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Influence of Soil and Water Chemistry on Marsh Plant Communities in Palo Verde National Park, Costa Rica

Permanent Link: http://ufdc.ufl.edu/UFE0024173/00001

Material Information

Title: Influence of Soil and Water Chemistry on Marsh Plant Communities in Palo Verde National Park, Costa Rica
Physical Description: 1 online resource (88 p.)
Language: english
Creator: Robichaux, Estelle
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Wetlands perform many important hydrologic and biogeochemical functions; for example, they generally improve water quality, provide flood protection and can retain nutrients such as phosphorous. Relatively little is known about wetlands in Central America, although the vital nature of tropical wetlands, on both the regional and global scale, is increasingly acknowledged. Palo Verde National Park (PVNP), located in Guanacaste Province, Costa Rica, is recognized under the Ramsar Convention on Wetlands of International Importance, due to its role as an important feeding and breeding ground for resident and migratory birds during the dry season. Once part of a large ranching operation, Palo Verde became a national park in the early 1980?s and soon, the open marsh known as Palo Verde Lagoon, became overgrown with cattail (Typha domingensis). Many blamed this transformation on the removal of cattle from the area, and efforts to restore the marsh are ongoing. The purposes of this study were: 1) to conduct a baseline analysis of soil and water chemistry in the marshes of PVNP; 2) to analyze plant species composition in relation to water and soil characteristics; and 3) to determine if Typha domingensis seeds establish preferentially in soils with specific conductivities. Fieldwork for this study was conducted during June and July 2008. Soil and water samples were collected and plant species surveys conducted in eight different areas of the park. Statistically significant differences were found among the areas for many soil and water characteristics (for soil: Ca, Mg, N, Cl, EC, sand and clay content; for water, Mg, K, Na, phosphate and Na). Species richness among the different areas was also statistically significant. Strong relationships between soil EC, Cl, S and K and species richness were found; water Fe, Na and depth were also highly related to species richness. Multivariate logistic regressions performed on the presence and absence of specific species found that soil N, P and K, water nitrate, P and depth all had significant and substantial effects. There were no significant results from the germination experiment. Alternative hypotheses for the establishment of the extensive Typha marshes are supported by the findings of this study. It is hoped that the results of and synthesis provided by this research will raise additional research questions to further evaluate the cattle-grazing hypothesis, which is strongly established in the local community.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Estelle Robichaux.
Thesis: Thesis (M.S.)--University of Florida, 2009.
Local: Adviser: Larkin, Sherry L.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024173:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024173/00001

Material Information

Title: Influence of Soil and Water Chemistry on Marsh Plant Communities in Palo Verde National Park, Costa Rica
Physical Description: 1 online resource (88 p.)
Language: english
Creator: Robichaux, Estelle
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Wetlands perform many important hydrologic and biogeochemical functions; for example, they generally improve water quality, provide flood protection and can retain nutrients such as phosphorous. Relatively little is known about wetlands in Central America, although the vital nature of tropical wetlands, on both the regional and global scale, is increasingly acknowledged. Palo Verde National Park (PVNP), located in Guanacaste Province, Costa Rica, is recognized under the Ramsar Convention on Wetlands of International Importance, due to its role as an important feeding and breeding ground for resident and migratory birds during the dry season. Once part of a large ranching operation, Palo Verde became a national park in the early 1980?s and soon, the open marsh known as Palo Verde Lagoon, became overgrown with cattail (Typha domingensis). Many blamed this transformation on the removal of cattle from the area, and efforts to restore the marsh are ongoing. The purposes of this study were: 1) to conduct a baseline analysis of soil and water chemistry in the marshes of PVNP; 2) to analyze plant species composition in relation to water and soil characteristics; and 3) to determine if Typha domingensis seeds establish preferentially in soils with specific conductivities. Fieldwork for this study was conducted during June and July 2008. Soil and water samples were collected and plant species surveys conducted in eight different areas of the park. Statistically significant differences were found among the areas for many soil and water characteristics (for soil: Ca, Mg, N, Cl, EC, sand and clay content; for water, Mg, K, Na, phosphate and Na). Species richness among the different areas was also statistically significant. Strong relationships between soil EC, Cl, S and K and species richness were found; water Fe, Na and depth were also highly related to species richness. Multivariate logistic regressions performed on the presence and absence of specific species found that soil N, P and K, water nitrate, P and depth all had significant and substantial effects. There were no significant results from the germination experiment. Alternative hypotheses for the establishment of the extensive Typha marshes are supported by the findings of this study. It is hoped that the results of and synthesis provided by this research will raise additional research questions to further evaluate the cattle-grazing hypothesis, which is strongly established in the local community.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Estelle Robichaux.
Thesis: Thesis (M.S.)--University of Florida, 2009.
Local: Adviser: Larkin, Sherry L.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024173:00001


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1 INFLUENCE OF SOIL AND WATER CHEMISTRY ON MARSH PLANT COMMUNITIES IN PALO VERDE NATIONAL PARK, COSTA RICA By ESTELLE S. ROBICHAUX A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2009

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2 2009 Estelle S. Robichaux

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3 For the little lion

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4 ACKNOWLEDGMENTS I wish to thank the Organizat ion for Tropical Studies and the NSF-funded International Research Experience for Graduate Students, whose financial support m a de this research possible. Thanks go to all the wonderful staff members of the OTS Palo Verde Biological Station, in particular Jose D. Ziga and Romelio, who provided incredible emotional support for me during my time at Palo Verde. My greatest appr eciation also goes out to Steven J. Hall, whose assistance in the development and execution of th is research was invaluable. I would like to thank Michael J. Osland for his accessibility upon my arrival at Palo Verde and John Wilkinson for his assistance in the field. Thanks also go to my advisor, Sherry L. Larkin, and my committee members, Wiley M. Kitchens and Todd Z. Osborne, for their insight and patience. My deepest gratitude goes to Richard and Nancy Robichaux, who ended up being wonderfully supportive parents despite all their faults, and mine. I am eternally indebted to my dear friends, Smriti Bhotka, Gabriela Blohm, Ondi Crino and Miramanni Mishkin, for their support, both academic and emotional. Lastly, I wish to thank William Sheard, who has been an incredible source of love, laughter and understanding over the past year-and-a-half.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4LIST OF TABLES................................................................................................................. ..........7LIST OF FIGURES.........................................................................................................................8ABSTRACT.....................................................................................................................................9CHAPTER 1 INTRODUCTION..................................................................................................................11Research Objectives and Proposed Hypotheses..................................................................... 12Background Information......................................................................................................... 12Importance of Wetlands.................................................................................................. 12Central American Wetlands............................................................................................ 13Palo Verde National Park................................................................................................ 14Typha as Invasive Species...............................................................................................16An Unproductive Restoration Based on an Unsubstantiated Hypothesis....................... 18Summary.................................................................................................................................202 METHODS.............................................................................................................................21Study Area..............................................................................................................................21Field Methods.........................................................................................................................22Plant Species Community Composition Surveys............................................................ 23Soil and Water Sample Collection.................................................................................. 23Typha domingensis Seed Collection................................................................................23Laboratory Methods............................................................................................................. ...24Soil Sample Analysis....................................................................................................... 24Water Sample Analysis................................................................................................... 24University of Costa Rica Sample Analysis..................................................................... 25Experimental Methods............................................................................................................25Statistical Methods............................................................................................................ ......26Categorization and Exclusion of Tr ansect 5 from Some Analysis.................................. 26Analysis of Soil and Water Chemistry............................................................................ 26Analysis Plant Species Community Composition........................................................... 27Linear regression analysis of species richness.........................................................27Logistic regression analysis of the most abundant species...................................... 28Analysis of Germination Experiment.............................................................................. 29

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6 3 RESULTS...............................................................................................................................35Soil and Water Chemistry....................................................................................................... 35Salinity Markers..............................................................................................................35Cations.............................................................................................................................36Nitrogen and Phosphorous..............................................................................................37pH....................................................................................................................................37Texture.............................................................................................................................38Correlations.....................................................................................................................38Salinity markers........................................................................................................ 38Cations......................................................................................................................39Nitrogen, phosphorus and pH...................................................................................39Plant Species Community Composition................................................................................. 39Linear Regressions of Species Richness.........................................................................39Logistic Regressions of the Most Abundant Species...................................................... 41Germination Experiment........................................................................................................ 42Summary of Results............................................................................................................. ...434 DISCUSSION.........................................................................................................................62Review of Results.............................................................................................................. .....62Soil and Water Chemistry....................................................................................................... 63Environmental Influences................................................................................................63Seasonal variation....................................................................................................63Geology....................................................................................................................65Tempisque River and Gulf of Nicoya...................................................................... 66Potential Impacts of the Former and Current Ranching Operations............................... 67Plant Species Community Composition................................................................................. 67Germination Experiment........................................................................................................ 69Overall Synthesis....................................................................................................................70Recommendations for Future Research..................................................................................72Conclusions.............................................................................................................................74 APPENDIX A METADATA..........................................................................................................................75B ANOVA AND T-TABLES.................................................................................................... 78C PEARSON CORRELATI ON COEFFICIENTS .................................................................... 80D PLANT SPECIES LIST......................................................................................................... 81LIST OF REFERENCES...............................................................................................................83BIOGRAPHICAL SKETCH.........................................................................................................88

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7 LIST OF TABLES Table page 3-1 ANOVA and T-test table for speci es richness (# of species/1 m2) at multiple scales....... 513-2 Linear model and ANOVA output for fina l regression equations for the response variable Species Richness...............................................................................................553-3 Model output for first order polynomial regression of Typha seed germination............... 61A-1 Plot locations and sample collection and processing dates................................................ 75B-1 ANOVA table for soil variables........................................................................................78B-2 T-table for soil variables....................................................................................................78B-3 ANOVA table for water variables..................................................................................... 79B-4 T-table for water variables................................................................................................ .79C-1 Correlation coefficient table for so il and water elemental variables................................. 80

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8 LIST OF FIGURES Figure page 2-1 Location of Palo Verde National Park in Guanacaste Province, Costa Rica ........312-2 Average total monthly rainfall recorded at the Palo Verde marsh, OTS Biological Station........................................................................................................................ ........322-3 Palo Verde National Park boundary and transect locations............................................... 332-4 Transect design and layout.................................................................................................343-1 Transect averages. For salinity markers............................................................................ 443-2 Transect averages. For electrical conductivity for soil and water.................................... 453-3 Transect averages. For dissolved cati ons in water and effective cation exchange capacity in soil............................................................................................................... ....463-4 Transect averages. For nitrog en compounds in soil and in water..................................... 473-5 Transect averages. For phosphor ous compounds in soil and in water.............................. 483-6 Transect averages. For water and soil pH......................................................................... 493-7 Transect averages. For soil content and texture................................................................ 503-8 Box plot of speci es richness (per 1 m2) by subtransect.....................................................523-9 Trends in species richness. With respect to soil EC, water depth, soil Cl, water Fe, soil K, water Na and soil S.................................................................................................533-10 Output for logistic regr essions. For the presence of A. martinicensis, E. paniculatus, Eleocharis spp., Nymphaea spp., S. clausum T. geniculata and T. domingensis with accompanying model equation output............................................................................... 563-11 Transect averages. For soil electrical conductivity and Typha seed germination, and scatter plot of soil EC and total germination..................................................................... 60

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9 Abstract of thesis Presente d to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science INFLUENCE OF SOIL AND WATER CHEMISTRY ON MARSH PLANT COMMUNITIES IN PALO VERDE NATIONAL PARK, COSTA RICA By Estelle S. Robichaux May 2009 Chair: Sherry L. Larkin Major: Interdisciplinary Ecology Wetlands perform many important hydrologic an d biogeochemical functions; for example, they generally improve water quality, provide flood protection and can retain nutrients such as phosphorous. Relatively little is known about wetlands in Centra l America, although the vital nature of tropical wetlands, on both the regional and global scale, is in creasingly acknowledged. Palo Verde National Park (PVNP), located in Guanacaste Province, Costa Rica, is recognized under the Ramsar Convention on Wetlands of Intern ational Importance, due to its role as an important feeding and breeding ground for reside nt and migratory birds during the dry season. Once part of a large ranching operation, Palo Verde became a national park in the early 1980s and soon, the open marsh known as Palo Verd e Lagoon, became overgrown with cattail ( Typha domingensis ). Many blamed this transformation on th e removal of cattle from the area, and efforts to restore the marsh are ongoing. The purposes of this study were: 1) to conduct a baseline analysis of soil and water chemistry in the marshes of PVNP; 2) to analy ze plant species composition in relation to water and soil characteristics; and 3) to determine if Typha domingensis seeds establish preferentially in soils with specific conductiv ities. Fieldwork for this study was conducted during June and

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10 July 2008. Soil and water samples were collected and plant species surveys conducted in eight different areas of the park. Statistically significant differences were found among the areas for many soil and water characteristics (for soil: Ca, Mg, N, Cl, EC, sand and clay content; for water, Mg, K, Na, phosphate and Na). Species richness among the diffe rent areas was also stat istically significant. Strong relationships between soil EC, Cl, S and K and species richness were found; water Fe, Na and depth were also highly rela ted to species richness. Multivariate logistic regressions performed on the presence and ab sence of specific species found th at soil N, P and K, water nitrate, P and depth all had statistically significant and magnit udinous effects. There were no statistically significant or notable resu lts from the germination experiment. Alternative hypotheses for the es tablishment of the extensive Typha marshes are supported by the findings of this study. It is hoped that the results of and synthesis provided by this research will raise additional res earch questions to further evalua te the cattle-grazing hypothesis, which is strongly established in the local community.

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11 CHAPTER 1 INTRODUCTION The Palo Verde area wetlands are recognized to be of international im portance to resident and migratory waterfowl. After becoming a nati onal park, some of the marshes within Palo Verde National Park (PVNP) experienced dramatic changes in vegetative community structure and no longer provide desirable habitat for avifa una. The restoration of the Palo Verde marsh has been a priority of the Costa Rican conserva tion agenda for over a decade. The basis of the restoration efforts, however, is a scientifically unf ounded hypothesis that the previous presence of cattle in the marshes helped control the growth and spread of Typha domingensis and that their removal has allowed this inva sive species to become dominant. Given the ecological significan ce of these wetlands, an effort to determine verifiable causes of the changes observed in the wetland pl ant communities should be made. Any efforts made now are hindered by a lack of historical information and ba seline data for almost every aspect of the system. Therefore, in addition to any conclusions drawn, any data collected will serve as a baseline datase t and will increase knowledge of the biophysical aspects of this system. The studies conducted in PVNP were based on hypotheses that the factors more likely to have influenced the establishment of Typha domingensis are soil and water chemical characteristics, rather than the presence or absence of cattle. The knowledge gained about this system, through both field and experimental re search, will increase understanding of the ecological framework within which the management and scientific communities must operate. Armed with greater knowledge of the biotic and ab iotic interactions taking place within the park, more effective and scientifically based rest oration techniques ca n be researched and implemented.

