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Self-organization of an ecologically engineered wetland in Central Florida

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Title:
Self-organization of an ecologically engineered wetland in Central Florida
Creator:
Howington, Tonya Mae, 1966-
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Language:
English
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xi, 143 leaves : ill. ; 29 cm.

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Subjects / Keywords:
African Americans ( jstor )
Biomass ( jstor )
Birds ( jstor )
Constructed wetlands ( jstor )
Marshes ( jstor )
Nutrients ( jstor )
Peasant class ( jstor )
Simulations ( jstor )
Warblers ( jstor )
Wetlands ( jstor )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (M.S.)--University of Florida, 1994.
Bibliography:
Includes bibliographical references (leaves 135-142).
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
Tonya Mae Howington.

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University of Florida
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University of Florida
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Copyright Tonya Mae Howington. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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33355058 ( OCLC )
ocm33355058

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SELF-ORGANIZATION OF AN ECOLOGICALLY ENGINEERED WETLAND IN CENTRAL FLORIDA













By

TONYA MAE HOWINGTON




















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 1994


























To my mother and father, for all that they inspired me to overcome.












ACKNOWLEDGEMENTS



I am grateful to my committee members for their individual guidance and
assistance in the classroom and in the field. Dr. Mark Brown consistently gave me the courage to spit in the face of disaster. Dr. G. Ronnie Best taught me to tread without fear into new and exciting wetland frontiers. And Dr. Stephen Humphrey showed me that I can boldly evaluate new and traditional view points in community ecology without permission.

Other professors also greatly influenced my development as a systems
ecologist. Most notable were Dr. Howard T. Odum and Dr. David Scienceman. Both provided me with new ways to look at the world and its future.

All my friends who helped me with avian and fish surveys deserve my special thanks. In particular I wish to thank Chuck Graham for helping me obtain a research project and for the use of his data. In addition, I wish to thank Ken Clough, Rodney Pond, David Day, John Stenberg, David Clayton, Mark and Amelda Clark, Harish Ramakarishna, Valerie Enck, Michelle Piazza, Sergio Lopez, Fred Gaines, and anyone else who risked life and limb among the alligators.

I especially thank my husband, Juan Jorge Haberkorn, for helping me conduct surveys and providing technical advice to improve my analysis. His patience and unending optimism kept me going even when the odds were clearly against me.

I am also indebted to Silvia Romitelli, David Clayton, and Dave Tilley for their support and patience during the last critical weeks of my thesis writing.


iii








Finally, I thank the St. Johns River Water Management District as the primary supporter of this project. They provided financial and technical support including water quality data, areal photos, and access to the Apopka Marsh Demonstration Project site.










































iv














TABLE OF CONTENTS


page
ACKNOWLEDGEMENTS ......... ........................ iii

LIST OF FIGURES..... ................................. vii

LIST OF TABLES.................................. ix

ABSTRACT ........................................ ................................. ......... x

INTRODUCTION ................................................................................... 1

Plan of Study ......................................................................... . 2
Self-Organization and Constructed Wetlands ......................... 2
Description of Study Site...................... ....... .................... 10

M ETH O D S............................................... .......................................... 13

Energy System Diagram.................................. 13
Emergy Analysis................................ ..... .................. 14
Vegetation Complexity and Structure ................................... 16
Avian Surveys................................................. 21
Fish Population Sampling................ ............ 23
Computer Simulation Model.............................. 23

RESULTS ............................................ 30

Ecological Systems Overview............................................ 30
Vegetative Communities ......................................................... 39
Avian Community Structure .................................................... 53
Fish Density and Biomass ...................................................... 65
Computer Simulation Model......................................... 65





V








D ISCU SSIO N ................................ ... ..... ....... .. ..... ........... 90

C onclusions ................................................................ 96

APPENDIX A: AVIAN SURVEY RESULTS FOR TRANSECTS 1-4 ... 97 APPENDIX B: AVIAN SURVEY RESULTS FOR TRANSECTS 5-6 ... 122 APPENDIX C: COMPUTER SIMULATION MODEL ........................... 131

REFERENCES CITED .............................. .......... 135

BIOLOGICAL SKETCH............................................... 143






































vi












LIST OF FIGURES

page
Figure 1. M ap of project site.................................... ............. 12
Figure 2. List of energy symbols................................................. 15
Figure 3. Map of site showing numbered transects............................. 18
Figure 4. Diagram of computer simulation model. ............................. 28
Figure 5. Systems diagram of subsidized marsh.................................. 31
Figure 6. Summary diagram of emergy analysis .................................. 37
Figure 7. Water budgets for both marshes ....................................... 40
Figure 8. Nutrient budgets for both marshes........................................ 41
Figure 9. Map of vegetative cover for November 1990................... 42
Figure 10. Map of vegetative cover for November 1991...................... 43
Figure 11. Map of vegetative cover for April 1992............................... 44
Figure 12. Map of vegetative cover for November 1992 ......................... 45
Figure 13. Vegetative cover richness for both marshes ............................ 46
Figure 14. Vegetative cover complexity for both marshes................. 48
Figure 15. Vegetative percent cover of subsidized marsh ....................... 49
Figure 16. Vegetative percent cover of unsubsidized marsh ........... 50
Figure 17. Diversity indices for avian species in both marshes .............. 54
Figure 18. Evennesss indices for avian species in both marshes............ 55
Figure 19. Overall avian density in subsidized marsh ............................... 57
Figure 20. Overall avian density in unsubsidized marsh ........................... 58
Figure 21. Overall avian biomass in subsdized marsh............................ 63
Figure 22. Overall avian biomass in unsubsidized marsh.................... 64
Figure 23. Results of fish survey including a)density and b) biomass ...... 66 Figure 24. Simulation of unsubsidized marsh.................................... 68
Figure 25. Simulation of marsh with 10% added subsidy................... 70
Figure 26. Simulation of marsh with 500/o added subsidy ...................... 71
Figure 27. Simulation of marsh with 100% added subsidy ............. 72
Figure 28. Simulation of marsh with 500% added subsidy ...................... 74
Figure 29. Simulation of marsh with 1000% added subsidy ................... 75
Figure 30. Summary of simulation results after 70 years .......................... 76
Figure 31. Simulation of unsubsidized marsh receiving nutrients
from rain only..................................................................... 77
Figure 32. Simulation of unsubsidized marsh with peat contributing
only 90% of orginal nutrients ................................................ 78


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Figure 33. Simulation of unsubsidized marsh with insects requiring
double their food requirements ....................... 79
Figure 34. Simulation of subsidized marsh with insects requiring
double their food requirements .............................................. 80
Figure 35. Simulation of unsubsidized marsh with fish requiring
double their food requirements ...................... ....................... 82
Figure 36. Simulation of subsidized marsh with fish requiring
double their food requirements ................................................ 83
Figure 37. Simulation of unsubsidized marsh with birds requiring
double their food requirements ....................... 84
Figure 38. Simulation of subsidized marsh with birds requiring
double their food requirements ............................................. 85
Figure 39. Simulation of periodic fish kill in unsubsidized marsh............ 86
Figure 40. Simulation of periodic fish kill in subsidized marsh ............... 87
Figure 41. Simulation of increased migration in unsubsidized marsh......... 88 Figure 42. Simulation of increased migration in subsidized marsh.......... 89

































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LIST OF TABLES


page
Table 1. List of transformities used for the emergy analysis ................... 17
Table 2. Vegetation cover types and descriptions ................................. 19
Table 3. Avian species by taxonomic group ............................ ............. 23
Table 4. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the subsidized marsh........ 33 Table 5. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the unsubsidized marsh... 35 Table 6. Summary of emergy analysis of both marshes .......................... 36
Table 7. Summary of vegetative community structure ............................. 52
Table 8. Avian size classes based on average weight of species ............. 60
Table 9. Summary of avian and fish community structure ........................ 67




























ix







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
SELF-ORGANIZATION OF AN ECOLOGICALLY ENGINEERED WETLAND IN CENTRAL FLORIDA

By

Tonya Mae Howington
December 1994

Chairperson: Dr. Mark T. Brown
Major Department: Environmental Engineering Sciences
A constructed wetland (subsidized marsh) in Central Florida receiving continuously pumped hypereutrophic lake water was studied for two years to determine the effect that an external subsidy had on its self-organization. This marsh was compared to an adjacent constructed wetland that did not receive this subsidy (unsubsidized marsh.)

Energy sources influencing each marsh's development were compared using an emergy analysis. Both marshes were similar in natural renewable energies (0.97 El5 sej ha-1 yr-1 ). However, when the pump structure and purchased energies were included, the emergy flux in the subsidized marsh was 14.3 E15 sej ha-1 yr-1 , while the unsubsidized marsh received only 2.0 E15 sej ha-1 yr- . The importance of this contrast in emergy flux was reflected in two emergy ratios. The environmental loading ratio between the subsidized marsh (13.8) and the unsubsidized marsh (0.10) indicated a significant difference in the amount of renewable energies (solar insolation, rain, nutrients in rain) to nonrenewable energies (primarily lake water and nutrients and pump system) stimulating marsh self-organization. The investment ratio for the subsidized marsh (2.10) was much greater than that of the unsubsidized marsh (0.10).




x










Therefore, purchased energies were much higher than the inputs of free energies for the subsidized marsh.
Aerial photos were interpreted to evaluate the number of vegetative cover
types (richness), complexity (fractal dimension), and percent vegetative cover. After two years, vegetative cover richness in the subsidized marsh was 3.25, while the unsubsidized marsh had a richness of 4.69. Both marshes had similar levels of moderate complexity (1.5) throughout the survey period. Tvpha Community had the highest percentage of cover dominance in the subsidized marsh (66.70%) and in the unsubsidized marsh (48.61%) at the end of the survey period. Overall, the subsidized marsh had 89% cover of types that include Tvyha sopp. The unsubsidized marsh had a 67% cover of Typha spp. cover types.
Avian surveys and a synoptic fish sampling were conducted in each marsh. Diversity and evenness were significantly higher in the unsubsidized marsh. Avian density and biomass were much higher in the subsidized marsh (18.48 birds ha-l; 5.11 kg ha-1) than in the unsubsidized marsh (7.05 birds ha-1 ,2.22 kg ha-1 ) . The subsidized marsh supported higher densities and biomass offish (230 fish m-2 ,6.44 kg m-2) than the unsubsidized marsh (169 fish m-2 ,4.39 kg m-2 ).

Overall, the external subsidy increased the emergy flux in the subsidized marsh by increasing the input of nonrenewable energy sources. As a result, community parameters such as vegetative percent cover dominance, animal density and overall biomass were higher in the subsidized marsh, but at a cost of lowered richness and diversity and evenness. Complexity of vegetative structure did not seem to be affected by the increased subsidy.




xi










INTRODUCTION


Theory would suggest that an external subsidy should increase the carrying

capacity for wildlife of an ecosystem, all other things being equal. Determining the effect that an external subsidy has on the organization of an emerging, created wetland is the main question being asked by this thesis.

One prediction of this study is that the external nutrient subsidy increases the

energy flow in productive pathways that in the short term results in an increased food base and leads to an increase in the number of consumers. Initially, species diversity and evenness are predicted to be relatively low. If the subsidy is continued over many years, then higher diversity and evenness are expected to occur. Significant structural differences in the vegetation community between created wetlands receiving a subsidy and created wetlands not receiving a subsidy might also be discernible such as the formation of a monoculture. The differences in structural characteristics (mosaic of vegetation types and open water) may account for differing wildlife densities and/or diversity between subsidized and unsubsidized wetlands. Finally, early successional trends in wildlife use and diversity may be observed and related to external subsidies.

This thesis is an investigation of the ecological self-organization of a constructed wetland in Central Florida receiving continuously pumped lake water, high in nutrients and suspended material. Called the Apopka Flow-way Demonstration Marsh Project, the constructed wetland is part of a larger project funded by the St. Johns River Water Management District (SJRWMD). The project's primary goals are to restore historic wetlands and improve water quality in Lake Apopka.





I





2


Plan of Study


The research for this thesis tested theories concerning the affect of an external subsidy on ecosystem structure and organization. Two newly established marshes (one receiving nutrient enriched lake water and the other not receiving the subsidy) were studied. The effect of the external subsidy was evaluated by comparing properties of the vegetative and avian communities in the wetland receiving nutrient enriched lake water with properties in the nearby unsubsidized wetland.

An emergy analysis was used to determine the energy sources influencing selforganization of each wetland system. In addition, budgets of water and nutrients for each marsh were evaluated and compared. A comparison of the vegetative community structure emerging in each marsh was presented using a landscape scale perspective. The vegetative cover of the subsidized marsh was determined, and the spatial organization of the vegetative community was measured. Next, wildlife usage of the subsidized marsh was compared to the unsubsidized marsh. The density, composition, and biomass of the avian community found in each marsh were compared. A synoptic fish survey was conducted to supplement the avian surveys in providing a detailed description of the wildlife communities using the project site. Finally, a computer simulation model was developed to further test theories of community response to increased and decreased external subsidy to a system.


Self-Organization and Constructed Wetlands


Processes which select species based on seeding or the available resources are examples of self-organization (Beyers and Odum 1994). Odum (1983) stated that selforganizational processes including those by which ecosystems develop structure when taken in aggregate is succession. Examples of self-organizational processes include





3


reinforcements produced by nutrient cycling, animal and plant interactions, and the role of keystones species.

Self-organization in constructed wetlands is dependent mostly on its hydrologic design. Wetlands that are continuously flooded, but have shallow flowing water, as in many constructed wetlands, have high productivities and develop quickly according to Mitsch and Gosselink (1986.) The actual relationship between wetland productivity and hydroperiods includes nutrient inputs, export, decomposition, and nutrient cycling.

Odum (1990) defines ecological engineering as an integration of humanity and nature while benefiting both. Constructed and restored wetlands can be ecologically engineered for the treatment of nonpoint source pollution (Odum 1990, Mitsch 1992, and Hammer 1992). Nonpoint source pollution from agricultural activities is often thought to be the major cause of surface water degradation in the United States (Baker 1992). According to Mitsch (1992), a wetlands system may provide more efficient treatment, greater longevity, and reduced operating requirements than other conventional methods.

Mitsch has outlined several principles of ecological engineering in various

publications which can be incorporated into the design of a treatment wetland (Mitsch 1990, 1992, Mitsch and Cronk 1992). These principles include designing the system for minimum maintenance by allowing the system to self-organize on its own. He recommends the use of available low quality energies such as potential energy of downstream flow to subsidize the system with water, energy, and nutrients. He also suggests that in some cases the use of pump systems may not increase treatment benefits derived from a treatment marsh system. For example, some hydrologic pump systems may require more energy resources to construct and operate than what the pumps actually contribute to desirable wetland functions in the marsh system such as the removal of nutrients in the water column. In environmental systems, the components of the system which require more work in their development either contribute more to the system





4


commensurate with what was required to make them, or the production is discontinued according to Odum and Arding (1991).

Knight (1992) explained that significant losses of vegetation and animals can occur as a result of high loading of pollutants including too much water, organic matter or nutrients. He pointed out that water flow and depth control can affect primary productivity of the wetland and the ability of the wetland to effectively treat nonpoint source pollution. He suggested that higher flows of shallow water provide higher dissolved oxygen levels leading to higher secondary productivity.

Hammer (1992a) predicted that if high loading of nutrients were added to a

constructed freshwater marsh, then Typha spp., Salix spp., or other woody shrubs will dominate and reduce the system's diversity. Moreover, a monoculture could develop resulting in an overall decrease in species diversity. In another study, Hammer (1992b) pointed out that manipulation of the water level alone can sustain a diverse, complex, and productive marsh for many years. Furthermore, fluctuations of water levels can create more ecological niches for more species of plants and animals.

Common techniques for establishing ecologically engineered wetlands include (1) re-establishing or managing wetland hydrology, (2) eliminating or controlling chemical or other contaminants affecting wetlands, and (3) reestablishing and managing native biota (Maurizi and Poillen 1992). Not all engineering projects, however, have the reestablishment of the original biota as a primary goal due to the immense amount of resources required to do so. In this case, it may be more important to consider the possible affects of the desired hydrology including the balance between nutrient removal and the potential to increase wildlife habitat and abundance.





5


Vegetative and Wildlife Community Structure


Avian communities are often used as the primary indicators of habitat quality given that many studies have shown that birds are often sensitive to changes in wetland structure and function (Kroodsma 1978, Frederick and Collopy 1988, Feirerabend 1989, Cable et al. 1989, Edelson and Collopy 1990). In addition, Edelson and Collopy (1990) determined that constructed wetlands can provide suitable habitat for many wetland avian species.

An important aspect of restoring wetlands converted to agricultural, or other intensive land uses, is that successional phases may also not be the same as in natural wetlands given that the seed source of the historic vegetative community may be lost or out competed by more aggressive invasive species. Marsh vegetation may not ever resemble the historic community (Maurizi and Poillon 1992). In addition, some animals which were known to frequent the site before it was in agricultural use may not return to use the site after its conversion back into a wetland. Animal densities may also be different than historic levels.

Wildlife production is generally high for constructed wetlands receiving high

concentrations of nutrients according to many studies (Maehr 1984, Buckner et al. 1990, Kerekes 1990, Kale 1992, Mcallister 1992, Knight 1992, Rader and Richardson 1992, Hammer 1992a, 1992b, Guntenspergen et al. 1993, McAllister 1993a, 1993b, Streever and Crisman 1993). Potential productivity at all trophic levels is set by nutrient supply (Carpenter et al. 1985). Moreover, actual productivity depends on the recycling of nutrients and their allocation among populations with different growth rates.

A constructed wetland (37.8 ha) in California used for wastewater treatment had much higher avian usage than nearby natural lake and bay fringe wetlands according to Gearheart and Higley (1993). In the first two years alone, avian species used the constructed wetland at rates exceeding ten times that of the natural wetlands. Waterfowl





6


used the constructed wetland between 38% and 78% more than the lake and bay wetlands. A total of ninety-eight species were documented as visiting the constructed wetland.

Lofgren (1993) found both high avian diversity and high avian density at Mitchell Lake in Texas. Mitchell Lake had been receiving high nutrient loadings for over thirty years. A total of 270 avian species have been sighted at the lake, thirty of which are known to breed in the marshes.

Edelson and Collopy (1990) conducted a study of wading bird usage of a hypereutrophic lake, and concluded that the abundance of fish stimulated a large population of egrets and herons. The large fish population was thought to be due to the high levels of nutrients. The birds also displayed unusual foraging behavior that may have allowed the birds feeding in the dense Typha spp. stands better access to fish in deep water areas.

Bird usage of late successional settling ponds of phosphate-mined lands may provide a useful comparison to bird usage of created freshwater marshes used to treat nonpoint source pollution. Both environments are high nutrient systems and are often dominated by Salix carolinana and Typha sopp. A survey of different phosphate mining sites showed that late successional settling ponds contained extensive colonies of double-crested cormorant, anhingas, black-crowned night herons, cattle and great egrets, wood storks and white ibises (Maehr, 1984).

Vegetation density irregardless of species has been found to be an indicator of habitat suitability for waterfowl in some studies. One study comparing plant-macroinvertebrates associations and waterfowl found that 1 gram of animal biomass was associated with every 100 grams of plant life (Krull 1970). Although the study did not differentiate between cover types, it was noted that plants considered to be poor waterfowl food harbor large quantities of macroinvertebrates which can make the area more desirable for waterfowl usage.





7


Although animals, including macroinvertebrates, consume and recycle nutrients from wetlands, Hammer (1992a) believes that animals do little to directly treat non-point source pollution. He suggested, however, that the presence or absence of certain animal communities can provide an indicator of the health of the system. It is important that one carefully interpret the animals communities present, according to Hammer, because certain types of species may survive better and persist longer than others in systems receiving high nutrient loadings. Indeed, the problem of undesirable high densities of mosquitoes during the early stages of marsh development is a real one for many treatment wetlands according to Dill (1990.)

A study by Oliver and Schoenberg (1989) found that birds can have an indirect

positive effect on fish and macroinvertebrate populations. In their study, they showed that ibis and other wading birds increased macro nutrient concentrations (particularly phosphorus) increased under rookeries. Under these rookeries the fish and macroinvertebrate densities slightly increased. In comparison, it was determined from a study of a oligotrophic lake by Kerekes et al. (1992) that there is a close balance between the size of a water body, nutrient loading, and its fish production to the occupancy and production of piscivorous birds.

Early successional processes that determine the abundance of macroinvertebrates can also affect higher trophic levels. Joyner (1980) found that pond selection by ducks in Ontario was partially determined by invertebrate density. Invertebrate abundance increases as the submergent vegetation replaced the emergent vegetation according to Voigts (1976). In his study, marshes that had submerged vegetation (suggesting some openness) interspersed with emergent vegetation (suggestion cover) had the greatest invertebrate abundance. He further suggested that nesting birds preferred the marshes with higher numbers of invertebrates. Feierabend (1989) also points out the importance of invertebrates stating that they are critical to entry dynamics and functions of wetlands and the foundation of wetland food chains.





8


Invertebrate abundance was positively correlated with marsh usage by waterfowl in a study by Murkin et al. (1982). However, invertebrate abundance was not affected by cover removal. According to Murkin, visual cues of openness may be what waterfowl used to judge where the greatest abundance of invertebrates were to be found. This theory was also supported by research conducted by Leschisin et al. (1992) and Wilcox and Meeker (1992).


Landscape Scale Studies of Community Structure


Landscapes go through successional phases or stages just as smaller scale

communities (Naveh and Lieberman 1984, Bell et al. 1990). Also like communities, landscapes are predicted to evolve over time towards more complex and diverse systems. The development and dynamics of landscape spatial heterogeneity can be an important factor that influences both biotic and abiotic processes (Risser et al. 1984, Forman and Godron 1986, Turner 1987). Moreover, each successive level of biological organization has properties that cannot be predicted from those of less complex levels such as the difference in characteristics of populations and the individuals of which they are composed (Odum 1971).

Often important information about a certain species behavior or the organization of a biological community is missed because the scale of the study is not appropriate. In addition, if the scale is spatial, then the behavior of an individual may be acting on cues of the community or vice versa (Cody 1981, Molofsky 1994, Holmes et al. 1994, Silverman 1994, Tilman 1994.)

The different dynamics of a wetland at different scales provides additional

problems when attempting to determine community structure. Wildlife populations are often more constant on a regional scale due to the asynchrony of the separate local








populations according to Willard and Hiller (1989). When some populations are at low levels, others are high.

Local short term disturbances could allow species with greater colonizing ability to recolonize disturbances (Bertness and Ellison 1987). The accumulative affect of these events could change the areal distribution of the species and provide new patterns. Moreover, Weller (1981) described a variety of behavioral adaptations for freshwater wildlife species in wetlands which combine both spatial and temporal heterogeneity on a landscape scale. Weller suggested that this heterogeneity allows internal adaptation.

A study by Doughtery (1990) evaluated the interrelationship between space and time. One of his conclusions was that community measurements of successional development were related to measurements of landscape pattern. Moreover, Brown (1989) suggested that the appropriate scale from which to view any problem is the next larger one.

Kareiva (1994) suggested in his review paper that more serious experimentation should be performed that explicitly tests major hypotheses emerging from recent theoretical explorations of spatial effects. Recently many ecologists are turning towards larger scale studies to explain ecological functions and dynamics.

In his recent study, Bowers (1994) modeled both age structured and habitat

structured populations to measure the affects of age on individual performance versus the affects of habitat selection. He found that habitat selection can have as much or more of an affect on population dynamics in a particular ecosystem as demographic forces such as birth, death, and migrations. Bowers also suggested that ignoring the affects of landscape scale processes could produce misleading results.

Shaw and Atkinson (1990) introduced the terminology, components, advantages, and current limitations of computerized GIS's for ornithological research. Two case studies were provided as illustrations of the potential utility of GIS for ornithological research.




10


Description of Study Site


Lake Apopka is a large (area = 124 km^2), shallow (mean depth= 1.7m)

hypereutrophic lake in Central Florida (Lowe et al. 1992). There is debate as to the naturally occurring trophic status of the lake (Schelske and Brezonik 1992). Schelske and Brezonik suggested that in the early 1940's a hurricane removed most of the rooted macrophytes in the lake which lead to the early stages of increased nutrient availability and subsequently increased algal productivity. Lowe et al. (1992) also believed that agricultural practices since 1947 may have contributed to the eutrophication of Lake Apopka.

Before 1947, much of the area surrounding the lake was freshwater marsh. State and federal programs assisted local farmers in converting the marshes into agricultural use. Nutrient enrichment of the lake further increased from water that was back pumped from the agricultural fields. The practice was for farmers to periodically flood their fields with lake water and then back pump nutrient enriched water into the lake prior to planting the fields. The continuation of this farming practice today may, in part, sustain the current trophic status of the lake which is undesirable to local fishermen and government agencies.

Addressing the nutrient status of this lake, the St. Johns River Water Management District (SJRWMD) constructed a 200 hectare freshwater marsh on former agricultural lands with the goal of pumping lake water through the system. Lowe et al. (1992) suggested that pumping enriched lake water through a created marsh, filtration of phosphorus and suspended sediments could be maximized. To determine the effectiveness of this treatment system, the SJRWMD is conducting a pilot study of the 200 hectare created marsh. The marsh occupies previous muck farm land which is adjacent to currently ongoing much farm operations and undeveloped woodlands.

The Apopka demonstration project contains two marshes that are receiving

pumped lake water from Lake Apopka shown as the north marsh and the subsidized marsh








shown in Figure 1. The southern marsh cell called the subsdized marsh was studied for this thesis. An unmanaged marsh located adjacent to the subsidized marsh was also studied for this thesis and referred to as the unsubsidized marsh. The subsidized marsh and the unsubsidized marsh maintained similar average water levels (0.76 m ) throughout the study period.




12



PROJECT SITE







NCRTH MARSH pump structure



old field

old field

hardwod hemock old field

borrow
pit

wier
wer2ED MARSH inlet









SCALE: METERS NORTH

500 500
I I
1000


Figure 1. Map of project site.













METHODS


This study was conducted in four stages. An emergy analysis was used to compare the subsidized and unsubsidized marshes based on their relative external energetic inputs. For the second stage, a geographical information system (GIS) program was used to estimate vegetative cover. Early successional structural complexity was compared for the first two years after the marshes were flooded with nutrient enriched water from Lake Apopka.

Field studies were conducted in the third stage to compare the emerging properties of the wildlife communities in each marsh. Both the fish and avian communities were evaluated, although the avian communities were more closely studied. In the final stage, a macroscopic-mini model of a hierarchically organized marsh community was simulated to test theories of early succession in nutrient subsidized marshes.


Energy System Diagram


Energy system diagrams were drawn and used to organize thinking and data

collection. First complex diagrams were drawn showing all pathways and compartments believed to be important. A second, aggregated macroscopic- minimodel was drawn and used for simulation programming.










13





14


Emergy Analysis


Emergy analysis was developed by Dr. H. T. Odum to provide a method of comparing general systems (1983, 1990). The sources driving each system and the component parts are related in the same measurable units. Generally, a systems diagram is developed first to account for each source driving the system and the interactions of different energies within the system. Figure 2 shows the general system symbols created by Odum used to draw the diagram. Pathways and storages were initially measured either in energy or material units.

Tables of the sources and the storages are made for comparisons. Each

component being evaluated is multiplied by its respective transformity to obtain its emergy value. The flows and storage components of each system can then be compared on the same basis. Often the transformities of the various components are compared to determine the differences in the amount of total energy to maintain each type.

An emergy analysis table was evaluated to put in perspective the relative

contributions of pumps, water, nutrients, human services, and renewable energies driving the marshes. Water, nutrient, and energy budgets from both renewable (rain) and non-renewable (pumped water) services were determined to evaluate the net contribution of each component. Renewable sources included sunlight and the chemical potential of rain. Nonrenewable sources from pumped water included water, nutrients, and organic matter from Lake Apopka. Purchased nonrenewable sources included the pump structure, fuel to run the pumps, and services for construction, operation and maintenance of the flow-away system.

Data were obtained from SJRWMD after two years of operation of the

demonstration project. Each source flow was converted into solar emjoules per year per hectare using predetermined transformities. Transformities had been determined in other




15



_ Energy circuit. A pathway whose flow is proportional to the quantity in the storage or source upstream.


Source. Outside source of energy delivering forces according to a program controlled form outside, a forcing function.



Tank. A compartment of energy storage within the system storing a quantity as the balanace of inflows and outflows, a state variable.



Interaction. Interactive intersection of two pathways coupled to produced an outflow in proportion to a function of both, control action of one flow on another, limiting factor action, work gate.



Consumer. Unit that transforms energy quality, stores it, and feeds it back autocatalytically to improve inflow.




Producer. Unit that collects and transforms low-quality energy under control interactions of highquality flows.





Box. Miescellaneous symbol to use for whatever unit or function is labeled.







Figure 2. List of energy symbols.




16


studies, so that it was not necessary to recalculate their values. Table I lists the transformities used in this study.

An environmental loading ratio and an investment ratio were calculated to compare the quantities of different energy qualities entering each system. The environmental loading ratio determined the input of nonrenewable energies (e.g., external subsidy) and divided it by the input of renewable energies (e.g., sun, rain, nutrients in rain.) The investment ratio divided the amount of purchased energy (e.g., pump system including fuel, construction, operation and maintenance, and pump structure) entering the system by the amount of free energies (e.g., sun, rain, nutrients, phytoplankton.)


Vegetation Complexity and Structure


Vegetative cover richness, complexity, and percent cover were determined using aerial photos and a computer mapping program (ARCinfo). Vegetative cover types were analyzed to provide insight into landscape scale successional processes occurring in the subsidized and unsubsidized marshes. In November 1990, November 1991, April 1992, and November 1992, the SJRWMD photographed the marshes from a small Cessna plane. The photos were analyzed at the Center for Wetlands and Water Resources using ARCinfo, a geographic information system computer mapping program.

The aerial photos of the marshes, taken by SJRWMD, were interpreted and

resulting land cover maps were digitized into ARCinfo as coverages. Vegetative percent cover was determined for each cover type in each marsh and for each transect shown in Figure 3 (transects were laid out for avian sampling.) Each transect had a fixed width of 35 meters on either side of the center line. Four 440 meter long transects (TI through T4) were established in the subsidized marsh, and two 750 meter long transects were establish in the unsubsidized marsh (T5 and T6). Table 2 describes the eight vegetative structure types used to generalize the cover types occurring in the survey areas.





17






Table 1. List of transformities used for the emergy analysis.


Energy Source Transformity Units References Sun 1.00E+00 Sej/J Odum et al. (1987) Rain-chemical potential 1.54E+04 Sej/J Odum et al. (1987) Total nitrogen 4.21E+09 Sej/g Brown and Arding 1991 Total phosphorus 6.88E+09 Sej/g Brown and Arding 1991 Phytoplankton 1.00E+04 Sej/J Odum and Arding1991 Pumped water-chemical potential 2.35E+04 Sej/J Odum et al. 1987 Liquid fuel 6.60E+04 Sej/J Brown and Arding 1990 Construction-structure 6.70E+09 Sej/g Brown and Arding 1991 Construction-services 1.60E+12 Sej/$ Brown and Arding 1991 Operation and maintenance 1.60E+12 Sej/$ Brown and Arding 1991




18


TRANSECT LOCATIONS



ST6
. T5

iT4 T3 T2 Ti






SCALE: METERS NORTH

250 250

500

Figure 3. Map of site showing numbered transects.











Table 2. Vegetation cover types and descriptions. Cover Type Includes one or more of the following: Herbs Panicum spp.. Bahia spp.. Bidens spp. Shrubs Ludwigia spp.. Eupatorium leptophyllum, Sambucus canadensis, Salix caroliana

Open Water Open areas with less the 25% cover vegetative cover Floating aquatics Hydrocotyle spp.. Polygum spp.. Alternathera spp., Eichhornia crassipes

Emergents Scripus spp., Sagittaria spp., Pontederia cordate Typha < open water Open water with 25-50% cover of Typha spp. Typha >= open water Open water with 50-75% cover of Typha spp. Typha Community Typha spp. interspersed with more than 25% cover of emergents or shrubs





20


The richness of the vegetative cover types was used to compare the complexity of the emerging marshes over the project period. Vegetative cover richness was calculated using Margalefs index for species richness (Margalef 1958). This index was modified to use the vegetative cover types as species and the number of vegetative patches within a marsh or transect as individuals. Hence, the vegetative cover richness was calculated as follows:


R = (C - l)/(log(F) (1) where R = vegetative cover richness
C = vegetative cover type
F = Number of cover type patches



Vegetative structure complexity was determined by measuring the fractal

dimension as described by LaGro (1991). The area and perimeter of the vegetative patches, formed by the vegetative cover types, provided the two-dimensional measurements of vegetative structure necessary for the calculations. Complexity was calculated as follows:


D = 2 * (log(P)/log(A)) (2) where D = fractal dimension
P = patch perimeter
A = patch area



Percent cover provided a further description of the changes in structural

complexity of each marsh over time. Vegetative cover percentage calculations divided the total area of each cover type by the total area of each transect or marsh as follows:





21

cj = (Ctj / A) * 100 (3) where Cj = percent cover of type j
Ctj = total area of vegetative cover type j
A = area of marsh or transect



Vegetative cover percentages were compared between the sites using a multivariant analysis.


Avian Surveys


The avifauna surveys were conducted using the Emlen strip technique (Emlen 1977). Avian sampling by transect began in August 1991 in the subsidized marsh. Surveying began on the two transects in the subsidized marsh in November 1992. Avian species were identified visually or by call. Only birds observed within thirty-five meters from the transect center line were recorded.

Transects were surveyed every six-weeks. Sampling order for the transects revolved from one sampling event to the next. The rotation lessened sampling bias by surveying each transect during different morning hours.


Diversity and Evenness


Shannon diversity and evenness indexes were used to compare the avian

communities found in the surveyed marshes (Browner 1989). Diversity indices were used to describe the number of avian species present in the marshes given the total avian abundance. Evenness indices were used to evaluate the distribution of individuals among the avian species present. In other words, the evenness of the avian community was high if all species were represented by similar numbers of individuals. Low evenness indicated





22


that one or very few species dominated the community. The equation used to determine diversity was the following:


H' = - (sum(Pi(sumln(Pi))) (4) where H' = diversity
Pi = ni /N ni = number of individuals in species i
N = total number of individuals in sample

Evenness was calculated as follows:

J' = H' / Hmax (5) where J' = evenness
Hmax = total number of species in sample




Avian diversity and evenness indexes were compared over the survey period

between the subsidized marsh and unsubsidized marsh. Only the time periods when both marshes were surveyed were evaluated for significant differences using a multivariate analysis.


Density and Biomass


A general profile of the changes in density occurring in the marshes compared the avian density by taxonomic groups found in each survey area. Table 3 shows the species included in each taxonomic group. The species under the category labeled "other " were grouped together due to the low number of species represented by the remaining taxonomic groups counted. A multivariate analysis was used to compare avian density in the subsidized marsh and unsubsidized marsh during the period when both marshes were surveyed.

Calculations for avian density divided the total number of birds counted in each taxonomic group by the total area of the transects in the surveyed marsh:





23







Table 3. Avian species by taxonomic group.



Taxonomic Group Scientific Name CorHnon Name Gallinules
Fulica americana American coot Gallinula cholorpus Conmnon moorhen Rallus elegans King rail Porphvrula martinica Purple gallinule Porzana carolina Sora rail

Wading Birds
Botaurus lentiginosus American bittern Nvcticorax nvcticorax Black crown night heron Bubulcus ibis Cattle egret Ardea herodias Great blue heron Casmerodius albus Great white egret Butorides striatus Green back heron Ixobrychus exilis Least bittern Egretta caerulea Little blue heron Egretta thula Snowy egret Egretta tricolor Tri-color heron Nycticorax violaceus Yellow crown night heron

Black Birds
Quiscalus major Boat tail grackle Quiscalus quiscalus Commrron grackle Agriaius phoeniceus Red wing black bird

Passerines
Hirunmdo rustica Barn swallow Polioptila caerulea Blue-gray gnatcatcher Guiraca caerrulea Blue grosbeak Cyanocitta cristata Blue jay Thrvothorus ludovicianus Carolina wren Chaetura pelagica Chinrey swift Geothlypis trichas Common yellow throat Tvramnus tvrannus Eastern kingbird





24







Table 3. --continued.



Taxonomic Group Scientific Nanme Conrnon Name Passerines
Savorrnis phoebe Eastern phoebe Sterna forsteri Foresters tern Columbina passerina Ground dove Passerrina cyanea Indigo bunting Charadrius vociferus Kill deer Cistothorus palustris Marsh wren Zenaida racroura Mourning dove Cardinalis cardinalis Northern cardinal Mimus polyglottos Northern mocking bird Dendroica palmrum Palm warbler Cistohorus platensis Sedge wren Melospiza melodia Song sparrow Melospiza georgiana Swamp sparrow Tachycineta biocolor Tree swallow Dendrocia coronata Yellow rumped warbler Dendroica petechia Yellow warbler

Ducks
Am americana American widgeon Anas discors Blue wing teal Dendroev na bicolor Fulvous whistling duck Anas strepera Gadwall Lophodtes cucullatus Hooded rmerganser Anas platvrhynchos Mallard duck Anas fulvigula Mottled duck Anas acuta Northern pintail Anas clypeata Northern shoveler Aix sponsa Wood duck

Ibis
Plegadis falcinellus Glossy ibis Eudocimus albus White ibis





25







Table 3. --continued.



Taxonomic Group Scientific Name Common Name Other
Falco sparverius American kestrel Anhinga anhinga Anhinga Hialiaeetus leucocephalus Bald eagle Ceryle alcvon Belted kingfisher Himantopus mexicanus Black neck stlit Coravyps atratus Black vulture Gallinago allinago Connmmon snipe Phalacrocorax pelagicus Double-crested cormorant Tringa melanoleuca Greater yellow legs Lanius ludovicianus Logger headed shrike Circus cyaneus Northern herrier Pandion haliaetus Osprey Podilymbus podiceps Pied billed grebe Buteo lineatus Red shoulder hawk Cathartes aura Turkey vulture Catoptrophorus semnialmatus Willet




26

Di = Nij / Ai (6) where Di = density of transect i
Nij = number of birds in taxonomic group j
Ai = area of transects



Calculations for overall avian density for each marsh divided the total number of birds in each taxonomic group by the total area of all surveyed transects in that marsh. Total area in the subsidized marsh using four transects was 15.2 ha. The area of two transects used in the unsubsidized marsh totaled 10.50 ha.

The survey results were averaged over three six month time periods to provide a more general representation of temporal changes in density. These time periods coincided with the dates of the aerial photography excluding the November 1990 photo. As previously mentioned, the total surveying period was not long enough to detect seasonal trends. Surveys averaged from August 1991 to January 1992 refereed to the November 1991 aerial photo of vegetation cover. Surveys averaged from February to June 1992 referred to the April 1992 aerial photo. All remaining averaged surveys referred to the November 1992 aerial photo. A multivariate analysis was used to compare differences in avian density between the surveyed areas over the survey period.

Avian biomass was used to further detail avian community organization at the project site. The average weight of each species determined the size class in which it belonged (Terres 1980). Size classes were grouped into six categories : a) 0-0.4 kg; b)

0.41-0.8 kg; c) 0.81-1 .2 kg; d) 1.21-1 .6 kg; e) 1.61-2.0 kg; and f) over 2.0 kg.

Calculations for size class biomass for the divided the total avian biomass in each size class by the total area of the transects in the surveyed marsh as follows:


Dt = Ntj / At (7) where Dt = biomass of transect
Ntj = biomass in size class j
At = area of transects




27


The results for avian biomass were averaged over the same three time periods to coincide with the vegetation sampling as for avian density. A multivariate analysis was used to compare biomass between the surveyed areas for significant differences.


Fish Population Sampling


A synoptic study on the fish population of the subsidized and unsubsidized marshes was based on a modified enclosure trap technique (Freeman, et al., 1984). A trash can with a quarter meter square bottom was used to capture fish. The can was quickly pushed down into the water at random locations off the transects in the surveyed marshes. Fish trapped within the can were scooped out by using net's and collected. A total often samples were taken per transect. Sampling events which resulted in no fish being tapped in the can were included as zeros when adding the total number of fish captured.

Sampling occurred three times every other week from June through August in 1993. Collected specimens from ten samples were weighed, sexed, and the species identified. The specimens were preserved in 10% formalin solution for six months for reference.

Fish diversity and evenness were not calculated because efficiencies for sampling were not calculated. Fish densities were calculated by dividing the number of fish captured by one square meter. Biomass of fish densities was calculated by dividing the total biomass of each fish captured by one square meter. Fish densities and biomass were compared between each marsh using a multivariate analysis.


Computer Simulation Model


A computer model of the marsh system, shown in Figure 4, was simulated to test theories related to the affects of external subsidies on community productivity. The model

















Apopka ~





Rain

Water




Peat Nutrients

Z
ird


zz
Z
fi sh
Plants

Sun

insets Detritus














re 4 Dirm of mtuter simulation model Figure 4. Diagram of computer simulation model. c





29


was an aggregated, macroscopic mini model of the marsh that retained the most important components and relationships, simplified from the more complex systems diagram.

The computer program, in Appendix C, was written directly from the systems diagram. Each component in the diagram is a state variable represented by a difference equation. Equations were written in a Basic program based on the interactions of the pathways between the components in the diagram. Values used to calibrate the model were taken from studies conducted in the unsubsidized marsh and the literature (Davis 1946, Robbins 1983, Goldstein 1988, Coveney 1993, Hairston and Hairston 1993, National Research Council 1993, Ann 1994, D'Angelo and Reddy 1994, Ivanoff and Reddy 1994).













