emergy Evaluation of Ecosystems

Energy, Emergy, and Transformity of Ecosystems

The emergy evaluation tables for the six ecosystems are given in Appendix B,

Tables 10 through 21. Details of calculations and data sources are given as footnotes to

each table. Emergy signatures for each ecosystem are shown in Figure 10. The emergy

signature of an ecosystem depicts the set of environmental energy flows on which its

processes and storage depend. The main driving emergy of the depressional wetland

ecosystems was geologic input. Geologic input to forested wetlands (Figure 10) is nearly

5 times the driving emergy of rain or run-in (5.5E+15 sej/ha/yr versus 1.17E+15 sej/ha/yr

respectively). Geologic input in the shrub/scrub wetland was only slightly higher than

rain or run-in (1.21E+15 sej/ha/yr versus 1.17E+15 sej/ha/yr and 1.18E+15 sej/ha/yr

respectively). Similar to the forested wetland, geologic input to the herbaceous marsh is

4.2 times the driving emergy of rain or run-in (4.95E+15 sej/ha/yr versus 1.17E+15

sej/ha/yr). River geopotential was the main driving emergy of the floodplain forest,

contributing nearly twice and 1.5 times the emergy of rain and run-in (2.2E+15 sej/ha/yr

versus 1.17E+15 and 1.49E+15 sej/ha/yr respectively). Geologic input to the floodplain

forest was very small (0.2E+15 sej/ha/yr) compared to the other wetland ecosystems.

The main driving emergy of the upland ecosystems was rain, which contributed nearly 6

times the emergy of geologic input in both the mesic hardwood forest and pine flatwoods














FORESTED WETLAND


7

6 6

5





2
0.4




3
0































1.4
1.2

































1.0
0




6

f5



.4


3


S42


1)


0





1.4

e 1.2

2 1.0

S0.8

S0.6


0.4

i 0.2

0.0


5.50









1.17 1.17

0.04 0.00

S W R RI G


HERBACEOUS MARSH


4.95










1.17 1.17


0.04 0.00

S W R RI G


MESIC HARDWOOD FOREST

1.17











0.20

0.04 0.00 0.00
S W R RI I
S W R RI G


1.5


' 1.2


o 0.9

-."
0.6


0.3


0.0




2.5


2.0


0 1.5


1.0


0.5


0.0





1.4

S1.

1.

0.

0.

0.

S0.

0.(


0.00


0.20

0.00


W R RI G


Figure 10. Emergy signature of six Florida ecosystems showing the

environmental inputs to the system. S = sun; W = wind; R = rain; RI = run-

in; G = geologic input; RG = river geopotential. Note the different scale on

each graph. Calculated from data in Appendix B, Tables 10-21.


SHRUB/SCRUB WETLAND


1.17 1.18 1.21











0.04 0.00


S W R RI G


FLOODPLAIN FOREST
2.20
-m


1.49

1.17






0.20
0.04 0.00


S W R RI RG G


PINE FLATWOODS
.


2

0

8

6

4

2


0










(1.17E+15 sej/ha/yr versus 0.2E+15 sej/ha/yr respectively).

A comparison across ecosystems showed that run-in and geologic input varied

considerably between wetland and upland ecosystems. Run-in was highest in the

floodplain forest (1.49E+15 sej/ha/yr), which receives its input from the adjacent stream,

while the upland ecosystems had no run-in. Geologic input was highest in the cypress

dome and herbaceous marsh ecosystems (5.5E+15 and 4.95E+15 sej/ha/yr respectively);

both had nearly 5 times the emergy than the shrub/scrub ecosystem (1.21E+15 sej/ha/yr)

and 25 times more than the floodplain forest and the terrestrial ecosystems (0.2E+15

sej/ha/yr).

Annual driving emergy of the six ecosystems is shown in Figure 11. Annual

driving emergy for the floodplain forest was the sum of transpiration, geologic input and

river geopotential, while for the other ecosystems it was the sum of transpiration and

geologic input. In all, the wetland ecosystems had between 3 and 9 times (range of

2.2E+15 and 6.17E+15 sej/ha/yr) the annual driving emergy of the terrestrial ecosystems

(range of 6.98E+14 and 8.74E+14 sej/ha/yr). A majority of this difference resulted from

differences in geologic inputs.

Ecosystem services of transpiration and infiltration are shown in Figure 12. The

emergy of transpiration for the floodplain forest (1.58E+15 sej/ha/yr) was approximately

twice the value of all other ecosystems. Infiltration was similar in the forested wetland

(0.76E+15 sej/ha/yr), herbaceous marsh (0.72E+15 sej/ha/yr), floodplain forest

(0.81E+15 sej/ha/yr), and mesic forest (0.46E+15 sej/ha/yr). However, it was

considerably lower for the shrub/scrub (0.17E+15 sej/ha/yr) and pine flatwoods




















7.00E+15
6.17
6.17 5.80
6.0E+15 -

.(CE+15 -
3.97
4. E+15-

|3.t+15 -
> 2.20
4.4UE+15 -

1.(E+15 874 6.98

0.00E+00 -









Figure 11. Annual driving emergy of six Florida ecosystems (sum of
transpiration, geologic input, and river geopotential for the floodplain
forest; sum of transpiration and geologic input for all other ecosystems).
Calculated from data in Appendix B, Tables 10-21.









6.0E+10
-5.0E+10
"4.0E+10
5 3.0E+10
~2.0E+10
S1.OE+10
O.OE+00




,3.0E+04
-.5E+04
:2.0E+04
c21.5E+04
~l.OE+04
05.0E+03
'b.OE+00


o .P a


rmr


nFl]


Transpiration
0 O Infiltration
I-










0 Transpiration
0 Infiltration
C,


7rhFn


.5
a
U
?o
,OF


0 Transpiration
2 []0 Infiltration


Figure 12. Transpiration and infiltration values of six Florida ecosystems.
(A) Power Density; (B) Solar Transformity; (C) Empower Density. See
Appendix B, Tables 10-21.


Cz0 Cz


. 8E+15
.5E+15
j.2E+15
.0E+14
.0OE+14
9.OE+14
.0E+00


I I~I I~ I ~I I~ I I~ I -










ecosystem (0.02E+15 sej/ha/yr). Transformity of transpiration and infiltration were

higher in the wetland ecosystems (mean of 26,887 sej/J) than in the terrestrial

ecosystems (18,199 sej/J), due to their lack of run-in.

GPP varied for the 6 ecosystems (Figure 13). The floodplain forest (3.21E+12

J/ha/yr) was twice as productive as the forested wetland (1.54E+12 J/ha/yr), and these

two ecosystems had considerably higher energy values than all other ecosystems (average

of 5.46E+1 1 J/ha). Transformity of GPP varied between 0.96E+3 and 14.4E+3 sej/J, and

it was 7 times higher in the wetland ecosystems than upland ecosystems (mean of 7.0E+3

and 1.0E+3 sej/J respectively). The forested wetland had the highest GPP emergy

(6.17E+15 sej/ha/yr).

Emergy storage of biomass (Figure 14) were nearly an order of magnitude higher

in forested wetlands (cypress and floodplain forest) than in forested uplands (average of

23.4E+16 sej/ha in wetlands and 2.6E+16 sej/ha in uplands). While the floodplain forest

had slightly higher biomass energy storage (3.3E+12 J/ha) than the forested wetland

(2.9E+12 J/ha), once the energy storage were multiplied by their respective transformity,

the forested wetland had approximately twice as much stored emergy than the floodplain

forest (3.09E+17 versus 1.59E+17 sej/ha respectively). The herbaceous marsh had the

lowest emergy storage of biomass (8.7E+15 sej/ha). Transformity of biomass ranged

from a high of 10.7E+4 sej/J in the forested wetland to a low of 9.9E +3 sej/J in the pine

flatwoods.