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12 Research Objectives and Proposed Hypotheses Objective 1 : To conduct a baseline analysis of water and soil chemistry throughout the marshes of PVNP. o Hypothesis: There will be statistically significant differences in concentrations of the major nutrients and cations between the marshes located in the Typha -dominated areas and those not in that area. Objective 2: To analyze area plant species comp osition in relation to water or soil characteristics. o Hypothesis: There will be statistically significant relationships between certain chemical components in soil a nd water, specifically the major cations and electrical conductivity, a nd plant species composition. Objective 3: To determine if Typha domingensis s eeds will establish preferentially in soils with specifi c conductivities. o Hypothesis: Typha domingensis seeds will have higher rates of germination in soils of mid-range co nductivity (1-3 mS/cm). Background Information Importance of Wetlands Throughout history, wetlands have b een view ed as menacing and gloomy places, offering little or no value to society or to industry. These perceptions have infiltrated everything from literature to historical repres entation, from language connotations to recent popular culture, where wetlands have been portrayed as misera ble, dirty and ominous (Mitsch and Gosselink 2007). Today, we know that wetlands perfor m important functions in hydrologic and biogeochemical cycles, such as cleansing pollu ted water, preventing floods, recharging ground water aquifers and retaining sediment and nutrients (Zedler and Kercher 2005). They are also downstream receivers of human and natural wast e and are essential in shoreline protection. Wetlands support an extensive and widely varied food web that services many industries and have also been recognized as vital in sustaining biodiversity (G ibbs 2000). Moreover, they are a

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13 source of cultural and historical identity that is of ten important to local economies in the form of recreation or touris m (Barbier 1994). Central American Wetlands For m illennia, the resources provided by inland freshwater wetlands have been used for agriculture, timber and hunting throughout Central America (Ellison 2004). In Guanacaste Province, Costa Rica, the land that once supporte d the agricultural economies of indigenous tribes (Helwig 1969) became the heartland of th e logging, farming and cattle ranching industries in Costa Rica at the outset of the 20th century (Becker 1943). As the ecological functions and economic reliance on these systems have become more widely recognized, the vital nature of tropical wetlands to their respective regions ha s become even more pronounced (Aylward and Barbier 1992, Barbier 1994). In contrast to the many well-studied wetland areas in North America and Europe, the wetlands of Central America are, in many ways, terra incognita Despite all Central American countries having adopted the 1971 Convention of Wetlands of Intern ational Importance, especially as Waterfowl Habitat (the Ramsar Co nvention), total wetland area within this region is still unknown and there is no universal wetland classification system defined among these countries (Finlayson and van der Valk 1995, Ellis on 2004). The paucity of research in Central American wetlands has been greatly influenced by two factors: the lack of adequate access to these areas and the harsh, unwelcoming and sometimes even threatening environments. This lack of knowledge is particularly acute when it comes to seasonal wetlands, which experience extreme conditions, ex acerbating even further the li miting factors mentioned above (Sarmiento et al. 2006). The seasonal wetla nd areas within Palo Ve rde National Park (PVNP) are no exception, since no literat ure regarding the wetlands them selves has been published in scholarly journals and very little research c onducted within them. Mo reover, the Organization

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14 for Tropical Studies (OTS), which manages the biological station w ithin the park, classifies all the surrounding marsh areas as lagoons and has no data on the soils in these areas. This is in stark contrast to the numerous studies and plethora of information available on the tropical dry forest system, also located within the park (e.g., Wetterer et al. 1998, Gillespie 1999, Gillespie and Walter 2001, Frankie et al. 2004). Palo Verde National Park The land now contained within the Palo Verd e N ational Park was on ce part of a large hacienda network owned by David Russell Stewart (a.k.a. George Wilson) and later, his sons, Donald and David Stewart Bonilla. This haci enda of nearly 30,000 ha was part of a 133,000 ha estate, which comprised approximately 13% of all of Guanacaste Province (Edelman 1992). From 1926 onwards, this land was primarily used for cattle ranching (Quesada and Stoner 2004). During the dry season, 10-15,000 cattle would ro am and graze the low-lying areas of the hacienda, resulting in the overgr azing and trampling of marsh vegetation (McCoy and Rodrguez 1994). Consequently, during the wet season, floati ng vegetation and low-growing sedges would dominate the Palo Verde wetland. This open mars h with almost no tall emergent vegetation, in combination with its slow exsiccation, became an important breeding and feeding ground for approximately 60 species of both resident and ne arctic migratory avifauna during the harsh dry season (McCoy and Rodrguez 1994, Ellison 2004). In 1975, the Costa Rican government expropriated much of the Stewart land and later donated some of it to the Costa Rican Wild life Service (McCoy and Rodrguez 1994, Quesada and Stoner 2004). On April 18, 197 7, President Daniel Oduber Quir s declared 4,800 ha of this land the Dr. Rafael Lucan Rodrguez Caballero National Wildlife Refuge, the first national wildlife refuge in Latin America, and the Stewart family removed the last of the cattle from the former Palo Verde hacienda in 1979 (McCoy and Rodrguez 1994, Quesada and Stoner 2004).

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15 In June of 1980, President Rodrigo Carazo Odio declared that nearly 10,000 ha adjacent to the Refuge would become Palo Verde National Park, put into executive order on July 2, 1981 (Evans 1999, Quesada and Stoner 2004). By Nove mber 1990, the park was expanded to include the Refuge and the neighboring Lomas Barbudal Bi ological Reserve, resulting in approximately 20,000 ha of land contained and protected within the park boundaries (Quesada and Stoner 2004). Palo Verde National Park, and other surrounding wetland areas, became recognized as wetlands of international importance under the Ra msar Convention in 1991 (Quirs et al. 2001). After the Refuge and National Park were design ated, a dramatic change in the vegetative community structure within the 6,000-ha Palo Verde wetland was observed. What had once been an open marsh, dominated by floating vegetation and almost no tall emergent vegetation, became the largest cattail ( Typha domingensis ) marsh in the region within a few years (McCoy and Rodrguez 1994). The thousands of birds that once graced the waters and skies of Palo Verde became displaced as Typha filled the marsh. The rapid changes in this well-known wetland were cause for alarm within the scientific and conservation communities. The hypothesis that occurred to many people, including renowned ornithologist F.G. Stiles, was that the cattle had been instrumental in sustaining the desired open water characteristics of the Palo Verde marsh (Hartshorn 1983). The idea of this connection between the presen ce of the cattle and the state of the marsh quickly became accepted into the local scientif ic, conservation and ranching communities; after all, the correlation seemed obvious. As a re sult, in 1986, the Costa Rican Wildlife Service signed a five-year contract with a private cattle rancher that allowed them to graze up to 1,000 cattle in the Palo Verde Lagoon (McCoy and Rodrguez 1994, Quesada and Stoner 2004). Although the reintroduction of cattle into the area wetlands did not curtail the Typha-domination,

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16 this idea attracted continued support because of the notion that such means would provide environmentally sustainable and steady income fo r local people (Quesada and Stoner 2004). In 1991, a group of private ranchers was given perm ission to graze cattle within the park and released approximately 4,000 more cattle into the area; the contract was renewed in 1998 and persists to this day (Quesada and Stoner 2004). Typha as Invasive Species Species of the genus Typha are found all over the world in freshwater m arshes, from Europe to the Everglades to Australia. Although in most cases specific species are native to a certain region, they are often considered invasive because their ability to rapidly colonize large areas and overtake other native plant habitat (Grace and Wetzel 1982). The genus is generally very resilient, some species being able to withstand extreme flooding (~2 m) and drought (~2 cm) for up to two months (Grace 1989, Fickbohm and Zhu 2006) and tolerating increased soil salinities (Miklovic and Galatowitsch 2005). Typha have also been documented to thrive under conditions of eutrophication and those otherwise into lerable to most plant species, such as acid seeps in coal mine drainage areas (Mitsch and Gosselink 2007). Nutrient availability, specif ically that of nitrogen, phos phorous and potassium, typically controls plant growth in wetland ecosystems. When one or any co mbination of these nutrients is increased, a positive response in plant growth, for many species, will be observed (Shardendu and Ambasht 1991, Verhoeven and Schmitz 1991, Sarmiento et al. 2006). Typha, however, exhibits exceptionally increased plant growth in response to nutr ification (Newman et al. 1996). Typha are also allelopathic plants, meaning they produce phytotoxins that inhibit the germination of seedlings (McNaughton 1968, Gall ardo et al. 1998), which serves as yet another enhancement of the species aggressive properties.

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17 An individual cattail head can produce up to 250,000 seeds (Sojda and Solberg 1993), which have the capability to successfully germinate and establish under flooded conditions of up to 75 cm (Yeo 1964), though they are unlikely to do so outside of controlled experiments (Shay and Shay 1986). Typha can germinate surprisingly well in the presence of NaCl and Na2SO4 (Choudhuri 1968); Typha latifolia was observed to germinate ve ry well (63% 10.2) in NaCl solutions with an osmotic pressure of 0.50 at m (0.735 ppt; 1.10 mS/cm). However, germination rates decreased rapidly with in creased osmotic pressure, reaching only 35% 9.0 in a solution of 1.0 atm (1.470 ppt; 2.19 mS/cm) (Choudhuri 1968). Although Typha germination may be negatively affected by mildly brackish conditions (0.5-3 ppt), once a plant has successfully established it can flourish under the same, or even more extreme, conditions (Choudhuri 1968, Zedler et al. 1990, Miklovic and Galatowitsch 2005). Zedler et al. (1990) found that Typha orientalis seedlings had an increased growth rate when treated with a 5 ppt (7.46 mS/cm) sea salt so lution at 4 and 5 weeks, rather than a 0 ppt solution; plants under these bracki sh conditions also had higher su rvival rates (83%) than those treated with the 0 ppt solution (2 8%) at 28 weeks. In an expe riment that observed biomass response to varying concentrations of NaCl solution (0-1000 mg L-1) combined with species competition, dramatically increased levels of Typha angustifolia biomass were recorded at the highest levels of NaCl concen tration (Miklovic and Galatowits ch 2005). Consequently, once a Typha community is established it will be able to survive despite elevated levels of salinity, having a negative effect on species richness (Mik lovic and Galatowitsch 2005, Jin 2008). The findings of Choudhuri (1968) and Ze dler et al. (1990) formed the basis for the germination experiment hypothesis.

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18 The robust nature of the Typha species allows it to withstand and flourish under conditions that result in the death of most species. Because of this, in the event of ecological disturbance, be it fire, flooding by fresh or sa line water or eutrophication, th e dominant vegetative community may perish and provide Typha with an opportunity to establis h. Given the history of hydrologic and ecological manipulation of Palo Verde Lagoon, there is considerable certainty that it was these alterations that allowed for the easy establishment of Typha throughout the marsh. An Unproductive Restoration Based on an Unsubstantiated Hypothesis An i mportant fact, not often considered, is that until 1979 the Palo Verde Lagoon was connected to the Tempisque River by five natural canals, which employed weirs that were used to maintain flooding within the lagoon during the dry season (Quesada and Stoner 2004). Although the Tempisque carries freshwater down from the plains of Guanacaste into the Gulf of Nicoya, it is often mixed with the Gulfs saline waters due to strong tid al influence (McCoy and Rodrguez 1994). After the cessation of the ra nching operation, the weirs were removed and the canals filled in with sediment and the tr ansformation of Palo Verde Lagoon into a Typhadominated marsh began. Five years later, th e cattle-grazing restorati on method was put into place (McCoy and Rodrguez 1994, Quesada and Stoner 2004). A number of other issues are associated with the development of this restoration program. One is that the cattle were never directly obser ved to graze on the ca ttail (Quesada and Stoner 2004), but consume the more herbaceous speci es both in the wetlands and the surrounding tropical dry forest (pers. obs.). It has also been shown that m oderate grazing in tropical flooded savannas, a similar system with regard to seas onality and vegetative community structure, does not have a substantial effect on plant producti on (Sarmiento et al. 2004 ). Additionally, the restoration efforts for Palo Verde marsh were implemented without having predetermined

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19 monitoring methods in place to ascertain impacts or changes within the system (Quesada and Stoner 2004). Today, two methods of Typha control are employed within Palo Verde National Park. The first is the cattle grazing technique, which is ut ilized in all areas of the park, not just those dominated by Typha. The second technique is the use of fangeo the mechanical crushing of cattails with paddle wheels. This method is effective in delaying Typha regrowth for a few seasons, but is expensive and produces short-term results. In fact, for the past several years, the scientific director of the OTS Biological Station has had to us e the bulk of his research budget to fund the fangeada of the Palo Verde marsh (J. Z iga pers. comm.). Additionally, because there has been no rigorous or long-term research condu cted regarding this restoration method, there may be unknown effects on the desired plant co mmunity, soil characteristics and decomposition dynamics. In the case of Palo Verde National Park, th ere is no known documentation of the state of the wetland areas before its time as a cattl e ranch; there is no record as to whether Typha was absent, present or dominant in this system. Also, other than the area known as Palo Verde marsh, there is no knowledge of purposeful hydrol ogic or other system manipulation before, during or after the hacienda era, yet there are extensive Typha -dominated marshes in the southern half of the park (Catal ina sector). Given the history of the Palo Verde wetland and the nature of Typha species discussed above, the hypothesi s of cattle grazi ng having controlled cattail growth is unfounded. Moreover, in the northern part of the park, an area known as la Varillal, there is no Typha present at all. There is, however, a considerable amount of Mimosa pigra in that area, another plant that is often viewed as i nvasive and indicative of disturbanc e. It is interesting that two

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20 areas, with no real barriers between them, coul d both experience such extensive disturbance that each would be overrun by a very distinctive invasive species. With this in mind, the questions raised are: What was the historical vegetative species composition of the area wetlands? Why has cattail invaded other areas of the park (i.e., Catalina sector)? Is it even invasive? Why did it not establish throughout the entire park? Are the restoration efforts currently employed effec tive? Given that the system is no longer hydrologically altered or managed, is it ev en possible to erad icate the cattail? Summary While this study will not deal w ith all of the questions m entioned above, the two relevant questions are: Why has cattail i nvaded other areas of the park? and; why did it not establish throughout the entire park? This research was focused on beginning to answer these questions. It is hoped that these answers will help the scientific and management communities begin to understand the dynamics of this system. As great er appreciation of biogeochemical influences, outside environmental impacts and system parame ters develops, more effective and efficient restoration methods can evolve and be implemented. Chapter 2 of this thesis provides a thorough description of the st udy area, Palo Verde National Park, and detailed information on the fi eld, laboratory, experimental and statistical methods used throughout this study. Results addr essing each of the objectives of this study information on soil and water chemistry, analysis of plant community composition and outcome of the germination experiment are described in Chapter 3. The final chapter of this thesis will attempt to provide explanations of the poten tial mechanisms underlying the patterns, and exceptions, seen in the results. These interp retations will be used to assess the hypotheses proposed for this study; these conclusions will be related back to the overarching concept of restoration.