RESULTS



Ecological Systems Overview


Given in Figure 5 is a systems diagram showing important processes

occurring in the subsidized marsh. The unsubsidized marshes the same components with the exception of the pump system. Energy sources influencing the marsh system included renewable and nonrenewable sources. Non-renewable sources were further divided into free sources obtained from the environment, and purchased sources which were obtained after the transfer of money. SJWMD was included as the source of money for the purchased nonrenewables.

Renewable sources, sunlight and rain, are shown on the left side of diagram

originating outside the marsh system's border. Free non-renewable sources were drawn in the upper left portion of the diagram. These sources include water, nutrients, and organic matter from Lake Apopka. Purchased non-renewables include fuel used to operate the pumps, construction costs for the physical components of the pump system and for the services required for installation. Also, the costs for operation and maintenance of the flow-way marsh project were represented.

Components within the system boundaries in the diagram were divided into three types: producers, consumers, and storages. Producers include macrophytes and algae which grow using sunlight and nutrients. As shown in the diagram by the pathway connections, the productivity of these plants largely depends on the nutrient concentration in the water column.
30

















Lake FulGoods
Apopkhytes
Main Services







Sunater inere btets
Organic
Matter
Pumps


Mammalsl




Birdss C02 Mocrophytes


Fish


Macro-o Sun inverte - \~Cboe Algoe Detritus brates Seeds












Figure 5. Systems diagram of subsidized marsh.




32


The consumers in the diagram are organized in trophic levels beginning with macroinvertebrates and ending with the bird population. Each trophic level was positioned in the diagram from left to right based on the principle of hierarchical organization according to decreasing amount of energy flux on pathways. Pathways to and from the consumers represent primary food sources and biological wastes. Macroinvertebrates are shown to primarily consume detritus. Fish consume both macroinvertebrates and submerged and floating vegetation. Finally, birds consume both macroinvertebrates and fish. The biological wastes of each species after death, including plants, recycle in the system to add to the nutrient storages. Depreciation of each component and the process was drawn to converge at the drain at the bottom of the diagram.


Emergy Analysis


Emergy analysis tables were developed separately for the subsidized and

unsubsidized marshes. Given in Tables 4 and 5 and summarized in Table 6 and Figure 6 is the emergy analysis of the energy sources of the two marsh systems. Each table was divided into four columns including: name of the energy source contributing to the system, energy, material or dollar flux, solar transformity, and resulting emergy flux. In addition to the driving forces were categorized as renewable and non-renewable sources. Ratios of free to purchased energy (environmental loading) and non-renewable energy to renewable energy (investment ratio) were calculated.

Renewable energy sources for the subsidized marsh and the unsubsidized marsh included solar energy and the chemical potential of rain. The total emergy flux for these flows was the same in both marshes. The emergy contribution of total nitrogen and phosphorus inputs to the unsubsidized marsh was assumed to come from rain only. The





33






Table 4. Annual energy, material and dollar flows and resulting emergy flows supporting 1 hectare of the subsidized marsh



Notes Energy Transformity Emergy
Renewables (J,g,$) (Sej/unit) (E15)
1 Sun 5.41E+09 J 1.00E+00 0.00 2 Rain-chemical potential 6.27E+10 J 1.54E+04 0.97

Nonrenewables - Free
3 Total nitrogen 7.85E+05 g 4.21E+09 3.30 4 Total phosphorus 4.31E+04 g 6.88E+09 0.30 5 Phytoplankton 2.12E+04 J 1.00E+04 0.00 6 Pumped water-chemical potential 2.39E+09 J 2.35E+04 0.06

Nonrenewables - Purchased
7 Liquid fuel 1.21E+1 J 6.60E+04 7.96 8 Construction-structure 5.11E+03 g 6.70E+09 0.03 9 Construction-services 9.34E+01 $ 1.60E+12 0.15 10 Operation and maintenance 9.55E+02 $ 1.60E+12 1.53



Notes to Table 4
1 Solar insolation: 1.29E6 cal/ha/yr (Odum et al. 1987)
(1.29E6 cal/halyr)(4.19E3J/cal) = 5.41E+09 J/ba/yr

2 Rain-chemical potential: 1.27 m/y (Odum et al. 1987)
(1.27 m/yrX 1E10 g/m ha)(4.94 J/g)= 6.27E+10 J/ha/yr

3 Total nitrogen 1.64 mg/1 (Coveney 1993)
(1.64 mg/lX40 cfsX28.3 1/cf)(3.15E7 sec/yr)
(1E-3 g/mg)/74.5 ha)= 7.85E+05 g/ha/yr

4 Total phosphorus: 0.09 mg/l (Coveney 1993)
(0.09 mg/1X40 cfsX28.2 I/cf)(3.15E7 sec/yr)
(1E-3)/(74.5 ha)= 4.31E+04 g/ha/yr





34






Table 4. --cortinued.



5 Phytoplanlkton (as chlorophyll-a): 8.84 E-3 mg/1 (Lowe et al. 1992)
(8.84E-3 mg/1X40 cfsX28.3 l/cf)(3.15E7 sec/yr)
(1E-3 g/mg)(5J/g)/74.5 ha)= 2.12E+04 J/ha/yr

6 Pumped water-chemical potential (Coveney 1993)
(40 cfs)(7.48 gal/cf)(3700 g/galX3.15E7 sec/yr)
((5J/g)/(74.5)= 2.39E+09 J/ha/yr

7 Liquid fuel: 61,532 gal/yr diesel and 1044 gal/yr oil (Coveney 1993)
(6.26E4 gal/yrXl1.46E8 J/gal)/(74.5 ha)= 1.21E+ 11 J/ha/yr

8 Construction- structure : 2.54 lb (Coveney 1993)
(2.54E4 lbX4.5E2 g/lb)/(30 yr usefl life)/(74.5 ha)= 5.11E+03 J/ha/yr

9 Construction-services (Coveney 1993)
(2.2E6 $)/(241.9 ha)/(30 yr uselful life)
(74.5 ha/241.9 ha)= 9.34E+01 $/ma/yr

10 Operation and maintenance (Coveney 1993)
(7.5E5 $)/(241.9 haX74.5/241.9 ha)= 9.55E+02 $/ha/yr





35






Table 5. Annual energy, material and dollar flows and resulting emergy flows supporting 1 hectare of the unsubsidized marsh.


Notes Energy Transformity Emergy
Renewables (J,g,$) (Sej/unit) (E15)
1 Sun 5.41E+09 J 1.00E+00 0.00 2 Rain-chemical potential 6.27E+10 J 1.54E+04 0.97 3 Total nitrogen 1.54E+04 g 4.21E+09 0.06 4 Total phosphorus 6.35E+02 g 6.88E+09 0.00

Nonrenewables - Purchased
5 Construction-services 3.76E+01 S 1.60E+12 0.06




Notes to Table 5
1 Solar insolation: 1.29E6 cal/ha/yr (Odum et al. 1987)
(1.29E6 cal/ha/yr)(4.19E3J/cal) = 5.41E+09 J/ha/yr

2 Rain-chemical potential: 1.27 m/y (Odumet al. 1987)
(1.27 mnyr)(lE10 g/m ha)(4.94 J/g)= 6.27E+10 J/ha/yr

3 Total nitrogen in rain: 1.21 mg/I (Coveney 1993)
(1.21 mg/1l)( IE-3g/mg)(1.27n)(10001/m^3)
(10000 m'2/ha)= 1.54E404 g/ha/yr

4 Total phosphorus in rain: 0.09 mg/1 (Coveney 1993)
(0.05 mg/l)(E-3g/mg)(1.27m)(10001/m^3)
(10000 m2/ha)= 6.35E+02 g/ha/yr

5 Construction-services (Coveney 1993)
(2.2E6 $)/(241.9 ha)/(30 yr uselful life)
(30 ha/241.9 ha) = 3.76E+01 S/ha/yr





36







Table 6. Summary of emergy analysis of both marshes. Emergy Flows Subsidized Marsh Unsubsidized Marsh (E15) (E15) Renewable Emergy 1.0 1.0 Nonrenewable Emergy
Free 3.7 1.0 Purchased 9.7 0.1 Total Emergy Flux 14.3 2.0



Emergy Index Subsidized Marsh Subsidized Marsh Environmental Loading 13.8 0.1 Investment Ratio 2.1 0.1




37


9.7








4.7 14.3






E15 sej/ha/yr



Subsidized Marsh


0.1








2.0 2.0






E15 sej/ho/yr



Unsubsidized Marsh


Figure 6. Summary diagram of emergy analysis.





38


additional lake water pumped into the subsidized marsh increased the emergy of total nitrogen and total phosphorus by two magnitudes higher than that entering the unsubsidized marsh. Free nonrenewable energy sources influencing self-organization in the subsidized marsh included nutrients and phytoplankton pumped into the marsh with lake water and the chemical potential of the pumped water itself The emergy flux of these flows contributed 26% of the total emergy flow to the subsidized marsh.

Only two nonrenewable purchased energy sources were included in the subsidized marsh system that were not also part of the unsubsidized system. These included liquid fuel used to operate the hydraulic pumps and the physical structure of the pump system itself The combination of these two flows contributed 68% of the total emergy flow to the subsidized marsh.

The environmental loading ratio showed a large contrast between the two marshes. In the subsidized marsh the environmental loading ratio was 13.8. The unsubsidized marsh had an environmental loading ratio of 0.1. Investment ratios for the two marshes showed a large difference in the amount of purchased energy necessary to maintain the flows of environmental inputs. The subsidized marsh had an investment ratio of 2.1 and the unsubsidized marsh had an investment ratio of 0.1.

The total solar emergy inputs entering the subsidized marsh were significantly

higher than the unsubsidized marsh system. The total solar emergy input to the subsidized marsh was 14.30 E15 sej ha-1 yr-1. In comparison, the total solar emergy input to the unsubsidized marsh is 1.09 E15 sej ha-1 yr-1. The largest single factor contributing to this difference was the fuel used to run the pump system in the subsidized marsh (7.96 E15 sej ha-1 yr-.)





39


Budgets of Water and Nutrients


Given in Figures 7 and 8 are water and nutrient budgets for both marshes. The pump system supplies 96% of the water entering the subsidized marsh. In the unsubsidized marsh, rain supplies the 100% of the water. In addition, the turnover of the water in the subsidized marsh was determined to be approximately 25 times faster than that of the unsubsidized marsh.

Nutrient budgets in the two marshes were also different. The pump system

supplied 55% of the total nitrogen and phosphorus entering the subsidized marsh, and the nutrient rich peat supplied 35%. Rain supplied the majority of total nitrogen and phosphorus to the unsubsidized marsh (75%).


Vegetative Communities


Richness of Vegetative Cover Types


Figures 9-12 show the vegetative cover of the overall marshes for four time periods. Over the avian survey period, richness of vegetative cover types changed following different patterns in each marsh as shown in Figure 13. Richness in the subsidized marsh increased between November 1990 to November 1991 by one index level from 2.86 to 3.86. In April 1992 richness decreased to 3.25, and remained at that level in November 1992.

Richness was highest in the unsubsidized marsh in November 1990 at 5.00. In November 1991 and April 1992 richness decreased. However, by November 1992, richness in the unsubsidized marsh had increased again to near its original level at 4.69.

Using a paired t-test it was determined that richness between the subsidized and the unsubsidized marsh was significantly different (n = 13, df= 5.5, p = 0.02).




40







Pumped lake water 5. Pumped water 222.6 225.0





E5 m3/yr

Subsidized Marsh (9 day turover)






Rain 2. Evapotranspiration
3.8 2.9





E5 m3/yr

Unsubsidized Marsh
(221 day turover)

Figure 7. Water budgets for both marshes.





41











i Tn Tp









Subsidized Marsh












0.84 0.01
4.61.2 0.0.8




E5 g/yrUnsubsidized Marsh Figure 8. Nutrient budgets for both marshes.




42


NOVEMBER 1990








SCALE: METERS NORTH
250 250
500
LEGEND

Herbs M Floating Aquatics
N Shrubs M Typha < Open Water
Open Water Typha >= Open Water
11 Emergents Typha Community

Figure 9. Map of vegetative cover for November 1990.




43



NOVEMBER 1991











SCALE: METERS NORTH
250 250

500
LEGEND

E Herbs I Floating Aquatics

Shrubs Typha < Open Water

Open Water Typha >= Open Water

IW Emergents U Typha Community Figure 10. Map of vegetative cover for November 1991.




44


APRIL 1992








SCALE: METERS NORTH
250 250
500
LEGEND

U Herbs Floating Aquatics
U Shrubs Typha < Open Tater
Open Water Typha >= Open Water
1 Emergents U Typha Community Figure 11. Map of vegetative cover for April 1992.




45



NOVEMBER 1992











SCALE: METERS NORTH
250 250

500
LEGEND

ni Herbs Floating Aquatics

Shrubs Typha < Open Water

Open Water Typha >= Open Tater

u Emergents U Typha Community Figure 12. Map of vegetative cover for November 1992.





46





6.00




5.00




4.00




a 3.00




2.00 1.00




0.00 4

Nov-90 Nov-91 Apr-92 Nov-92 U Subsidized Marsh [0 Unsubsidized Marsh Figure 13. Vegetative cover richness for both marshes.




47


Vegetative Structure Complexity


Complexity, measured as the fractal dimension of vegetative structure, was similar in the subsidized and unsubsidized marshes (n = 8, df = 7, p = .63.) In addition, complexity appeared to change in a similar pattern in both marshes as shown in Figure 14. Each marsh seemed to display moderate complexity throughout the survey period.


Percent Cover of Vegetative Cover Types


Figures 15 and 16 show the vegetative cover of the subsidized and unsubsidized marsh over the two year period. Vegetative cover in the subsidized marsh changed significantly over time (n = 36, df= 11, p = 0.01) as well as in the unsubsidized marsh (n = 36, df= 11, p = 0.03.)

In November 1990, the two marshes had significantly different distribution of cover types (n = 18, df= 8, p = 0.01). The subsidized marsh was dominated by herbs (86.17%.) Shrub cover and open water were the only other predominant cover types in the subsidized marsh, but were at less than 10% cover.

Although in the unsubsidized marsh herbs (43.04%) were the predominate cover type, shrub cover (29.79%) was greater in this marsh than in the subsidized marsh. The cover of floating aquatics and Typha dominated community were also greater than 10% in the unsubsidized marsh.

Overall, vegetative cover in the two marshes had changed considerably over the

previous year. In November 1991, the percent cover of the various cover types in the two marshes were again significantly different ( n = 18, df= 8, p = 0.01). Typha >= open water in the subsidized marsh covered the greatest area (34.20%), and Typha < open water had the next highest percent cover (28.58%).





48





2.00 1.80 1.60


1.40


8 1.20





S0.80


0.60 -


0.40


0.20


0.00

Nov-90 Nov-91 Apr-91 Apr-92 Nov-92 U Subsidized Marsh OD Unsubsidized Marsh






Figure 14. Vegetative cover complexity for both marshes.







49





Nov-90 100.00 80.00 60.00

40.00 20.00

0.001
Habs Shrubs Open Water Flotng Emeats Typha < Open Typha Opmn Typha Aquai Water Wate Community


Nov-91 100.00 80.00"

60.0040.00 20.00

0.00 I "
Habs Smubs Op Water Floating Emagaes Typha < Op Typha > Opa Typha Aquatic Waer Wate Coamumity


Apr-92 100.00

80.00

S60.00

40.00 20.00

0.00
Herbs Shrmbs Open Warer Floating Emagents Typha < Opm Typha Open Typha Aquats Wat Wat Community


Nov-92 100.0080.00

60.00



0.00


Habs Shrubs Opa Water Floating Emeagats Typha < Opem Typha >= Opem Typha Aquatis Wate Water Commumty








Figure 15. Vegetative percent cover of subsidized marsh.







50





Nov-90 100.00 80.00

U 60.00







S80.00
20.00

0.00 _ I+ Herbs Shrubs Open Water Floaing Em Its Typha < Opm Typha >Op Typha AquaMci Wsat Wate Coamunity


NApv-9 100.00

80.00


S60.00
40.00 20.00


Habs Shrumbs Op Wate Flaetmg Emengats Typha < Opm Typha >- Opm Typha Aquati Water Wate COmmurty


ApNovr-92 100.00 80.00u 60.00

S40.00
20.00

0.00
Hubs Shn1bs Opm Water Floaing Emagants Typha < Open Typha Open Typha Aqua i Wate War Community


percent cover of unsubsidized mv-92 100.00

11 80.00 c 60.00

40.00


0.00 U
Habs Shrubs OpnWat Floating EMrCgaris Typha








Figure 16. Vegetative percent cover of unsubsidized marsh.





51


Shrubs were the predominate cover type in the unsubsidized marsh in November 1991 at 59.86%. The next highest percent cover was open water at 15.71%. In addition, Typha >= open water had increased to 10.88% cover in the unsubsidized marsh.

In April 1992 the percent cover of the various cover types had significantly

distributions (n = 18, df= 8, p = 0.03). Both marshes reflected a progression towards more dense cover types that included TyPha spp. In the subsidized marsh the Typha Community had increased to 57.51% cover. Typha >= open water and open water were also important cover types in the subsidized marsh at this time at 18.32% and 17.51%, respectively.

In April 1992 Typha Community had become the most important cover type in the unsubsidized marsh covering 70.71%. For the first time in the unsubsidized marsh, emergents began to become a significant cover type at 12.74% in April 1992.

In November 1992 the marshes again had significantly different distributions of percent cover (n = 27, df= 8, p = 0.02). The subsidized marsh was covered mostly by Typha Community at 66.70% cover. The next most important cover type was Typha >= open water at 14.36% cover. The remaining cover types present were represented at a cover of less than 10% each.

Typha Community was also the predominate cover type in the unsubsidized marsh covering 48.61%. However, other cover types also began to become more evident such as emergents (21.53%) and Typha >= Open Water (18.12%.) Table 7 summarizes the results of the vegetative community structure study in both marshes.












Table 7. Summary of vegetative community structure. Parameter Subsidized Marsh Unsubsidized Marsh Significant Difference

Richness 3.31 4.32 n = 13, df= 5.5, p = 0.02 Complexity 1.45 1.49 Dominate Cover Type (%)

Nov-90 Herbs Herbs n = 18, df = 8, p = 0.02 86.17% 43.04% Nov-91 Typha >= Open Water Shrubs n = 18, df = 8, p = 0.01 34.20% 59.86% Apr-92 Typha Community Typha Community n = 18, df= 8, p = 0.03 34.07% 15.98% Nov-92 Typha Community Typha Community n = 18, df= 8, p = 0.02 66.70% 48.61%




53


Avian Community Structure


Diversity of Avian Community


Average avian species diversity in the two marsh areas was lowest in the

subsidized marsh and highest in the unsubsidized marsh as shown in Figure 17. The subsidized marsh had an average species diversity of 2.65, and the unsubsidized marsh had an average diversity of 3.04. Average diversity among the subsidized and unsubsidized marshes was significantly different (n = 54, df= 4, p = 0.02) over the time both marshes were surveyed.

After an initial increase, averaged diversity in the subsidized marsh seemed to

gradually decrease over the survey period. The change in diversity over the survey period was significant (n = 14, d = 5, p = 0.04.)


Evenness of Avian Community


In Figure 18 it is shown that evenness for the subsidized marsh did not differ

significantly over time (n = 14, df= 5, p = 0.08). Average evenness was 0.67. Results for evenness revealed that the unsubsidized marsh had more species of greater abundance than the subsidized marsh. Average evenness for the unsubsidized marsh was 0.82. Evenness was significantly different between the subsidized and unsubsidized marsh (n = 54, df= 4, p = 0.02).















4Shannon Diversity Index Shannon Diversity Index



Aug-91 Aug-91 Sep-91 Sep-91 Nov-91 Nov-91 r. Jan-92 Jan-92 W Feb-92 Feb-92

Apr-92 Apr-92 May-92 May-92 Jun-92 Jun-92

Aug-92 Aug-92 l

Sep-92 Sep-92 O Oct-92 m. Oct-92

Nov-92 mm Nov-92

Dec-92 EN Dec-92

SJan-93 mmJan-93

Feb-93 m m Feb-93 Mar-93 m m Mar-93 Apr-93 m l Apr-93 May-93 m m May-93 Jun-93 A Jun-93 Mean E E Mean

-t















Shannon Evenness Index Shannon Evenness Index C o oo- c oo o o


i Aug-91 Aug-91

Sep-91 Sep-91 Nov-91 Nov-91 Jan-92 Jan-92 Feb-92 Feb-92 Apr-92 Apr-92

May-92 May-92 Jun-92 Jun-92





0 Oct-92 . Oct-92

Nov-92 Nov-92 c"

Dec92 Dc-92

SJan-93 Jan-93

Feb-93 Feb-93 Mar-93 Mar-93 Apr-93 Apr-93 May-93 May-93 Jun-93 Jun-93 Mean Mean


____ ____ ___ ____ ___ ____ ___ ____ ___ ____ ___ ____ _ U





56


Density of Avian Species


Shown in Figures 19 and 20 are avian densities for the subsidized and unsubsidized marshes. Data were aggregated to correspond to data of aerial photos. The results for each transect individually by marsh is presented in Appendix B for the subsidized marsh and in Appendix C for the unsubsidized marsh.

Avian density increased over the survey period in the subsidized marsh (n = 14, df= 6, p = 0.01) with some fluctuation. Overall average avian density (18.48 birds ha-1) remained high in the subsidized marsh throughout the survey period. In November 1991, the average avian density decreased to 16.58 birds ha-1. By April 1992 average density had begun to increase. In November 1992, avian density averaged 20.18 birds ha-1.

During the period that the unsubsidized marsh was surveyed the average avian density was 7.07 birds ha-1. Avian density did not change significantly over the survey period (n = 8, df= 2, p = 0.08.)

In the subsidized marsh, black birds had the highest average density of all

taxonomic groups over the survey period representing 46.11% of the overall density. In contrast, gallinules had the highest average density of all other taxonomic groups in the unsubsidized marsh for the November 1992 survey period. Gallinules represented 28.57% of the overall density in the unsubsidized marsh. In April 1993, black birds had the highest average density in the unsubsidized marsh with 27.44% of the overall density.

The taxonomic groups were compared among the two marshes for overall

differences. Overall, the feeding types had significantly different densities between the marshes (n = 21, df= 6, p = 0.02). Within each marsh, the density of the individual feeding types were also significantly different (n = 98, df= 9, p = 0.04).







57





Nov-91 25.00 20.00

. 15.00

10.00

5.00


Gallinules Wading Birds Black Birds Insectivorous Duds ibis Othe Total Passnnes


Apr-92 25.00

20 00

. 15.00

10.00

= 5.00

0.00
Gallinules Wading Birds Bladk Birds Insectivorous Duds ibis Othe Total Pass aines


Nov-92 25.00


. 15.00

10.00

c 5.00

0.00 I
Gallinules Wading Birds Bladk Birds Insativorous Ducks iis Othe Total Paseines


Mean

25.00

S20.00

S15.00

10.00 5.00

0.00 M L
Gallinules Wading Birds Black Birds Irseivorous Dudks ibis Othe Total Passaines







Figure 19. Overall avian density in subsidized marsh.







58





Nov-91

25.00

20.00

. 15.00

10.00

M 5.00

0.00
Gallinules Wading Birds Blade Birds Insectivorous Dudes ibis Other Total Passmnes


Apr-92 25.00

20.00 15.00 10.00

c 5.00

0.00*
Gallinules Wading Birds Black Birds Insectivorous Ducks ibis Other Toal Passees


Mea

25.00 20.00

S15.00

10.00

m 5.00

0.00
Gallinules Wading Birds Blade Birds Imetivarous Dudcs ibis Other Total Passennes








Figure 20. Overall avian density in unsubsidized marsh.





59


Biomass of Avian Community


Table 8 lists the size classes used for this study given the avian species found in both marshes. Given in Figures 21 and 22 is avian biomass over the survey period in the subsidized marsh and unsubsidized marsh. Overall, the size classes had significantly different biomass between the marshes (n = 21, df= 6, p = 0.03). Within each marsh, the biomass of the individual size classes were also significantly different (n = 21, df= 2, p = 0.03). Changes over time in biomass were not significant over the survey period in either marsh (n = 22, df= 2 , p = 0.09).

Overall avian biomass in the subsidized marsh averaged 5.11 kg ha-1 over the entire survey period. Average avian biomass in the subsidized marsh did not change significantly over the survey period (n = 14, df= 1, p = 0.06.) Average avian biomass in the unsubsidized marsh was 2.22 kg ha-1 and did not significantly change over its survey period (n = 12, df = 1, p = 0.10).

In the subsidized marsh, birds weighing 0.41-0.80 kg had the highest average

biomass of all size classes contributing 49.12% of the overall biomass. Moreover, birds weighing 0.41-0.80 kg had the highest average biomass of all feeding types during each of the survey periods. Birds weighing between 0-0.4 kg had the next highest average biomass of all size classes in the subsidized marsh over the survey period. This size class contributed 30.72% of the overall biomass.

Birds weighing 0-0.41 kg had the highest average density (39.19% of overall

biomass) in the unsubsidized marsh. In April 1993, this size class contributed 43.24% of the overall biomass. The 0.41-0.8 kg size class had the next highest average biomass and contributed 29.28% of the overall biomass. This size class remained unchanged over the survey period.





60







Table 8. Avian species by size class.



Size Class (kg) Common Name Average Weight (kg)
0 - 0.4
American kestrel 0.11 Barn swallow 0.02 Belted kingfisher 0.15 Bluejay 0.03 Blue wing teal 0.09 Boat tail grackle 0.11 Bue-gray gnatcatcher 0.04 Carolina wren 0.02 Cattle egret 0.34 Chimney swift 0.02 Common grackle 0.11 Common moorhen 0.40 Common snipe 0.13 Common yellow throat 0.01 Eastern kingbird 0.04 Eastern phoebe 0.02 Foresters tern 0.11 Greater yellow legs 0.21 Green back heron 0.18 Ground dove 0.00 Indigo bunting 0.02 Kill deer 0.09 Least bittern 0.07 Little blue heron 0.40 Logger headed shrike 0.05 Marsh wren 0.02 Mourning dove 0.00 Northern cardinal 0.04 Northern mocking bird 0.06 Palm warbler 0.01 Pied billed grebe 0.30 Purple gallinule 0.40 Red wing black bird 0.03





61







Table 8. --continued.



Size Class (kg) Common Name Average Weight (kg)
0 - 0.4
Sedge wren 0.01 Snowy egret 0.37 Song sparrow 0.02

0.41 - 0.80
American bittern 0.68 American coot 0.76 American widgeon 0.79 Black crown night heron 0.66 Black neck stlit 0.43 Blue grosbeak 0.41 Fulvous whistling duck 0.76 Gadwall 0.79 Glossy ibis 0.79 Hooded merganser 0.70 King rail 0.43 Northern herrier 0.45 Red shoulder hawk 0.64 Wood duck 0.68 Yellow crown night heron 0.66

0.81 - 1.20
Great white egret 1.02 Mallard duck 1.18 Mottled duck 1.02 Northern pintail 0.91 Northern shoveler 1.00 White ibis 0.91

1.21 - 1.60
Anhinga 1.36 Double-crested cormorant 1.36





62







Table 8. --continued.



Size Class (kg) Common Name Average Weight (kg)
1.21 - 1.60
Osprey 1.36

>2.10
Bald eagle 4.54 Black vulture 2.28 Great blue heron 2.95 Turkey vulture 2.20







63





Nov-91

8.00 7.00
o 6.00
5.00

3.00 200 1.00
000
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total

Size Classes (kg)



Apr-92

8.00 7.00
6.00
5.00
4.00

2.00
I 1.00
0.00
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total

Sie classes (kg)



Nov-92

8.00
7.00
e 6.00Is 5.00
4.00 3.00
2.00
1.00
0.00 (
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total

Size Classes (g)



Meen

8 .00 7 00

5.00
4.00 3.00 '
2.00 1
" !.00
0.00
0-0.4 0. 8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total

Size Clases (kg)









Figure 21. Overall avian biomass in subsidized marsh.







64





Nov-92

8.00
7 00 6.00 54.00
,4 00 3 00 2.00
100 0.00
0-0.4 0.41-08 081-1.2 1.21-1.6 1.61-2.0 >2.0 Total

Size Clases (kg)



Apr-93


8 00 7. 00 6. 00 5 4.00 3.00 2.00
S1. 00
-0.00.
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Clases (kg)



Mean

8. 00 6.00
S5.00

43.00

2.00
3 1.00
0.00
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total

Size Classe (kcg)








Figure 22. Overall avian biomass in unsubsidized marsh.





65


Fish Density and Biomass


Although similar species were found in the subsidized and unsubsidized marshes, fish densities were significantly different (n = 30, df= 5, p = 0.01). The subsidized marsh had an average density of 230 fish m-2 as shown in Figure 23. Average fish density in the unsubsidized marsh was 165 fish m-2.

Fish species found in the subsidized marsh included Gambusia affinis, Heterandria formosa, and Ictalurus nebulosus. G. affinis, H. formosa, and Talapia spp. were the species found in the unsubsidized marsh. Although subsidized marsh samples did not include Talapia spp. there were sightings of large individuals and nests in open areas. G. affinis was at a higher density in the subsidized marsh, but a higher percentage was found in the unsubsidized marsh. Of the fish collected in the subsidized marsh, 76.09% were G. affinis. In the unsubsidized marsh, 81.82% were G. affinis. The second most abundant fish species in the subsidized marsh was H. formosa (17.39% of overall catch), and this species was also less abundant in the unsubsidized marsh (18.18% of overall catch.) Fish biomass was also significantly different in each marsh. In the subsidized marsh, fish biomass was at 6.44 kg m-2. The unsubsidized marsh had 4.39 kg m-2 of fish. By far the greatest biomass offish was G. affinis contributing about 80.01% of the total in the subsidized marsh, and 85.87% of the total in the unsubsidized marsh. Table 9 summarizes the results of the wildlife study.


Computer Simulation Model


Figure 24 shows the results for the simulation of the unsubsidized marsh when fuel inputs and nutrients from the hypereutrophic lake are zero. Each storage in the marsh system had an initial level of zero.






66





a Daityoffih S250 200
150 100



GmHLkT aipnspp Iclirs Tod Isid sh Unsubamiirsh b Hasoffhh

6.00 0





















adums Hrxlia Tapapp. Iskrus Tota ISutabdi ddrsh OUmuubfddrmsh








Figure 23. Results offish survey including a) density and b) biomass.












Table 9. Summary of avian and fish community structure. Parameter Subsidized Marsh Unsubsidized Marsh Significant Difference

Avian Diversity 2.65 3.04 n = 54 , df= 4, p = 0.02 Avian Evenness 0.67 0.82 Avian Density 18.48 ha-I 7.07 ha-I n = 54, df= 6, p = 0.02 Avian Biomass 5.11 kg ha-I 2.22 kg ha-I n = 54, df= 6, p = 0.03 Fish Density 230 m-2 165 m-2 n = 30, df =5, p = 0.01 Fish Biomass 6.44 kg m-2 4.29 kg m-2 n = 30, df =5, p = 0.03





68




Fuel- 0%


300.00



250.00 /

- Nutrients 200.00 \ - Plants

* - Insects

iFish


1 0 0 .0 0 ........ ........ . . . . . .





0.00 4


0 15 30 45 6 0 Years





Figure 24. Simulation of unsubsidized marsh.





69


After approximately 75 years, the storages of nutrients, plant biomass, insects, fish, and birds reach steady state. This steady state was reached when each storage reached 100% of the marsh's carrying capacity.

When the pump system is turned on using 10% of the fuel used in the subsidized marsh, the storages reach a new steady state after approximately 65 years as shown in Figure 25. Plant biomass does not exceed the carrying capacity of the unsubsidized marsh; however, it does reach steady state approximately five years sooner.
Insect, fish, and bird storages also increase at faster rates. Moreover, each of these storages have an increase in carrying capacity with the increased nutrient subsidy. The storage of insect biomass is increased by approximately 10% while fish and bird biomass storages increased by 35% above the carrying capacity of the unsubsidized marsh.
An increase in fuel of 50% of that used in the subsidized marsh had the effect of





70




Fuel- 100/


300.00


, \
250.00 /

Nutrients
200.00 - Plants



150.00 - Fish ,Fish


""- Birds 100.00 -- -
! !
I i

50. 00 !
I I


!/



0 15 30 45 6 0 Years





Figure 25. Simulation of marsh with 10% added subsidy.





71




Fuel 50/o 700.00


600.00


500.00
. Plants : 400.00 Insects

- Fish 300.00
Birds 200.00


100.00 - -I


0.00
0 1 5 3 0 4 5 6 0 Years





Figure 26. Simulation of marsh with 50% added subsidy.





72




Fuel 100%/o 1000.00

900.0000 \

800.00
Nutrients 700.00
i 0...Insects 500.00 -- Fish 400.00 - Birds

300.00






0.00
0 15 30 45 60 Years





Figure 27. Simulation of marsh with 100% added subsidy.





73


shown in Figure 28. Moreover, steady state was reached after only 28 years. The wildlife storages had greatly increased their carrying capacities, and had reached those levels over forty years sooner than in the unsubsidized marsh.
Ten times the fuel (or 1000%) used in the subsidized marsh enables the marsh to
reach steady state after approximately 25 years as shown in Figure 29. In addition, greater flucuations are shown in the biomass storages. Biomass storages all reached a higher carrying capacity much sooner than the unsubsidized marsh.
Figure 30 summarizes the changes in biomass carrying capacity with different levels of fuel used. It appears that the increases may be logistic; however, the model overflowed after more than 15 times the fuel used in the subsidized marsh was simulated.
Seven sensitivity tests were performed to test the response of the computer model to various conditions. The first two tests were simulations of the unsubsidized marsh only. The remaining tests compared simulations of both the unsubsidized marsh and the subsidized marsh (100% fuel) under the same conditions.
Figure 31 shows the results of running the unsubsidized marsh supplied with only the nutrients in rain. All of the storages reached a lower steady state than in the original simulation. In addition, the animal storages all soon began to decrease, and therefore their maximum carrying capacity under these conditions was probably very low. With only a small reduction in nutrients, as shown in Figure 32, the biological components of the model are more successful in reaching a carrying capacity more similar to the original.
Figures 33 and 34 show the response of the unsubsidized marsh and the subsidized marsh if the insects required more resources to survive. Given this scenario, the macroinvertebrates pursue the available resources much more vigourously and in turn their numbers multiply more quickly. The increased abundance of macroinvertebrates is then quickly consumed by the fish and birds elevating their populations above what was found in the original simulations.





74




Fuel 500% 350000 3000.00


250.00 N e
Plants



- Fish 1500.00 1000.00


500.00 I r


0.00f
0 1 5 3 0 4 5 6 0 Years





Figure 28. Simulation of marsh with 500% added subsidy.





75




Fuel- 1000/ 7000.00


6000.00

00 -----Nutrients
5000.00 - 0
... Plants 0000 Insects
S3000.00


2000.00





0.00 .
0 1 5 3 0 4 5 6 0 Years





Figure 29. Simulation of marsh with 1000% added subsidy.





76




Percent Increase After 70 Years 2500 2000



1500 1000



500




0 10 50 100 500 1000 Percent Fuel Increase SNutrients E Plants El Insects [I Fish OBirds





Figure 30. Summary of simulation results after 70 years.





77




Rain Only (Unsubsidized Marsh) 60.00

I

50.00 i

Nutrients 40.00 .............. .
40.00 -- Plants Insects 30.00 -- Fish

- Birds 20.00



10.00



0.00
0 15 30 43 60 Years





Figure 31. Simulation of unsubsidized marsh receiving nutrients from rain only.





78




90% Peat (Unsubsidized Marsh) 250.00




200.00 \
Nutrients ...... ....... Plants

Insects







50.00 .




0.00
0 1 5 3 0 4 5 6 0 Years







Figure 32. Simulation of unsubsidized marsh with peat contributing only 90% of original nutrients.





79




Insects Double Intake Rate (Unsubsidized Marsh)


1200.00



1000.00 i

Nutrients 800.00 Plants oFi:
3 .......... Insects

-600.00 - Fish



400.00



200.00



0.00
0 1 5 3 0 45 6 0
Years








Figure 33. Simulation of unsubsidized marsh with insects requiring double their food
requirements.





80




Insects Double Intake Rate (Subsidized Marsh)


3000.00



2500.00

Nutrients 2000.00 ............ . Plants

Insects 1500.00 - - Fish I- Birds 1000.00 -


500.00



0.00
0 15 3 0 4 5 6 0 Years






Figure 34. Simulation of subsidized marsh with insects requiring double their food
requirements.





81


If fish were the element to require more resources, then the affect on the other populations is much different as shown in Figures 35 and 36. The macroinvertebrate population is eventually depleted as the fish and birds consume them. In addition, the increased population of fish also benefits the bird population allowing it to be sustained without the macroinvertebrate population.
When the food requirements of birds is increased as in Figures 37 and 38, the

macroinvertebrate population is not delepleted. However, competetion between the fish and birds appeared to develop with fish receiving the negetative consequences of this relationship. As the fish population decreases, some feeding pressure on the macroinvertebrates is eventually elievated.

Figures 39 and 40 show the results of periodic disturbances to the marshes using fish kills as an example. Immediately after the fish kill, the macroinvertebrate population increases while the bird population temporarily decreases. The reverse occurs as the fish population recovers.

Increases in migration allow rapid exploitation of the marcroinvertebrate

population as shown in Figures 41 and 42. The growth of the populations, however, is soon limited as each resource nears its carrying capacity.





82




FishDouble Intake Rate (Unsubsidized Marsh)


2500.00



2000.00
Nutients ....... Plants
-1500.00 Insects "" Fish S1000.00 Birds



500.00



0.00
0 15 30 45 60 Years






Figure 35. Simulation of unsubsidized marsh with fish requiring double their food
requirements.





83





Fish Double Intake Rate (Subsidized Marsh)


4000.00 3500.00


3000.00 Nutrients . Plants
* 2500.00
. Insects C 2000.00 -- Fish

-" Birds 1500.00 -_1000.00 500.00


0.00
0 1 5 3 0 4 5 6 0 Years






Figure 36. Simulation of subsidized marsh with fish requiring double their food
requirements.





84




Birds Double Intake Rate (Unsubsidized Marsh)


300.00



250.00

Nutrients 200.00 Plus .. Insects ~ 50.00 -- Fish



100.00



530.00 - i



0.00
0 1 5 3 0 4 5 6 0 Years






Figure 37. Simulation of unsubsidized marsh with birds requiring double their food
requirements.





85




Birds Double Intake Rate ~Subsidized Marsh)


1000.00 900.00 800.00
Nutrients 700.00
Plants






600.00 300.00

200.00 -/ ' -- - - - - - - -

10 0 .0 0 . ...... ..... ...............................

0.00
0 1 5 3 0 4 5 6 0 Years






Figure 38. Simulation of subsidized marsh with birds requiring double their food
requirements.





86




Habitat Disturbance (Unsubsidized Marsh)






200.00


Plants
S150.00 t

Fish





50.00
OO~./



0.00
0 0 1 5 3 0 4 5 6 0 Years






Figure 39. Simulation of periodic fish kill in unsubsidized marsh.





87




Habitat Disturbance (Subsidized Marsh) 1000.00

900.00 8M.00
soo.oo
� Nutrients 700.00
Plats 600.0..... Insects 500M.00-- Fish

400.00 - Birds

300.00

200.00 100.00

0.00
0 15 3 0 4 5 6 0 Years






Figure 40. Simulation of periodic fish kill in subsidized marsh.





88




Increased Migration (Sx) (Unsubsidized Marsh)


140.00


120.0 ;


100.00
Plants

* 80.00 .........- Insects

- Fish 40.00


20.00



0.0
0 1 5 3 0 45 6 0 Years






Figure 41. Simulation of increased migration in unsubsidized marsh.





89




Increased Migration (5S) (Subsidized Marsh)


700.00 600.00


0Nutrients
500.00
Plants

400.00 -Insects "-.. .. Fish

300.00 200.00


100.00 -- ......-............................---------0.00
0 1 5 3 0 4 5 6 0 Years






Figure 42. Simulation of increased migration in subsidized marsh.




Full Text
133
Table C-1. continued.
190 K24 = .0006
195 K25 = .2
200 k26 = .207
205 K27 = .001
210 K28 = .001
215 K29 = .0025
220 K30 = .002
225 K31 = .065
230 K32 = .025
235 K33 = .0001
240 K34 = .0015
245 K35 = .00105
250 K36 = .01
255 K37 = .01
260 k38 = .0007
265 k40 = 21
270 k41 =42
275 k42 = 1
280 k43 = 1.75
285 k44 = .1
290 k45 = .021
295 k46 = 42
300 k47 = 3.5
305 k48 = 3.5
310 z = 1
315 IF T < 10 THEN zz = 2 ELSE zz = 0
320 ALBEDO = SUN / (1 + (K0 PLANTS NUTRIENTS))
325 DWATER = K1 RAIN + K2 WATER FUEL K3 WATER FUEL
- K4 WATER K5 WATER K6 WATER
330 DNUTRIENTS = k40 RNUTRIENTS + k41 PNUTRIENTS
+ k42 LNUTRIENTS FUEL + k43 (DETRITUS + INSECTS +
FISH + BIRDS) k44 LNUTRIENTS FUEL k45 PLANTS *
NUTRIENTS ALBEDO k46 NUTRIENTS k47 NUTRIENTS -
k48 NUTRIENTS
335 DPLANTS = K14 ALBEDO PLANTS NUTRIENTS
- K15 ALBEDO PLANTS NUTRIENTS K16 PLANTS K17 *
PLANTS K18 PLANTS FISH + z zz
340 DDETRITUs = K19 PLANTS K20 DETRITUS K21 DETRITUS
- K22 DETRITUS INSECTS + k39 NUTRIENTS


Fuel-10%
Nutrients
Plants
Insects
Fish
Girds
Years
Figure 25. Simulation of marsh with 10% added subsidy.