Organic matter storage (Figure 15) was greatest in the herbaceous marsh (9680

E15 sej/ha) and smallest in the pine flatwoods (27 E15 sej/ha). Storages of organic

matter were over fifteen times larger in the wetland ecosystems (49E+16 sej/ha) than in












4.00E+12


43.00E+12


2.00E+12


l.00OE+12 -


0.00E+O ,00









4.50E+04 -
,2.OOE+04 -


S.00E+03
u P4OE O , u ,












8.00E+15


.&6.00E+15


4.00E+15


2.OOE+15

O.OOE+00
.--
Cr 2 2





















Figure 13. GPP values of six Florida ecosystems. (A) Power Density;
(B) Solar Transformity; (C) Empower Density. See Appendix B,
Tables 10-21.
Tables 10-21.











3.5E+12

3.0E+12

S2.5E+12
-c
22.0E+12

|1.5E+12

S1.OE+12

5.0E+11 -

O.OE+00
-e


i


1.2E+05

1.OE+05 -

OE+04

.05E+04 -

OE+04 -

.0E+04 -

O.OE+00 ----
-e -e






32.0E+17
23.5E+17

32.OE+17


31.5E+17

1.OE+17 -

5.0E+16 -

O.OE+ 00

a)




Figure 14. Biomass values of six Florida ecosystems. (A) Energy;
(B) Transformity; (C) Emergy. See Appendix B, Tables 10-21.











1.2E+13
1.OE+13
8.0E+12
& 6.0E+12
S4.0E+12
2.0E+12
O.OE+00


H


O- 0
F-I F-
Cz


-e
0,
0


3 3.0 03 C "JS-
lz Is 4 *a ^'a s
00 0
B E>o h^
CA
0 Cz U
U0


-e-e0 -0 0S a S
^.is 33 a aM"t
""^ r^ CS^ a "0
_aa E ]
-o
F4 O 7F
1


Figure 15. Organic matter values of six Florida ecosystems. (A) Energy;
(B) Transformity; (C) Emergy. See Appendix B, Tables 10-21.


H


1.4E+05
1.2E+05
' 1.OE+05
.z8.0E+04
26.0E+04
4.0E+04
2.0E+04
O.OE+00


1.2E+18
1.OE+18
8.0E+17
6.0E+17
4.0E+17
2.0E+17
0.OE+00










the terrestrial ones (3.2E+16 sej/ha). Transformity of organic matter ranged from a high

of 12.3E+4 sej/J in the forested wetland to a low of 1.91E+4 sej/J in the mesic forest.

Soil water is a function of the amount of organic matter in the system. The

storage of water in the wetland ecosystems was assumed to be the water content of the

peat soil plus the average standing water in the wetland (estimated as half the wetland

depth). Differences of more than two orders of magnitude exist in emergy values of

water storage (Figure 16) between the wetland and terrestrial ecosystems (5.9E+14

sej/ha and 4.4E+12 sej/ha respectively). Transformity of water storage and flows

(transpiration and infiltration) in the wetland ecosystems was calculated as the weighted

average of the inputs of rainfall (1.82E+4 sej/J) and run-in (from 4.6E+4 to 5.2E+4 sej/J).

Geologic structure (Figure 17), the result of thousands of years of geologic work,

was the highest emergy storage in each of the wetland systems, and ranged from 11.2

E18 sej/ha in forested wetlands to 3.97E18 sej/ha in floodplain forests. Transformity of

geologic structure (emergy per gram of material eroded to create the basin or channel)

ranged from 1.12E+9 sej/g for forested wetlands to 1.8E+9 sej/g for the shrub/scrub

ecosystem.

Emdollar Values of Ecosystems

Representative emdollar values of ecosystem services and natural capital for each

ecosystem are given in the last column of each of the evaluation tables (Appendix B,

Tables 10-21) and summarized in Tables 1 and 2.

Ecosystem services of transpiration, infiltration, and GPP are given in Table 1.

Total ecosystem services, represented by GPP only to avoid double counting, ranged












4.80E+10
4.00E+10

E 3.20E+10
( 2.40E+10
a 1.60E+10

8.00E+09

0.00E+00


3.0E+04

2.5E+04

S2.0E+04

S1.5E+04

S1.OE+04

5.0E+03

O.OE+00


n N


-a a
c C
co _


1.2E+15

1.OE+15



.OE+14
.4.OE+14



2.0E+14

O.OE+00 ---

3a-e




Figure 16. Soil water values of six Florida ecosystems. (A) Energy;
(B) Transformity; (C) Emergy. See Appendix B, Tables 10-21.


Q;40


.2


^a
.- C)
t<<
ns












1.2E+10


1.OE+10


8.0E+09


6.0E+09


4.0E+09


2.0E+09


O.OE+00


Forested Wetland Shrub/scrub Marsh Floodplain forest


2.0E+09


1.6E+09

'C
1.2E+09


8.0E+08


4.0E+08


O.OE+00


Fnrostecl Wetlnncl


Shnih/senimh


lfnrqsh


Flnnclnlain fnrest


1.2E+19


1.OE+19


S8.0E+18


6.0E+18 -


4.0E+18 -


2.0E+18


0.OE+00 -
Forested Wetland Shrub/scrub Marsh Floodplain forest


Figure 17. Geologic structure of four wetland ecosystems. (A) Energy;
(B) Transformity; (C) Emergy. See Appendix B, Tables 10-21.


I I I I I










Table 1. Summary of emdollar values of environmental services of six Florida
ecosystems.



Ecosystem Type Transpiration Infiltration GPP
(em$/ha/yr)

Forested Wetland $701 $787 $6,430
Shrub/Scrub Wetland $1,034 $177 $2,295
Freshwater Marsh $887 $754 $6,043
Floodplain Forest $1,642 $841 $4,140
Mesic Hardwood Forest $702 $479 $911
Pine Flatwoods $519 $18 $727

(See Appendix B, Tables 10-21)










from 6,430 em$/ha/yr in forested wetlands to 727 em$/ha/yr in pine flatwoods. Wetland

ecosystems contribute almost six times the environmental services of upland ecosystems

(averages of 4,727 and 819 em$/ha/yr, respectively).

Emdollar values of ecosystem storage (Table 2) ranged from 12.6 million

em$/ha/yr for forested wetlands to 49,819 em$/ha/yr for pine flatwoods. This significant

difference in value is due to the large contribution of geologic structure to the wetland

ecosystems. Geologic structure accounted for as much as 93% of total emdollar values.

Without the geologic structure, herbaceous marshes had the highest emdollar value of

1,018,641 em$/ha. After subtracting geologic structure, organic matter (peat) accounted

for nearly 99% of herbaceous marsh value.

Organic matter had the second largest emdollar value in the four wetland

ecosystems, and it was the highest contribution of upland ecosystems. Organic matter

ranged from over 1,000,000 em$/ha in herbaceous marshes to 28,000 em$/ha in pine

flatwoods. Organic matter accounted for, on average, 56% of total stored value in pine

flatwoods and mesic forests.

The range of emdollar values for live biomass was relatively large. The emdollar

value of forested wetland biomass was about 35 times as large as that of a typical marsh

wetland (321,510 and 9,065 em$/ha/yr respectively). The floodplain forest biomass

storage value was the second highest at 165,582 em$/ha, with shrub/scrub, mesic forest

and pine flatwoods following at 45,896, 27,321, and 18,698 em$/ha/yr respectively.