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21 CHAPTER 2 METHODS A num ber of different methods were used to collect and anal yze data for this study. Field methods included plant species surveys and the collection of soil and water samples. These samples were sent to the University of Costa Ri ca, where the majority of the chemical analysis took place. Some of aspects of the analysis, however, were conducted in the laboratory at Palo Verde. The statistical analysis of each datase t varied. For soil and water chemistry data, basic descriptive statistics, analysis of variance and t-tests were applied. Se veral regression models were used to analyze plant community and germination experiment data. Study Area This study was conducted in the seasonally fl ooded freshwater m arshes of Palo Verde National Park (10 20'N, 85 20'W). PVNP, in Guanacaste Province, Costa Rica, has its southern border at the convergence of the Temp isque and Bebedero Rivers, approximately 8 km north of where the Tempisque flows into the Gulf of Nicoya (Figure 2-1) The Tempisque River valley is characterized by sa vannah plains between the moun tainous, forest-covered Nicoya Peninsula to the west and a volcanic mountain range, la Cordillera del Guanacaste, to the east (Helwig 1969). The river itself is s ubject to strong tidal fluctuati ons, having a range of nearly 3 m between high and low tides (McCoy and R odrguez 1994); it is not known how far up the Tempisque River the saline waters of the Gulf of Nicoya travel. This region of Costa Rica has two seasons wet and dry. The wet season, usually beginning in mid-May and lasting until mid-Novemb er (Figure 2-2), is typified by clear blue skies in the morning and heavy afternoon t hunderstorms. While average annual rainfall throughout the province is upwar ds of 1700 mm, the lower Temp isque is the driest area, receiving average rainfall of only 1200 mm (Helwig 1969, McCoy and Rodrguez 1994).

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22 Temperatures average between 25 and 30 throughout the year, but can reach up to 38 during the peak of the dry season (March-April) (Helwig 1969, McCoy and Rodrguez 1994). These dramatically fluctuating environmen tal conditions are what drive the seasonal changes within the wetlands of Palo Verde Nationa l Park. Before the rains set in, apart from a few permanently flooded areas, the freshwater marshes around the park are dry, with their Vertisols exposed and cracked (McCoy and R odrguez 1994, Gallaher and Stiles 2003), much like the hyperseasonal savannas of South America (Sarmiento et al. 2006). When the wet season arrives, the marshes quickly become inundated and remain so until th e beginning of December when they gradually start to dry down. By Marc h, most of the area wetla nds no longer retain any water. Vertisols have very high clay content to depth, show ev idence of movement, for example in the form of slickensides, and are present under such conditions that allow them to crack during the dry season and swell when saturated during th e wet season (Comerma 1999). Each of these characteristics has either been previously documented or is presented here (McCoy and Rodrguez 1994, Gallaher and Stiles 2003). The area known as the Palo Verde marsh exsi ccates much more slow ly than many of the other marshes in the area and is able to support many species of migratory and resident waterbirds during the dry season when other area marshes cannot (McCoy and Rodrguez 1994, Ellison 2004). It was this unique feature that was the primary driver behind the continued and expanding protection of this area as a national park and, eventu ally, its recognition under the Ramsar Convention. Field Methods All field research was conducted between J une 10 and July 16, 2008 at eight transects throughout the park, each being 2.5 5 km apart (Figure 2-3; A ppendix A for a complete listing of study dates).

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23 Plant Species Community Composition Surveys A nested design was used in conducting the p lan t surveys. At each transect location, 4-10 plots were chosen at random, stratified in linear segments of 100 m (Appendix A for plot coordinates). The start points for each transect an d the locations for each pl ot were all chosen at random. Transects 1, 2 and 3 had 6 plots each; tran sect 4 had 10 plots; and transects 5, 6, 7 and 8 each had 4 plots. At each plot location, two 1-m2 quadrats, nested in a 20-m2 quadrat, were established. After plant surveys for these quadrats were conduct ed, two satellite plots, at a distance between 10 and 15 meters on opposite sides of each main plot were also established (Figure 2-4). BraunBlanquet cover classes (1, < 1%; 2, 1-5%; 3, 625%; 4, 26-50%; 5, 51-75%; 6, 76-100%) were used to record percent cover for each species. Soil and Water Sample Collection W ithin each of the eight transects, composite core soil samples of 100 cm3 were taken, using a soil corer, at four plot locations. For trans ects 1, 2 and 3, samples were taken at plots 1, 3, 4 and 6; within transect 4, samples were take n at plots 1, 4, 7 and 10; and for transects 5, 6, 7 and 8, samples were taken at all four plots. Soil samples from an additional area were taken (Site 9; Figure 2-3) and used for in -house laboratory analysis and th e germination experiment only. A 2 soil corer was used to obtain 5-7 cm of soil; loose organic matter was removed from the tops of the cores. Each composite consisted of 4-5 cores taken from w ithin a 2.5-m radius of the initial plot locations. Two 50-ml water sample s were taken at the same locations as the soil samples. Typha domingensis See d Collection Seeds from 20 Typha domingensis seedheads were harvested from all transect areas where Typha was present (transects 1, 2, 3 and 4).

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24 Laboratory Methods Soil Sample Analysis Prior to b eing dried, soil samples were stored in a laboratory refrigerator; each sample was oven dried at 105C until a consis tent weight was reached. After the soil samples were dried, 50-ml of each sample was hand-ground with mortar and pestle and passed through a 0.2-mm sieve. The remaining dried soil was bagged a nd stored. Using a volumetric flask, two 25-ml replicates of each sample were measured out and combined with 25-ml of distilled water in 50ml centrifuge tubes; the samples were then mixe d for one minute on a Vortex Maxi Mix II. All samples remained saturated for 24 hours before being spun in a Sorvall GLC-1 Bench Top Centrifuge. Due to the age and condition of th e centrifuge the maximu m frequency of rotation was approximately 1200 rpm, thus samples were spun for two hours at this speed. Once the samples had been centrifuged, the extracted por e water was measured for pH and conductivity using a Hanna HI9813 Grocheck Combo Meter. Before each laboratory session, the meter was calibrated for both pH and conduc tivity, using solutions with a measured pH of 7.0 and total dissolved solids of 1500 ppm, respectively. Water Sample Analysis Of the two water sam ple replicates from each plot, one was refrigerated after collection and tested within 48 hours, while the other was fro zen. Before testing, all samples were spun for 15 minutes in the Sorvall GLC-1 Bench Top Cent rifuge in order to isolate any particulate organic matter. pH and conductivity were m easured using the Hanna HI9813 Grocheck Combo Meter. Nitrate and phosphate were m easured using a Hach DR/2010 Portable Spectrophotometer. Nitrat e was analyzed following mid-range (0 to 4.5 mg/L NO3 -) protocols with NitraVer 5 Nitr ate Reagent Powder Pillows (Hach Company 2000). Reactive phosphorus (0 to 2.50 mg/L PO4 3-) was analyzed following the ascorb ic acid method using PhosVer 3

PAGE 25

25 Powder Pillows; in several case s, phosphate levels were out of range for this method and the amino acid method (0 to 30.00 mg/L PO4 3-) protocols were thus fo llowed (Hach Company 2000). University of Costa Rica Sample Analysis The unanalyzed soil and water sam ples we re sent to the Center for Agronomic Investigation at the University of Costa Rica in San Jos for analysis of nutrient content and other characteristics. Soil samples were anal yzed for the following using Modified KCl-Olsen extraction solutions: pH, acidity, Ca, Mg, K, P, Z n, Cu, Fe, Mn and S. Cl, %N and soil texture were also analyzed.1 Due to costs, soil samples were combined, resulting in two composite samples per transect rather than four. Each co mposite sample represents the soil chemical makeup of a subtransect (Figure 2-4). Water samples were analyzed for pH, NH4 +, NO3 -, Ca, Mg, K, P, Fe, Zn, Cu, Mn, Na and electrical conductivity (EC). Experimental Methods The soils previously prepared and used to m easure pH and conductivity were remixed and 15-ml of each rewetted soil sample were put in a Petri dish. While the soils were being prepared, the Typha domingensis seeds were soaked in distilled water to separate the viable seeds from the attached bristle hairs. Once the viable seeds we re separated and gently dried using paper towels, they were counted out in groups of 100. Each of the 48 soil samples we re planted with 100 of the Typha seeds and then placed in the station shade house. When necessary, equal amounts of 1 The following is a description of the procedures utilized at the Center for Agronomic Investigation (CIA) at the University of Costa Rica, tran slated from a description provided with the results report. The codes in parentheses refer to procedural sections within the CIA manual: pH procedures were conducted with water of pH 5.5 (CIASC09-01-02-P02). Acidity, Ca and Mg procedures were co nducted with a KCl 1M solution; P, K, Zn, Fe, Mn and Cu procedures were conducted with an Olsen Modified pH 8.5 solution (CIA-SC09-01-02-P04). Acidity was determined by valuation (CIA-SC09-01-02-P05); P was determined by UV-Visual Spectrophotometer (CIA-SC0901-02-P07); and all other elements were determined by Atomic Absorption Spectrophotometer (CIA-SC09-01-02P06). The values listed with each element indicate the general c ritical levels of the extracting solutions used for the respective procedures: Acidity, 0.5; Ca, 4; Mg, 1; K, 0.2; P, 10; Zn, 3; Cu, 1; Fe, 10; Mn, 5; S, 12. Please see (Silver et al. 1994) for more detail on Modified KCl-Olsen solutions.

PAGE 26

26 distilled water were put into each dish in order to maintain a reasonable level of soil moisture. Germination was observed and recorded every 48 hours over a two-week period. Statistical Methods Categorization and Exclusion of Transect 5 from Some Analysis Although the soil and water sam ples from transect 5 were used during an alysis to establish the general trends of soil and water chemistry throughout the park, the data collected from plant community surveys were not used. Because of the active restoration of the Palo Verde Lagoon (the area where transect 5 was located), the plant communities cannot be said to accurately reflect the edaphic and hydrologic conditions of the area. These restoration activities may also have unknown effects on the seed bank, but since the data collected from tr ansect 5 soil samples could not be determined as outliers, they were used in analysis of the germination experiment results. Transects were grouped into southern and northern sites for some analysis. The southern site included transects 1, 2, 3 and 4; the northern site included transects 6, 7 and 8. The divisions were based on location and gene ral plant community composition, the marshes in the southern site being dominated by Typha domingensis and those in the northern site by Mimosa pigra another species associated with disturbance and often considered to be invasive. Transect 5 would have been grouped within the southern site, but was excluded from all categorized analysis. Analysis of Soil and Water Chemistry For baseline soil and water data analysis, a number of descriptive sta tis tics were applied to all components using Microsoft Excel. In order to become familiarized with the data, frequency histograms were constructed and measures of central tendency (mean, median, mode) and dispersion (range, variance, standard deviation, coefficient of vari ation) were calculated. These

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27 calculations were applied to each transect (1-9) as well as to the site groupings (northern and southern). This suite of statis tics will elucidate biogeochemical trends on a spatial scale and may indicate environmental influences, such as impact s from agriculture, ranching or proximity to the Tempisque River and Gulf of Nicoya. Pearson co rrelation coefficients were calculated, using the R statistical package, to determine whether any linear relationships existed between variables; these results could reinforce any inferences made regarding environmental influences. To determine statistically significant di fferences between groups, ANOVAs were conducted on all variables among transects and T-te sts between the northern and southern sites. Any statistically significant differences for sp ecific variables among transects may highlight and reiterate the trends and influences revealed throu gh basic statistical analys is. As variations in soil and water chemistry throughout the park are established and corrobora ted, an understanding of the system dynamics will begin to develop. Analysis Plant Species Community Composition Linear regression analysis of species richness Species richness was calculated by counting the num ber of species found in each quadrat; averages were taken when species richness wa s needed for a different scale (i.e., by plot, subtransect or transect). These species richness values were used, in conjunction with soil and water chemistry data, to create scatter plots in Excel, which became the basis for regression equations and related coefficients of determina tion. Evaluating these data in such a manner allows for any tendencies of species richness to be revealed; that is, whether samples of high or low relative species richness are associated with high, low or mid-range concentrations of specific nutrients or other char acteristics. How much of the variation in the response data (species richness) is explained by the independent variable (soil or water chemical variable) is

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28 demonstrated through the coefficient of determination ( R2); the higher the R2 value, the more variation is explained by the independent variable. Using R, fixed-effects ANOVAs were conducted, based on multivariate linear models (lm), for several variable combinations. In orde r to minimize any issues of multicollinearity, all variables within a model equation had correlation coefficients of less than .20. Once initial regressions were run, those variables whose coefficients were not statistically significant ( p > 0.15) were removed and ANOVAs ca lculated for the new iteration of regressions. These regressions were performed because, whereas single-variable regression can reveal interesting trends, plant species are not a ffected by only one chemical com ponent. Multiple variables must be included in one instance to reflect more accurately potential reactions in nature. There are assumptions made, subs tantiated by data, associating Typha-dominated areas with low species richness. Since the results of these regressions will provide information about which chemical components ar e associated with high, low or mid-range species richness, inferences can then be made regarding thes e chemical components and the predominance of Typha in certain areas. Logistic regression analysis of the most abundant species The m ost abundant species, common to both the northern and southern sites, were ascertained by tallying each cover category for each species. The tally total was then multiplied by its cover category number (i.e., 1-6) and the results for each category added together. The species with the highest final num bers were determined to be the most abundant and were those used in further analysis. The presence or absence of each of these species within each subtransect was established; if a species was present in a quadrat, it was scored and if it was absent from a quadrat, it was scored For each subtransect, the total number of present or absent occurrences for each species was totaled.