26
Di Nij / Ai (6)
where Di = density of transect i
Nij = number of birds in taxonomic group j
Ai = area of transects
Calculations for overall avian density for each marsh divided the total number of
birds in each taxonomic group by the total area of all surveyed transects in that marsh.
Total area in the subsidized marsh using four transects was 15.2 ha. The area of two
transects used in the unsubsidized marsh totaled 10.50 ha.
The survey results were averaged over three six month time periods to provide a
more general representation of temporal changes in density. These time periods coincided
with the dates of the aerial photography excluding the November 1990 photo. As
previously mentioned, the total surveying period was not long enough to detect seasonal
trends. Surveys averaged from August 1991 to January 1992 refereed to the November
1991 aerial photo of vegetation cover. Surveys averaged from February to June 1992
referred to the April 1992 aerial photo. All remaining averaged surveys referred to the
November 1992 aerial photo. A multivariate analysis was used to compare differences in
avian density between the surveyed areas over the survey period.
Avian biomass was used to further detail avian community organization at the
project site. The average weight of each species determined the size class in which it
belonged (Terres 1980). Size classes were grouped into six categories : a) 0-0.4 kg; b)
0.41-0.8 kg; c) 0.81'1 .2 kg; d) 1.21-1 .6 kg; e) 1.61-2.0 kg; and f) over 2.0 kg.
Calculations for size class biomass for the divided the total avian biomass in each size class
by the total area of the transects in the surveyed marsh as follows:
Dt = Ntj / At (7)
Dt = biomass of transect
Ntj = biomass in size class j
At = area of transects
where


Table A-2. -continued.
Common Name
Teb-9'2
Apr-92 May-92
"Jh-92
Aug-92
American bittern
2
0
5
0
1
American coot
5
3
1
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
3
2
17
4
30
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
5
7
12
6
8
Common snipe
1
0
0
0
0
Common yellow throat
1
2
0
0
0
Double-creasted cormorn
0
0
0
0
1
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
1
0
0
0
Foresters tern
0
0
0
0
0
Fulvous whistling duck
2
1
4
0
0
Gad wall
0
0
0
0
0
Glossy ibis
0
1
0
0
4
Great blue heron
0
0
0
0
1
Great white egret
0
1
1
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
0
0
1
6
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
0
0
0
5
3
Little blue heron
0
1
1
0
0
Logger headed shrike
0
0
0
0
0


27
The results for avian biomass were averaged over the same three time periods to
coincide with the vegetation sampling as for avian density. A multivariate analysis was
used to compare biomass between the surveyed areas for significant differences.
Fish Population Sampling
A synoptic study on the fish population of the subsidized and unsubsidized marshes
was based on a modified enclosure trap technique (Freeman, et al., 1984). A trash can
with a quarter meter square bottom was used to capture fish. The can was quickly pushed
down into the water at random locations off the transects in the surveyed marshes. Fish
trapped within the can were scooped out by using net's and collected. A total of ten
samples were taken per transect. Sampling events which resulted in no fish being tapped in
the can were included as zeros when adding the total number of fish captured.
Sampling occurred three times every other week from June through August in
1993. Collected specimens from ten samples were weighed, sexed, and the species
identified. The specimens were preserved in 10% formalin solution for six months for
reference.
Fish diversity and evenness were not calculated because efficiencies for sampling
were not calculated. Fish densities were calculated by dividing the number of fish
captured by one square meter. Biomass of fish densities was calculated by dividing the
total biomass of each fish captured by one square meter. Fish densities and biomass were
compared between each marsh using a multivariate analysis.
Computer Simulation Model
A computer model of the marsh system, shown in Figure 4, was simulated to test
theories related to the affects of external subsidies on community productivity. The model


ACKNOWLEDGEMENTS
I am grateful to my committee members for their individual guidance and
assistance in the classroom and in the field. Dr. Mark Brown consistently gave me the
courage to spit in the face of disaster. Dr. G. Ronnie Best taught me to tread without
fear into new and exciting wetland frontiers. And Dr. Stephen Humphrey showed me
that I can boldly evaluate new and traditional view points in community ecology
without permission.
Other professors also greatly influenced my development as a systems
ecologist. Most notable were Dr. Howard T. Odum and Dr. David Scienceman. Both
provided me with new ways to look at the world and its future.
All my friends who helped me with avian and fish surveys deserve my special
thanks. In particular I wish to thank Chuck Graham for helping me obtain a research
project and for the use of his data. In addition, I wish to thank Ken Clough, Rodney
Pond, David Day, John Stenberg, David Clayton, Mark and Amelda Clark, Harish
Ramakarishna, Valerie Enck, Michelle Piazza, Sergio Lopez, Fred Gaines, and anyone
else who risked life and limb among the alligators.
I especially thank my husband, Juan Jorge Haberkom, for helping me conduct
surveys and providing technical advice to improve my analysis. His patience and
unending optimism kept me going even when the odds were clearly against me.
I am also indebted to Silvia Romitelli, David Clayton, and Dave Tilley for their
support and patience during the last critical weeks of my thesis writing.
m


79
Insects Double Intake Rate (Unsubsidized Marsh)
Nutrients
Plants
Insects
111 Fish
Birds
Years
Figure 33. Simulation of unsubsidized marsh with insects requiring double their food
requirements.


Figure 4. Diagram of computer simulation model.
to
00


2
Plan of Study
The research for this thesis tested theories concerning the affect of an external
subsidy on ecosystem structure and organization. Two newly established marshes (one
receiving nutrient enriched lake water and the other not receiving the subsidy) were
studied. The effect of the external subsidy was evaluated by comparing properties of the
vegetative and avian communities in the wetland receiving nutrient enriched lake water
with properties in the nearby unsubsidized wetland.
An emergy analysis was used to determine the energy sources influencing self
organization of each wetland system. In addition, budgets of water and nutrients for each
marsh were evaluated and compared. A comparison of the vegetative community
structure emerging in each marsh was presented using a landscape scale perspective. The
vegetative cover of the subsidized marsh was determined, and the spatial organization of
the vegetative community was measured. Next, wildlife usage of the subsidized marsh
was compared to the unsubsidized marsh. The density, composition, and biomass of the
avian community found in each marsh were compared. A synoptic fish survey was
conducted to supplement the avian surveys in providing a detailed description of the
wildlife communities using the project site. Finally, a computer simulation model was
developed to further test theories of community response to increased and decreased
external subsidy to a system.
Self-Organization and Constructed Wetlands
Processes which select species based on seeding or the available resources are
examples of self-organization (Beyers and Odum 1994). Odum (1983) stated that self-
organizational processes including those by which ecosystems develop structure when
taken in aggregate is succession. Examples of self-organizational processes include


136
Corrascal, L. M. and J. L. Telleria. 1991. Bird size and density: A regional approach.
American Naturalist. 138(3):777-784.
D'Angelo, Elisa M. and K. R. Reddy. 1994. Nutrient accumulation in a constructed marsh
receiving hypereutrophic lake water. Paper presented at the Third Symposium on
Biogeocheinistry of Wetlands. Orlando, FI. June 26-29, 1994.
Damuth, J. 1981. Interspecific allometry of population density in mammals and other
animals: The independence of body mass and population energy use. Biological
Journal of the Linnean Society. 31:193-246.
Davis, John H., Jr. 1946. The peat deposits of Florida: Their occurrence, development,
and uses. Geological Bulletin no. 30. Florida Geological Survey.
Delphey, Philip J. and James J. Dinsmore. 1993. Breeding bird communities of recently
restored and natural prairie potholes. Wetlands. 13(3):200-206.
Dill, Charles H. 1989. Wasterwater wetlands: User friendly mosquito habitats p. 664-668
in Donald A. Hammer ed., Constructed Wetlands for Wasterwater Treatment:
Municipal, Industrial, and Agricultural. Lewis Publishers.
Doherty, Steven James. 1991. Patterns of landscape organization and their role in the
successional recovery of disturbed areas in Central Florida. Masters Thesis.
Duncan, Colin P. and Peter M. Groffinan. 1994. Comparing microbial parameters in
natural and constructed wetlands. Journal of Environmental Quality. 23:298-305.
Edelson, Naomi A. and Dr. Michael W. Collopy. 1990. Foraging Ecology of Wading
Birds using an Altered Landscape in Central Florida. Publication No. 04-039-087.
Florida Institute of Phosphate Research. Bartow, FL.
Emlen, J. T. 1977. Estimating breeding season birds densities from transect counts. Auk.
24:12-14.
Ethridge, Beverly J. and Richard K. Olson. 1992. Research and information needs related
to nonpoint source pollution and wetlands in the watershed: an EPA perspective.
Ecological Engineering. 1 (1/2): 149-156.
Feierabend, J. Scott. 1989. Wetlands: The lifeblood of wildlife, pp. 107-120 in Donald A.
Hammer ed., Constructed Wetlands for Wasterwater Treatment: Municipal,
Industrial, and Agricultural. Lewis Publishers.
Fields, Sherri. 1992. Regulations and policies relating to the use of wetlands for nonpoint
source pollution control. Ecological Engineering. 1(1/2): 135-141.


42
NOVEMBER 1990
lili
¡HI lip
n
i
i
I
i
i
j
H1!
SCALE: METERS
250 250
1 1 1
500
NORTH
LEGEND
Hl! :5
lilil Herbs ;3 Flo
E3 Shrubs K// Typ
Open Water ^ Typ
. Eme r gen t s S! Typ
ating Aquatics
b a < Open Water
b a >= Open Water
la Connnunity
Figure 9. Map of vegetative cover for November 1990.


91
system in the subsidized marsh. Total nitrogen and total phosphorus each have high
transformities; therefore, the nutrients pumped in with the lake water potentially had the
most influence on the development of the marsh. The importance of certain high emergy
sources is their ability to facilitate the input of additional nonrenewable energies. For
example, the nutrient subsidy was made available to the marsh by the use of other high
emergy subsidies including fuel used to run the pump system. In constructed wetlands,
external subsidies increase the total emergy flow in an ecosystem and have the potential to
increase the rate of successional processes in both the vegetative and wildlife communities.
Rapidly changing vegetative structure in the subsidized marsh may have allowed
for a varied and highly productive food source for the avian communities. High densities
and biomass in the subsidized marsh compared to the unsubsidized marsh were probably a
direct result of the addition of high emergy resources. In addition, the synoptic fish survey
may indicate how the food base available to higher trophic levels may increase with the
addition of an external subsidy. Thus, the external subsidy probably increased the overall
carrying capacity of the wildlife communities.
In his study of plant-animal interactions, Price (1992) emphasized the importance
of abiotic contributions that have the potential to become driving variables by influencing
plant production and quality for herbivores. He found that an increase in certain nutrients
in a pelagic system can lead to an overall population increase. The process was bottom-
up. In other words, Price determined that a subsidy induced a cascading effect up through
the trophic system through paths of energy flow. Kerekes (1990) also found that densities
of aquatic birds tend to increase with the trophic state of a water body.
The wildlife community in the subsidized marsh seems to follow a similar
bottom-up pattern. As the nutrient subsidy (enriched lakewater) was added to the marsh,
the plant community seems to increase in productivity. Plant quality may not have
increased given that many freshwater plants including Tvpha spp. are considered poor in
nutrient quality for most animals. Krull (1970) and Voights (1974) found that aquatic


20
The richness of the vegetative cover types was used to compare the complexity of
the emerging marshes over the project period. Vegetative cover richness was calculated
using Margalefs index for species richness (Margalef 1958). This index was modified to
use the vegetative cover types as species and the number of vegetative patches within a
marsh or transect as individuals. Hence, the vegetative cover richness was calculated as
follows:
R = (C-l)/(log(F) (1)
where R = vegetative cover richness
C = vegetative cover type
. F = Number of cover type patches
Vegetative structure complexity was determined by measuring the fractal
dimension as described by LaGro (1991). The area and perimeter of the vegetative
patches, formed by the vegetative cover types, provided the two-dimensional
measurements of vegetative structure necessary for the calculations. Complexity was
calculated as follows:
D = 2 (log(P)/log(A)) (2)
where D = fractal dimension
P = patch perimeter
A = patch area
Percent cover provided a further description of the changes in structural
complexity of each marsh over time. Vegetative cover percentage calculations divided the
total area of each cover type by the total area of each transect or marsh as follows:


140
Murtn, Henry R. 1982. Responses by dabbling ducks and aquatic invertebrates to an
experimentally manipulated cattail marsh. Canadian Journal of Zoology.
60:2324-2331.
National Research Council. 1993. Nutrient Requirements of Fish. National Academy
Press. Washington, D C.
Odum, E. P. 1969. The strategy of ecosystem development. Science. 164:262-270.
Odum, E. P. 1971. Fundamentals of Ecology. Third Edition. W. B. Saunders Co.,
Philadelphia, PA.
Odum, Howard T. 1983 Systems Ecology: An Introduction. John Wiley and Sons. New
York.
Odum, Howard T. 1981. Energy Basis for Man and Nature. McGraw-Hill. New York.
Odum, Howard T. and Jan E. Arding. 1991. Emergy analysis of shrimp mariculture in
Ecuador. Center for Wetlands and Water Resources. Gainesville, Florida.
Oliver, J. Douglas and Steven A. Schoenberg. 1989. Residual influence of macronutrient
enrichment of the aquatic food webs of an Okefenokee Swamp abandoned bird
rookery. Oikos 55:175-182.
Olson, Richard K. 1992. Evaluating the role of created and natural wetlands in controlling
nonpoint source pollution. Ecological Engineering. l(l/2):xi-xv.
Orians, Gordon H. and James F. Wittenberger. 1991. Spatial and temporal scales in
habitat selection. American Naturalist. 137(supplement):s29-s49.
Peters, Robert Henry. 1986. The ecological implications of body size. New York.
Cambridge University Press.
Price, Peter W. 1992. Plant resources and insect herbivore population dynamics, pp. 139-
176 in Mark D. Hunter, Takayuk Ohgushi and Peter W. Price (eds.) Effects of
Resource Distribution on Animal-Plant Interactions. Academic Press. San Diego.
Rader, Russell B. and Curtis J. Richardson. 1992. The effects of nutrient enrichment on
algae and macroinvertebrates in the Everglades: a review. Wetlands
12(2): 121-135.
Risser, D. G., J. R. Karr, and R. T. T. Forman. 1983. Landscape Ecology: Directions and
Approaches. Illinois Natural History Survey Special Publications Number 2.
Champaign: Illinois Natural History Survey.


Fuel-100%
0 15 30 45 60
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 27. Simulation of marsh with 100% added subsidy.


REFERENCES CITED
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135


Fish Double Intake Rate (Unsubsidized Marsh)
0 15 30 45 60
Years
Figure 35. Simulation of unsubsidized marsh with fish requiring double their food
requirements.


Table B-l. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Meaning dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
T5cc9T
o
0
0
0
0
0
0
0
0
0
0
0
0
24
0
0
0
0
0
3
0
0
0
0
0
0
0
0
27
Nov-92
o
8
0
0
0
0
0
0
0
0
1
0
0
7
0
0
0
2
2
0
0
0
0
0
0
0
0
0
20
Dec-92 Jan-93
1T
5
0
0
0
0
0
0
0
0
0
0
0
3
1
0
0
3
0
0
0
0
0
0
0
0
0
0
12
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
7
0
0
0
0
0
0
1
0
0
0
8


32
The consumers in the diagram are organized in trophic levels beginning with
macroinvertebrates and ending with the bird population. Each trophic level was
positioned in the diagram from left to right based on the principle of hierarchical
organization according to decreasing amount of energy flux on pathways. Pathways to
and from the consumers represent primary food sources and biological wastes.
Macroinvertebrates are shown to primarily consume detritus. Fish consume both
macroinvertebrates and submerged and floating vegetation. Finally, birds consume both
macroinvertebrates and fish. The biological wastes of each species after death, including
plants, recycle in the system to add to the nutrient storages. Depreciation of each
component and the process was drawn to converge at the drain at the bottom of the
diagram.
Emergv Analysis
Entergy analysis tables were developed separately for the subsidized and
unsubsidized marshes. Given in Tables 4 and 5 and summarized in Table 6 and Figure 6 is
the emergy analysis of the energy sources of the two marsh systems. Each table was
divided into four columns including: name of the energy source contributing to the
system, energy, material or dollar flux, solar transformity, and resulting emergy flux. In
addition to the driving forces were categorized as renewable and non-renewable sources.
Ratios of free to purchased energy (environmental loading) and non-renewable energy to
renewable energy (investment ratio) were calculated.
Renewable energy sources for the subsidized marsh and the unsubsidized marsh
included solar energy and the chemical potential of rain. The total emergy flux for these
flows was the same in both marshes. The emergy contribution of total nitrogen and
phosphorus inputs to the unsubsidized marsh was assumed to come from rain only. The


137
Forman, R. T. T., and M. Godron. 1986. Landscape ecology. New York. John Wiley and
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Freeman, B. J., H. S. Greening, and J. D. Oliver. 1984. Comparison of three methods for
sampling fishes and macroinvertebrates in a vegetated freshwater wetland. Journal
of Freshwater Ecology 2:603-610.
Furness, R. W. and J. J. D. Greenwood. 1993. Birds as monitors of environmental change.
Chapman and Hall. London.
Gill, Frank B. 1990. Ornithology. W. H. Freeman. New York.
Goldstein, David L. 1988. Estimates of daily energy expenditure in birds: The time-energy
budget as an integrator of laboratory and field studies. American Zoology. 28:829-
844.
Goldwasser, L., Cook, J., and E. D. Silverman. 1994. The effects of variability on
metapopulation dynamics and rates of invasion. Ecology. 75(l):40-47.
Hairston, Nelson G., Jr. and Nelson G. Hairston, Sr. 1993. Cause-effect relationships in
energy flow, trophic structure, and interspecific interactions. The American
Naturatlist. 143(3):379-419.
Hammer, Donald A.. 1992a. Creating Freshwater Wetlands. Lewis Publishers, Inc.
Chelsea, MI.
Hammer, Donald A. 1992b. Designing constructed wetlands systems to treat agricultural
nonpoint source pollution. Ecological Engineering. l(l/2):49-82.
Hobbs, N. Thompson and Tohas A. Hanley. 1990. Habitat evaluation: Do use/availability
data reflect carrying capacity? Journal of Wildlife Management. 54(4):515-522.
Holmes, M. A. Lewis, J. E. Banks, and R. R. Veit. 1994. Partial differential equations in
ecology: spatial interactions and population dynamics. Ecology. 75(1): 17-29.
Ivanoff, D. B. 1994 Phosphorus release from alternately flooded and drained histosols.
Paper presented at the Third Symposium on Biogeochemistry of Wetlands.
Orlando, FI. June 26-29, 1994.
Johnston, D. W. and E. P. Odum. 1956. Patterns in species diversity of bird communities.
Ecology. 37:50.
Joyner, David E. 1980. Influence of invertebrates on pond selection by ducks in Ontario.
Journal of Wildlife Management 44(3):700-705.


18
TRANSECT LOCATIONS
SCALE: METERS
NORTH
250 250
1 1 1
A
500
Figure 3. Map of site showing numbered transects.


40
Subsidized Marsh
(9 day turover)
Unsubsidized Marsh
(221 day turover)
Figure 7. Water budgets for both marshes.


49
Nov-90
100.00
o 80.00
U 60.00
I 40.00
JJ
20.00
0.00
Nov-91
Herbs Sfinite Open Water Floating Emergents Typha< Open Typha >= Open Typha
Aquatics Water Water Community
Apr-92
100.00
80.00
60.00 "
40.00
20.00
0.00
Herbs
Shrubs
Open Water
Floating
Aquatics
Emergents
Typha < Open Typha >= Open
Wala Water
Typha
Community
100.00 -
g 80.00 "
5 60.00 "
§ 40.00 "
CL
20.00 -
0.00 4-
Herbs
Nov-92
Shmbs
Open Water Floating Emergents TyphaOpen Typha >= Open Typha
Aquatics Water Water Community
Figure 15. Vegetative percent cover of subsidized marsh.


To my mother and father, for all that they inspired me to overcome.


15
Energy circuit. A pathway whose flow is proportional to
the quantity in the storage or source
upstream.
Source. Outside source of energy delivering forces
according to a program controlled form
outside, a forcing function.
Tank. A compartment of energy storage within the
system storing a quantity as the balanace
of inflows and outflows, a state variable.
Interaction. Interactive intersection of two pathways
coupled to produced an outflow in
proportion to a function of both, control
action of one flow on another, limiting
factor action, work gate.
Consumer. Unit that transforms energy quality, stores it,
and feeds it back autocatalytically to
improve inflow.
Producer. Unit that collects and transforms low-quality
energy under control interactions of high-
quality flows.
Box. Miscellaneous symbol to use for whatever unit or
function is labeled.
Figure 2. List of energy symbols.


Table B-1. -continued.
Common Name
TZSZT
Mar-93
Apr-93
May-93
Jul-93
American bittern
2
4
3
2
0
American coot
5
4
3
3
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
1
1
0
1
2
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
1
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
1
2
19
1
8
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
18
14
9
10
3
Common snipe
0
0
0
0
0
Common yellow throat
0
0
0
0
0
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
0
0
Foresters tern
0
0
1
0
0
Fulvous whistling duck
0
2
0
0
0
Gad wall
0
0
0
0
0
Glossy ibis
0
0
0
0
3
Great blue heron
0
0
0
0
2
Great white egret
0
0
0
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
1
4
2
1
3
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
1
0
0
Least bittern
0
0
2
0
3
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0


Table A-l. continued.
Common Name
Aug-91
"Sep-Sl
Nov-91
Jan-92
Mallard duck
0
o

Marsh wren
0
0
1
1
Mottled duck
0
0
0
0
Mouring dove
0
0
0
0
Northern cardinal
0
0
0
0
Northern herrier
0
0
1
0
Northern mocking bird
0
0
0
0
Northern pintail
0
0
0
0
Osprey
0
0
1
4
Palm warbler
0
0
0
0
Pied billed grebe
0
0
0
0
Purple gallinule
0
0
0
0
Red shoulder hawk
0
0
0
0
Red wing black bird
21
1
4
59
Sedge wren
0
0
0
0
Snowy egret
0
0
0
0
Song sparrow
0
0
0
0
Sora rail
0
1
0
0
Swamp sparrow
0
0
0
0
Tree swallow
1
0
0
0
Tri-color heron
0
0
0
0
Turkey vulture
0
0
0
0
White ibis
0
0
0
0
Willet
0
0
0
0
Wood duck
0
2
0
8
Yellow crown night heron
0
0
0
0
Yellow rumped warbler
0
0
0
0
Yellow warbler
0
0
0
0
Total
31
12
14
84


Table B-2. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
iwm
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
0
0
15
TJ5v32'

3
0
0
0
0
0
0
0
1
1
0
0
6
0
0
0
1
2
0
0
0
0
0
0
0
0
0
23
Dec-92
0
0
0
0
0
0
0
0
0
1
0
0
0
28
0
0
0
0
0
0
0
0
0
0
0
0
0
0
38
Jan-93
~ir~
0
4
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
3
0
0
0
16


33
Table 4. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the subsidized marsh
Notes
Energy
Transformity
Emergy
Renewables
(Sej/unit)
(E15)
1
Sun
5.41E+09
J
l.OOE+OO
0.00
2
Rain-chemical potential
6.27E+10
J
1.54E+04
0.97
Nonrenewables Free
3
Total nitrogen
7.85E+05
g
4.21 E+09
3.30
4
Total phosphorus
4.31E+04
g
6.88E+09
0.30
5
Phytoplankton
2.12E+04
J
1.00E+04
0.00
6
Pumped water-chemical potential
2.39E+09
J
2.35E+04
0.06
Nonrenewables Purchased
7
Liquid fuel
1.21E+11
J
6.60E+04
7.96
8
Construction-structure
5.11E+03
g
6.70E+09
0.03
9
Construction-services
9.34E+01
$ .
1.60E+12
0.15
10
Operation and maintenance
9.55E+02
$
1.60E+12
1.53
Notes to Table 4
1 Solar insolation; 1.29E6 cal/ha/yr (Odum et al. 1987)
(1.29E6 cal/ha/yr)(4.19E3J/cal) =
5.41 E+09
J/ha/yr
2
Rain-chemical potential: 1.27 m/y(Odum etal. 1987)
(1.27 m/yrXlE10 g/mha)(4.94 J/g)=
6.27E+10
J/ha/yr
3
Total nitrogen; 1.64 mg/1 (Coveney 1993)
(1.64 mg/lX40 cfeX28.3 l/cf)(3.15E7 sec/yr)
(IE-3 g/mg)/74.5 ha)=
7.85E+05
g/ha/yr
4
Total phosphorus: 0.09 mg/1 (Coveney 1993)
(0.09 mg/lX40 cfsX28.2 l/cf)(3.15E7 sec/yr)
(lE-3)/(74.5 ha)=
4.31E+04
g/ha/yr


Table A-3. -continued.
Common Name
Feb-92 Apr-92 May-
92 Jun-92
Aug-92
Amen can bittern
Amen can coot
I
0
I
0
0
' 0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
1
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Blue jay
0
0
0
0
0
Blue wing teal
8
3
9
15
4
Boat tail grackle
0
0
0
0
0
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
7
13
6
16
9
Common moorhen
0
0
0
0
0
Common snipe
3
2
0
0
0
Common yellow throat
0
0
0
0
0
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
1
0
Foresters tern
0
0
0
0
0
Fulvous whistling duck
0
0
0
0
0
Gadwall
0
0
2
0
27
Glossy ibis
0
0
0
0
0
Great blue heron
0
0
0
0
0
Great white egret
0
0
0
0
0
Greater yellow legs
0
1
0
1
0
Green back heron
0
0
0
0
0
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
1
0
0
0
King rail
0
0
1
3
6
Least bittern
1
1
0
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0


APPENDIX A. AVIAN SURVEY RESULTS FOR TRANSECTS 1-4
97


6
used the constructed wetland between 38% and 78% more than the lake and bay wetlands.
A total of ninety-eight species were documented as visiting the constructed wetland.
Lofgren (1993) found both high avian diversity and high avian density at Mitchell
Lake in Texas. Mitchell Lake had been receiving high nutrient loadings for over thirty
years. A total of 270 avian species have been sighted at the lake, thirty of which are
known to breed in the marshes.
Edelson and Collopy (1990) conducted a study of wading bird usage of a
hypereutrophic lake, and concluded that the abundance of fish stimulated a large
population of egrets and herons. The large fish population was thought to be due to the
high levels of nutrients. The birds also displayed unusual foraging behavior that may have
allowed the birds feeding in the dense Tvpha spp. stands better access to fish in deep water
areas.
Bird usage of late successional settling ponds of phosphate-mined lands may
provide a useful comparison to bird usage of created freshwater marshes used to treat
nonpoint source pollution. Both environments are high nutrient systems and are often
dominated by Salix carolinana and Tvpha spp. A survey of different phosphate mining
sites showed that late successional settling ponds contained extensive colonies of
double-crested cormorant, anhingas, black-crowned night herons, cattle and great egrets,
wood storks and white ibises (Maehr, 1984).
Vegetation density irregardless of species has been found to be an indicator of
habitat suitability for waterfowl in some studies. One study comparing
plant-macroinvertebrates associations and waterfowl found that 1 gram of animal biomass
was associated with every 100 grams of plant life (Krull 1970). Although the study did
not differentiate between cover types, it was noted that plants considered to be poor
waterfowl food harbor large quantities of macroinvertebrates which can make the area
more desirable for waterfowl usage.


Increased Migration (5x) (Subsidized Marsh)
Years
Figure 42. Simulation of increased migration in subsidized marsh.


69
After approximately 75 years, the storages of nutrients, plant biomass, insects, fish,
and birds reach steady state. This steady state was reached when each storage reached
100% of the marsh's carrying capacity.
When the pump system is turned on using 10% of the fuel used in the subsidized
marsh, the storages reach a new steady state after approximately 65 years as shown in
Figure 25. Plant biomass does not exceed the carrying capacity of the unsubsidized
marsh; however, it does reach steady state approximately five years sooner.
Insect, fish, and bird storages also increase at faster rates. Moreover, each of these
storages have an increase in carrying capacity with the increased nutrient subsidy. The
storage of insect biomass is increased by approximately 10% while fish and bird biomass
storages increased by 35% above the carrying capacity of the unsubsidized marsh.
An increase in fuel of 50% of that used in the subsidized marsh had the effect of


Table A-l. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mowing dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
Feb-92 Apr-92 May-92 Jun-92 Aug-92
~TJ 13 0
3
0
0
0
0
0
0
3
0
0
0
0
25
0
0
0
1
5
0
0
0
0
0
0
0
0
0
80
3
0
0
0
0
0
0
0
0
0
0
0
12
0
4
0
4
0
0
0
0
3
0
0
0
0
0
59
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
42
0
0
0
0
0
0
0
0
0
0
0
0
8
0
0
0
0
0
0
7
0
0
0
0
0
0
0
24
0
0
0
0
0
0
0
0
0
0
0
0
18
0
0
0
0
0
0
2
0
1
0
0
0
0
0
67


130
Table B-2. continued.
Common Name
Feb-93
Mar-93
Apr-97"
May-93
Jul-93
Mallard duck
'
0
0
6
0
Marsh wren
2
4
4
2
0
Mottled duck
0
0
0
0
0
Mouring dove
0
0
0
0
0
Northern cardinal
0
1
0
0
0
Northern herrier
1
0
0
1
0
Northern mocking bird
0
0
0
0
0
Northern pintail
0
0
0
0
0
Osprey
0
0
0
0
1
Palm warbler
0
0
0
0
0
Pied billed grebe
0
0
0
0
0
Purple gallinule
0
0
0
0
0
Red shoulder hawk
0
0
0
0
0
Red wing black bird
0
0
2
0
6
Sedge wren
0
0
1
0
0
Snowy egret
1
0
0
1
1
Swig sparrow
0
0
0
0
0
Sora rail
0
1
2
0
0
Swamp sparrow
0
0
0
0
0
Tree swallow
0
5
0
0
0
Tri-color heron
0
0
0
0
1
Turkey vulture
0
0
0
0
0
White ibis
0
1
1
0
5
Willet
0
0
0
0
0
Wood duck
0
0
0
0
0
Yellow crown night heron
0
0
0
0
0
Yellow rumped warbler
0
0
0
0
0
Yellow warbler
0
0
0
0
0
Total
20
31
24
17
26


Figure 5. Systems diagram of subsidized marsh.


41
Unsubsidized Marsh
Figure 8. Nutrient budgets for both marshes.


Table A-4. continued.
Common Name
'Feb-92' Apr-92 May-92
Jun-92
Aug-92
American bittern
2
2
0
0
' '
American coot
0
0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
43
52
0
0
0
Black crown night heron
0
0
1
0
0
Black neck stilt
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Blue jay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
16
9
8
24
13
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
1
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
8
9
9
13
9
Common snipe
1
0
0
0
1
Common yellow throat
1
1
0
0
0
Double-creasted cormoran;
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
0
0
Foresters tern
0
0
0
0
0
Fulvous whistling duck
0
7
0
3
4
Gad wall
0
0
0
0
0
Glossy ibis
21
1
8
0
3
Great blue heron
2
3
1
0
0
Great white egret
0
1
1
11
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
0
0
0
0
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
0
1
0
0
2
Little blue heron
3
0
0
0
0
Logger headed shrike
0
0
0
0
0


LIST OF TABLES
page
Table 1. List of transformities used for the emergy analysis 17
Table 2. Vegetation cover types and descriptions 19
Table 3. Avian species by taxonomic group 23
Table 4. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the subsidized marsh 33
Table 5. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the unsubsidized marsh... 35
Table 6. Summary of emergy analysis of both marshes 36
Table 7. Summary of vegetative community structure 52
Table 8. Avian size classes based on average weight of species 60
Table 9. Summary of avian and fish community structure 67
IX


57
Nov-91
25.00
20.00
Apr-92
Passerines
Nov-92
u
Gallinules Wading Birds Black Birds Insectivorous Ducks ibis Other Total
Passerines
Mean
25.00
20.00
Passerines
Figure 19. Overall avian density in subsidized marsh.


22
that one or very few species dominated the community. The equation used to determine
diversity was the following:
If = (sum(Pi(sumIn(Pi))) (4)
where If = diversity
Pi = ni /N ni = number of individuals in species i
N = total number of individuals in sample
Evenness was calculated as follows:
f = If / Umax (5)
where f = evenness
Hmax = total number of species in sample
Avian diversity and evenness indexes were compared over the survey period
between the subsidized marsh and unsubsidized marsh. Only the time periods when both
marshes were surveyed were evaluated for significant differences using a multivariate
analysis.
Density and Biomass
A general profile of the changes in density occurring in the marshes compared the
avian density by taxonomic groups found in each survey area. Table 3 shows the species
included in each taxonomic group. The species under the category labeled "other were
grouped together due to the low number of species represented by the remaining
taxonomic groups counted. A multivariate analysis was used to compare avian density in
the subsidized marsh and unsubsidized marsh during the period when both marshes were
surveyed.
Calculations for avian density divided the total number of birds counted in each
taxonomic group by the total area of the transects in the surveyed marsh:


141
Robb, Doreen M., 1992. The role of wetland water quality standards in nonpoint source
pollution control strategies. Ecological Engineering. 1(1/2): 143-148.
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Rodgers, Jr., John H. and Arthur Dunn. 1992. Developing design guidelines for
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Engineering. l(l/2):83-95.
Root, Terry. 1988. Energy constraints on avian distributions and abundances. Ecology.
69(2):330-339.
Shaw, Denice M. and Samuel F. Atkinson. 1990. An introduction to the use of
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Schelske, Claire and Patrick Brezonik. 1992. Can Lake Apopka be restored? pp. 393-398
in Susan Maurizi and Florence Poillon, ed. Restoration of Aquatic Ecosystems:
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DC.
Shumway, Scott W. and Mark D. Bertness. 1994. Patch size effects on marsh plant
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Streever, W. J. and T. L. Crisman. 1993. A comparison of fish populations from natural
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Telleria, J. L. 1986. Manual para el censo de los vertebrados terrestres. Raices. Madrid.
Terres, John K. 1980. The Audobon Society encyclopedia of North American birds.
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TABLE OF CONTENTS
page
ACKNOWLEDGEMENTS iii
LIST OF FIGURES vii
LIST OF TABLES ix
ABSTRACT x
INTRODUCTION 1
Plan of Study 2
Self-Organization and Constructed Wetlands 2
Description of Study Site 10
METHODS 13
Energy System Diagram 13
Emergy Analysis 14
Vegetation Complexity and Structure 16
Avian Surveys 21
Fish Population Sampling 23
Computer Simulation Model 23
RESULTS 30
Ecological Systems Overview 30
Vegetative Communities 39
Avian Community Structure 53
Fish Density and Biomass 65
Computer Simulation Model 65
v


Invertebrate abundance was positively correlated with marsh usage by waterfowl
in a study by Murkin et al. (1982). However, invertebrate abundance was not affected by
cover removal. According to Murkin, visual cues of openness may be what waterfowl
used to judge where the greatest abundance of invertebrates were to be found. This
theory was also supported by research conducted by Leschisin et al. (1992) and Wilcox
and Meeker (1992).
Landscape Scale Studies of Community Structure
Landscapes go through successional phases or stages just as smaller scale
communities (Naveh and Lieberman 1984, Bell et al. 1990). Also like communities,
landscapes are predicted to evolve over time towards more complex and diverse systems.
The development and dynamics of landscape spatial heterogeneity can be an important
factor that influences both biotic and abiotic processes (Risser et al. 1984, Forman and
Godron 1986, Turner 1987). Moreover, each successive level of biological organization
has properties that cannot be predicted from those of less complex levels such as the
difference in characteristics of populations and the individuals of which they are composed
(Odum 1971).
Often important information about a certain species behavior or the organization of
a biological community is missed because the scale of the study is not appropriate. In
addition, if the scale is spatial, then the behavior of an individual may be acting on cues of
the community or vice versa (Cody 1981, Molofsky 1994, Holmes et al. 1994, Silverman
1994, Tilman 1994.)
The different dynamics of a wetland at different scales provides additional
problems when attempting to determine community structure. Wildlife populations are
often more constant on a regional scale due to the asynchrony of the separate local


Table A-4. continued.
Common Name
Sep-92
Oct-92
Dec-92
Jan-93'
Feb-93
Amen can bittern
0

0
0
0
American coot
0
0
0
1
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
6
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Blue jay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
3
5
4
1
10
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
4
15
8
12
0
Common snipe
0
0
0
1
0
Common yellow throat
1
1
0
2
1
Double-creasted cormoram
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
0
0
Foresters tem
0
0
0
0
0
Fulvous whistling duck
0
0
0
0
0
Gad wall
0
0
0
0
0
Glossy ibis
0
0
0
1
0
Great blue heron
0
0
0
0
0
Great white egret
1
0
1
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
0
0
0
0
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
0
0
0
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0


45
NOVEMBER 1992
SCALE: METERS
250 250
1 1
500
"LEGEND
Floating Aquatics
Typha < Open Water
Typha >= Open later
Typha Community
Herbs
Shrubs
Open later
Emergent s
P7;
(A
m
m
NORTH
Figure 12. Map of vegetative cover for November 1992.


Insects Double Inieke Rete (Subsidized Marsh)
0 15 3 0 4 5 6 0
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 34. Simulation of subsidized marsh with insects requiring double their food
requirements.


139
Margalef, D. R. 1958. Information theory in ecology. Yearbook for the Society of General
Systems Theory. 3:36-61.
Margalef, D. R. 1963. Biodiversity. Advanced Frontiers in Plant Science. 2:137.
Maurer, Brian and James H. Brown. 1988. Distribution of energy use and biomass among
species of North American terrestrial birds. Ecology. 69(6): 1923-1932.
Maurizi, Susan and Florence Poillon, ed. 1992. Restoration of Aquatic Ecosystems:
Science, Technology, and Public Policy. National Academy Presses. Washington,
DC.
McAllister, Lynne S. 1993a. Habitat quality assessment of two wetland treatment systems
in FloridaA pilot study. Report EPA/600/R-93/222. US Environmental
Protection Agency.
McAllister, Lynne S. 1993b. Habitat quality assessment of two wetland treatment systems
in the arid westA pilot study. Report EPA/600/R-93/117. US Environmental
Protection Agency.
McAllister, Lynne S. 19932. Habitat quality assessment of two wetland treatment systems
in MississippiA pilot study. Report EPA/600/R-92/229. US Environmental
Protection Agency.
Mitsch, William J. 1992. Landscape design and the role of created, restored and natural
riparian wetlands in controlling nonpoint source pollution. Ecological Engineering.
l(l/2):27-47.
Mitsch, William J. 1990. Wetlands for the control of nonpoint source pollution:
Preliminary feasibility study for Swan Creek Watershed of Northwestern Ohio.
Ohio Environmental Protection Agency.
Mitsch, William. J. and J. K. Cronk. 1992. Creation and Restoration of Wetlands: Some
Design Considerations for Ecological Engineering, in Soil Restoration. Rattan Lai
and B.A. Stewart (eds.) Advances in Soil Science, vol. 17. Springer-Verlag, New
York. 217-260p.
Mitsch, William J. and James G. Gosselink. 1986. Wetlands. Van Nostrand Reinhold, New
York.
Molofsky, Jane. 1994. Population dynamics and pattern formation in theoretical
populations. Ecology. 75(l):30-39.


66
Figure 23. Results of fish survey including a) density and b) biomass.


Table A-2. -continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
"Feb-92
0
0
0
0
0
1
0
0
0
0
0
0
0
4
1
0
0
1
0
1
0
0
0
0
0
0
0
0
27
Apr-92
' 0
5
0
0
0
0
0
0
0
5
0
0
0
8
0
0
0
0
1
12
0
0
0
0
0
0
0
0
50
May-92 Jun-92 Aug-92
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
47
0
0
0
0
0
0
0
0
0
0
0
0
0
7
0
0
0
0
0
0
0
0
0
0
0
0
0
0
23
0
0
0
0
0
0
0
0
0
0
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
64


commensurate with what was required to make them, or the production is discontinued
according to Odum and Arding (1991).
Knight (1992) explained that significant losses of vegetation and animals can occur
as a result of high loading of pollutants including too much water, organic matter or
nutrients. He pointed out that water flow and depth control can affect primary
productivity of the wetland and the ability of the wetland to effectively treat nonpoint
source pollution. He suggested that higher flows of shallow water provide higher
dissolved oxygen levels leading to higher secondary productivity.
Hammer (1992a) predicted that if high loading of nutrients were added to a
constructed freshwater marsh, then Tvpha spp.. Salix spp or other woody shrubs will
dominate and reduce the system's diversity. Moreover, a monoculture could develop
resulting in an overall decrease in species diversity. In another study, Hammer (1992b)
pointed out that manipulation of the water level alone can sustain a diverse, complex, and
productive marsh for many years. Furthermore, fluctuations of water levels can create
more ecological niches for more species of plants and animals.
Common techniques for establishing ecologically engineered wetlands include (1)
re-establishing or managing wetland hydrology, (2) eliminating or controlling chemical or
other contaminants affecting wetlands, and (3) reestablishing and managing native biota
(Maurizi and Poillen 1992). Not all engineering projects, however, have the
reestablishment of the original biota as a primary goal due to the immense amount of
resources required to do so. In this case, it may be more important to consider the possible
affects of the desired hydrology including the balance between nutrient removal and the
potential to increase wildlife habitat and abundance.