Finally, the emdollar values of stored water were the lowest of the four storage

evaluated, accounting for less than 1% of total stored values.















Table 2. Summary of emdollar values of natural capital (above ground biomass, organic matter, soil water and geologic structure)
of 6 Florida ecosystems.

Ecosystem Type Live Biomass Organic Matter Water Geologic Structure Total Without Structure
(em$/ha)

Forested Wetland $321,510 $566,304 $511 $11,690,095 $12,578,420 $888,325
Shrub/Scrub Wetland $45,896 $237,184 $206 $11,379,949 $11,663,235 $283,286
Freshwater Marsh $9,065 $1,008,438 $1,139 $6,104,113 $7,122,754 $1,018,641
Floodplain Forest $165,582 $240,376 $618 $4,139,553 $4,546,129 $406,576
Mesic Forest $31,875 $39,030 $5 $0 $70,909 $70,909
Pine Flatwoods $21,814 $28,000 $4 $0 $49,819 $49,819

(See Appendix B, Tables 10-21).










Replacement Values of Ecosystems

Table 3 summarizes the estimated replacement values of each ecosystem

assuming complete elimination. The environmental services lost are calculated as the

annual services (GPP) times half the recovery time of the newly constructed ecosystem

(assuming construction of new wetlands to replace those destroyed). This was done to

reflect that as a newly constructed wetland matures some services are replaced annually

until a mature system has developed. Recovery times were estimated to be 60 years for

forested wetland and floodplain forest, 50 years for mesic forest, 40 years for pine

flatwoods, and 16 and 4 years for shrub/scrub and marsh wetlands, respectively. The

value of ecosystem structure (natural capital) that is destroyed is equal to the sum of

biomass, peat and water, as shown in Table 3. The storage value of geologic structure

was not included in the totals for natural capital since elimination of a wetland does not

eliminate the underlying geologic structure (see Figure 1). The total calculated

replacement values ranged between 1,081,230 and 64,362 em$/ha.

Emergy Evaluation of a Constructed Forested Wetland

Emdollar costs of one hectare of constructed wetland are shown in Table 4. The

table is divided into four sections: renewable energy sources, purchased goods and

services, environmental losses, and longterm monitoring efforts. Footnotes to each item

appear in the following pages. Items 1-3 are the renewable energies that contribute to the

system. These are also called "free" inputs as no money (dollars) circulates to pay for

those services, and they are the same contributions evaluated in the six Florida

ecosystems (Tables 10-21). Items 4-11 are the economic contributions to the













Table 3. Summary of replacement values per hectare assuming complete elimination
of wetland ecosystem.


Ecosystem Type


Environmental Services(a) Natural Capital(b) Total value(c)
(Em$/ha)


Forested Wetland $192,906 $888,325 $1,081,230
Shrub/Scrub Wetland $18,358 $283,286 $301,645
Freshwater Marsh $12,086 $1,018,641 $1,030,727
Floodplain Forest $124,187 $406,576 $530,763
Mesic Forest $22,768 $70,909 $93,677
Pine Flatwoods $14,543 $49,819 $64,362



(a) Replacement value of environmental services is the emdollar value of GPP over 1/2 recovery time.
Estimate 60 years for both cypress and floodplain forest, 16, and 4 years for shrub/scrub, and marsh
systems respectively, 50 years for mesic hardwood forest and 40 years for pine flatwoods.
(b) Replacement values of natural capital are the sum of storage in each ecosystem. The loss of basin
structure was not considered.
c) Total replacement value is the sum of environmental services and natural capital.












Table 4. Emergy evaluation of the inputs to construct a forested wetland in Florida (J/ha).


Note Item Data Units Transformity Solar Emergy Em$ Value*
(sej/unit) (E+15 sej) (2000 em$)
Renewable Energy Sources
1Sun 4.19E+13 J/yr 1 0.04 $44
2Wind 2.96E+09 J/yr 1496 0.004 $5
3Rain, chemical potential 6.42E+10 J/yr 18199 1.17 $1,217
Total Renewable Energy (taken as largest to avoid double counting) $1,217
Purchased Goods and Services
4Construction services 2.33E+04 $ 1.12E+12 26.08 $27,170
Vegetation Planting
5 Biomass 8.39E+07 J 40000 0.00 $3
6 Cost $870 $ 1.E+12 0.83 $870
Fertilizer
7 Active ingredients 6.68E+03 g 2.80E+09 0.02 $19
8 Cost $102 $ 9.60E+11 0.10 $102
Labor
9 Planting 3.06E+07 J 2.5E+07 0.75 $783
10 Planning and permitting 5.54E+07 J 7.3E+07 4.06 $4,229
11 Costs $4,125 $ 9.6E+11 3.96 $4,125
Environmental losses
12Biomass 2.53E+12 J 1.2E+04 30.60 $31,875
130rganic Matter 1.96E+12 J 1.9E+04 37.47 $39,030
Total Goods and Services and Environmental Losses (Items 4, 6, 8, 9, 10, 12,
13) $103,111
Longterm monitoring efforts
14Chemicals (Herbicides) $64 $ 9.60E+11 0.06 $64
Labor
15 Spraying 1.15E+07 J 2.5E+07 0.28 $294
16 Monitoring 2.29E+07 J 7.3E+07 1.68 $1,750
Total $2,108
Per year $703


* em$ = solar emergy in column 6 divided by 0.96E+12 sej/$ for U.S. in 2000.












Notes to Table 4.
RENEWABLE ENERGY SO URCES
1SOLAR INSOLATION (assume 1 year of sunlight)
Area of wetland = 1.00ha
Mean Net Radiation = 274Ly (Henning 1989)
=(1.0E+04 m2/ha)(274 Ly)(10 Cal/m2/Ly)(4186 J/Cal)(365 days)
= 4.19E+13J/ha/yr


Transformity =
2WIND (assume 1 year of wind)
Area=
Density =
Drag. Coefficient =
Av. Annual Velocity =
Geostrophic wind =


Transformity =1,496


defined as 1 (Odum 1996)


1.00E+04 m2
1.3 Kg/m3
=1.00E-03
1.16 mps


(Odum 1996)
(Jones et al. 1984)


1.93 (observed winds are about 0.6 of geostrophic wind)
=(area)(density)(Drag Coeff.)(velocity)3(3.15E7 sec/yr)
=2.96E+09 J/ha/yr


sej/J (Odum 1996)


3RAIN, CHEMICAL POTENTIAL (assume 1 year of rain)
Area =1.00E+00 ha


Rainfall =1.3
Gibbs Free Energy =4.94


m/yr


(NOAA 1985)


=(1.00E+04 m2/ha)(1.3 m)(4.94 J/g)(1.00E+06 g/m3)
= 6.42E+10J/ha/yr
Transformity = 18,199
PURCHASED GOODS AND SERVICES


(Odum 1996)


CONSTRUCTION SERVICES
Six weeks of earthwork for entire site (7.66 ha: 5.26 ha of forested wetland and 2.4 ha of freshwater
marsh) using the following equipment: 5 pans, 3 dozers, 1 backhoe, 2 trucks, and 1 motor grader.
Total cost of construction (including labor) was approximately $175,000. Cost for forested area
(70% of total area) approximately $122,500, or $23,289/ha.
Cost = 23,289$/ha
Transformity = 9.60E+llsej/$
VEGETATION BIOMASS

Planting for forested wetlands occurs on 7-10 foot centers. 8 tree species were planted at this site:
Taxodium ascendens, Nyssa aquatica, Acer Rubrum, Persea palustris, Magnolia virginiana, Betula
nigra, Ilex cassine, and Fraxinus americanus. Total number of tree seedlings was 8790.