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29 The determined presence or absence of each sp ecies and the initial variable combinations used in the multivariate linear models, binomial l ogistic regressions were preformed in R (glm, binomial logit family). Two additional variable combinations were used for logistic regression; the first, containing all the variables noted to have high R2 values in the species richness analysis, and the second, based on the resu lts of Sarmiento et al. (2006) and Caraco et al. (1989). As above, after the initial regressions were run, non -statistically si gnificant variables were removed and the models were run again. The results of these model iterations are presente d in the form of variable coefficients, their levels of significance, likelihoods and graphic output that plots act ual data and model fit. That is, on the x-axis of the graph, the actual number of occurrences for a species is plotted and on the y-axis, the model-predicted numbe r of occurrences for a species given the independent variable data is plotted. G2, the likelihood-ratio-chi-squa red statistic, is used to compare the observed (xaxis) and expected (y-axis) of the response variable to assess th e goodness of fit of the model. Analyzing the presence or absence of specific species with respect to chemical components will build upon and help evolve the interpretations of biogeochemical interactions occurring within the system. The results from these mode ls considering multiple variables for individual species will provide indications as to which elements in soil or water have the most influence on whether that species can successfu lly survive in an area. Having these specific results will allow for the definition of niche differentiation among pl ant species in this system. This kind of information can be essential in developing restor ation goals and methods, as it often shapes or limits what can be done and in what manner. Analysis of Germination Experiment As with the rest of the data gathered, the germ ination experiment data were subject to a set of descriptive statistical analysis in Excel and several regressions in R. A simple linear model,

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30 based on site, transect and conductivity, was the initial effort, using up to third order polynomials in the regression and then comparing m odel fits. A model using site and transect as nested random variables was subsequently used, also employing first and second order polynomials. These models were used to ascertai n any relationships between the area within the park the soil was collected from, the specific location it was collected from, conductivity and Typha germination.

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31 Figure 2-1. Location of Palo Ve rde National Park in Guanacaste Province, Costa Rica. Image source: University of Texas Libraries, Perry-Castaeda Library Map Collection, http://www.lib.utexas.edu/maps/americas/costa_rica.gif [Accessed October 9, 2009].

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32 Figure 2-2. Average total monthly rainfall reco rded at the Palo Verde marsh, OTS Biological Station. Data source: Organization for Tropical Studies, September 1996 October 2007.

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33 Transect 8 Transect 7 Transect 6 Transect 5 Transect 9* Transect 4 Transect 3 Transect 2 Transect 1 Figure 2-3. Palo Verde National Pa rk boundary and transect locations

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34 Figure 2-4. Transect design and la yout. Figure is not to scale.

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35 CHAPTER 3 RESULTS The results presented in this ch apter are organi zed to address the specif ic objectives of this research. Generally, results are for analysis on the transect-level (1-8) are described, followed by those on the site-level (s outhern and northern). The first sec tion describes patterns of different component groupings seen in the soil and wa ter chemistry throughout the park. The second section gives the results of th e regression models generated to analyze species richness and abundance. The final section details the outcome of the germination experiment. Soil and Water Chemistry Salinity Markers The analysis of soil and water sam ples conducte d by the University of Costa Rica showed some marked trends across both transects and s ites. Samples from transects 1, 2, 3, 4 and 5 showed substantially higher concentrations of soil Cl, soil S and water Na, all of which are salinity markers (Figure 3-1). ANOVA tests demons trated statistically significant differences amongst transects for soil Cl ( p = 0.0065) and water Na ( p = 0.0082); although soil S did not prove to have statistically significant differences among transects ( p = 0.3940), the general trend in elemental concentration was present. Thes e findings are supported by the higher electrical conductivity (EC) found in both the soil and water samples from transects 1, 2, 3, 4 and 5 (Figure 3-2). Transect 1 had the hi ghest soil conductivity of these areas (5.03 mS/cm 0.73 (1 SD)), followed by transect 5 (3.81 mS/cm 0.95); transects 6, 7 and 8 all had average soil conductivities of 0.87 mS/cm (transect 6, 0.15; 7, 0.16; 8, 0.11). Water conductivity, however, was highest at tran sect 4 (0.380 mS/cm 0.272). Some of these trends seen across transects were shown to be statistically significant between sites using Studen ts t-test, while others were not. Soil Cl ( p = 0.008) was statistically

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36 significant and soil S ( p = 0.101) slightly so, with higher levels being in the southern site (Cl, 130.16 mg kg-1 79.50; S, 87 mg L-1 61.55) rather than in the northern site (Cl, 20.85 mg kg-1 4.83; S, 44 mg L-1 12.73). The tendency was the same for both soil and water EC (soil, p = 0.001; water, p = 0.018; Appendix B for complete ANOVA an d T-statistic tables). Conversely, water Na (p = 0.980) showed no statistically significant differences between sites, presumably because of the large variance among the southern site transects (29.32 mg L-1 34.84). Cations Concentrations of cations (C a, Mg, K) in water had som e statistically significant differences among transects (Ca, p = 0.1712; Mg, p = 0.0044; K, p = 0.0006) and tended towards the same general trend seen in the salinity mark ers, with lower concentrations observed from transects 6, 7 and 8 (Figure 3-3). The measured effective cation exchange capacity (ECEC) of soil samples did not have the same tendency, howe ver. Although concentra tions of the specific cations varied significantly across transects (acidity, p = 0.1304; Ca, p = 0.0019; Mg, p = 0.0400; K, p = 0.0884), and the proportional concentrations were different amongst tr ansects, the lowest cation concentrations were at transect 1 (26.02 cmol+ L-1 6.43) and the highest at transect 8 (51.47 cmol+ L-1 1.41). The concentrations found at all other transects ranged between 31 and 38 cmol+ L-1 (Figure 3-3). Although water Ca was not statis tically significant among tran sects, it was statistically significant between the northe rn and southern sites ( p = 0.028), as was water Mg ( p = 0.072). Water K, on the other hand, was hi ghly statistically significant am ong transects, but not between sites ( p = 0.506). Overall soil ECEC ( p = 0.026) was statistically signi ficant between sites, even though the significance of individual cat ions diverged greatly (acidity, p = 0.440; Ca, p = 0.036; Mg, p = 0.534; K, p = 0.005). As with the transect averages cation concentrations in water were higher at the southern site transects (S-Ca, 14.34 mg L-1 4.30; N-Ca, 11.22 mg L-1 1.97) and

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37 higher in soil at the northern site transects (S-ECEC, 32.04 cmol+ L-1 5.77; N-ECEC, 40.65 cmol+ L-1 7.50). Nitrogen and Phosphorous Total N (TN) and P (TP) concentrations in the so il samples showed some interesting results as well. TN was highest at transect 5 (0.539 % 0.069) followed by transects 7 and 8 would have the next highest levels of TN (0.422 % 0.083 and 0.322 % 0.025, respectively; Figure 3-4). Similarly, TP concentrati on was highest at transect 6 (19 mg L-1 1.41), followed by transects 1, 4 and 5, all of which ha d average concentrations of 11.5 mg L-1 (1, 2.12; 4, 13.43; 5, 6.36; Figure 3-5). For soil samples, TP did not have statistically significant differences among transects ( p = 0.2683), while TN did ( p = 0.0018). These results are intriguing because it would be expected that the highest levels of these important nutrients would be found in the most productive areas: those dominated by Typha. For related concentrations found in water samp les, the reverse was true. Nitrate did not have statistically significant differences amongst transects ( p = 0.1691) and ammonium was slightly statistically significant ( p = 0.0779; Figure 3-4); phosphorus ( p = 0.0594) and phosphate ( p = 0.0010), on the other hand, both show statisti cally significant differences among transects (Figure 3-5). Yet, between sites, nitrate was the only component in either water or soil that was even close to statistically significant (p = 0.119). pH Individually, neither soil nor water pH show ed any obvious trend am ong transects (Figure 3-6), although water pH did prove to be statistically significant (p = 0.0507). Soil pH for all transects was circumneutral, ranging from 5.5 to 6.6, and water pH slightly more basic, ranging from 6.7 to 7.5. It is noteworthy, however, that the differences between soil and water pH are greatest at transects 6 and 7 a nd least at transects 8 and 5.

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38 The differences, or lack thereof, in pH am ong transects was reitera ted by the absence of significance between the northern an d southern sites for both soil and water pH. The differences seen in transect water and soil pH was masked in the site averages, showing slightly higher pH for both in the southern site (S: water, 7.14 0.58; soil, 6.05 0.53. N: water, 6.92 0.35; soil, 5.73 0.30.). Texture A f inal soil characteristic of interest is te xture. There were st atistically significant differences in all components of soil content (sand, p = 0.0174; silt, p = 0.0623; clay, p = 0.0209). Sand content decreased and clay content increased on the northern route from transect 1 to transect 4; for transects 6, 7 and 8, texture differences came from increases in sand content and decreases in silt content (Fi gure 3-7). Surprisingly, transect 5 had the highest level of sand content (41.9 % 3.5) and, consequently, the lo west level of clay content (34.7 % 1.8). When comparing texture between the northern and southern sites, the overall differences in soil composition become quite clear. While there is no statistically significant difference in silt content ( p = 0.245) between sites, th ere are in both sand ( p = 0.036) and clay content ( p = 0.016). Following the trends seen among transects, the sand content in the southern site was higher than that in the northern site (S, 24.02 % 8.32; N, 15.75 % 4.60), and conversely for clay content (S, 52.68 9.53; N, 63.09 3.04). Despite any diffe rences in specific soil content, all soil samples were classified by the UCR-CIA, using the American texture triangle, as either clay ( n = 14) or clay loam (n = 3). Correlations Salinity markers A num ber of interesting and st atistically significant correl ations were found between soil and water components (Appendix C for complete correlation matrix). The salinity markers

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39 discussed above (soil Cl, S and EC; water Na an d EC) generally have some kind of correlation between them. Soil Cl, S and EC are all statistica lly significantly and positively correlated with one another. Water Na and EC have a str ong, positive correlation; soil EC is positively correlated with the two as well. However, neither soil Cl nor S is well correlated with water Na; soil Cl is positively correlated with water EC, though not highly. Cations Water Ca has a positive correla tion with water Mg and K, a lthough it is not a very strong correlation, and with sand content; water Mg and K are positively and very statistically significantly correlated. Water Mg also has a strong, positive corre lation with water Na and EC; water K is s tatistically significantly and positively correlated with water and soil P. There were, however, very few correlations between the cation concentrations in soil. Soil Ca has a strong negative relationship with soil K and silt content; soil Mg and ECEC both have strong positive correlations with clay content. Nitrogen, phosphorus and pH Soil P and water PO4 3both have relatively strong, positive correlations with silt content. Soil N and Mg are statistically significan tly and negatively correlated. Water NH4 + has very strong and positive relationships with water Mn and Fe; water NO3 has a statistically significant, positive relationship with soil Mn. The salinity markers and some of the major cation in the water (Na, EC, Mg, K) have statistically signifi cant, positive relationships with water pH; soil pH has a negative correlation with both soil Mn and Fe. Plant Species Community Composition Linear Regressions of Species Richness Analysis of species richness on the subtransect, transect and site scales all showed highly statistically significan t differences between their respective areas (Table 3-1). Before beginning

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40 regression analysis, comparing species richness summary statistics with those of specific variables, visual patterns begin to emerge (Figures 3-1, 2, 3 & 8). In relation to species richness, the variables whose models had th e highest coefficients of determ ination were primarily salinity markers: soil Cl, EC and S and water Na. So il K, water Fe and water depth also had higher R2 values. The variable with the highest R2-value was soil EC (0.67357), followed by water depth (0.49409), soil Cl (0.48364), water Fe (0.4729), so il K (0.46802), water Na (0.36625) and soil S (0.32061). Most of these statistical models were based on polynomial equations; only soil K and S were exponentially-based (Figure 3-9). For so il EC, soil Cl, water Fe and water Na, there was a trend of high species richness in areas of low elemental concentration, with a gradual decrease in species richness with increase in concentration, and eventually an increase is species richness with further increase in concentration. For wate r depth, soil K and soil S, there was a decrease in species richness with an increase in the respective variables. When multiple variables were placed in a li near model, the components that seemed to have the largest effects on species richness were not centered on salinity markers. The final regression equations were Sp.Rich ~ -3.077 + 0.209 clay + -0.207 so il Cu + 0.012 soil Fe + 28.384 soil N + 0.152 water Fe + -0.021 water Na + -2.935 water NO3 + 0.692 water P + -0.050 water depth (3-1) Sp.Rich ~ -1.040 + -6.313 soil K + 11.734 soil N + -0.302 soil Cu + -0.206 sand + -0.009 soil S + 0.110 water Fe + 2.310 water pH + -0.005 water depth (3-2) Soil N had a strong positive effect on species richness, while soil K had a strong negative effect (Table 3-2). Water pH had a positive effect and soil acidity a negative effect on species richness. Although water depth, water Fe, sand c ontent and clay content were consistently statistically significant in the regression mode ls, their coefficients were quite small.