126
Table B-1. -continued.
Common Name
Feb-93
Mar-93
Apr-93
May-93
JuI-93
Mallard duck
O'
0
0
0
o
Marsh wren
4
8
4
4
0
Mottled duck
3
0
0
3
0
Mouring dove
0
0
0
0
0
Northern cardinal
0
0
0
0
0
Northern herrier
0
0
0
0
0
Northern mocking bird
0
0
0
0
0
Northern pintail
0
0
0
0
0
Osprey
0
0
0
0
2
Palm warbler
0
2
0
0
0
Pied billed grebe
0
0
0
0
0
Purple gallinule
0
0
1
0
0
Red shoulder hawk
0
0
0
0
0
Red wing black bird
15
3
0
15
5
Sedge wren
0
0
3
0
0
Snowy egret
0
0
0
0
1
Song sparrow
0
0
0
0
0
Sora rail
0
0
2
0
0
Swamp sparrow
0
0
0
0
0
Tree swallow
24
0
0
4
0
Tri-color heron
0
0
1
0
1
Turkey vulture
0
0
0
0
0
White ibis
0
0
0
0
7
Willet
0
0
0
0
0
Wood duck
0
0
0
0
0
Yellow crown night heron
0
0
0
0
0
Yellow rumped warbler
0
0
0
0
0
Yellow warbler
0
0
0
0
0
Total
46
13
11
26
16


Habitat Disturbance (Unsubsidized Marsh)
Nutrients

Plants

"" Insects
Fish
Birds
Years
Figure 39. Simulation of periodic fish kill in unsubsidized marsh.


7
Although animals, including macroinvertebrates, consume and recycle nutrients
from wetlands, Hammer (1992a) believes that animals do little to directly treat non-point
source pollution. He suggested, however, that the presence or absence of certain animal
communities can provide an indicator of the health of the system. It is important that one
carefully interpret the animals communities present, according to Hammer, because certain
types of species may survive better and persist longer than others in systems receiving high
nutrient loadings. Indeed, the problem of undesirable high densities of mosquitoes during
the early stages of marsh development is a real one for many treatment wetlands according
to Dill (1990.)
A study by Oliver and Schoenberg (1989) found that birds can have an indirect
positive effect on fish and macroinvertebrate populations. In their study, they showed that
ibis and other wading birds increased macro nutrient concentrations (particularly
phosphorus) increased under rookeries. Under these rookeries the fish and
macroinvertebrate densities slightly increased. In comparison, it was determined from a
study of a oligotrophic lake by Kerekes et al. (1992) that there is a close balance between
the size of a water body, nutrient loading, and its
fish production to the occupancy and production of piscivorous birds.
Early successional processes that determine the abundance of macroinvertebrates
can also affect higher trophic levels. Joyner (1980) found that pond selection by ducks in
Ontario was partially determined by invertebrate density. Invertebrate abundance
increases as the submergent vegetation replaced the emergent vegetation according to
Voigts (1976). In his study, marshes that had submerged vegetation (suggesting some
openness) interspersed with emergent vegetation (suggestion cover) had the greatest
invertebrate abundance. He further suggested that nesting birds preferred the marshes
with higher numbers of invertebrates. Feierabend (1989) also points out the importance of
invertebrates stating that they are critical to entry dynamics and functions of wetlands and
the foundation of wetland food chains.


Table A-3. Avian survey results for Transect 3.
Common Name
-fciprr
Sep-91
Nov-91
" Jan-"92
Amen can bittern
0

0
0
American coot
0
0
0
0
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
0
0
Bald eagle
0
0
0
0
Bam swallow
0
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
1
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Blue jay
0
0
0
1
Blue wing teal
2
0
0
0
Boat tail grackle
0
0
0
0
Carolina wren
0
0
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
1
2
10
1
Common moorhen
0
0
0
0
Common snipe
0
2
3
0
Common yellow throat
0
0
0
0
Double-crested cormorant
0
0
0
0
Eastern kingbird
0
0
1
0
Eastern phoebe
0
0
0
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
0
0
Gad wall
1
0
0
0
Glossy ibis
2
0
0
0
Great blue heron
1
0
0
0
Great white egret
0
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
0
0
0
0
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
2
0
0
0
Little blue heron
0
0
0
0
Logger headed shrike
0
0
0
0


38
additional lake water pumped into the subsidized marsh increased the emergy of total
nitrogen and total phosphorus by two magnitudes higher than that entering the
unsubsidized marsh. Free nonrenewable energy sources influencing self-organization in
the subsidized marsh included nutrients and phytoplankton pumped into the marsh with
lake water and the chemical potential of the pumped water itself. The emergy flux of
these flows contributed 26% of the total emergy flow to the subsidized marsh.
Only two nonrenewable purchased energy sources were included in the subsidized
marsh system that were not also part of the unsubsidized system. These included liquid
fuel used to operate the hydraulic pumps and the physical structure of the pump system
itself. The combination of these two flows contributed 68% of the total emergy flow to
the subsidized marsh.
The environmental loading ratio showed a large contrast between the two marshes.
In the subsidized marsh the environmental loading ratio was 13.8. The unsubsidized
marsh had an environmental loading ratio of 0.1. Investment ratios for the two marshes
showed a large difference in the amount of purchased energy necessary to maintain the
flows of environmental inputs. The subsidized marsh had an investment ratio of 2 .1 and
the unsubsidized marsh had an investment ratio of 0.1.
The total solar emergy inputs entering the subsidized marsh were significantly
higher than the unsubsidized marsh system. The total solar emergy input to the subsidized
marsh was 14.30 E15 sej ha-1 yr"1. In comparison, the total solar emergy input to the
unsubsidized marsh is 1.09 El5 sej ha"1 yr'1. The largest single factor contributing to
this difference was the fuel used to run the pump system in the subsidized marsh (7.96 El5
sej ha-1 yr.)


12
PROJECT SITE
SCALE: METERS
500 500
1 1
1000
NORTH
Figure 1. Map of project site.


Fuel **500%
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 28. Simulation of marsh with 500% added subsidy.


142
Voigts, David K. 1976. Aquatic invertebrate abundance in relation to changing marsh
vegetation. The American Midland Naturalist. 95(2):313-322.
Weins, J. A. 1989. The ecology of bird communities. Cambridge University Press.
Cambridge.
Weller, Milton W. 1989. Waterfowl management techniques for wetland enhancement,
restoration and creation useful in mitigation procedures, in Wetland creation and
restoration: The status of the science, vol 2. Environmental Protection Agency.
Weller, Milton W. and Cecil S. Spatcher. 1965. Role of habitat in the distribution and
abundance of marsh birds. Agricultural and Home Economics Experiment Station,
Iowa State University. Special Report No. 43.
Whitaker, Gene and Charles R. Terrell. 1992. Federal programs for wetland restoration
and use of wetlands for nonpoint source pollution control. Ecological Engineering.
1(1/2): 157-170.
Wilcox, Douglas A. and James E. Meeker. 1992. Implications for faunal habitat related to
altered macrophyte structure in regulated lakes in Northern Minnesota. Wetlands.
12(3): 192-203.
Willard, Daniel E. and Amanda K. Hiller. 1989. Wetland dynamics: Considerations for
restored and created wetlands in wetland creation and restoration: The status of
the science, vol 2. Environmental Protection Agency, pp. 47-54.
Willson, Mary F. 1974. Avian community organization and habitat structure. Ecology.
55(5): 1017-1029.
Wylie, John L. and David J. Currie. 1993. Species-energy theory and patterns of species
richness: I. Patterns of birds, angiosperm, and mammals species richness on
islands. BioConservation. 63:137-144.


51
Shrubs were the predominate cover type in the unsubsidized marsh in November
1991 at 59.86%. The next highest percent cover was open water at 15.71%. In addition,
Tvpha >= open water had increased to 10.88% cover in the unsubsidized marsh.
In April 1992 the percent cover of the various cover types had significantly
distributions (n = 18, df = 8, p = 0.03). Both marshes reflected a progression towards
more dense cover types that included Tvpha spp. In the subsidized marsh the Tvpha
Community had increased to 57.51% cover. Tvpha >= open water and open water were
also important cover types in the subsidized marsh at this time at 18.32% and 17.51%,
respectively.
In April 1992 Tvpha Community had become the most important cover type in the
unsubsidized marsh covering 70.71%. For the first time in the unsubsidized marsh,
emergents began to become a significant cover type at 12.74% in April 1992.
In November 1992 the marshes again had significantly different distributions of
percent cover (n = 27, df = 8, p = 0.02). The subsidized marsh was covered mostly by
Tvpha Community at 66.70% cover. The next most important cover type was Tvpha >=
open water at 14.36% cover. The remaining cover types present were represented at a
cover of less than 10% each.
Tvpha Community was also the predominate cover type in the unsubsidized marsh
covering 48.61%. However, other cover types also began to become more evident such
as emergents (21.53%) and Typha >= Open Water (18.12%.) Table 7 summarizes the
results of the vegetative community structure study in both marshes.


21
Cj = (Ctj / A) 100 (3)
where Cj = percent cover of type j
Ctj = total area of vegetative cover type j
A = area of marsh or transect
Vegetative cover percentages were compared between the sites using a
multivariant analysis.
Avian Surveys
The avifauna surveys were conducted using the Emlen strip technique (Emlen
1977). Avian sampling by transect began in August 1991 in the subsidized marsh.
Surveying began on the two transects in the subsidized marsh in November 1992. Avian
species were identified visually or by call. Only birds observed within thirty-five meters
from the transect center line were recorded.
Transects were surveyed every six-weeks. Sampling order for the transects
revolved from one sampling event to the next. The rotation lessened sampling bias by
surveying each transect during different morning hours.
Diversity and Evenness
Shannon diversity and evenness indexes were used to compare the avian
communities found in the surveyed marshes (Browner 1989). Diversity indices were used
to describe the number of avian species present in the marshes given the total avian
abundance. Evenness indices were used to evaluate the distribution of individuals among
the avian species present. In other words, the evenness of the avian community was high
if all species were represented by similar numbers of individuals. Low evenness indicated


55
Subsidized Marsh
1.00
Unsubsidized Marsh
1.00
o
.S
0.75
0.50
£ 025
0.00
Figure 18. Evenness indices for avian species in both marshes.


11
shown in Figure 1. The southern marsh cell called the subsdized marsh was studied for
this thesis. An unmanaged marsh located adjacent to the subsidized marsh was also
studied for this thesis and referred to as the unsubsidized marsh. The subsidized marsh
and the unsubsidized marsh maintained similar average water levels (0.76 m ) throughout
the study period.


Table A-3. -continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
Au^-9 1
0
0
0
0
0
0
0
0
0
0
0
50
0
0
0
0
0
1
0
0
0
0
5
0
0
0
0
65
Sip^T
{T~
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
6
Nov-91
1
0
0
0
0
0
0
0
2
0
0
1
0
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
21
7am9I
0
0
0
0
0
0
0
0
3
0
0
0
14
0
0
0
0
2
2
0
0
0
0
0
0
0
0
0
23


Ram Only (Unsubsidrzed Marsh)
Years
Figure 31. Simulation of unsubsidized marsh receiving nutrients from rain only.


INTRODUCTION
Theory would suggest that an external subsidy should increase the carrying
capacity for wildlife of an ecosystem, all other things being equal. Determining the effect
that an external subsidy has on the organization of an emerging, created wetland is the
main question being asked by this thesis.
One prediction of this study is that the external nutrient subsidy increases the
energy flow in productive pathways that in the short term results in an increased food base
and leads to an increase in the number of consumers. Initially, species diversity and
evenness are predicted to be relatively low. If the subsidy is continued over many years,
then higher diversity and evenness are expected to occur. Significant structural differences
in the vegetation community between created wetlands receiving a subsidy and created
wetlands not receiving a subsidy might also be discernible such as the formation of a
monoculture. The differences in structural characteristics (mosaic of vegetation types and
open water) may account for differing wildlife densities and/or diversity between
subsidized and unsubsidized wetlands. Finally, early successional trends in
wildlife use and diversity may be observed and related to external subsidies.
This thesis is an investigation of the ecological self-organization of a constructed
wetland in Central Florida receiving continuously pumped lake water, high in nutrients and
suspended material. Called the Apopka Flow-way Demonstration Marsh Project, the
constructed wetland is part of a larger project funded by the St. Johns River Water
Management District (SJRWMD). The project's primary goals are to restore historic
wetlands and improve water quality in Lake Apopka.
1


Table A-4. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
~0~
0
1
0
0
0
0
0
0
0
0
0
0
13
0
0
0
0
0
0
0
0
0
0
2
0
0
0
25
~ir~
12
0
0
0
0
0
0
0
0
0
0
0
206
0
0
0
11
0
0
0
0
0
0
0
0
0
0
250
Dec-92
0
2
0
0
0
0
0
0
0
0
0
0
0
24
0
0
0
6
0
0
0
0
0
0
0
0
0
0
45
75H3TT

9
0
0
0
2
0
0
0
4
0
0
0
8
0
0
0
6
0
0
0
0
0
0
0
0
0
0
53
TeB^T
~IT-
6
0
0
0
0
0
0
0
3
0
0
0
12
0
0
0
1
1
0
0
0
0
0
0
0
0
0
34


Table A-2. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
3ip3H
(T
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
1
0
0
0
0
0
0
0
0
0
0
22
TZiVI
73
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17
Dec-92
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
20
Jan-03
~TT~
0
0
0
0
0
0
0
0
30
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
49
Teb^T
0
1
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
1
0
8
0
0
0
0
0
0
0
0
38


96
marsh relative to the amount of purchased energies. The addition of certain high emergy
sources (e g., the pump system) may facilitate the input of other resources (free
nonrenewables) at a rate that is proportional to the added subsidy.
Conclusions
The nutrient enrichment seemed to speed up self-organizational processes
in the subsidized marsh increasing the rate of vegetative coverage of the marsh. The
prevelance of large bodied birds in the unsubsidized marsh was likely due to the larger
percentage of open water. More open water may have also allowed greater diversity in
the avian community given a greater variety of feeding habitats.
Given the higher animal densities and biomass, the external subsidy may have also
increased the rate that these components reached their respective carrying capacities. This
theory seemed to be validated by the computer model simulations. Moreover, the
computer simulations suggest that the carrying capacity varies with different levels of
external subsidy. In general, the greater the subsidy of available nutrients, the greater
carrying capacity to be expected.
Overall, the external subsidy increased the emergy flux in the subsidized marsh by
increasing the input of nonrewable energy sources. As a result community parameters
such as density and overall biomass also increased in the subsidized marsh, but at a cost
of lowered richness, diversity, and evenness. Complexity of community structures did not
seem to be affected.


14
Ernergy Analysis
Emergy analysis was developed by Dr. H. T. Odum to provide a method of
comparing general systems (1983, 1990). The sources driving each system and the
component parts are related in the same measurable units. Generally, a systems diagram is
developed first to account for each source driving the system and the interactions of
different energies within the system. Figure 2 shows the general system symbols created
by Odum used to draw the diagram. Pathways and storages were initially measured either
in energy or material units.
Tables of the sources and the storages are made for comparisons. Each
component being evaluated is multiplied by its respective transformity to obtain its emergy
value. The flows and storage components of each system can then be compared on the
same basis. Often the transformities of the various components are compared to
determine the differences in the amount of total energy to maintain each type.
An emergy analysis table was evaluated to put in perspective the relative
contributions of pumps, water, nutrients, human services, and renewable energies driving
the marshes. Water, nutrient, and energy budgets from both renewable (rain) and
non-renewable (pumped water) services were determined to evaluate the net contribution
of each component. Renewable sources included sunlight and the chemical potential of
rain. Nonrenewable sources from pumped water included water, nutrients, and organic
matter from Lake Apopka. Purchased nonrenewable sources included the pump structure,
fuel to run the pumps, and services for construction, operation and maintenance of the
flow-away system.
Data were obtained from SJRWMD after two years of operation of the
demonstration project. Each source flow was converted into solar emjoules per year per
hectare using predetermined transformities. Transformities had been determined in other


81
If fish were the element to require more resources, then the affect on the other
populations is much different as shown in Figures 35 and 36. The macroinvertebrate
population is eventually depleted as the fish and birds consume them. In addition, the
increased population of fish also benefits the bird population allowing it to be sustained
without the macroinvertebrate population.
When the food requirements of birds is increased as in Figures 37 and 38, the
macroinvertebrate population is not delepleted. However, competetion between the fish
and birds appeared to develop with fish receiving the negetative consequences of this
relationship. As the fish population decreases, some feeding pressure on the
macroinvertebrates is eventually elievated.
Figures 39 and 40 show the results of periodic disturbances to the marshes using
fish kills as an example. Immediately after the fish kill, the macroinvertebrate population
increases while the bird population temporarily
decreases. The reverse occurs as the fish population recovers.
Increases in migration allow rapid exploitation of the marcroinvertebrate
population as shown in Figures 41 and 42. The growth of the populations, however, is
soon limited as each resource nears its carrying capacity.


3
reinforcements produced by nutrient cycling, animal and plant interactions, and the role of
keystones species.
Self-organization in constructed wetlands is dependent mostly on its hydrologic
design. Wetlands that are continuously flooded, but have shallow flowing water, as in
many constructed wetlands, have high productivities and develop quickly according to
Mitsch and Gosselink (1986.) The actual relationship between wetland productivity and
hydroperiods includes nutrient inputs, export, decomposition, and nutrient cycling.
Odum (1990) defines ecological engineering as an integration of humanity and
nature while benefiting both. Constructed and restored wetlands can be ecologically
engineered for the treatment of nonpoint source pollution (Odum 1990, Mitsch 1992, and
Hammer 1992). Nonpoint source pollution from agricultural activities is often thought to
be the major cause of surface water degradation in the United States (Baker 1992).
According to Mitsch (1992), a wetlands system may provide more efficient treatment,
greater longevity, and reduced operating requirements than other conventional methods.
Mitsch has outlined several principles of ecological engineering in various
publications which can be incorporated into the design of a treatment wetland (Mitsch
1990, 1992, Mitsch and Cronk 1992). These principles include designing the system for
minimum maintenance by allowing the system to self-organize on its own. He
recommends the use of available low quality energies such as potential energy of
downstream flow to subsidize the system with water, energy, and nutrients. He also
suggests that in some cases the use of pump systems may not increase treatment benefits
derived from a treatment marsh system. For example, some hydrologic pump systems may
require more energy resources to construct and operate than what the pumps actually
contribute to desirable wetland functions in the marsh system such as the removal of
nutrients in the water column. In environmental systems, the components of the system
which require more work in their development either contribute more to the system


56
Density of Avian Species
Shown in Figures 19 and 20 are avian densities for the subsidized and unsubsidized
marshes. Data were aggregated to correspond to data of aerial photos. The results for
each transect individually by marsh is presented in Appendix B for the subsidized marsh
and in Appendix C for the unsubsidized marsh.
Avian density increased over the survey period in the subsidized marsh (n = 14,
df- 6, p = 0.01) with some fluctuation. Overall average avian density (18.48 birds ha'l)
remained high in the subsidized marsh throughout the survey period. In November 1991,
the average avian density decreased to 16.58 birds haV By April 1992 average density
had begun to increase. In November 1992, avian density averaged 20.18 birds ha" V
During the period that the unsubsidized marsh was surveyed the average avian
density was 7.07 birds ha"*. Avian density did not change significantly over the survey
period (n = 8, df = 2, p = 0.08.)
In the subsidized marsh, black birds had the highest average density of all
taxonomic groups over the survey period representing 46.11% of the overall density. In
contrast, gallinules had the highest average density of all other taxonomic groups in the
unsubsidized marsh for the November 1992 survey period. Gallinules represented 28.57%
of the overall density in the unsubsidized marsh. In April 1993, black birds had the highest
average density in the unsubsidized marsh with 27.44% of the overall density.
The taxonomic groups were compared among the two marshes for overall
differences. Overall, the feeding types had significantly different densities between the
marshes (n = 21, df = 6, p = 0.02). Within each marsh, the density of the individual
feeding types were also significantly different (n = 98, df = 9, p = 0.04).


Table 2. Vegetation cover types and descriptions.
Cover Type
Includes one or more of the following:
Herbs
Panicum sdd.. Bahia spD.. Bidens spp.
Shrubs
Ludwieia spo.. Euoatorium leptophvllum.
Sambucus canadensis. Salix caroliana
Open Water
Open areas with less the 25% cover vegetative cover
Floating aquatics
Hvdrocotvle sdd.. Polveum sdd.. Altemathera spD..
Eichhomia crassipes
Emergents
Scripus spp.. Sagittaria spp.. Pontederia cordata
Typha < open water
Open water with 25-50% cover of Tvoha sdd.
Typha >= open water
Open water with 50-75% cover of Tvpha sdd.
Typha Community
Tvpha spp. interspersed with more than 25% cover of
emergents or shrubs


APPENDIX C: COMPUTER SIMULATION MODEL


36
Table 6. Summary of emergy analysis of both marshes.
Emergy Flows
Subsidized Marsh
Unsubsidi2ed Marsh
(E15)
(El 5)
Renewable Emergy
1.0
1.0
Nonrenewable Emergy
Free
3.7
1.0
Purchased
9.7
0.1
Total Emergy Flux
14.3
2.0
Emergy Index Subsidized Marsh Subsidized Marsh
Environmental Loading 13.8 0.1
Investment Ratio 2.1 0.1


Table 9. Summary of avian and fish community structure.
Parameter
Subsidized Marsh
Unsubsidized Marsh
Significant Difference
Avian Diversity
2.65
3.04
n = 54 df= 4, p
= 0.02
Avian Evenness
0.67
0.82
Avian Density
18.48 ha-1
7.07 ha-1
n = 54, df= 6, p =
= 0.02
Avian Biomass
5 .11 kg ha-1
2.22 kg ha-1
n = 54, df=6, p =
= 0.03
Fish Density
230 m-2
165 m-2
n = 30, df =5, p =
= 0.01
Fish Biomass
6.44 kg m-2
4.29 kg m-2
n = 30, df =5, p =
= 0.03


Habitat Disturbance (Subsidized Marsh)
0 13 30 45 60
Years
Figure 40. Simulation of periodic fish kill in subsidized marsh.


73
shown in Figure 28. Moreover, steady state was reached after only 28 years. The wildlife
storages had greatly increased their carrying capacities, and had reached those levels over
forty years sooner than in the unsubsidized marsh.
Ten times the fuel (or 1000%) used in the subsidized marsh enables the marsh to
reach steady state after approximately 25 years as shown in Figure 29. In addition, greater
flucuations are shown in the biomass storages. Biomass storages all reached a higher
carrying capacity much sooner than the unsubsidized marsh.
Figure 30 summarizes the changes in biomass carrying capacity with different
levels of fuel used. It appears that the increases may be logistic; however, the model
overflowed after more than 15 times the fuel used in the subsidized marsh was simulated.
Seven sensitivity tests were performed to test the response of the computer model
to various conditions. The first two tests were simulations of the unsubsidized marsh
only. The remaining tests compared simulations of both the unsubsidized marsh and the
subsidized marsh (100% fuel) under the same conditions.
Figure 31 shows the results of running the unsubsidized marsh supplied with only
the nutrients in rain. All of the storages reached a lower steady state than in the original
simulation. In addition, the animal storages all soon began to decrease, and therefore their
maximum carrying capacity under these conditions was probably very low. With only a
small reduction in nutrients, as shown in Figure 32, the biological components of the
model are more successful in reaching a carrying capacity more similar to the original.
Figures 33 and 34 show the response of the unsubsidized marsh and the subsidized
marsh if the insects required more resources to survive. Given this scenario, the
macroinvertebrates pursue the available resources much more vigorously and in turn their
numbers multiply more quickly. The increased abundance of macroinvertebrates is then
quickly consumed by the fish and birds elevating their populations above what was found
in the original simulations.


APPENDIX B: AVIAN SURVEY RESULTS FOR TRANSECTS 5-6
122


I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a thesis for the degree of Masters of Science.
Mark T. Brown, Chairman
Associate Scientist of Environmental
Engineering Sciences
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a thesis for the degree of Masters of Science.
G. Ronnie Best
Scientist of Environmental Engineering
Sciences
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a thesis for the degree of Masters of Science.
Stephen R. Humphrey
Interim Dean, College of Na
Resources and Environment
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a thesis for the degree of Masters of Science.
Winfred M. Phillips
Dean, College of Engineering
Karen A. Holbrook
Dean, Graduate School


134
T able C-1. continued.
345 DINSECTS = K23 INSECTS DETRITUS K24 INSECTS *
DETRITUS K25 INSECTS k26 INSECTS K27 INSECTS *
FISH K28 INSECTS BIRDS + z zz
350 DFISH = K29 FISH (PLANTS + INSECTS)
- K30 FISH (PLANTS + INSECTS) K31 FISH K32 FISH
- K33 FISH BIRDS + z zz
355 DBIRDS = K34 BIRDS (FISH + INSECTS)
- K35 BIRDS (INSECTS + FISH) K36 BIRDS K37 BIRDS
- k38 BIRDS BIRDS + z zz
360 WATER = WATER + DWATER DT
365 NUTRIENTS = NUTRIENTS + DNUTRIENTS DT
370 PLANTS = PLANTS + DPLANTS DT
375 DETRITUS = DETRITUS + DDETRITUs DT
380 INSECTS = INSECTS + DINSECTS DT
385 FISH = FISH + DFISH DT
390 BIRDS = BIRDS + DBIRDS DT
395 TT = 3
400 PSET (T TT, 180 BIRDS / 9), 2
405 PSET (T TT, 180 FISH / 9), 1
410 PSET (T TT, 180 NUTRIENTS / 9), 3
415 PSET (T TT, 180 INSECTS / 9), 3
420 DT = .01
425 T = T + DT
430 PRINT #1, USING ####.##"; NUTRIENTS; PLANTS; INSECTS; FISH;
BIRDS
435 IF T TT < 319 THEN GOTO 310
440 CLOSE
445 END


Finally, I thank the St. Johns River Water Management District as the primary
supporter of this project. They provided financial and technical support including
water quality data, areal photos, and access to the Apopka Marsh Demonstration
Project site.
IV


29
was an aggregated, macroscopic mini model of the marsh that retained the most important
components and relationships, simplified from the more complex systems diagram.
The computer program, in Appendix C, was written directly from the systems
diagram. Each component in the diagram is a state variable represented by a difference
equation. Equations were written in a Basic program based on the interactions of the
pathways between the components in the diagram. Values used to calibrate the model
were taken from studies conducted in the unsubsidized marsh and the literature (Davis
1946, Robbins 1983, Goldstein 1988, Coveney 1993, Hairston and Hairston 1993,
National Research Council 1993, Ann 1994, D'Angelo and Reddy 1994, Ivanoff and
Reddy 1994).


BIOGRAPHICAL SKETCH
Tonya Mae Howington was bom at Fort Gordon Army Base in Augusta, Georgia,
on January 2, 1966. She has three brothers (Alfred, Michael, and John) and two
half-sisters (Georgette and Shari). Her family moved to Tallahassee, Florida, in 1970
where she lived until 1991. In Tallahassee, she received an Associate in Arts degree from
Tallahassee Community College and a bachelor's degree in American Studies from Florida
State University. In 1991, she moved to Gainesville, Florida, to pursue a Master of
Science degree in environmental engineering sciences at the University of Florida. Upon
graduation, she will continue at the University of Florida to pursue a Ph.D. in the same
program. Her research will be conducted in Venezuela where she will also make her new
home.
On April 2, 1994, Tonya married Juan Jorge Haberkom. In the summer of 1994,
they moved together to Venezuela to find adventure and start a family.
143


24
Table 3. continued.
Taxonomic Group
Scientific Name
Common Name
Passerines
Savormis ohoebe
Eastern phoebe
Sterna forsteri
Foresters tern
Columbina passerina
Ground dove
Passerrina cvanea
Indigo bunting
Charadrius vociferus
Kill deer
Cistothorus Dalustris
Marsh wren
Zenaida macroura
Mourning dove
Cardinalis cardinalis
Northern cardinal
Mimus polvdottos
Northern mocking bird
Dendroica Dalmarum
Palm warbler
Cistohorus olatensis
Sedge wren
Melosn2a meloda
Song sparrow
Melosniza aeoraana
Swamp sparrow
Tachvcineta biocolor
Tree swallow
Dendrocia coronata
Yellow rumped warbler
Dendroica Detechia
Yellow warbler
Ducks
Ana americana
American widgeon
Anas discors
Blue wing teal
Dendrocvszna bicolor
Fulvous whistling duck
Anas strepera
Gadwall
Lophodvtes cucullatus
Hooded merganser
Anas platvrhvnchos
Mallard duck
Anas fulvinula
Mottled duck
Anas acuta
Northern pintail
Anas clvpeata
Northern shoveler
Aix snonsa
Wood duck
Ibis
Plegadis falcinellus
Glossy ibis
Rudocimus albus
White ibis


5
Vegetative and Wildlife Community Structure
Avian communities are often used as the primary indicators of habitat quality given
that many studies have shown that birds are often sensitive to changes in wetland structure
and function (Kroodsma 1978, Frederick and Collopy 1988, Feirerabend 1989, Cable et
al. 1989, Edelson and Collopy 1990). In addition, Edelson and Collopy (1990)
determined that constructed wetlands can provide suitable habitat for many wetland avian
species.
An important aspect of restoring wetlands converted to agricultural, or other
intensive land uses, is that successional phases may also not be the same as in natural
wetlands given that the seed source of the historic vegetative community may be lost or
out competed by more aggressive invasive species. Marsh vegetation may not ever
resemble the historic community (Maurizi and Poillon 1992). In addition, some animals
which were known to frequent the site before it was in agricultural use may not return to
use the site after its conversion back into a wetland. Animal densities may also be
different than historic levels.
Wildlife production is generally high for constructed wetlands receiving high
concentrations of nutrients according to many studies (Maehr 1984, Buckner et al. 1990,
Kerekes 1990, Kale 1992, Mcallister 1992, Knight 1992, Rader and Richardson 1992,
Hammer 1992a, 1992b, Guntenspergen et al. 1993, McAllister 1993a, 1993b, Streever
and Crisman 1993). Potential productivity at all trophic levels is set by nutrient supply
(Carpenter et al. 1985). Moreover, actual productivity depends on the recycling of
nutrients and their allocation among populations with different growth rates.
A constructed wetland (37.8 ha) in California used for wastewater treatment had
much higher avian usage than nearby natural lake and bay fringe wetlands according to
Gearheart and Higley (1993). In the first two years alone, avian species used the
constructed wetland at rates exceeding ten times that of the natural wetlands. Waterfowl


Fuel *1000%
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 29. Simulation of marsh with 1000% added subsidy.


63
Nov-91
0-0-4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Classes (kg)
Apr-92
8.00
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Classes (kg)
Nov-92
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Classes (kg)
Mean
8 00
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Classes (kg)
Figure 21. Overall avian biomass in subsidized marsh.


44
APRIL 1992
SCALE
: METERS
NORTH
250
250
i
i i
500
LEGEND
Herbs
Shrubs
Open later
Emer gen t s
Floating Aquat i c s
Typha < Open Water
Typha >= Open Water
Typha Community
Figure 11. Map of vegetative cover for April 1992.


35
Table 5. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the unsubsidized marsh.
Notes
Energy
Transformity
Emergy
1
Renewables
Sim
(J,g,$)
5.41E+09
J
(Sej/unit)
1.00E+00
(E15)
0.00
2
Rain-chemical potential
6.27E+10
J
1.54E+04
0.97
3
Total nitrogen
1.54E+04
g
4.21E+09
0.06
4
Total phosphorus
6.35E+02
g
6.88E+09
0.00
5
Nonrenewables Purchased
Construction-services
3.76E+01
$
1.60E+12
0.06
Notes to Table 5
1 Solar insolation: 1.29E6 cal/ha/yr (Odumet al. 1987)
(1.29E6 cal/ha/yr)(4.19E3J/cal) =
5.41E+09
J/ha/yr
2
Rain-chemical potential: 1.27 m/y (Odumet al. 1987)
(1.27 nVyr)(lE10 g/mha)(4.94 J/g)=
6.27E+10
J/ha/yr
3
Total nitrogen in rain: 1.21 mg/1 (Coveney 1993)
(1.21 mg/l)(lE-3g/mg)(1.27m)( 10001/11^3)
(10000 mA2/ha)=
1.54E+04
g/ha/yr
4
Total phosphorus in rain: 0.09 mg/1 (Coveney 1993)
(0.05 mg/l)(lE-3g/mg)(1.27m)( lOOOl/nf^)
(10000 mA2/ha)=
6.35E+02
g/ha/yr
5
Construction-services (Coveney 1993)
(2.2E6 $)/(241.9 ha)/(30 yr uselM life)
(30 ha/241.9 ha) =
3.76E+01
$/ha/yr


61
Table 8. --continued.
Size Class (kg)
Common Name
Average Weight (kg)
0-0.4
Sedge wren
0.01
Snowy egret
0.37
Song sparrow
0.02
0.41 -0.80
American bittern
0.68
American coot
0.76
American widgeon
0.79
Black crown night heron
0.66
Black neck stlit
0.43
Blue grosbeak
0.41
Fulvous whistling duck
0.76
Gadwall
0.79
Glossy ibis
0.79
Hooded merganser
0.70
King rail
0.43
Northern herrier
0.45
Red shoulder hawk
0.64
Wood duck
0.68
Yellow crown night heron
0.66
0.81 1.20
Great white egret
1.02
Mallard duck
1.18
Mottled duck
1.02
Northern pintail
0.91
Northern shoveler
1.00
White ibis
0.91
1.21 1.60
Anhinga
1.36
Double-crested cormorant
1.36


132
Table C-1. Computer simulation model.
5 REM SIMULATION OF CONSTRUCTED MARSH WITH PUMP SYSTEM
10 SCREEN 1, 0: COLOR 0, 0
15CLS
20 LINE (0, 0)-(319, 180), 1, B
25 OPEN "SIMMODEL" FOR OUTPUT AS #1
30 T = 1
35 WATER = 0
40 NUTRIENTS = 0
45 RNUTRIENTS = 100
50 PNUTRIENTS = 100
55 LNUTRIENTS = 100
60 PLANTS = 0
65 DETRITUS = 0
70 INSECTS = 0
75 FISH = 0
80 BIRDS = 0
85 FUEL = 0
90 SUN = 100
95 RAIN = 100
100 K0 = .0009
105K1 =30
110 K2 = .00001
115 K3 = .000099
120 K4 = .286
125 K5 = 7.5
130 K6 = 22.5
135 K14 = .0005
140 K15 = .00015
145 K16 = .05
150 K17 = .295
155 K18 = .00005
160 K19 = .3
165 K20 = .3
170K21 = .2
175 K22 = .001
180 k39 = .3
185 K23 = .00667


Increased Migration (5x) (Unsubsidized Marsh)
Years
Figure 41. Simulation of increased migration in unsubsidized marsh.


59
Biomass of Avian Community
Table 8 lists the size classes used for this study given the avian species found in
both marshes. Given in Figures 21 and 22 is avian biomass over the survey period in the
subsidized marsh and unsubsidized marsh. Overall, the size classes had significantly
different biomass between the marshes (n = 21, df = 6, p = 0.03). Within each marsh, the
biomass of the individual size classes were also significantly different (n = 21, df = 2, p =
0.03). Changes over time in biomass were not significant over the survey period in either
marsh (n = 22, df = 2 p = 0.09).
Overall avian biomass in the subsidized marsh averaged 5.11 kg ha" 1 over the
entire survey period. Average avian biomass in the subsidized marsh did not change
significantly over the survey period (n = 14, df = 1, p = 0.06.) Average avian biomass in
the unsubsidized marsh was 2.22 kg ha'l and did not significantly change over its survey
period (n = 12, df = 1, p = 0.10).
In the subsidized marsh, birds weighing 0.41-0.80 kg had the highest average
biomass of all size classes contributing 49.12% of the overall biomass. Moreover, birds
weighing 0.41-0.80 kg had the highest average biomass of all feeding types during each of
the survey periods. Birds weighing between 0-0.4 kg had the next highest average
biomass of all size classes in the subsidized marsh over the survey period. This size class
contributed 30.72% of the overall biomass.
Birds weighing 0-0.41 kg had the highest average density (39.19% of overall
biomass) in the unsubsidized marsh. In April 1993, this size class contributed 43.24% of
the overall biomass. The 0.41-0.8 kg size class had the next highest average biomass and
contributed 29.28% of the overall biomass. This size class remained unchanged over the
survey period.


SELF-ORGANIZATION OF AN ECOLOGICALLY ENGINEERED WETLAND
IN CENTRAL FLORIDA
By
TONYA MAE HOWINGTON
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
1994

To my mother and father, for all that they inspired me to overcome.