Number of seedlings


8790seedlings


Average dry weight/seedling = 3g
Biomass =(3 g/seedling)(8790 seedlings)(4 kcal/g)(4186 J/kcal)/5.26 ha
= 8.39E+07J/ha
Transformity = 4.00E+04sej/J (estimate)












Notes to Table 4 continued.
VEGETATION COST
Cost of seedlings only was $4574.
Cost =870 $/ha
Transformity =9.60E+11 sej/$ (Odum 1
FERTILIZER, ACTIVE INGREDIENTS
The slow release fertilizer "Agriform" was applied to each hole in which a seedling was planted.
One 10 g tablet for each seedling. Main ingredients are: 20% Total N, 10% Phosphoric Acid
(P205), 5% soluble Potash (K20), 2.8% Ca, 2% Na, .5% Fe, .5% Mg, and binding agents.
Fertilizer =(10 g/seedling)* 8790 seedlings/5.26ha
=16711 g
Active Ingredients =6684 g (40% of mass)
Transformity =2.80E+09 sej/g (weighted ave., Lagerberg and Brown 1
FERTILIZER, COST
Agriform: 1 box (1000, 10g tablets) = $61. No. of boxes for this site: 8.8. Total cost $537, or
$102/ha.


Cost =102
Transformity =9.60E+11


$/ha
sej/$


(Odum 1996)


HUMAN LABOR
9HUMAN LABOR, PLANTING: 16 people for 1 day (8 hours).
Combined days of work= 16 days
Human Input=(16 days)(2,400 kcal/day)(4186 J/kcal)/5.26ha
= 3.06E+07J/ha
Transformity = 2.46E+07sej/J


(Odum 1996)


10HUMAN LABOR, PLANNING AND PERMITTING: Surveying, Planning, Permitting and
Monitoring. Pre-construction = 6 days; design = 8 days; construction oversight = 15 days.


Combined days of work
Human Input=



Transformity =
11HUMAN LABOR, COSTS
Total Costs for forested wetland
Per hectare =
Transformity =


29days
=(29 days)(2,400 kcal/day)(4186 J/kcal)
S2.91E+08J/5.26 ha
S5.54E+07J/ha
S7.33E+07sej/J


$21,700$/5.26 ha
$4,125$/ha
9.6E+11lsej/$


996)


999)


(Odum 1996)


(Odum 1996)












Notes to Table 4 continued.
ENVIRONMENTAL LOSSES
12BIOMASS
Assume construction site was historically a mesic hardwood forest. Biomass structure taken from
Table 19 in this study.

130RGANIC MATTER
Assume construction site was historically a mesic hardwood forest. Organic matter structure taken
from Table 19 in this study.

LONGTERMMONITORING EFFORTS

14CHEMICALS
Rodeo herbicide for aquatic conditions is used to spray exotic species. Based on 2 spray events/year
for 3 years of monitoring for a total of 6 events. 2.5 gallons at $337.
Chemicals= 64$/ha (Forestry Suppliers catalog)
Transformity = 9.60E+11sej/$ (Odum 1996)


LABOR
150ne person spraying for 1 day for each event. Two spray events per year for 3 years.
Combined work days= 6days
Labor-(6 days)(2,400 kcal/day)(4186 J/kcal)/5.26 ha
= 1.15E+07J/ha
Transformity = 2.46E+07sej/J
16Monitoring: 2 person 2 days/year for 3 years.
Work days = 12days
Labor =(12 days)(2,400 kcal/day)(4186 J/kcal)/5.26 ha
= 2.29E+07J/ha
Transformity = 7.33E+07sej/J


(Odum 1996)


(Odum 1996)










construction of a wetland. Construction services make up approximately 84% of total

purchased goods and services. Emdollar values of the other economic inputs (vegetation,

fertilizer and labor) were calculated both on the basis of the dollar spent and the energy

contributed. In the case of vegetation and fertilizer, the emergy contributed by the actual

products was much smaller than the price paid for it. Items 12 and 13 represent the loss of

natural capital (biomass and organic matter) of the ecosystem previously present on the

constructed site. Wetlands are usually built on degraded uplands, therefore the values of

biomass and organic matter for the mesic hardwood forest ecosystem were used to

quantify those losses. When tabulating total emdollar costs, only items 4, 6, 8, 9, and 10,

12, and 13 were added to avoid double counting. Total construction costs were 103,111

em$/ha/yr. Environmental losses were almost 70% of total costs, with construction

services accounting for 26%. Labor costs were about 4% of total costs, while vegetation

and fertilizer accounted for the remainder.

Following construction, the created wetland is monitored for approximately 3

years. Total longterm monitoring efforts were equal to 2,108 em$/ha, or 703 em$/ha/yr.

Labor accounts for 96% of those costs, while herbicides account for the remainder.

Simulation Models

Forested Wetland Simulation Model

Figure 18 is a system diagram of the ecosystem flows and storage included in the

simulation model. The system boundary of the model is one hectare of forested wetland.

Main driving energies of this ecosystem are sun, rain, run-in, and geologic input. Main

ecosystem storage are soil water, biomass, organic matter, and nutrients. Nutrients are

modeled as a storage rather than a flow through the system since in forested wetlands






























+infiltration


Figure 18. Systems diagram of the forested wetland simulation model showing energy flows and storage evaluated.










nutrient turnover is tightly linked to biomass and organic matter turnover. Table 5

presents the mathematical equations and flow values used in the model, as well as the

notes to those calculations. Table 6 provides the values used for each storage and the

calibrated coefficients. Emergy and transformity of biomass and organic matter were

calculated using formulas in Figure 19 and 20.

Energy, Emergy and Transformity of Forested Wetland Model

Figure 21 shows the simulation results of biomass and organic matter storage in

the forested wetland model. Biomass grew at a faster rate than organic matter and

reached 90% (2.61E+12 J/ha) of its maximum (2.9E+12 J/ha) after 165 years. Organic

matter had much slower growth and reached 90% (3.98E+12 J/ha) of its maximum

(4.42E+12 J/ha) by year 386.

Simulated emergy and transformity of biomass are given in Figure 22. While

emergy values increase steadily from time 0, transformity values start out extremely high

(1.9E+5 sej/J) and keep increasing for the first 11 years to a maximum of 1.14E+6. At

year 12 they begin decreasing steadily until they reach steady state by year 924 at 4.3E+4

sej/J. Emergy of biomass storage reached steady state of 1.25E+17 sej/ha by 421 years.

Organic matter emergy and transformity values peaked around year 1700 (Figure

23). Transformity of organic matter rapidly increased until year 29 to a value of 3.15E+5

sej/J. Between year 29 and year 164, transformity decreased slightly to 7.88E+4 sej/J,

and then began ascending until it leveled off by 1700 years at a value of 1.3E+5 sej/J.

Emergy of organic matter reached a maximum value of 5.77E+17 by 1880.

Increasing the organic matter storage to 25%, 50%, and 90% of its steady state

value had a considerable effect on biomass storage growth (Figure 24), but did not result












Table 5. Storage and internal flow equations for the forested wetland simulation
model.

