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Littoral Vegetation of Lake Tohopekaliga: Community Descriptions Prior to a Large-Scale Fisheries Habitat-Enhancement Project

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PAGE 1

LITTORAL VEGETATION OF LAKE TOHOPEKALIGA: COMMUNITY DESCRIPTIONS PRIOR TO A LARGE-SCALE FISHERIES HABITAT-ENHANCEMENT PROJECT By ZACHARIAH C. WELCH 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 2004

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Copyright 2004 by Zachariah C Welch

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iii ACKNOWLEDGMENTS I thank my coworkers and volunteers who ga ve their time, sweat, and expertise to the hours of plant collection a nd laboratory sortin g throughout this study. Special thanks go to Scott Berryman, Janell Brush, Jamie Duberstein and Ann Marie Muench for repeatedly contributing to the sampling efforts and making th e overall experience extremely enjoyable. This dream team and I have traversed and molested wetland systems from Savannah, GA, to the Everglades of south Florida, braving and enjoying whatever was offered. Their camaraderie and unparalleled work ethic will be sorely missed. My advisor, Wiley Kitchens, is directly responsible for the completion of this degree and my positive experiences over the ye ars. With a stubborn, adamant belief in my potential and capability, he provided me with the confidence I needed to face the physical and emotional challenges of graduate school. His combination of guidance and absence was the perfect medium for persona l and professional growth, giving me the freedom to make my own decisions and th e education to make the right ones. I thank my committee members, George Tanner and Phil Darby, for generously giving their expertise and time while providi ng the freedom for me to learn from my mistakes. Additionally, I thank Phil Darby fo r introducing me to the wonderful world of airboats and wetlands, and for sparking my inte rest in graduate school I thank Franklin Percival for repeatedly and reliably lending his equipment, and for continually exhibiting the professionalism and fairness every leader should possess. I thank the Florida Fish

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iv and Wildlife Conservation Commission, sp ecifically Duke Hammond and Marty Mann for going out of their way to accommodate the need s of this project, and for their patience throughout my learning process. Most importantly, I thank the people who give me the strength to tackle all of lifes challenges with unwavering love, support and gu idance: my parents, Curt and Sandy; and my wife, Christa Zweig. My pa rents are ultimately responsible for all my past and future successes, having instilled in me every good quality I possess. My wife, whom I met during this degree process, has provided th e good qualities I do not possess, and my life has been a breeze since.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iii LIST OF TABLES............................................................................................................vii LIST OF FIGURES.........................................................................................................viii ABSTRACT....................................................................................................................... ..x CHAPTER 1 INTRODUCTION........................................................................................................1 Florida Lakes................................................................................................................1 Lake Tohopekaliga.......................................................................................................7 History of Lake Tohopekaliga...............................................................................9 Restoration Efforts a nd Previous Studies............................................................11 Study Objectives.........................................................................................................14 2 SPECIES OF INTEREST...........................................................................................18 Introduction.................................................................................................................18 Exotic Species.............................................................................................................19 Nuisance Natives........................................................................................................21 Desired Aquatics.........................................................................................................22 3 TREATMENT-SELECTION STUDY.......................................................................24 Introduction.................................................................................................................24 Methods......................................................................................................................26 Study Sites...........................................................................................................26 Environmental Variables.....................................................................................30 Data Analysis.......................................................................................................31 Results........................................................................................................................ .38 Discussion...................................................................................................................55 Community Descriptions.....................................................................................57 Previous Studies..................................................................................................60 Management Implications...................................................................................62

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vi 4 WHOLE-LAKE MONITORING...............................................................................64 Introduction.................................................................................................................64 Methods......................................................................................................................65 Study Sites...........................................................................................................65 Vegetation Sampling...........................................................................................66 Data Analysis.......................................................................................................67 Results........................................................................................................................ .68 Discussion...................................................................................................................84 Community Descriptions.....................................................................................84 Previous Studies..................................................................................................87 5 SUMMARY................................................................................................................89 Communities...............................................................................................................89 Shallow Grasses and Sedges...............................................................................90 Dense Emergents.................................................................................................90 Cattails.................................................................................................................91 Floating-Leaved Communities............................................................................92 Deep-Water Communities...................................................................................92 Conclusion..................................................................................................................93 Habitat-Enhancement Schedule for 2004...................................................................94 APPENDIX A TREATMENT-STUDY SPECIES LIST...................................................................96 B WHOLE-LAKE MONITORI NG STUDY SPECIES LIST.......................................98 LIST OF REFERENCES.................................................................................................100 BIOGRAPHICAL SKETCH...........................................................................................108

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vii LIST OF TABLES Table page 3-1 Indicator values of sp ecies in the Treatment-Sele ction study, with values ranging from 0-100...................................................................................................40 3-2 Species variance in the MRT analys is of the Treatment-Selection study................56 4-1 Indicator values of sp ecies in the Lake-Monitoring study, with values ranging from 0-100................................................................................................................71 4-2 Tabulation of species variance for the MRT analysis of Lake-Monitoring sites.....83 A-1 Most abundant species sampled in the Treatment-Selection study..........................96 A-2 Less abundant species sampled in the Treatment-Selection study...........................97 B-1 Most abundant species sampled in the Whole-Lake Monitoring study...................98 B-2 Less abundant species sampled in the Whole-Lake Monitoring study....................99

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viii LIST OF FIGURES Figure page 1-1 Location of Lake Tohopekaliga and Ea st Lake Toho in relation to Lake Okeechobee and the Kissimmee River.......................................................................8 1-2 Daily mean water elevations in meters (NGVD) from January 1942 until March 2004. .......................................................................................................................1 0 1-3 The formation of floating mats and s ubsequent organic barrier, blocking the access of sport fish to important shallow water spawning areas.............................13 3-1 Locations of three replicate study sites receiving various treatments......................27 3-2 Individual study sites and their assigned treatments................................................29 3-3 Percent of cumulative Importance Va lue (IV) for each species, with 24 comprising 95% of the total.....................................................................................39 3-4 Plot of mean IV’s of the indicator species in each cluster over several depth classes…...................................................................................................................41 3-5 NMS ordination plot of sample units in species space, color coded by community..42 3-6 The same NMS plot shown in Figure 3-5 but with sample units labeled for interpretative purposes.............................................................................................43 3-7 Weighted average species scores overlayed onto NM S ordination plot..................44 3-8 Importance values of Panicum repens in the sample units plotted in the NMS ordination.................................................................................................................46 3-9 Importance values of Eleocharis spp. in the sample units plotted in the NMS ordination.................................................................................................................47 3-10 Importance values of Luziola fluitans in the sample units plotted in the NMS ordination.................................................................................................................48 3-11 Importance values of Pontederia cordata in the sample units plotted in the NMS ordination........................................................................................................49

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ix 3-12 Percentage of organic ma tter in each of the sample units plotted in the NMS ordination.................................................................................................................50 3-13 Importance values of Hydrilla verticillata in the sample units plotted in the NMS ordination........................................................................................................51 3-14 CART model of community distribu tion along the measured environmental gradients...................................................................................................................52 3-15 MRT analysis, with terminal groups of species based on IV’s and their associated environmental variables..........................................................................54 3-16 A hypothetical CART model to be creat ed following years of post-treatment data collection..........................................................................................................63 4-1 Five study site locations, each encompassing the 0–2 m depth zone.......................66 4-2 Percent of cumulative Importance Value (IV) for each species, with 20 comprising 95% of the total.....................................................................................70 4-3 Lake-Monitoring Study ordina tion plot of sample units in species space, color coded by community................................................................................................72 4-4 Weighted average species scores ov erlayed onto the Lake-Monitoring study NMS ordination........................................................................................................73 4-5 Importance values of Panicum repens in the Lake-Monitoring samples, as plotted by the NMS ordination.................................................................................74 4-6 Importance values of Luziola fluitans in the Lake-Monitoring samples, as plotted by the NMS ordination.................................................................................75 4-7 Importance values of Pontederia cordata in the Lake-Monitoring samples, as plotted by the NMS ordination.................................................................................76 4-8 Importance values of Hydrilla verticillata in the Lake-Monitoring samples, as plotted by the NMS ordination.................................................................................77 4-9 Importance values of Paspalidium geminatum in the Lake-Monitoring samples, as plotted by the NMS ordination............................................................................78 4-10 Importance values of Nuphar luteum in the Lake-Monitoring samples, as plotted by the NMS ordination.................................................................................79 4-11 CART model of Lake-Monitoring comm unity distributions along the measured environmental gradients...........................................................................................81 4-12 Communities identified in the La ke-Monitoring study by IV’s and their associated environmental variab les, using the MRT analysis..................................82

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x Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science LITTORAL VEGETATION OF LAKE TOHOPEKALIGA: COMMUNITY DESCRIPTIONS PRIOR TO A LARGE-SCALE FISHERIES HABITAT-ENHANCEMENT PROJECT By Zachariah C. Welch December 2004 Chair: Wiley Kitchens Major Department: Wildlife Ecology and Conservation An extreme dry-down and muck-remova l project was conducted at Lake Tohopekaliga, Florida, in 2003-2004, to remove dense vegetation from inshore areas and improve habitat degraded by stabilized wate r levels. Vegetation was monitored from June 2002 to December 2003, to describe th e pre-existing communities in terms of composition and distribution along the envir onmental gradients. Three study areas (Treatment-Selection Sites) were designed to te st the efficacy of different treatments in enhancing inshore habitat, and five other study areas (W hole-Lake Monitoring Sites) were designed to monitor the responses of th e emergent littoral vegetation as a whole. Five general community types were identif ied within the study areas by recording aboveground biomasses and stem densities of each species. These communities were distributed along water and soils gradients, with water depth and bulk density explaining most of the variation. The shallowest de pths were dominated by a combination of

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xi Eleocharis spp., Luziola fluitans, and Panicum repens ; while the deeper areas had communities of Nymphaea odorata and Nuphar luteum ; Typha spp.; or Paspalidium geminatum and Hydrilla verticillata Mineralized soils were common in both the shallow and deep-water communities, while the intermediate depths had high percentages of organic material in the soil. These intermed iate depths (occurring just above and just below low pool stage) were dominated by Pontederia cordata the main species targeted by the habitat enhancement project. This emergent community occurred in nearly monocultural bands around the lake (from roughly 60–120 cm in depth at high pool stage) often having more diverse floating ma ts along the deep-water edge. The organic barrier these mats create is believed to impede access of sport fish to shallow-water spawning areas, while the overa ll low diversity of the community is evidence of its competitive nature in stabilized waters. With continued monitoring of these study areas long-term effects of the restoration project can be assessed and predictive models may be created to determine the efficacy and legi timacy of such projects in the future.

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1 CHAPTER 1 INTRODUCTION Florida Lakes Historically, Florida was once much wetter than it is today, with as much as 25% of the peninsula covered with freshwater dur ing wet years (Tebeau 1971). Low elevation, flat topography, and poorly drained soils suppo rt a landscape pockmarked with swamps, lakes, and marshes, many of which were on ce connected. In fact, over 7700 lakes occur in the state of Florida; most formed from gr adual dissolving and collapsing of subsurface limestone (solution processes) or from relict sea-bottom depressions that were filled with freshwater as the oceans receded (Edmist on and Myers 1983). These lakes generally have a large area:volume rati o as a result of the forma tion processes and lack of topography in the landscape. The largest lake in the state and third larg est in the country, Lake Okeechobee, is an example of a depression la ke, with an area of 1732 km2 and an average depth of only 2.7 m. Large, shallow lakes of this nature have considerable st retches of shoreline capable of supporting vegetation, with sections of the 400 km2 of Lake Okeechobee marsh so large that the interior is hydrologi cally isolated from the lake itself. The maximum depth to which vegetation extends into the lake generally depends on light availability, but is closely related to water chemistry (S pence 1967, Heegard et al. 2001), lacustrine topography (Duarte & Kalffe 1986), fluctuations in water level and depth (Hudon et al. 2000), substrate composition (Pow er 1996), and interact ions with other flora and fauna (Leslie et al. 1983, Wilson and Keddy 1985). The vegetated portion of

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2 the lake, including either emergent or submersed communities, is loosely referred to as the littoral zone, and in many shallow lakes may include the entire water body. For the remainder of this thesis, the littoral zone is defined as the portion of shoreline that supports emergent or floating-leaved vege tation only; not includi ng the deeper-water, submersed aquatics. These areas are primar y zones of productivity, driving nutrient and oxygen cycles; preventing erosion; trapping sedi ment; and providing cover, substrate, and forage for a suite of aquatic organisms ra nging from microscopic zooplankton to large vertebrate predators. Unfortunately, these systems are vulnerable to changes in watersheds and shoreline activities, as surrounding huma n populations increase. Many of Florida’s lakes are facing problems such as degraded water qualities fr om urban and agricultural runoff, seawall construction, flood control and water-use dema nds disrupting historic al hydroperiods and stage fluctuations, substrate a lterations as a result of sedi mentation or organic material accumulation, and the introduction of hundreds of exotic species of flora and fauna competing with and displacing natives. The most recognized and prevalent of these issues is eutrophication, the degradation of habitat and water quality as a result of artificially increased nutrient levels (by means of fertilizers, stormwater, sewage effluent, etc.). The term eutrophication became more widely used in the 1940s as scientists realized that nutrients entering and accumulating in lakes as a result of industria l activities were causing changes in a matter of decades that would otherwise occur natura lly over centuries or longer (Harper 1992). A general theory of succe ssion supports the idea of la kes gradually accumulating nutrients and increasing productivity over time. This theory suggests that in early stages,

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3 lakes have few nutrients and low productivity (oligotrophic); and gradually accumulate nutrients through sedimentation and their own biological turnover, le ading to a highly productive state, eventually eliminat ing macrophytes and becoming dominated by phytoplankton (hypereutrophic) (L indeman 1942). This trend is considered a natural process of lakes evolving from a clear-water state with vegetation ad apted to low nutrient levels; to an eventual muck-filled, algaeladen lake unable to support vegetation and having turbid, high-energy water columns. Th eoretically, agricultur al and urban runoff dramatically accelerates the speed and ma gnitude of nutrient increases, causing noticeable changes within decades (rather than centuries). However, some argue that increasing the level of nutrients in a lake does not necessarily guarantee a turbid algal state, especially in shallow, warm-water lakes (Scheffer 1998). In Florida, where grow ing seasons are basically year-round, and submersed aquatics can occupy 100% of shallowlake areas, high levels of nutrients can be tied up in extremely productive macrophyt ic and epiphytic communities, reducing wind/wave actions and limiting nutrient levels in the water column. These conditions are unfavorable for the development of phytoplankt on for several reasons (Moss et al. 1996): calm waters within dense vegetation are not turbulent enough to keep phytoplankton suspended, which is necessary for substantial development; the structure of the vegetation provides cover and substrate for micro-inve rtebrates that gra ze on phytoplankton; and through macrophytic and epiphytic uptake, the am ount of nutrients in the water column is reduced. However, large-scale vegetation rem oval by natural or arti ficial disturbances may be enough to switch the lake to a turbi d, algal state. This phenomenon of highly eutrophic lakes existing as ei ther algaeor macrophyte-dominated lakes is a theory

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4 known as alternative stable st ates. Indeed, shallow eutrophi c lakes have been shown to switch from one state to another without a ny change in nutrient inputs (Blindow et al. 1993, Scheffer et al. 1993, and Mo ss et al. 1996). One example of such a switch is Lake Apopka, located in central Florida. Once renowned for its largemouth-bass fishery, Lake Apopka was almost completely covered with submersed vege tation in the 1940s (Clugston 1963) though sewage effluent and agricultural runoff had been increasing since the 1920s. In 1947, a category four hurricane moved across Flor ida, uprooting substantial amounts of vegetation and stirring sediments throughout the lake, resulting in large fish kills and unvegetated areas in the lake. By 1950, all of the submersed vegetation had disappeared and high wind events in 1951 resulted in addi tional fish kills, presumably due to oxygen depletion from highly organic se diments. Since then, Lake Apopka has been in a turbid, algal state; and all attempts at restoration, beginning as early as 1952 (US Environmental Protection Agency 1978) have failed to reestablish vegetation. This is a serious issue facing most wate r bodies in Florida, and its effects are compounded by the disruption of historical sheet flows and hydr operiods of these systems. Watershed development increases nut rient inputs and also increases demand for flood control and water supply; turning naturally dynamic lakes and wetlands into reservoirs, and meandering rivers into st reamlined channels. Many of the major hydrological changes in Florida were a result of devastating hurricanes in the 1920s and 1940s that caused large-scale losses of life and property. In the 1930s the Army Corps of Engineers responded with aggressive plan s to improve flood c ontrol and navigation, creating a vast system of levees and canals throughout central and southern Florida.

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5 Ultimately, results of this program were compartmentalization of the Everglades, impoundment and isolation of Lake Okeechobe e, and channelization of the Kissimmee River (a major inflow to Okeechobee). Lake Okeechobee was completely encircle d by levees in the 1960s, isolating it from much of its historical littoral zone (although lev ee construction early in the 20th century gradually lowered water levels, and allowed the current littoral zone to develop over the past 100 years) (Davis 1943). U pon impoundment in the 1960s, water levels were regulated to minimize flooding duri ng the wet season (May–October) and to maximize water storage for the dry season (N ovember–April), raisi ng the average lake level from 4.3–5.0 m (14.3–16.4 ft) above sea leve l (Ager and Kerce 1970). Vegetation studies in 1969 (Ager an d Kerce 1970) documented a doubling of cattail ( Typha spp.) populations in deeper water and a tripling of torpedo grass ( Panicum repens ) populations in shallower water since the late 1950s (Sincock 1957). In 1978, the water-regulation schedule was raised by 0.5 m a nd substantial decreases in the diversity of community types and willow ( Salix caroliniana ) were noted, with further increases in cattail and torpedo grass; the latter displacing dive rse, native communities of rushes ( Eleocharis spp. and Rhynchospora spp.) (Pesnell and Brown 1977, Mill eson 1987). By the early 1990s, more than 60 km2 of shallow, native marsh had been displaced by torpedo grass (Schardt 1994). A general decrease in specific diversity or structural complexity of communities after water-level stabiliza tion (Keddy 1983, Wilson and Keddy 1988, Wilcox and Meeker 1991) or eutrophication (Seddon 1972, Lachavanne 1985, Harper 1992) has been well documented. Additionally, the degree of spa tial or structural he terogeneity of plant

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6 communities affects the diversities of other organisms that are more or less vegetation dependent (Juge and Lachavanne 1997), includi ng associated microf lora (Wetzel 1975), invertebrates (Anderson and Day 1986, Giudicel li and Bournard 1996), and fish (Tonn and Magnuson 1982). Declines in fisheries were noticed after habitat degradation (Wegener and Williams 1974) and consequently, habitat restoration became a priority for agencies in charge of Florida lake manage ment. In addition to implementing pollution controls to limit nutrient i nputs, the need to more clos ely mimic natural hydrological patterns was also recognized. Although watershed development eliminated the possibility of reaching historical flood levels mimicking historical droughts was possible. Artificial dry downs were performed to c ounteract the effects of prolonged impoundment, by exposing organic substrates to oxidation a nd sparking seed germination and vegetative propagation of stressed plant populations. Wh ile successful in expanding the lakeward extent of the littoral zone, r eestablishing native flora, and c onsolidating organic substrates (Wegener and Williams 1974), the benefits of these projects seemed to diminish as the systems became further removed from their pre-impoundment state. Over time, more aggressive, competitive species became esta blished under stable-water conditions; and extremely infrequent dry downs became ineffective at reducing the abundance of these competitive species. As the benefits of dr y downs became more short-lived, efforts to prolong and increase their im pacts were developed. To expedite the natural removal processes of organic substrates and to assist the establishment of desirable species, manage rs began using bulldozers and other heavy equipment to mechanically remove muck and unwanted vegetation from shorelines during artificial dry downs. This process wa s first performed in 1987 on a large lake in

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7 central Florida, called Lake Tohopekaliga. Though many lakes have undergone such treatment since (Lake Kissimmee, Lake Istokpoga, Alligator Chain of Lakes, Lake Jackson, Orange Lake, etc.), effects of this type of disturbance are still not fully understood even in terms of the fisheries they are supposed to benefit (Allen et al. 2003). In spite of the uncertainty, this practice is commonly used, and another larger scale muck removal project was scheduled for Lake T ohopekaliga in 2004. The remainder of this paper will detail the history of the lake, th e specifics of this project and the studies designed to monitor its effects. Lake Tohopekaliga Lake Tohopekaliga (hereafter referred to as Lake Toho) is one of several large lakes located in the Upper Kissimmee River Basin, collectively draining thousands of square kilometers into the Kissimmee Ri ver and ultimately Lake Okeechobee (Figure 1-1). Lake Toho and an adjacent sister lake East Lake Toho, are the northernmost lakes in the basin, lying between th e Orlando and Mount Dora Ridges in the Osceola Plain. This plain consists mainly of poorly drai ned, clayey sediments with poor groundwater recharge, having over 73 lakes at least 3.2 ha in size (HDR Engineering 1989). Most of the lakes in this region were formed from solution activities and are precipitation driven. Lake Toho is the largest lake in the Osceo la Plain, covering an area of 8,176 ha at an average depth of 2.1 m at maximum pool (16.75 m NGVD) (HDR Engineering 1989, Remetrix LLC 2003). The immediate watershed is 340 km2, though an additional 686 km2 of East Lake Toho watershed ultimately dr ains into Lake Toho through canal C-31 (HDR Engineering 1989). N early half of these 1334 km2 are drained primarily by two main stream systems: Shingle Creek, located north of Lake Toho and flowing directly into the northwest side of the lake; and B oggy Creek, northeast of Lake Toho and flowing