ACKNOWLEDGEMENTS
I am grateful to my committee members for their individual guidance and
assistance in the classroom and in the field. Dr. Mark Brown consistently gave me the
courage to spit in the face of disaster. Dr. G. Ronnie Best taught me to tread without
fear into new and exciting wetland frontiers. And Dr. Stephen Humphrey showed me
that I can boldly evaluate new and traditional view points in community ecology
without permission.
Other professors also greatly influenced my development as a systems
ecologist. Most notable were Dr. Howard T. Odum and Dr. David Scienceman. Both
provided me with new ways to look at the world and its future.
All my friends who helped me with avian and fish surveys deserve my special
thanks. In particular I wish to thank Chuck Graham for helping me obtain a research
project and for the use of his data. In addition, I wish to thank Ken Clough, Rodney
Pond, David Day, John Stenberg, David Clayton, Mark and Amelda Clark, Harish
Ramakarishna, Valerie Enck, Michelle Piazza, Sergio Lopez, Fred Gaines, and anyone
else who risked life and limb among the alligators.
I especially thank my husband, Juan Jorge Haberkom, for helping me conduct
surveys and providing technical advice to improve my analysis. His patience and
unending optimism kept me going even when the odds were clearly against me.
I am also indebted to Silvia Romitelli, David Clayton, and Dave Tilley for their
support and patience during the last critical weeks of my thesis writing.
m

Finally, I thank the St. Johns River Water Management District as the primary
supporter of this project. They provided financial and technical support including
water quality data, areal photos, and access to the Apopka Marsh Demonstration
Project site.
IV

TABLE OF CONTENTS
page
ACKNOWLEDGEMENTS iii
LIST OF FIGURES vii
LIST OF TABLES ix
ABSTRACT x
INTRODUCTION 1
Plan of Study 2
Self-Organization and Constructed Wetlands 2
Description of Study Site 10
METHODS 13
Energy System Diagram 13
Emergy Analysis 14
Vegetation Complexity and Structure 16
Avian Surveys 21
Fish Population Sampling 23
Computer Simulation Model 23
RESULTS 30
Ecological Systems Overview 30
Vegetative Communities 39
Avian Community Structure 53
Fish Density and Biomass 65
Computer Simulation Model 65
v

DISCUSSION 90
Conclusions 96
APPENDIX A: AVIAN SURVEY RESULTS FOR TRANSECTS 1 -4 ... 97
APPENDIX B: AVIAN SURVEY RESULTS FOR TRANSECTS 5-6 ... 122
APPENDIX C: COMPUTER SIMULATION MODEL 131
REFERENCES CITED 135
BIOLOGICAL SKETCH 143
vi

LIST OF FIGURES
page
Figure 1. Map of project site 12
Figure 2. List of energy symbols 15
Figure 3. Map of site showing numbered transects 18
Figure 4. Diagram of computer simulation model 28
Figure 5. Systems diagram of subsidized marsh 31
Figure 6. Summary diagram of emergy analysis 37
Figure 7. Water budgets for both marshes 40
Figure 8. Nutrient budgets for both marshes 41
Figure 9. Map of vegetative cover for November 1990 42
Figure 10. Map of vegetative cover for November 1991 43
Figure 11. Map of vegetative cover for April 1992 44
Figure 12. Map of vegetative cover for November 1992 45
Figure 13. Vegetative cover richness for both marshes 46
Figure 14. Vegetative cover complexity for both marshes 48
Figure 15. Vegetative percent cover of subsidized marsh 49
Figure 16. Vegetative percent cover of unsubsidized marsh 50
Figure 17. Diversity indices for avian species in both marshes 54
Figure 18. Evennesss indices for avian species in both marshes 55
Figure 19. Overall avian density in subsidized marsh 57
Figure 20. Overall avian density in unsubsidized marsh 58
Figure 21. Overall avian biomass in subsdized marsh 63
Figure 22. Overall avian biomass in unsubsidized marsh 64
Figure 23. Results of fish survey including a)density and b) biomass 66
Figure 24. Simulation of unsubsidized marsh 68
Figure 25. Simulation of marsh with 10% added subsidy 70
Figure 26. Simulation of marsh with 50% added subsidy 71
Figure 27. Simulation of marsh with 100% added subsidy 72
Figure 28. Simulation of marsh with 500% added subsidy 74
Figure 29. Simulation of marsh with 1000% added subsidy 75
Figure 30. Summary of simulation results after 70 years 76
Figure 31. Simulation of unsubsidized marsh receiving nutrients
from rain only 77
Figure 32. Simulation of unsubsidized marsh with peat contributing
only 90% of orginal nutrients 78
vii

Figure 33. Simulation of unsubsidized marsh with insects requiring
double their food requirements 79
Figure 34. Simulation of subsidized marsh with insects requiring
double their food requirements 80
Figure 35. Simulation of unsubsidized marsh with fish requiring
double their food requirements 82
Figure 36. Simulation of subsidized marsh with fish requiring
double their food requirements 83
Figure 37. Simulation of unsubsidized marsh with birds requiring
double their food requirements 84
Figure 38. Simulation of subsidized marsh with birds requiring
double their food requirements 85
Figure 39. Simulation of periodic fish kill in unsubsidized marsh 86
Figure 40. Simulation of periodic fish kill in subsidized marsh 87
Figure 41. Simulation of increased migration in unsubsidized marsh 88
Figure 42. Simulation of increased migration in subsidized marsh 89
VUl

LIST OF TABLES
page
Table 1. List of transformities used for the emergy analysis 17
Table 2. Vegetation cover types and descriptions 19
Table 3. Avian species by taxonomic group 23
Table 4. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the subsidized marsh 33
Table 5. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the unsubsidized marsh... 35
Table 6. Summary of emergy analysis of both marshes 36
Table 7. Summary of vegetative community structure 52
Table 8. Avian size classes based on average weight of species 60
Table 9. Summary of avian and fish community structure 67
IX

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
SELF-ORGANIZATION OF AN ECOLOGICALLY ENGINEERED WETLAND
IN CENTRAL FLORIDA
By
Tonya Mae Howington
December 1994
Chairperson: Dr. Mark T. Brown
Major Department: Environmental Engineering Sciences
A constructed wetland (subsidized marsh) in Central Florida receiving
continuously pumped hypereutrophic lake water was studied for two years to
determine the effect that an external subsidy had on its self-organization. This marsh
was compared to an adjacent constructed wetland that did not receive this subsidy
(unsubsidized marsh.)
Energy sources influencing each marsh's development were compared using an
emergy analysis. Both marshes were similar in natural renewable energies (0.97 El5
sej ha"* yrl ). However, when the pump structure and purchased energies were
included, the emergy flux in the subsidized marsh was 14.3 El5 sej ha"^ yrl while
the unsubsidized marsh received only 2.0 El 5 sej ha" 1 yrl The importance of this
contrast in emergy flux was reflected in two emergy ratios. The environmental loading
ratio between the subsidized marsh (13.8) and the unsubsidized marsh (0.10) indicated
a significant difference in the amount of renewable energies (solar insolation, rain,
nutrients in rain) to nonrenewable energies (primarily lake water and nutrients and
pump system) stimulating marsh self-organization. The investment ratio for the
subsidized marsh (2.10) was much greater than that of the unsubsidized marsh (0.10).
x

Therefore, purchased energies were much higher than the inputs of free energies for
the subsidized marsh.
Aerial photos were interpreted to evaluate the number of vegetative cover
types (richness), complexity (fractal dimension), and percent vegetative cover. After
two years, vegetative cover richness in the subsidized marsh was 3.25, while the
unsubsidized marsh had a richness of 4.69. Both marshes had similar levels of
moderate complexity (1.5) throughout the survey period. Typha Community had the
highest percentage of cover dominance in the subsidized marsh (66.70%) and in the
unsubsidized marsh (48.61%) at the end of the survey period. Overall, the subsidized
marsh had 89% cover of types that include Tvpha spp. The unsubsidized marsh had a
67% cover of Typha spp. cover types.
Avian surveys and a synoptic fish sampling were conducted in each marsh.
Diversity and evenness were significantly higher in the unsubsidized marsh. Avian
density and biomass were much higher in the subsidized marsh (18.48 birds ha-*; 5.11
kg ha-*) than in the unsubsidized marsh (7.05 birds ha'* ,2.22 kg ha*l ). The
subsidized marsh supported higher densities and biomass of fish (230 fish m'2 ,6.44 kg
m'2) than the unsubsidized marsh (169 fish m"2 ,4.39 kg m"2 ).
Overall, the external subsidy increased the emergy flux in the subsidized marsh
by increasing the input of nonrenewable energy sources. As a result, community
parameters such as vegetative percent cover dominance, animal density and overall
biomass were higher in the subsidized marsh, but at a cost of lowered richness and
diversity and evenness. Complexity of vegetative structure did not seem to be affected
by the increased subsidy.
xi

INTRODUCTION
Theory would suggest that an external subsidy should increase the carrying
capacity for wildlife of an ecosystem, all other things being equal. Determining the effect
that an external subsidy has on the organization of an emerging, created wetland is the
main question being asked by this thesis.
One prediction of this study is that the external nutrient subsidy increases the
energy flow in productive pathways that in the short term results in an increased food base
and leads to an increase in the number of consumers. Initially, species diversity and
evenness are predicted to be relatively low. If the subsidy is continued over many years,
then higher diversity and evenness are expected to occur. Significant structural differences
in the vegetation community between created wetlands receiving a subsidy and created
wetlands not receiving a subsidy might also be discernible such as the formation of a
monoculture. The differences in structural characteristics (mosaic of vegetation types and
open water) may account for differing wildlife densities and/or diversity between
subsidized and unsubsidized wetlands. Finally, early successional trends in
wildlife use and diversity may be observed and related to external subsidies.
This thesis is an investigation of the ecological self-organization of a constructed
wetland in Central Florida receiving continuously pumped lake water, high in nutrients and
suspended material. Called the Apopka Flow-way Demonstration Marsh Project, the
constructed wetland is part of a larger project funded by the St. Johns River Water
Management District (SJRWMD). The project's primary goals are to restore historic
wetlands and improve water quality in Lake Apopka.
1

2
Plan of Study
The research for this thesis tested theories concerning the affect of an external
subsidy on ecosystem structure and organization. Two newly established marshes (one
receiving nutrient enriched lake water and the other not receiving the subsidy) were
studied. The effect of the external subsidy was evaluated by comparing properties of the
vegetative and avian communities in the wetland receiving nutrient enriched lake water
with properties in the nearby unsubsidized wetland.
An emergy analysis was used to determine the energy sources influencing self
organization of each wetland system. In addition, budgets of water and nutrients for each
marsh were evaluated and compared. A comparison of the vegetative community
structure emerging in each marsh was presented using a landscape scale perspective. The
vegetative cover of the subsidized marsh was determined, and the spatial organization of
the vegetative community was measured. Next, wildlife usage of the subsidized marsh
was compared to the unsubsidized marsh. The density, composition, and biomass of the
avian community found in each marsh were compared. A synoptic fish survey was
conducted to supplement the avian surveys in providing a detailed description of the
wildlife communities using the project site. Finally, a computer simulation model was
developed to further test theories of community response to increased and decreased
external subsidy to a system.
Self-Organization and Constructed Wetlands
Processes which select species based on seeding or the available resources are
examples of self-organization (Beyers and Odum 1994). Odum (1983) stated that self-
organizational processes including those by which ecosystems develop structure when
taken in aggregate is succession. Examples of self-organizational processes include

3
reinforcements produced by nutrient cycling, animal and plant interactions, and the role of
keystones species.
Self-organization in constructed wetlands is dependent mostly on its hydrologic
design. Wetlands that are continuously flooded, but have shallow flowing water, as in
many constructed wetlands, have high productivities and develop quickly according to
Mitsch and Gosselink (1986.) The actual relationship between wetland productivity and
hydroperiods includes nutrient inputs, export, decomposition, and nutrient cycling.
Odum (1990) defines ecological engineering as an integration of humanity and
nature while benefiting both. Constructed and restored wetlands can be ecologically
engineered for the treatment of nonpoint source pollution (Odum 1990, Mitsch 1992, and
Hammer 1992). Nonpoint source pollution from agricultural activities is often thought to
be the major cause of surface water degradation in the United States (Baker 1992).
According to Mitsch (1992), a wetlands system may provide more efficient treatment,
greater longevity, and reduced operating requirements than other conventional methods.
Mitsch has outlined several principles of ecological engineering in various
publications which can be incorporated into the design of a treatment wetland (Mitsch
1990, 1992, Mitsch and Cronk 1992). These principles include designing the system for
minimum maintenance by allowing the system to self-organize on its own. He
recommends the use of available low quality energies such as potential energy of
downstream flow to subsidize the system with water, energy, and nutrients. He also
suggests that in some cases the use of pump systems may not increase treatment benefits
derived from a treatment marsh system. For example, some hydrologic pump systems may
require more energy resources to construct and operate than what the pumps actually
contribute to desirable wetland functions in the marsh system such as the removal of
nutrients in the water column. In environmental systems, the components of the system
which require more work in their development either contribute more to the system

commensurate with what was required to make them, or the production is discontinued
according to Odum and Arding (1991).
Knight (1992) explained that significant losses of vegetation and animals can occur
as a result of high loading of pollutants including too much water, organic matter or
nutrients. He pointed out that water flow and depth control can affect primary
productivity of the wetland and the ability of the wetland to effectively treat nonpoint
source pollution. He suggested that higher flows of shallow water provide higher
dissolved oxygen levels leading to higher secondary productivity.
Hammer (1992a) predicted that if high loading of nutrients were added to a
constructed freshwater marsh, then Tvpha spp.. Salix spp or other woody shrubs will
dominate and reduce the system's diversity. Moreover, a monoculture could develop
resulting in an overall decrease in species diversity. In another study, Hammer (1992b)
pointed out that manipulation of the water level alone can sustain a diverse, complex, and
productive marsh for many years. Furthermore, fluctuations of water levels can create
more ecological niches for more species of plants and animals.
Common techniques for establishing ecologically engineered wetlands include (1)
re-establishing or managing wetland hydrology, (2) eliminating or controlling chemical or
other contaminants affecting wetlands, and (3) reestablishing and managing native biota
(Maurizi and Poillen 1992). Not all engineering projects, however, have the
reestablishment of the original biota as a primary goal due to the immense amount of
resources required to do so. In this case, it may be more important to consider the possible
affects of the desired hydrology including the balance between nutrient removal and the
potential to increase wildlife habitat and abundance.

5
Vegetative and Wildlife Community Structure
Avian communities are often used as the primary indicators of habitat quality given
that many studies have shown that birds are often sensitive to changes in wetland structure
and function (Kroodsma 1978, Frederick and Collopy 1988, Feirerabend 1989, Cable et
al. 1989, Edelson and Collopy 1990). In addition, Edelson and Collopy (1990)
determined that constructed wetlands can provide suitable habitat for many wetland avian
species.
An important aspect of restoring wetlands converted to agricultural, or other
intensive land uses, is that successional phases may also not be the same as in natural
wetlands given that the seed source of the historic vegetative community may be lost or
out competed by more aggressive invasive species. Marsh vegetation may not ever
resemble the historic community (Maurizi and Poillon 1992). In addition, some animals
which were known to frequent the site before it was in agricultural use may not return to
use the site after its conversion back into a wetland. Animal densities may also be
different than historic levels.
Wildlife production is generally high for constructed wetlands receiving high
concentrations of nutrients according to many studies (Maehr 1984, Buckner et al. 1990,
Kerekes 1990, Kale 1992, Mcallister 1992, Knight 1992, Rader and Richardson 1992,
Hammer 1992a, 1992b, Guntenspergen et al. 1993, McAllister 1993a, 1993b, Streever
and Crisman 1993). Potential productivity at all trophic levels is set by nutrient supply
(Carpenter et al. 1985). Moreover, actual productivity depends on the recycling of
nutrients and their allocation among populations with different growth rates.
A constructed wetland (37.8 ha) in California used for wastewater treatment had
much higher avian usage than nearby natural lake and bay fringe wetlands according to
Gearheart and Higley (1993). In the first two years alone, avian species used the
constructed wetland at rates exceeding ten times that of the natural wetlands. Waterfowl

6
used the constructed wetland between 38% and 78% more than the lake and bay wetlands.
A total of ninety-eight species were documented as visiting the constructed wetland.
Lofgren (1993) found both high avian diversity and high avian density at Mitchell
Lake in Texas. Mitchell Lake had been receiving high nutrient loadings for over thirty
years. A total of 270 avian species have been sighted at the lake, thirty of which are
known to breed in the marshes.
Edelson and Collopy (1990) conducted a study of wading bird usage of a
hypereutrophic lake, and concluded that the abundance of fish stimulated a large
population of egrets and herons. The large fish population was thought to be due to the
high levels of nutrients. The birds also displayed unusual foraging behavior that may have
allowed the birds feeding in the dense Tvpha spp. stands better access to fish in deep water
areas.
Bird usage of late successional settling ponds of phosphate-mined lands may
provide a useful comparison to bird usage of created freshwater marshes used to treat
nonpoint source pollution. Both environments are high nutrient systems and are often
dominated by Salix carolinana and Tvpha spp. A survey of different phosphate mining
sites showed that late successional settling ponds contained extensive colonies of
double-crested cormorant, anhingas, black-crowned night herons, cattle and great egrets,
wood storks and white ibises (Maehr, 1984).
Vegetation density irregardless of species has been found to be an indicator of
habitat suitability for waterfowl in some studies. One study comparing
plant-macroinvertebrates associations and waterfowl found that 1 gram of animal biomass
was associated with every 100 grams of plant life (Krull 1970). Although the study did
not differentiate between cover types, it was noted that plants considered to be poor
waterfowl food harbor large quantities of macroinvertebrates which can make the area
more desirable for waterfowl usage.

7
Although animals, including macroinvertebrates, consume and recycle nutrients
from wetlands, Hammer (1992a) believes that animals do little to directly treat non-point
source pollution. He suggested, however, that the presence or absence of certain animal
communities can provide an indicator of the health of the system. It is important that one
carefully interpret the animals communities present, according to Hammer, because certain
types of species may survive better and persist longer than others in systems receiving high
nutrient loadings. Indeed, the problem of undesirable high densities of mosquitoes during
the early stages of marsh development is a real one for many treatment wetlands according
to Dill (1990.)
A study by Oliver and Schoenberg (1989) found that birds can have an indirect
positive effect on fish and macroinvertebrate populations. In their study, they showed that
ibis and other wading birds increased macro nutrient concentrations (particularly
phosphorus) increased under rookeries. Under these rookeries the fish and
macroinvertebrate densities slightly increased. In comparison, it was determined from a
study of a oligotrophic lake by Kerekes et al. (1992) that there is a close balance between
the size of a water body, nutrient loading, and its
fish production to the occupancy and production of piscivorous birds.
Early successional processes that determine the abundance of macroinvertebrates
can also affect higher trophic levels. Joyner (1980) found that pond selection by ducks in
Ontario was partially determined by invertebrate density. Invertebrate abundance
increases as the submergent vegetation replaced the emergent vegetation according to
Voigts (1976). In his study, marshes that had submerged vegetation (suggesting some
openness) interspersed with emergent vegetation (suggestion cover) had the greatest
invertebrate abundance. He further suggested that nesting birds preferred the marshes
with higher numbers of invertebrates. Feierabend (1989) also points out the importance of
invertebrates stating that they are critical to entry dynamics and functions of wetlands and
the foundation of wetland food chains.

Invertebrate abundance was positively correlated with marsh usage by waterfowl
in a study by Murkin et al. (1982). However, invertebrate abundance was not affected by
cover removal. According to Murkin, visual cues of openness may be what waterfowl
used to judge where the greatest abundance of invertebrates were to be found. This
theory was also supported by research conducted by Leschisin et al. (1992) and Wilcox
and Meeker (1992).
Landscape Scale Studies of Community Structure
Landscapes go through successional phases or stages just as smaller scale
communities (Naveh and Lieberman 1984, Bell et al. 1990). Also like communities,
landscapes are predicted to evolve over time towards more complex and diverse systems.
The development and dynamics of landscape spatial heterogeneity can be an important
factor that influences both biotic and abiotic processes (Risser et al. 1984, Forman and
Godron 1986, Turner 1987). Moreover, each successive level of biological organization
has properties that cannot be predicted from those of less complex levels such as the
difference in characteristics of populations and the individuals of which they are composed
(Odum 1971).
Often important information about a certain species behavior or the organization of
a biological community is missed because the scale of the study is not appropriate. In
addition, if the scale is spatial, then the behavior of an individual may be acting on cues of
the community or vice versa (Cody 1981, Molofsky 1994, Holmes et al. 1994, Silverman
1994, Tilman 1994.)
The different dynamics of a wetland at different scales provides additional
problems when attempting to determine community structure. Wildlife populations are
often more constant on a regional scale due to the asynchrony of the separate local

populations according to Willard and Hiller (1989). When some populations are at low
levels, others are high.
Local short term disturbances could allow species with greater colonizing ability to
recolonize disturbances (Bertness and Ellison 1987). The accumulative affect of these
events could change the areal distribution of the species and provide new patterns.
Moreover, Weller (1981) described a variety of behavioral adaptations for freshwater
wildlife species in wetlands which combine both spatial and temporal heterogeneity on a
landscape scale. Weller suggested that this heterogeneity allows internal adaptation.
A study by Doughtery (1990) evaluated the interrelationship between space and
time. One of his conclusions was that community measurements of successional
development were related to measurements of landscape pattern. Moreover, Brown
(1989) suggested that the appropriate scale from which to view any problem is the next
larger one.
Kareiva (1994) suggested in his review paper that more serious experimentation
should be performed that explicitly tests major hypotheses emerging from recent
theoretical explorations of spatial effects. Recently many ecologists are turning towards
larger scale studies to explain ecological functions and dynamics.
In his recent study, Bowers (1994) modeled both age structured and habitat
structured populations to measure the affects of age on individual performance versus the
affects of habitat selection. He found that habitat selection can have as much or more of
an affect on population dynamics in a particular ecosystem as demographic forces such as
birth, death, and migrations. Bowers also suggested that ignoring the affects of landscape
scale processes could produce misleading results.
Shaw and Atkinson (1990) introduced the terminology, components, advantages,
and current limitations of computerized GIS's for ornithological research. Two case
studies were provided as illustrations of the potential utility of GIS for ornithological
research.

10
Description of Study Site
Lake Apopka is a large (area = 124 kmA2), shallow (mean depth=1.7m)
hypereutrophic lake in Central Florida (Lowe et al. 1992). There is debate as to the
naturally occurring trophic status of the lake (Schelske and Brezonik 1992). Schelske and
Brezonik suggested that in the early 1940's a hurricane removed most of the rooted
macrophytes in the lake which lead to the early stages of increased nutrient availability and
subsequently increased algal productivity. Lowe et al. (1992) also believed that
agricultural practices since 1947 may have contributed to the eutrophication of Lake
Apopka.
Before 1947, much of the area surrounding the lake was freshwater marsh. State
and federal programs assisted local farmers in converting the marshes into agricultural use.
Nutrient enrichment of the lake further increased from water that was back pumped from
the agricultural fields. The practice was for farmers to periodically flood their fields with
lake water and then back pump nutrient enriched water into the lake prior to planting the
fields. The continuation of this farming practice today may, in part, sustain the current
trophic status of the lake which is undesirable to local fishermen and government agencies.
Addressing the nutrient status of this lake, the St. Johns River Water Management
District (SJRWMD) constructed a 200 hectare freshwater marsh on former agricultural
lands with the goal of pumping lake water through the system. Lowe et al. (1992)
suggested that pumping enriched lake water through a created marsh, filtration of
phosphorus and suspended sediments could be maximized. To determine the effectiveness
of this treatment system, the SJRWMD is conducting a pilot study of the 200 hectare
created marsh. The marsh occupies previous muck farm land which is adjacent to currently
ongoing much farm operations and undeveloped woodlands.
The Apopka demonstration project contains two marshes that are receiving
pumped lake water from Lake Apopka shown as the north marsh and the subsidized marsh

11
shown in Figure 1. The southern marsh cell called the subsdized marsh was studied for
this thesis. An unmanaged marsh located adjacent to the subsidized marsh was also
studied for this thesis and referred to as the unsubsidized marsh. The subsidized marsh
and the unsubsidized marsh maintained similar average water levels (0.76 m ) throughout
the study period.

12
PROJECT SITE
SCALE: METERS
500 500
1 1
1000
NORTH
Figure 1. Map of project site.

METHODS
This study was conducted in four stages. An emergy analysis was used to compare
the subsidized and unsubsidized marshes based on their relative external energetic inputs.
For the second stage, a geographical information system (GIS) program was used to
estimate vegetative cover. Early successional structural complexity was compared for the
first two years after the marshes were flooded with nutrient enriched water from Lake
Apopka.
Field studies were conducted in the third stage to compare the emerging properties
of the wildlife communities in each marsh. Both the fish and avian communities were
evaluated, although the avian communities were more closely studied. In the final stage, a
macroscopic-mini model of a hierarchically organized marsh community was simulated to
test theories of early succession in nutrient subsidized marshes.
Energy System Diagram
Energy system diagrams were drawn and used to organize thinking and data
collection. First complex diagrams were drawn showing all pathways and compartments
believed to be important. A second, aggregated macroscopic- minimodel was drawn and
used for simulation programming.
13

14
Ernergy Analysis
Emergy analysis was developed by Dr. H. T. Odum to provide a method of
comparing general systems (1983, 1990). The sources driving each system and the
component parts are related in the same measurable units. Generally, a systems diagram is
developed first to account for each source driving the system and the interactions of
different energies within the system. Figure 2 shows the general system symbols created
by Odum used to draw the diagram. Pathways and storages were initially measured either
in energy or material units.
Tables of the sources and the storages are made for comparisons. Each
component being evaluated is multiplied by its respective transformity to obtain its emergy
value. The flows and storage components of each system can then be compared on the
same basis. Often the transformities of the various components are compared to
determine the differences in the amount of total energy to maintain each type.
An emergy analysis table was evaluated to put in perspective the relative
contributions of pumps, water, nutrients, human services, and renewable energies driving
the marshes. Water, nutrient, and energy budgets from both renewable (rain) and
non-renewable (pumped water) services were determined to evaluate the net contribution
of each component. Renewable sources included sunlight and the chemical potential of
rain. Nonrenewable sources from pumped water included water, nutrients, and organic
matter from Lake Apopka. Purchased nonrenewable sources included the pump structure,
fuel to run the pumps, and services for construction, operation and maintenance of the
flow-away system.
Data were obtained from SJRWMD after two years of operation of the
demonstration project. Each source flow was converted into solar emjoules per year per
hectare using predetermined transformities. Transformities had been determined in other

15
Energy circuit. A pathway whose flow is proportional to
the quantity in the storage or source
upstream.
Source. Outside source of energy delivering forces
according to a program controlled form
outside, a forcing function.
Tank. A compartment of energy storage within the
system storing a quantity as the balanace
of inflows and outflows, a state variable.
Interaction. Interactive intersection of two pathways
coupled to produced an outflow in
proportion to a function of both, control
action of one flow on another, limiting
factor action, work gate.
Consumer. Unit that transforms energy quality, stores it,
and feeds it back autocatalytically to
improve inflow.
Producer. Unit that collects and transforms low-quality
energy under control interactions of high-
quality flows.
Box. Miscellaneous symbol to use for whatever unit or
function is labeled.
Figure 2. List of energy symbols.

16
studies, so that it was not necessary to recalculate their values. Table 1 lists the
transformities used in this study.
An environmental loading ratio and an investment ratio were calculated to
compare the quantities of different energy qualities entering each system. The
environmental loading ratio determined the input of nonrenewable energies (e g., external
subsidy) and divided it by the input of renewable energies (e g., sun, rain, nutrients in
rain.) The investment ratio divided the amount of purchased energy (e.g., pump system
including fuel, construction, operation and maintenance, and pump structure) entering the
system by the amount of free energies (e.g., sun, rain, nutrients, phytoplankton.)
Vegetation Complexity and Structure
Vegetative cover richness, complexity, and percent cover were determined using
aerial photos and a computer mapping program (ARCinfo). Vegetative cover types were
analyzed to provide insight into landscape scale successional processes occurring in the
subsidized and unsubsidized marshes. In November 1990, November 1991, April 1992,
and November 1992, the SJRWMD photographed the marshes from a small Cessna plane.
The photos were analyzed at the Center for Wetlands and Water Resources using
ARCinfo, a geographic information system computer mapping program.
The aerial photos of the marshes, taken by SJRWMD, were interpreted and
resulting land cover maps were digitized into ARCinfo as coverages. Vegetative percent
cover was determined for each cover type in each marsh and for each transect shown in
Figure 3 (transects were laid out for avian sampling.) Each transect had a fixed width of
35 meters on either side of the center line. Four 440 meter long transects (T1 through T4)
were established in the subsidized marsh, and two 750 meter long transects were establish
in the unsubsidized marsh (T5 and T6). Table 2 describes the eight vegetative structure
types used to generalize the cover types occurring in the survey areas.

Table 1. List of transformities used for the emergy analysis.
Energy Source
Transformity
Units
References
Sun
1.00E+00
Sej/J
Odum et al. (1987)
Rain-chemical potential
1.54E+04
Sej/J
Odum et al. (1987)
Total nitrogen
4.21E+09
Sej/g
Brown and Arding 1991
Total phosphorus
6.88E+09
Sej/g
Brown and Arding 1991
Phytoplankton
1.00E+04
Sej/J
Odum and Arding 1991
Pumped water-chemical potential
2.35E+04
Sej/J
Odum et al. 1987
Liquid fuel
6.60E+04
Sej/J
Brown and Arding 1990
Construction-structure
6.70E+09
Sej/g
Brown and Arding 1991
Construction-services
1.60E+12
Sej/$
Brown and Arding 1991
Operation and maintenance
1.60E+12
Sej/$
Brown and Arding 1991

18
TRANSECT LOCATIONS
SCALE: METERS
NORTH
250 250
1 1 1
A
500
Figure 3. Map of site showing numbered transects.

Table 2. Vegetation cover types and descriptions.
Cover Type
Includes one or more of the following:
Herbs
Panicum sdd.. Bahia spD.. Bidens spp.
Shrubs
Ludwieia spo.. Euoatorium leptophvllum.
Sambucus canadensis. Salix caroliana
Open Water
Open areas with less the 25% cover vegetative cover
Floating aquatics
Hvdrocotvle sdd.. Polveum sdd.. Altemathera spD..
Eichhomia crassipes
Emergents
Scripus spp.. Sagittaria spp.. Pontederia cordata
Typha < open water
Open water with 25-50% cover of Tvoha sdd.
Typha >= open water
Open water with 50-75% cover of Tvpha sdd.
Typha Community
Tvpha spp. interspersed with more than 25% cover of
emergents or shrubs

20
The richness of the vegetative cover types was used to compare the complexity of
the emerging marshes over the project period. Vegetative cover richness was calculated
using Margalefs index for species richness (Margalef 1958). This index was modified to
use the vegetative cover types as species and the number of vegetative patches within a
marsh or transect as individuals. Hence, the vegetative cover richness was calculated as
follows:
R = (C-l)/(log(F) (1)
where R = vegetative cover richness
C = vegetative cover type
. F = Number of cover type patches
Vegetative structure complexity was determined by measuring the fractal
dimension as described by LaGro (1991). The area and perimeter of the vegetative
patches, formed by the vegetative cover types, provided the two-dimensional
measurements of vegetative structure necessary for the calculations. Complexity was
calculated as follows:
D = 2 (log(P)/log(A)) (2)
where D = fractal dimension
P = patch perimeter
A = patch area
Percent cover provided a further description of the changes in structural
complexity of each marsh over time. Vegetative cover percentage calculations divided the
total area of each cover type by the total area of each transect or marsh as follows:

21
Cj = (Ctj / A) 100 (3)
where Cj = percent cover of type j
Ctj = total area of vegetative cover type j
A = area of marsh or transect
Vegetative cover percentages were compared between the sites using a
multivariant analysis.
Avian Surveys
The avifauna surveys were conducted using the Emlen strip technique (Emlen
1977). Avian sampling by transect began in August 1991 in the subsidized marsh.
Surveying began on the two transects in the subsidized marsh in November 1992. Avian
species were identified visually or by call. Only birds observed within thirty-five meters
from the transect center line were recorded.
Transects were surveyed every six-weeks. Sampling order for the transects
revolved from one sampling event to the next. The rotation lessened sampling bias by
surveying each transect during different morning hours.
Diversity and Evenness
Shannon diversity and evenness indexes were used to compare the avian
communities found in the surveyed marshes (Browner 1989). Diversity indices were used
to describe the number of avian species present in the marshes given the total avian
abundance. Evenness indices were used to evaluate the distribution of individuals among
the avian species present. In other words, the evenness of the avian community was high
if all species were represented by similar numbers of individuals. Low evenness indicated

22
that one or very few species dominated the community. The equation used to determine
diversity was the following:
If = (sum(Pi(sumIn(Pi))) (4)
where If = diversity
Pi = ni /N ni = number of individuals in species i
N = total number of individuals in sample
Evenness was calculated as follows:
f = If / Umax (5)
where f = evenness
Hmax = total number of species in sample
Avian diversity and evenness indexes were compared over the survey period
between the subsidized marsh and unsubsidized marsh. Only the time periods when both
marshes were surveyed were evaluated for significant differences using a multivariate
analysis.
Density and Biomass
A general profile of the changes in density occurring in the marshes compared the
avian density by taxonomic groups found in each survey area. Table 3 shows the species
included in each taxonomic group. The species under the category labeled "other were
grouped together due to the low number of species represented by the remaining
taxonomic groups counted. A multivariate analysis was used to compare avian density in
the subsidized marsh and unsubsidized marsh during the period when both marshes were
surveyed.
Calculations for avian density divided the total number of birds counted in each
taxonomic group by the total area of the transects in the surveyed marsh:

23
Table 3. Avian species by taxonomic group.
Taxonomic Group
Scientific Name
Common Name
Gallinules
Flica americana
American coot
Gallinula cholorpus
Common moorhen
Rallus elecans
King rail
Porrihvrula martinica
Purple gallinule
Porzana Carolina
Sora rail
Wading Birds
Botaurus lenlitnnosus
American bittern
Nvcticorax nvcticorax
Black crown mght heron
Bubulcus ibis
Cattle egret
Ardea herodias
Great blue heron
Casmerodius albus
Great white egret
Butorides striatus
Green back heron
Lxobrvchus exilis
Least bittern
Egretta caerulea
Little blue heron
Egretta thula
Snowy egret
Eeretta tricolor
Tri-color heron
Nvcticorax violaceus
Yellow crown night heron
Black Birds
Ouiscalus major
Boat tail grackle
Ouiscalus quiscalus
Common grackle
Aeriaius phoeniceus
Red wing black bird
Passerines
Hirundo rustica
Bam swallow
Polioptila caerulea
Blue-gray gnatcatcher
Guiraca caerrulea
Blue grosbeak
Cvanocitta cristata
Blue jay
Thrvothorus ludovicianus
Carolina wren
Chaetura pelasnca
Chimney swift
Geothlvpis trichas
Common yellow throat
Tvrannus tvrarmus
Eastern kingbird

24
Table 3. continued.
Taxonomic Group
Scientific Name
Common Name
Passerines
Savormis ohoebe
Eastern phoebe
Sterna forsteri
Foresters tern
Columbina passerina
Ground dove
Passerrina cvanea
Indigo bunting
Charadrius vociferus
Kill deer
Cistothorus Dalustris
Marsh wren
Zenaida macroura
Mourning dove
Cardinalis cardinalis
Northern cardinal
Mimus polvdottos
Northern mocking bird
Dendroica Dalmarum
Palm warbler
Cistohorus olatensis
Sedge wren
Melosn2a meloda
Song sparrow
Melosniza aeoraana
Swamp sparrow
Tachvcineta biocolor
Tree swallow
Dendrocia coronata
Yellow rumped warbler
Dendroica Detechia
Yellow warbler
Ducks
Ana americana
American widgeon
Anas discors
Blue wing teal
Dendrocvszna bicolor
Fulvous whistling duck
Anas strepera
Gadwall
Lophodvtes cucullatus
Hooded merganser
Anas platvrhvnchos
Mallard duck
Anas fulvinula
Mottled duck
Anas acuta
Northern pintail
Anas clvpeata
Northern shoveler
Aix snonsa
Wood duck
Ibis
Plegadis falcinellus
Glossy ibis
Rudocimus albus
White ibis

25
Table 3. continued.
Taxonomic Group Scientific Name Common Name
Other
Falco sparverius
American kestrel
Anhinca anhinga
Anhinga
Hialiaeetus leucocephalus
Bald eagle
Cervle alcvon
Belted kingfisher
Himantoous mexicanus
Black neck stlit
Coraevps atratus
Black vulture
Gallinas calimaco
Common snipe
Phalacrocorax nelacicus
Double-crested cormorant
Trinca melanoleuca
Greater yellow legs
Lanius ludovicianus
Logger headed shrike
Circus cvaneus
Northern herrier
Pandion haliaetus
Osprey
Podilvmbus podiceps
Pied billed grebe
Buteo lineatus
Red shoulder hawk
Cathartes aura
Turkey vulture
CatoDtroDhorus semiDalmatus
Willet

26
Di Nij / Ai (6)
where Di = density of transect i
Nij = number of birds in taxonomic group j
Ai = area of transects
Calculations for overall avian density for each marsh divided the total number of
birds in each taxonomic group by the total area of all surveyed transects in that marsh.
Total area in the subsidized marsh using four transects was 15.2 ha. The area of two
transects used in the unsubsidized marsh totaled 10.50 ha.
The survey results were averaged over three six month time periods to provide a
more general representation of temporal changes in density. These time periods coincided
with the dates of the aerial photography excluding the November 1990 photo. As
previously mentioned, the total surveying period was not long enough to detect seasonal
trends. Surveys averaged from August 1991 to January 1992 refereed to the November
1991 aerial photo of vegetation cover. Surveys averaged from February to June 1992
referred to the April 1992 aerial photo. All remaining averaged surveys referred to the
November 1992 aerial photo. A multivariate analysis was used to compare differences in
avian density between the surveyed areas over the survey period.
Avian biomass was used to further detail avian community organization at the
project site. The average weight of each species determined the size class in which it
belonged (Terres 1980). Size classes were grouped into six categories : a) 0-0.4 kg; b)
0.41-0.8 kg; c) 0.81'1 .2 kg; d) 1.21-1 .6 kg; e) 1.61-2.0 kg; and f) over 2.0 kg.
Calculations for size class biomass for the divided the total avian biomass in each size class
by the total area of the transects in the surveyed marsh as follows:
Dt = Ntj / At (7)
Dt = biomass of transect
Ntj = biomass in size class j
At = area of transects
where

27
The results for avian biomass were averaged over the same three time periods to
coincide with the vegetation sampling as for avian density. A multivariate analysis was
used to compare biomass between the surveyed areas for significant differences.
Fish Population Sampling
A synoptic study on the fish population of the subsidized and unsubsidized marshes
was based on a modified enclosure trap technique (Freeman, et al., 1984). A trash can
with a quarter meter square bottom was used to capture fish. The can was quickly pushed
down into the water at random locations off the transects in the surveyed marshes. Fish
trapped within the can were scooped out by using net's and collected. A total of ten
samples were taken per transect. Sampling events which resulted in no fish being tapped in
the can were included as zeros when adding the total number of fish captured.
Sampling occurred three times every other week from June through August in
1993. Collected specimens from ten samples were weighed, sexed, and the species
identified. The specimens were preserved in 10% formalin solution for six months for
reference.
Fish diversity and evenness were not calculated because efficiencies for sampling
were not calculated. Fish densities were calculated by dividing the number of fish
captured by one square meter. Biomass of fish densities was calculated by dividing the
total biomass of each fish captured by one square meter. Fish densities and biomass were
compared between each marsh using a multivariate analysis.
Computer Simulation Model
A computer model of the marsh system, shown in Figure 4, was simulated to test
theories related to the affects of external subsidies on community productivity. The model

Figure 4. Diagram of computer simulation model.
to
00

29
was an aggregated, macroscopic mini model of the marsh that retained the most important
components and relationships, simplified from the more complex systems diagram.
The computer program, in Appendix C, was written directly from the systems
diagram. Each component in the diagram is a state variable represented by a difference
equation. Equations were written in a Basic program based on the interactions of the
pathways between the components in the diagram. Values used to calibrate the model
were taken from studies conducted in the unsubsidized marsh and the literature (Davis
1946, Robbins 1983, Goldstein 1988, Coveney 1993, Hairston and Hairston 1993,
National Research Council 1993, Ann 1994, D'Angelo and Reddy 1994, Ivanoff and
Reddy 1994).

RESULTS
Ecological Systems Overview
Given in Figure 5 is a systems diagram showing important processes
occurring in the subsidized marsh. The unsubsidized marshes the same components with
the exception of the pump system. Energy sources influencing the marsh system included
renewable and nonrenewable sources. Non-renewable sources were further divided into
free sources obtained from the environment, and purchased sources which were obtained
after the transfer of money. SJWMD was included as the source of money for the
purchased nonrenewables.
Renewable sources, sunlight and rain, are shown on the left side of diagram
originating outside the marsh system's border. Free non-renewable sources were drawn in
the upper left portion of the diagram. These sources include water, nutrients, and organic
matter from Lake Apopka. Purchased non-renewables include fuel used to operate the
pumps, construction costs for the physical components of the pump system and for the
services required for installation. Also, the costs for operation and maintenance of the
flow-way marsh project were represented.
Components within the system boundaries in the diagram were divided into three
types: producers, consumers, and storages. Producers include macrophytes and algae
which grow using sunlight and nutrients. As shown in the diagram by the pathway
connections, the productivity of these plants largely depends on the nutrient concentration
in the water column.
30

Figure 5. Systems diagram of subsidized marsh.

32
The consumers in the diagram are organized in trophic levels beginning with
macroinvertebrates and ending with the bird population. Each trophic level was
positioned in the diagram from left to right based on the principle of hierarchical
organization according to decreasing amount of energy flux on pathways. Pathways to
and from the consumers represent primary food sources and biological wastes.
Macroinvertebrates are shown to primarily consume detritus. Fish consume both
macroinvertebrates and submerged and floating vegetation. Finally, birds consume both
macroinvertebrates and fish. The biological wastes of each species after death, including
plants, recycle in the system to add to the nutrient storages. Depreciation of each
component and the process was drawn to converge at the drain at the bottom of the
diagram.
Emergv Analysis
Entergy analysis tables were developed separately for the subsidized and
unsubsidized marshes. Given in Tables 4 and 5 and summarized in Table 6 and Figure 6 is
the emergy analysis of the energy sources of the two marsh systems. Each table was
divided into four columns including: name of the energy source contributing to the
system, energy, material or dollar flux, solar transformity, and resulting emergy flux. In
addition to the driving forces were categorized as renewable and non-renewable sources.
Ratios of free to purchased energy (environmental loading) and non-renewable energy to
renewable energy (investment ratio) were calculated.
Renewable energy sources for the subsidized marsh and the unsubsidized marsh
included solar energy and the chemical potential of rain. The total emergy flux for these
flows was the same in both marshes. The emergy contribution of total nitrogen and
phosphorus inputs to the unsubsidized marsh was assumed to come from rain only. The

33
Table 4. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the subsidized marsh
Notes
Energy
Transformity
Emergy
Renewables
(Sej/unit)
(E15)
1
Sun
5.41E+09
J
l.OOE+OO
0.00
2
Rain-chemical potential
6.27E+10
J
1.54E+04
0.97
Nonrenewables Free
3
Total nitrogen
7.85E+05
g
4.21 E+09
3.30
4
Total phosphorus
4.31E+04
g
6.88E+09
0.30
5
Phytoplankton
2.12E+04
J
1.00E+04
0.00
6
Pumped water-chemical potential
2.39E+09
J
2.35E+04
0.06
Nonrenewables Purchased
7
Liquid fuel
1.21E+11
J
6.60E+04
7.96
8
Construction-structure
5.11E+03
g
6.70E+09
0.03
9
Construction-services
9.34E+01
$ .
1.60E+12
0.15
10
Operation and maintenance
9.55E+02
$
1.60E+12
1.53
Notes to Table 4
1 Solar insolation; 1.29E6 cal/ha/yr (Odum et al. 1987)
(1.29E6 cal/ha/yr)(4.19E3J/cal) =
5.41 E+09
J/ha/yr
2
Rain-chemical potential: 1.27 m/y(Odum etal. 1987)
(1.27 m/yrXlE10 g/mha)(4.94 J/g)=
6.27E+10
J/ha/yr
3
Total nitrogen; 1.64 mg/1 (Coveney 1993)
(1.64 mg/lX40 cfeX28.3 l/cf)(3.15E7 sec/yr)
(IE-3 g/mg)/74.5 ha)=
7.85E+05
g/ha/yr
4
Total phosphorus: 0.09 mg/1 (Coveney 1993)
(0.09 mg/lX40 cfsX28.2 l/cf)(3.15E7 sec/yr)
(lE-3)/(74.5 ha)=
4.31E+04
g/ha/yr

34
Table 4. continued.
5 Phytoplankton (as chlorophyll-a): 8.84 E-3 mg/1 (Lowe et al. 1992)
(8.84E-3 mg/lX40 cfsX28.3 l/cf)(3.15E7 sec/yr)
(IE-3 g/mg)(5J/g)/74.5 ha) = 2.12E+04 J/ha/yr
6 Pumped water-chemical potential (Coveney 1993)
(40 cfs)(7.48 gal/cf)(3700 g/galX3.15E7 sec/yr)
((5J/g)/(74.5)= 2.39E+09 J/ha/yr
7 liquid fuel: 61,532 gal/yr diesel and 1044 gal/yr oil (Coveney 1993)
(6.26E4 gal/yrX 1-46E8 J/gal)/(74.5 ha)= 1.21 E+l 1 J/ha/yr
8 Construction structure : 2.54 lb (Coveney 1993)
(2.54E4 lbX4.5E2 g/lb)/(30 yr useful life)/(74.5 ha)= 5.11 E-K)3 J/ha/yr
9 Construction-services (Coveney 1993)
(2.2E6 $V(241.9 ha)/(30 yr uselful life)
(74.5 ha/241.9 ha) = 9.34E+01 $/ha/yr
10 Operation and maintenance (Coveney 1993)
(7.5E5$)/(241.9haX74.5/241.9ha)= 9.55E+02 $/ha/yr

35
Table 5. Annual energy, material and dollar flows and resulting
emergy flows supporting 1 hectare of the unsubsidized marsh.
Notes
Energy
Transformity
Emergy
1
Renewables
Sim
(J,g,$)
5.41E+09
J
(Sej/unit)
1.00E+00
(E15)
0.00
2
Rain-chemical potential
6.27E+10
J
1.54E+04
0.97
3
Total nitrogen
1.54E+04
g
4.21E+09
0.06
4
Total phosphorus
6.35E+02
g
6.88E+09
0.00
5
Nonrenewables Purchased
Construction-services
3.76E+01
$
1.60E+12
0.06
Notes to Table 5
1 Solar insolation: 1.29E6 cal/ha/yr (Odumet al. 1987)
(1.29E6 cal/ha/yr)(4.19E3J/cal) =
5.41E+09
J/ha/yr
2
Rain-chemical potential: 1.27 m/y (Odumet al. 1987)
(1.27 nVyr)(lE10 g/mha)(4.94 J/g)=
6.27E+10
J/ha/yr
3
Total nitrogen in rain: 1.21 mg/1 (Coveney 1993)
(1.21 mg/l)(lE-3g/mg)(1.27m)( 10001/11^3)
(10000 mA2/ha)=
1.54E+04
g/ha/yr
4
Total phosphorus in rain: 0.09 mg/1 (Coveney 1993)
(0.05 mg/l)(lE-3g/mg)(1.27m)( lOOOl/nf^)
(10000 mA2/ha)=
6.35E+02
g/ha/yr
5
Construction-services (Coveney 1993)
(2.2E6 $)/(241.9 ha)/(30 yr uselM life)
(30 ha/241.9 ha) =
3.76E+01
$/ha/yr

36
Table 6. Summary of emergy analysis of both marshes.
Emergy Flows
Subsidized Marsh
Unsubsidi2ed Marsh
(E15)
(El 5)
Renewable Emergy
1.0
1.0
Nonrenewable Emergy
Free
3.7
1.0
Purchased
9.7
0.1
Total Emergy Flux
14.3
2.0
Emergy Index Subsidized Marsh Subsidized Marsh
Environmental Loading 13.8 0.1
Investment Ratio 2.1 0.1

37
9.7
Subsidized Marsh
0.1
Unsubsidized Marsh
Figure 6. Summary diagram of emergy analysis.