Note Symbol Equation Value Definition


Storage Equations
dB = J -J2 J3 J4
dOM= J5- J6- J7
dN =J8 +J9+J1o+Jl J12-J13
dSW = Rain + Run-in- J J15 J16


Item Internal Flows
1 R
2 Jo
3 Ji
4 J2
5 J3
6 J4


Item
20
21
22


I/(I+Ko*SW*B*N*G)
kO*SW*B*N*G*R
kl*SW*B*N*G*R
k2*B
k3*B
k4*B
k5*B
k6*OM
k7*OM
k8*B
k9*OM
kio*Rain
kl *Run-in
kl2*N
kl3*SW*B*N*G*R
kl4*SW*B*N*G*R
ki5*SW
kl6*SW
kl,*SW*B*N*G*R


Constant Flows
Rain
Run-in


4.19E+12
4.19E+13
2.05E+11
7.72E+10
6.63E+10
6.15E+10
3.86E+10
1.27E+10
2.59E+10
7.44E+05
3.84E+05
3.99E+05
4.70E+05
4.99E+05
1.50E+06
2.57E+10
3.49E+10
2.88E+10
1.34E+12


6.42E+10
2.52E+10
5.50E+06


Remaining Sunlight
Sunlight Received by Trees
Net Primary Production
Litterfall
Exported Biomass
Biomass depreciation
Litter Accumulation
Exported OM
OM Depreciation
Nutrients from Litter Decomposition
Nutrients from OM depreciation
Nutrients in Rain
Nutrients in Run-in
Exported Nutrients
Nutrient uptake by Trees
Transpiration
Evaporation
Runoff & Infiltration
Respiration


Rain input to the system
Run-in input to the system
Geologic Input















Notes and calculations to flow values in Table 5.


1Remaining Sunlight
Estimated as 10% of Sunlight
2Sunlight Received by Trees
3Net Primary Production
4Litterfall
Litterfall
Energy


Table 10
Table 10


461g/m2/yr (Deghi 1977)
=(461 g/m2/yr)(1.0E+04 m2/ha)(4 Cal/g)(4186 J/Cal)
= 7.72E+10J/ha/yr


5Exported Biomass
Calculated as NPP Litterfall Biomass depreciation
Exports = 6.63E+10J/ha/yr


6Biomass depreciation
Approximately
7Litter Accumulation
Organic matter from litterfall
8Exported OM


30%of NPP

50%of litterfall


OM in percolating waters = 100g/m3 (Odum 1984)
=(100 g/m3)*(.584 m)*(1E+4 m2/ha)(5.2 Cal/g)(4186 J/Cal)
= 1.27E+10J/ha/yr
90M Depreciation
Calculated as OM from litter Exported OM
10Nutrients from Litterfall Decomposition
P in litter = 0.84mg/g dry weight (Brown 1978)
=(.84 mg/g)(461 g/m2/yr)*(50% decomp.)*(1E+4 m2/ha)
*(1E-3 g i n-, i x4 J/g)
= 7.44E+05J/ha/yr
11Nutrients from OM depreciation
P from OM = P concentration in depreciation OM
OM Depreciation = 2.59E+10J/ha/yr
= 1.19E+06g/ha/yr
P in OM = 0.84 mg/g dry weight (assume same as litterfall)
P from OM = 3.84E+05J/ha/yr
12Nutrients in Rain


P in rain = 0.08g/m3
Rain =(1.3 m)(1E+4 m2/ha)(0.08 g/m3)
1040g/ha/yr
P in rain =(1040 g P)(384 J/g)
= 3.99E+05J/ha/yr


(Brown 1978)


(Deghi 1977)












Notes and calculations to flow values in Table 5 continued.

13Nutrients in Run-in


P in rn-in=


0.24g/m3


(Brown 1978)


Run-in =(.51 m)(lE+4 m2/ha)(.24 g/m3)
P in run-in = 1224g/yr
=(1224 gP)(384 J/g)
= 4.70E+05J/ha/yr
14Exported Nutrients
EXPORTED P = Balance J8 + J + J10 + J11- J13
15Nutrient uptake by Trees


P uptake by Biomass


16Transpiration
17Evaporation


= 0.39g P/m2/yr
= 1.50E+06J/ha/yr
Table 109


(Brown 1978)


From water balance
Rain + Run-in = Transpiration + Evaporation + Runoff&Infil
= 3.49E+10J/ha/yr
18Runoff&Infil Table 10
19Respiration Table 10
20Rain input to the system Table 10
21Run-in input to the system Table 10
22Geologic input Table 10








62






Table 6. Steady-state values of the storage and calibrated coefficients for the
forested wetland simulation model.


Symbol


Storages
B
OM
N
SW


Value


=2.90E+12
=4.42E+12
=6.37E+07
=1.87E+10


Coefficients


4.73E-37
2.57E-39
2.66E-02
2.29E-02
2.12E-02
1.33E-02
2.88E-03
5.86E-03
2.56E-07
8.68E-08
6.22E-06
1.87E-05
7.83E-03
1.88E-44
3.23E-40
1.87E+00
1.54E+00
1.52E-38



















Rain used =
I ,u i u , ,, i


Transpiration Emergy 1i ... i ,,
(Energy of Transpiration)(Tws)


Input Emergy (Geoem) =
s of Geo input)(Tgeo)










Emergy in Exported Biomass =
J I (Energy of Biomass Exported)(TB)


Ts = 26202 sej/J Tgeo = 1.00E+9 sej/g
Emergy of Biomass (Bem)= J6 Tws) + (G Tgeo) (J2 TB) (J3 TB)
= [(k6*SW*B*N*G*R Tws)] + [(G Tgeo)] [(k2 B) TB]- [(k3 B) TB]

Transformity of Biomass (TB) = Emergy of Biomass
Energy of Biomass






Figure 19. Emergy system diagram showing calculations of emergy and
transformity of biomass in the forested wetland simulation model.





















Emergy in Litterfall =
(Energy of Litterfall)(TB)


- Decomposition


Decomposition = 50% of Litterfall


Emergy in Exported OM =
(Energy of ExportedOM)(TOM)


Emergy of Organic Matter (OMem) = Accumulationem ExOMem
=(J5 TB)- (J6 TOM)
=[(k5* B) TB]- [(k5 OM) TOM]

Transformity of Organic Matter (TOM) = Emergy of Organic Matter (sei/J)
Energy of OM (J)






Figure 20. Energy diagram showing calculations of emergy and transformity
of organic matter in the forested wetland simulation model.

















5.E+12


4.8E+12


S4.E+12 -Organic Matter 4.2E+12
3.6E+12

D 3.E+12 Biomass 3.0E+12
2.4E+12 I
. 2.E+12 -
1.8E+12

S1.2E+12
O 1.E+12 -1.2E+12
6.0E+11

O.E+00 O.OE+00
0 100 200 300 400

Time, yr


Figure 21. Simulation results of the forested wetland model showing time
series of forest biomass and organic matter storage.


















2.E+17 1.2E+06

Emergy
Ergy 1.0E+06
1.E+17 .OE+0

F \ 8.0E+05
'& 9.E+16 -
> 6.0E+05
6.E+16
S\- 4.0E+05

3.E+16
2.0E+05
Transformity 2.E+05

O.E+00 O.OE+00
0 50 100 150 200

Time, yr


Figure 22. Emergy and transformity of forest biomass storage in forested
wetland model.



















6.E+17

5.E+17

4.E+17

3.E+17

2.E+17

1.E+17

O.E+00


2.0E+05


1.6E+05


1.2E+05


8.0E+04


4.0E+04


0.OE+00


0 300 600 900 1200 1500 1800
Time, yr

Figure 23. Emergy and transformity of organic matter storage in forested
wetland model.










in any changes to emergy and transformity of biomass. The 25%, 50%, and 90% increase

resulted in biomass reaching 90% of its steady state within 141,119, and 98 years,

respectively, instead of the 165 years required in the baseline simulation. Setting organic

matter to 25% and 50% of its steady state value enabled the organic matter storage to

reach 90% of its steady state value in 360 and 328 years, respectively, instead of the 386

years necessary in the baseline simulation (Figure 25).