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41 Logistic Regressions of the Most Abundant Species Of the 51 plant species surveyed in the m arshes (Appendix D), the most abundant species found in both the small (1 m2) and large (20 m2) quadrats were Typha domingensis Mimosa pigra Eleocharis spp. Hymenachne amplexicaulis Nymphaea spp. Aniseia martinicensis Echinodorus paniculatus Sarcostemma clausum Croton argenteus Thalia geniculata Cyperus articulatus Oryza latifolia Paspalidium germinatum Despite these species being those generally most abundant, some of them were present only in a few subtransects. Because of this, some species did not return any successful regressions, including some of the more focal species such as M. pigra. A number of the regressions had several statistica lly significant variables, but only a few had this in addition to low residual deviance. T. domingensis Eleocharis spp., Nymphaea spp., A. martinicensis E. paniculatus, S. clausum and T. geniculata all returned statistically significant and good-fitting results for at least one model (F igure 3-10). The regressions for M. pigra, H. amplexicaulis O. latifolia and P. germinatum all had at least one model run suc cessfully, but the results were far from statistically significant. C. argenteus and C. articulatus did not have any successful regression output. The final regr ession equations for the successful models (Figure 3-10) on the presence or absence of these species were Ani.mar ~ -5.276 + -0.138 sand + 0.021 soil Fe + 36.249 soil N + -0.010 soil S + -5.596 water NO3+ 1.561 water pH + 0.390 water PO4 3(3-3)

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42 Ech.pan ~ 32.404 + -30.761 soil N + -0.847 so il P + -17.596 soil K +-0.119 soil S + 0.010 (soil P soil S) (3-4) Ele.spp ~ -8.233 + -0.062 soil Fe + -0.019 soil Mn + 0.014 water Na + 4.483 water NO3 + -0.069 water depth (3-5) Nym.spp ~ 21.318 + 34.825 soil N + -3.436 soil P + 7.718 soil K + -0.914 soil S + 0.076 (soil P soil S) (3-6) Sar.cla ~ 34.340 + -0.379 clay + -8.226 soil K + 0.219 soil P + -5.049 water EC + -0.505 water Fe + -2.041 water PO4 3+ -0.134 water depth (3-7) Tha.gen ~ 35.790 + -0.510 soil Mg + -3.18533 soil pH + -3.008 water NO3 + 0.595 water PO4 3+ -0.104 water depth (3-8) Typ.dom ~ -10.586 + 0.060 soil Cl + 5.610 soil EC + -0.048 soil C + 0.843 water Fe + -0.327 water Na + 0.124 water depth (3-9) Because of the variation in inputs and response variables, it is difficult to note any general trends. However, there were a few consistenc ies observed. As seen in the species richness regressions, soil K had a strong negative e ffect on the presence or absence of E. paniculatus and S. clausum and soil N had a strong positive effect on the presence or absence of A. martinicensis and Nymphaea spp. (Figure 3-10). While higher so il pH had a negative effect on T. geniculata presence, water pH had a positive effect on the occurrence A. martinicensis and E. paniculatus, as well as species richness. Water depth had a small negative, though ge nerally statistically significant, effect on the presence of the modeled species, except for T. domingensis which had a positive coefficient for water depth. Water nitrat e, water P and clay content all varied in their effects on the presence or absence of specific spec ies, but the coefficients were consistent in magnitude and statistical significance. Germination Experiment While m ean soil EC showed great variation among transects, average Typha seed germination did not have the same tendency (F igure 3-11). T-tests between southern and northern site conductivity and germ ination provided the same results: statistically significant

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43 differences in EC ( p < 0.001) but none in germination ( p = 0.664). Plotting the conductivity and germination data did not reveal any obvious patterns either. The simple linear model did not show any differences between the distinct polynomial regressions (2nd order, p = 0.6462; 3rd order, p = 0.9363), although all thre e models presented statistically significant coefficients for site a nd multiple transects (Table 3-3). Additionally, there was a substantial difference in the magnitude and significance of coefficients for transects from the southern versus the northern site The linear mixed-effects model showed no statistically significant results, fo r the first or the second order polynomial regressions. Inputting site and transect as random ne sted variables did not provide for any results of note either. Summary of Results Analysis of the soil and water chem istry data provided some very intriguing results, which may be explained by a number of different hypothese s. It can be concluded, however, that there are distinct differences in the soil and wate r chemistry between the southern and northern marshes. Whether these distin ct characteristics are directly or indirect ly responsible for variations in species richne ss and composition is unknown, but it can be said that there are definite connections between soil and water chemistry and plant species community composition. It is unfortunate that there were no viable results fr om the germination experiment. It could have given some insight into why Typha domingensis was able to initially establish in these marshes.

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44 Figure 3-1. Transect averages. For salinity markers, 1 SD. For soil Cl, the calculated F-statistic = 7.1 ( p = 0.0065); for soil S, F = 1.2 ( p = 0.3940); for water Na, F = 3.6 ( p = 0.0082). Unless otherwise noted, sample si zes for variables in all figures are as follows: soil components, n = 2 for all transects except transect 7, where n = 3; water components, n = 4 for transects 1, 2, 4, 5, 6 and 8, n = 5 for transect 3, and n = 6 for transect 7.

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45 Figure 3-2. Transect averages. For electrical co nductivity for soil and water, 1 SD. For soil EC, the calculated F-statistic = 100.4 ( p < 0.0001); for water EC, F = 2.9 ( p = 0.0247). For soil measurements, n = 4 for transects 1, 2 and 3, n = 3 for transect 4, n = 8 for transects 5, 6 and 8, and n = 16 for transect 7.

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46 A B Figure 3-3. Transect averages. A) For dissolv ed cations in water and B) effective cation exchange capacity in soil, 1 SD. For soil ECEC, the calculate d F-statistic = 5.8 ( p = 0.0123); for water Ca, F = 1.6 ( p = 0.1712); for water Mg, F = 4.1 ( p = 0.0044); for water K, F = 5.6 ( p = 0.0006).

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47 A B Figure 3-4. Transect averages. A) For ni trogen compounds in soil and B) in water, 1 SD. For soil TN, the calculated F-stat istic = 10.5 ( p = 0.0018); for water NO3 -, F = 1.7 ( p = 0.1691); for water NH4 +, F = 2.1 ( p = 0.0779).

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48 A B Figure 3-5. Transect averages. A) For phos phorous compounds in soil and B) in water, 1 SD. For soil TP, the calculated F-s tatistic = 1.6 ( p = 0.2683); for water P, F = 2.3 ( p = 0.0594); for water PO4 3-, F = 5.2 ( p = 0.0010). For water phosphate, n = 8 for transect 7 and n = 7 for transect 8; all othe r sample sizes are the same.

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49 Figure 3-6. Transect averages. For water and soil pH, 1 SD. For soil pH, the calculated Fstatistic = 1.4 ( p = 0.3286); for water pH, F = 2.4 ( p = 0.0507).

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50 Figure 3-7. Transect averages. For soil content a nd texture. For sand cont ent, the calculated Fstatistic = 5.1 ( p = 0.0174); for silt, F = 3.2 ( p = 0.0623); for clay, F = 4.8 ( p = 0.0209).

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51 Table 3-1. ANOVA and T-test table for species ri chness (# of species/1 m2) at multiple scales. df(b)df(w)F/T-statistic p-value Subtransect 1322629.40 <0.0001 Transect 623329.46 <0.0001 Site 238 -7.99 <0.0001

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52 Figure 3-8. Box plot of species richness (per 1 m2) by subtransect.

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53 A B C Figure 3-9. Trends in species ri chness. A) With respect to soil EC, B) water depth, C) soil Cl, D) water Fe, E) soil K, F) wa ter Na and G) soil S.

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54 D E F G Figure 3-9. Continued.

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55 Table 3-2. Linear model and ANOVA output for final regression equations for the response variable Species Richne ss. Statistically significant coefficients: ***, p < 0.005; **, p < 0.01; *, p < 0.05. CoefficientF-Statistic p-value Clay 0.2094610.18300.0051*** Soil Cu -0.206853.97450.0616* Soil Fe 0.011490.28720.5986 Soil N 28.3842117.86560.0005*** Water Fe 0.151843.70080.0703* Water Na -0.020630.66730.4247 Water NO3 -2.934776.48160.0202** Water P 0.692152.10290.1642 Water depth -0.049815.47320.0310** Sum Sq Mean Sq df Residuals 71.3373.96318 CoefficientF-Statistic p-value Soil K 27.86734.28e-05*** Soil N 5.82800.0260* Soil Cu 3.49780.0769* Sand 19.41150.0003*** Soil S 0.42650.5216 Water Fe 0.15490.6983 Water pH 6.33210.0210* Water depth 0.05830.8119 Sum Sq Mean Sq df Residuals 62.6803.29919

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56 0 2 4 6 8 # occurrences of species presence 0 1 2 3 4 5 6 # occurrences of species presence Model fit 0 2 4 6 8 Model fit 0 1 2 3 4 5 6 A B Figure 3-10. Output for logistic re gressions. A) For the presence of A. martinicensis B) E. paniculatus, C) Eleocharis spp., D) Nymphaea spp., E) S. clausum F) T. geniculata and G) T. domingensis, with accompanying model equation output. Likelihoods are log values. # Terms added sequentially, first to last. Statistically significant coefficients: ***, p < 0.001; **, p < 0.01; *, p < 0.05; p < 0.1. Coefficient P (<|Chi|)# P (<|z|) Sand -0.1377 0.008 0.0718 Soil Fe 0.0207 0.341 0.07908 Soil N 36.2490 1.485e-05 8.98e-05 *** Soil S -0.0098 7.535e-06 0.0257 Water NO3 -5.5958 5.680e-07 0.00284 ** Water pH 1.5612 0.038 0.17002 Water PO4 30.3903 0.154 0.17965 Residual deviance 3.6853 Df 6 Likelihood (HO) Likelihood (HA) G2 -80.3385 -41.2684 78.1404 Coefficient P (<|Chi|)# P (<|z|) Soil N -30.7614 0.638 0.00691 ** Soil P -0.8468 0.468 0.00867 ** Soil K -17.5957 1.760e-13 0.00381 ** Soil S -0.118996 0.024 0.00836 ** Soil P:S 0.0098 0.011 0.01248 ** Residual deviance 11.609 Df 8 Likelihood (HO) Likelihood (HA) G2 -71.5289 -38.2606 66.5365

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57 0 1 2 3 4 5 6 7 # occurrences of species presence 0 0.5 1 1.5 2 2.5 3 3.5 # occurrences of species presence (output log transformed) Model fit 0 0.5 1 1.5 2 2.5 3 3.5 Model fit 0 2 4 6 C D Figure 3-10. Continued. Coefficient P (<|Chi|)# P (<|z|) Soil Fe -0.0619 0.770 0.1784 Soil Mn -0.0194 0.570 0.0855 Water Na 0.01398 9.971e-08 0.37885 Water NO3 4.4833 1.4323-07 0.00657 ** Water depth -0.0690 0.076 0.08007 Residual deviance 4.6084 Df 8 Likelihood (HO) Likelihood (HA) G2 -62.7188 -32.9159 59.6057 Coefficient P (<|Chi|)# P (<|z|) Soil N 34.82451 0.002 0.00104 *** Soil P -3.4356 0.331 3.79e-05 *** Soil K 7.71836 5.149e-07 0.03948 Soil S -0.9136 0.246 3.01e-05 *** Soil P:S 0.07635 6.89e-12 2.99e-05 *** Residual deviance 2.6851 Df 8 Likelihood (HO) Likelihood (HA) G2 -79.3876 -37.4478 83.8795

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58 0 0.5 1 1.5 2 2.5 # occurrences of species presence (output log transformed) 0 0.5 1 1.5 2 2.5 3 # occurrences of species presence (output log transformed) Model fit 0 0.5 1 1.5 2 2.5 3 Model fit 0 0.5 1 1.5 2 2.5 E F Figure 3-10. Continued. Coefficient P (<|Chi|)# P (<|z|) Clay -0.3790 0.018 0.0017 ** Soil K -8.2265 0.011 0.0014 ** Soil P 0.2190 0.347 0.1419 Water EC -5.0493 0.143 0.0606 Water Fe -0.5048 0.515 0.0496 Water PO4 3-2.0411 1.189e-06 0.0004 *** Water depth -0.1314 0.005 0.0163 Residual deviance 13.271 Df 6 Likelihood (HO) Likelihood (HA) G2 -81.8226 -58.4409 46.7634 Coefficient P (<|Chi|)# P (<|z|) Soil Mg -0.51009 0.024 0.00556 ** Soil pH -3.1853 0.002 0.0097 ** Water NO3 -3.0081 0.687 0.0031 ** Water PO4 30.5948 3.183e-06 0.0192 Water depth -0.1038 4.995e-04 0.0099 ** Residual deviance 8.300 Df 8 Likelihood (HO) Likelihood (HA) G2 -66.3592 -42.2474 48.2237

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59 0 1 2 3 4 # occurrences of species presence (output log transformed) Model fit 0 1 2 3 4 G Figure 3-10. Continued. Coefficient P (<|Chi|)# P (<|z|) Soil Cl 0.0600 0.810 0.02623 Soil EC 5.6099 0.002 6.08e-05 *** Soil S -0.0480 4.932e-08 0.0006 *** Water Fe 0.8425 0.146 0.3042 Water Na -0.3274 7.580e-18 0.0056 ** Water depth 0.1240 0.001 0.0071 ** Residual deviance 16.708 Df 7 Likelihood (HO) Likelihood (HA) G2 -83.1777 -20.1465 126.062

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60 A B C Figure 3-11. Transect averages. A) For soil electrical conductivity and B) Typha seed germination, 1 SD, and C) scatter plot of soil EC and total germination. For soil EC, the calculated F-statistic = 67.48 ( p < 0.0001; excluding transect 5); for seed germination, F = 0.59 ( p = 0.7562; excluding transect 5). For soil measurements, n = 18 for transect 2, n = 16 for transect 7, n = 12 for transects 1 and 3, n = 11 for transect 4, n = 8 for transects 5, 6 and 8, and n = 6 for transect 9. For germination, n = 9 for transect 2, n = 6 for transects 1, 2, 3 and 7, n = 4 for transects 5, 6 and 8, and n = 3 for transect 9.

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61 Table 3-3. Model output for firs t order polynomial regression of Typha seed germination. Multiple R2 = 0.2143; adjusted R2 = 0.02944. F-statistic = 1.159 ( p = 0.3514). Coefficient p-value Site(S) -35.7390.0588* Transect(2)40.5510.0113** Transect(3)20.3170.1516 Transect(4)23.9380.0650* Transect(6)-1.2640.9316 Transect(7)-3.9890.7670 Transect(8)NANA Transect(9)-17.3290.4016 mS (1st) 104.1560.0573*

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62 CHAPTER 4 DISCUSSION Review of Results Higher levels of salinity m arkers in soil and water were found in the southern area (Figure 3-1). These transects also had higher cation concentrations in the water, but the greatest concentrations of cations in soil were observed within the norther n transects (Figure 3-3). In fact, the greatest concentration level in soil was found at transect 8, which had the lowest cation concentration in water; the lowest cation concentration in soil was found at transect 1, which had the second highest concentration level in water. Within the southern site transects, sand content decreased and clay content increased with increased distance from the river mouth. For the northern site transects, sand content increased an d silt content decreased with distances further upstream. N and P levels were high at some of the southe rn site transects, but were also surprisingly elevated for some of the northern site transects. Transects 7 and 8 had the second and third highest levels of total soil nitr ogen, respectively (Figure 3-4), and transect 6 had the highest level of total soil phosphorus (Figure 3-5). Although there were no trends or statistically significant differences between pH levels of water or soil for the transects, there were great differences between the water pH and soil pH; that is, water pH was substantially higher than soil pH at each transect (Figure 3-6). Soil Cl, S, K, EC and water Na, Fe and wate r depth explained much of the variation in species richness among subtransects using single-var iable regressions (Figure 3-9). Multivariate linear models of species richness showed that th e variables of soil N, K and water P, pH, EC and depth were both large in magnitude and statistically significant (Table 3-2).