38
additional lake water pumped into the subsidized marsh increased the emergy of total
nitrogen and total phosphorus by two magnitudes higher than that entering the
unsubsidized marsh. Free nonrenewable energy sources influencing self-organization in
the subsidized marsh included nutrients and phytoplankton pumped into the marsh with
lake water and the chemical potential of the pumped water itself. The emergy flux of
these flows contributed 26% of the total emergy flow to the subsidized marsh.
Only two nonrenewable purchased energy sources were included in the subsidized
marsh system that were not also part of the unsubsidized system. These included liquid
fuel used to operate the hydraulic pumps and the physical structure of the pump system
itself. The combination of these two flows contributed 68% of the total emergy flow to
the subsidized marsh.
The environmental loading ratio showed a large contrast between the two marshes.
In the subsidized marsh the environmental loading ratio was 13.8. The unsubsidized
marsh had an environmental loading ratio of 0.1. Investment ratios for the two marshes
showed a large difference in the amount of purchased energy necessary to maintain the
flows of environmental inputs. The subsidized marsh had an investment ratio of 2 .1 and
the unsubsidized marsh had an investment ratio of 0.1.
The total solar emergy inputs entering the subsidized marsh were significantly
higher than the unsubsidized marsh system. The total solar emergy input to the subsidized
marsh was 14.30 E15 sej ha-1 yr"1. In comparison, the total solar emergy input to the
unsubsidized marsh is 1.09 El5 sej ha"1 yr'1. The largest single factor contributing to
this difference was the fuel used to run the pump system in the subsidized marsh (7.96 El5
sej ha-1 yr.)

39
Budgets of Water and Nutrients
Given in Figures 7 and 8 are water and nutrient budgets for both marshes. The
pump system supplies 96% of the water entering the subsidized marsh. In the
unsubsidized marsh, rain supplies the 100% of the water. In addition, the turnover of the
water in the subsidized marsh was determined to be approximately 25 times faster than
that of the unsubsidized marsh.
Nutrient budgets in the two marshes were also different. The pump system
supplied 55% of the total nitrogen and phosphorus entering the subsidized marsh, and the
nutrient rich peat supplied 35%. Rain supplied the majority of total nitrogen and
phosphorus to the unsubsidized marsh (75%).
Vegetative Communities
Richness of Vegetative Cover Types
Figures 9-12 show the vegetative cover of the overall marshes for four time
periods. Over the avian survey period, richness of vegetative cover types changed
following different patterns in each marsh as shown in Figure 13. Richness in the
subsidized marsh increased between November 1990 to November 1991 by one index
level from 2.86 to 3.86. In April 1992 richness decreased to 3.25, and remained at that
level in November 1992.
Richness was highest in the unsubsidized marsh in November 1990 at 5.00. In
November 1991 and April 1992 richness decreased. However, by November 1992,
richness in the unsubsidized marsh had increased again to near its original level at 4.69.
Using a paired t-test it was determined that richness between the subsidized and
the unsubsidized marsh was significantly different (n = 13, df = 5.5, p = 0.02).

40
Subsidized Marsh
(9 day turover)
Unsubsidized Marsh
(221 day turover)
Figure 7. Water budgets for both marshes.

41
Unsubsidized Marsh
Figure 8. Nutrient budgets for both marshes.

42
NOVEMBER 1990
lili
¡HI lip
n
i
i
I
i
i
j
H1!
SCALE: METERS
250 250
1 1 1
500
NORTH
LEGEND
Hl! :5
lilil Herbs ;3 Flo
E3 Shrubs K// Typ
Open Water ^ Typ
. Eme r gen t s S! Typ
ating Aquatics
b a < Open Water
b a >= Open Water
la Connnunity
Figure 9. Map of vegetative cover for November 1990.

43
NOVEMBER 1991
SCALE: METERS
NORTH
250 250
1 1 1
-4
k
500
Herbs
Shrubs
Open Water
Erne r g e n t s
LEGEND
Floating Aquatics
Typha < Open Water
Typha >= Open Water
Typha Community
Figure 10. Map of vegetative cover for November 1991

44
APRIL 1992
SCALE
: METERS
NORTH
250
250
i
i i
500
LEGEND
Herbs
Shrubs
Open later
Emer gen t s
Floating Aquat i c s
Typha < Open Water
Typha >= Open Water
Typha Community
Figure 11. Map of vegetative cover for April 1992.

45
NOVEMBER 1992
SCALE: METERS
250 250
1 1
500
"LEGEND
Floating Aquatics
Typha < Open Water
Typha >= Open later
Typha Community
Herbs
Shrubs
Open later
Emergent s
P7;
(A
m
m
NORTH
Figure 12. Map of vegetative cover for November 1992.

Figure 13. Vegetative cover richness for both marshes.

47
Vegetative Structure Complexity
Complexity, measured as the fractal dimension of vegetative structure, was similar
in the subsidized and unsubsidized marshes (n = 8, df = 7, p = .63 .) In addition,
complexity appeared to change in a similar pattern in both
marshes as shown in Figure 14. Each marsh seemed to display moderate complexity
throughout the survey period.
Percent Cover of Vegetative Cover Types
Figures 15 and 16 show the vegetative cover of the subsidized and unsubsidized
marsh over the two year period. Vegetative cover in the subsidized marsh changed
significantly over time (n = 36, df = 11, p = 0.01) as well as in the unsubsidized marsh (n =
36, df= 11, p = 0.03.)
In November 1990, the two marshes had significantly different distribution of
cover types (n = 18, df = 8, p = 0.01). The subsidized marsh was dominated by herbs
(86.17%.) Shrub cover and open water were the only other predominant cover types in
the subsidized marsh, but were at less than 10% cover.
Although in the unsubsidized marsh herbs (43.04%) were the predominate cover
type, shrub cover (29.79%) was greater in this marsh than in the subsidized marsh. The
cover of floating aquatics and Tvpha dominated community were also greater than 10% in
the unsubsidized marsh.
Overall, vegetative cover in the two marshes had changed considerably over the
previous year. In November 1991, the percent cover of the various cover types in the two
marshes were again significantly different (n=18, df=8,p = 0.01). Tvpha >= open
water in the subsidized marsh covered the greatest area (34.20%), and Tvpha < open
water had the next highest percent cover (28.58%).

2.00
1.80
Nov-90 Nov-91 Apr-91 Apr-92 Nov-92
Subsidized Marsh D Unsubsidized Marsh
Figure 14. Vegetative cover complexity for both marshes.

49
Nov-90
100.00
o 80.00
U 60.00
I 40.00
JJ
20.00
0.00
Nov-91
Herbs Sfinite Open Water Floating Emergents Typha< Open Typha >= Open Typha
Aquatics Water Water Community
Apr-92
100.00
80.00
60.00 "
40.00
20.00
0.00
Herbs
Shrubs
Open Water
Floating
Aquatics
Emergents
Typha < Open Typha >= Open
Wala Water
Typha
Community
100.00 -
g 80.00 "
5 60.00 "
§ 40.00 "
CL
20.00 -
0.00 4-
Herbs
Nov-92
Shmbs
Open Water Floating Emergents TyphaOpen Typha >= Open Typha
Aquatics Water Water Community
Figure 15. Vegetative percent cover of subsidized marsh.

50
Nov-90
CL
100.00 -
80.00
60.00 -
40.00
20 00 WmSim
0.00 4
Herbs
Shrubs Open Water Floating Emugents Typha < Open Typha >= Open Typha
Aquatics Water Water Community
Nov-91
100.00 -
80.00-
5 60.00 '-
| 40.00 -
** 20.00 -
0.00
Herbs
Shrubs Open Water Floating Emergents Typha < Open Typha >= Opm Typha
Aquatics Water Water Community
Apr-92
loo.oo --
80.00 -
60.00 -
40.00 -
20.00 --
0.00
Herbs
Shrubs Open Water Floating Emergen ts Typha < Opm Typha >= Opm Typha
Aquatics Water Water Community
loo.oo --
0 80.00 --
O 60.00 '
| 40.00-
0
20.00 -
0.00
Herbs
Nov-92
Shrubs Opm Water Floating Emergents Typha < Opm Typha >= Opm Typha
Aquatics Water Water Community
Figure 16. Vegetative percent cover of unsubsidized marsh.

51
Shrubs were the predominate cover type in the unsubsidized marsh in November
1991 at 59.86%. The next highest percent cover was open water at 15.71%. In addition,
Tvpha >= open water had increased to 10.88% cover in the unsubsidized marsh.
In April 1992 the percent cover of the various cover types had significantly
distributions (n = 18, df = 8, p = 0.03). Both marshes reflected a progression towards
more dense cover types that included Tvpha spp. In the subsidized marsh the Tvpha
Community had increased to 57.51% cover. Tvpha >= open water and open water were
also important cover types in the subsidized marsh at this time at 18.32% and 17.51%,
respectively.
In April 1992 Tvpha Community had become the most important cover type in the
unsubsidized marsh covering 70.71%. For the first time in the unsubsidized marsh,
emergents began to become a significant cover type at 12.74% in April 1992.
In November 1992 the marshes again had significantly different distributions of
percent cover (n = 27, df = 8, p = 0.02). The subsidized marsh was covered mostly by
Tvpha Community at 66.70% cover. The next most important cover type was Tvpha >=
open water at 14.36% cover. The remaining cover types present were represented at a
cover of less than 10% each.
Tvpha Community was also the predominate cover type in the unsubsidized marsh
covering 48.61%. However, other cover types also began to become more evident such
as emergents (21.53%) and Typha >= Open Water (18.12%.) Table 7 summarizes the
results of the vegetative community structure study in both marshes.

Table 7. Summary of vegetative community structure.
Parameter Subsidized Marsh Unsubsidized Marsh Significant Difference
Richness 3.31
Complexity 1.45
Dominate Cover Type (%)
Nov-90 Herbs
86.17%
Nov-91 Typha >= Open Water
34.20%
4.32
n= 13, df = 5.5, p = 0.02
1.49
Herbs
n= 18, df = 8, p = 0.02
43.04%
Shrubs
n= 18, df = 8, p = 0.01
59.86%
Apr-92 Typha Community
34.07%
Typha Community
15.98%
n = 18, df= 8, p = 0.03
Nov-92 Typha Community
66.70%
Typha Community
48.61%
n= 18, df= 8, p = 0.02

53
Avian Community Structure
Diversity of Avian Community
Average avian species diversity in the two marsh areas was lowest in the
subsidized marsh and highest in the unsubsidized marsh as shown in Figure 17. The
subsidized marsh had an average species diversity of 2.65, and the unsubsidized marsh had
an average diversity of 3.04. Average diversity among the subsidized and unsubsidized
marshes was significantly different (n = 54, df = 4, p = 0.02) over the time both marshes
were surveyed.
After an initial increase, averaged diversity in the subsidized marsh seemed to
gradually decrease over the survey period. The change in diversity over the survey period
was significant (n = 14, d = 5, p = 0.04.)
Evenness of Avian Community
In Figure 18 it is shown that evenness for the subsidized marsh did not differ
significantly over time (n = 14, df = 5, p = 0.08). Average evenness was 0.67. Results for
evenness revealed that the unsubsidized marsh had more species of greater abundance than
the subsidized marsh. Average evenness for the unsubsidized marsh was 0.82. Evenness
was significantly different between the subsidized and unsubsidized marsh (n = 54, df=
4, p = 0.02).

TI
f
ft
<
rt>
n
en
a
o-
(
o
C/3
&
1.
J
3
en
T3
8
*
a>
en
CT
O
PJ
H
en
3*
n>
en
Shannon Diversity Index
Unsubsidized Marsh
Shannon Diversity Index
OOt KKJUOJJ^
onouionono
ooooooooo
Aug-91
Sep-91
Nov-91
Jan-92
Feb-92
Apr-92
May-92
Jun-92
Aug-92
Sep-92
Oct-92
Nov-92
Dec-92
Jan-93
Feb-93
Mar-93
Apr-93
May-93
Jun-93
Mean
en
&
2
5
e-n

55
Subsidized Marsh
1.00
Unsubsidized Marsh
1.00
o
.S
0.75
0.50
£ 025
0.00
Figure 18. Evenness indices for avian species in both marshes.

56
Density of Avian Species
Shown in Figures 19 and 20 are avian densities for the subsidized and unsubsidized
marshes. Data were aggregated to correspond to data of aerial photos. The results for
each transect individually by marsh is presented in Appendix B for the subsidized marsh
and in Appendix C for the unsubsidized marsh.
Avian density increased over the survey period in the subsidized marsh (n = 14,
df- 6, p = 0.01) with some fluctuation. Overall average avian density (18.48 birds ha'l)
remained high in the subsidized marsh throughout the survey period. In November 1991,
the average avian density decreased to 16.58 birds haV By April 1992 average density
had begun to increase. In November 1992, avian density averaged 20.18 birds ha" V
During the period that the unsubsidized marsh was surveyed the average avian
density was 7.07 birds ha"*. Avian density did not change significantly over the survey
period (n = 8, df = 2, p = 0.08.)
In the subsidized marsh, black birds had the highest average density of all
taxonomic groups over the survey period representing 46.11% of the overall density. In
contrast, gallinules had the highest average density of all other taxonomic groups in the
unsubsidized marsh for the November 1992 survey period. Gallinules represented 28.57%
of the overall density in the unsubsidized marsh. In April 1993, black birds had the highest
average density in the unsubsidized marsh with 27.44% of the overall density.
The taxonomic groups were compared among the two marshes for overall
differences. Overall, the feeding types had significantly different densities between the
marshes (n = 21, df = 6, p = 0.02). Within each marsh, the density of the individual
feeding types were also significantly different (n = 98, df = 9, p = 0.04).

57
Nov-91
25.00
20.00
Apr-92
Passerines
Nov-92
u
Gallinules Wading Birds Black Birds Insectivorous Ducks ibis Other Total
Passerines
Mean
25.00
20.00
Passerines
Figure 19. Overall avian density in subsidized marsh.

58
Nov-91
Figure 20. Overall avian density in unsubsidized marsh.

59
Biomass of Avian Community
Table 8 lists the size classes used for this study given the avian species found in
both marshes. Given in Figures 21 and 22 is avian biomass over the survey period in the
subsidized marsh and unsubsidized marsh. Overall, the size classes had significantly
different biomass between the marshes (n = 21, df = 6, p = 0.03). Within each marsh, the
biomass of the individual size classes were also significantly different (n = 21, df = 2, p =
0.03). Changes over time in biomass were not significant over the survey period in either
marsh (n = 22, df = 2 p = 0.09).
Overall avian biomass in the subsidized marsh averaged 5.11 kg ha" 1 over the
entire survey period. Average avian biomass in the subsidized marsh did not change
significantly over the survey period (n = 14, df = 1, p = 0.06.) Average avian biomass in
the unsubsidized marsh was 2.22 kg ha'l and did not significantly change over its survey
period (n = 12, df = 1, p = 0.10).
In the subsidized marsh, birds weighing 0.41-0.80 kg had the highest average
biomass of all size classes contributing 49.12% of the overall biomass. Moreover, birds
weighing 0.41-0.80 kg had the highest average biomass of all feeding types during each of
the survey periods. Birds weighing between 0-0.4 kg had the next highest average
biomass of all size classes in the subsidized marsh over the survey period. This size class
contributed 30.72% of the overall biomass.
Birds weighing 0-0.41 kg had the highest average density (39.19% of overall
biomass) in the unsubsidized marsh. In April 1993, this size class contributed 43.24% of
the overall biomass. The 0.41-0.8 kg size class had the next highest average biomass and
contributed 29.28% of the overall biomass. This size class remained unchanged over the
survey period.

60
Table 8. Avian species by size class.
Size Class (kg) Common Name Average Weight (kg)
_____
American kestrel
0.11
Bam swallow
0.02
Belted kingfisher
0.15
Blue jay
0.03
Blue wing teal
0.09
Boat tail grackle
0.11
Bue-gray gnatcatcher
0.04
Carolina wren
0.02
Cattle egret
0.34
Chimney swift
0.02
Common grackle
0.11
Common moorhen
0.40
Common snipe
0.13
Common yellow throat
0.01
Eastern kingbird
0.04
Eastern phoebe
0.02
Foresters tem
0.11
Greater yellow legs
0.21
Green back heron
0.18
Ground dove
0.00
Indigo buntirg
0.02
Kill deer
0.09
Least bittern
0.07
Little blue heron
0.40
Logger headed shrike
0.05
Marsh wren
0.02
Mourning dove
0.00
Northern cardinal
0.04
Northern mocking bird
0.06
Palm warbler
0.01
Pied billed grebe
0.30
Purple gallinule
0.40
Red wing black bird
0.03

61
Table 8. --continued.
Size Class (kg)
Common Name
Average Weight (kg)
0-0.4
Sedge wren
0.01
Snowy egret
0.37
Song sparrow
0.02
0.41 -0.80
American bittern
0.68
American coot
0.76
American widgeon
0.79
Black crown night heron
0.66
Black neck stlit
0.43
Blue grosbeak
0.41
Fulvous whistling duck
0.76
Gadwall
0.79
Glossy ibis
0.79
Hooded merganser
0.70
King rail
0.43
Northern herrier
0.45
Red shoulder hawk
0.64
Wood duck
0.68
Yellow crown night heron
0.66
0.81 1.20
Great white egret
1.02
Mallard duck
1.18
Mottled duck
1.02
Northern pintail
0.91
Northern shoveler
1.00
White ibis
0.91
1.21 1.60
Anhinga
1.36
Double-crested cormorant
1.36

Table 8. continued.
Size Class (kg)
Common Name
Average Weight (kg)
1.21 1.60
Osprey
1.36
>2.10
Bald eagle
4.54
Black vulture
2.28
Great blue heron
2.95
Turkey vulture
2.20

63
Nov-91
0-0-4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Classes (kg)
Apr-92
8.00
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Classes (kg)
Nov-92
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Classes (kg)
Mean
8 00
0-0.4 0.41-0.8 0.81-1.2 1.21-1.6 1.61-2.0 >2.0 Total
Size Classes (kg)
Figure 21. Overall avian biomass in subsidized marsh.

Figure 22. Overall avian biomass in unsubsidized marsh.
Size Classes (kg)
Kilograms per hectare
Kilograms per hectare
Kilograms per hectare
ON
4^
Nov-92

65
Fish Density and Biomass
Although similar species were found in the subsidized and unsubsidized marshes,
fish densities were significantly different (n = 30, df = 5, p = 0.01). The subsidized marsh
had an average density of 230 fish m"2 as shown in Figure 23. Average fish density in the
unsubsidized marsh was 165 fish m"2.
Fish species found in the subsidized marsh included Gambusia affinis. Heterandria
formosa. and Ictalurus nebulosus. G. affinis. H, formosa. and Talapia spp. were the
species found in the unsubsidized marsh. Although subsidized marsh samples did not
include Talapia spp. there were sightings of large individuals and nests in open areas.
G. affinis was at a higher density in the subsidized marsh, but a higher percentage was
found in the unsubsidized marsh. Of the fish collected in the subsidized marsh, 76.09%
were G. affinis. In the unsubsidized marsh, 81.82% were G. affinis. The second most
abundant fish species in the subsidized marsh was H. formosa (17.39% of overall catch),
and this species was also less abundant in the unsubsidized marsh (18.18% of overall
catch.) Fish biomass was also significantly different in each marsh. In the subsidized
marsh, fish biomass was at 6.44 kg m'2. The unsubsidized marsh had 4.39 kg m*2 of
fish. By far the greatest biomass of fish was G. affinis contributing about 80.01% of the
total in the subsidized marsh, and 85.87% of the total in the unsubsidized marsh. Table 9
summarizes the results of the wildlife study.
Computer Simulation Model
Figure 24 shows the results for the simulation of the unsubsidized marsh when fuel
inputs and nutrients from the hypereutrophic lake are zero. Each storage in the marsh
system had an initial level of zero.

66
Figure 23. Results of fish survey including a) density and b) biomass.

Table 9. Summary of avian and fish community structure.
Parameter
Subsidized Marsh
Unsubsidized Marsh
Significant Difference
Avian Diversity
2.65
3.04
n = 54 df= 4, p
= 0.02
Avian Evenness
0.67
0.82
Avian Density
18.48 ha-1
7.07 ha-1
n = 54, df= 6, p =
= 0.02
Avian Biomass
5 .11 kg ha-1
2.22 kg ha-1
n = 54, df=6, p =
= 0.03
Fish Density
230 m-2
165 m-2
n = 30, df =5, p =
= 0.01
Fish Biomass
6.44 kg m-2
4.29 kg m-2
n = 30, df =5, p =
= 0.03

Fuel = 0%
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 24. Simulation of unsubsidized marsh.

69
After approximately 75 years, the storages of nutrients, plant biomass, insects, fish,
and birds reach steady state. This steady state was reached when each storage reached
100% of the marsh's carrying capacity.
When the pump system is turned on using 10% of the fuel used in the subsidized
marsh, the storages reach a new steady state after approximately 65 years as shown in
Figure 25. Plant biomass does not exceed the carrying capacity of the unsubsidized
marsh; however, it does reach steady state approximately five years sooner.
Insect, fish, and bird storages also increase at faster rates. Moreover, each of these
storages have an increase in carrying capacity with the increased nutrient subsidy. The
storage of insect biomass is increased by approximately 10% while fish and bird biomass
storages increased by 35% above the carrying capacity of the unsubsidized marsh.
An increase in fuel of 50% of that used in the subsidized marsh had the effect of

Fuel-10%
Nutrients
Plants
Insects
Fish
Girds
Years
Figure 25. Simulation of marsh with 10% added subsidy.

Fuel = 50%
0 15 30 45 60
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 26. Simulation of marsh with 50% added subsidy.

Fuel-100%
0 15 30 45 60
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 27. Simulation of marsh with 100% added subsidy.

73
shown in Figure 28. Moreover, steady state was reached after only 28 years. The wildlife
storages had greatly increased their carrying capacities, and had reached those levels over
forty years sooner than in the unsubsidized marsh.
Ten times the fuel (or 1000%) used in the subsidized marsh enables the marsh to
reach steady state after approximately 25 years as shown in Figure 29. In addition, greater
flucuations are shown in the biomass storages. Biomass storages all reached a higher
carrying capacity much sooner than the unsubsidized marsh.
Figure 30 summarizes the changes in biomass carrying capacity with different
levels of fuel used. It appears that the increases may be logistic; however, the model
overflowed after more than 15 times the fuel used in the subsidized marsh was simulated.
Seven sensitivity tests were performed to test the response of the computer model
to various conditions. The first two tests were simulations of the unsubsidized marsh
only. The remaining tests compared simulations of both the unsubsidized marsh and the
subsidized marsh (100% fuel) under the same conditions.
Figure 31 shows the results of running the unsubsidized marsh supplied with only
the nutrients in rain. All of the storages reached a lower steady state than in the original
simulation. In addition, the animal storages all soon began to decrease, and therefore their
maximum carrying capacity under these conditions was probably very low. With only a
small reduction in nutrients, as shown in Figure 32, the biological components of the
model are more successful in reaching a carrying capacity more similar to the original.
Figures 33 and 34 show the response of the unsubsidized marsh and the subsidized
marsh if the insects required more resources to survive. Given this scenario, the
macroinvertebrates pursue the available resources much more vigorously and in turn their
numbers multiply more quickly. The increased abundance of macroinvertebrates is then
quickly consumed by the fish and birds elevating their populations above what was found
in the original simulations.

Fuel **500%
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 28. Simulation of marsh with 500% added subsidy.

Fuel *1000%
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 29. Simulation of marsh with 1000% added subsidy.

O 10 50 100 500 1000
Percent Fuel Increase
H Nutrients H Plants 9 Insects QD Fish O Birds
Figure 30. Summary of simulation results after 70 years.

Ram Only (Unsubsidrzed Marsh)
Years
Figure 31. Simulation of unsubsidized marsh receiving nutrients from rain only.

78
90% Peat(U nsub sidize d M arsh)
Years
Figure 32. Simulation of unsubsidized marsh with peat contributing only 90% of original nutrients.

79
Insects Double Intake Rate (Unsubsidized Marsh)
Nutrients
Plants
Insects
111 Fish
Birds
Years
Figure 33. Simulation of unsubsidized marsh with insects requiring double their food
requirements.

Insects Double Inieke Rete (Subsidized Marsh)
0 15 3 0 4 5 6 0
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 34. Simulation of subsidized marsh with insects requiring double their food
requirements.

81
If fish were the element to require more resources, then the affect on the other
populations is much different as shown in Figures 35 and 36. The macroinvertebrate
population is eventually depleted as the fish and birds consume them. In addition, the
increased population of fish also benefits the bird population allowing it to be sustained
without the macroinvertebrate population.
When the food requirements of birds is increased as in Figures 37 and 38, the
macroinvertebrate population is not delepleted. However, competetion between the fish
and birds appeared to develop with fish receiving the negetative consequences of this
relationship. As the fish population decreases, some feeding pressure on the
macroinvertebrates is eventually elievated.
Figures 39 and 40 show the results of periodic disturbances to the marshes using
fish kills as an example. Immediately after the fish kill, the macroinvertebrate population
increases while the bird population temporarily
decreases. The reverse occurs as the fish population recovers.
Increases in migration allow rapid exploitation of the marcroinvertebrate
population as shown in Figures 41 and 42. The growth of the populations, however, is
soon limited as each resource nears its carrying capacity.

Fish Double Intake Rate (Unsubsidized Marsh)
0 15 30 45 60
Years
Figure 35. Simulation of unsubsidized marsh with fish requiring double their food
requirements.

Fish Double Intake Rate (Subsidized Marsh)
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 36. Simulation of subsidized marsh with fish requiring double their food
requirements.

Birds Double Intake Rate (Unsubsidized Marsh)
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 37. Simulation of unsubsidized marsh with birds requiring double their food
requirements.

Birds Double Intake Rate (Subsidized Marsh)
0 15 30 45 60
Nutrients
P1ants
Insects
Fish
Birds
Years
Figure 38. Simulation of subsidized marsh with birds requiring double their food
requirements.

Habitat Disturbance (Unsubsidized Marsh)
Nutrients

Plants

"" Insects
Fish
Birds
Years
Figure 39. Simulation of periodic fish kill in unsubsidized marsh.

Habitat Disturbance (Subsidized Marsh)
0 13 30 45 60
Years
Figure 40. Simulation of periodic fish kill in subsidized marsh.

Increased Migration (5x) (Unsubsidized Marsh)
Years
Figure 41. Simulation of increased migration in unsubsidized marsh.

Increased Migration (5x) (Subsidized Marsh)
Years
Figure 42. Simulation of increased migration in subsidized marsh.

DISCUSSION
The external subsidy seems to affect the self-organization of the constructed
wetland as the theory predicted at least in the early stages of succession or equilibration.
The predicted response of the marsh is evidenced in the more rapid conversion of the
subsidized marsh into a monoculture and the higher animal densities and biomass.
Vegetative communities, as identified by cover type, changed more rapidly in the
subsidized marsh over the study period. Open areas were more quickly over grown and
contained a higher percentage of Tvpha spp. After two years the dominate cover type of
the subsidized marsh was Tvpha Community which although includes many well
represented vegetative species it is more comparable to a monoculture. The unsubsidized
marsh also became less open, but did not seem to progress towards a monoculture plant
community at the same rate as the subsidized marsh. A possible explanation could be that
an external subsidy increases the rate of early successional or equilibration processes.
The simulation model showed a more dramatic rate of change of vegetative
communities and wildlife biomass over a much longer period of time. The field
observations were not taken over a long enough time to interpolate the progression of
successional stages that may occur in a constructed wetland. However, the simulation
model, which was calibrated using data collected from the field, allows a good prediction
of marsh self-organization. Overall, the model predicted the rate of succession will
increase with an increase in nutrient subsidy.
All sources entering the system's boundary have a potential to influence the
system's self-organization. Sources most likely to have the greatest influence are those that
have high transformities or require a large amount of energy such as use fuel and the pump
90

91
system in the subsidized marsh. Total nitrogen and total phosphorus each have high
transformities; therefore, the nutrients pumped in with the lake water potentially had the
most influence on the development of the marsh. The importance of certain high emergy
sources is their ability to facilitate the input of additional nonrenewable energies. For
example, the nutrient subsidy was made available to the marsh by the use of other high
emergy subsidies including fuel used to run the pump system. In constructed wetlands,
external subsidies increase the total emergy flow in an ecosystem and have the potential to
increase the rate of successional processes in both the vegetative and wildlife communities.
Rapidly changing vegetative structure in the subsidized marsh may have allowed
for a varied and highly productive food source for the avian communities. High densities
and biomass in the subsidized marsh compared to the unsubsidized marsh were probably a
direct result of the addition of high emergy resources. In addition, the synoptic fish survey
may indicate how the food base available to higher trophic levels may increase with the
addition of an external subsidy. Thus, the external subsidy probably increased the overall
carrying capacity of the wildlife communities.
In his study of plant-animal interactions, Price (1992) emphasized the importance
of abiotic contributions that have the potential to become driving variables by influencing
plant production and quality for herbivores. He found that an increase in certain nutrients
in a pelagic system can lead to an overall population increase. The process was bottom-
up. In other words, Price determined that a subsidy induced a cascading effect up through
the trophic system through paths of energy flow. Kerekes (1990) also found that densities
of aquatic birds tend to increase with the trophic state of a water body.
The wildlife community in the subsidized marsh seems to follow a similar
bottom-up pattern. As the nutrient subsidy (enriched lakewater) was added to the marsh,
the plant community seems to increase in productivity. Plant quality may not have
increased given that many freshwater plants including Tvpha spp. are considered poor in
nutrient quality for most animals. Krull (1970) and Voights (1974) found that aquatic

92
macrophytes were important to waterfowl production despite their poor nutritional value
because they harbor large quantities of macroinvertebrates.
Meeker (1992) suggested that as macrophyte productivity increased, the
abundance of macroinvertebrates and fish increased. Avian densities would then increase
until the carrying capacity was reached given the available food base. Therefore, the
external nutrient subsidy increased the energy flow in productive pathways which resulted
in an increased food base and an increase in the number of higher order consumers.
Avian biomass may follow a similar successional pattern as the vegetation in that
processes are more rapid in the subsidized marsh, but the structure may eventually be the
same in both marshes. In the subsidized marsh, the changes in biomass indicated that the
hierarchy of large to small birds changed slightly over the survey period. Relative to the
overall number of birds present in the subsidized marsh, more larger bodied birds were
present in this marsh. The distribution of the size classes, however, was not even.
Increases in avian density and biomass seem to reflect the expected pattern given in
the systems energy diagram and simulations of the subsidized marsh. This increase could
be also indicate an increase in the carrying capacity of the subsidized marsh given the
comparatively low avian density and biomass found in the unsubsidized marsh. Therefore,
density, biomass, and possibly the carrying capacity increase as the external lakewater
subsidy is continued to be added to the system. In this study, productivity does not level
off, but given a longer study period productivity may eventually reach the carrying
capacity level.
The computer simulations showed that with an increase in nutrient subsidy biomass
the rate at which steady state is reached is increased. This may indicate that the rate of
successional processes are increased. In addition, the biomass storages also increased, and
this may indicate an increase in carrying capacity. For a more realistic depiction of the
increases in subsidy, a component which included the affect that moving water has on
vegetation structure should be added. At very high rates of pumping, a substantial current

93
would form and could influence self-organizational processes. This model, however,
accomplishes the task of comparing an unsubsidized marsh to a subsidized marsh and
predicting the rate of succession and the increase in carrying capacity.
The storages in the energy systems diagram represent the volume of water in the
marsh, the total amounts of nitrogen and phosphorus, organic matter, detritus, and assets
pertaining to the pump structure. The growth of any one of these storages causes the
others to grow because the whole marsh system is autocatalytic.
For example, if more fuel is put into the structure (assets) of the pumps more
water would be pumped from Lake Apopka; hence, more nutrients will be added to the
system. More nutrients will increase the productivity of the primary producers, and will
theoretically lead to an increase in consumer productivity. Productivity will level off
eventually, but the growth rate may prevent this from happening until later than would be
expected in an unsubisdized system. Not shown in the diagram are the effects of the
subsidy on species diversity or distribution. In theory, as productivity levels off, then
energy pathways diversify to facilitate the input of more energy resources and increase
efficiency of energy use.
Material and energy balances as shown in the emergy analysis were significantly
different between the subsidized and unsubsidized marshes. For example, environmental
loading of the subsidized marsh was three and a half times as that of the unsubsidized
marsh. Due to the nonrenewable energy sources from the lake (e g., nutrients,
phytoplankton) and the pump system itself, the subsidized system had much higher flows
of available resources. This is also clearly evident in the higher densities and biomass of
the avian and fish communities. On the other hand, the complexity of the subsidized
marsh as measured by diversity and community structure was lower. Therefore, high
energy subsidies may compromise the complexity of the system in favor of high
productivity. Moreover, low diversity of the food base (eg., the fish community) was
probably not a factor in the increase in the overall carrying capacity of the subsidized

94
marsh. Lower avian diversity and evenness may reflect that fewer avian species were able
to exploit a sustainable food source as those in the unsubsidized marsh. However, higher
numbers of a few avian species could be supported (e.g., black birds) in the subsidized
marsh.
Species diversities in the subsidized marsh seemed to have been compromised
over productivity. Although classical succession predicts that over many years diversity
will eventually increase in highly productive systems (Odum 1969), this may not be
apparent in the earliest stages of succession. The nutrient subsidy seemed to dampen
vegetative cover richness in the subsidized marsh over the survey period except for a slight
increase in November 1991. Vegetative cover richness in the unsubsidized marsh
appeared to not only have a higher average but could be increasing. In contrast,
vegetative structure complexity was relatively unchanged and was similar in both marshes.
Thus, the nutrient subsidy did not seem to affect the patch shape patterns formed by early
successional processes.
Avian diversity and evenness generally declined in the subsidized marsh over the
survey period. This could be a result of declines in vegetative cover richness, less open
water, and/or more dense vegetation (e g., pure Tvpha spp. stands or Tvpha Community
with dense shrubs). The unsubsidized marsh maintained a higher percentage of open water
throughout the vegetative study period.
High productivity coupled with low diversity, such as in the subsidized marsh,
could be considered as the early stages of system development when most of the energy in
the system is being put towards facilitating the input of resources (Odum 1969, Odum,
1971, Odum 1981, Odum 1983). In the later stages of ecosystem self-organization,
energy resources are more efficiently recycled within the system allowing more diverse
uses of the energy such as more opportunity for the development of specialized niches.
The unsubsidized marsh may provide more specialized niches for the avian community
only because its rate of equilibration is slower than that of the subsidized marsh.

95
Therefore, the avian community in the unsubsidized marsh may also become less diverse
as open areas become smaller and species such as Tvpha spp. become more dense.
Baln (1993) suggested a different explanation for self-organizational processes in
early successional ecosystems. If a more diverse trophic structure was present initially,
then the system may have utilized more energy pathways eariler creating a more diverse
system. Hence, avian diversity in constructed wetlands may be limited by rate of trophic
structure development rather than the available energetic resources. Both the subsidized
and unsubsidized marshes, however, were in early succession throughout the study period.
Higher avian diversities with may be reached as each marsh continues to self-organize.
Community structure and dynamics are likely a result of many processes including
demographics, energy cycling, habitat disturbance, and the influence of other populations
(Wiens 1989). For example, competetion appeared evident between the animal
communities in the computer simulation sensitivity tests including those that affected
eating rates and migration. However, it is difficult to asses the changes in community
structure which occur due to specific processes because the processes do not act as
independent variables, but rather as components of the same system. In this case,
however, organization and community dynamics are probably more controlled by the
availability of energy sources with high transformities.
The difference between the available resources of each marsh is indicated in the
environmental loading ratios. The pump system and its required support (e g., fuel,
structure, goods and services) account for 78.04% of the nonrenewable energies available
to the subsidized system for self-organizing processes. In contrast, the unsubsidized
marsh does not have these subsidies and therefore has to rely more on available renewable
resources. The investment ratios indicate the contribution of purchased energies (e.g.,
marsh construction, operation and maintenance, pump system) toward facilitating the
input of renewable and nonrenewable free energies (e.g., sun, rain, nutrients,
phytoplankton). Much higher amounts of free energies are available to the subsidized

96
marsh relative to the amount of purchased energies. The addition of certain high emergy
sources (e g., the pump system) may facilitate the input of other resources (free
nonrenewables) at a rate that is proportional to the added subsidy.
Conclusions
The nutrient enrichment seemed to speed up self-organizational processes
in the subsidized marsh increasing the rate of vegetative coverage of the marsh. The
prevelance of large bodied birds in the unsubsidized marsh was likely due to the larger
percentage of open water. More open water may have also allowed greater diversity in
the avian community given a greater variety of feeding habitats.
Given the higher animal densities and biomass, the external subsidy may have also
increased the rate that these components reached their respective carrying capacities. This
theory seemed to be validated by the computer model simulations. Moreover, the
computer simulations suggest that the carrying capacity varies with different levels of
external subsidy. In general, the greater the subsidy of available nutrients, the greater
carrying capacity to be expected.
Overall, the external subsidy increased the emergy flux in the subsidized marsh by
increasing the input of nonrewable energy sources. As a result community parameters
such as density and overall biomass also increased in the subsidized marsh, but at a cost
of lowered richness, diversity, and evenness. Complexity of community structures did not
seem to be affected.