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8 into East Lake Toho. Depending on precipitatio n and the operation of control structures on C-31 (drainage canal from East Lake Toho to Lake Toho) either Shingle Creek or the discharge from East Lake Toho can account for as much as 50% of the inflow to Lake Toho (Fan and Lin 1984, HDR Engineering 1989). Lake Okeechobee Orange County Osceola County Kissimmee River Florida East Lake Toho Lake Tohopekaliga N E W S 5km Lake Okeechobee Orange County Osceola County Kissimmee River Florida East Lake Toho Lake Tohopekaliga N E W S 5km 5km Figure 1-1. Location of Lake Tohopekaliga a nd East Lake Toho in relation to Lake Okeechobee and the Kissimmee River Considered a eutrophic lake, the water is slightly stained from upland tannins and relatively free of algal blooms, with visi bility ranging from 0.5.5 m. The mixed emergent littoral vegetation covers roughly 25% of the lakes area (Remetrix LLC 2003), supporting highly productive fisheries, large pop ulations of winteri ng migratory birds, significant nesting of endangered an d threatened species (Snail Kite, Rostrhamus sociabilis and Sandhill Crane, Grus canadensis ) and dozens of species of reptiles and

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9 amphibians. Like most water bodies in Flor ida, however, constant vigil and intervention is required to maintain productivity or natural habitats in the face of watershed development and exotic species introductions. Below is a brief summary of the history of Lake Toho and the challenges of balancing flood control and water storage capacities, recreational and economical benef its, and quality habitat for na tive faunal communities. History of Lake Tohopekaliga Historically, much of the watershed in the Upper Kissimmee River Basin was dominated by wetlands, with lakes bordered and interconnected by large wet prairie sloughs, including the connection of Lake T oho and East Lake Toho by Fennel and Cross Prairies (HDR Engineering 1989). This netw ork of water bodies flowed south primarily through the Kissimmee River, virt ually connecting waters of in terior central Florida to Lake Okeechobee. As early as the 1850s, pioneers began to modify the hydrology of the system and by 1884 a navigable waterway was opened from Kissimmee all the way to Fort Myers (HDR Engineering 1989). Afte r the Florida Legislature pass ed the General Drainage Act in 1913 (Chap. 298, FS), a reported 108 km (67 mi) of canals were dug throughout the Shingle and Boggy Creek Basins (Blackman 197 3). Catastrophic hurricanes in the 1940s sparked several flood control projects w ith major changes occurring in the Upper Kissimmee River Basin by 1957. Th ese projects were designed to construct levees and control structures on the south ends of th e larger lakes, to improve channels to downstream lakes, and for regul ation of upper lake levels within a 0.6–1.2 m range (HDR Engineering 1989, U.S. Army Corps of Engin eers 1956). Water control structures and canals regulating flows to and from Lake Toho were completed in 1964 (Blake 1980), marking the end of natural water level fluctuations. This resulted in a reduction in the

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10 range of stage levels from at least 3.2 m to a maximum of 1.1 m (Wegener et al. 1973). Figure 1-2 shows the sharp cont rast between the dynamic, asta tic condition of the lake prior to impoundment in 1964 and the stab ilization that has oc curred since. 14.50 15.00 15.50 16.00 16.50 17.00 17.50 18.0019501960198019902000 1970Elevation in meters (NGVD) Artificial Dry Downs Impoundment 14.50 15.00 15.50 16.00 16.50 17.00 17.50 18.0019501960198019902000 1970Elevation in meters (NGVD) Artificial Dry Downs Impoundment Figure 1-2. Daily mean water elevations in meters (NGVD) from January 1942 until March 2004. The vertical black line re presents the approximate time of impoundment in 1964 while the blue lines indicate artificial dry downs. The natural drought in 1962 was the lowe st on record at that point. Sewage treatment plants began pumping e ffluent into the Shingle and Boggy Creek basins as early as the 1940s, and by 1986 an estimated 113 million liters per day (30 million gallons) were being discharged into these systems (Wegener et al. 1973). Though water quality problems were recognized and attr ibuted to these plants in 1969, discharges were not completely eliminated until 1988. By this point nutrient lo ading and water level stabilization had noticeably affected the l ittoral habitats, water qualities, and fish populations, sparking a new er a in lake restoration by management agencies.

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11 Restoration Efforts and Previous Studies In 1969, the Florida Fish and Wildlife Conservation Commission recommended that all effluent discharges into Lake Toho be stopped and that an artificial dry down be performed in hopes of sparking seed germina tion and recolonization of desired species (Wegener 1969). The first managed drawdow n of the lake took place in 1971, lowering the water from a high pool stage of 16.75 m to 14.65 m (55–48 ft) NGVD (National Geodetic Vertical Datum). The lake was he ld there for nearly six months and drought conditions further extended the refilling to high pool stage until March of 1973. During this period the FFWCC conducted studies on fish invertebrates, vegetation, soils, algae, and water chemistry. Vegetation studies cons isted of fixed sampli ng along line transects established perpendicular to the shore, ranging from above high pool stage to the lakeward extent of emergent vegetation. Frequencies of occurrence of species were recorded based on a form of line intercept me thod using a five-pointed rake (Sincock et al. 1957). At that time the only vegetation considered a nuisance was water hyacinth ( Eichhornia crassipes ) and the overall expansion of littoral communities into the lake by 16% was hailed as a success (Wegener and Williams 1974). Another drawdown was performed in 1979 ba sed on the successes of the previous effort. Sport-fish populations increased to a maximum by 1982 and then gradually declined to the lowest leve l since 1972. Based on these da ta it was assumed the habitat had degraded substantially and would no l onger support maximum fish densities. No vegetation studies were conducted. In 1987, the discharge of effluent to the la ke was almost eliminated and another dry down was performed. Contrary to the others which were performed to increase the density and area of the littoral zone in ge neral, the purpose of this project was to

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12 eliminate dense, monocultural stands of vegetation ( Polygonum spp. and Pontederia cordata ) that had formed an organic barrier fr om accumulated organic matter; isolating many shallow areas of littoral zone to the point of blocking access of sport fish to important spawning grounds. This process o ccurs as stable, high water levels cause a buildup of gases in the root mats of sene scing vegetation and as organic debris are deposited by wind and wave actions; eventu ally causing the mat to become buoyant enough to release from the substrate and create a floating mat of organic matter and root material. Over time, wind and wave actions act to push back, break apart, or fold over the deep water edge of these mats (Kahl 1993) creating progressively thicker mats that can eventually support woody vegetation (M allison et al. 2001) (Figure 1-3). The goal of the 1987 dry down was to reestablish native grasses in place of the dense, monocultural stands of unwanted vege tation. This marked the first mechanical muck-removal project, scraping approximately 172,000 m3 of muck and vegetation from the southeastern shorelines. After just two years, however, line transect studies established in 1986 showed an almost comp lete rebound of the vegetation targeted for removal ( Pontederia cordata ), though several grass species increased in frequency as well (Moyer et al. 1989). A natural drought in 1991 gave lake manage rs another opportunity to remove some of the unwanted vegetation and two removal experiments were performed, one involving mowing the vegetation to a maximum height of 15 cm and the other, uprooting and removing it. It was found that Pontederia rebounded in both treatments, though at a slower rate after uprooting. Herbicide applications we re also made in hopes of minimizing the regrowth of Pontederia but were only effectiv e at slowing regrowth.

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13 Figure 1-3. The formation of floating mats a nd subsequent organic barrier, blocking the access of sport fish to important, sha llow water spawning areas. The process occurs as follows: A) Stabilized wa ter levels begin to drown emergent vegetation at the deeper end of its de pth tolerance, causing senescence and a buildup of gases in the root mat B) Gas buildup reaches a point that causes floatation, pulling the root mat from the organic layer beneath it C) Wave actions fold over the thinner, lead ing edges of the floating root mat D) Prolonged folding and the presence of the floating edge act to build organic material under and within the r oot mat, forming a thicker, drier mat E) Eventually the mat supports wood ier and shorter hydroperiod vegetation, forming an organic barrier that limits access of sport fish to shallow water spawning areas. All line drawings of plan ts used in these figures were copied with permission from Aquatic Plants in Pen and Ink (IFAS Pub. No. SP233).

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14 Figure 1-3. Continued In 2004, the largest and most comprehensiv e muck removal project to date was implemented on Lake Toho. Upon dropping la ke levels roughly 2 m below high pool stage, nearly 7,000,000 m3 of muck and vegetation were removed from over 80% of the shoreline. The remainder of this paper will focus on the studies designed to monitor the effects of this project. Study Objectives Sampling methods implemented in earlier st udies have focused on the frequency of species occurrence along water depth gradients, comparing preand pos t-restoration data. These methods reveal inundation tolerances of individual species and are effective in

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15 monitoring shifts in their locations along th e measured gradient. However, they are primarily exploratory methods, not generally used to test hypot heses or to make inference to any area other than that occupied by the line transect. In this re spect, previous studies have not quantitatively measured the response of vegetation to rest oration efforts, nor have they attempted to monitor the response of the littoral communities as a whole (rather than on an individual species basis). Ke rshaw and Looney (1985) stated that to understand vegetative dynamics of a system species composition, distribution, and the relative degree of abundance of each must be described. Differences in structural and specific diversities can have profound effect s on organisms relying on that habitat for food, cover, or substrate (Wetzel 1975, Gi udicelli and Bournaud 1996), on rate of nutrient uptake or immobili zation (Mitsch and Gosselink 1993, Sorrell et al. 1997, Van der Nat and Middelburg 1998), on quality and qu antity of detritus, rate of organic accumulation in the soil (Wilson and Keddy 1988), erosion control, wave energies, and so on. To fully comprehend treatment effects applied to the littora l communities of Lake Toho, quantitative measurements of successional responses are critic al. Densities and biomasses are more stringent measures of the spatial and architectural complexity of the habitats targeted for restorat ion than frequency of occurren ce, as recorded in previous studies. Defining the pre-existing communities and monitoring their response at a multi-species level will provide insight to th e effects and efficacy of these restoration efforts. The ultimate goal of this project is theref ore to establish long-term monitoring sites and protocols to address th e following questions: At a community level, what are the e ffects of different habitat restoration techniques in terms of vegetation successi on? Essentially, are both muck removal

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16 and herbicide application nece ssary to establish historical grassy habitats or are either of them effective by themselves? On a lake-wide scale, how will the littoral vegetative communities respond to this restoration project? These questions were addressed with the designation of two separate study areas; the first hereafter referred to as the Tr eatment-Selection study a nd the second called the Whole-Lake Monitoring study. Long-term effect s of these treatments will not be known until years of post-treatment data have been collected and analyzed. Chapters 3 and 4 will detail the design, establishment and m onitoring protocols of these study areas, respectively, that are essential to estimating those effects. However, as no restoration efforts had yet been performed during the peri od of this study, the bul k of these chapters and the majority of this paper will focus on the description of the lake’s littoral communities before the treatment was applied. These questions are addressed for each study area: What vegetative communities were present before the project and how were they distributed? What were the underlying gradients associated with those compositions and distributions? Based on this pre-treatment information, what inferences can be made about the littoral communities within the lake? Brief discussions of the findings in each study area are included at the end of Chapters 3 and 4 with comparisons to severa l previous studies, and Chapter 5 includes a summated, cumulative discussion of the communities identified in these chapters. Before presenting these results, basic descriptions of several of the important species encountered on Lake Toho are provided in Chapter 2. Most of these species will be

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17 continually referred to in the following ch apters and an understa nding of their growth forms, life histories and physical char acteristics will aid interpretation.

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18 CHAPTER 2 SPECIES OF INTEREST Introduction Habitat management of any type, aquatic or terrestrial, ultimately leads to the classification of frequently en countered species as native, na tural, desirable or invasive, exotic, nuisance, aggressive, and so on. Typically, managers ha ve a target habitat consisting of a suite of desirable native speci es, usually an approximation of the historic or natural habitat, and are faced with the elimination or cons tant invasion of species that are considered disruptive to th at habitat. In Florida, nonnative or exotic species are assigned labels according to their potential to spread, invade, or otherwise dominate, alter, and disrupt natural habita ts. A list of these aggressive, invasive exotics is posted by the Florida Exotic Pest Plan t Council (www.fleppc.org). The most well known exotics in Florida include water hyacinth ( Eichhornia crassipes ) and hydrilla ( Hydrilla verticillata ). Both of these plants have the remarkable ability to completely dominate water bodies, displacing practically every other species if left unmanaged. Hundreds of millions of dollars have been spent in attempts to control the spread and abundance of these two species alone since their introductions. At present there are at least 35 exotic species in Fl orida’s aquatic systems and over $70 million a year is spent in fighting th eir spread or abundance. In attempting to restore a system to some hi storical state, eliminating exotic species is only a small part of the process. The bigge st challenge usually lies with identifying the causal mechanisms that altered the system to begin with. Changes in water qualities,

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19 nutrient levels, depth and duration of fl ooding, etc. have major impacts on species compositions and distributions, resulting in undesirable changes in native vegetation as well. One of the best cases of such hab itat alterations and vege tation response is the expansion of cattail ( Typha spp.) into the Everglades Water Conservation Areas as a result of high phosphorous levels in r eceiving waters (SFWMD 1992, Davis 1994). The historically oligotrophic Ever glades and the vegetation adap ted to those conditions are unable to compete with species like cattail at higher nutrient levels, and alterations to natural hydroperiods, sheet flow, and fire frequencies compound these effects. The problems facing many of Florida’s lakes are quite similar. As a result of decreased flood stages, water level stabilization, and increased nutrient inputs, exotics and several native sp ecies have become problematic to lake managers in the restoration of historical hab itat. Listed below is a brief description of important species on Lake Toho, including inva sive exotics, nuisance natives, and the desired species that comprise the target habitat of the lake restoration project. Exotic Species Hydrilla ( Hydrilla verticillata ): experts argue whether hydri lla or water hyacinth is the most invasive and disruptive exotic plan t in Florida. Hydrilla is a submersed aquatic brought to the US fr om Asia through Florida as an aquarium plant, most likely in the 1950s, through Miami or Tampa Bay ports. It was first discovered in the 1960s in Miami and Crystal River (B lackburn et al. 1969 ) and by the 1970s occurred in all major water bodies in all drainage basins. It out competes most native submersed species with rapid grow th of up to 2.5 cm per day (Langeland 1996) and extensive branching at the water surface, up to one ha lf of its standing crop occurring in the top 0.5 m of water (Halle r and Sutton 1975). An exceptional tolerance to low light conditions allows its establishment in depths beyond most other submersed species, and as such can be found in up to 15 m in depth in springfed Crystal River and regularly occurring at 3 m in most lakes (Langeland 1996). Vegetative and asexual reproduction are most common, forming new plants from any whorl of leaves broken off or from turi ons produced on tubers and in leaf axils. Subterranean turions can remain viable afte r several days out of water and for up to 4 years in undisturbed sediments (Van and Steward 1990), surviving herbicide applications and ingestion by waterfowl. This makes the plant easy to spread

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20 between water bodies on boats and boat trai lers, fishing lures and bird legs. After 30 years of herbicide applicati ons, more resistant strains of Hydrilla are much more common. Non-target, native speci es that used to be unaffected by the low levels of herbicides used to kill Hydrilla, are no w being affected by the need for higher concentrations. Without constant herbic ide application and mechanical removal by management agencies statewide, Hydrilla would quickly fill most water bodies in Florida from substrate to water surface. Thus far, no methods have been effective at killing the roots of the plant, with rapid regrowth occurring from tubers immediately following decreased herbicide c oncentrations in the water column. A leaf-mining fly ( Hydrellia pakistanae ) has been established in Florida as a biological control, but its efficacy is as of yet unknown (Buckingham et al. 1989). Water hyacinth ( Eichhornia crassipes ): arguably the most invasive and disruptive exotic plant in Florida. A free floating plant, it is att ached to mother and daughter plants by floating stolons, creating dense ma ts of vegetation capa ble of completely covering most water bodies. It was introdu ced to the United Stat es in 1884 at an exposition in New Orleans and reached Florida in 1890 (Gopal and Sharma 1981). By the late 1950s it occupied about 51,000 ha of Florida’s waterways (Schmitz et al. 1993). Its growth rates exceed any other tested vascular plant (Wolverton and McDonald 1979), doubling its populations in as little as 6-18 da ys (Mitchell 1976). Large mats degrade water quality by depleting oxygen le vels, shading out submersed species, rapidly producing orga nic matter, crowding out and crushing emergent species and blocking access to th e air-water interface essential to many aquatic organisms (Gowanloch 1944, Penfound and Earle 1948). After 100 years of effort, populations are finally under control through constant maintenance and herbicide applications. Torpedo grass ( Panicum repens ): A very competitive grass with stems to 1 m tall, growing from sharp-tipped (t orpedo like) floating or creepi ng rhizomes. It was first collected in the US in Alabama in 1876 (B eal 1896) and introduced to Florida for cattle forage in 1926 (Tarver 1979). By 1992 it was established in over 70% of Florida’s public waters, displacing 6000 ha of native marsh in Lake Okeechobee (Schardt 1994). It will gr ow in upland areas but thri ves in wet, sandy soils, stimulated by tilling and fertilization (Hodges and Jones 1950), rapidly colonizing disturbed shorelines by rhizome extensi on and fragmentation (Holm et al. 1977). Para grass ( Brachiaria mutica also Urochloa mutica ): A rapidly growing grass with stems from 1–4 m long, with floati ng stems up to 6 m long (Handley and Eckern 1981). The lengthy and extremely dense stems fall over and lay on top of one another, creating horizontal mats up to 1 m thick (Holm et al. 1977). It aggressively competes with other plan ts by high productivity and allelopathic qualities that enable the formation of dense monocultural stands (Chang-Hung 1977, Handley et al. 1989). It was most likel y introduced to Florida as early as the late 1870s (Austin 1978) and was reco mmended for pasturage here in 1919 (Thompson 1919). This grass occurred in up to 52% of Florida’s public water bodies in 1986 but decreased to 46% by 1994 (Schardt 1997). Grazing remains a highly effective method of control.

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21 Water lettuce ( Pistia stratiotes ) : Experts argue whether th is plant is native or exotic but is included in this list due to its potentially invasive and highly competitive nature. Like water hyacinth, it is a free floating plant connected by short stolons to mother and daughter plants William Bartram first reported it in 1756, describing it as blocking waterways a nd preventing boat access. While the effects of dense floating mats are th e same as hyacinth, including shading submersed species, decreasing oxygen leve ls and crowding out emergents, its slower growth rate has kept it from b ecoming as big a problem. Through regular removal and herbicide applications, and w ith several biological insect controls successfully established, water lettuce populations remain under control. Alligator weed ( Alternanthera philoxeroides ): – An emergent perennial with hollow stems able to form large, dense mats, occasionally floating. This species was problematic when its populations reached a high in the 1960s before the first biological insect control ( Agasicles hygrophila ) for an exotic plant was released. With unprecedented success, by the 1980s its populations were severely limited and no longer posed a threat. Though still very frequent in Florida lakes and water bodies, insect damage can easily be seen on most plants, constantly keeping its populations in check. Nuisance Natives While each of the species listed below may be desirable in many situations and certainly have high value to wildlife under many circumstance s, their potential to form dense, monocultural stands or floating ma ts and to produce massive amounts of organic litter often leads to their cl assification as a nuisance. Typically, dense vegetation and high amounts of organic matter are considered to impede sport-fish reproduction, block recreational access and eventual ly create the same problems in terms of diversity and habitat as the aforementioned invasive exotics. For these reasons the native species listed below are frequently sprayed with herbicides to keep their abundance and distribution under control. Pickerel weed ( Pontederia cordata ): A stout, broadleaf, emergent plant with stems up to 1 m in height. Large, highly ae renchymous rhizomes form dense mats, capable of lifting off the substrate and b ecoming buoyant with rising water levels. Provides good habitat for macroinvertebrates, reptiles, amphibians and small fish when not floating, and nesting substrat e for several bird s (common moorhen, Gallinula chloropus ; purple gallinule, Porphyrula martinica ; sandhill crane, Grus canadensis ) when floating. Pickerelweed is highly productive, out-competes many

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22 species in stable environments and contri butes large amounts of organic material to the substrate, capable of forming nearly monocultural stands around shorelines of lakes. Smartweed ( Polygonum spp.): Another broadleaf emergent plant, with stems up to 1.5 m in length. In deeper water, P. densiflorum forms floating mats with long horizontal stems. It is highly competitive, especially in shallow, disturbed shorelines and is usually among the first to colonize such areas. Capable of forming dense, monocultural stands, producing large amounts of litter. Cattails ( Typha spp.): A tall, robust, emergent sp ecies, growing to over 3 m in height and covering large ar eas of wetlands, lakes and rivers. One of the most common aquatic and wetland pl ants anywhere in the world, capable of forming monocultural stands of only one or two individuals due to prolific rhizominous reproduction. Occasionally, floating mats may form in large colonies if high water levels persist. Each seed head contai ns tens of thousands of wind and water dispersed seeds, rapidly colonizing r ecently disturbed or early successional wetlands. While providing excellent cover and nesting substrate for many animals and birds, their tremendous amounts of litter production and dense growth habit occasionally makes them problematic to lake managers. Desired Aquatics Though not specifically more useful to w ildlife than many of the nuisance native vegetation, the relatively sparse growth patt erns of the species listed below lends to higher diversities, lower litte r production, increased oxygen leve ls, and better access for anglers. These plants are also more typi cal of oligotrophic syst ems where a lack of productivity contributes to sandi er substrates and clearer wate r. The association of these species to oligotrophic conditi ons leads to their preference ov er species more typical of eutrophic, highly productive syst ems that accumulate organic material and have turbid water. The following are a few species genera lly thought to be representative of a more natural, historic system before higher nutrient levels and water level stabilization affected their ability to compete. Egyptian paspalidium (commo nly called Knot Grass) ( Paspalidium geminatum ): A tall species of grass with st ems reaching heights of 3 m. It typically grows on sandy substrates and is generally thought to be good sport fish habitat. Though capable of forming monoc ultural stands, it often coincides with

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23 submersed species in deeper water. Grows to depths of at least 2 m but generally is out competed in shallow waters without si gnificant efforts to establish it there. Maidencane ( Panicum hemitomon ): Another deep water grass species that forms thin stands among submersed species. Relies solely on vegetative reproduction through rhizomes unless seeds are exposed during drought conditions. Grows to depths of 3 m in clear water and on sandy substrates. Also thought to be good sport fish habitat. Southern watergrass ( Luziola fluitans Synonymy: Hyrdochloa caroliniensis Beauv.): A perennial grass that forms dense colonies in many water bodies in Florida, occurring in shallow water or on normally flooded shorelines. Its leaves can be underwater (to 1 m), floating, or em ergent to 20 cm in height and on stems to 1 m long. When occurring on moist soils, stems act as runners and leaves are attached to the soil, creati ng a dense carpet of small, fr agile leaves (7.4 mm wide to 7 cm long). Upon flooding, the stems become erect and the leaf blades densely cover the surface of the water, giving the a ppearance of a firm substrate. This grass tends to be more common in disturbed area s, especially on grazed shorelines where herbivory limits the height of competing vegetation. Giant bulrush ( Scirpus californicus ): A large species of rush, stems reaching heights over 3 m. Typically grows on sandy substrates with vegetative rhizome reproduction. Dense stands provide nesti ng substrates for some bird species, though generally occurs in higher energy e nvironments and deeper water (2 m). Lack of any leaf cover permits growth of submersed aquatics within dense stands. Also thought to be good sport fish habitat. The aforementioned species ar e a select few of interest to those managing aquatic habitats within the state of Florida. A ll of these species occur on Lake Toho, some constantly managed against and others phys ically planted for establishment. The manipulation of species and habitats re quires monitoring programs to assess the responses and effectiveness of the treatments and strategies applied. The scale and intensity of the habitat management pr oject on Lake Toho provides an excellent opportunity for discerning bot h the immediate and long-term effects of the commonly applied treatments, as well as experimental combinations of treatments. The following chapters detail the distributions and abundan ces of the species and communities found on Lake Toho prior to the treatments, including the species listed above.