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63 Results from the logistic regressions run on the most abundant sp ecies produced strong models for several of the species, most of them containing some form of N, P or K in the variable selection (F igure 3-10). The presence or absence of Typha, however, was best modeled using salinity markers; none of the regressions run on Typha resulted in statistically significant and magnitudinous effects for nitrogen or phosphorus compounds. The Typha domingensis germination experiment did not provide any statistically significant or noteworthy results. Although there were statistically significant differences among the specific soil porewat er conductivities for the transects, there were no differences in germination totals. A scatter plot of these data revealed no patterns or tr ends of any kind (Figure 3-11). Soil and Water Chemistry Environmental Influences Seasonal variation When looking at the soil and water chem istry of wetlands, one must always keep in mind that the numbers of interest are concentrations Concentrations change often varying with the volume of water present in the wetland. This is especially true when considering seasonal wetlands (Sarmiento et al. 2004), whose dynamic hydr ology results in conti nual changes in soil conditions and available nutrients. Although this study did not address the seasonal va riation that occurs in the area marshes, it is important to recognize these cyclic trends with regard to timing of sample collection. A study conducted in a tropical freshw ater wetland in India, with similar climatic patterns to those seen in the Palo Verde region, found that, during the months of June and July, NO3 -, PO4 3and Ca concentrations in water were very high, K very low and Mg concentrations were on the rise (Shardendu and Ambasht 1991). Sodium showed no distinct seasonal pattern. These exact

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64 trends would probably not be observed in the ma rshes of Palo Verde National Park, because of their hyperseasonality, but we would expect something quite similar. Since this study made no effort to track seas onal changes within the Palo Verde wetlands, it is impossible to know whether these trends in concentrations would be present or not. However, K concentrations found in the water ar ound Palo Verde seem to be particularly high, relative to Ca and Mg concentr ations (Figure 3-3). This is the opposite of what was found by Shardendu and Ambasht (1991). While it may be the case that K concentrations would have continued to increase over the following months, K is typically not more dominant than Mg in tropical wetlands (Shardendu and Ambasht 1991, McDowell and Asbury 1994). Beyond the flux of water due to seasonalit y, such dynamics may bring about other responses. For example, the continual wett ing and drying of soil can result in mineral accumulation (Johnson and Steingraeber 2003), which wi ll lead to higher electrical conductivity. These seasonal changes could partially explain why soil ECs are much higher at some transects than their corresponding water ECs (Figure 3-2) and do not tend to follow the same spatial pattern. Soils throughout the park were found to be slightly acidic re lative to water (Figure 3-6), which is a trend also seen in calcareous mire s (Johnson and Steingraeber 2003); these differences might be intensified by seasonal variation. Duri ng the wet season, soil su lfur will reduce to S2-; once the marshes dry out the sulfur will oxidize into SO4 2-. Increased sulfate concentrations have been shown to dramatically decr ease pH in wetlands (Mossmark et al. 2008). Since many of the marshes had been flooded for less than a month and pH can be slow to change, this may still be a reasonable explanation for the low pH levels, ev en though soil samples for this study were taken during the wet season.

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65 Geology It is not unusual to find differences in c oncentration levels w hen comparing elemental compositions of soil and water. Some of those noted within PVNP migh t be due, in part, to seasonal variation. Although it is not immediately obvious, there is a vast difference in the overall concentrations of Ca and Mg in soil and water (Figure 3-3). Throughout the park, calcium constitutes approximately 58% of the total cation concentration (Ca, Mg, K) in both soil and water; Mg, on the other hand, comprises nearly 39% of soil cation concentrations but only 20% in water. While these findings are in accord ance with the results of the study carried out in the tropical freshwater wetland in India, they mi ght be altered by rainwater runoff from the large limestone ridges that dominate the central area of the park. Presumably, such a considerable influx of calcium carbonate could skew the results of th is study, making it appe ar to reflect those of the Shardendu and Ambasht (199 1) study, even if they do not. Unexpected patterns in spatial variation of cation concentratio ns in soil might also be explained by runoff from the limestone ridges w ithin the park. The la goons of the south are large and, in some places, very far from the limes tone outcroppings that dominate the skyline. The marshes of the north, on the ot her hand, are much smaller and are much closer to the ridges. Higher cation concentrations in water within the southern mars hes could be accounted for by their proximity to the river; higher cation concen trations in soil, particularly Ca, within the northern marshes could be accounted for by th eir proximity to the limestone ridges. Differences in soil texture might also contribute to varying levels of cation concentration throughout the park. Higher clay co ntent in soil results in higher total surface area of the soil particles, allowing for the adsorp tion of more cations onto soil pa rticles (Mengel et al. 2001). Soil from transect 1 was found to have one of the lowest clay contents wi thin the park (Figure 37); this could easily explain the low concentrations of cations in this area, despite the proximity

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66 of both the Tempisque and the Gulf of Nicoya. The extremely high concentrations of cations in soil found at transect 8 could be the result of both high clay cont ent and its loca tion between two limestone ridges. Tempisque River and Gulf of Nicoya Proxim ity to the Tempisque River and the Gulf of Nicoya could explain some of the spatial patterns seen in soil concentrations of specific elements, particularly in the southern area marshes. The natural levees along the Tempisque River generally keep it s waters, the recipient of nitrogen-loaded runoff from agricultural fields to the north and the saline waters from the Gulf of Nicoya to the south (McCoy and Rodrguez 1994, Kress et al. 2002, Tabash Blanco 2007), from flowing into the Palo Verde marshes. Du ring extreme rain events or tropical storms, the river will flood and overtop the levees. There is also speculation that the Palo Verde and Nicaragua Lagoons, where the southern marshes ar e located, were previously the main channel of the Tempisque River (E. Gonzlez, pers. comm.). Elevated levels of salinity markers, such as sulfur and chloride, and phosphorus (Figures 31 and 3-5) in the southern marshes could be expl ained by the presence of relict marine deposits. Inland saline lakes and wetlands often exist due to the remnants of their former marine landscapes (Strehlow et al. 2005). High levels of P are also found in areas known to have been previously inundated by marine waters (Hein 2004, Benito et al. 2005, Kametaka et al. 2005). Although very specific conditions are required for major phosphate deposits to occur (Orris and Chernoff 2004), the concept of marine sediment ary deposits of phosphate is plausible in the setting of Palo Verde due to a presumably slow sedimentation rate, warm climate and stable basin conditions (Hein 2004, Orri s and Chernoff 2004). Given that S is often deposited with P in such situations (Nathan and Nielsen 1980, Hein 2004), this hy pothesis could explain the high levels of both P and S in the southern area of the park.

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67 Higher levels of N in the northern marshes (Figure 3-4) might be explained by occasional inundation by the nitrified waters of the Tempis que River. Relatively recent flooding of the southern marshes by the Tempisque could be the s ource of elevated concentrations of soil Cl, S and water Na as well. What is curious, however is that Cl concentrat ions were highest for transects 1 and 5, while transect 3 had the highest S concentration and the highest Na levels were found at transect 4. These disc ontinuities may be explained by more localized hydrologic and biogeochemical interactions. Potential Impacts of the Former and Current Ranching Operations Because of the dom inant presence of Typha domingensis in Palo Verde Lagoon and Catalina sector (the southern site ), it would be expected that the highest levels of nitrogen and phosphorus compounds would be found there (McC ormick et al. 1996, Newman et al. 1996, Noe et al. 2001). This, however, was not the case (Figures 3-4 and 35). As discussed previously, there is active cattle -grazing throughout the marshes of Palo Verde. Some of the shallower marsh areas are also used as pastures for the cab alleros horses; the mars h where transect 6 was located is one of these areas. Continuous deposition of nutrient-ri ch organic matter (in the form of feces) could potentially be the cause for such elevated levels of phosphorus compounds in this area. Soil P concentrations th roughout the park were generally high and could be justified under the same hypothesis: that more than 50 years of grazing cattle in the marshes of Palo Verde has dramatically altered soil chemistry through the con tinual deposition of such nutrient-rich organic matter. Plant Species Community Composition There ar e several interesting points with rega rds to the analysis of species composition throughout the park marshes, the first of which is the marked trend seen in salinity markers and species richness (Figure 3-9). Mo st of the trendlines show the opposite of what is typically

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68 observed in species richness respon se to nutrients (Pausas and Au stin 2001). Generally, species richness is low at low nutrient le vels and begins to increase when nutrient levels are increased; once a critical point is reached, species richness w ill start to decline as nutrient levels continue to rise. The contrary trend seen here may be due, in part, to the elements of focus, the concentration range and this Typha-dominated system. Moreover, even though single variable regressions can give us insight into simple patterns and tren ds observed throughout a landscape, ecosystems and biogeochemical dynamics are much more complex than one dimension is capable of capturing (Bedford et al. 1999, Pausas and Austin 2001). The Typha species numerous and vigorously productiv e properties, including resilience in the presence of salinity (Zedler et al. 1990) and th e ability to colonize rapi dly (Grace and Wetzel 1982), have been discussed previously. These factors, combined with data that show the subtransects with only one or two species ( T. domingensis dominated; Figure 3-8) have high concentrations of chloride, sulfur or sodium (F igure 3-1), support the hypot hesis that the soil and water characteristics in the different marshes do indeed influence plant species composition. These areas give Typha a competitive advantage over other species because of its robust nature. The fact that the transect area with the most Typha (transect 3) has the lo west concentration of soil P (Figure 3-5) may be a very important f actor in determining the biogeochemical dynamics of this specific system. Additionally, the successful iteration of a salinity-centric model for Typha abundance, rather than one related for P, re inforces the idea that these characteristics have, in one way or another, allowed Typha to establish and become the dominant species. The pattern seen between species richness and soil K c oncentration is easily interpreted in support of this hypothesis as well. The areas dominated by T. domingensis an emergent macrophyte, will generally be much more produc tive and have much higher biomass per unit

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69 area than the areas dominated by herbaceous or even small shrub species, such as H. amplexicaulis or M. pigra (Brinson et al. 1981). In Europ ean wetlands, higher species richness has been associated with lower levels of biomass in Kor K/ N-limited systems (Venterink et al. 2003). If higher aboveground biomass is associated with the Typha dominated areas, then the validity of the continuously decreasing trend of species ri chness with greater soil K concentrations seen in these data (Figure 3-9) is upheld. Multivariate logistic regressions performed on the presence and absence of specific species demonstrated the strong influence of nitrogen and phosphorous components (Figure 3-10). The combination of variables that yielded the most ex citing results was that in spired by the work of Sarmiento et al. (2006) and Caraco et al. (1989) In a flooded savanna in Venezuela, areas fertilized with N, P or N and P showed little to no increase in primary and biomass production; however, when a fertilizer combining N, P, K and S was used, the observed increases in production were remarkable (Sarmiento et al. 2006). A review of aquatic systems suggests that relative phosphorus release from sediment may in part be regu lated by the concentration of sulfate present (Caraco et al. 1989). The high an d frequent levels of significance for all of the terms, including the interaction between S and P, demonstrates that this is a first-generation model for understanding the biotic and abio tic reactions occurring in this system. Germination Experiment Unfortunately, the results of the germination experim ent provided no results to support the hypothesis presented here. It is in teresting to note, however, that there was equally high levels of germination throughout the park, ot her than at transect 5 (Figure 3-11). The measured soil conductivity for the samples from transect 5 was lower than that from transects 1 and 9, but higher than all the other transects. This low le vel of germination implies that there are other factors at work in that particular ma rsh. It could be that the continued fangeada does have long-

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70 term effects either on the viability of T. domingensis seeds or through the ra pid release of toxic compounds (McNaughton 1968) into the soil through the crushing process. These effects might have been easily capture d by having control samples of unplanted soil from several of the different soils. Limitation in necessary supplies in field situations is an unfortunate reality and one that is central to the lack of controls in this experiment. All available resources were used to obtain the maximum amo unt of data possible. Retrospectively, a few samples could have been foregone in order to allow for control samples. Overall Synthesis Although this study did not addr ess the cattle-grazing restoration m ethod utilized within Palo Verde National Park, evidence that contradi cts its foundations has been provided. To begin with, the removal of the weir s that connected Palo Verde Lagoon to the Tempisque River certainly had more to do with the establishment of Typha than the removal of the cattle. Secondly, cattle do not eat Typha; they prefer to consume the more herbaceous species. Finally, since there is no historical information on the pl ant community structure of these marshes before they were used as cattle grazing pastures, it is impossible to k now whether these wetlands even need restoring. Data that point to other possibl e hypotheses for the invasion of Typha domingensis have also been provided. That many areas of the marshes in both the southern and northern areas of PVNP have a dominant invasive species present ( T. domingensis or Mimosa pigra) suggests that the entire park has seen some kind of disturbance, which gave these plants an opportunity to establish, and that there are underlying reasons why Typha flourished in the south and Mimosa in the north. The most obvious reasons for this, sup ported by the data presented in this thesis, are differences in soil and water ch emistry between the two areas.

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71 The southern area of PVNP has been shown to have much higher concentrations of elements indicative of marine infl uences chloride, sulfur and sodium in the soil. Even though the soils of the northern area marshes have hi gher cation concentrations another salinity indicator these can be explaine d with higher clay content in soil and proximity to limestone outcroppings. The water of the southern area, however, has much higher cation concentrations than those found in the north. This is congruous with the hypothesis that the southern area marshes are subject to much greater marine in fluences, whether current or relict, than the northern area marshes. It is difficult to draw direct conclusions fr om some of the analysis conducted on the plant species communities. It is unlikely that variatio ns in soil and water chemistry have directly caused species richness to decline. What is more likely is that su ch conditions inhibited regrowth rates of other species af ter a disturbance event and that Typha was able to quickly establish and colonize the area ra pidly. Thus, the question remains how specific soil and water chemical characteristics influence the establishment of Typha domingensis in Palo Verde National Park. Despite this, and the lack of results from the germination experiment, it is hoped that this research will begin the process of debunking the cattle-grazing hypothe sis and restoration technique. Unfortunately, because the McCoy Rodrguez (1994) paper is one of the few published works specifically addressing the Palo Verde wetlands, its unsubstantiated hypothesis continues to receive re cognition and support, even by some of the most well-known wetlands ecologists of today. In the most recent edition of their renowned book Wetlands (4th edition), Bill Mitsch and James Gosselink (2007) state, in their section discussing Palo Verde National Park, that [c]uriously, the divers ity of birds was partially mainta ined because of cattle grazing

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72 (76). This demonstrates how powerful one publica tion can be. The results from this research will begin to counteract the pervasiveness of illogical hypotheses and ineffective restoration methods. However, continued research will be necessary to reinforce and develop these findings. Recommendations for Future Research While the research p resented in this thesis lays out the initial f undamentals necessary to understanding the biogeochemical dynamics within the marshes of Palo Verde National Park, it is not yet complete. Many other as pects with respect to the system and associated research need to be addressed. It is now known that there are considerable differences in soil and water chemistry in the different areas of the park. What needs to be undertaken next is research that begins to address why. The di stinct characteristics of the salinity markers are readily explained by the proximity of the southern area marshes to the mouth of the Tempisque River. However, it may be relevant to know to what extent the river, rather than the degree to which relic deposits, is currently influencing these characteristics. Th ere were also statistica lly significant differences found in concentrations of the major cations, nitrogen, copper and manganese in soil and water samples. Further research into system speci fic biogeochemical or hydrologic functions should be pursued in order to understand not only the orig in of these differences, but also their effects. It should be recognized that there was a lack of specificity in the chemical analysis conducted for this research. While it is important to have the baseline knowledge of elemental composition in soil and water, it is also essential that the conc entrations of different compound forms be measured. For instance, there were no statistically significant differences found in soil phosphorous, an element that is known to have a large influence on pl ant growth and plant community structure. But it was total phosphorous that was measured in soil samples, rather