APPENDIX A. AVIAN SURVEY RESULTS FOR TRANSECTS 1-4
97

Table A-l. Avian survey results for Transect 1.
Common Name
Aug-91
"Sep-91
Nov-91
"Jan-92
American bittern
"" 0
"" 0
0
o
American coot
0
0
0
0
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
0
0
Bald eagle
0
0
0
0
Bam swallow
0
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Bluejay
0
0
0
0
Blue wing teal
0
0
0
0
Boat tail grackle
3
0
0
0
Carolina wren
0
1
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
0
0
0
0
Common moorhen
1
3
4
8
Common snipe
0
0
0
1
Common yellow throat
1
3
1
0
Double-creasted cormorant
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
0
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
2
2
Gad wall
0
0
0
0
Glossy ibis
0
0
0
0
Great blue heron
0
1
0
0
Great white egret
0
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
4
0
0
1
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
0
0
0
0
Little blue heron
0
0
0
0
Logger headed shrike
0
0
0
0

Table A-l. continued.
Common Name
Aug-91
"Sep-Sl
Nov-91
Jan-92
Mallard duck
0
o

Marsh wren
0
0
1
1
Mottled duck
0
0
0
0
Mouring dove
0
0
0
0
Northern cardinal
0
0
0
0
Northern herrier
0
0
1
0
Northern mocking bird
0
0
0
0
Northern pintail
0
0
0
0
Osprey
0
0
1
4
Palm warbler
0
0
0
0
Pied billed grebe
0
0
0
0
Purple gallinule
0
0
0
0
Red shoulder hawk
0
0
0
0
Red wing black bird
21
1
4
59
Sedge wren
0
0
0
0
Snowy egret
0
0
0
0
Song sparrow
0
0
0
0
Sora rail
0
1
0
0
Swamp sparrow
0
0
0
0
Tree swallow
1
0
0
0
Tri-color heron
0
0
0
0
Turkey vulture
0
0
0
0
White ibis
0
0
0
0
Willet
0
0
0
0
Wood duck
0
2
0
8
Yellow crown night heron
0
0
0
0
Yellow rumped warbler
0
0
0
0
Yellow warbler
0
0
0
0
Total
31
12
14
84

Table A-l. --continued.
Common Name
Feb-92
Apr-92
May-92
"Jun-92 1
Aug-92
American bittern
2
2

0
1
American coot
0
0
1
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
2
0
0
Black neck stilt
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Blue jay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grdele
16
6
5
1
16
Carolina wren
0
0
1
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grdele
0
0
0
0
0
Common moorhen
16
7
15
5
21
Common snipe
1
3
0
0
0
Common yellow throat
5
1
1
0
0
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
3
0
0
0
0
F westers tem
0
0
0
0
0
Fulvous whistling duck
0
0
0
0
0
Gad wall
0
0
0
0
0
Glossy ibis
0
4
1
0
2
Great blue heron
0
0
4
0
1
Great white egret
0
7
1
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
2
0
3
2
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
0
0
1
0
3
Little blue heron
0
1
4
0
0
Logger headed shrike
0
0
0
0
0

Table A-l. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mowing dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
Feb-92 Apr-92 May-92 Jun-92 Aug-92
~TJ 13 0
3
0
0
0
0
0
0
3
0
0
0
0
25
0
0
0
1
5
0
0
0
0
0
0
0
0
0
80
3
0
0
0
0
0
0
0
0
0
0
0
12
0
4
0
4
0
0
0
0
3
0
0
0
0
0
59
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
42
0
0
0
0
0
0
0
0
0
0
0
0
8
0
0
0
0
0
0
7
0
0
0
0
0
0
0
24
0
0
0
0
0
0
0
0
0
0
0
0
18
0
0
0
0
0
0
2
0
1
0
0
0
0
0
67

Table A-l. continued.
Common Name
Sif>92
Oct-92
'DSc-92
Jaffsr
Feb-93
American bittern
0
0
1
0
0
American coot
0
0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
1
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
1
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
5
1
15
0
9
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
5
7
18
40
11
Common snipe
0
0
0
0
0
Common yellow throat
0
0
11
2
1
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
1
1
1
0
Foresters tem
0
0
0
3
6
Fulvous whistling duck
0
0
0
0
103
Gad wall
0
0
0
0
0
Glossy ibis
0
0
0
0
1
Great blue heron
2
1
0
1
1
Great white egret
0
0
0
1
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
2
3
2
1
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
1
Least bittern
1
0
1
0
0
Little blue heron
1
0
0
0
0
Logger headed shrike
0
0
0
0
0

Table A-l. -continued.
Common Nlame
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
55537
"T"
o
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
30
H37
0
8
0
0
0
0
0
0
1
0
0
0
0
10
0
0
0
0
2
0
0
0
0
0
0
0
0
0
33
c-92
o
6
0
0
0
0
0
0
1
0
0
0
0
108
0
0
0
11
0
0
0
0
0
0
0
0
0
0
177
Jan-93
TT-
1
0
0
0
0
0
0
0
0
0
0
0
33
0
0
0
0
0
0
0
0
0
0
0
0
0
0
84
P553J
0
o
o
0
0
0
0
0
0
1
0
0
0
4
0
0
0
1
0
0
0
0
0
0
0
0
0
0
140

Table A-2. Avian survey results for Transect 2.
Common Name
Aug-91
Sep-91
Nov-91
Jan-92
American bittern
0
0
0
0
American coot
0
0
0
10
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
0
0
Bald eagle
0
0
0
1
Bam swallow
0
0
0
0
Belted kingfisher
0
2
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Bluejay
0
0
0
0
Blue wing teal
0
0
0
44
Boat tail grackle
0
3
5
0
Carolina wren
0
0
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
0
0
0
0
Common moorhen
1
7
1
14
Common snipe
0
0
0
1
Common yellow throat
0
0
0
0
Double-crested cormorant
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
5
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
1
0
52
Gad wall
0
0
0
0
Glossy ibis
0
0
0
5
Great blue heron
1
0
0
0
Great white egret
3
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
1
0
0
1
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
0
0
0
0
Little blue heron
0
0
0
1
Logger headed shrike
0
0
0
0

Table A-2. Avian survey results for Transect 2.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow wait>ler
Total
Aug-91 Sep-91 Nov-91 Jan-92
0 0 0 0~
0
0
0
0
0
0
0
0
0
0
0
0
25
0
0
0
0
0
0
0
0
6
0
0
0
0
1
38
0
0
0
0
0
0
0
0
0
0
0
0
16
0
1
0
0
0
0
0
0
0
0
2
0
0
0
32
3
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
1
0
0
0
69
0
0
0
0
0
0
0
0
3
0
0
0
0
0
202

Table A-2. -continued.
Common Name
Teb-9'2
Apr-92 May-92
"Jh-92
Aug-92
American bittern
2
0
5
0
1
American coot
5
3
1
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
3
2
17
4
30
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
5
7
12
6
8
Common snipe
1
0
0
0
0
Common yellow throat
1
2
0
0
0
Double-creasted cormorn
0
0
0
0
1
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
1
0
0
0
Foresters tern
0
0
0
0
0
Fulvous whistling duck
2
1
4
0
0
Gad wall
0
0
0
0
0
Glossy ibis
0
1
0
0
4
Great blue heron
0
0
0
0
1
Great white egret
0
1
1
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
0
0
1
6
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
0
0
0
5
3
Little blue heron
0
1
1
0
0
Logger headed shrike
0
0
0
0
0

Table A-2. -continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
"Feb-92
0
0
0
0
0
1
0
0
0
0
0
0
0
4
1
0
0
1
0
1
0
0
0
0
0
0
0
0
27
Apr-92
' 0
5
0
0
0
0
0
0
0
5
0
0
0
8
0
0
0
0
1
12
0
0
0
0
0
0
0
0
50
May-92 Jun-92 Aug-92
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
47
0
0
0
0
0
0
0
0
0
0
0
0
0
7
0
0
0
0
0
0
0
0
0
0
0
0
0
0
23
0
0
0
0
0
0
0
0
0
0
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
64

Table A-2. continued.
Common Name
Sep-92"
Oct-92
"Dec-92
Jan-93
"'FeB-93
American bittern
0
0
0
0
1
American coot
0
0
2
1
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
1
0
0
2
0
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
12
11
12
10
13
Common snipe
0
0
0
0
0
Common yellow throat
0
3
4
3
1
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
1
0
0
Foresters tem
0
0
0
2
6
Fulvous whistling duck
0
0
0
0
2
Gad wall
0
0
0
0
0
Glossy ibis
0
0
0
0
0
Great blue heron
0
0
0
0
0
Great white egret
0
0
0
0
1
Greater yellow legs
0
0
0
0
0
Green back heron
2
1
0
0
1
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
4
0
0
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0

Table A-2. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
3ip3H
(T
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
1
0
0
0
0
0
0
0
0
0
0
22
TZiVI
73
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17
Dec-92
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
20
Jan-03
~TT~
0
0
0
0
0
0
0
0
30
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
49
Teb^T
0
1
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
1
0
8
0
0
0
0
0
0
0
0
38

Table A-3. Avian survey results for Transect 3.
Common Name
-fciprr
Sep-91
Nov-91
" Jan-"92
Amen can bittern
0

0
0
American coot
0
0
0
0
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
0
0
Bald eagle
0
0
0
0
Bam swallow
0
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
1
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Blue jay
0
0
0
1
Blue wing teal
2
0
0
0
Boat tail grackle
0
0
0
0
Carolina wren
0
0
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
1
2
10
1
Common moorhen
0
0
0
0
Common snipe
0
2
3
0
Common yellow throat
0
0
0
0
Double-crested cormorant
0
0
0
0
Eastern kingbird
0
0
1
0
Eastern phoebe
0
0
0
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
0
0
Gad wall
1
0
0
0
Glossy ibis
2
0
0
0
Great blue heron
1
0
0
0
Great white egret
0
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
0
0
0
0
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
2
0
0
0
Little blue heron
0
0
0
0
Logger headed shrike
0
0
0
0

Table A-3. -continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
Au^-9 1
0
0
0
0
0
0
0
0
0
0
0
50
0
0
0
0
0
1
0
0
0
0
5
0
0
0
0
65
Sip^T
{T~
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
6
Nov-91
1
0
0
0
0
0
0
0
2
0
0
1
0
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
21
7am9I
0
0
0
0
0
0
0
0
3
0
0
0
14
0
0
0
0
2
2
0
0
0
0
0
0
0
0
0
23

Table A-3. -continued.
Common Name
Feb-92 Apr-92 May-
92 Jun-92
Aug-92
Amen can bittern
Amen can coot
I
0
I
0
0
' 0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
1
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Blue jay
0
0
0
0
0
Blue wing teal
8
3
9
15
4
Boat tail grackle
0
0
0
0
0
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
7
13
6
16
9
Common moorhen
0
0
0
0
0
Common snipe
3
2
0
0
0
Common yellow throat
0
0
0
0
0
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
1
0
Foresters tern
0
0
0
0
0
Fulvous whistling duck
0
0
0
0
0
Gadwall
0
0
2
0
27
Glossy ibis
0
0
0
0
0
Great blue heron
0
0
0
0
0
Great white egret
0
0
0
0
0
Greater yellow legs
0
1
0
1
0
Green back heron
0
0
0
0
0
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
1
0
0
0
King rail
0
0
1
3
6
Least bittern
1
1
0
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0

Table A-3. --continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
Feb-92 Apr-92 May-92 Jun-92 Au'£97
0 1 0 0
0
0
0
0
0
0
0
2
0
0
0
24
5
0
0
0
2
0
0
0
0
0
0
0
0
0
0
53
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
1 0 0
0 0 0
0 0 0
0 0 0
10 17 9
0 0 0
0 0 0
0 0 0
2 1 0
0 0 0
0 0 0
0 0 0
0 0 0
0 2 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
36 39 45
0
0
0
0
0
0
0
0
0
0
0
21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
67

Table A-3. --continued.
Common Name
Sep-92
Oct-92
Dec-92
Jari-^r
Feb-93
American bittern
0

0
0
1
American coot
0
0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
1
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
14
0
0
3
Boat tail grackle
0
1
0
0
0
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
3
24
20
8
20
Common moorhen
0
0
0
0
0
Common snipe
0
2
5
1
0
Common yellow throat
1
0
0
0
0
Double-creasted cormorani
0
0
0
0
0
Eastern kingbird
0
0
2
1
0
Eastern phoebe
0
0
0
0
25
Foresters tern
0
0
0
0
0
Fulvous whistling duck
0
0
0
0
0
Gad wall
0
0
0
0
1
Glossy ibis
0
0
0
0
0
Great blue heron
0
0
0
0
0
Great white egret
0
0
0
0
0
Greater yellow legs
1
2
0
0
0
Green back heron
0
0
0
0
0
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
1
0
0
King rail
1
0
0
0
0
Least bittern
0
0
0
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0

Table A-3. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
0
0
0
0
0
0
0
0
0
0
0
0
9
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
17
y~
0
0
0
0
0
0
0
0
0
0
0
18
0
0
0
5
0
0
0
0
0
0
0
0
0
0
0
71
Dec-92
7
2
0
0
0
0
0
0
0
0
0
0
17
0
0
0
5
2
0
0
0
0
0
0
0
0
0
0
61
7ar£9T
I
0
0 '
0
0
0
0
0
0
0
0
0
2
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
16
Teb^T
~~T~
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
58

Table A-4. Avian survey results for Transect 4.
Common Name
Aug-91
"Sep-91"
Nov-91
"Jan-92"
American bittern
0
0
0
1
American coot
0
0
0
0
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
0
0
Bald eagle
0
0
0
0
Bam swallow
2
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Blue jay
0
0
0
0
Blue wing teal
0
0
0
0
Boat tail grackle
0
5
22
2
Carolina wren
0
0
0
0
Cattle egret
0
4
0
0
Chimney swift
2
0
0
0
Common grackle
0
0
0
0
Common moorhen
0
1
4
2
Common snipe
0
2
0
3
Common yellow throat
0
0
2
2
Double-crested cormorant
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
2
1
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
0
0
Gad wall
0
0
0
0
Glossy ibis
0
6
0
0
Great blue heron
1
0
0
0
Great white egret
0
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
0
0
0
0
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
0
0
0
0
Little blue heron
0
5
0
0
Logger headed shrike
0
0
0
0

Table A-4. -continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
Au^-91
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
20
SipNT
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
6
0
0
0
30
Nov-91
U~
11
3
0
0
0
0
0
0
5
0
0
0
121
0
0
0
0
2
0
0
0
0
0
0
0
0
0
172
7ST9I
~TT~
0
1
0
0
0
0
0
0
2
0
0
0
38
0
0
0
0
0
0
0
0
0
0
0
0
0
0
52

Table A-4. continued.
Common Name
'Feb-92' Apr-92 May-92
Jun-92
Aug-92
American bittern
2
2
0
0
' '
American coot
0
0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
43
52
0
0
0
Black crown night heron
0
0
1
0
0
Black neck stilt
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Blue jay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
16
9
8
24
13
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
1
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
8
9
9
13
9
Common snipe
1
0
0
0
1
Common yellow throat
1
1
0
0
0
Double-creasted cormoran;
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
0
0
Foresters tern
0
0
0
0
0
Fulvous whistling duck
0
7
0
3
4
Gad wall
0
0
0
0
0
Glossy ibis
21
1
8
0
3
Great blue heron
2
3
1
0
0
Great white egret
0
1
1
11
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
0
0
0
0
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
0
1
0
0
2
Little blue heron
3
0
0
0
0
Logger headed shrike
0
0
0
0
0

Table A-4. --continued.
Common Name Feb-92
Mallard duck 0
Marsh wren 0
Mottled duck 0
Mouring dove 0
Northern cardinal 0
Northern herrier 0
Northern mocking bird 0
Northern pintail 0
Osprey 0
Palm warbler 5
Pied billed grebe 0
Purple gallinule 0
Red shoulder hawk 0
Red wing black bird 17
Sedge wren 0
Snowy egret 0
Song sparrow 0
Sora rail 0
Swamp sparrow 0
Tree swallow 0
Tri-color heron 0
Turkey vulture 0
White ibis 0
Willet 0
Wood duck 0
Yellow crown night heron 0
Yellow rumped warbler 0
Yellow warbler 0
Total 119
XF92'Wy792 Jun-92 Aug-92
<3 0 8
5 0 0
2 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
1 0 0
0 0 0
0 0 0
0 0 0
11 46 16
0 0 0
0 0 0
0 0 0
2 0 0
0 0 0
0 0 0
0 0 2
0 0 0
0 3 0
0 0 0
0 1 0
0 0 0
0 0 0
0 2 0
107 80 69
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
2
0
0
0
0
0
0
0
50

Table A-4. continued.
Common Name
Sep-92
Oct-92
Dec-92
Jan-93'
Feb-93
Amen can bittern
0

0
0
0
American coot
0
0
0
1
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
6
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Blue jay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
3
5
4
1
10
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
4
15
8
12
0
Common snipe
0
0
0
1
0
Common yellow throat
1
1
0
2
1
Double-creasted cormoram
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
0
0
Foresters tem
0
0
0
0
0
Fulvous whistling duck
0
0
0
0
0
Gad wall
0
0
0
0
0
Glossy ibis
0
0
0
1
0
Great blue heron
0
0
0
0
0
Great white egret
1
0
1
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
0
0
0
0
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
0
0
0
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0

Table A-4. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
~0~
0
1
0
0
0
0
0
0
0
0
0
0
13
0
0
0
0
0
0
0
0
0
0
2
0
0
0
25
~ir~
12
0
0
0
0
0
0
0
0
0
0
0
206
0
0
0
11
0
0
0
0
0
0
0
0
0
0
250
Dec-92
0
2
0
0
0
0
0
0
0
0
0
0
0
24
0
0
0
6
0
0
0
0
0
0
0
0
0
0
45
75H3TT

9
0
0
0
2
0
0
0
4
0
0
0
8
0
0
0
6
0
0
0
0
0
0
0
0
0
0
53
TeB^T
~IT-
6
0
0
0
0
0
0
0
3
0
0
0
12
0
0
0
1
1
0
0
0
0
0
0
0
0
0
34

APPENDIX B: AVIAN SURVEY RESULTS FOR TRANSECTS 5-6
122

Table B-l. Avian survey results for Transect 5.
Common Name
7H-9I
Nov-92"
Dec-92
Jan-93
Amen can bittern
1
6
1
2
American coot
0
1
6
10
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
2
1
Bald eagle
0
0
0
0
Bam swallow
0
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Blue jay
0
0
0
0
Blue wing teal
0
0
0
0
Boat tail grackle
11
0
0
0
Carolina wren
0
0
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
0
0
0
0
Common moorhen
4
21
14
28
Common snipe
0
1
0
0
Common yellow throat
0
4
1
0
Double-creasted cormorani
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
0
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
0
0
Gad wall
0
0
0
0
Glossy ibis
0
0
0
0
Great blue heron
0
0
1
0
Great white egret
0
0
0
1
Greater yellow legs
0
0
0
0
Green back heron
3
3
2
5
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
1
0
1
1
Least bittern
3
0
0
0
Little blue heron
0
0
0
0
Logger headed shrike
0
0
1
0

Table B-l. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Meaning dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
T5cc9T
o
0
0
0
0
0
0
0
0
0
0
0
0
24
0
0
0
0
0
3
0
0
0
0
0
0
0
0
27
Nov-92
o
8
0
0
0
0
0
0
0
0
1
0
0
7
0
0
0
2
2
0
0
0
0
0
0
0
0
0
20
Dec-92 Jan-93
1T
5
0
0
0
0
0
0
0
0
0
0
0
3
1
0
0
3
0
0
0
0
0
0
0
0
0
0
12
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
7
0
0
0
0
0
0
1
0
0
0
8

Table B-1. -continued.
Common Name
TZSZT
Mar-93
Apr-93
May-93
Jul-93
American bittern
2
4
3
2
0
American coot
5
4
3
3
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
1
1
0
1
2
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
1
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
1
2
19
1
8
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
18
14
9
10
3
Common snipe
0
0
0
0
0
Common yellow throat
0
0
0
0
0
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
0
0
Foresters tern
0
0
1
0
0
Fulvous whistling duck
0
2
0
0
0
Gad wall
0
0
0
0
0
Glossy ibis
0
0
0
0
3
Great blue heron
0
0
0
0
2
Great white egret
0
0
0
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
1
4
2
1
3
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
1
0
0
Least bittern
0
0
2
0
3
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0

126
Table B-1. -continued.
Common Name
Feb-93
Mar-93
Apr-93
May-93
JuI-93
Mallard duck
O'
0
0
0
o
Marsh wren
4
8
4
4
0
Mottled duck
3
0
0
3
0
Mouring dove
0
0
0
0
0
Northern cardinal
0
0
0
0
0
Northern herrier
0
0
0
0
0
Northern mocking bird
0
0
0
0
0
Northern pintail
0
0
0
0
0
Osprey
0
0
0
0
2
Palm warbler
0
2
0
0
0
Pied billed grebe
0
0
0
0
0
Purple gallinule
0
0
1
0
0
Red shoulder hawk
0
0
0
0
0
Red wing black bird
15
3
0
15
5
Sedge wren
0
0
3
0
0
Snowy egret
0
0
0
0
1
Song sparrow
0
0
0
0
0
Sora rail
0
0
2
0
0
Swamp sparrow
0
0
0
0
0
Tree swallow
24
0
0
4
0
Tri-color heron
0
0
1
0
1
Turkey vulture
0
0
0
0
0
White ibis
0
0
0
0
7
Willet
0
0
0
0
0
Wood duck
0
0
0
0
0
Yellow crown night heron
0
0
0
0
0
Yellow rumped warbler
0
0
0
0
0
Yellow warbler
0
0
0
0
0
Total
46
13
11
26
16

Table B-2. Avian survey results for Transect 6.
Common Name
"Oct-92"
Nov-92
Dec-92
Jan-93
American bittern
0
1
u
1
American coot
0
0
4
0
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
2
1
2
Bald eagle
0
0
0
0
Bam swallow
0
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Bluejay
0
0
0
0
Blue wing teal
0
0
0
0
Boat tail grackle
0
0
0
1
Carolina wren
0
0
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
0
0
0
0
Common moorhen
6
0
0
0
Common snipe
0
0
0
0
Common yellow throat
1
3
1
1
Double-crested cormorant
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
1
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
0
0
Gad wall
0
0
0
0
Glossy ibis
0
0
0
0
Great blue heron
1
0
0
0
Great white egret
0
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
3
3
2
2
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
0
0
0
0
Little blue heron
0
0
0
0
Logger headed shrike
0
0
0
0

Table B-2. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
iwm
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
0
0
15
TJ5v32'

3
0
0
0
0
0
0
0
1
1
0
0
6
0
0
0
1
2
0
0
0
0
0
0
0
0
0
23
Dec-92
0
0
0
0
0
0
0
0
0
1
0
0
0
28
0
0
0
0
0
0
0
0
0
0
0
0
0
0
38
Jan-93
~ir~
0
4
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
3
0
0
0
16

Table B-2. continued.
Common Name
Feb-93
"Mar-93
Apr-93'
' M ay- 9'3
"Jul-93
Amen can bittern
3
2
0
6
o
American coot
0
0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
2
2
1
2
1
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
2
13
7
2
1
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
0
0
4
0
4
Common snipe
0
0
0
0
0
Common yellow throat
2
2
0
2
0
Double-creasted cormoram
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
0
0
Foresters tern
0
0
0
0
0
Fulvous whistling duck
2
0
0
2
0
Gadwall
0
0
0
0
0
Glossy ibis
0
0
0
0
2
Great blue heron
0
0
0
0
0
Great white egret
0
0
0
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
5
0
0
5
4
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
1
0
0
Least bittern
0
0
1
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0

130
Table B-2. continued.
Common Name
Feb-93
Mar-93
Apr-97"
May-93
Jul-93
Mallard duck
'
0
0
6
0
Marsh wren
2
4
4
2
0
Mottled duck
0
0
0
0
0
Mouring dove
0
0
0
0
0
Northern cardinal
0
1
0
0
0
Northern herrier
1
0
0
1
0
Northern mocking bird
0
0
0
0
0
Northern pintail
0
0
0
0
0
Osprey
0
0
0
0
1
Palm warbler
0
0
0
0
0
Pied billed grebe
0
0
0
0
0
Purple gallinule
0
0
0
0
0
Red shoulder hawk
0
0
0
0
0
Red wing black bird
0
0
2
0
6
Sedge wren
0
0
1
0
0
Snowy egret
1
0
0
1
1
Swig sparrow
0
0
0
0
0
Sora rail
0
1
2
0
0
Swamp sparrow
0
0
0
0
0
Tree swallow
0
5
0
0
0
Tri-color heron
0
0
0
0
1
Turkey vulture
0
0
0
0
0
White ibis
0
1
1
0
5
Willet
0
0
0
0
0
Wood duck
0
0
0
0
0
Yellow crown night heron
0
0
0
0
0
Yellow rumped warbler
0
0
0
0
0
Yellow warbler
0
0
0
0
0
Total
20
31
24
17
26

APPENDIX C: COMPUTER SIMULATION MODEL

132
Table C-1. Computer simulation model.
5 REM SIMULATION OF CONSTRUCTED MARSH WITH PUMP SYSTEM
10 SCREEN 1, 0: COLOR 0, 0
15CLS
20 LINE (0, 0)-(319, 180), 1, B
25 OPEN "SIMMODEL" FOR OUTPUT AS #1
30 T = 1
35 WATER = 0
40 NUTRIENTS = 0
45 RNUTRIENTS = 100
50 PNUTRIENTS = 100
55 LNUTRIENTS = 100
60 PLANTS = 0
65 DETRITUS = 0
70 INSECTS = 0
75 FISH = 0
80 BIRDS = 0
85 FUEL = 0
90 SUN = 100
95 RAIN = 100
100 K0 = .0009
105K1 =30
110 K2 = .00001
115 K3 = .000099
120 K4 = .286
125 K5 = 7.5
130 K6 = 22.5
135 K14 = .0005
140 K15 = .00015
145 K16 = .05
150 K17 = .295
155 K18 = .00005
160 K19 = .3
165 K20 = .3
170K21 = .2
175 K22 = .001
180 k39 = .3
185 K23 = .00667

133
Table C-1. continued.
190 K24 = .0006
195 K25 = .2
200 k26 = .207
205 K27 = .001
210 K28 = .001
215 K29 = .0025
220 K30 = .002
225 K31 = .065
230 K32 = .025
235 K33 = .0001
240 K34 = .0015
245 K35 = .00105
250 K36 = .01
255 K37 = .01
260 k38 = .0007
265 k40 = 21
270 k41 =42
275 k42 = 1
280 k43 = 1.75
285 k44 = .1
290 k45 = .021
295 k46 = 42
300 k47 = 3.5
305 k48 = 3.5
310 z = 1
315 IF T < 10 THEN zz = 2 ELSE zz = 0
320 ALBEDO = SUN / (1 + (K0 PLANTS NUTRIENTS))
325 DWATER = K1 RAIN + K2 WATER FUEL K3 WATER FUEL
- K4 WATER K5 WATER K6 WATER
330 DNUTRIENTS = k40 RNUTRIENTS + k41 PNUTRIENTS
+ k42 LNUTRIENTS FUEL + k43 (DETRITUS + INSECTS +
FISH + BIRDS) k44 LNUTRIENTS FUEL k45 PLANTS *
NUTRIENTS ALBEDO k46 NUTRIENTS k47 NUTRIENTS -
k48 NUTRIENTS
335 DPLANTS = K14 ALBEDO PLANTS NUTRIENTS
- K15 ALBEDO PLANTS NUTRIENTS K16 PLANTS K17 *
PLANTS K18 PLANTS FISH + z zz
340 DDETRITUs = K19 PLANTS K20 DETRITUS K21 DETRITUS
- K22 DETRITUS INSECTS + k39 NUTRIENTS

134
T able C-1. continued.
345 DINSECTS = K23 INSECTS DETRITUS K24 INSECTS *
DETRITUS K25 INSECTS k26 INSECTS K27 INSECTS *
FISH K28 INSECTS BIRDS + z zz
350 DFISH = K29 FISH (PLANTS + INSECTS)
- K30 FISH (PLANTS + INSECTS) K31 FISH K32 FISH
- K33 FISH BIRDS + z zz
355 DBIRDS = K34 BIRDS (FISH + INSECTS)
- K35 BIRDS (INSECTS + FISH) K36 BIRDS K37 BIRDS
- k38 BIRDS BIRDS + z zz
360 WATER = WATER + DWATER DT
365 NUTRIENTS = NUTRIENTS + DNUTRIENTS DT
370 PLANTS = PLANTS + DPLANTS DT
375 DETRITUS = DETRITUS + DDETRITUs DT
380 INSECTS = INSECTS + DINSECTS DT
385 FISH = FISH + DFISH DT
390 BIRDS = BIRDS + DBIRDS DT
395 TT = 3
400 PSET (T TT, 180 BIRDS / 9), 2
405 PSET (T TT, 180 FISH / 9), 1
410 PSET (T TT, 180 NUTRIENTS / 9), 3
415 PSET (T TT, 180 INSECTS / 9), 3
420 DT = .01
425 T = T + DT
430 PRINT #1, USING ####.##"; NUTRIENTS; PLANTS; INSECTS; FISH;
BIRDS
435 IF T TT < 319 THEN GOTO 310
440 CLOSE
445 END

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BIOGRAPHICAL SKETCH
Tonya Mae Howington was bom at Fort Gordon Army Base in Augusta, Georgia,
on January 2, 1966. She has three brothers (Alfred, Michael, and John) and two
half-sisters (Georgette and Shari). Her family moved to Tallahassee, Florida, in 1970
where she lived until 1991. In Tallahassee, she received an Associate in Arts degree from
Tallahassee Community College and a bachelor's degree in American Studies from Florida
State University. In 1991, she moved to Gainesville, Florida, to pursue a Master of
Science degree in environmental engineering sciences at the University of Florida. Upon
graduation, she will continue at the University of Florida to pursue a Ph.D. in the same
program. Her research will be conducted in Venezuela where she will also make her new
home.
On April 2, 1994, Tonya married Juan Jorge Haberkom. In the summer of 1994,
they moved together to Venezuela to find adventure and start a family.
143

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a thesis for the degree of Masters of Science.
Mark T. Brown, Chairman
Associate Scientist of Environmental
Engineering Sciences
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a thesis for the degree of Masters of Science.
G. Ronnie Best
Scientist of Environmental Engineering
Sciences
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a thesis for the degree of Masters of Science.
Stephen R. Humphrey
Interim Dean, College of Na
Resources and Environment
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a thesis for the degree of Masters of Science.
Winfred M. Phillips
Dean, College of Engineering
Karen A. Holbrook
Dean, Graduate School



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
SELF-ORGANIZATION OF AN ECOLOGICALLY ENGINEERED WETLAND
IN CENTRAL FLORIDA
By
Tonya Mae Howington
December 1994
Chairperson: Dr. Mark T. Brown
Major Department: Environmental Engineering Sciences
A constructed wetland (subsidized marsh) in Central Florida receiving
continuously pumped hypereutrophic lake water was studied for two years to
determine the effect that an external subsidy had on its self-organization. This marsh
was compared to an adjacent constructed wetland that did not receive this subsidy
(unsubsidized marsh.)
Energy sources influencing each marsh's development were compared using an
emergy analysis. Both marshes were similar in natural renewable energies (0.97 El5
sej ha"* yrl ). However, when the pump structure and purchased energies were
included, the emergy flux in the subsidized marsh was 14.3 El5 sej ha"^ yrl while
the unsubsidized marsh received only 2.0 El 5 sej ha" 1 yrl The importance of this
contrast in emergy flux was reflected in two emergy ratios. The environmental loading
ratio between the subsidized marsh (13.8) and the unsubsidized marsh (0.10) indicated
a significant difference in the amount of renewable energies (solar insolation, rain,
nutrients in rain) to nonrenewable energies (primarily lake water and nutrients and
pump system) stimulating marsh self-organization. The investment ratio for the
subsidized marsh (2.10) was much greater than that of the unsubsidized marsh (0.10).
x


Therefore, purchased energies were much higher than the inputs of free energies for
the subsidized marsh.
Aerial photos were interpreted to evaluate the number of vegetative cover
types (richness), complexity (fractal dimension), and percent vegetative cover. After
two years, vegetative cover richness in the subsidized marsh was 3.25, while the
unsubsidized marsh had a richness of 4.69. Both marshes had similar levels of
moderate complexity (1.5) throughout the survey period. Typha Community had the
highest percentage of cover dominance in the subsidized marsh (66.70%) and in the
unsubsidized marsh (48.61%) at the end of the survey period. Overall, the subsidized
marsh had 89% cover of types that include Tvpha spp. The unsubsidized marsh had a
67% cover of Typha spp. cover types.
Avian surveys and a synoptic fish sampling were conducted in each marsh.
Diversity and evenness were significantly higher in the unsubsidized marsh. Avian
density and biomass were much higher in the subsidized marsh (18.48 birds ha-*; 5.11
kg ha-*) than in the unsubsidized marsh (7.05 birds ha'* ,2.22 kg ha*l ). The
subsidized marsh supported higher densities and biomass of fish (230 fish m'2 ,6.44 kg
m'2) than the unsubsidized marsh (169 fish m"2 ,4.39 kg m"2 ).
Overall, the external subsidy increased the emergy flux in the subsidized marsh
by increasing the input of nonrenewable energy sources. As a result, community
parameters such as vegetative percent cover dominance, animal density and overall
biomass were higher in the subsidized marsh, but at a cost of lowered richness and
diversity and evenness. Complexity of vegetative structure did not seem to be affected
by the increased subsidy.
xi


Table A-l. --continued.
Common Name
Feb-92
Apr-92
May-92
"Jun-92 1
Aug-92
American bittern
2
2

0
1
American coot
0
0
1
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
2
0
0
Black neck stilt
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Blue jay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grdele
16
6
5
1
16
Carolina wren
0
0
1
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grdele
0
0
0
0
0
Common moorhen
16
7
15
5
21
Common snipe
1
3
0
0
0
Common yellow throat
5
1
1
0
0
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
3
0
0
0
0
F westers tem
0
0
0
0
0
Fulvous whistling duck
0
0
0
0
0
Gad wall
0
0
0
0
0
Glossy ibis
0
4
1
0
2
Great blue heron
0
0
4
0
1
Great white egret
0
7
1
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
2
0
3
2
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
0
0
1
0
3
Little blue heron
0
1
4
0
0
Logger headed shrike
0
0
0
0
0


Table 1. List of transformities used for the emergy analysis.
Energy Source
Transformity
Units
References
Sun
1.00E+00
Sej/J
Odum et al. (1987)
Rain-chemical potential
1.54E+04
Sej/J
Odum et al. (1987)
Total nitrogen
4.21E+09
Sej/g
Brown and Arding 1991
Total phosphorus
6.88E+09
Sej/g
Brown and Arding 1991
Phytoplankton
1.00E+04
Sej/J
Odum and Arding 1991
Pumped water-chemical potential
2.35E+04
Sej/J
Odum et al. 1987
Liquid fuel
6.60E+04
Sej/J
Brown and Arding 1990
Construction-structure
6.70E+09
Sej/g
Brown and Arding 1991
Construction-services
1.60E+12
Sej/$
Brown and Arding 1991
Operation and maintenance
1.60E+12
Sej/$
Brown and Arding 1991


Fuel = 0%
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 24. Simulation of unsubsidized marsh.


Table A-3. continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
0
0
0
0
0
0
0
0
0
0
0
0
9
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
17
y~
0
0
0
0
0
0
0
0
0
0
0
18
0
0
0
5
0
0
0
0
0
0
0
0
0
0
0
71
Dec-92
7
2
0
0
0
0
0
0
0
0
0
0
17
0
0
0
5
2
0
0
0
0
0
0
0
0
0
0
61
7ar£9T
I
0
0 '
0
0
0
0
0
0
0
0
0
2
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
16
Teb^T
~~T~
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
58


LIST OF FIGURES
page
Figure 1. Map of project site 12
Figure 2. List of energy symbols 15
Figure 3. Map of site showing numbered transects 18
Figure 4. Diagram of computer simulation model 28
Figure 5. Systems diagram of subsidized marsh 31
Figure 6. Summary diagram of emergy analysis 37
Figure 7. Water budgets for both marshes 40
Figure 8. Nutrient budgets for both marshes 41
Figure 9. Map of vegetative cover for November 1990 42
Figure 10. Map of vegetative cover for November 1991 43
Figure 11. Map of vegetative cover for April 1992 44
Figure 12. Map of vegetative cover for November 1992 45
Figure 13. Vegetative cover richness for both marshes 46
Figure 14. Vegetative cover complexity for both marshes 48
Figure 15. Vegetative percent cover of subsidized marsh 49
Figure 16. Vegetative percent cover of unsubsidized marsh 50
Figure 17. Diversity indices for avian species in both marshes 54
Figure 18. Evennesss indices for avian species in both marshes 55
Figure 19. Overall avian density in subsidized marsh 57
Figure 20. Overall avian density in unsubsidized marsh 58
Figure 21. Overall avian biomass in subsdized marsh 63
Figure 22. Overall avian biomass in unsubsidized marsh 64
Figure 23. Results of fish survey including a)density and b) biomass 66
Figure 24. Simulation of unsubsidized marsh 68
Figure 25. Simulation of marsh with 10% added subsidy 70
Figure 26. Simulation of marsh with 50% added subsidy 71
Figure 27. Simulation of marsh with 100% added subsidy 72
Figure 28. Simulation of marsh with 500% added subsidy 74
Figure 29. Simulation of marsh with 1000% added subsidy 75
Figure 30. Summary of simulation results after 70 years 76
Figure 31. Simulation of unsubsidized marsh receiving nutrients
from rain only 77
Figure 32. Simulation of unsubsidized marsh with peat contributing
only 90% of orginal nutrients 78
vii


Table B-2. Avian survey results for Transect 6.
Common Name
"Oct-92"
Nov-92
Dec-92
Jan-93
American bittern
0
1
u
1
American coot
0
0
4
0
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
2
1
2
Bald eagle
0
0
0
0
Bam swallow
0
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Bluejay
0
0
0
0
Blue wing teal
0
0
0
0
Boat tail grackle
0
0
0
1
Carolina wren
0
0
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
0
0
0
0
Common moorhen
6
0
0
0
Common snipe
0
0
0
0
Common yellow throat
1
3
1
1
Double-crested cormorant
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
1
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
0
0
Gad wall
0
0
0
0
Glossy ibis
0
0
0
0
Great blue heron
1
0
0
0
Great white egret
0
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
3
3
2
2
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
0
0
0
0
Little blue heron
0
0
0
0
Logger headed shrike
0
0
0
0


16
studies, so that it was not necessary to recalculate their values. Table 1 lists the
transformities used in this study.
An environmental loading ratio and an investment ratio were calculated to
compare the quantities of different energy qualities entering each system. The
environmental loading ratio determined the input of nonrenewable energies (e g., external
subsidy) and divided it by the input of renewable energies (e g., sun, rain, nutrients in
rain.) The investment ratio divided the amount of purchased energy (e.g., pump system
including fuel, construction, operation and maintenance, and pump structure) entering the
system by the amount of free energies (e.g., sun, rain, nutrients, phytoplankton.)
Vegetation Complexity and Structure
Vegetative cover richness, complexity, and percent cover were determined using
aerial photos and a computer mapping program (ARCinfo). Vegetative cover types were
analyzed to provide insight into landscape scale successional processes occurring in the
subsidized and unsubsidized marshes. In November 1990, November 1991, April 1992,
and November 1992, the SJRWMD photographed the marshes from a small Cessna plane.
The photos were analyzed at the Center for Wetlands and Water Resources using
ARCinfo, a geographic information system computer mapping program.
The aerial photos of the marshes, taken by SJRWMD, were interpreted and
resulting land cover maps were digitized into ARCinfo as coverages. Vegetative percent
cover was determined for each cover type in each marsh and for each transect shown in
Figure 3 (transects were laid out for avian sampling.) Each transect had a fixed width of
35 meters on either side of the center line. Four 440 meter long transects (T1 through T4)
were established in the subsidized marsh, and two 750 meter long transects were establish
in the unsubsidized marsh (T5 and T6). Table 2 describes the eight vegetative structure
types used to generalize the cover types occurring in the survey areas.


Table A-4. --continued.
Common Name Feb-92
Mallard duck 0
Marsh wren 0
Mottled duck 0
Mouring dove 0
Northern cardinal 0
Northern herrier 0
Northern mocking bird 0
Northern pintail 0
Osprey 0
Palm warbler 5
Pied billed grebe 0
Purple gallinule 0
Red shoulder hawk 0
Red wing black bird 17
Sedge wren 0
Snowy egret 0
Song sparrow 0
Sora rail 0
Swamp sparrow 0
Tree swallow 0
Tri-color heron 0
Turkey vulture 0
White ibis 0
Willet 0
Wood duck 0
Yellow crown night heron 0
Yellow rumped warbler 0
Yellow warbler 0
Total 119
XF92'Wy792 Jun-92 Aug-92
<3 0 8
5 0 0
2 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
1 0 0
0 0 0
0 0 0
0 0 0
11 46 16
0 0 0
0 0 0
0 0 0
2 0 0
0 0 0
0 0 0
0 0 2
0 0 0
0 3 0
0 0 0
0 1 0
0 0 0
0 0 0
0 2 0
107 80 69
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
2
0
0
0
0
0
0
0
50


DISCUSSION
The external subsidy seems to affect the self-organization of the constructed
wetland as the theory predicted at least in the early stages of succession or equilibration.
The predicted response of the marsh is evidenced in the more rapid conversion of the
subsidized marsh into a monoculture and the higher animal densities and biomass.
Vegetative communities, as identified by cover type, changed more rapidly in the
subsidized marsh over the study period. Open areas were more quickly over grown and
contained a higher percentage of Tvpha spp. After two years the dominate cover type of
the subsidized marsh was Tvpha Community which although includes many well
represented vegetative species it is more comparable to a monoculture. The unsubsidized
marsh also became less open, but did not seem to progress towards a monoculture plant
community at the same rate as the subsidized marsh. A possible explanation could be that
an external subsidy increases the rate of early successional or equilibration processes.
The simulation model showed a more dramatic rate of change of vegetative
communities and wildlife biomass over a much longer period of time. The field
observations were not taken over a long enough time to interpolate the progression of
successional stages that may occur in a constructed wetland. However, the simulation
model, which was calibrated using data collected from the field, allows a good prediction
of marsh self-organization. Overall, the model predicted the rate of succession will
increase with an increase in nutrient subsidy.
All sources entering the system's boundary have a potential to influence the
system's self-organization. Sources most likely to have the greatest influence are those that
have high transformities or require a large amount of energy such as use fuel and the pump
90


39
Budgets of Water and Nutrients
Given in Figures 7 and 8 are water and nutrient budgets for both marshes. The
pump system supplies 96% of the water entering the subsidized marsh. In the
unsubsidized marsh, rain supplies the 100% of the water. In addition, the turnover of the
water in the subsidized marsh was determined to be approximately 25 times faster than
that of the unsubsidized marsh.
Nutrient budgets in the two marshes were also different. The pump system
supplied 55% of the total nitrogen and phosphorus entering the subsidized marsh, and the
nutrient rich peat supplied 35%. Rain supplied the majority of total nitrogen and
phosphorus to the unsubsidized marsh (75%).
Vegetative Communities
Richness of Vegetative Cover Types
Figures 9-12 show the vegetative cover of the overall marshes for four time
periods. Over the avian survey period, richness of vegetative cover types changed
following different patterns in each marsh as shown in Figure 13. Richness in the
subsidized marsh increased between November 1990 to November 1991 by one index
level from 2.86 to 3.86. In April 1992 richness decreased to 3.25, and remained at that
level in November 1992.
Richness was highest in the unsubsidized marsh in November 1990 at 5.00. In
November 1991 and April 1992 richness decreased. However, by November 1992,
richness in the unsubsidized marsh had increased again to near its original level at 4.69.
Using a paired t-test it was determined that richness between the subsidized and
the unsubsidized marsh was significantly different (n = 13, df = 5.5, p = 0.02).