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24 CHAPTER 3 TREATMENT-SELECTION STUDY Introduction To counteract the effects of impoundment eutrophication, and invasion of exotic species on aquatic habitats, lake restorati on efforts have become higher priority and increasingly disruptive in na ture. In 1971, for example, th e artificial dry down of Lake Toho was considered a ‘drastic’ move and the removal of 172,000 m3 of muck in 1987, unprecedented (HDR Engineering 1989). These projects pale in comparison to the 2004 dry down and removal of 7,000,000 m3 of muck. With the ex ception of three study sites on the lake, virtually every si gnificant stretch of shoreline is scheduled to be scraped, leaving sandy beaches from roughly 30–120 cm in depth at high water. These depth zones targeted for removal are generally o ccupied by dense, monocultural stands of species like Pontederia cordata or Typha spp., and often create floating mats either within or on the deep-water edge of these communities. As described in Chapter 1, these mats can become progressively thicker as wi nd and wave actions fold the leading edge over and onto itself and deposit dr ifting organic materials. The purpose of the 1987 muck removal project was to remove the mats and dense vegetation that were blocking fish spawning and nursery utilization of the shallower reaches of the littoral zone, as well as impedi ng navigation of anglers. Habitat diversity was also believed to be much lower in dense stands of Pontederia than native grassy communities that once occupied the shorelines, before impoundment and eutrophication. Since Pontederia had become extremely dominant in the shallower zones and was

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25 thought to be at least partially responsible fo r the creation of organi c barriers, mechanical scraping for the 2004 project was sc ripted to remove this entire community. Literally, the shoreward and lakeward extent of the Pontederia community was marked with PVC poles, and bulldozers removed everything in between. The 1987 project revealed that muck re moval had only temporary effects, as Pontederia and Polygonum species quickly reestablished and out competed most others upon reflooding. The solution was thought to lie in monitoring and managing littoral succession with cocktails of herbicides to control which species rebound and flourish. Unfortunately, several broad applications must be made in order to impede the growth of unwanted vegetation and to establish more de sirable species, leaving the scraped areas relatively barren during this period. These pr actices, combined with muck removal at such a large scale, greatly increase the un certainty of desired outcomes since both the intensity and temporal extent of the di sturbance are increase d. With only small percentages of the shoreline left unscraped, and the regrow th process slowed and limited, monitoring the effects of this disturbance is imperative to making decisions about future, similar projects. The ultimate goal of this study was to establish and test a robust sampling design to compare the differential vegetation responses to three separate s horeline-restoration practices performed during an artificial dry down. These treatments will be tested in another study at a later date and include Mechanical removal of muck and vegeta tion with unrestricted succession (i.e., no herbicide management) during dry down. Mechanical removal during dry down, follo wed by herbicide application to aid establishment of desirable species.

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26 Aggressive herbicide app lication during and following dry down, with the goal of eliminating unwanted species without any mechanical removal of substrates or vegetation. No treatment (control), othe r than artificial dry down. These treatments were not applied during the term of this study, w ith the dry down and muck removal process beginning several months after sampling concluded. The primary objective of this study was to co llect baseline data for the experiment prior to dry down and treatment applicati on. This included 1) defining pre-existing littoral communities and their compositions, 2) identifying the underlying environmental gradients associated with littoral distribut ions, and 3) using th ese baseline data to construct a predictive vegetation model as an example of a future management tool in lake restoration. Methods Study Sites The littoral zone of Lake Toho is highly variable in terms of slope, communities, wave actions, shoreline use, and so on. To minimize interand intrasite variation that would confound treatment comparisons, yet prov ide robust spatial inference, we chose three replicate areas (study sites) with sim ilar slopes, an absence of physical anomalies such as coves, stream outflows or abrupt changes in topography, a nd areas with similar grazing pressures, all bordered by cattle ranc hes (Figure 3-1). Cattle ranches are the predominant land use practice for the southern two-thirds of the lake, with most ungrazed or substantially developed shorelines occurring on the northern end. The sites all contained fairly dense stands of Pontederia and occupied a depth zone of roughly 0–135 cm (0–53 in) in water de pth at a maximum p ool stage of 16.75 m

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27 N E W S H erbici de N one 0 1 1 6 1 7 3 2 S N H S/HSite 3S /H H N SSite 1H S/ H N SSite 2 L a k e T o h o p e k a l i g a 0 –14 ft depth classes N E W S H erbici de N one 0 1 1 6 1 7 3 2 S N H S/HSite 3S /H H N SSite 1H S/ H N SSite 2 L a k e T o h o p e k a l i g a 0 –14 ft depth classes 0 –14 ft depth classes Figure 3-1. Locations of three replicate study s ites receiving various tr eatments. Site one is located just south of Brown’s Poin t on the south western shoreline of the lake, site two is located on South Stee r Beach on the southeastern stretch of shoreline and site three is located in Goblet’s Cove on the east shore. (55 ft) NGVD. Each study site stretched 1600 m (approx. 1 mi) of shoreline, composed of the four previously descri bed treatment blocks of 400 m each (Figure 3-2). Maximum water depth of the plots, or their lakeward extent from the shoreline, was delimited by the approximate maximum water depth to be m echanically scraped during a dry down and extended just beyond the deep water extent of the Pontederia community. The total area of each treatment block varied slightly the n, as each was 400 m in shoreline length but the lakeward extent determined by slope a nd community type. A 25 m spray buffer was established around each 1600 m study site to mi nimize the effects of routine herbicide applications in other areas of the lake. Du e to the extremely invasive nature of water

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28 hyacinth ( Eichhornia crassipes ) and water lettuce ( Pistia stratiotes ) and given the problems they have caused on Lake Toho hist orically, occasional spraying of small groups of these species was allowed when and if they appeared. Additionally, study sites were unable to be isolated from lake-wide applications of floridone treatments, which were applied systemically in the consta nt management of the nuisance submersed aquatic, Hydrilla All other applications, however including the periodic spraying of cattails or floating mats was eliminated. Digital Orthographic Quarter Quad s (DOQQ’s) taken in 1999 at 1-m2 resolution were layered with a bathymetric map (Rem etrix LLC 2003) of the lake using Arcview GIS 3.2 software. Eight random sample point s were selected in each treatment block, stratified by four depth classes. The locations of these points were rest ricted to areas with a maximum slope of 0.3 m over 30 m. This was accomplished by overlaying a 30x30 m grid onto the bathymetric GIS (Geographical Information Syst ems) layer and restricting point selection to the contour li nes that were at least one grid cell apart. Two of the grid cells were randomly selected from each depth class and the coordinates of their centroids were located in the field with a Global Positi oning System. This procedure resulted in 32 random sample locations per study site, eight pe r treatment block and two per depth class, all located a minimum of 30-m apart and on similar slope gradients. Sampling was initiated in June of 2002, provi ding two years of pretreatment habitat descriptions. All three study areas were samp led in their entirety twice a year, in June and December of 2002 and May and December of 2003. These sampling times coincided with low pool (summer) and high pool (winte r) water stages as well as growing and

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29 Herbicide None (Control) S/H H N S Scraped w/ Herbicide Scraped (No herbicide) 25 m Spray Buffer0 1 2 3 4 5 Depth classes (feet) N E W S 4 0 0 mA Herbicide None (Control) S/H H N S Scraped w/ Herbicide Scraped (No herbicide) 25 m Spray Buffer0 1 2 3 4 5 Depth classes (feet) N E W S 4 0 0 m Herbicide None (Control) S/H H N S Scraped w/ Herbicide Scraped (No herbicide) 25 m Spray Buffer0 1 2 3 4 5 Depth classes (feet) N E W S Herbicide None (Control) S/H H N S Scraped w/ Herbicide Scraped (No herbicide) 25 m Spray Buffer0 1 2 3 4 5 Depth classes (feet) N E W S 4 0 0 mA H S/H N S Scraped (No herbicide) Scraped w/ Herbicide None (Control) HerbicideDepth classes (feet) 5 4 3 2 1 025 m Spray Buffer 6 N E W SB H S/H N S Scraped (No herbicide) Scraped w/ Herbicide None (Control) HerbicideDepth classes (feet) 5 4 3 2 1 025 m Spray Buffer 6 N E W S H S/H N S Scraped (No herbicide) Scraped w/ Herbicide None (Control) HerbicideDepth classes (feet) 5 4 3 2 1 025 m Spray Buffer 6 N E W SB Figure 3-2. Individual study sites and their assigned treatments. A) Site 1. B) Site 2. C) Site 3. White is designated as a c ontrol plot, Orange is an aggressive herbicide treatment, Green is muck removal without herbicide follow-up and Blue is muck removal followed by repeated herbicide application.

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30 S N H S/H Herbicide None (Control) Scraped w/ Herbicide Scraped (No herbicide)Depth classes (feet) 5 4 3 2 1 025 m Spray Buffer N E W S C S N H S/H Herbicide None (Control) Scraped w/ Herbicide Scraped (No herbicide)Depth classes (feet) 5 4 3 2 1 025 m Spray Buffer N E W S S N H S/H Herbicide None (Control) Scraped w/ Herbicide Scraped (No herbicide)Depth classes (feet) 5 4 3 2 1 025 m Spray Buffer N E W S C Figure 3-2. Continued non-growing seasons. For temporal analys es, one site was randomly selected for sampling each month, resulting in 11 months of 32 samples in the period of our study. Environmental Variables Vegetation samples were collected using a 0.25-m2 quadrat, cutting all standing vegetation at the substrate leve l and placing it in plastic bags where it was transported to the University of Florida for sorting. Th e numbers of stems were counted for each species in each quadrat and the species were then oven dried to a constant weight to determine dry biomass. Importance values were calculated for each species in each quadrat with the formula: (Relative Biomass + Relative Density)/2 *100 This value gives a good estimate of species importance within a given quadrat and is not biased towards large, few-stemmed (e.g., Typha spp.) or small, numerous-stemmed

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31 species (e.g., Eleocharis spp.) (McCune and Grace 2002). This calculation also relativizes the dataset, eliminating the need for transformations typically applied to density or biomass data that can vary by orders of magnitude between species and samples. Soil cores were collected from each sampling location in June 2003, using cylindrical aluminum corers. These corers m easured 7 cm in diameter and were used to extract the top 10 cm of substrate (Blake and Hartge 1986). Samples were packed in Ziploc bags and placed on ice until moved to a freezer at the University of Florida. After being oven dried to constant weight bulk densities were de termined (Blake and Hartge 1986). Percent of organic c ontent in the samples was calculated by loss on ignition (Chapman and Pratt 1961, Jacobs 1971). Hydrological variables were all collected based on the lake stage as recorded by water control structure S-61 H on the south end of the lake. The average of at least four water depths taken at each sampling location wa s referenced to the lake stage on that day, giving a rough estimate of elevation for each sample. All depths were computed based on high pool stage (16.75 m NGVD). Hydr operiods were then calculated for each location based on the number of days floode d over the two year pe riod of October 2001 to October 2003. Data Analysis The four sampling periods during th e winter and summer of 2002–2003 yielded four repeated measures of the 96 sampli ng locations. Plant species densities and biomasses in each quadrat were summed from those sampling periods and then relativized and their Importance Values (IV) computed. This gave an estimate of the relative importance of each sp ecies in each quadrat over the four sample periods. For

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32 example, the stem counts and biomasses of species one (Sp1) in quadrat one (Q1) were added together for the four sampling periods. Assuming the species occurred in all four samples, the formula would look like (Sp1Q1T1+ Sp1Q1T2 + Sp1Q1T3 + Sp1Q1T4) = Importance Value The IV’s of all species were added to gether and a percentage of the total cumulative IV was calculated for each species. To reduce noise from rare species, only those with cumulative IV’s composing 95% of the total were retained for analysis. Typically, species that occur in <5% of the samples are deleted (McCune and Grace 2002) but we used 5% of the total IV. This method is more representative of the actual importance of a species throughout the samp le for the same reason IV’s are more representative of a species ’ abundance than frequency. The resultant matrix consisted of 96 sa mples by 24 species, reduced from the 66 species encountered throughout th e study. All analyses of th is matrix, unless otherwise specified, were performed using PCOR D software (McCune and Mefford 1999). Outlier samples were tested for using an Outlier Analysis, which creates a frequency distribution of average Sorenson di stances of each sample from every other sample in species space. At a cutoff level of 2.0 standard deviations from the grand mean (McCune and Grace 2002), no outliers were detected. A hierarchical, agglomerative Cluster Anal ysis was performed to find groups (or communities) of similar speci es compositions. Flexible beta (-0.25) linkage and Sorenson distance measures were chosen for their space conserving properties, compatibilities with each othe r, and their advantages with non-normal data (McCune and

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33 Grace 2002). This analysis grouped similar sample units based on species IV’s, using multiple species as a basis for deciding on the fusion of additional groups. An Indicator Species Analysis was perfor med for two reasons: 1) to determine the optimum number of clusters for further analysis and 2) to define those clusters in terms of representative species. This analysis us es the proportional IV and frequency of a particular species in a partic ular cluster relative to its IV and frequency in all other clusters (Dufrene and Legendre 1997). The results are expressed as a percentage, or Indicator Value, which is a measure of how re presentative a species is of a particular group. A value of 100 would indicate a perfect representative, a species that was always present in that group and never occurred in any other group. The st atistical significance of that value is then evaluated with a Mont e Carlo test (1000 permut ations), with the null hypothesis being that the value is no larger than expected by chance (McCune and Grace 2002). The corresponding p-values of each sp ecies were the basis for the decision on how many clusters to choose (i .e., the level of clustering th at produced the most species with p-values <0.05) (McCune and Grace 2002). The species with low p-values and high indicator values were used as the community descriptors (cluster labels) in future analyses. The mean IV’s of the indicator species at several depths were tallied for each cluster and plotted against water depth. Th is was done as a simple, direct gradient analysis to show a preliminary distributi on of communities as related to depth. A Nonmetric Multidimensional Scaling (N MS) ordination was used to assess the dimensionality of our dataset (see followi ng paragraph). This method of ordination works well with typical heterogeneous community datasets that are laden with zeros and

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34 have non-normal distributions. Generally, in a species by sample unit matrix there may be a large proportion of zeros, or many sp ecies with few occurrences (high betadiversity). The broader the range of environment covered by the study, the more sparse the matrix. This creates problems in many or dinations as zeros can be interpreted as shared values or positive relationships and are grouped together. This is referred to as the “zero-truncation problem” (Beals 1984 and McCune and Grace 2002). NMS is less affected by this problem because of its us e of ranked distances. Additionally, NMS avoids assumptions of linear relationships among variables unlike other, more common ordination methods like PCA and CCA. The purpose of the ordination was expl oratory in nature to assess the dimensionality of the dataset (i.e., to see how well the data were structured). Too many dimensions are difficult to interpret and w ould be representative of a very complex dataset. The goal of the ordination is to examine the data in as few dimensions as possible, without losing the st ructure inherent in the data. Each dimension, or axis, is synthetic and represents measured or unm easured environmental variables along which samples are distributed. The amount of vari ance explained by the ordination and how it is distributed along the primary axes is repo rted as a coefficient of determination (r2) between distances in the ordination space and the original space. Pearson and Kendall correlations of the measured environmental va riables are also calcu lated to show which, if any variables are related to the synthetic axes. The overall stru cture, or how well the dataset was able to be grouped, is reported as a stress value and in stability measure. McCune and Grace (2002) state that stress values for community data typically lie

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35 between 10 and 20 and instabilities ar ound 0.0001. Clarke (1993) and McCune and Grace (2002) give more information on NMS. Ordination results are shown in a graph of sample units plotted in species space in the number of dimensions (axes) suggeste d, grouping samples with similar species compositions and separating those with differenc es. This plot shows the relationship of each sample to one another; the larger the distance between samples, the more dissimilar their compositions. To show the dist ribution of samples along the measured environmental gradients, joint plots of correlated variables (r2>0.30) were overlayed onto the ordination diagram, with length and dire ction representative of their correlation to the axes. The sample units were color coded according to the groups formed by the Cluster Analysis to show community dist ribution along the gradients. A Classification And Regression Tree (CAR T) model (S-Plus Tr ee Library, De’ath 2002) was then used to predict the communities identified by the cluster analysis using the measured environmental variables alone. These models have been applied most often to classify habitats or vegetation communities based on environmental characteristics, resulting in an overall descri ption of how different the groups are, which variables distinguish the groups and a pr edictive model that can classify new samples into those groups (Urban 2002). This procedure works by recursively partitioning the multidimensional dataset into subsets that are more homogeneous in terms of the response variable, in this cas e, cluster or community membership (Vayssieres et al. 2000). The heterogeneity of each subset is m easured as an impurity, calculated in our model using the Gini index (Breiman et al. 1984, Crawley 2002, Venables and Ripley 2002). The goal of each split is to maximi ze the reduction in impurity. The model

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36 identifies a single variable (and its threshold va lue) as the indicator for each branch of the tree, as opposed to groups being distinguished along multivariate axes as in discriminant analysis or logistic regressi on. This approach allows the inclusion of non-linear species responses and is unaffected by interactions among variab les (Vayssieres et al. 2000, McCune and Grace 2002). Once the largest possible tree has been gr own, a process of eliminating superfluous branches begins, called “pruning back to an honest tree” (Breiman et al. 1984). This is done by testing each subtree for its error rate ba sed on data that were not used to grow the largest tree. Using cross validation, whic h acts as a test sample while extracting information for all the cases of a data set, the final tree is constructed from all of the data, using the best tree size (Vaysieres et al 2000). The performance of the model is measured by a misclassification rate, while th e amount of variation explained by the tree is reported as 1-Relative Error, or more strictly, 1-Cross Validated Error. The final output is a prun ed tree with barplots u nder each leaf showing the composition of the final groups, as well as the nu mber of samples in that leaf. Threshold values of the variables determ ining the splits are shown at each node and the length of the branches between nodes indicates the strength of the split. Several combinations of the variables water depth, hydroperiod, percent organic and bulk density were used as continuous predictors, while site and whethe r or not the sample occurred on a floating mat were used as categorical variables. The final tree incorpor ated water depth, bulk density, study site, and floating mat variables. A Multivariate Regression Tree (MRT) an alysis was conducted to identify communities based on species IV’s and wh ere they occurred along environmental

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37 gradients, and to compare the resultant communities (leaves of the tree) with those formed in the cluster analysis and CART model. This was done with the same Tree Library in S-Plus as our CART analysis, whic h is somewhat limited in terms of distance measure options. This software only allows for Euclidian distance measures with MRT analyses, which is not typical ly used with non-normal data De’ath (2002) and Urban (2002) suggested ideally using a distance-based MRT (db-MRT) for data of this type, but since we were primarily interested in MRT as an independent comparison to the other analyses, we opted for a practical rather th an ideal solution and employed the Euclidian distance measure provided in the software. This method uses the sum of squared Euclidian distances about the multivariate mean of samples as an impurity measure of each node, and each split is made to maximize this sum of squares between nodes and to minimize it within nodes (De’ath 2002). E ach leaf is then characterized by the multivariate mean of its samples, the number of samples within that leaf and their defining environmental variables. The per cent of variation expl ained by the tree is reported as 1-Relative Error, or more strictly 1-Cross Validated Erro r. Species variances are tabulated to show the contributions of individual species at each split and how well the tree explains their variations, as well as the percent of variation explained by each split. In short, this technique partitions the samples into communities using both species IV’s as well as the associated environmenta l variables, and provide s the threshold values for each partitioning variable. The resultant communities are defined not just by species compositions but where they occurred on the en vironmental gradients as well, providing a more detailed, inclusive description than those defined by the Cluster Analysis.