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73 than bioavailabile phosphorous, which is what ac tually influences plan t productivity (Grunwald et al. 2006). Other components integral to system dynamics and function that are not addressed in this thesis are the use of historical data, such as flooding and fire hist ory, and overall hydrology (Sarmiento and Pinillos 2001). This is primarily because this information is inexistent. There are data, however, that could be used to create pseudo-historical data. Water level data for the Palo Verde marsh are available for the past several years; these could be used to generate a benchmark for comparative water levels throughout the park. Unfortunately, for some years, data for the critical period of the onset of the rainy season are missing. Information regarding fire history of the park is also available; these data, however, ar e on a very coarse scale and give no details other than the dates of the fires. Th e scale of these data are very important, as was noted this summer when fire spread throughout Cata lina sector, but the ro ads functioned as large firebreaks and protected larg e areas of this sector fr om the fire (pers. obs.). Besides this research, there ar e two other, ongoing projects involving Palo Verde National Park. The first is doctoral research being conduc ted by Michael J. Oslan d, at Duke University, studying the response of plant communities to seasonal flooding, grazing and the mechanical crushing of cattails. This study wi ll be the first scientifically rigorous research conducted on the effects of the current restorati on techniques employed in the par k. The second is a fire ecology study that was carried out this summer, in co njunction with the resear ch presented here, by Steven J. Hall, of the University of Wisconsin and UCLA-Berkeley, and myself. This project was focused on studying the seedbank and re-emergent plant communities after intense fire and subsequent flooding in the Typha marshes of Catalina sector. It is hoped that the results from

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74 this and future research will be used to inform conservation policy and restoration efforts within Palo Verde National Park. Conclusions The m arshes within Palo Verde National Park have been the subject of ongoing restoration efforts for over two decades. The results have been far from desirable. The broader aim of this research was to provide objective information on the ecological conditions of these marshes, intending to demonstrate to the management and conservation agencies involved with PVNP that the restoration methods currently employed need reevaluating. This study has successfully shown that: Differences in soil and water chemistry betw een the northern and southern areas of the park are statistically significant. Specific soil and water characteristics are related to species richness and the presence or absence of specific plant species. These initial findings, combined with continue d research into the ecological history, and hydrologic and biogeochemical characteristics of th is system will provide a scientifically based foundation for management of the park and the de velopment of a long-term restoration plant.

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75 APPENDIX A METADATA Table A-1. Plot loc ations and sample collection and pr ocessing dates. P = plant; S = soil; W = water. Transect Plot Latitude (10) Longitude (85) Data Collection Sample Processing (W) Sampling Drying (S) 1 1 19.195 13.481 P, S, W 6/12/08; S 6/20/08 6/14/08 6/19/08; 7/15/08 1 2 19.075 13.490 P 6/20/08 1 3 18.993 85.488 P, S, W 6/12/08; S 6/20/08 6/14/08 6/17/08; 7/13/08 1 4 18.929 13.503 P, S, W 6/12/08; W 6/20/08 6/21/08 6/19/08 1 5 18.957 13.595 P 6/20/08 1 6 18.935 13.658 P, S, W 6/12/08 6/14/08 6/19/08 2 1 18.999 14.878 S, W 6/11/08; P, S 6/25/08 6/13/08 6/19/08; 7/9/08 2 18.952 14.964 S 6/11/08 6/19/08 2 18.943 14.987 S 6/11/08 6/17/08 2 2 18.928 15.046 P 6/25/08 2 18.902 15.103 S 6/11/08 6/17/08 2 3 18.887 15.149 S, W 6/11/08; P, S 6/25/08 6/13/08 6/17/08; 7/9/08 2 4 18.935 15.167 S, W 6/11/08; P, S 6/25/08 6/13/08 7/9/08 2 5 18.983 15.287 P 6/25/08 2 6 18.990 15.329 S, W 6/11/08; P, S 6/25/08 6/13/08 7/13/08 3 1 19.759 16.368 S, W 6/11/08; P, S 6/23/08 6/13/08 6/17/08; 7/9/08 3 2 19.749 16.449 P 6/23/08 3 3 19.754 16.478 S, W 6/11/08; P, S 6/23/08 6/13/08 6/19/08; 7/9/08 3 4 19.738 16.570 S, W 6/11/08; P, S 6/23/08 6/13/08 6/17/08; 7/9/08 3 5 19.732 16.609 P 6/23/08 3 6 19.728 16.706 S, W 6/11/08; P, S 6/23/08 6/13/08 7/13/08 4 1 19.733 18.068 P, S, W 6/14/08 6/16/08 7/13/08 4 2 19.690 18.129 P 6/14/08 4 3 19.664 18.160 P 6/14/08 4 4 19.653 18.190 P, S, W 6/14/08 6/16/08 7/13/08 4 5 19.630 18.263 P 6/14/08 4 6 19.585 18.300 P 6/13/08 4 7 19.559 18.327 P, S, W 6/13/08 6/16/08 7/9/08 4 8 19.533 18.355 P 6/13/08 4 9 19.509 18.379 P 6/13/08 4 10 19.496 18.418 P, S, W 6/13/08 6/16/08 7/13/08

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76 Table A-1. Continued. Transect Plot Latitude (10) Longitude (85) Data Collection Sample Processing (W) Sample Drying (S) 5 1 20.607 20.370 P, S, W 7/8/08 7/10/08 7/17/08 5 2 20.533 20.365 P, S, W 7/8/08 7/10/08 7/17/08 5 3 20.485 20.360 P, S, W 7/9/08 7/10/08 7/17/08 5 4 20.433 20.349 P, S, W 7/9/08 7/10/08 7/17/08 6 1 20.543 21.934 P, W 6/17/08; S 6/18/08; W 7/16/08 6/19/08; 7/20/08 7/17/08 6 2 20.571 21.884 P, W 6/17/08; S 6/18/08 6/19/08 7/17/08 6 3 20.602 21.855 P, S, W 6/18/08 6/19/08 7/17/08 6 4 20.577 21.959 P, S, W 6/18/08 6/19/08 7/17/08 7 21.836 24.141 S, W 6/10/08 6/13/08 6/19/08 7 1 21.811 24.161 P, S, W 7/16/08 7/20/08 7/18/08 7 2 21.891 24.192 P, S, W 6/26/08; W 7/16/08 6/27/08; 7/20/08 7/9/08 7 3 21.931 24.234 P, S, W 6/26/08 6/27/08 7/9/08 7 4 22.001 24.251 P, S, W 6/27/08 6/27/08 7/9/08 7 22.034 24.186 S, W 6/10/08 6/13/08 6/19/08 7 22.146 24.251 S 7/16/08 7/18/08 7 22.210 24.231 S, W 6/10/08 6/13/08 6/17/08 8 1 22.630 22.581 P, S, W 6/15/08; W 6/26/08 6/16/08; 6/27/08 7/17/08 8 2 22.650 22.629 P, S, W 6/15/08; W 6/26/08 6/16/08; 6/27/08 7/17/08 8 3 22.671 22.697 P, S, W 6/15/08 6/16/08 7/17/08 8 4 22.707 22.746 P, S, W 6/15/08; W 7/16/08 6/16/08; 7/20/08 7/17/08 Notes on Soil and Water Sample Processing Beyond the risk of the typical potential sources of error sampling, equipm ent or statistical error in this study th ere was the added risk of error due to sample processing. When storing soil and water samples, there is the poten tial that properties of chemical components will change. Any microbes within the samples themselves will con tinue do what they do best reduce nitrogen, sulfur, phosphorous, etc., perhaps transforming them into gaseous forms that are easily released from the samples when exposed to air or when dried (Carter and Gregorich 2008). While certain procedures can be used to help minimize these changes, some alterations in sample chemistry are inevitable.

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77 Length of, temperature of and moisture leve ls during storage can affect the amounts of extractable nutrients and cations from soil (Allen and Grimshaw 1962, Shuman 1980, Meyer and Arp 1994, Silver et al. 1994). The degree and type of drying, whether air-dried or oven-dried at 105C or at an intermediate temperature, will al so have an effect on microbial activity or other soil properties (Carter and Gregorich 2008). Once dried, even the method and intensity of grinding can impact the extractable levels of so me nutrients (Neary and Ba rnes 1993, Silver et al. 1994). For this study, many of these issues are no t of particular concern because the type of analysis conducted was for total elemental comp osition. Despite the damaging effects of drying soil at 105C, it was necessary under the humid c onditions to obtain the reference standard for moisture content (Carter and Gregorich 2008). The accuracy of field equipment is always in question, though they provide for very timely testing of samples. The portable spectrophotomete r used to measure nitrate and phosphate levels was calibrated regularly and used with as much pr ecision as possible. It would have been more accurate to use the low-range procedures for nitr ate measurements, but the only available reagent was that for the mid-range procedures. These measurements, however, were not used in analysis, since the University of Costa Rica anal ysis included nitrate conc entrations. Phosphate measurements were used in analysis and are in accordance with the phos phorus levels found in soil, though water phosphorous c oncentrations reported by UCR we re much lower than those observed for phosphate. This may be, in part, due to bacteria or plankton present in the water that could change phosphorus concentrations during sample storage (Worsfold et al. 2005).

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78 APPENDIX B ANOVA AND T-TABLES Table B-1. ANOVA table for soil va riables. df(b)df(w)F-ratio p-value pH 7 8 1.4 0.3286 Acidity 7 8 2.3 0.1304 Ca 7 8 10.4 0.0019** Mg 7 8 3.8 0.0400* K 7 8 2.8 0.0884 ECEC 7 8 5.8 0.0123* % AS 7 8 2.6 0.1066 EC 8 44 100.4 <0.0001*** P 7 8 1.6 0.2683 Zn 7 8 2.8 0.0847 Cu 7 8 6.9 0.0069** Fe 7 8 1.0 0.4749 Mn 7 8 8.6 0.0035** S 7 8 1.2 0.3940 Cl 7 8 7.1 0.0065** % N 7 8 10.5 0.0018** % Sand 7 8 5.1 0.0174* % Silt 7 8 3.2 0.0623 % Clay 7 8 4.8 0.0209* Table B-2. T-table for soil variables. df TOBSp-value pH 131.40.183 Acidity 130.80.440 Ca 13-2.30.036* Mg 13-0.60.534 K 133.30.005** ECEC 13-2.50.026* EC# 144.30.001*** P 13-0.30.793 Zn 130.30.784 Cu 13-1.10.290 Fe 130.030.972 Mn 13-2.90.013* S# 6 1.90.101 Cl# 6 3.90.008** % N 13-1.50.153 % Sand132.30.036* % Silt 131.20.245 % Clay 13-2.80.016*

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79 Table B-3. ANOVA table for wa ter variables. All groups have df(b) = 7, df(w) = 24. F-ratio p-value pH 2.4 0.0507 Ca 1.6 0.1712 Mg 4.1 0.0044** K 5.6 0.0006** EC 2.9 0.0247* P 2.3 0.0594 PO4 3-5.2 0.0010** NH4 +2.1 0.0779 NO3 1.7 0.1691 Fe 1.1 0.4116 Na 3.6 0.0082** Table B-4. T-table for water variables. df TOBSp-value pH 261.30.205 NH4 +,#1101 NO3 26-1.60.119 PO4 3-,#11-1.20.255 Ca 262.30.028** Mg 261.90.072* K 260.70.506 EC# 112.80.018** P# 110.40.667 Fe# 11-1.00.332 Na# 110.030.980 # Unequal population variances. ***, p < 0.001; **, p < 0.01; *, p < 0.05

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80 APPENDIX C PEARSON CORRELATI ON COE FFICIENTS Table C-1. Correlation coeffi cient table for soil and water elemental variables. Table C-1. Continued. Table C-1. Continued. ***, p < 0.01; **, p < 0.05; *, p < 0.1.

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81 APPENDIX D PLANT SPECIES LIST Plants species found while conducted survey s in PVNP, listed by life-form and function. *, m ultiple listing. See (Crow 2002) for more information on individual species. Trees, shrubs or suffrutescent Bactris guineensis Coccoloba venosa Crateva palmeri Croton argenteus Ipomoea carnea Ludwigia spp. ( L. erecta, L. octovalvis ) Mimosa pigra Pithecellobium lanceolatum Tabebuia rosea Plants free-floating on surface Azolla microphylla Eichhornia crassipes Lemna aequinoctialis Limnobium laevigatum Pistia stratiotes Salvinia spp. ( S. auriculata, S. minima ) Spirodela polyrhiza Wolffiella welwitschii Rooted plants, with leaves and/or stems floating on surface Neptunia natans Nymphaea spp. ( N. amazonum, N. prolifera, N. pulchella ) Paspalum repens Emergent plants Ammannia coccinia Canna glauca Caperonia palustris Echinodorus paniculatus Heliotropium indicum Kosteletzkya depressa Ludwigia spp. ( L. erecta L. octovalvis )* Malachra spp. ( M. alceifolia, M. radiata ) Neptunia natans Polygonum segetum Thalia geniculata

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82 Typha domingensis Vigna longifolia Family Cyperaceae o Cyperus articulatus o Cyperus spp. ( C. digitatus, C. gigantean) o Eleocharis spp. ( E. elegans, E. mutata, Eleocharis sp. (round)) o Fimbristylis spadicea Family Poaceae o Echinochloa colona o Hymenachne amplexicaulis o Leersia hexandra o Oryza latifolia o Paspalidium germinatum o Paspalum repens Facultative wetland plants and terrestria l plants with high flooding tolerance Aniseia martinicensis Cayaponia attenuata Chamaesyce thymifolia Croton argenteus* Echinochloa colona* Ipomoea piurensis Sarcostemma clausum

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83 LIST OF REFERENCES Allen, S. E. and H. M. Grim shaw. 1962. Effect of low-temperature stor age on the extractable nutrient ions in soils. Journal of the Science of Food and Agriculture 13:525-529. Aylward, B. A. and E. B. Barbier. 1992. Valu ing environmental functions in developing countries. Biodiveristy and Conservation 1:34-50. Barbier, E. B. 1994. Valuing environmental functions: Tropical wetlands. Land Economics 70:155-173. Becker, H. F. 1943. Land utilitzation in Guanacaste Province of Costa Rica. Geographical Review 33:74-85. Bedford, B. L., M. R. Walbridge, and A. Aldous. 1999. Patterns in nutrient availability and plant diversity of temperate North American wetlands. Ecology 80:2151-2169. Benito, M. I., R. de la Horra, J. F. Barrenechea, J. Lpez-Gmez, M. Rodas, J. Alonso-Azcrate, A. Arche, and J. Luque. 2005. Late Permian continental sediments in the SE Iberian Ranges, eastern Spain: Petrological a nd mineralogical characteristics and palaeoenvironmental significance. Palae ogeography Palaeoclim atology Palaeoecology 229:24-39. Brinson, M. M., A. E. Lugo, and S. Br own. 1981. Primary production, decomposition and consumer activity in freshwater wetlands. Annual Review of Ecology and Systematics 12:123-161. Caraco, N. F., J. J. Cole, and G. E. Likens. 1989. Evidence for sulphate-controlled phosphorus relase from sediments of aquatic systems. Nature 341:316-318. Carter, M. R. and E. G. Gregorich. 2008. Soil sa mpling and methods of analysis. Second edition. CRC Press, Boca Raton, FL. Choudhuri, G. N. 1968. Effect of soil salinity on germ ination and survival of some steppe plants in Washington. Ecology 49:465-471. Comerma, J. 1999. Vertisols. Pages 783-817 Soil taxonomy: A basic system of soil classification for making and in terpreting soil surveys. U.S. Department of Agriculture, Natural Resources Conservation Service, Washington, D.C. Company, H. 2000. DR/2010 Spectrophotometer Pro cedures Manual. Hach Company, Loveland, CO. Crow, G. E. 2002. Aquatic plants of Palo Verde National Park and the Tempisque River Valley. Instituto Nacional de Biodiversidad, Sa nto Domingo de Heredia, Costa Rica. Edelman, M. 1992. The logic of the latifundio: Th e large estates of northwestern Costa Rica since the late nineteenth century. Stanford University Press, Stanford, CA.