Table A-l. continued.
Common Name
Sif>92
Oct-92
'DSc-92
Jaffsr
Feb-93
American bittern
0
0
1
0
0
American coot
0
0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
1
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
1
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
5
1
15
0
9
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
5
7
18
40
11
Common snipe
0
0
0
0
0
Common yellow throat
0
0
11
2
1
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
1
1
1
0
Foresters tem
0
0
0
3
6
Fulvous whistling duck
0
0
0
0
103
Gad wall
0
0
0
0
0
Glossy ibis
0
0
0
0
1
Great blue heron
2
1
0
1
1
Great white egret
0
0
0
1
0
Greater yellow legs
0
0
0
0
0
Green back heron
0
2
3
2
1
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
1
Least bittern
1
0
1
0
0
Little blue heron
1
0
0
0
0
Logger headed shrike
0
0
0
0
0


Fuel = 50%
0 15 30 45 60
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 26. Simulation of marsh with 50% added subsidy.


TI
f
ft
<
rt>
n
en
a
o-
(
o
C/3
&
1.
J
3
en
T3
8
*
a>
en
CT
O
PJ
H
en
3*
n>
en
Shannon Diversity Index
Unsubsidized Marsh
Shannon Diversity Index
OOt KKJUOJJ^
onouionono
ooooooooo
Aug-91
Sep-91
Nov-91
Jan-92
Feb-92
Apr-92
May-92
Jun-92
Aug-92
Sep-92
Oct-92
Nov-92
Dec-92
Jan-93
Feb-93
Mar-93
Apr-93
May-93
Jun-93
Mean
en
&
2
5
e-n


53
Avian Community Structure
Diversity of Avian Community
Average avian species diversity in the two marsh areas was lowest in the
subsidized marsh and highest in the unsubsidized marsh as shown in Figure 17. The
subsidized marsh had an average species diversity of 2.65, and the unsubsidized marsh had
an average diversity of 3.04. Average diversity among the subsidized and unsubsidized
marshes was significantly different (n = 54, df = 4, p = 0.02) over the time both marshes
were surveyed.
After an initial increase, averaged diversity in the subsidized marsh seemed to
gradually decrease over the survey period. The change in diversity over the survey period
was significant (n = 14, d = 5, p = 0.04.)
Evenness of Avian Community
In Figure 18 it is shown that evenness for the subsidized marsh did not differ
significantly over time (n = 14, df = 5, p = 0.08). Average evenness was 0.67. Results for
evenness revealed that the unsubsidized marsh had more species of greater abundance than
the subsidized marsh. Average evenness for the unsubsidized marsh was 0.82. Evenness
was significantly different between the subsidized and unsubsidized marsh (n = 54, df=
4, p = 0.02).


43
NOVEMBER 1991
SCALE: METERS
NORTH
250 250
1 1 1
-4
k
500
Herbs
Shrubs
Open Water
Erne r g e n t s
LEGEND
Floating Aquatics
Typha < Open Water
Typha >= Open Water
Typha Community
Figure 10. Map of vegetative cover for November 1991


Birds Double Intake Rate (Unsubsidized Marsh)
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 37. Simulation of unsubsidized marsh with birds requiring double their food
requirements.


Birds Double Intake Rate (Subsidized Marsh)
0 15 30 45 60
Nutrients
P1ants
Insects
Fish
Birds
Years
Figure 38. Simulation of subsidized marsh with birds requiring double their food
requirements.


Table 7. Summary of vegetative community structure.
Parameter Subsidized Marsh Unsubsidized Marsh Significant Difference
Richness 3.31
Complexity 1.45
Dominate Cover Type (%)
Nov-90 Herbs
86.17%
Nov-91 Typha >= Open Water
34.20%
4.32
n= 13, df = 5.5, p = 0.02
1.49
Herbs
n= 18, df = 8, p = 0.02
43.04%
Shrubs
n= 18, df = 8, p = 0.01
59.86%
Apr-92 Typha Community
34.07%
Typha Community
15.98%
n = 18, df= 8, p = 0.03
Nov-92 Typha Community
66.70%
Typha Community
48.61%
n= 18, df= 8, p = 0.02


Table A-4. Avian survey results for Transect 4.
Common Name
Aug-91
"Sep-91"
Nov-91
"Jan-92"
American bittern
0
0
0
1
American coot
0
0
0
0
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
0
0
Bald eagle
0
0
0
0
Bam swallow
2
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Blue jay
0
0
0
0
Blue wing teal
0
0
0
0
Boat tail grackle
0
5
22
2
Carolina wren
0
0
0
0
Cattle egret
0
4
0
0
Chimney swift
2
0
0
0
Common grackle
0
0
0
0
Common moorhen
0
1
4
2
Common snipe
0
2
0
3
Common yellow throat
0
0
2
2
Double-crested cormorant
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
2
1
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
0
0
Gad wall
0
0
0
0
Glossy ibis
0
6
0
0
Great blue heron
1
0
0
0
Great white egret
0
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
0
0
0
0
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
0
0
0
0
Little blue heron
0
5
0
0
Logger headed shrike
0
0
0
0


2.00
1.80
Nov-90 Nov-91 Apr-91 Apr-92 Nov-92
Subsidized Marsh D Unsubsidized Marsh
Figure 14. Vegetative cover complexity for both marshes.


25
Table 3. continued.
Taxonomic Group Scientific Name Common Name
Other
Falco sparverius
American kestrel
Anhinca anhinga
Anhinga
Hialiaeetus leucocephalus
Bald eagle
Cervle alcvon
Belted kingfisher
Himantoous mexicanus
Black neck stlit
Coraevps atratus
Black vulture
Gallinas calimaco
Common snipe
Phalacrocorax nelacicus
Double-crested cormorant
Trinca melanoleuca
Greater yellow legs
Lanius ludovicianus
Logger headed shrike
Circus cvaneus
Northern herrier
Pandion haliaetus
Osprey
Podilvmbus podiceps
Pied billed grebe
Buteo lineatus
Red shoulder hawk
Cathartes aura
Turkey vulture
CatoDtroDhorus semiDalmatus
Willet


37
9.7
Subsidized Marsh
0.1
Unsubsidized Marsh
Figure 6. Summary diagram of emergy analysis.


Table A-2. Avian survey results for Transect 2.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow wait>ler
Total
Aug-91 Sep-91 Nov-91 Jan-92
0 0 0 0~
0
0
0
0
0
0
0
0
0
0
0
0
25
0
0
0
0
0
0
0
0
6
0
0
0
0
1
38
0
0
0
0
0
0
0
0
0
0
0
0
16
0
1
0
0
0
0
0
0
0
0
2
0
0
0
32
3
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
1
0
0
0
69
0
0
0
0
0
0
0
0
3
0
0
0
0
0
202


23
Table 3. Avian species by taxonomic group.
Taxonomic Group
Scientific Name
Common Name
Gallinules
Flica americana
American coot
Gallinula cholorpus
Common moorhen
Rallus elecans
King rail
Porrihvrula martinica
Purple gallinule
Porzana Carolina
Sora rail
Wading Birds
Botaurus lenlitnnosus
American bittern
Nvcticorax nvcticorax
Black crown mght heron
Bubulcus ibis
Cattle egret
Ardea herodias
Great blue heron
Casmerodius albus
Great white egret
Butorides striatus
Green back heron
Lxobrvchus exilis
Least bittern
Egretta caerulea
Little blue heron
Egretta thula
Snowy egret
Eeretta tricolor
Tri-color heron
Nvcticorax violaceus
Yellow crown night heron
Black Birds
Ouiscalus major
Boat tail grackle
Ouiscalus quiscalus
Common grackle
Aeriaius phoeniceus
Red wing black bird
Passerines
Hirundo rustica
Bam swallow
Polioptila caerulea
Blue-gray gnatcatcher
Guiraca caerrulea
Blue grosbeak
Cvanocitta cristata
Blue jay
Thrvothorus ludovicianus
Carolina wren
Chaetura pelasnca
Chimney swift
Geothlvpis trichas
Common yellow throat
Tvrannus tvrarmus
Eastern kingbird


Table B-l. Avian survey results for Transect 5.
Common Name
7H-9I
Nov-92"
Dec-92
Jan-93
Amen can bittern
1
6
1
2
American coot
0
1
6
10
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
2
1
Bald eagle
0
0
0
0
Bam swallow
0
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Blue jay
0
0
0
0
Blue wing teal
0
0
0
0
Boat tail grackle
11
0
0
0
Carolina wren
0
0
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
0
0
0
0
Common moorhen
4
21
14
28
Common snipe
0
1
0
0
Common yellow throat
0
4
1
0
Double-creasted cormorani
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
0
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
0
0
Gad wall
0
0
0
0
Glossy ibis
0
0
0
0
Great blue heron
0
0
1
0
Great white egret
0
0
0
1
Greater yellow legs
0
0
0
0
Green back heron
3
3
2
5
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
1
0
1
1
Least bittern
3
0
0
0
Little blue heron
0
0
0
0
Logger headed shrike
0
0
1
0


Fish Double Intake Rate (Subsidized Marsh)
Nutrients
Plants
Insects
Fish
Birds
Years
Figure 36. Simulation of subsidized marsh with fish requiring double their food
requirements.


60
Table 8. Avian species by size class.
Size Class (kg) Common Name Average Weight (kg)
_____
American kestrel
0.11
Bam swallow
0.02
Belted kingfisher
0.15
Blue jay
0.03
Blue wing teal
0.09
Boat tail grackle
0.11
Bue-gray gnatcatcher
0.04
Carolina wren
0.02
Cattle egret
0.34
Chimney swift
0.02
Common grackle
0.11
Common moorhen
0.40
Common snipe
0.13
Common yellow throat
0.01
Eastern kingbird
0.04
Eastern phoebe
0.02
Foresters tem
0.11
Greater yellow legs
0.21
Green back heron
0.18
Ground dove
0.00
Indigo buntirg
0.02
Kill deer
0.09
Least bittern
0.07
Little blue heron
0.40
Logger headed shrike
0.05
Marsh wren
0.02
Mourning dove
0.00
Northern cardinal
0.04
Northern mocking bird
0.06
Palm warbler
0.01
Pied billed grebe
0.30
Purple gallinule
0.40
Red wing black bird
0.03


78
90% Peat(U nsub sidize d M arsh)
Years
Figure 32. Simulation of unsubsidized marsh with peat contributing only 90% of original nutrients.


Table A-3. --continued.
Common Name
Sep-92
Oct-92
Dec-92
Jari-^r
Feb-93
American bittern
0

0
0
1
American coot
0
0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
1
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
14
0
0
3
Boat tail grackle
0
1
0
0
0
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
3
24
20
8
20
Common moorhen
0
0
0
0
0
Common snipe
0
2
5
1
0
Common yellow throat
1
0
0
0
0
Double-creasted cormorani
0
0
0
0
0
Eastern kingbird
0
0
2
1
0
Eastern phoebe
0
0
0
0
25
Foresters tern
0
0
0
0
0
Fulvous whistling duck
0
0
0
0
0
Gad wall
0
0
0
0
1
Glossy ibis
0
0
0
0
0
Great blue heron
0
0
0
0
0
Great white egret
0
0
0
0
0
Greater yellow legs
1
2
0
0
0
Green back heron
0
0
0
0
0
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
1
0
0
King rail
1
0
0
0
0
Least bittern
0
0
0
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0


METHODS
This study was conducted in four stages. An emergy analysis was used to compare
the subsidized and unsubsidized marshes based on their relative external energetic inputs.
For the second stage, a geographical information system (GIS) program was used to
estimate vegetative cover. Early successional structural complexity was compared for the
first two years after the marshes were flooded with nutrient enriched water from Lake
Apopka.
Field studies were conducted in the third stage to compare the emerging properties
of the wildlife communities in each marsh. Both the fish and avian communities were
evaluated, although the avian communities were more closely studied. In the final stage, a
macroscopic-mini model of a hierarchically organized marsh community was simulated to
test theories of early succession in nutrient subsidized marshes.
Energy System Diagram
Energy system diagrams were drawn and used to organize thinking and data
collection. First complex diagrams were drawn showing all pathways and compartments
believed to be important. A second, aggregated macroscopic- minimodel was drawn and
used for simulation programming.
13


Table A-4. -continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
Au^-91
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
20
SipNT
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
6
0
0
0
30
Nov-91
U~
11
3
0
0
0
0
0
0
5
0
0
0
121
0
0
0
0
2
0
0
0
0
0
0
0
0
0
172
7ST9I
~TT~
0
1
0
0
0
0
0
0
2
0
0
0
38
0
0
0
0
0
0
0
0
0
0
0
0
0
0
52


50
Nov-90
CL
100.00 -
80.00
60.00 -
40.00
20 00 WmSim
0.00 4
Herbs
Shrubs Open Water Floating Emugents Typha < Open Typha >= Open Typha
Aquatics Water Water Community
Nov-91
100.00 -
80.00-
5 60.00 '-
| 40.00 -
** 20.00 -
0.00
Herbs
Shrubs Open Water Floating Emergents Typha < Open Typha >= Opm Typha
Aquatics Water Water Community
Apr-92
loo.oo --
80.00 -
60.00 -
40.00 -
20.00 --
0.00
Herbs
Shrubs Open Water Floating Emergen ts Typha < Opm Typha >= Opm Typha
Aquatics Water Water Community
loo.oo --
0 80.00 --
O 60.00 '
| 40.00-
0
20.00 -
0.00
Herbs
Nov-92
Shrubs Opm Water Floating Emergents Typha < Opm Typha >= Opm Typha
Aquatics Water Water Community
Figure 16. Vegetative percent cover of unsubsidized marsh.


Table 8. continued.
Size Class (kg)
Common Name
Average Weight (kg)
1.21 1.60
Osprey
1.36
>2.10
Bald eagle
4.54
Black vulture
2.28
Great blue heron
2.95
Turkey vulture
2.20


58
Nov-91
Figure 20. Overall avian density in unsubsidized marsh.


10
Description of Study Site
Lake Apopka is a large (area = 124 kmA2), shallow (mean depth=1.7m)
hypereutrophic lake in Central Florida (Lowe et al. 1992). There is debate as to the
naturally occurring trophic status of the lake (Schelske and Brezonik 1992). Schelske and
Brezonik suggested that in the early 1940's a hurricane removed most of the rooted
macrophytes in the lake which lead to the early stages of increased nutrient availability and
subsequently increased algal productivity. Lowe et al. (1992) also believed that
agricultural practices since 1947 may have contributed to the eutrophication of Lake
Apopka.
Before 1947, much of the area surrounding the lake was freshwater marsh. State
and federal programs assisted local farmers in converting the marshes into agricultural use.
Nutrient enrichment of the lake further increased from water that was back pumped from
the agricultural fields. The practice was for farmers to periodically flood their fields with
lake water and then back pump nutrient enriched water into the lake prior to planting the
fields. The continuation of this farming practice today may, in part, sustain the current
trophic status of the lake which is undesirable to local fishermen and government agencies.
Addressing the nutrient status of this lake, the St. Johns River Water Management
District (SJRWMD) constructed a 200 hectare freshwater marsh on former agricultural
lands with the goal of pumping lake water through the system. Lowe et al. (1992)
suggested that pumping enriched lake water through a created marsh, filtration of
phosphorus and suspended sediments could be maximized. To determine the effectiveness
of this treatment system, the SJRWMD is conducting a pilot study of the 200 hectare
created marsh. The marsh occupies previous muck farm land which is adjacent to currently
ongoing much farm operations and undeveloped woodlands.
The Apopka demonstration project contains two marshes that are receiving
pumped lake water from Lake Apopka shown as the north marsh and the subsidized marsh


DISCUSSION 90
Conclusions 96
APPENDIX A: AVIAN SURVEY RESULTS FOR TRANSECTS 1 -4 ... 97
APPENDIX B: AVIAN SURVEY RESULTS FOR TRANSECTS 5-6 ... 122
APPENDIX C: COMPUTER SIMULATION MODEL 131
REFERENCES CITED 135
BIOLOGICAL SKETCH 143
vi


Figure 13. Vegetative cover richness for both marshes.


93
would form and could influence self-organizational processes. This model, however,
accomplishes the task of comparing an unsubsidized marsh to a subsidized marsh and
predicting the rate of succession and the increase in carrying capacity.
The storages in the energy systems diagram represent the volume of water in the
marsh, the total amounts of nitrogen and phosphorus, organic matter, detritus, and assets
pertaining to the pump structure. The growth of any one of these storages causes the
others to grow because the whole marsh system is autocatalytic.
For example, if more fuel is put into the structure (assets) of the pumps more
water would be pumped from Lake Apopka; hence, more nutrients will be added to the
system. More nutrients will increase the productivity of the primary producers, and will
theoretically lead to an increase in consumer productivity. Productivity will level off
eventually, but the growth rate may prevent this from happening until later than would be
expected in an unsubisdized system. Not shown in the diagram are the effects of the
subsidy on species diversity or distribution. In theory, as productivity levels off, then
energy pathways diversify to facilitate the input of more energy resources and increase
efficiency of energy use.
Material and energy balances as shown in the emergy analysis were significantly
different between the subsidized and unsubsidized marshes. For example, environmental
loading of the subsidized marsh was three and a half times as that of the unsubsidized
marsh. Due to the nonrenewable energy sources from the lake (e g., nutrients,
phytoplankton) and the pump system itself, the subsidized system had much higher flows
of available resources. This is also clearly evident in the higher densities and biomass of
the avian and fish communities. On the other hand, the complexity of the subsidized
marsh as measured by diversity and community structure was lower. Therefore, high
energy subsidies may compromise the complexity of the system in favor of high
productivity. Moreover, low diversity of the food base (eg., the fish community) was
probably not a factor in the increase in the overall carrying capacity of the subsidized


34
Table 4. continued.
5 Phytoplankton (as chlorophyll-a): 8.84 E-3 mg/1 (Lowe et al. 1992)
(8.84E-3 mg/lX40 cfsX28.3 l/cf)(3.15E7 sec/yr)
(IE-3 g/mg)(5J/g)/74.5 ha) = 2.12E+04 J/ha/yr
6 Pumped water-chemical potential (Coveney 1993)
(40 cfs)(7.48 gal/cf)(3700 g/galX3.15E7 sec/yr)
((5J/g)/(74.5)= 2.39E+09 J/ha/yr
7 liquid fuel: 61,532 gal/yr diesel and 1044 gal/yr oil (Coveney 1993)
(6.26E4 gal/yrX 1-46E8 J/gal)/(74.5 ha)= 1.21 E+l 1 J/ha/yr
8 Construction structure : 2.54 lb (Coveney 1993)
(2.54E4 lbX4.5E2 g/lb)/(30 yr useful life)/(74.5 ha)= 5.11 E-K)3 J/ha/yr
9 Construction-services (Coveney 1993)
(2.2E6 $V(241.9 ha)/(30 yr uselful life)
(74.5 ha/241.9 ha) = 9.34E+01 $/ha/yr
10 Operation and maintenance (Coveney 1993)
(7.5E5$)/(241.9haX74.5/241.9ha)= 9.55E+02 $/ha/yr


95
Therefore, the avian community in the unsubsidized marsh may also become less diverse
as open areas become smaller and species such as Tvpha spp. become more dense.
Baln (1993) suggested a different explanation for self-organizational processes in
early successional ecosystems. If a more diverse trophic structure was present initially,
then the system may have utilized more energy pathways eariler creating a more diverse
system. Hence, avian diversity in constructed wetlands may be limited by rate of trophic
structure development rather than the available energetic resources. Both the subsidized
and unsubsidized marshes, however, were in early succession throughout the study period.
Higher avian diversities with may be reached as each marsh continues to self-organize.
Community structure and dynamics are likely a result of many processes including
demographics, energy cycling, habitat disturbance, and the influence of other populations
(Wiens 1989). For example, competetion appeared evident between the animal
communities in the computer simulation sensitivity tests including those that affected
eating rates and migration. However, it is difficult to asses the changes in community
structure which occur due to specific processes because the processes do not act as
independent variables, but rather as components of the same system. In this case,
however, organization and community dynamics are probably more controlled by the
availability of energy sources with high transformities.
The difference between the available resources of each marsh is indicated in the
environmental loading ratios. The pump system and its required support (e g., fuel,
structure, goods and services) account for 78.04% of the nonrenewable energies available
to the subsidized system for self-organizing processes. In contrast, the unsubsidized
marsh does not have these subsidies and therefore has to rely more on available renewable
resources. The investment ratios indicate the contribution of purchased energies (e.g.,
marsh construction, operation and maintenance, pump system) toward facilitating the
input of renewable and nonrenewable free energies (e.g., sun, rain, nutrients,
phytoplankton). Much higher amounts of free energies are available to the subsidized


65
Fish Density and Biomass
Although similar species were found in the subsidized and unsubsidized marshes,
fish densities were significantly different (n = 30, df = 5, p = 0.01). The subsidized marsh
had an average density of 230 fish m"2 as shown in Figure 23. Average fish density in the
unsubsidized marsh was 165 fish m"2.
Fish species found in the subsidized marsh included Gambusia affinis. Heterandria
formosa. and Ictalurus nebulosus. G. affinis. H, formosa. and Talapia spp. were the
species found in the unsubsidized marsh. Although subsidized marsh samples did not
include Talapia spp. there were sightings of large individuals and nests in open areas.
G. affinis was at a higher density in the subsidized marsh, but a higher percentage was
found in the unsubsidized marsh. Of the fish collected in the subsidized marsh, 76.09%
were G. affinis. In the unsubsidized marsh, 81.82% were G. affinis. The second most
abundant fish species in the subsidized marsh was H. formosa (17.39% of overall catch),
and this species was also less abundant in the unsubsidized marsh (18.18% of overall
catch.) Fish biomass was also significantly different in each marsh. In the subsidized
marsh, fish biomass was at 6.44 kg m'2. The unsubsidized marsh had 4.39 kg m*2 of
fish. By far the greatest biomass of fish was G. affinis contributing about 80.01% of the
total in the subsidized marsh, and 85.87% of the total in the unsubsidized marsh. Table 9
summarizes the results of the wildlife study.
Computer Simulation Model
Figure 24 shows the results for the simulation of the unsubsidized marsh when fuel
inputs and nutrients from the hypereutrophic lake are zero. Each storage in the marsh
system had an initial level of zero.


Table A-3. --continued.
Common Name
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
Feb-92 Apr-92 May-92 Jun-92 Au'£97
0 1 0 0
0
0
0
0
0
0
0
2
0
0
0
24
5
0
0
0
2
0
0
0
0
0
0
0
0
0
0
53
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
1 0 0
0 0 0
0 0 0
0 0 0
10 17 9
0 0 0
0 0 0
0 0 0
2 1 0
0 0 0
0 0 0
0 0 0
0 0 0
0 2 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
0 0 0
36 39 45
0
0
0
0
0
0
0
0
0
0
0
21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
67


Table A-l. -continued.
Common Nlame
Mallard duck
Marsh wren
Mottled duck
Mouring dove
Northern cardinal
Northern herrier
Northern mocking bird
Northern pintail
Osprey
Palm warbler
Pied billed grebe
Purple gallinule
Red shoulder hawk
Red wing black bird
Sedge wren
Snowy egret
Song sparrow
Sora rail
Swamp sparrow
Tree swallow
Tri-color heron
Turkey vulture
White ibis
Willet
Wood duck
Yellow crown night heron
Yellow rumped warbler
Yellow warbler
Total
55537
"T"
o
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
30
H37
0
8
0
0
0
0
0
0
1
0
0
0
0
10
0
0
0
0
2
0
0
0
0
0
0
0
0
0
33
c-92
o
6
0
0
0
0
0
0
1
0
0
0
0
108
0
0
0
11
0
0
0
0
0
0
0
0
0
0
177
Jan-93
TT-
1
0
0
0
0
0
0
0
0
0
0
0
33
0
0
0
0
0
0
0
0
0
0
0
0
0
0
84
P553J
0
o
o
0
0
0
0
0
0
1
0
0
0
4
0
0
0
1
0
0
0
0
0
0
0
0
0
0
140


populations according to Willard and Hiller (1989). When some populations are at low
levels, others are high.
Local short term disturbances could allow species with greater colonizing ability to
recolonize disturbances (Bertness and Ellison 1987). The accumulative affect of these
events could change the areal distribution of the species and provide new patterns.
Moreover, Weller (1981) described a variety of behavioral adaptations for freshwater
wildlife species in wetlands which combine both spatial and temporal heterogeneity on a
landscape scale. Weller suggested that this heterogeneity allows internal adaptation.
A study by Doughtery (1990) evaluated the interrelationship between space and
time. One of his conclusions was that community measurements of successional
development were related to measurements of landscape pattern. Moreover, Brown
(1989) suggested that the appropriate scale from which to view any problem is the next
larger one.
Kareiva (1994) suggested in his review paper that more serious experimentation
should be performed that explicitly tests major hypotheses emerging from recent
theoretical explorations of spatial effects. Recently many ecologists are turning towards
larger scale studies to explain ecological functions and dynamics.
In his recent study, Bowers (1994) modeled both age structured and habitat
structured populations to measure the affects of age on individual performance versus the
affects of habitat selection. He found that habitat selection can have as much or more of
an affect on population dynamics in a particular ecosystem as demographic forces such as
birth, death, and migrations. Bowers also suggested that ignoring the affects of landscape
scale processes could produce misleading results.
Shaw and Atkinson (1990) introduced the terminology, components, advantages,
and current limitations of computerized GIS's for ornithological research. Two case
studies were provided as illustrations of the potential utility of GIS for ornithological
research.


138
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Kareiva, Peter. 1994. Space: the final frontier for ecological theory. Ecology. 75(1): 1.
Kerekes, Joseph J. 1990. Possible correlation of summer common loon (Gavia immerl
population with the trophic state of a water body. Verh, Intemat. Verein.
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Kerekes, J., Tordon, R., Nieuwburg, A., and L. Risk. 1992. Fish-eating bird abundance in
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Hydrobiologia 0:1-5.
Knight, Robert L. 1992. Ancillary benefits and potential problems with the use of
wetlands for nonpoint source pollution control. Ecological Engineering.
l(l/2):97-l 13.
Krull, John N. 1970. Aquatic Plant-Macroinvertebrate Associations and Waterfowl.
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Leschisin, Douglas A, Gary L. Williams, and Milton W, Weller. 1992. Factors Affecting
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12(3): 178-183.
Lotka, Alfred G. 1925. Elements of Mathmatical Biology. Dover. New York.
Lotka, Alfred G. 1922. Natural selection as a physical principle. Proceedings of the
Natural Academy of Sciences. 8:151 -154.
Lowe, Edgar F., Stites, David L., and Michael F. Coveney. 1989. Potential role of marsh
creation in restoration of hypereutrophic lakes pp. 710-715 in Donald A. Hammer
ed., Constructed Wetlands for Wasterwater Treatment: Municipal, Industrial, and
Agricultural. Lewis Publishers.
Lowe, Edgar F., Battoe, Lawrence E., Stites, David L., and Michael F. Coveney. 1992.
Particulate Phosphorus Removal via Wetland Filtration: An Examination of
Potential for Hypertrophic Lake Restoration. Environmental Management
16(l):67-74.
Maehr, David S. 1984. Status of birds using phosphate-mined lands in Florida. American
Birds. 38(1) 28-31.
Marble, Anne D. 1992. A guidebook to wetland functional design. Lewis Publishers,
Cnelsea, MI.


Figure 33. Simulation of unsubsidized marsh with insects requiring
double their food requirements 79
Figure 34. Simulation of subsidized marsh with insects requiring
double their food requirements 80
Figure 35. Simulation of unsubsidized marsh with fish requiring
double their food requirements 82
Figure 36. Simulation of subsidized marsh with fish requiring
double their food requirements 83
Figure 37. Simulation of unsubsidized marsh with birds requiring
double their food requirements 84
Figure 38. Simulation of subsidized marsh with birds requiring
double their food requirements 85
Figure 39. Simulation of periodic fish kill in unsubsidized marsh 86
Figure 40. Simulation of periodic fish kill in subsidized marsh 87
Figure 41. Simulation of increased migration in unsubsidized marsh 88
Figure 42. Simulation of increased migration in subsidized marsh 89
VUl


RESULTS
Ecological Systems Overview
Given in Figure 5 is a systems diagram showing important processes
occurring in the subsidized marsh. The unsubsidized marshes the same components with
the exception of the pump system. Energy sources influencing the marsh system included
renewable and nonrenewable sources. Non-renewable sources were further divided into
free sources obtained from the environment, and purchased sources which were obtained
after the transfer of money. SJWMD was included as the source of money for the
purchased nonrenewables.
Renewable sources, sunlight and rain, are shown on the left side of diagram
originating outside the marsh system's border. Free non-renewable sources were drawn in
the upper left portion of the diagram. These sources include water, nutrients, and organic
matter from Lake Apopka. Purchased non-renewables include fuel used to operate the
pumps, construction costs for the physical components of the pump system and for the
services required for installation. Also, the costs for operation and maintenance of the
flow-way marsh project were represented.
Components within the system boundaries in the diagram were divided into three
types: producers, consumers, and storages. Producers include macrophytes and algae
which grow using sunlight and nutrients. As shown in the diagram by the pathway
connections, the productivity of these plants largely depends on the nutrient concentration
in the water column.
30


Table A-l. Avian survey results for Transect 1.
Common Name
Aug-91
"Sep-91
Nov-91
"Jan-92
American bittern
"" 0
"" 0
0
o
American coot
0
0
0
0
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
0
0
Bald eagle
0
0
0
0
Bam swallow
0
0
0
0
Belted kingfisher
0
0
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Bluejay
0
0
0
0
Blue wing teal
0
0
0
0
Boat tail grackle
3
0
0
0
Carolina wren
0
1
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
0
0
0
0
Common moorhen
1
3
4
8
Common snipe
0
0
0
1
Common yellow throat
1
3
1
0
Double-creasted cormorant
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
0
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
0
2
2
Gad wall
0
0
0
0
Glossy ibis
0
0
0
0
Great blue heron
0
1
0
0
Great white egret
0
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
4
0
0
1
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
0
0
0
0
Little blue heron
0
0
0
0
Logger headed shrike
0
0
0
0


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INGEST IEID EEMGBGT4N_IBNVS1 INGEST_TIME 2015-03-18T19:55:55Z PACKAGE AA00027492_00001
AGREEMENT_INFO ACCOUNT UF PROJECT UFDC
FILES


Table B-2. continued.
Common Name
Feb-93
"Mar-93
Apr-93'
' M ay- 9'3
"Jul-93
Amen can bittern
3
2
0
6
o
American coot
0
0
0
0
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
2
2
1
2
1
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
2
13
7
2
1
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
0
0
4
0
4
Common snipe
0
0
0
0
0
Common yellow throat
2
2
0
2
0
Double-creasted cormoram
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
0
0
0
Foresters tern
0
0
0
0
0
Fulvous whistling duck
2
0
0
2
0
Gadwall
0
0
0
0
0
Glossy ibis
0
0
0
0
2
Great blue heron
0
0
0
0
0
Great white egret
0
0
0
0
0
Greater yellow legs
0
0
0
0
0
Green back heron
5
0
0
5
4
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
1
0
0
Least bittern
0
0
1
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0


Table A-2. continued.
Common Name
Sep-92"
Oct-92
"Dec-92
Jan-93
"'FeB-93
American bittern
0
0
0
0
1
American coot
0
0
2
1
0
American kestrel
0
0
0
0
0
American widgeon
0
0
0
0
0
Anhinga
0
0
0
0
0
Bald eagle
0
0
0
0
0
Bam swallow
0
0
0
0
0
Belted kingfisher
0
0
0
0
0
Black crown night heron
0
0
0
0
0
Black neck stlit
0
0
0
0
0
Black vulture
0
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
0
Blue grosbeak
0
0
0
0
0
Bluejay
0
0
0
0
0
Blue wing teal
0
0
0
0
0
Boat tail grackle
1
0
0
2
0
Carolina wren
0
0
0
0
0
Cattle egret
0
0
0
0
0
Chimney swift
0
0
0
0
0
Common grackle
0
0
0
0
0
Common moorhen
12
11
12
10
13
Common snipe
0
0
0
0
0
Common yellow throat
0
3
4
3
1
Double-creasted cormorant
0
0
0
0
0
Eastern kingbird
0
0
0
0
0
Eastern phoebe
0
0
1
0
0
Foresters tem
0
0
0
2
6
Fulvous whistling duck
0
0
0
0
2
Gad wall
0
0
0
0
0
Glossy ibis
0
0
0
0
0
Great blue heron
0
0
0
0
0
Great white egret
0
0
0
0
1
Greater yellow legs
0
0
0
0
0
Green back heron
2
1
0
0
1
Ground dove
0
0
0
0
0
Hooded merganser
0
0
0
0
0
Indigo bunting
0
0
0
0
0
Kill deer
0
0
0
0
0
King rail
0
0
0
0
0
Least bittern
4
0
0
0
0
Little blue heron
0
0
0
0
0
Logger headed shrike
0
0
0
0
0


Table A-2. Avian survey results for Transect 2.
Common Name
Aug-91
Sep-91
Nov-91
Jan-92
American bittern
0
0
0
0
American coot
0
0
0
10
American kestrel
0
0
0
0
American widgeon
0
0
0
0
Anhinga
0
0
0
0
Bald eagle
0
0
0
1
Bam swallow
0
0
0
0
Belted kingfisher
0
2
0
0
Black crown night heron
0
0
0
0
Black neck stlit
0
0
0
0
Black vulture
0
0
0
0
Blue grey gnatcatcher
0
0
0
0
Blue grosbeak
0
0
0
0
Bluejay
0
0
0
0
Blue wing teal
0
0
0
44
Boat tail grackle
0
3
5
0
Carolina wren
0
0
0
0
Cattle egret
0
0
0
0
Chimney swift
0
0
0
0
Common grackle
0
0
0
0
Common moorhen
1
7
1
14
Common snipe
0
0
0
1
Common yellow throat
0
0
0
0
Double-crested cormorant
0
0
0
0
Eastern kingbird
0
0
0
0
Eastern phoebe
0
0
5
0
Foresters tern
0
0
0
0
Fulvous whistling duck
0
1
0
52
Gad wall
0
0
0
0
Glossy ibis
0
0
0
5
Great blue heron
1
0
0
0
Great white egret
3
0
0
0
Greater yellow legs
0
0
0
0
Green back heron
1
0
0
1
Ground dove
0
0
0
0
Hooded merganser
0
0
0
0
Indigo bunting
0
0
0
0
Kill deer
0
0
0
0
King rail
0
0
0
0
Least bittern
0
0
0
0
Little blue heron
0
0
0
1
Logger headed shrike
0
0
0
0


O 10 50 100 500 1000
Percent Fuel Increase
H Nutrients H Plants 9 Insects QD Fish O Birds
Figure 30. Summary of simulation results after 70 years.


92
macrophytes were important to waterfowl production despite their poor nutritional value
because they harbor large quantities of macroinvertebrates.
Meeker (1992) suggested that as macrophyte productivity increased, the
abundance of macroinvertebrates and fish increased. Avian densities would then increase
until the carrying capacity was reached given the available food base. Therefore, the
external nutrient subsidy increased the energy flow in productive pathways which resulted
in an increased food base and an increase in the number of higher order consumers.
Avian biomass may follow a similar successional pattern as the vegetation in that
processes are more rapid in the subsidized marsh, but the structure may eventually be the
same in both marshes. In the subsidized marsh, the changes in biomass indicated that the
hierarchy of large to small birds changed slightly over the survey period. Relative to the
overall number of birds present in the subsidized marsh, more larger bodied birds were
present in this marsh. The distribution of the size classes, however, was not even.
Increases in avian density and biomass seem to reflect the expected pattern given in
the systems energy diagram and simulations of the subsidized marsh. This increase could
be also indicate an increase in the carrying capacity of the subsidized marsh given the
comparatively low avian density and biomass found in the unsubsidized marsh. Therefore,
density, biomass, and possibly the carrying capacity increase as the external lakewater
subsidy is continued to be added to the system. In this study, productivity does not level
off, but given a longer study period productivity may eventually reach the carrying
capacity level.
The computer simulations showed that with an increase in nutrient subsidy biomass
the rate at which steady state is reached is increased. This may indicate that the rate of
successional processes are increased. In addition, the biomass storages also increased, and
this may indicate an increase in carrying capacity. For a more realistic depiction of the
increases in subsidy, a component which included the affect that moving water has on
vegetation structure should be added. At very high rates of pumping, a substantial current


47
Vegetative Structure Complexity
Complexity, measured as the fractal dimension of vegetative structure, was similar
in the subsidized and unsubsidized marshes (n = 8, df = 7, p = .63 .) In addition,
complexity appeared to change in a similar pattern in both
marshes as shown in Figure 14. Each marsh seemed to display moderate complexity
throughout the survey period.
Percent Cover of Vegetative Cover Types
Figures 15 and 16 show the vegetative cover of the subsidized and unsubsidized
marsh over the two year period. Vegetative cover in the subsidized marsh changed
significantly over time (n = 36, df = 11, p = 0.01) as well as in the unsubsidized marsh (n =
36, df= 11, p = 0.03.)
In November 1990, the two marshes had significantly different distribution of
cover types (n = 18, df = 8, p = 0.01). The subsidized marsh was dominated by herbs
(86.17%.) Shrub cover and open water were the only other predominant cover types in
the subsidized marsh, but were at less than 10% cover.
Although in the unsubsidized marsh herbs (43.04%) were the predominate cover
type, shrub cover (29.79%) was greater in this marsh than in the subsidized marsh. The
cover of floating aquatics and Tvpha dominated community were also greater than 10% in
the unsubsidized marsh.
Overall, vegetative cover in the two marshes had changed considerably over the
previous year. In November 1991, the percent cover of the various cover types in the two
marshes were again significantly different (n=18, df=8,p = 0.01). Tvpha >= open
water in the subsidized marsh covered the greatest area (34.20%), and Tvpha < open
water had the next highest percent cover (28.58%).


Figure 22. Overall avian biomass in unsubsidized marsh.
Size Classes (kg)
Kilograms per hectare
Kilograms per hectare
Kilograms per hectare
ON
4^
Nov-92


94
marsh. Lower avian diversity and evenness may reflect that fewer avian species were able
to exploit a sustainable food source as those in the unsubsidized marsh. However, higher
numbers of a few avian species could be supported (e.g., black birds) in the subsidized
marsh.
Species diversities in the subsidized marsh seemed to have been compromised
over productivity. Although classical succession predicts that over many years diversity
will eventually increase in highly productive systems (Odum 1969), this may not be
apparent in the earliest stages of succession. The nutrient subsidy seemed to dampen
vegetative cover richness in the subsidized marsh over the survey period except for a slight
increase in November 1991. Vegetative cover richness in the unsubsidized marsh
appeared to not only have a higher average but could be increasing. In contrast,
vegetative structure complexity was relatively unchanged and was similar in both marshes.
Thus, the nutrient subsidy did not seem to affect the patch shape patterns formed by early
successional processes.
Avian diversity and evenness generally declined in the subsidized marsh over the
survey period. This could be a result of declines in vegetative cover richness, less open
water, and/or more dense vegetation (e g., pure Tvpha spp. stands or Tvpha Community
with dense shrubs). The unsubsidized marsh maintained a higher percentage of open water
throughout the vegetative study period.
High productivity coupled with low diversity, such as in the subsidized marsh,
could be considered as the early stages of system development when most of the energy in
the system is being put towards facilitating the input of resources (Odum 1969, Odum,
1971, Odum 1981, Odum 1983). In the later stages of ecosystem self-organization,
energy resources are more efficiently recycled within the system allowing more diverse
uses of the energy such as more opportunity for the development of specialized niches.
The unsubsidized marsh may provide more specialized niches for the avian community
only because its rate of equilibration is slower than that of the subsidized marsh.


SELF-ORGANIZATION OF AN ECOLOGICALLY ENGINEERED WETLAND
IN CENTRAL FLORIDA
By
TONYA MAE HOWINGTON
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
1994