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38 Results Of the 66 species recorded over the four sampling periods, 24 comprised the top 95% of the cumulative importance values (Figure 3-3, Appendix A). The summed dataset resulted in 96 samples by 24 species, which was divided into five communities based on the cluster analysis. The number of clusters was chosen based on the ISA, where the group with the highest number of sp ecies with indicator values greater than expected by chance was selected. With five groups, 17 of the 24 species had p-values <0.05 (Table 3-1). The ISA identified the following species as strong indicators of community type (clusters): Luziola fluitans : (LUZFL) also known as Hydrochloa caroliniensis Nuphar luteum and Nymphaea odorata : (NUPLU_NYMOD ) Nuphar luteum is currently being reclassified as Nuphar advena Pontederia cordata and Alternanthera philoxeroides : (PONCO_ALTPH) Hydrilla verticillata Lymnobium spongia and Ceratophyllum spp.: (HYDVE_LYMSP_CERSP) Panicum repens and Eleocharis spp.: (PANRE_ELESP) These groups are hereafter referred to by sp ecies code, which consists of the first three letters of genus and the fi rst two of specific epithet (e.g., Luziola fluitans = LUZFL) (Appendix A). The approximate distributions of these cl usters were preliminarily displayed by simply plotting the mean IV’s of each of th e indicator species in each cluster against water depth (Figure 3-4). This plot showed the PANR E_ELESP community occurred in the shallowest depth zones, exhibiting a bi modal distribution with LUZFL occurring at intermediate depths. The PONCO_ALTPH community completely dominated depths

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39 ranging from roughly 0.6–1.2 m in depth, while the HYDVE_LYMSP_CERSP and NYMOD_NUPLU communities occurred at deeper water depths. 0 5 10 15 20 25 30 35 95% 66 Total Species 24 Species 0 5 10 15 20 25 30 35ELEQU BRAMU L U D SP BA C C A UTRSP TYPSP LU D RE POLHY AXOFU SA GL N CERSP E IC C R U N PA S PA N HE H YDS P NYMOD LYMSP NUPLU ELESP H Y DVE P A NRE AL T PH LUZFL PONCOSpecies% Cumulative IV 0 5 10 15 20 25 30 35 95% 66 Total Species 24 Species 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 95% 66 Total Species 24 Species 0 5 10 15 20 25 30 35ELEQU BRAMU L U D SP BA C C A UTRSP TYPSP LU D RE POLHY AXOFU SA GL N CERSP E IC C R U N PA S PA N HE H YDS P NYMOD LYMSP NUPLU ELESP H Y DVE P A NRE AL T PH LUZFL PONCOSpecies% Cumulative IV 0 5 10 15 20 25 30 35ELEQU BRAMU L U D SP BA C C A UTRSP TYPSP LU D RE POLHY AXOFU SA GL N CERSP E IC C R U N PA S PA N HE H YDS P NYMOD LYMSP NUPLU ELESP H Y DVE P A NRE AL T PH LUZFL PONCOSpecies% Cumulative IV Figure 3-3. Percent of cumulative Importan ce Value (IV) for each species, with 24 comprising 95% of the total. Appendix A lists these 24 and the 42 less common species. The NMS ordination resulted in three dime nsions, cumulatively explaining 78% of the information in the dataset. Axis 1 expl ained the majority (41%) and bulk density and percent organic were most correlated (Pearson and Kendall) to this axis (r2 = 0.54 and 0.27, respectively). Water depth and hydrope riod were most correlated to Axis 2 (r2 = 0.55 and 0.48, respectively), but this axis explained the least amount of variation (17%). Axis 3 was the second most important axis, explaining 21%, suggesting some of the structure in species composition remains unexplained by our measured variables.

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40 Figure 3-5 is a plot of sample units in species space, showin g the two dimensions most correlated to our measur ed environmental variables. By overlaying cluster Table 3-1. Indicator values of species in the Treatment-Selection study, with values ranging from 0-100. P-value Spp code Group ID Cluster 1 2 3 4 5 0.001 ALTPH 3 19 3 55 1 3 0.001 AXOFU 5 2 0 0 0 48 0.188 BRAMU 3 2 0 19 0 8 0.043 HYDSP 3 1 0 26 1 0 0.047 LUDRE 5 8 1 0 0 23 0.001 LUZFL 1 78 2 0 0 12 0.001 PANRE 5 6 0 1 1 71 0.024 UNPAS 1 33 3 2 0 10 0.051 BACCA 5 0 0 1 12 24 0.499 POLHY 3 6 9 14 1 0 0.001 EICCR 2 0 37 0 0 0 0.001 LYMSP 4 0 1 0 60 0 0.001 PONCO 3 10 0 70 1 0 0.023 PANHE 2 0 31 1 0 3 0.023 LUDSP 3 0 0 24 0 0 0.001 CERSP 4 0 8 0 52 0 0.001 HYDVE 4 0 0 0 91 0 0.001 ELESP 5 0 0 0 0 93 0.03 UTRSP 2 0 33 2 3 0 0.001 NUPLU 2 0 73 0 0 0 0.045 TYPSP 3 0 0 20 0 0 0.001 NYMOD 2 0 49 0 0 0 0.388 SAGLN 3 2 0 8 0 0 0.481 ELEQU 5 0 0 0 0 5 Species with high indicator values ar e highlighted accordingly and are used as community descriptors for each group. membership onto the ordination, we see the distribution of the communities along these axes and their relati on to one another. Shallow water communities are located at the top of the graph and deeper water communities at the bottom. Those associated with highly organic soils are on the left and those with high bulk densities (mineral, low or ganic) are on the right. This figure also shows the obvious interactions between hydr operiod and water depth as well as between bulk density and percent organic, and their orthogonality to e ach other. Figure 3-6 is the

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41 same diagram but with the plots labeled, showin g a clear grouping of Site 1 in the deepest water zone. Nearly the entire HYDVE_LY MSP_CERSP community comprised Site 1 samples, while the deeper samples of S ite 2 and 3 lie within the PONCO_ALTPH community. The labels assigned to each sa mple indicate the site first (1-2-3), the treatment plot second (A-B-C-D), the dept h class third (1-2-3-4 ) and which of two samples it represents from that depth class last (A-B). 0 20 40 60 80 100 00.20.40.60.811.21.4Water Depth (meters)Summed Avg IV LUZFL NUPLU/NYMOD PONCO/ALTPH HYDVE/LYMSP/CERSP PANRE/ELESP Figure 3-4. Plot of mean IV’s of the indicat or species in each clus ter over several depth classes Plotting the weighted average species scor es onto the ordination diagram shows the average position of each species along each ordination axis (McCune and Meoff 1999). Figure 3-7 shows all 24 species and their rela tive positions to the measured gradients, with the indicator species from each clus ter highlighted accordingly. The species occupying the upper right corner of the graph, in the shallow water and with high bulk

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42 densities are mostly grassy species, including Eleocharis spp. Axonopus furcatus, Panicum repens, Luziola fluitans, Eleocharis quadrangulata and a small, succulent Water Depth Hydroperiod Pct Organic Bulk Density Axis 1Axis 2 Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP PANRE_ELESM Water Depth Hydroperiod Pct Organic Bulk Density Axis 1Axis 2 Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP PANRE_ELESM Water Depth Hydroperiod Pct Organic Bulk Density Axis 1Axis 2 Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP PANRE_ELESM Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP PANRE_ELESM Figure 3-5. NMS ordination plot of sample units in species space, color coded by community. Distances between samples is representative of the dissimilarities in species compositions. Jo int plots of correlated environmental variables are displayed as red vectors, based on Pears on and Kendall correlation coefficients. The direction and length of the vector is representative of the direction and strength of the variable’s rela tionship to the corresponding axis.

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43 1A1A 1A1B 1A2A 1A2B 1A3A 1A3B 1A4A 1A4B 1B1A 1B1B 1B2A 1B2B 1B3A 1B3B 1B4A 1B4B 1C1A 1C1B 1C2A 1C2B 1C3A 1C3B 1C4A 1C4B 1D1A 1D1B 1D2A 1D2B 1D3A 1D3B 1D4A 1D4B 2A1A 2A1B 2A2A 2A2B 2A3A 2A3B 2A4A 2A4B 2B1A 2B1B 2B2A 2B2B 2B3A 2B3B 2B4A 2B4B 2C1A 2C1B 2C2A 2C2B 2C3A 2C3B 2C4A 2C4B 2D1A 2D1B 2D2A 2D2B 2D3A 2D3B 2D4A 2D4B 3A1A 3A1B 3A2A 3A2B 3A3A 3A3B 3A4A 3A4B 3B1A 3B1B 3B2A 3B2B 3B3A 3B3B 3B4A 3B4B 3C1A 3C1B 3C2A 3C2B 3C3A 3C3B 3C4A 3C4B 3D1A 3D1B 3D2A 3D2B 3D3A 3D3B 3D4A 3D4B Water Depth Hydroperiod Pct Organic Bulk Density Axis 1Axis 2 Cluster 1 3 5 7 9 Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM 1A1A 1A1B 1A2A 1A2B 1A3A 1A3B 1A4A 1A4B 1B1A 1B1B 1B2A 1B2B 1B3A 1B3B 1B4A 1B4B 1C1A 1C1B 1C2A 1C2B 1C3A 1C3B 1C4A 1C4B 1D1A 1D1B 1D2A 1D2B 1D3A 1D3B 1D4A 1D4B 2A1A 2A1B 2A2A 2A2B 2A3A 2A3B 2A4A 2A4B 2B1A 2B1B 2B2A 2B2B 2B3A 2B3B 2B4A 2B4B 2C1A 2C1B 2C2A 2C2B 2C3A 2C3B 2C4A 2C4B 2D1A 2D1B 2D2A 2D2B 2D3A 2D3B 2D4A 2D4B 3A1A 3A1B 3A2A 3A2B 3A3A 3A3B 3A4A 3A4B 3B1A 3B1B 3B2A 3B2B 3B3A 3B3B 3B4A 3B4B 3C1A 3C1B 3C2A 3C2B 3C3A 3C3B 3C4A 3C4B 3D1A 3D1B 3D2A 3D2B 3D3A 3D3B 3D4A 3D4B Water Depth Hydroperiod Pct Organic Bulk Density Axis 1Axis 2 Cluster 1 3 5 7 9 1A1A 1A1B 1A2A 1A2B 1A3A 1A3B 1A4A 1A4B 1B1A 1B1B 1B2A 1B2B 1B3A 1B3B 1B4A 1B4B 1C1A 1C1B 1C2A 1C2B 1C3A 1C3B 1C4A 1C4B 1D1A 1D1B 1D2A 1D2B 1D3A 1D3B 1D4A 1D4B 2A1A 2A1B 2A2A 2A2B 2A3A 2A3B 2A4A 2A4B 2B1A 2B1B 2B2A 2B2B 2B3A 2B3B 2B4A 2B4B 2C1A 2C1B 2C2A 2C2B 2C3A 2C3B 2C4A 2C4B 2D1A 2D1B 2D2A 2D2B 2D3A 2D3B 2D4A 2D4B 3A1A 3A1B 3A2A 3A2B 3A3A 3A3B 3A4A 3A4B 3B1A 3B1B 3B2A 3B2B 3B3A 3B3B 3B4A 3B4B 3C1A 3C1B 3C2A 3C2B 3C3A 3C3B 3C4A 3C4B 3D1A 3D1B 3D2A 3D2B 3D3A 3D3B 3D4A 3D4B Water Depth Hydroperiod Pct Organic 1A1A 1A1B 1A2A 1A2B 1A3A 1A3B 1A4A 1A4B 1B1A 1B1B 1B2A 1B2B 1B3A 1B3B 1B4A 1B4B 1C1A 1C1B 1C2A 1C2B 1C3A 1C3B 1C4A 1C4B 1D1A 1D1B 1D2A 1D2B 1D3A 1D3B 1D4A 1D4B 2A1A 2A1B 2A2A 2A2B 2A3A 2A3B 2A4A 2A4B 2B1A 2B1B 2B2A 2B2B 2B3A 2B3B 2B4A 2B4B 2C1A 2C1B 2C2A 2C2B 2C3A 2C3B 2C4A 2C4B 2D1A 2D1B 2D2A 2D2B 2D3A 2D3B 2D4A 2D4B 3A1A 3A1B 3A2A 3A2B 3A3A 3A3B 3A4A 3A4B 3B1A 3B1B 3B2A 3B2B 3B3A 3B3B 3B4A 3B4B 3C1A 3C1B 3C2A 3C2B 3C3A 3C3B 3C4A 3C4B 3D1A 3D1B 3D2A 3D2B 3D3A 3D3B 3D4A 3D4B Water Depth Hydroperiod Pct Organic Bulk Density Axis 1Axis 2 Cluster 1 3 5 7 9 Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Figure 3-6. The same NMS plot shown in Figur e 3-5 but with sample units labeled for interpretative purposes.

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44 ALTPH AXOFU BRAMU HYDSP LUDRE LUZFL PANRE UNPAS BACCA POLHY EICCR LYMSP PONCO PANHE LUDSP HYDVE ELESM UTRSP NUPLU TYPSP NYMOD SAGLN ELEQU Water Depth Hydroperiod Pct Organic Bulk Density Axis 1Axis 2 Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM CERSP ALTPH AXOFU BRAMU HYDSP LUDRE LUZFL PANRE UNPAS BACCA POLHY EICCR LYMSP PONCO PANHE LUDSP HYDVE ELESM UTRSP NUPLU TYPSP NYMOD SAGLN ELEQU Water Depth Hydroperiod Pct Organic Bulk Density Axis 1Axis 2 Cluster LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM CERSP Figure 3-7. Weighted average species scores overlayed onto NM S ordination plot. Indicator species are highlighted and color coded according to cluster (community) membership. Locations are representative of each species’ average location along the measured environmental gradients. Ludwigia repens As the samples increased in de pth, the bulk densities generally decreased. The species with the lowest bulk densities and organic matter were Pontederia, Sagittaria lancifolia and Typha spp. The deepest water samples had higher bulk densities and consisted of mostly s ubmersed or free floating species, including Hydrilla, Utricularia spp. Ceratophyllum spp., and Lymnobium spongia

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45 We can also show the distribution of our indicator species in relation to these gradients by scaling the symbols of the samp le units they occurred in according to their IV’s; the larger the symbol, the higher the IV in that sample. There was considerable overlap between samples with high values of Panicum repens and Eleocharis spp., justifying the grouping of these species into a single commun ity (Figures 3-8 and 3-9). Luziola fluitans was also important in several of the PANRE_ELESP samples, though highest values occurred in slightly deeper water (Figure 3-10). Dominance of Pontederia is evident in Figure 3-11, though some overlap occurs with the LUZFL community at shallower depths and higher bulk densities, representing the transitional area between dense Pontederia and shallower, grassy communities. The high values of percent organic matter associat ed with this community is easily displayed by scaling the sample symbols according to thei r soil percentages, instead of their species IV’s. Clearly, there is a strong relationship between samples with high IV’s of Pontederia and those with highly or ganic soils (Figure 3-12). Figure 3-13 shows the distribution of Hydrilla along the gradients. The CART model produced a tree pruned to six leaves, with four of the five communities represented (Figure 3-14). The NYMOD_NUPLU community was not delineated at this level of branching, while the LUZFL and the PANRE_ELESP communities were found at varying levels of dominance depending on soil characteristics and water depth. Essentially, the PANRE_ ELESP community was completely dominant at less than 18 cm (7 in) in water depth but overlapped with LUZFL from 28–57 cm (11– 22 in). LUZFL, meanwhile, was dominan t between 18–28 cm ( 7–11 in) and was the most dominant community at less than 57 cm (22 in) when bulk densities were low.

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46 Axis 1Axis 2 PANRE Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Axis 1Axis 2 Axis 1Axis 2 PANRE Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Figure 3-8. Importance values of Panicum repens in the sample units plotted in the NMS ordination. Larger symbols represent larg e IV’s within that sample. Samples are colored according to community.

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47 Axis 1Axis 2 ELESP Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Axis 1Axis 2 Axis 1Axis 2 ELESP Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Figure 3-9. Importance values of Eleocharis spp. in the sample units plotted in the NMS ordination. Larger symbols represent larg e IV’s within that sample. Samples are colored according to community.

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48 Axis 1Axis 2 LUZFL Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Axis 1Axis 2 Axis 1Axis 2 LUZFL Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Figure 3-10. Importance values of Luziola fluitans in the sample units plotted in the NMS ordination. Larger symbols represent larg e IV’s within that sample. Samples are colored according to community.

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49 Axis 1Axis 2 PONCO Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Axis 1Axis 2 Axis 1Axis 2 PONCO Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Figure 3-11. Importance values of Pontederia cordata in the sample units plotted in the NMS ordination. Larger symbols represen t large IV’s within that sample. Samples are colored according to community.

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50 Axis 1Axis 2 Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESMPercent Organic Axis 1Axis 2 Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESMPercent Organic Figure 3-12. Percentage of orga nic matter in each of the samp le units plotted in the NMS ordination. Larger symbols represent pe rcentages of organic material within that sample.

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51 Axis 1Axis 2 HYDVE Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Axis 1Axis 2 Axis 1Axis 2 HYDVE Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Community LUZFL NUPLU_NYMOD PONCO_ALTPH HYDVE_LYMSP_CERSP PANRE_ELESM Figure 3-13. Importance values of Hydrilla verticillata in the sample units plotted in the NMS ordination. Larger symbols represen t large IV’s within that sample. Samples are colored according to community.

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52 HYDVE_CERSP_LYMSP LUZFL NUPLU_NYMOD PANRE_ELESP PONCO_ALTPH Water <57 (22”) Bulk Dens <0.79 Water >18cm (7”) Water <28cm (11”) Bulk Dens >0.93 Water >57cm (22”) Bulk Dens>0.79 Water <18cm (7”) Water >28cm (11)” Bulk Dens <0.93 LUZFL (9) LUZFL (5) PANRE_ELESP (13) PANRE_ELESP (6) HYDVE_CERSP_LYMSP (10) PONCO_ALTPH(53)• • • • • •Error : 0.364 CV Error ( pick ) : 0.618 SE : 0.0852 Missclassrates : Null = 0.573 : Model = 0.208 : CV = 0.354Importance of Predictor Variables Bulk Dens 100 Water Dpth95.6 Floating31.6 Site9.5 HYDVE_CERSP_LYMSP LUZFL NUPLU_NYMOD PANRE_ELESP PONCO_ALTPH HYDVE_CERSP_LYMSP LUZFL NUPLU_NYMOD PANRE_ELESP PONCO_ALTPH Water <57 (22”) Bulk Dens <0.79 Water >18cm (7”) Water <28cm (11”) Bulk Dens >0.93 Water >57cm (22”) Bulk Dens>0.79 Water <18cm (7”) Water >28cm (11)” Bulk Dens <0.93 LUZFL (9) LUZFL (5) PANRE_ELESP (13) PANRE_ELESP (6) HYDVE_CERSP_LYMSP (10) PONCO_ALTPH(53)• • • • • • Water <57 (22”) Bulk Dens <0.79 Water >18cm (7”) Water <28cm (11”) Bulk Dens >0.93 Water >57cm (22”) Bulk Dens>0.79 Water <18cm (7”) Water >28cm (11)” Bulk Dens <0.93 LUZFL (9) LUZFL (5) PANRE_ELESP (13) PANRE_ELESP (6) HYDVE_CERSP_LYMSP (10) PONCO_ALTPH(53)• • • • • •Error : 0.364 CV Error ( pick ) : 0.618 SE : 0.0852 Missclassrates : Null = 0.573 : Model = 0.208 : CV = 0.354Importance of Predictor Variables Bulk Dens 100 Water Dpth95.6 Floating31.6 Site9.5 Importance of Predictor Variables Bulk Dens 100 Water Dpth95.6 Floating31.6 Site9.5 Figure 3-14. CART model of community dist ribution along the measured environmental gradients. This model was pruned fro m a maximum tree size of 12 branches to six, based on a cost complexity pruni ng curve, selecting the smallest tree within one standard error of the best. The numbers of samples in each leaf are shown in parentheses below each barg raph, which shows the compositions of communities within each leaf (e.g. nearly all of 53 samples in the right-most leaf are the PONCO_ALTPH community). On the deeper water side of the tree, two leaves were formed based on bulk densities. The PONCO_ALTPH commun ity had lower bulk densities (<0.93g/cm3) while more mineral soils had HYDVE_LYMSP_CERSP communities. The number in parentheses below the PONCO_ALTPH commun ity shows the complete dominance of this group over all others in the tree, with 53 of the 96 total samples occurring in this group. Bulk density was slightly more impor tant in determining community distribution in the model than water depth, while site and floating mat categorical variables were the

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53 least important. The misclassification rate of the model was 35% and the amount of variation explained was 64% (1 -Relative Error). These values are well within range considering the dynamic and complex system this dataset represents. The confirmatory MRT was pruned to eight leaves with very similar groups as the CART model (Figure 3-15). Water depth was only slightly more important than bulk density in leaf formation, while site differen ces did account for one split in the tree. The first split was at 48 cm (19 in) in water depth, with Panicum repens, Luziola fluitans, and Eleocharis spp. comprising the shallower groups, ve ry similar to the CART model. Below 18 cm (7 in) in water depth, Eleocharis was common, while between 18 and 28 cm (7 and 11 in) Luziola was extremely dominant. From 28–48 cm (11–19 in), however, there was a considerable mix of all three species, Panicum repens, Luziola fluitans and Eleocharis spp. This overlap between comm unities was also evident in the NMS diagram. On the deeper water side of the tree, be tween 48 and 61 cm (19 and 24 in), a mix of Luziola and Pontederia is found representing the border between the shallower grassy communities and the dominant zone of Pontederia The dense, monocultural zone of Pontederia occurred between 61 and 108 cm (24 and 42.5 in) with 36 of the 96 total samples representing this group. At water dept hs greater than 108 cm (42.5 in), however, there were three groups depending on site a nd soil characteristics. Site 1 had very dominant Hydrilla and Lymnobium spp., while Sites 2 and 3 had Nymphaea odorata at higher bulk densities and a Pontederia/Hydrocotyle spp. community at low bulk densities. The occurrence of Hydrocotyle spp. with Pontederia at that water depth and