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84 Ellison, A. M. 2004. Wetlands of Central Am erica. Wetlands Ecology and Management 12:3-55. Evans, S. 1999. The green republic: A conservati on history of Costa Rica. First edition. University of Texas Press, Austin, TX. Fickbohm, S. S. and W. Zhu. 2006. Exotic purple loos estrife invasion of nativ e cattail freshwater wetlands: Effects on organic matter distribution and soil nutrient cyc ling. Applied Soil Ecology 32:123-131. Finlayson, C. M. and A. G. van der Valk. 1995. Wetland classificati on and inventory: A summary. Vegetatio 118 :185-192. Frankie, G. W., A. Mata, and S. B. Vins on. 2004. Biodiveristy conservation in Costa Rica: Learning the lessons in a seas onal dry forest. University of California Press, Berkeley. Gallaher, C. M. and C. A. Stiles. 2003. Using soils to understand ecosystem change in wetlands in Palo Verde National Park, Costa Rica. in Geologic Society of America Annual Meeting, Seattle, WA. Gallardo, M. T., B. B. Martin, and D. F. Martin. 1998. An annotated biblio graph of allelopathic properties of cattails, Typha spp. Florida Scientist 61:52-58. Gibbs, J. P. 2000. Wetland loss and biodivers ity conservation. Conservation Biology 14:314317. Gillespie, T. W. 1999. Life history characteristic s and rarity of woody plants in tropical dry forest fragments of Central America. Journal of Tropical Ecology 15:637-649. Gillespie, T. W. and H. Walter. 2001. Distribution of bird species richness at a regional scale in tropical dry forest of Central America. Journal of Biogeography 28:651-662. Grace, J. B. 1989. Effects of water depth on Typha latifolia and Typha domingensis American Journal of Botany 76:762-768. Grace, J. B. and R. G. Wetzel. 1982. Niche di fferentiation between two rhizomatous plant species: Typha latifolia and Typha angustifolia Canadian Journal of Botany 60:46-57. Grunwald, S., R. Corstanje, B. E. Weinrich, a nd K. R. Reddy. 2006. Spatial patters of labile forms of phosphorus in a subtropical wetland. Journal of Environmental Quality 35 :378389. Hartshorn, G. S. 1983. Plants: Introduction. Pages 118-183 in D. H. Janzen, editor. Costa Rican natural history. University of Chicago Press, Chicago, IL. Hein, J. R. 2004. The Permian Earth. Pages 3-18 in J. R. Hein, editor. Life cycle of the phosphoria formation: from deposition to the po st-mining environment. Elsevier Science, Amsterdam.

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85 Helwig, J. F. 1969. Problems of social and economic development in the Province of Guanacaste, Costa Rica. University of Kansas. Jin, C. H. 2008. Biodiversity dynamics of freshwat er wetland ecosystems affected by secondary salinisation and seasonal hydrology varia tion: a model-based study. Hydrobiologia 598:257-270. Johnson, J. B. and D. A. Steingraeber. 2003. Th e vegeation and ecol ogical gradients of calcareous mires in the South Park valle y, Colorado. Canadian Journal of Botany 81:201219. Kametaka, M., M. Takebe, H. Nagai, S. Zhu, and Y. Takayanagi. 2005. Sedimentary environments of the Middle Permian phosphor ite-chert complex fr om the northeastern Yangtze platform, China; the Gufeng Formation: a continental shelf radiolarian chert. Sedimentary Geology 174:197-222. Kress, N., S. L. Coto, C. L. Brenes, S. Bre nner, and G. Arroyo. 2002. Horizontal transport and seasonal distribution of nutrients, dissolve d oxygen and chlorophylla in the Gulf of Nicoya, Costa Rica: a tropical estu ary. Continental Shelf Research 22 :51-66. McCormick, P. V., P. S. Rawlik, K. Lurding, E. P. Smith, and F. H. Sklar. 1996. PeriphytonWater Quality Relationships along a Nutrient Gradient in the Northern Florida Everglades. Journal of the North American Benthological Society 15 :433-449. McCoy, M. B. and J. M. Rodrguez. 1994. Cattail ( Typha domingensis ) eradication methods in the restoration of a tropical, seas onal, freshwater marsh. Pages 469-482 in W. J. Mitsch, editor. Global Wetlands: Old Word and New. Elsevier Science. McDowell, W. H. and C. E. Asbury. 1994. Export of carbon, nitrogen, and ma jor ions from three tropical montane watersheds. Limnology and Oceanography 39 :111-125. McNaughton, S. J. 1968. Autotoxic feedback in re lation to germination and seedling growth in Typha latifolia Ecology 49:367-369. Mengel, K., E. A. Kirkby, H. Kosegarten, and T. Appel. 2001. The soil as a plant nutrient medium. Pages 15-110 Principles of Plant Nutrition. Kluwer Academic Publishers, Dordrecht, The Netherlands. Meyer, W. L. and P. A. Arp. 1994. Exchangeble cat ions and cation exchange capacity of forest soil samples: Effects of drying, storage, and horizon. Canadian Journal of Soil Science 74:421-429. Miklovic, S. and S. M. Galato witsch. 2005. Effect of NaCl and Typha angustifolia L. on marsh community establishment: A greenhouse study. Wetlands 25 :420-429. Mitsch, W. J. and J. G. Gosselink. 2007. Wetland s. Fourth edition. John Wiley & Sons, Inc., Hoboken, NJ.

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86 Mossmark, F., H. Hultberg, and L. O. Ericsson. 2008. Recovery from groundwater extraction in a small catchment area with crys talline bedrock and thin soil cover in Sweden. Science of the Total Environment 404:253-261. Nathan, Y. and H. Nielsen. 1980. Sulfur isotopes in phosphorites. Pages 73-78 in Y. K. Bentor, editor. Marine phosphorites Geochemistry, oc curence, genesis. Society of Economic Paleontologists and Mineralogi sts, Jerusalem, Israel. Neary, A. J. and S. R. Barnes. 1993. The effect of sample grinding on extractable iron and aluminum in soils. Canadian Journal of Soil Science 73:73-80. Newman, S., J. B. Grace, and J. W. Koeb el. 1996. Effects of nutrients and hydroperiod on Typha, Cladium and Eleocharis : Implications for Everglad es restoration. Ecological Applications 6:774-783. Noe, G. B., D. L. Childers, and R. D. Jones. 2001. Phosphorus Biogeochemistry and the Impact of Phosphorus Enrichment: Why Is the Everglades So Unique? Ecosystems 4:603-624. Orris, G. J. and C. B. Chernoff. 2004. Review of world sedimentary phosphate despoits and occurences. Pages 559-573 in J. R. Hein, editor. Life cy cle of the Phophoria Formation: From deposition to the post-mining envir onment. Elsevier Science, Amsterdam. Pausas, J. G. and M. P. Austin. 2001. Patterns of plant species richness in relation to different environments: An appraisal. Journal of Vegetation Science 12 :153-166. Quesada, M. and K. E. Stoner. 2004. Threats to th e conservation of tropical dry forest in Costa Rica. Pages 266-280 in G. W. Frankie, A. Mata, and S. B. Vinson, editors. Biodiversity conservation in Costa Rica: Learning the lessons in a seasonal dry fo rest. University of California Press, Berkeley, CA. Quirs, G., M. Solano M., and J. Gamboa E. 2001. Palo Verde Ramsar Information Sheet. Sarmiento, G. and M. Pinillos. 2001. Patterns and Processes in a S easonally Flooded Tropical Plain: The Apure Llanos, Venezu ela. Journal of Biogeography 28:985-996. Sarmiento, G., M. Pinillos, M. P. d. Silva, a nd D. Acevedo. 2004. Effects of Soil Water Regime and Grazing on Vegetation Diversity and Produc tion in a Hyperseasonal Savanna in the Apure Llanos, Venezuela. Journal of Tropical Ecology 20:209-220. Sarmiento, G., M. P. d. Silva, M. E. Naranjo, and M. Pinillos. 2006. Nitrogen and Phosphorus as Limiting Factors for Growth and Primary Production in a Flooded Savanna in the Venezuelan Llanos. Journal of Tropical Ecology 22:203-212. Shardendu and R. S. Ambasht. 1991. Relationship of nutrients in water with biomass and nutrient accumulation of submerged macrophytes of a tropical wetland. New Phytologist 117:493-500.

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87 Shay, J. M. and C. T. Shay. 1986. Prairie marshes in western Canada, with specific reference to the ecology of five emergent macr ophytes. Canadian Journal of Botany 64:443-454. Shuman, L. M. 1980. Effects of soil temperatur e, moisture, and air-d rying on extractable manganese, iron, copper, and zinc. Soil Science 130:336-343. Silver, W. L., F. N. Scatena, A. J. Johnson, T. G. Siccama, and M. J. Sanchez. 1994. Nutrient availability in a montane wet tropical forest: Spatial patterns and methodological considerations. Plant and Soil 164:129-145. Sojda, R. S. and K. L. Solberg. 1993. Management and control of cattails. Fish and Wildlife Leaflets 13:1-7. Strehlow, K., J. Davis, L. Sim, J. Chambers, S. Halse, D. Hamilton, P. Horwitz, A. McComb, and R. Froend. 2005. Temporal changes betw een ecological regimes in a range of primary and secondary salinised wetlands. Hydrobiologia 552 :17-31. Tabash Blanco, F. A. 2007. A biogeochemical model for the Gulf of Nicoya, Costa Rica. Revista De Biologia Tropical 55:33-42. Venterink, H. O., M. J. Wassen, A. W. M. Verkroost, and P. C. d. Ruiter. 2003. Species Richness-Productivity Patterns Differ between N-, P-, and K-Limited Wetlands. Ecology 84:2191-2199. Verhoeven, J. T. A. and M. B. Schmitz. 1991. Control of plant grow th by nitrogen and phosphorus in mesotrophic fens. Biogeochemistry 12:135-148. Wetterer, J. K., D. S. Gruner, and J. E. Lopez. 1998. Foraging and Nesting Ecology of Acromyrmex octospinosus (Hymenoptera: Formicidae) in a Costa Rican Tropical Dry Forest. The Florida Entomologist 81:61-67. Worsfold, P. J., L. J. Gimbert, U. Mankasingh, O. N. Omaka, G. Hanrahan, P. Gardolinski, P. M. Haygarth, B. L. Turner, M. J. Keith-Roach, and I. D. McKelvie. 2005. Sampling, sample treatment and quality assurance issues for the determination of phosphorus species in natural waters and soils. Talanta 66 :273-293. Yeo, R. R. 1964. Life histor y of common cattail. Weeds 12:284-288. Zedler, J. B. and S. Kercher. 2005. Wetland res ources: Status, trends, ecosystem services, and restorability. Annual Review of Environmental Resources 30 :39-74. Zedler, J. B., E. Paling, and A. McComb. 1990. Diffe rential responses to sa linity help explain the replacement of native Juncus kraussii by Typha orientalis in Western Australian salt marshes. Austral Ecology 15:57-72.

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88 BIOGRAPHICAL SKETCH Estelle Scheuerm ann Robichaux was born at St. Anne General Hospital in Matthews, Louisiana. With Bayou Lafourche located just across Highway 1, it was a very fitting beginning for Estelle. A long line of fishermen, hunters and farmers helped pave her familys way to Baton Rouge, where she grew up. As a child, she became a fledgling environmentalist keen to start an environmental rights campaign, trying to get people to recycle and attempting to go vegetarian (that one didnt really work out). Over the years, these proclivities t ook a back seat to the normal life of being a teenager; but she alwa ys enjoyed the feel of the wind and sea spray on her face, as her father raced his boat ac ross Lake Barre, surrounded by mysterious marshes and inky waters. Estelle attended Wellesley College, majo ring in economics and French, intending to become involved in international economic polic y. She abandoned these pl ans after attending a semester abroad with the School for Field Stud ies, on South Caicos, TC I, BWI. The months spent studying tropical marine ecology, resource management and environmental economics reawakened her enthusiasm for conservation, this time in the form of academic ambition. Desiring to become a well-rounded environmen tal policymaker, Estelle decided she would have to attend graduate school and focus on the natural sciences. After working for the Florida Fish & Wildlife Conservation Commissions Res earch Institute in St Petersburg, she was accepted into the Masters program of the School of Natural Resources and Environment at the University of Florida. Within a few months, fo r she had decided that she wanted to focus her research, and her career, on wetlands. Havi ng completed her Masters degree, with a concentration in wetland sciences, she will continue her studies at UF as a doctoral student in the IGERT Adaptive Management: Wise Use of Water, Wetlands & Watersheds program.