Constructed Wetland Cost Recovery Model

Emdollar GPP flows for the forested wetland model are shown in Figure 26. GPP was

calculated by adding NPP (J1), and respiration (J17). In the forested wetland model, GPP

grows rapidly until year 50, after which growth is much slower and it begins to level off

around 6.0E+3 em$/ha/yr at 214 years. Figure 26 depicts the recovery time of a

constructed wetland ecosystem. At time 0, the ecosystem has a negative balance of

103,11 lem$/ha. Though the ecosystem begins to recover some of its initial costs with

the addition of GPP, its balance is lower by year one because of the monitoring costs.

The lowest balance occurs at year 3 (-105,000 em$/ha) with the last installment of

monitoring costs. Then, the ecosystem begins to recover and as it matures more GPP

services are added each year. The value of ecosystem services of GPP equals the costs of

construction by year 54. At this time the ecosystem has paid off its debt and begins

accruing positive value.

Increasing the baseline organic matter storage to 25%, 50% and 90% of its

maximum had considerable effects on GPP rates and thus recovery time (Figure 27).

Additionally, increasing the baseline organic matter storage also translated into decreased

environmental losses, and thus decreased construction costs. Mesic hardwood













3.OE+12


2.5E+12


2.OE+12


v 1.5E+12
1 = Baseline, OM=1%
S--OM=25%
1.OE+12 / -~ OM=50%
OM=90%
5.OE+11


O.OE+00
c-I -r \C oO O cl 't \C CO

Time, year



Figure 24. Simulation results of biomass energy storage after increasing initial
organic matter storage to 25%, 50% and 90% of its steady state value, showing
increased growth rates as the initial organic matter value increases.













4.5E+12


4.0E+12

3.5E+12

3.0E+12

S2.5E+12

2.0E+12
S.+12 Baseline, OM=1%
S1.5E+12M -2
-OM=25%
1.0E+12 OM=50%

5.0E+11 -

O.OE+00
0 50 100 150 200 250 300 350

Time, year



Figure 25. Simulation results of organic matter energy storage after increasing
initial organic matter storage to 25% and 50% of its steady state value,
showing increased growth rates of organic matter.











7.0E+03


6.0E+03


5.0E+03


= 4.0E+03


-3.0E+03


2.0E+03


1.OE+03


O.OE+00
m t Tiie, year 0 n F t


6.0E+05


5.0E+05


4.0E+05


3.0E+05


S2.0E+05


1.OE+05


O.OE+00
C0 00 0C C C C C C C C C C C C

-1.OE+05


-2.0E+05 Time, year

Figure 26. Simulation of (A) GPP emdollar value and (B) recovery time
needed to payback construction costs (calculated by adding yearly GPP to
initial debt).










forests have approximately half of the organic matter of forested wetland (Appendix B,

Table 11 and 19). Therefore, if the organic matter starts off at 25% of its steady state

value in the simulation model, then initial construction costs amounted to 83,600 em$/ha

(the original 103,11 lem$/ha minus 19,115 em$/ha, or 50% of organic matter of mesic

hardwood forests). In this scenario, ecosystem services of GPP equal construction costs

by year 48 (Figure 27). Similarly, increasing the organic matter storage to 50% in the

simulation model resulted in construction costs of 64,081 em$/ha (original 103,111

em$/ha minus 39,030 em$/ha, or approximately 100% of organic matter value of mesic

hardwood forests) and a recovery time of 42 years (Figure 27). Finally, if additional

organic matter is imported from other sources to equal 90% of the forested wetland

steady state value, construction costs remain at 64,081 em$/ha, but GPP slightly increases

to yield a recovery time of 40 years (Figure 27).











(A)
7.E+03

6.E+03

5.E+03

4.E+03

S3.E+03- Baseline, OM=1%
-OM=25%
2.E+03 OM=50%

1.E+03 OM=90%

O.E+00


Time, year


(B)
4.E+05


3.E+05 Baseline, OM=1%
-OM=25%

2.E+05 OM=50%
2.E+05
OM=90%


1.E+05






-2.E+05
Time, year


Figure 27. Simulation results of GPP and recovery time under
different initial organic matter storage values, showing an increase
in GPP (A) and a decrease in recovery time (B) as the initial organic
matter storage is increased by 25%, 50% and 90% of its steady state
value.















DISCUSSION


Ecosystem Services and Natural Capital

This study calculated emergy and emdollar values for services and natural capital

of six Florida ecosystems. Wetlands in Florida are protected by laws and regulations that

prevent their uncompensated destruction. These policies are justified since this research

showed that from an energetic analysis, wetland ecosystems are much more valuable than

uplands both in terms of the yearly services they provide to society and in the natural

capital (structure) they store. However, current policy that values wetlands between

$45,000 and $75,000 per acre ($112,500 to $187,500 per hectare) seriously undervalues

them.

The emdollar values of structure and environmental services (Tables 1 and 2) can

be used to determine an approximate monetary value for wetlands and their

environmental services. These values are appropriate for deriving fair mitigation ratios

among different ecosystems and should not be confused with market values of wetlands.

On an annual basis wetlands provide between 2,295 and 6,430 em$/ha/yr of value to

regional human economies, compared to the two upland ecosystems values of 727 and

911 em$/ha/yr (Table 1). The natural capital of wetlands (without including geologic

structure) ranges from approximately 283,000 to over 1,000,000 em$/ha (Table 2).

Compared to the upland ecosystems, whose emdollar values ranges from approximately










50,000 to 71,000 em$/ha, wetlands, on the average, have almost 11 times as much value

in their natural capital.

These values can be used to determine the monetary costs for replacing services

and natural capital lost as a result of development. Whenever a "price" is placed on

wetlands, it usually reflects the costs of building wetlands, which includes land

acquisition, planning, construction, and monitoring. These values are costs in economic

terms based on actual (or maybe perceived) costs to construct wetlands in Florida, but in

reality they do not reflect the value of environmental services or structure that is lost

when a wetland is destroyed. A better measure of what society loses with each hectare of

wetland conversion is suggested by the replacement values (Table 3) calculated in this

study. For instance, if a forested wetland were cut, the appropriate loss value could be

calculated from the biomass storage and GPP loss. The current "price" for wetlands in

Florida ranges between $112,500 and $187,500 per hectare. Even at the highest range,

$187,500 per hectare is only about 17% to 62%, depending on the type of wetlands, of

the value of ecosystem services and natural capital that is lost with the elimination of

wetlands (Table 3).

Mitigation Ratios

The current trend in public policy concerning wetland losses associated with

development is "no net loss". It is believed that no net loss can be achieved by

constructing wetlands to replace those that are eliminated, or by enhancing degraded

wetlands to replace functions and values lost from impacted ones. In most cases a

wetland is built "on-site," but in mitigation banks, it may be built somewhere within the

watershed (service area).










Under current regulations, a mitigation ratio is calculated by subjectively

quantifying ecosystem value of the proposed impacted site, as well as accounting for the

perceived ease of replacement and recovery time needed. Representatives of

government agencies and consulting companies visit the proposed impacted site and

"score" the wetlands using rapid assessment procedures. The wetland value achieved by

this methodology is a result of perceived values by the scorers. Since no quantitative

studies are required, mitigation ratios are thus affected by individual preferences rather

than actual contributions. Problems arise when wetland scoring is done by hundreds of

professionals throughout the state, each one evaluating wetlands according to their

individual preferences. For this reason, mitigation ratios across the state and in different

years may be highly variable. This methodology is even more questionable when

mitigation ratios have to be calculated for wetlands that are not replaced type for type, as

may occur with the onset of mitigation banks.