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54 Water <48cm (19”) Water >18cm (7”) Water >28cm (11”) Water >108cm (42.5”) Site: 2,3 Bulk.Dens>0.24 Water <61cm (24”) Water >48cm (19”) Water <18cm (7”) Water <28cm (11”) Water <108cm (42.5”) Site: 1 Bulk.Dens<0.24 Water >61cm (24”) ALTPH AXOFU BRAMU HYDSP LUDRE LUZFL PANRE UNPAS BACCA POLHY EICCR LYMSP PONCO PANHE LUDSP CERSP HYDVE ELESP UTRSP NUPLU TYPSP NYMOD SAGLN ELEQU • • • • • • ••(13)(6) (8) (5)(7) (9) (12)(36)Error : 0.456 CV Error ( pick ) : 0.8 SE : 0.0819PANRE_LUZFL_ELESPLUZFL ELESP NYMODPONCO_HYDSP LUZFL_PONCO HYDVE_LYMSP PONCOImportance of Predictor Variables Water Depth 100 Bulk Dens 98.5 Site58.9 Floating16.9 Water <48cm (19”) Water >18cm (7”) Water >28cm (11”) Water >108cm (42.5”) Site: 2,3 Bulk.Dens>0.24 Water <61cm (24”) Water >48cm (19”) Water <18cm (7”) Water <28cm (11”) Water <108cm (42.5”) Site: 1 Bulk.Dens<0.24 Water >61cm (24”) ALTPH AXOFU BRAMU HYDSP LUDRE LUZFL PANRE UNPAS BACCA POLHY EICCR LYMSP PONCO PANHE LUDSP CERSP HYDVE ELESP UTRSP NUPLU TYPSP NYMOD SAGLN ELEQU • • • • • • ••(13)(6) (8) (5)(7) (9) (12)(36)Error : 0.456 CV Error ( pick ) : 0.8 SE : 0.0819PANRE_LUZFL_ELESPLUZFL ELESP NYMODPONCO_HYDSP LUZFL_PONCO HYDVE_LYMSP PONCO Water <48cm (19”) Water >18cm (7”) Water >28cm (11”) Water >108cm (42.5”) Site: 2,3 Bulk.Dens>0.24 Water <61cm (24”) Water >48cm (19”) Water <18cm (7”) Water <28cm (11”) Water <108cm (42.5”) Site: 1 Bulk.Dens<0.24 Water >61cm (24”) ALTPH AXOFU BRAMU HYDSP LUDRE LUZFL PANRE UNPAS BACCA POLHY EICCR LYMSP PONCO PANHE LUDSP CERSP HYDVE ELESP UTRSP NUPLU TYPSP NYMOD SAGLN ELEQU ALTPH AXOFU BRAMU HYDSP LUDRE LUZFL PANRE UNPAS BACCA POLHY EICCR LYMSP PONCO PANHE LUDSP CERSP HYDVE ELESP UTRSP NUPLU TYPSP NYMOD SAGLN ELEQU • • • • • • ••(13)(6) (8) (5)(7) (9) (12)(36)Error : 0.456 CV Error ( pick ) : 0.8 SE : 0.0819PANRE_LUZFL_ELESPLUZFL ELESP NYMODPONCO_HYDSP LUZFL_PONCO HYDVE_LYMSP PONCOImportance of Predictor Variables Water Depth 100 Bulk Dens 98.5 Site58.9 Floating16.9 Importance of Predictor Variables Water Depth 100 Bulk Dens 98.5 Site58.9 Floating16.9 Figure 3-15. MRT analysis, with terminal groups of species based on IV’s and their associated environmental variables. Th is confirmatory analysis shows species groupings and distributions along environm ental gradients, independent of the cluster analysis. The numbers of samples in each leaf are shown in parentheses below each bargraph, which shows the compositions of species within each leaf. low bulk densities is indicative of a floati ng mat community. This difference between sites in the deep water was also evident in the NMS diagram (Figure 3-6). Table 3-2 details the nodes of the tree, show ing the contributions of each species at each split and the variance explained for each species. For example, PONCO comprises 27.8% of the total species vari ance, of which 19.8% is explained by the tree, 8.7% by the first split. LUZFL, also responsible for the first split, comprises 19.9% of the total species variance, 10.7% of which is explained by the tree, with 5.6% in the first split.

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55 The second split of 18cm is determined by LUZFL (1.2 %) and ELESP (1.2%), and the third by LUZFL (2.8%) and PANRE (1.1%). The fifth split in the tree, separating Sites 2 and 3 from Site 1 is determined by HYDVE (5.5%). These five species, PONCO, LUZFL, PANRE, ELESP, and HYDVE comprise 75.3% of the total species variance, with 47.6% of it explained by th e tree. Cumulatively, then, these species comprise 87.5% of the variance explained by the tree (47.6% of 54.4%). This confirms their importance as species representative of structure in our dataset, as suggested by the Indicator Species Analysis. The importance of the environmental variab les is also displaye d by Table 3-2, with the summed total of each column represen ting the tree variation explained by that threshold value of the variable in the split. The first split of 48 cm in water depth was by far the most important, accounting for 36.4% of the variation explained by the tree (19.81% of 54.43%). This suggests the larges t differences in communities and the most obvious structural variations occurred at r oughly 48 cm in water depth. The second most important split was at 108 cm in water depth, accounting for 21.4% (11.65% of 54.43%) of the variation. These two splits represent the shallow and deep water extent of the PONCO community, respectively, and outline the two primary community transitional zones in terms of species compositions and di stributions along the wa ter depth gradient. Discussion In vegetation science, the concept of the plant community is absolutely fundamental. It is at the community level that populations and i ndividuals of a plant species can be identified and gr ouped together to characterize the vegetation of an area of a few square meters to several square kilometers. It is also at this level that the effects of

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56 Table 3-2. Species variance in the MRT anal ysis of the Treatment-Selection study. Species Water <48cm Water >18cm Water >28cm Water >108cm Site: 2,3 Bulk dens>0.24 Water <61cm Tree total Spp total ALTPH 0.18 0 0.01 0.41 0.02 0.03 0.1 0.76 2.64 AXOFU 0.2 0.65 0 0 0 0 0 0.86 1.92 BRAMU 0 0 0 0 0 0 0 0.01 0.1 HYDSP 0.08 0 0 0.03 0.12 0.22 0.04 0.49 1.93 LUDRE 0.02 0.01 0 0 0 0 0 0.04 0.26 LUZFL 5.6 1.22 2.76 0.26 0 0 0.9 10.73 19.88 PANRE 1.39 0.3 1.07 0.05 0 0 0.15 2.96 7.24 UNPAS 0 0.01 0 0.01 0 0 0.06 0.08 0.39 BACCA 0 0 0 0.02 0 0.01 0 0.04 0.23 POLHY 0 0 0 0 0 0 0.02 0.03 0.18 EICCR 0 0.01 0.06 0.03 0.06 0.1 0.03 0.29 2.51 LYMSP 0.16 0 0 0.3 0.59 0.02 0.05 1.12 4.9 PONCO 8.72 0.02 0.03 6.52 0.7 1.39 2.43 19.81 27.8 PANHE 0 0 0 0.05 0.08 0.17 0 0.32 1.06 LUDSP 0.01 0 0 0.02 0.03 0.05 0 0.11 0.3 CERSP 0.01 0 0 0.07 0 0.06 0 0.14 0.47 HYDVE 0.51 0 0 3.48 5.45 0.06 0 9.52 12.82 ELESP 2.78 1.16 0.56 0 0 0 0.03 4.54 7.57 UTRSP 0 0 0 0.01 0.02 0.06 0 0.1 0.2 NUPLU 0.05 0 0 0.04 0.09 0.22 0.02 0.43 3.2 TYPSP 0.01 0 0 0.01 0 0 0 0.02 0.49 NYMOD 0.05 0 0 0.32 0.38 1.25 0 2.01 2.77 SAGLN 0.01 0 0 0.01 0 0 0.01 0.03 0.98 ELEQU 0 0 0 0 0 0 0.01 0.01 0.17 Total 19.81 3.38 4.5 11.65 7.56 3.67 3.87 54.43 100 Column totals represent the contribution of each split to the amount of variation explained by the tree. Row totals represent the amount of species variance explained by the tree (tree total) and the contribution of each species to total species variance, respectively. allogenic factors are more easily examined and quantified, as in teractions between species affect the responses of individual species (Kent a nd Coker 1992). No studies on Lake Toho in the past have approached vege tation descriptio n from a community level, nor have any documented quantitative measures of individuals. This study provides the first detailed description of the littoral communities targeted by restoration efforts, explains their distributions along environmen tal gradients, and implements a sampling design for the development of predictive management tools in lake restoration.

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57 Community Descriptions The Cluster Analysis, the NMS ordinati on, the CART and the confirmatory MRT analyses all described the dominance of the PONCO_ALTPH community. NMS ordination diagrams clearly showed the differenc es in soil characteri stics for this group, having the lowest average bulk density (0.27 g/cm3) and highest average percent organic matter (51.6%) of any community. The CART model showed that regardless of site differences, 53 of 63 samples taken in over 57 cm (22 in) of water were dominated by PONCO_ALTPH. The confirmatory MRT produ ced very similar results, with 55 of 69 samples in over 48 cm (19 in) of water composed primarily of Pontederia only substantially occurring with other individua ls at the shallower (48–61 cm) and deeper (>108 cm) ends of its range. The three groups identified by the MRT at depths greater than 108 cm (42.5 in) consisted of Nymphaea odorata Pontederia and Hydrocotyle spp., or Hydrilla and Lymnobium The presence of Hydrocotyle spp. with Pontederia suggests that the community is floating at that depth, indi cative of the deep-wat er extent of the Pontederia community, transitioning to either floati ng leaved or submersed species, depending on the site. At this transitional zone, habitats ranged from dense, organic floating mats to sparsely vegetated, sandy soils over the distan ce of as little as one meter. The factors determining community composition in this ar ea were probably more related to storm events and wave energies than actual water depths. With calm, stable water levels the floating edge of the PONC O_ALTPH community would mo st likely march lakeward, while periods of high wave ener gies would work to push back, break apart and even fold over the floating mat edge (Figure 1-3, Chapter 1). Some of the most diverse samples in this study occurred on thick floating mats, with as many as 18 species in one quadrat.

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58 The small groups identified in this study containing Nymphaea and Hydrilla (14 of 96) were not representative of their overa ll presence in the littoral zone, but rather a result of their more frequent occurrence in deeper water beyond the study sites. The Whole-Lake Monitoring study detailed in formation regarding compositions and distributions of communities beyond 130 cm in depth (Chapter 4). The transition from dominant Pontederia to shallower, grassy species was represented by the Luziola fluitans and Pontederia mixed group formed between 48 and 61 cm (19 and 24 in) in depth by the MRT. From there, groups were formed with varying levels of Panicum repens, Eleocharis spp., and Luziola as depths decreased. The same patterns were evident in the CART model, the NMS ordination, and the plot of IV’s vs. depth, showing a general, dominant mixture of these species in shallow water. The highest average species richness wa s in the PANRE_ELESP and the LUZFL communities, averaging 12.4 and 7.7 species per sample, respectively. As water depths increased, richness decreased, going from 6.0 species per sample in the PONCO_ALTPH community to 5.9 and 5.3 in the NYMOD_NUPLU and HYDVE_LYMSP_CERSP communities, respectively. However, if the floating mat samples were excluded from the PONCO_ALTPH community, two of which had 14 and 18 species in a single quadrat, the average richness fell to 5.1 species per samp le, the lowest average of any community. These results show the hi ghly competitive nature of Pontederia and its associated community in shallow water habitats and its ability to accumulate organic material with its high productivity and densities. However, our data do not provide any information as to the extent of organic accumulation in this community as we only collected the top 10 cm of substrate for our soils analyses. Based on several deeper cores taken for

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59 photograph purposes, however, it is our belief that Site 3 had the deepest organic soils but still rarely in excess of 20 cm This would be logical sinc e Site 3 occurs in a narrow, isolated cove on the east side of the lake w ith presumably much lower energies than Sites 1 and 2. Additionally, this cove is the r eceiving point for canal C-31, which directly drains East Lake Toho and is most likely a source of elevated nutrient levels. In retrospect, peat depths in a ddition to our measured propertie s would have been useful for comparative reasons, but our focus was on the so il characteristics in the zone of highest root/rhizome activity. Regardless of the actual depths of orga nic material on the lake, there is good evidence that the majority of the littoral zone has very sa ndy substrates both shoreward and lakeward of the Pontederia community. With the exception of the NYMOD_NUPLU community (21.3%), no ot her group had an average organic soil content of more than 11%, as compared to 51.6% in PONCO_ALTPH. In fact, the sandiest soils occurred in the HYDVE_LYM SP_CERSP community, w ith an average of only 3.6% organic material. These data high light the concerns of the lake managers, showing that much of the shallow reaches of littoral zone on Lake Toho are densely vegetated and dominated by Pontederia communities, having low diversities, highly organic soils and occasionally forming floa ting mats. These communities are located primarily between 57 and 108 cm (22 and 42.5 in) in water depth at maximum pool, beyond which lie sandy substrates and seve ral communities of floating leaved and submersed aquatics. The formation of such distinct zones of vegetation is no doubt aided by the stable water levels maintained since the lake was impounded in 1964. For example, lake stage

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60 data for the 10 years prior to the dry down in itiated in November of 2003, show that the present dense zone of Pontederia was flooded 82-100% of the time. The highest water levels over this period covered the shallow e dge of this community with up to 0.88 m of water, while the lowest water levels never exposed the deep edge, remaining flooded at a minimum depth of 60 cm. However, if we look at the stage data for a 10-year period prior to the impoundment (1950-1960), this same zone had a hydroperiod of 66%–90%, drying out much more frequently than at present. In fact, the lowest water levels dropped below even the deepest edge of this commun ity by nearly 0.5 m. The biggest contrast, however, between historic and present day water levels, were the flood stages. The highest water levels over th e historical 10-year period would have flooded even the shallowest edge of this community by almost 2 m. Such an astatic environment would surely limit the ability of species like Pontederia to dominate large sections of shoreline, with droughts encouraging germination of grass species and flood waters ripping loose floating mats. It is clear from the results of this study that the Pontederia community has benefited from the stabilized lake levels and has increased its shoreward and possibly lakeward extent since impoundment. Previous Studies Vegetation studies in the early 1970s (H olcomb and Wegener 1971) and late 1950s (Sincock et al. 1957) recorded species freque ncies along transects that ran perpendicular to shore and spanned the entire extent of the littoral zone, providing indundation tolerances or distributional ranges of each species. The only previous study that compared pre and post muck-removal habitats in 1986 (Moyer et al. 1989) also looked at individual species responses by recordi ng their frequency of occurrence along four transects. These data were presented as the frequency of several common species and

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61 gave no reports of how they were distribute d along depth gradients. No quantitative measures were recorded and evidence of increased/decreased densities or changes in structural habitat characteris tics could not be identified. Though these three studies were conducted in different ar eas of the lake and used different techniques, a general trend in habitat change is still eviden t. The earliest study, prior to the impoundment of th e lake in 1964, showed a higher diversity of grassy species in the zones now targeted for restoration, most of which no longer occur. However, Panicum repens and Luziola fluitans were among the most freque nt in shallow areas even then. In the early 1970’s, Pontederia cordata and Polygonum spp. had appeared at low frequencies and were described as occurri ng in narrow bands just below the low pool line. It was reported that Luziola and Panicum were the dominant plants in the zones of periodic inundation and together with Pontederia served as good spawning habitat for sport fish, including largemouth ba ss. By the 1986 study, however, Pontederia, Polygonum and Alternanthera philoxeroides were among the most frequently encountered species, along with Luziola, Panicum repens and Bracharia mutica These findings were more similar to the resu lts of this study, though no quantitative comparisons can be made. While Panicum repens and Luziola still dominate the shallower areas, it appears that Pontederia has moved shoreward from the mean low pool level into the zone of peri odic inundation. One reason for this may have been the dry down in 1987 that coincided with the muck re moval. Wegener et al. (1973) suggested there were substantial increases in both the densities and expansion of Pontederia following the 1971 dry down, and similar re sults probably occurred after the 1979 and 1987 dry downs. Even the transects located in scraped areas showed an almost complete

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62 rebound of Pontederia in just two years after the 1987 muck rem oval project (Moyer et al. 1989) and an even quicker response probably occurred in the unscraped areas. Management Implications The results of this study will he lp to more accurately determine Pontederia community responses to dry down and several ot her treatments. By measuring structural characteristics of the habitat targeted fo r restoration and defining the communities in terms of specific densities and biomasses, the effects of the various treatments will be quantified and much less cryptic than in previous studies. The CART model used in this study on the pretreatment data was able to predict which communities occurred in the targeted areas, given several environm ental conditions. The MRT analysis was extremely supportive of those predictions a nd community definitions, as well as their distributions among water depths soil types and site locati ons. Using the same CART and MRT analyses on data collected in the future, predictive models can be used to determine community types and responses to given treatments. For example, Figure 3-16 shows a hypothetical CART model that pred icts communities based on several factors (type of treatment applied, water depth, time since application, etc. ) that would provide managers with a valuable tool in lake rest oration. These models will be applicable to future restoration efforts on Lake Toho as well as other similar lakes in the region. With the framework implemented in this study, th e long-term monitoring programs necessary to determine the effects of these large-scale restoration efforts are now in place.

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63 Treatment Control No Herbicide Scraped Herbicide Herbicide Water Water Bulk Dens 3 4 6 5 8 7 9 11 10 12 2 1 Treatment Control No Herbicide Scraped Herbicide Herbicide Water Water Bulk Dens 3 4 6 5 8 7 9 11 10 12 2 1 Figure 3-16. A hypothetical CART model to be created following years of post-treatment data collection. With reasonable probab ilities, for example, one could predict community compositions based on the treatment applied and the location along the environmental gradients.

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64 CHAPTER 4 WHOLE LAKE MONITORING Introduction The previous chapter dealt primarily w ith the pre-restoration communities lying within the targeted ar eas of muck removal. The sampli ng techniques of that project were designed specifically to monitor the diffe rential successions of littoral communities following various treatments. Th erefore, interand intra-site variations were minimized and the sampling efforts were restricted to depth zones receiving sp ecific treatments. Beyond the treatment plots, however, similar re storation efforts are planned for most of the remaining shoreline, including muck rem oval and aggressive herb icide application to control successions. These treatments will undoubtedly have an enormous impact on the littoral communities of the lake, including thos e not specifically targeted by mechanical removal or even herbicide efforts. This emphasizes the need to monitor and document the spatial and temporal responses of the littoral zone as a whole, in addition to determining the efficacy of specific tr eatments, as discussed in Chapter 3. Previous studies of natural or artificial dry downs on Lake Toho (Wegener et al. 1973, Moyer et al. 1989) and Lake Okeec hobee (Smith and Smart 2004) have documented a rapid growth and lakeward expa nsion of several gras s and sedge species ( Eleocharis spp. Panicum hemitomon, Panicum repens, Paspalidium geminatum, Luziola fluitans etc.) in response to sediment exposur e. However, these studies generally only reported increases in frequencies and gave no estimates of changes in the structures of communities. Without such information, th ere is little known about the spatial and

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65 temporal effects of such activities. For example, was the increase in grassy species temporary or still evident y ears after flooding? Were the effects similar throughout the lake and along the same depth gradients? How long, if ever, did it take for the littoral communities to rebound to pre dry down conditions and for that matter, what were the pre and post dry-down communities? More questions arise as the intensity of re storation efforts incr ease and now include mechanical removal and aggressive herbicide applications in additi on to dry downs. The ultimate goal of this study was to establish a long-term sampling protocol to determine quantitatively, the spatial and temporal responses of littoral communities throughout Lake Toho. Upon establishment, the object ives were to 1) define preexisting communities and their compositions and 2) identify the underlying environmental gradients associated with their distributions. Methods Study Sites Lake Toho has a highly variable littoral zone in terms of slopes, wave energies, shoreline activities, and so on, and the result ant communities differ as well. To capture this variability, five monito ring sites were selected from the less-developed, southern two-thirds of the lake (Figure 4-1). Sites1, 3 and 4 were located in broad, gently sloping areas of shoreline, presumably more sedime ntary in nature and subject to lower wave energies, while Sites 2 and 5 were located on much steeper, higher energy areas of shoreline. Additionally, all s ites were subjected to grazi ng pressures with the exception of Sites 4 and 5. The boundaries of each site were determined by placing a 60-ha rectangle on DOQQ’s with 1-m2 resolution (1999) and bathymetric (R emetrix) layers in ArcView GIS

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66 3.2 software. The area of the rectangle stayed constant but the sh ape was altered such that it encompassed the zone of 0–2 m in de pth (0–6 ft) (i.e., the sites on steep slopes were stretched along the shore while those on gentle slopes extended much farther into the lake). # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S N E W SSite 3 1 1 0 0 m e t e r s Site 4 Site 1 Site 2 Site 5 Site 3Sampling locations 0 –6 ft depth classes # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S N E W SSite 3 1 1 0 0 m e t e r s Site 4 Site 1 Site 2 Site 5 Site 3 # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S # S N E W SSite 3 1 1 0 0 m e t e r s Site 4 Site 1 Site 2 Site 5 Site 3 Site 4 Site 1 Site 2 Site 5 Site 3Sampling locations 0 –6 ft depth classes 0 –6 ft depth classes Figure 4-1. Five study site locations, each en compassing the 0–2 m depth zone. Sites 4 and 5 were located on ungrazed shorelines and Sites 2 and 4 were located on steep slopes. Each site contained 18 sa mple locations, stratified by six depth classes, with two samples occurring in each. Vegetation Sampling Sampling locations were stratified by si x depth classes and were located on maximum slopes of 30 cm change over 30 m in distance. This was accomplished by placing 30x30 m grids onto the same GIS bathym etry layer and randomly selecting three grid numbers from each depth class (Chapter 3). Coordinates of the centroids were

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67 recorded and the sample was located in the field with a GPS (Global Positioning System) on each sampling occasion. A total of three samples per depth zone were selected, resulting in 18 per site and 90 on the lake (F igure 4-1). These locations were sampled twice a year during high (winte r) and low (summer) water periods, in June and December of 2003, and May and December of 2004. Vegetation was clipped at the substrate from 0.25-m2 circular plots and sorted by species. Stem counts and biomass were recorded on sight. Before weighing, each sample was squeezed and shaken until residua l water was removed. While giving less accurate measures of biomass than dry wei ght methods, this was an efficient way to account for the overall size of an individual and combined with its stem count, the relative importance of a speci es in a particular quadrat. Importance values were calculated using the formula: (Relative Biomass + Relative Density)/2 *100 This value is not overly biased by large, few-stemmed species (e.g. Typha spp.) or small, numerous-stemmed species (e.g., Eleocharis spp.). This measure had an additional advantage since wet weights were used and undoubtedly, different species had differential amounts of water retention, even after squeezing. The Importance Values (IV’s) were relativized to each sample, eliminating potential bias of heavier weight, submersed species in one sample versus dr ier, shallow-emergent species in other samples. Data Analysis The four sampling periods during th e winter and summer of 2002–2003 yielded four repeated measures of our 90 sampling lo cations. The densities and biomasses of the species in each quadrat were added togeth er from those sampling periods and then

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68 relativized and IV’s computed. This gave an estimate of th e relative importance of each species in each quadrat over the four samp le occasions. For example, the stem counts and biomasses of species one in quadrat one were added together over the four sample times; assuming the species occurred each period, the formula would be (Sp1Q1T1+ Sp1Q1T2 + Sp1Q1T3 + Sp1Q1T4) = Importance Value The IV’s of all species were added to gether and a percentage of the total cumulative IV was calculated for each species. To reduce noise from rare species, only those with cumulative IV’s composing 95% of the total were retained for analyses. Samples were grouped based on species compositions using an agglomerative, hierarchical cluster analysis. The number of groups and th e representative species of those groups were identified us ing an Indicator Species An alysis (ISA). A Nonmetric Multidimensional Scaling (NMS) ordination was used to illustrate the relationships between groups and to show their distribu tion along the water dept h gradient. Detailed descriptions of these analyses are provided in the Methods secti on of Chapter 3. A Classification And Regression Tree (CAR T) analysis was performed to see how accurately the communities defined by the cluste r analysis could be predicted using water depth, study site, grazing influence and whet her or not a sample occurred on a floating mat as environmental variables. A Multivariate Regression Tree (MRT) was then created to compare the communities defined by the clus ter analysis to those defined by species IV’s and their positions along environmental gr adients. Detailed descriptions of these methods are provided in Chapter 3. Results Of the 52 species recorded over the four sampling periods, 20 comprised the top 95% of the cumulative importance values (Figure 4-2, Appendix B). Our summed

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69 dataset resulted in 90 samples by 20 species, which was divided into six communities based on the Cluster Analysis. The number of clusters was chosen based on the ISA, where the group with the highest number of sp ecies with indicator values greater than expected by chance was selected. With six groups, 14 of the 20 species had p-values <0.05 (Table 4-1). The ISA identified the fo llowing species as strong indicators of those groups: Luziola fluitans and Panicum repens : (LUZFL_PANRE) Typha spp.: (TYPSP) Pontederia cordata: (PONCO) Hydrilla verticillata and Ceratophyllum spp .: (HYDVE_CERSP) Nuphar luteum : (NUPLU) Paspalidium geminatum : (PASGE) The NMS ordination resulted in a thr ee dimensional solution, cumulatively explaining 0.739 percent of the variation in our dataset. Axis 1 explained the majority, 0.392, with Axes 2 and 3 explaining 0.195 a nd 0.152, respectively. For illustrative purposes, only the two most important dimens ions were displayed. Pearson and Kendall correlation coefficients showed a fairly str ong correlation of water depth to Axis 1 (r2 = 0.576) and a slight corr elation to Axis 2 (r2 = 0.307). Figure 4-3 s hows a joint plot of sample units in species space with the water depth correlation vector. The distance between sample units is repres entative of the dissimilarities in their species compositions, with like samples grouped and unlike samples separated. The correlation of water depth to Axis 1 and the direction of the vector sugge st that the samples lo cated on the right side of the graph occur in deeper water than thos e on the left. The numb ers of species that occurred in each sample before rare species were deleted was also plotted as a diversity, or richness measure. Richness was found to be slightly correlated to Axis 2, simply

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70 0 5 10 15 20 25UNPAW S AGLT CR AGR U NG R SA HAB RE UF P OLY N E L L U POL D E A ND RO EICCR SAGLN SESPU AXOFU LU DR E P OL HY L Y M S P N Y MA Q CHARA B AHIA HYDSP CERS P B RAM U NY M OD NUPLU L UZ FL PONCOSpecies% of Cumulative IV 95% of Total 20 Species 52 Total Species 0 5 10 15 20 25NY MAQ SCICA C HARA L UDSP BA HI A PANHE HYDSP BACCA CE RS P A LTPH BRAMU ELE SM NYMOD P A NRE N UP LU TYPSP LUZFL PASGE P ONCO HYDV ESpecies% Cumulative I V 0 5 10 15 20 25UNPAW S AGLT CR AGR U NG R SA HAB RE UF P OLY N E L L U POL D E A ND RO EICCR SAGLN SESPU AXOFU LU DR E P OL HY L Y M S P N Y MA Q CHARA B AHIA HYDSP CERS P B RAM U NY M OD NUPLU L UZ FL PONCOSpecies% of Cumulative IV 95% of Total 20 Species 52 Total Species 0 5 10 15 20 25UNPAW S AGLT CR AGR U NG R SA HAB RE UF P OLY N E L L U POL D E A ND RO EICCR SAGLN SESPU AXOFU LU DR E P OL HY L Y M S P N Y MA Q CHARA B AHIA HYDSP CERS P B RAM U NY M OD NUPLU L UZ FL PONCOSpecies% of Cumulative IV 95% of Total 20 Species 52 Total Species 0 5 10 15 20 25NY MAQ SCICA C HARA L UDSP BA HI A PANHE HYDSP BACCA CE RS P A LTPH BRAMU ELE SM NYMOD P A NRE N UP LU TYPSP LUZFL PASGE P ONCO HYDV ESpecies% Cumulative I V Figure 4-2. Percent of cumulative Importan ce Value (IV) for each species, with 20 comprising 95% of the total. See Appendix B for a list of these 20 and the 32 less common species. showing that the samples near the bottom of the graph generally had more species than those near the top. Additionally, the weighted av erage species scores were plotted along these axes, showing the average location of each species along the measur ed gradient (Figure 4-4). Keeping in mind that water depth increases fr om left to right along Axis 2 and diversity increases from top to bottom along Axis 1, we can suggest that genera lly, the species to the right occur in deeper water, while the sp ecies on the top of the graph occur in fairly uniform, or even monotypic communities. Th is indicates that when those species occurred, diversity tended to be lower, or they tended to dominate each quadrat they were found in.

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71 Table 4-1. Indicator values of species in the Lake-Monitoring study, with values ranging from 0-100. P-values Spp code ID Cluster 1 2 3 4 5 6 0.019 ALTPH 3 20 4 33 0 0 0 0.057 BACCA 1 23 1 0 2 1 0 0.033 BAHIA 1 25 0 0 0 0 0 0.004 ELESM 1 37 0 0 0 0 1 0.177 HYDSP 3 2 1 18 0 0 0 0.001 LUZFL 1 92 0 0 0 0 0 0.516 PANHE 1 14 0 10 3 0 0 0.001 PANRE 1 76 0 0 1 0 0 0.38 BRAMU 6 2 0 3 0 0 14 0.001 PONCO 3 8 4 75 0 0 0 0.001 TYPSP 2 0 93 2 0 0 0 0.537 LUDSP 6 0 0 2 0 0 9 0.002 CERSP 4 0 4 0 53 23 4 0.001 HYDVE 4 0 1 0 77 16 4 0.002 PASGE 6 0 0 0 13 17 44 0.001 NUPLU 5 0 2 0 0 85 0 0.058 SCICA 6 0 0 0 0 0 17 0.04 NYMAQ 5 0 0 0 5 22 2 0.08 NYMOD 6 0 2 0 0 6 18 0.627 CHARA 5 0 0 0 3 5 0 Species with high indicator values are highlighted accordingly and are used as community descriptors for each group. The indicators species’ distributions in relation to these grad ients can be shown by scaling the symbols of the sample units they occurred in according to their IV’s; the larger the symbol, the higher th e IV in that sample. Figur es 4-5 and 4-6, respectively, show how Panicum repens and Luziola occur frequently and w ith high values in the shallower depth zones as well as with higher diversities. Pontederia cordata however, shows significant occurrence in other comm unities as well, specifically with the LUZFL_PANRE community at the deeper end of their range (Figure 4-7). Many of the samples in the deeper water had large amounts of Hydrilla (Figure 4-8) and a few were dominated by Paspalidium geminatum (Figure 4-9). The grouping of the HYDVE_CERSP and PASGE clusters and the o ccurrence of both species in either group shows the similarity and spatial prox imity of these two communities.

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72 Depth Diverse Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE Depth Diverse Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE Depth Diverse Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE Figure 4-3. Lake-Monitoring Study or dination plot of sample un its in species space, color coded by community. Distances between samples is representative of the dissimilarities in species compositions. Joint plots of correlated environmental variables are displayed as red vectors, based on Pearson and Kendall correlation coefficients. The di rection and length of the vector is representative of the direc tion and strength of the vari able’s relationship to the corresponding axis.

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73 ALTPH BACCA PASNO ELESM HYDSP LUZFL PANHE BRAMU PONCO TYPSP LUDSP CERSP HYDVE PASGE NUPLU SCICA NYMAQ NYMOD CHASP Depth Diversity Axis 1Axis 2 PANRE Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE ALTPH BACCA PASNO ELESM HYDSP LUZFL PANHE BRAMU PONCO TYPSP LUDSP CERSP HYDVE PASGE NUPLU SCICA NYMAQ NYMOD CHASP Depth Diversity Axis 1Axis 2 PANRE ALTPH BACCA PASNO ELESM HYDSP LUZFL PANHE BRAMU PONCO TYPSP LUDSP CERSP HYDVE PASGE NUPLU SCICA NYMAQ NYMOD CHASP Depth Diversity Axis 1Axis 2 PANRE Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE Figure 4-4. Weighted average species scores overlayed onto the Lake-Monitoring study NMS ordination. Indicator species are highlighted and color coded according to cluster (community) membership. Locations are representative of each species’ average location along the measured environmental gradients.

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74 Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE PANRE Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE PANRE Figure 4-5. Importance values of Panicum repens in the Lake-Monitoring samples, as plotted by the NMS ordination. Larger symbols represent la rge IV’s within that sample. Samples are co lored according to community.

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75 Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE LUZFL Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE LUZFL Figure 4-6. Importance values of Luziola fluitans in the Lake-Monitoring samples, as plotted by the NMS ordination. Larger symbols represent la rge IV’s within that sample. Samples are co lored according to community.

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76 Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE PONCO Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE PONCO Figure 4-7. Importance values of Pontederia cordata in the Lake-Monitoring samples, as plotted by the NMS ordination. Larger symbols represent la rge IV’s within that sample. Samples are co lored according to community.

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77 Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE HYDVE Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE HYDVE Figure 4-8. Importance values of Hydrilla verticillata in the Lake-Monitoring samples, as plotted by the NMS ordination. Larger symbols represent la rge IV’s within that sample. Samples are co lored according to community.

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78 Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE PASGE Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE PASGE Figure 4-9. Importance values of Paspalidium geminatum in the Lake-Monitoring samples, as plotted by the NMS ordina tion. Larger symbols represent large IV’s within that sample. Sample s are colored according to community.

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79 Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE NUPLU Axis 1Axis 2 Community LUZFL_PANRE TYPSP PONCO HYDVE_CERSP NUPLU PASGE NUPLU Figure 4-10. Importance values of Nuphar luteum in the Lake-Monitoring samples, as plotted by the NMS ordination. Larger symbols represent la rge IV’s within that sample. Samples are co lored according to community. Nuphar luteum also overlaps with the HYDVE_C ERSP community and occurs in the TYPSP community as well (Figure 4-10). Th e large spread of samples in the TYPSP community suggests Typha occurs over a broad range of water depths and occasionally overlaps with either the PONCO or NUPLU communities. The PONCO, TYPSP and NUPLU communities occur near the top of axis one, indicating lower diversities where these species dominate.

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80 The CART model produced a rather complex tree, prune d to 11 groups. At this level, 68.8% of the variation was explained by the model, with a 40% misclassification rate. There were essentially three la rge groups formed; LUZFL_PANRE community occurring in <63 cm (25 in) of water, a mix of PONCO communities and transitional groups between 63 and 127 cm (25 and 50 in) of water, and a predominantly HYDVE_CERSP community occurring at depths greater than 127 cm (50 in) (Figure 4-11). There were several site differences de lineated in the tree, most separating Sites 2 and 4 from the others. This separation occurred at both above and below 127 cm in water depth, indicating significant site variation at se veral depths. Sites 2 and 4 were split from the others at depths <127 cm due to a less robust PONCO community. The terminal groups of these sites showed a mixture of either LUZFL_PANRE or HYDVE_CERSP with the PONCO communities, while Sites 1, 3, and 5 displayed the more typical, moncultural PONCO group. At depths >127 cm, Sites 2 and 4 were split from the others due to a more dominant PASGE community, with mixes of TY PSP and HYDVE_CERSP co mmunities occurring at various depths. Sites 1, 3, and 5 however, all had robust HYDVE_CERSP communities at >127 cm in water depth. The MRT was pruned to eight leaves and produced similar results to the CART (Figure 4-12). The four most abundant communities were Luziola fluitans at <63 cm (25 in) in water depth, a robust Pontederia community between 63 and 117 cm (25 and 46 in), dominant Hydrilla between 117 and 158 cm (46 and 62 in), and a codominant community of Hydrilla and Paspalidium geminatum at depths >158 cm (62 in). These

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81 results were confirmatory of the CART mode l, with the same dominant species occurring at similar depth locations. Water <63cm (25in) Water >127cm (50in) Site:1,3,5 Water >178cm (70in) Site:2 <145cm Site:2,4 >89cm Site:3,5 Water >63cm (25in) Site:2,4 <196cmSite:4 >145cm Site:1,3,5 <89cm Site:1 LUZFL_PANRE (22) HYDVE_CERSP (24) HYDVE_CERSP (3) PASGE (3) HYDVE_CERSP (5) PASGE (3) TYPSP (5) HYDVE_CERSP (4) LUZFL_PANRE (5) PONCO (13) TYPSP (3)HYDVE_CERSP LUZFL_PANRE NUPLU PASGE PONCO TYPSPError : 0.312 CV Error ( pick ) : 0.562 SE : 0.0726 Missclassrates : Null = 0.711 : Model = 0.222 : CV = 0.4 Water <127cm (50in) Water <178cm (70in) >196cmImportance of Predictor Variables Water Depth 100 Floating32.8 Site22.8 Water <63cm (25in) Water >127cm (50in) Site:1,3,5 Water >178cm (70in) Site:2 <145cm Site:2,4 >89cm Site:3,5 Water >63cm (25in) Site:2,4 <196cmSite:4 >145cm Site:1,3,5 <89cm Site:1 LUZFL_PANRE (22) HYDVE_CERSP (24) HYDVE_CERSP (3) PASGE (3) HYDVE_CERSP (5) PASGE (3) TYPSP (5) HYDVE_CERSP (4) LUZFL_PANRE (5) PONCO (13) TYPSP (3)HYDVE_CERSP LUZFL_PANRE NUPLU PASGE PONCO TYPSP HYDVE_CERSP LUZFL_PANRE NUPLU PASGE PONCO TYPSP LUZFL_PANRE NUPLU PASGE PONCO TYPSPError : 0.312 CV Error ( pick ) : 0.562 SE : 0.0726 Missclassrates : Null = 0.711 : Model = 0.222 : CV = 0.4 Water <127cm (50in) Water <178cm (70in) >196cmImportance of Predictor Variables Water Depth 100 Floating32.8 Site22.8 Importance of Predictor Variables Water Depth 100 Floating32.8 Site22.8 Figure 4-11. CART model of Lake-Monito ring community distributions along the measured environmental gradients. This model was pruned to 11 leaves based on a cost complexity pruning curve, se lecting the smallest tree within one standard error of the best. The numbers of samples in each leaf are shown in parentheses below each bargraph, which shows the compositions of communities within each leaf (e.g., all 22 samples in the left-most leaf are the LUZFL_PANRE community). One interesting difference between the MRT and CART model was the separation of grazed and un-grazed sites at <63 cm in wa ter depth in the MRT. Sites 4 and 5 had no grazing pressures and the commun ities were much more diverse, with the terminal node represented by a suite of species ra ther than one i ndividual, including Eleocharis spp., Bacopa caroliniana, Bracharia mutica, Panicum repens, Paspalum notatum and

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82 Pontederia The other substantial site differenc es occurred between 117 and 158 cm (46 and 62 in) in depth, with Site s 3 and 4 having significant Nymphaea odorata and Typha communities while Sites 1, 2, and 5 were dominated by Hydrilla Water <117cm (46in) Site:4,5Site:2 Water <158cm (62in) Site:1,2,5 <145cm (57in) Water >63cm (25in) Site:1,2,3Site:1,3,4,5 Site:3,4 >145cm (57in) ALTPH BACCA BAHIA ELESM HYDSP LUZFL PANHE PANRE BRAMU PONCO TYPSP LUDSP CERSP HYDVE PASGE NUPLU SCICA NYMAQ NYMOD CHARA •(8) (14) (4) (19) (11) (6)(5)(23)Error : 0.537 CV Error ( pick ) : 0.814 SE : 0.0757Water <63cm (25in) Water >117cm (46in) Water >158cm (62in)UngrazedDiverse Community PONCO HYDVE_PONCO LUZFL HYDVE NYMODTYPSP PASGE_HYDVEImportance of Predictor Variables Water Depth 100 Site63.8 Floating14.9 Water <117cm (46in) Site:4,5Site:2 Water <158cm (62in) Site:1,2,5 <145cm (57in) Water >63cm (25in) Site:1,2,3Site:1,3,4,5 Site:3,4 >145cm (57in) ALTPH BACCA BAHIA ELESM HYDSP LUZFL PANHE PANRE BRAMU PONCO TYPSP LUDSP CERSP HYDVE PASGE NUPLU SCICA NYMAQ NYMOD CHARA •(8) (14) (4) (19) (11) (6)(5)(23)Error : 0.537 CV Error ( pick ) : 0.814 SE : 0.0757Water <63cm (25in) Water >117cm (46in) Water >158cm (62in)UngrazedDiverse Community PONCO HYDVE_PONCO LUZFL HYDVE NYMODTYPSP PASGE_HYDVE Water <117cm (46in) Site:4,5Site:2 Water <158cm (62in) Site:1,2,5 <145cm (57in) Water >63cm (25in) Site:1,2,3Site:1,3,4,5 Site:3,4 >145cm (57in) ALTPH BACCA BAHIA ELESM HYDSP LUZFL PANHE PANRE BRAMU PONCO TYPSP LUDSP CERSP HYDVE PASGE NUPLU SCICA NYMAQ NYMOD CHARA ALTPH BACCA BAHIA ELESM HYDSP LUZFL PANHE PANRE BRAMU PONCO TYPSP LUDSP CERSP HYDVE PASGE NUPLU SCICA NYMAQ NYMOD CHARA •(8) (14) (4) (19) (11) (6)(5)(23)Error : 0.537 CV Error ( pick ) : 0.814 SE : 0.0757Water <63cm (25in) Water >117cm (46in) Water >158cm (62in)UngrazedDiverse Community PONCO HYDVE_PONCO LUZFL HYDVE NYMODTYPSP PASGE_HYDVEImportance of Predictor Variables Water Depth 100 Site63.8 Floating14.9 Importance of Predictor Variables Water Depth 100 Site63.8 Floating14.9 Figure 4-12. Communities identified in th e Lake-Monitoring study by IV’s and their associated environmental variables, using the MRT analysis. This confirmatory analysis shows speci es groupings and distributions along environmental gradients, independent of the cluster analysis. The numbers of samples in each leaf are shown in parentheses below each bargraph, which shows the compositions of sp ecies within each leaf. Table 4-2 details the species variance amount explained by the tree, and the species responsible for e ach split of the MRT. Hydrilla comprised 22.5% of the total species variance, of which 13.03% was explaine d by the tree, 5.96% in the first split. Also responsible for the first split was Pontederia with 3.97% of its variance explained. This simply means that the abundances of Hydrilla and Pontederia were both highly