Static Replacement Ratios

One option to calculate mitigation ratios among different ecosystems is to use

static replacement ratios of wetland value. Replacement values are based on several

assumptions from the following rationale: when a wetland is eliminated, vegetation is cut,

peat is removed, water is drained, and the depression might be filled and covered with

impervious surface (roads or buildings). Consequently, annual ecosystem services are

lost since the wetland no longer exists. A wetland that is eliminated and not replaced,

cannot contribute environmental services and therefore, the loss of environmental

services accumulates indefinitely. Conversely, if the wetland is replaced, eventually, the

created wetland will provide the services that were provided by the original wetland,










assuming the new ecosystem is similar to the destroyed one. Since a constructed wetland

is a growing system, each year there is an incremental replacement of the lost services. If

we assume that ecosystem services increase linearly, that is, approximately half the

environmental services are gained over the replacement time of an ecosystem, then the

replacement value is the emdollar value of structure plus half the environmental services

multiplied by the recovery time (Table 3).

Examples of ratios calculated for the six Florida ecosystems using replacement

values are given in Table 7. For instance, for every one hectare of forested wetland

destroyed, 3.6 hectares of shrub/scrub are needed to replace the value lost. Similarly, 1.0

ha of herbaceous marsh is equivalent to 1 ha of forested wetland, and 2.0 ha of floodplain

forest replace 1 ha of forested wetland. If the wetland is mitigated by an upland

ecosystem, 11.5 ha of mesic forest and 16.8 ha of pine flatwoods are needed to replace 1

ha of forested wetland.

These static calculations, however, do not take into account the investment costs

needed to construct a wetland and the fact that the natural capital is later replaced. While

biomass and organic matter may be completely replaced if the constructed wetland is

successful, the services of the mature ecosystem lost during the period of replacement are

never recovered. A static calculation, however, yields a 1:1 ratio for type-for-type

wetland replacement (Table 7), and thus, it does not account for the services lost.

Cost Recovery Mitigation Ratios

Results of the cost recovery model summarized in Figure 26 show that 54 years are

required to pay back construction costs of a typical constructed forested wetland.

GPP em$ of mature ecosystems accumulated over the recovery time can be













Table 7. Static replacement ratios for the six Florida ecosystems using values from
Table 3.



With


Forested
Wetland


Shrub
Scrub


Herbaceous
Wetland


Floodplain
Forest


Mesic
Forest


Forested
Forested 1 3.6 1.0 2.0 11.5 16.8
Wetland
Shrub
hrub 0.3 1 0.3 0.6 3.2 4.7
Scrub
Herbaceous
erace1.0 3.4 1 1.9 11.0 16.0
Wetland
Floodplain
Floodplain 0.5 1.8 0.5 1 5.7 8.2
Forest
Mesic
esc 0.1 0.3 0.1 0.2 1 1.5
Forest
Pine
P e 0.1 0.2 0.1 0.1 0.7 1
Flatwoods


Replace


Pine
Flatwoods










calculated by multiplying yearly GPP values from Table 1 (6430 em$/ha/yr for the

forested wetland ecosystem) by 54 years. Thus, after 54 years total em$ from GPP of a

mature system equals 347,220 em$/ha. A growing system, on the other hand, will have

lower initial GPP values, and as it matures, yearly GPP will approach that of a mature

forested wetland. Using emdollar GPP values shown in Figure 26 and adding them for

54 years, yields 108,000 em$/ha. This results in a loss of ecosystem services equal to

239,220 em$/ha over 54 years. This loss is never recovered if the type for type

mitigation ratio is 1:1. In other words, in order for a constructed wetland to reach

347,220 em$ of accumulated GPP, 100 years of growth are required. By that time, the

mature ecosystem would have accrued 643,000 em$ (6430 em$/yr 100 years), so the

constructed wetland would always fall short of the original ecosystem. Therefore, a

higher mitigation ratio is needed to recover those losses. Dividing accumulated GPP em$

values of the mature ecosystem by the GPP values of the created site at year 54 yields a

1.9:1 ratio for type-for-type mitigation.

When costs of construction are subtracted from GPP em$ of constructed wetlands,

it takes 54 years for the new ecosystem to pay back its initial investment (Figure 26). So

while a mature forested wetland would have accrued 347,220 em$ in 54 years, the

constructed ecosystem is just beginning to provide a net benefit to society and its accrued

value is merely 3000 em$. In this scenario, for the constructed wetland to accrue 347,220

em$, 119 years from the time of construction are required. By that time, a mature

ecosystem would have accrued 765,000 em$/ha. This pattern is shown in Figure 28. If

t=54 years is used to calculate the mitigation ratio, it would yield a value of 116:1.

Clearly, this ratio is unreasonable considering that mitigation is a result of land scarcity











1.00E+06


8.00E+05


= 6.00E+05


S4.00E+05


S2.00E+05


0.00E+00


-2.00E+05

Time, year



Figure 28. Graph of GPP accrual in mature forested wetland and
constructed ecosystem. The ratio of these two lines at any point in time
constitutes the mitigation ratio necessary to recover losses due to
construction within that time frame.










and competition for this limited resource. When mitigation ratios are computed yearly, it

is apparent that the ratios are decreasing, and though the two lines will never meet, by

year 100 the ratio is reduced to 2.7:1 (Figure 29) and it will be as low as 1.2:1 by year

500.

This decrease in mitigation ratios begs the question: what is the appropriate time

frame in which to calculate mitigation ratios? If mitigation sites are successful and

protected in perpetuity, then long term trends in ecosystem services accrual show that,

given enough time, constructed ecosystems recover close to 100% of the initial losses.

Therefore, type-for-type mitigation ratios calculated over thousands of years can be as

low as 1.05:1. However, when decisions are made to maximize contributions to society,

this time frame is not appropriate. A more reasonable time frame would be 70-100 years,

or the equivalent of one generation of human life. Mitigation ratios at year 70 and 100

are 5.5:1 and 2.7:1, respectively. That is, if society wants to recover the ecosystem

services lost to impacts within 70 years of wetland creation, 5.5 hectares will have to be

constructed for each hectare impacted. Similarly, if ecosystem services are to be

recovered within 100 years of impacts, then 2.7 hectares of wetlands will have to be

constructed for each hectare of impact. Thus, mitigation ratios decrease as the time frame

allowed to recover ecosystem losses increases (Figure 29).

Simulation Model

Mature ecosystems are the work of decades of ecosystem services and natural

capital accrual. When a forested wetland is cut down and replaced by a created one, a

huge investment is needed from the economy to mitigate the wetland losses. While the

created wetlands are usually monitored for only a few years, at least 165 years are












130
120
S110
I 100
90
80
c 70
S60
50
0 40
P 30

2 20
10
0 -------------------------------
54 60 66 72 78 84 90 96

Time, year


Figure 29. Simulated mitigation ratios for forested wetlands from 54 to
100 years after construction showing decrease in mitigation ratios as the
time frame allowed to offset losses increases.










required for the ecosystem to reach 90% of its steady state biomass, and 386 years to

achieve 90% of organic matter (Figure 21).