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83 variable among samples, and largely dete rmined community structure as well. Pontederia (4.14%) and Luziola (3.35%) determined the second split, while Luziola (2.62%), Hydrilla (1.74%), Paspalidium (3.26%), Hydrilla (5.13%) and Typha (1.71%) determined the remaining splits, consecutivel y. Summarily, these five species comprised 73.4% of the total species variance, 40.1% of which was explained by the tree. Cumulatively, then, these species comprised 87% of the variance explained by the tree (40.1 of 46.3). This supports the results of the cluster and indicat or species analysis which identified these species as indicative of the inherent community structure in our study areas. Table 4-2. Tabulation of species variance for th e MRT analysis of Lake-Monitoring sites. Species <117cm <63cm Site:4,5 Site:2 <158cm Site:1,2,5 <145cm Tree Spp Total ALTPH 0.06 0.01 0 0 0 0 0 0.07 0.34 BACCA 0.01 0.04 0.04 0 0 0 0 0.1 0.7 BAHIA 0.02 0.05 0.04 0 0 0 0 0.11 1.06 ELESP 0.13 0.02 0.03 0.02 0 0 0 0.2 2.12 HYDSP 0 0 0 0 0.05 0.06 0 0.12 1.03 LUZFL 1.91 3.35 2.62 0.07 0 0 0 7.95 11.19 PANHE 0 0 0 0 0 0.01 0 0.02 0.47 PANRE 0.38 0.65 0.13 0 0 0.02 0 1.18 3.12 BRAMU 0.07 0.05 0.31 0.01 0 0 0 0.44 2.62 PONCO 3.97 4.14 0 0.75 0.07 0.12 0 9.05 16.22 TYPSP 0.04 0.87 0 0.37 0.27 0.71 1.71 3.98 11.22 LUDSP 0.02 0.04 0 0.02 0 0 0 0.07 1.52 CERSP 0.03 0 0 0.01 0 0.01 0 0.06 0.3 HYDVE 5.96 0.2 0 1.74 0 5.13 0 13.03 22.51 PASGE 2.77 0 0 0 3.26 0.01 0.04 6.08 12.24 NUPLU 0.55 0 0 0 0.01 0.01 0.16 0.73 6.07 SCICA 0 0 0 0 0.01 0 0 0.02 0.71 NYMAQ 0.01 0 0 0 0 0 0 0.01 0.18 NYMOD 0.28 0 0 0 0.54 1.11 0.93 2.87 5.21 CHARA 0.02 0 0 0 0.03 0.07 0.11 0.22 1.17 Split total 16.25 9.42 3.17 3 4.27 7.25 2.96 46.32 100 Column totals represent the contribution of each split to the amount of variation explained by the tree. Row totals represen t the amount of species variance explained by the tree (tree total) and the contribution of each species to total species variance, respectively. The most important split in the tree occurred at 117 cm in water depth, accounting for 35% (16.25% of 46.32%) of the variation explained by the tree. The second most

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84 important split occurred at 63 cm in water depth, accounting for 20.3% (9.42% of 46.32%) of the variation. These two splits represent the most abrupt changes in communities in terms of species compositions and their distribution along the depth gradient. Discussion Community Descriptions There were six distinct comm unities identified within the littoral zone of Lake Toho during our study. Based on the NMS and CART analyses and confirmed by the MRT, most of these communities were distinctly distributed along the depth gradient, with the LUZFL_PANRE community dominating betwee n the high and low pool water lines, dense PONCO communities occu rring just above and below the low pool line, and the deeper water generally having either HYD VE_CERSP or PASGE communities. TYPSP and NUPLU communities were also present but were less common and more patchily distributed in the deeper water zones. Average species richness for each community ranged from 9.5 species per sample in the LUZFL_PANRE community to 3.5 in the HYDVE_CERSP community, following a general decreasing trend with increasing water depths. The exception to the rule was the NUPLU community that ha d the deepest average depth of any community (159 cm) and the second highest richness, with an average of 6.0 species per sample. However, other deep water communities (HYDVE_CERSP and PASGE) had lower average depths than NUPLU due to their broader range of distribution, not necessarily because they never occurred in deeper water. However, th e relatively high numb er of species in the few NUPLU samples is of interest and may he lp to explain the fr equent visitation of these habitats by anglers.

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85 The dominant PONCO community had higher average richness than the HYDVE_CERSP (3.5), TYPSP (3.8) and PASGE (3.8) communities, with an average of 4.8 species per sample. However, if the fl oating mat samples were excluded, having an average of 7.0 species per sample, the P ONCO community richness fell to 3.6, the second lowest of all communities. The CART mode l found that between 63 and 127 cm (25 and 50 in ) in water depth, the PONCO commun ity was extremely dominant in 13 of 25 samples and had a significant presence in all 25, occurring with HYDVE_CERSP, LUZFL_PANRE, and TYPSP communities at these depths. The MRT confirmed these results, showing Pontederia as the single dominant spec ies between 63 and 117 cm (25 and 46 in) in 19 of 23 samples and was still abundant in the remaining four samples, occurring with Hydrilla These two species do not actually occur in the same area, spatially, but do occupy the same depths on occasion. Their grouping in both the CART and MRT analyses is representative of the transitional zone between the dense, leading edge of the PONCO floating communities a nd the open water, submersed communities, where sharp, distinct boundaries separate the two. The fact they do not overlap spatially is evident in the NMS diagrams of species IV’s or weighted species averages. Notice that the samples with high IV’s of either species do not overlap and th at the two are very distant from each other in the ordination, showing distinctly different compositions between samples containing either species. Variations in communities by site were delineated in CART and confirmed in the MRT, with each defining similar patterns. The CART model found th at Sites 2 and 4 had more dominant PASGE communities in deeper water (>127 cm) than Sites 1, 3, and 5, which were dominated by HYDVE_CERSP co mmunities. The MRT produced slightly

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86 different terminal groups, s howing a mixed community of Paspalidium and Hydrilla in all 23 samples (100%) in depths >158 cm, rega rdless of site, and th at site differences occurred between 117 and 158 cm (46 and 62 in), with Hydrilla dominating those depths at Sites 1, 2 and 5. Sites 3 and 4 were found to have Nymphaea communities between 117 and 145 cm and Typha communities between 145 and 158 cm. The NMS diagram of species IV’s shows the regular occurrence of Hydrilla and Paspalidium at the same depths and even in the same samples (Figures 4-8 and 4-9). Additionally, the very close proximity of the two communities in the ordination, HYDVE_CERSP and PASGE, shows the similarities in their species compositions. It is probable that these two species occur together more often than the CART model suggests. Most of the deeper water site differences were a result of the clumped distributions of the communities at those depths. While Paspalidium and Hydrilla tended to occur throughout the deep water, the floating leaved and cattail communities were much sparser and patchily distributed. Panicum hemitomon and Scirpus californicus were also patchy, and did not occur frequently enough in our samples to be classified as their own communities. While the shoreline slope dr amatically affected the width of the communities between sites, their compositions or distributions by depth did not seem to differ consistently. Another interesting site difference deli neated by the MRT was between grazed and ungrazed sites at depths <63 cm. While ther e was no substantial difference in average species richness between th e sites (9.5 and 11.7, respectiv ely) there were no singly dominant species throughout th e shallow depths of the ungraz ed areas. The bar graphs under the terminal groups of the MRT show th is difference well, as the eight samples

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87 from the ungrazed sites had several frequent ly dominant species, while the 14 samples from the grazed sites were completely dominated by Luziola (Figure 4-12). The visual difference between the grazed and ungrazed sh orelines was quite striking, with species like Bracharia mutica Hibiscus grandiflorus and Ludwigia spp. much more prevalent in the ungrazed areas. Apparently, the low st ature and carpet forming growth habit of Luziola allows it to escape herbivory while be nefiting from the absence of canopy grasses eliminated by grazing. Without it, other sp ecies most likely tower above and shade out Luziola resulting in several taller, dominant sp ecies in the ungrazed communities. Previous Studies The studies conducted in the late 1950s (Sincock et al. 1957) and early 1970s (Holcomb and Wegener 1971) suggest the li ttoral zone of Lake Toho has changed substantially over the last 30 years. Though their techniques did not provide quantitative estimates or community descriptions, general di fferences can be detect ed. Prior to lake impoundment, for example, Pontederia did not occur in the vegetation studies and species like Psilocarya, Stenophyllus, Echinocloa, and Fuirena were fairly common in the seasonally inundated areas of shoreline. Hydrilla was not even documented until 1972, with species like Valisneria occurring in the deeper water. By 1970, however, Alternanthera philoxe roides, Polygonum spp., and Pontederia had become more common, though still described as occurring in narrow bands below the low pool line. Scirpus californicus was reported to exist in stands up to several acres in size in deeper water and Paspalidium was described as abundant. Th ese descriptions do not provide comparable estimates of the littoral communities to our studies, but do depict major changes.

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88 While Panicum repens and Luziola have long been recorded in the shallow communities, they may be more dominant today than historically. Both the 1971 and 1987 dry down studies seemed to substa ntially increase the frequencies of Panicum repens (Wegner et al. 1973 and Moyer et al. 19 89), an effect also documented on Lake Okeechobee (Smith and Smart 2004). The biggest difference lies within the Pontederia community, which has seemingly pushed the Panicum repens, Luziola, and Eleocharis spp. communities shoreward with stabilized water levels. Whether the large-scale removal of this community is an effective m eans in reestablishing grassy species in its stead is not yet known. The implementation of long-term sampling protocols and the detailed descriptions of pre-treatment co mmunities provided by this study will help to answer that question.

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89 CHAPTER 5 SUMMARY Communities The vegetation samples we collected from June 2002 through December 2003 provided detailed information on the compos ition and distribution of plant communities that occurred during this period. Unlike prev ious studies, we sought to define, analyze, and monitor vegetation at a community level rather than by indivi dual species and to collect quantitative measures of habitat quality rather than frequencies or percent cover estimates. The communities we defined were based on biomasses and densities of species, giving strong representation of the ha bitat and compositions as they occurred. The results of our two studies were very si milar, showing distinct zones of vegetation distributed along depth and soils gradients. The communities defined by the Cluster Analyses and their predicted distributions with the CART models were well supported by the confirmatory MRT analyses performed in both studies. Had soils data been collected for the Lake-Monitoring study covered in Chap ter 4, stronger predic tions of community distributions would have been available for areas beyond those targeted for muck removal. These results are based on the latest multivariate community techniques, using far more descriptive measures of the vegetati on characteristics than collected previously. Such descriptions are the first of their kind for Lake Tohopekaliga, and the resultant predictive models may eventually be applic able to other lakes undergoing restoration activities. The pre-treatment littoral comm unities defined by this study are described below.

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90 Shallow Grasses and Sedges These communities generally occurred in depths of less than 60 cm at high pool stage, having a 10-year hydrope riod of roughly 25%–85% (based on lake stage data from 1993–2003). The dominant species in this commun ity varied over small changes in water depth, with considerable overlap between the three most important species. The shallowest group was mainly comprised of several species of Eleocharis and then shifted to Panicum repens and Luziola fluitans as depths increased. Luziola was the single most important species of the three except along gr azed shorelines, where it was virtually nonexistent. The Luziola community occurred over a broade r range of soil properties than the others, with values ra nging from 4.8–13.5% organic materi al. This community had the highest average species richne ss, ranging from 2–23 species per 0.25-m2 quadrat, with an average of nearly 10. High sp ecific diversities ar e common in boundary communities lying within seasonally inundated areas. The ungrazed sections of shor eline had high values of Panicum repens and Eleocharis spp. as well, but were not singly dominan t as in the grazed areas, occurring more frequently with Bacopa caroliniana, Hibiscus grandiflora and Bracharia mutica These ungrazed shorelines differed in that no one or two individuals completely dominated the communities. Dense Emergents Occurring just above the lo w pool line and extending we ll into the continuously flooded zone (60–120 cm, or 24–48 in) Pontederia cordata formed an extremely robust community. There were as many as 20 individu al plants (not just stems) sampled in a single 0.25-m2 quadrat, with wet biomasses as high as 3.1 kg and stems reaching over 1 m in height. All of the floating mats en countered during our studies occurred within

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91 this community as well, lying at the deeper extent of its range. The average number of species occurring on these ma ts was 9.0, ranging from 5–18 per sample. Without the inclusion of the mats in the Pontederia community, average richness fell from 5.7 to 4.9 species per sample. This value is still higher than any other community occurring in deeper water, with the exception of floating-leaved communities. The soils in the Pontederia group varied significan tly, from 3.6–94.9% organic matter and from 0.03–0.82 g/cm3 bulk densities. This was a result of the large depth range this species occurred in, from the edge of the grassy communities in the sandier, shallow sections of shoreline to the submersed and floating-le aved communities in deeper water, where it formed organic mats in depths greater than 1 m. This community seems to have become more robust and expanded shor eward even since the late 1980s, and is far more abundant than recorded in the 1950s a nd 1970s. While water level stabilization is an obvious factor in its expansion, evidence fr om previous studies s uggests artificial dry downs may have increased its lakeward extent as well. Cattails Typha spp. were patchily distributed al ong the deep water edge of the Pontederia community, forming extremely dense, monoc ultural communities, with the lowest average species richness (3.8) of any other group. This community was too infrequently encountered in our Treatment-Selections study, generally becoming dominant between 120 and 180 cm (48 and 71 in) in depth, and no soil cores were co llected. Of the approximately 50 sample locations within this depth range, only eight were identified as predominantly Typha communities. This species is evidently extremely vulnerable to drought, which suggests it has probably expanded in the 13 years of flooded, stabilized

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92 conditions on the lake since the 1987 dry down, though no comparisons to previous studies are available. Floating Leaved Communities This group occurred over a wide range of water depths (20–180 cm, or 9–70 in) occurring infrequently within dense Pontederia communities but was most dominant just beyond the deep water extent of this group (> 110 cm). Two common species collectively formed this community, Nymphaea odorata and Nuphar luteum though they rarely occurred in the same sample. While occupying the same depth zones, dense stands of either species occurred within a few meters of each other, but did not usually overlap. This is most likely due to light availabi lity or underground competition, with either species capable of densely covering the surf ace of the water and dominating the substrate with large, creeping tubers. Species richness was higher for this group th an any other, with the exception of the shallow grassy communities, with an average of 5.9 species per sample. This was due to a large association with submersed aquatics, including Hydrilla, Ceratophyllum spp., Utricularia spp., and several grasses, including Paspalidium geminatum and Panicum hemitomon as well as other floating-leaved species, Nelumbo lutea and Nymphoides aquatica Two extremely infrequent species were located in this community, the submersed aquatic Vallisneria americana and a macroalgae, Chara spp. Deep Water Communities Several analyses distinguished between deep water communities of the submersed aquatics Hydrilla and Ceratophyllum spp. and the emergent grass Paspalidium geminatum This distinction was primar ily due to the occurrence of Hydrilla at virtually every water depth beyon d the extent of the Pontederia community, at varying levels of

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93 dominance. Occasionally, Hydrilla was the only species oc cupying heavily traveled, open water areas between Typha, Nymphaea/Nuphar and Paspalidium communities, which led to a distinct comm unity of submersed aquatics. However, the most abundant community identified by the Lake-Monitoring study in deeper water was a mix of Paspalidium and Hydrilla All 23 samples located in de pths >158 cm (62 in) in water were grouped with this community. The aver age number of species per sample was 4.0, the lowest of any group besides Typha Given that this commun ity represents the deepest extent of emergent species into the la ke, low diversities were expected. Conclusion The vegetation communities identified in this study follow the classic zonation patterns typically occurring in the transitio nal zone between terrestrial and aquatic ecosystems (Clements 1916, Odum 1971, Segal 1971) This ecotone and its associated dynamic conditions support higher diversities and productivities of the species occupying those areas than in adjacent ecosystems (O dum 1971). As conditi ons stabilize along the water depth gradient, for example, hydrostatic pressures increase, light availability and oxygen levels decrease, and the environmen t becomes increasingly harsh with fewer species adapted to such cond itions (Juge and Lachavanne 199 7). This results in lower specific diversities and distinct zonation patterns, i.e. concen tric belts running parallel to the shoreline (Segal 1971), as adapted species competitively exclude others in the harsh environment. These are the patterns s hown on Lake Toho prior to dry down, with stabilized water levels having dramatically re duced the extent of s horeline subjected to past dynamics. With the high and low pool stages reduced by at least 2 m from historical ranges, the more diverse grassy communities occupying the highly astatic shorelines of the lake have been pushed back to less th an 60 cm in depth, replaced by robust, dense

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94 bands of vegetation well adapted to the st abilized conditions. The zone of dense Pontederia identified in this study would have hi storically been stranded nearly 0.5 m above the lake level during droughts and cove red with up to 2 m of water during floods (based on the period of record from 1950–1960). Such large, historical disturbance even ts continually reduced and expanded the range and abundance of species adapted to either dry or wet c onditions, resulting in constant recession and succession, creating ex tremely diverse and dynamic environments (Mitsch and Gosselink 1993, Odum 1993). Consequently, when flood stages were dramatically reduced, so too was the pertur bation that kept these communities from reaching equilibrium, and the “pulse-stabilized subclimax” vegetation (Odum 1971) was limited to the new low pool/high pool elevations Lake managers are now creating their own large-scale disturbances in an effort to mimic the events that kept the shoreline in a state of ever changing conditions, with co mmunities reflecting those dynamics. Whether the disturbances caused by bulldozers and he rbicides can replace the effects of drought and floods is a question that will take y ears to answer. In hopes of reducing the uncertainties, we have implemented the long-term monitoring studies mentioned throughout this paper, and have provided a clear before picture of the littoral communities of Lake Tohopekaliga. 2004 Habitat Enhancement Schedule In the spring of 2004 (data collection ceased in December 2003) the water levels in Lake Toho reached a target stage of 14.8 m (48.5 ft) NGVD and heavy equipment began removing muck from the shorelines. Two of the four treatment blocks at each of the sites were scraped with bulldozers and the material was deposit ed either upland or on the lakeshore well outside of the study areas. As stated previousl y, muck removal was

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95 focused within the Pontederia community, scraping at least as far out as the deepest Pontederia plants. All vegetation, root mat and organic sediment were removed from these areas, leaving mostly sand from 30–120 cm in water depth at high pool. The plots designated for the herbicide treatment had not been completed as of August 2004, but broad-scale helicopter applications were scheduled to begin in October.

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96 APPENDIX A TREATMENT-STUDY SPECIES LIST Table A-1. Most abundant species sa mpled in the Treatment-Selection study. Species Code Scientific Name Common Name ALTPH Alternanthera philoxeroides Alligator weed AXOFU Axonopus furcatus Big carpet grass BACCA Bacopa caroliniana Lemon Bacopa BRAMU Bracharia mutica (Forssk.) Stapf Para grass CERSP Ceratophyllum spp. Coontail EICCR Eichhornia crassipes Water hyacinth ELEQU Eleocharis quadrangulata Square-stemmed Spikerush ELESP Eleocharis spp. (Small) Spikerushes HYDSP Hydrocotyle spp. Pennywort HYDVE Hydrilla verticillata Hydrilla LUDRE Ludwigia repens Red ludwigia LUDSP Ludwigia spp (leptocarpa and peruviana) Ludwigia/Water Primrose LUZFL Luziola fluitans (Michx.) Terrell & H. Robbins Watergrass (Syn. Hydrochloa caroliniensis ) LYMSP Lymnobium spongia Frog's bit NUPLU Nuphar luteum Spatterdock (Syn. Nuphar advena ) NYMOD Nymphaea odorata Fragrant water lily PANHE Panicum hemitomon Maidencane PANRE Panicum repens Torpedo grass POLHY Polygonum hydropiperoides Wild water-pepper PONCO Pontederia cordata Pickerel weed SAGLN Sagittaria lancifolia Duck potato TYPSP Typha spp. Cattails PASSP Paspalum sp. Unidentified species of Paspalum UTRSP Utricularia spp. Bladderworts Nomenclature follows that of Tobe et al. 1998

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97 Table A-2. Less abundant species samp led in the Treatment-Selection study. Species code Scientific name Common name ANDVI Andropogon virginicus Broom grass BIDLA Bidens laevis Bur-marigold CARSP Carex spp. Sedge species CENAS Centella asiatica Coinwort CHASP Chara spp. Musk grasses CRAGR Crab grass Crab grass CYPSP Cyperus spp. Sedge species DIOVI Diodia virginiana Buttonweed ELELG Eleocharis sp. (Large) Large species of Eleocharis EUPSP Eupatorium spp. Dogfennel HABRE Habenera repens Water-spider orchid JUNEF Juncus effusus Soft Rush JUNMA Juncus marginatus Rush LEEHE Leersia hexandra Southern cut grass MICSP Micranthemum spp. Baby tears MYRCE Myrica cerifera Wax-myrtle NELLU Nelumbo lutea Water lotus NYMAQ Nymphoides aquatica Banana lily PANSP Panicum spp. Panicum spp. (not including hemitomon ) PASGE Paspalidium geminatum Egyptian paspalidium (commonly called knot grass) PASNO Paspalum notatum Bahia grass POLDE Polygonum densiflorum Smartweed POLSP Polygonum sp. Unidentified fuzzy species of Polygonum RHECU Rhexia cubensis Meadowbeauty RHYNSP Rhyncospora spp. Beakrushes SACIN Saciolepis indica Indian cupscale SAGLT Sagittaria lattifolia Arrowhead SCICA Scirpus californicus Giant bulrush SCICU Scirpus cubensis Bulrush SESPU Sesbania punicea Purple sesban WOOVI Woodwardia virginica Virginia chain fern UNKNOWN 11 Unknowns Infreque nt ecotonal grasses and seasonal floating mat species. Nomenclature follows that of Tobe et al. 1998