Some wetland scientists involved in wetland creation have been trying to "jump

start" created sites by adding organic matter from the impacted sites or saving the on-site

organic pool. The effects of "jump starting" constructed wetlands by adding organic

matter prior to planting was illustrated in the simulation results by increasing the initial

organic matter storage. The simulation model of a forested wetland showed that

increasing the organic matter pool by 25%, 50%, and 90% of its maximum value

increased biomass growth and decreased ecosystem recovery time by as much as 11% to

26%. A 25% increase in organic matter storage resulted in biomass reaching 90% of

steady state value in 140 years, 35 years faster than with the baseline simulation (Figure

24). A 50% increase in organic matter storage resulted in biomass reaching 90% of

steady state values in 119 years (Figure 24), 46 years faster than without the organic pool.

Similarly, increasing the organic matter storage to 90% of its steady state value resulted

in biomass reaching 90% of its steady state value by 98 years, 67 years faster (Figure 24).

GPP rates were also positively affected, and translated into faster recovery times of

constructed wetlands. While 54 years are required to recover costs of construction when

no organic matter is added, this time frame is reduced to 48 years with a 25% increase of

organic matter, 42 years with a 50% addition and 40 years with a 90% addition of organic

matter (Figure 27). Saving the on-site organic matter pool not only increases growth

rates, but it also decreases costs associated with construction.










Consequently, dynamic mitigation ratios also decrease as greater percentages of

organic matter are added to the constructed wetland (Figure 30). For example, without

organic matter, a mitigation ratio of 5.5:1 is necessary to recover losses within 70 years

of wetland construction (Figure 30). Increasing the initial organic matter pool to 25%,

50%, and 90% of its steady state value yields mitigation ratios of 3.9:1, 3.1:1 and 2.7:1,

respectively, for the 70 year time frame (Table 8). Similarly, in order to recover losses

within 100 years of construction, mitigation ratios of 2.3:1, 2.0:1, and 1.9:1 are necessary

with a 25%, 50%, and a 90% increase in organic matter, compared to the ratio of 2.7:1

calculated from the baseline simulation.

The simulated emergy and transformity values of biomass of forested wetlands

(Figure 22) are slightly lower than the ones given in the emergy evaluation table (Table

11). This could be due to the fact that the tabulated value tends to overestimate total

emergy inputs since the same steady state value (6.17E+15 sej/ha/yr) is multiplied by the

turnover time. In reality, when an ecosystem is in early successional stages, transpiration

rates are lower and therefore total driving emergy contributed from the process is also

lower. On the other hand, organic matter emergy and transformity values (Figure 23)

resulting from the simulation model are slightly higher than the tabulated ones (Table

10). This could be due to the slightly different calculation methodology employed in

tabulating emergy and transformity, as explained in Table 11 and Figure 20.

Transformity values of GPP, biomass, and organic matter for the six Florida

ecosystems (Appendix B, Tables 10 through 21) in this study are substantially higher














14

S 12
1 -Baseline, OM=1%
- 10 OM=25%
10
--- OM=50%
S\ OM=90%
(2 8

0 6




2

0


Time, year




Figure 30. Simulated mitigation ratios for forested wetlands from
60 to 120 years after construction showing decrease in mitigation
ratios as the initial storage of organic matter is increased by 25%,
50% and 90% of its steady state value.









Table 8. Mitigation ratios of forested wetlands at 10 year intervals (from 60
to 100 years after construction) resulting from varying initial organic matter
storage to 1%, 25%, 50%, and 90% of its steady state value.



Initial organic matter storage

Time 1% 25% 50% 90%

60 12.1 6.2 4.2 3.6

70 5.5 3.9 3.1 2.7

80 3.8 3.1 2.6 2.3

90 3.1 2.6 2.2 2.1

100 2.7 2.3 2.0 1.9










compared to previous studies (Orrell 1998; Tilley 1999). This is primarily a result of

calculations of annual driving emergy inputs, particularly the addition of geologic input

to total driving emergy. Moreover, the simulated transformity values of biomass and

organic matter storage in this study yield a different pattern than the one presented by

Tilley (2000). Tilley found that transformity values increase as a function of time. In

this study, transformity of biomass and, to a smaller extent, organic matter had higher

initial values than steady state values (Figures 22 and 23). This is also a result of adding

geologic input to the annual driving emergy of the ecosystem; in fact, annual driving

emergy in the early stages of ecosystem growth is primarily in the form of geologic input.

When this value is divided by the ecosystem energy storage to derive its transformity, it

results in extremely high transformity values since the amount of biomass and organic

matter energy present is still small. As the ecosystem matures, transpiration increases

and begins contributing to annual driving emergy, but the ecosystem storage also

increase, thus resulting in lower transformities.

Limitations and Suggestions for Further Research

This study relied on already published data for the ecosystem evaluations and the

forested wetland model. While literature data were cross-referenced, sometimes the lack

of published data resulted in educated estimates in order to carry out the evaluations.

This problem was especially true for the floodplain forest and the upland ecosystems.

For example, while I was able to gather data for the biota of the riparian wetland,

understanding the processes and scale of floodplain formation posed several challenges.

First, the system analyzed in this study was a lake-fed, black water, low flow stream for

which there is virtually no data relating to floodplain formation and structure. Most of










the stream studies focus on large, alluvial systems that usually pose a flooding threat to

human development. Extrapolating structure and turnover times from those studies, and

applying those values to this research yields approximations at best. Thus, the value of

floodplain structure is reported with caution.

Similarly, the upland ecosystems lacked complete reports on organic matter

storage, litterfall, and decomposition rates. While published decomposition rates in pine

flatwoods appeared low compared to other upland and wetland systems, pine flatwoods

experience frequent fires that arrest litter accumulation. However, published data on pine

flatwoods decomposition rates largely ignored the effects of fire on this ecosystem.

As a result of relying on data specific to only a few sites within Florida, the

ecosystems evaluations reflect conditions found at those sites, and average values for

Florida should be derived with caution. The ecosystem tables can also be used as

templates to generate values for other sites throughout Florida by inserting site specific

data collected at those locations if available.

Ideally, the constructed wetland model that was developed to explore the benefits,

costs, and recovery time of wetland creation should have been calibrated using actual

GPP values from a mitigation site. In reality, mature constructed wetlands are rare and

since developers are only required to monitor them until compliance, the fate of those

wetlands post compliance is largely unknown. The mitigation ratios calculated in this

study depend on GPP values from the literature, and thus are specific to the sites sampled

in those studies.










Further Research

This research focused on quantifying the value of ecosystem services and natural

capital of six Florida ecosystems to investigate differences among various ecosystems.

Results from this study have shown that wetlands on average contribute more wealth to

society than upland ecosystems. However, it is important to stress the fact that wetland

mitigation should not be at the expense of all uplands in Florida. Mitigation ratios

between ecosystems should vary as the relative abundance of upland ecosystems change.

As certain ecosystems become scarce, for instance longleaf pine savannahs or maritime

forests, their value should increase to reflect their "rarity" in the landscape. Abundance

of ecosystems could be determined by reviewing Geographic Information Systems land

use coverages of Florida over time. Based on results from these analyses, statewide

policies could be implemented that valued ecosystems on the basis of their relative

abundance as well as their contributions to society.

This study demonstrated that created forested wetlands require 54 years before the

benefits (in the form of ecosystem services of GPP) from the created ecosystem outweigh

the costs of construction (the sum of economic inputs to constructed wetlands as well as

the environmental losses from the destruction of the pre-existing ecosystem). Mitigation

ratios derived from the model have used data pertaining to constructed forested wetlands.

Future research is needed to explore the concept of mitigation further and include

calculations of mitigation ratios for different ecosystems, as well as for different

mitigation alternatives, such as restoration, enhancement, and preservation. What are the

appropriate ratios if we construct a freshwater marsh to replace a forested wetland? What

range of mitigation ratios should we use for restored, enhanced, or preserved wetlands?




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