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98 APPENDIX B WHOLE-LAKE MONITORI NG STUDY SPECIES LIST Table B-1. Most abundant species samp led in the Whole-Lake Monitoring study. Species code Scientific name Common name ALTPH Alternanthera philoxeroides Alligator weed BACCA Bacopa caroliniana Lemon Bacopa BRAMU Bracharia mutica (Forssk.) Stapf Para grass CERSP Ceratophyllum spp. Coontail CHASP Chara spp. Musk grasses ELESP Andropogon virginicus Broom grass HYDSP Hydrocotyle spp. Pennywort HYDVE Hydrilla verticillata Hydrilla LUDSP Ludwigia spp. (leptocarpa and peruviana) Ludwigia/Water Primrose LUZFL Luziola fluitans (Michx.) Terrell & H. Robbins Watergrass (Syn. Hydrochloa caroliniensis ) NUPLU Nuphar luteum Spatterdock (Syn. Nuphar advena ) NYMAQ Nymphoides aquatica Banana lily NYMOD Nymphaea odorata Fragrant water lily PANHE Panicum hemitomon Maidencane PANRE Panicum repens Torpedo grass PASGE Paspalidium geminatum Egyptian paspalidium (commonly called knot grass) PASNO Paspalum notatum Bahia grass PONCO Pontederia cordata Pickerel weed SCICA Scirpus californicus Giant bulrush TYPSP Typha spp. Cattails Nomenclature follows that of Tobe et al. 1998

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99 Table B-2. Less abundant species sample d in the Whole-Lake Monitoring study. Species code Scientific name Common name ANDVI Axonopus furcatus Big carpet grass AXOFU Bidens laevis Bur-marigold BIDLA Centella asiatica Coinwort CENAS Crab grass Crab grass CRAGR Cyperus spp. Sedges CYPSP Diodia virginiana Buttonweed DIOVI Eichhornia crassipes Water hyacinth EICCR Eleocharis spp ( Small ) Spikerushes EUPSP Eupatorium spp Dogfennel HABRE Habenera repens Water-spider orchid HIBGR Hibiscus grandiflorus Swamp Hibiscus JUNMA Juncus marginatus Rush LUDRE Ludwigia repens Red ludwigia LYMSP Lymnobium spongia Frog's bit MIKSC Mikania scandens Climbing hempweed NELLU Nelumbo lutea Water lotus POLDE Polygonum densiflorum Smartweed POLHY Polygonum hydropiperoides Wild water-pepper RHYNSP Rhyncospora spp. Beakrushes SACIN Saciolepis indica Indian cupscale SAGLN Sagittaria lancifolia Duck potato SAGLT Sagittaria lattifolia Arrowhead SCICU Scirpus cubensis Bulrush SESPU Sesbania punicea Purple sesban UTRSP Utricularia spp. Bladderworts VALSP Vallisneria spp. Eel grass UNKNOWNS Six Unknowns Infrequent ecotonal grasses and seasonal floating mat species. Nomenclature follows that of Tobe et al. 1998

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100 LIST OF REFERENCES Ager, L. A., and K. E. Kerce. 1970. Vegeta tional changes associated with water level stabilization in Lake Okeechobee, FL. In Proceedings of the 24th Annual Conference of the Southeastern Associat ion of Game and Fish Commissions. Colombia, SC. Allen, M. S., K. I. Tugend, and M. J. Mann. 2003. Largemouth bass abundance and angler catch rates following a habitat enhancement project at Lake Kissimmee, Florida. North American Jour nal of Fisheries Management 23 :845-855. Anderson, R. V., and D. M. Day. 1986. Predic tive quality of macr oinvertebrate-habitat associations in lower navigational pools of the Mississippi River. Hydrobiologia 136 :101-112. Austin, D. F. 1978. Exotic plants and th eir effects in southeastern Florida. Environmental Conservation 5 :25-34. Beal, W. J. 1896. Grasses of North America. Vol. II. H. Holt and Co., New York, NY. Beals, E. W. 1984. Bray-Curtis ordination: an effective strategy for analysis of multivariate ecological data. Advances in Ecological Research 14 :1-55. Best, E. P. H., D. De Vries, and A. Rein s. 1984. The macrophytes in the Loosdrecht Lakes: a story of their decline in the course of eutrophicati on. Verhandlungen Internationale Vereinigung fur Th eoretische und Angewandte Limnologie 21 :14841491. Blackburn, R. D., L. W. Weldon, R. R. Yeo, and T. M. Taylor. 1969. Identification and distribution of certain similar-appearing submersed aquatic weeds in Florida. Hyacinth Control Journal 8 :17-23. Blackman, W. F. 1973. Histor y of Orange County. Mickler House Publishers, Chulota, FL. Blake, G. R., and K. H. Hartge. 1986. Bulk density. In A. Klute, editor. Methods of soil analysis: part 1. Physical and mine ralogical methods. American Society of Agronomy, Madison, WI. Blake, N. M. 1980. Land into water – water into land. University Presses of Florida, Tallahassee, FL.

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103 Hodges, E. M., and D. W. Jones. 1950. Manual of the grasses of the United States. Second edition. U.S. Department of Agriculture, Washington DC. Holcomb, D., and W. Wegener. 1971. Hydrophy tic changes related to lake fluctuation as measured by point transects. In Proceedings of the 25th Annual Conference of the Southeastern Association of Game and Fish Commissioners. Colombia, SC Holm, L., D. L. Plucknett, J. V. Pancho, and J. P. Herberger. 1977. The world’s worst weeds: distribution and biology. University of Hawaii, Honolulu. Hudon, C., S. Lalonde, and P. Gagnon. 2000. Ranki ng the effects of site exposure, plant growth form, water depth and transparency on aquatic plant biomass. Canadian Journal of Fisheries and Aquatic Sciences 57 (1):31-42. Jacobs, H. S. 1971. Soils laboratory ex ercise source book. American Society of Agronomy, Madison, WI. Juge, R., and J. B. Lachavanne. 1997. Pl ant diversity in lacustrine ecotones. In J. B. Lachavanne, and R. Juge, editors. Biodi versity in land-inland water ecotones. Parthenon Publishing Group, New York, NY. Kahl, R. 1993. Aquatic macrophyte ecology in the Upper Winnebago Pool Lakes, Wisconsin. Technical Bulletin. Wisconsin Department of Natural Resources, Madison, WI. Keddy, P. A. 1983. Shoreline vegetation in Ax e Lake, Ontario: effects of exposure on zonation patterns. Ecology 64 :331-344. Kent, M., and P. Coker. 1992. Vegetation desc ription and analysis: a practical approach. CRC Press, Boca Raton, FL. Kershaw, K. A., and J. H. H. Looney. 1985. Quantitative and dynamic plant ecology. Edward Arnold, Baltimore, MD. Lachavanne, J. B. 1985. The influence of accelerated eutrophication on the macrophytes of Swiss Lakes: abundance and distri bution. Verhandlungen Internationale Vereinigung fur Theoretische und Angewandte Limnologie 22 :2950-2955. Langeland, K. A. 1996. Hydrilla verticillata (L.F.) Royle (Hydrocharitaceae), "The Perfect Aquatic Weed". Castanea 61 :293-304. Leslie, A. J., L. E. Nall, and J. M Van Dyke. 1983. Effects of vegetation control by grass carp on selected water-quality variable s in four Florida lake s. Transactions of the American Fisheries Society 112 :777-787. Lindeman, R. L. 1942. The tropho-dyna mic aspect of ecology. Ecology 23 :399-418.

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104 Mallison, C. T., R. K. Stocker, and C. E. Cichra. 2001. Physical and vegetative characteristics of floating islands. Journal of Aquatic Plant Management 39 :107111. McCune, B., and J. B. Grace. 2002. Anal ysis of ecological communities. MjM Software Design, Gleneden Beach, OR. McCune, B., and M. J. Mefford. 1999. Multivariate analysis of ecological data, version 4.20. MjM Software Design, Gleneden Beach, OR. Milleson, J. F. 1987. Vegetation changes in the Lake Okeechobee li ttoral zone: 1972 to 1982. Technical Publication. South Flor ida Water Management District, West Palm Beach, FL. Mitchell, D. S. 1976. The growth and management of Eichhornia crassipes and Salvinia spp. in their native environmen t and in alien situations. In C. K. Varshney, and J. Rzoska, editors. Aquatic weeds in sout heast Asia. Dr. W. Junk b.v. Publishers, The Hague, Netherlands. Mitsch, W. J., and J. G. Gosselink. 1993. Wetlands. Second edition. John Wiley & Sons, New York, NY. Moss, B., J. Madgwick, and G. Phillips. 1996. A guide to the rest oration of nutrientenriched shallow lakes. Borads Authority, Norwich, UK. Moyer, E. J., M. W. Hulon, R. S. Butler, and R. W. Hujik. 1989. Kissimmee chain of lakes studies: study 1. Lake Tohopekaliga investigations. Florida Game and Freshwater Fish Commi ssion, Tallahassee, FL. Odum, E. P. 1971. Fundamentals of eco logy. Third edition. W.B. Saunders, Philadelphia, PA. Odum, E. P. 1993. Ecology: and our endangere d life-support systems. Second edition. Sinauer Associates, Sunderland, MA. Penfound, W. T., and T. T. Earle. 1948. Th e biology of the waterhyacinth. Ecological Monographs 18 :449-472. Pesnell, G. L., and R. T. Brown. 1977. The major plant communities of Lake Okeechobee, Florida, and their associated inundation characteris tics as determined by gradient analysis. Technical Publi cation. South Florida Water Management District, West Palm Beach, FL. Planert, M., and W. R. Aucott. 1985. Wate r supply potentia l of the Florida aquifer in Osceola, eastern Orange and southwestern Brevard counties, Florida. Water Resources Investigation Report. U.S. Geological Survey.

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105 Power, P. 1996. Effects of current velocity and substrate composition of phytoplankton on growth of Texas wildrice ( Zizania tezana ). Aquatic Botany 55 :199-204. Remetrix LLC. 2000. Bathymetric map of Lake Tohopekaliga. Remetrix LLC, Carmel, IN. Remetrix LLC. 2003. Aquatic vegetation surv ey of Lake Tohopekaliga. Remetrix LLC, Carmel, IN. Schardt, J. D. 1994. Florida aquatic plan t survey 1992. Technical Report. Florida Department of Environmental Protection, Tallahassee, FL. Schardt, J. D. 1997. Florida aquatic plan t survey 1994. Technical Report. Florida Department of Environmental Protection, Tallahassee, FL. Scheffer, M. 1998. Ecology of shallow lakes. Chapman & Hall, London, UK. Scheffer, M., S. H. Hosper, M-L. Meijer, B. Moss, and E. Jeppesen. 1993. Alternative equilibria in shallow lakes. Trends in Ecology and Evolution 8 :275-279. Schmitz, D. C., J. D. Schardt, A. J. Leslie, F. A. Dray, J. A. Osborne, and B. V. Nelson. 1993. The ecological impact and management history of three invasive alien aquatic plant species in Florida. In B. N. McKnight, editor. Biological pollution: the control and impact of invasive exotic species. Indiana Academy of Sciences, Indianapolis, IN. Seddon, B. 1972. Aquatic macrophytes as limnol ogical indicators. Freshwater Biology 2 (2):107-130. Segal, S. 1971. Principles on structure, zonation and succession of aquatic macrophytes. Hydrobiologia 12 :89-95. SFWMD (South Florida Wate r Management District). 1992. Surface water improvement plan for the Everglades. Supporting Information Document. South Florida Water Management Dist rict, West Palm Beach, FL. Sincock, J. L. 1957. A study of the vege tation on the northwest shore of Lake Okeechobee. Technical Report. Florida Game and Freshwater Fish Commission, Tallahassee, FL. Sincock, J. L., J. A. Powell, R. K. Hyde, and H. E. Wallace. 1957. The relationship of the wintering waterfowl populations of the Kissimmee River Valley to the hydrology, topography, distribution of the vegetation and the proposed hydrological regulations. Technical Report. Florida Game and Freshwater Fish Commission, Tallahassee, FL.

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106 Smith, D. H., and R. M. Smart. 2004. Influence of water level on torpedograss establishment in Lake Okeechobee, Florid a. Lake and Reservoir Management 20 (1):1-13. Sorrell, B. K., H. Brix, H-H Schierup, and B. Lorenzen. 1997. Die-back of Phragmites australis : influence on the distri bution and rate of sediment methanogenesis. Biogeochemistry 36 :173-188. Spence, D. H. N. 1967. Factors controlli ng the distribution of freshwater macrophytes with particular reference to the lo chs of Scotland. Journal of Ecology 55 :147-170. Tarver, D. P. 1979. Torpedo grass ( Panicum repens L.). Aquatics 1 :5-6. Tebeau, C. 1971. A history of Florida. Un iversity of Miami Press, Coral Gables, FL. Thompson, J. B. 1919. Para grass. Univer sity of Florida Agricultural Experiment Station Press, Gainesville, FL. Tobe, J. D., K. C. Burks, R. W. Cantrell, M. A. Garland, M. E. Sweeley, D. W. Hall, P. Wallace, G. Anglin, G. Nelson, J. R. Coope r, D. Bickner, K. Gilbert, N. Aymond, K. Greenwood, and N. Raymond. 1998. Flor ida wetland plants: an identification manual. Florida Department of Envi ronmental Protection. Rose Printing, Tallahassee, FL. Tonn, W. M., and J. Magnuson. 1982. Patterns in the species composition and richness of fish assemblages in northern Wisconsin lakes. Ecology 63 :1149-1166. Urban, D. L. 2002. Classifi cation and regression trees. In B. McCune, and J. B. Grace, editors. Analysis of ecological communities. MjM Software Design, Gleneden Beach, OR. Urban, D. L., S. Goslee, K. Pierce, and T. Lookingbill. 2002. Extending community ecology to landscapes. Ecoscience 9 (2):200-212. U.S. Army Corps of Engineers. 1956. Cent ral and southern Florida project for flood control and other purposes: part 2. Kissimmee River ba sin and related areas. General Design Memorandum, Kissimmee Ri ver Basin. Office of the District Engineer, Jacksonville, FL. U.S. Environmental Protection Agency. 1978. Lake Apopka restoration project, Lake and Orange counties, Florida. Draft E nvironmental Impact Statement. U.S. Environmental Protection Agen cy, Region 4, Atlanta, GA. Van, T. K., and K. K. Steward. 1990. L ongevity of monoecious hydrilla propagules. Journal of Aquatic Plant Management 28 :74-76.

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107 Van der Nat, F-J. W. A., and J. J. Middelburg. 1998. Effects of two common macrophytes on methane dynamics in freshw ater sediments. Biogeochemistry 43 :79-104. Vayssieres, M. P., R. E. Plant, and B. H. Allen-Diaz. 2000. Cl assification trees: an alternative non-parametric a pproach for predicting species distributions. Journal of Vegetation Science 11 :679-694. Venables, W. N., and B. D. Ripley. 2002. Statistics and compu ting: modern applied statistics with S. Fourth edition. J. Chambers, W. Eddy, W. Hardle, S. Sheather and L. Tierney, series editors. Springer-Verlag, New York, NY. Wegener, W.L. 1969. Lake Tohopekaliga fish ery investigation. Technical Report. Florida Game and Freshwater Fi sh Commission, Tallahassee, FL. Wegener, W. L., and V. P. Williams. 1974. Extreme lake drawdown, a working fish management technique. Technical Memo randum. Florida Game and Freshwater Fish Commission, Tallahassee, FL. Wegener, W. L., V. P. Williams, and D. Holcomb. 1973. Water level manipulation. Annual Progress Report. Federal Aid in Fish Restoration. Florida Game and Freshwater Fish Commi ssion, Tallahassee, FL. Wetzel, R.G. 1975. Limnology. Saunders College Publishing, Philadelphia, PA. Wilcox, B. A., and J. E. Meeker. 1991. Di sturbance effects on aquatic vegetation in regulated and unregulated lakes in northe rn Minnesota. Canadian Journal of Botany 69 (7):1542-1551. Wilson, S. D., and P. A. Keddy. 1985. Pl ant zonation on the s horeline gradient; physiological response curves of com ponent species. Journal of Ecology 73 :851860. Wilson, S. D., and P. A. Keddy. 1988. Speci es richness, survivorship and biomass accumulation along an environmental gradient. Oikos 53 :375-380. Wolverton, B. C., and R. C. Mc Donald. 1979. Waterhyacinth ( Eichhornia crassipes ) productivity and harvesting studies. Economical Botany 33 :1-10.

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108 BIOGRAPHICAL SKETCH Zachariah C. Welch was born in Gra nd Rapids, Michigan, on March 30, 1976. Moving to Florida at the age of two, he spent most of his childhood trying to manipulate his younger siblings, and to beat his older brother at anything. It was evident at an early age that he had a propensity for getting dirt y and an awkward shyness. As a toddler he gleefully emptied a can of oil-based wood stain onto his head and was often found romping through mud puddles if left unattend ed. When guests came to the house, he would hide in the corner or put his hands over his face, retreating like a turtle at the first sign of attention. He spent the majority of the first day of kindergarten underneath his desk, prompting home schooling from the first through the third grade. The combination of social awkwardness and a love for gett ing dirty drove him outdoors, and his older brother and he would spend hours every da y running through and exploring the woods that surrounded their house, developing a grea t appreciation for nature over the years. During high school he learned the importa nce of camaraderie and group morale playing football, while developing discipline and a strong work ethic carrying lumber and pounding nails for his father’s construction company. Following his older brother’s footsteps, he enrolled at the University of Florida where he struggl ed with the transition from a small-town school to the highly competitive college atmosphere. After two disappointing years of poor GPAs and a lack of direction, he decided to do what he loved and pursued a career in the outdoors, changing his major from engineering to wildlife ecology and conservation.

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109 Thrilled with the fact that classes in hi s new major involved treks through the forest and identifying the same trees he ogled as a child, he excelled in upper division, graduating with honors and a Bachelor of Scie nce degree in 1999. He also worked parttime for a doctoral student (while completi ng his undergraduate degree) who introduced him to the wonderful world of airboats and th e beautiful swamps and marshes of Florida. Finally, he found his niche, working and st udying in Mother Nature’s mud puddles. Through several fortuitous meetings and s ituations, he was eventually offered a research assistantship for a Master of Scie nce degree at the University of Florida, returning to his Alma Mater in 2000. Initially, he studied th e colonial behaviors of the endangered Florida Snail Kite, driving air boats through virtually every major wetland system in south and central Florida. While collecting data in the summer, he stayed in temporary housing at a national wildlife refuge in south Fl orida, where he met another UF graduate student, Christa Zweig. After completing their respective field seasons and returning to Gainesville to take classes in the fall semester, they fell in love and married 2 years later. Immediately after his return from south Fl orida, Zach had the opportunity to switch research projects and begin monitoring vege tation responses on a c ontroversial habitat restoration project. Having been denied co lonial nesting data by a drought year in the Everglades and having always had an interest in systems ecology, he was thrilled with the idea of establishing a habitat-m onitoring program. For the rest of his graduate degree he enjoyed swimming in the weeds of Lake Tohope kaliga, forming lifelong friendships with revered colleagues. After presenting his thes is at local, statewide, and international

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110 conferences he finally whipped his public-s peaking fears, determined to never spend another day under his desk. Another day in the mud puddles, however, is inevitable.


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LITTORAL VEGETATION OF LAKE TOHOPEKALIGA: COMMUNITY
DESCRIPTIONS PRIOR TO A LARGE-SCALE FISHERIES
HABITAT-ENHANCEMENT PROJECT

















By

ZACHARIAH C. WELCH


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

UNIVERSITY OF FLORIDA


2004

































Copyright 2004

by

Zachariah C Welch















ACKNOWLEDGMENTS

I thank my coworkers and volunteers who gave their time, sweat, and expertise to

the hours of plant collection and laboratory sorting throughout this study. Special thanks

go to Scott Berryman, Janell Brush, Jamie Duberstein and Ann Marie Muench for

repeatedly contributing to the sampling efforts and making the overall experience

extremely enjoyable. This dream team and I have traversed and molested wetland

systems from Savannah, GA, to the Everglades of south Florida, braving and enjoying

whatever was offered. Their camaraderie and unparalleled work ethic will be sorely

missed.

My advisor, Wiley Kitchens, is directly responsible for the completion of this

degree and my positive experiences over the years. With a stubborn, adamant belief in

my potential and capability, he provided me with the confidence I needed to face the

physical and emotional challenges of graduate school. His combination of guidance and

absence was the perfect medium for personal and professional growth, giving me the

freedom to make my own decisions and the education to make the right ones.

I thank my committee members, George Tanner and Phil Darby, for generously

giving their expertise and time while providing the freedom for me to learn from my

mistakes. Additionally, I thank Phil Darby for introducing me to the wonderful world of

airboats and wetlands, and for sparking my interest in graduate school. I thank Franklin

Percival for repeatedly and reliably lending his equipment, and for continually exhibiting

the professionalism and fairness every leader should possess. I thank the Florida Fish









and Wildlife Conservation Commission, specifically Duke Hammond and Marty Mann

for going out of their way to accommodate the needs of this project, and for their patience

throughout my learning process.

Most importantly, I thank the people who give me the strength to tackle all of life's

challenges with unwavering love, support and guidance: my parents, Curt and Sandy; and

my wife, Christa Zweig. My parents are ultimately responsible for all my past and future

successes, having instilled in me every good quality I possess. My wife, whom I met

during this degree process, has provided the good qualities I do not possess, and my life

has been a breeze since.
















TABLE OF CONTENTS

page

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

LIST OF TABLES ....................................................... .. ......... .............. vii

LIST O F FIG U RE S .............. ......................................... ... ....... .......... viii

A B S T R A C T ............................................ ... ......... ................................... x

CHAPTER

1 IN TR O D U C T IO N ............................................................. .. ......... ...... .....

Florida Lakes .................................... .................................. ...............
L ake T ohopekaliga ............... ...... ........................................................ .
H history of Lake Tohopekaliga.......................................... ........................... 9
Restoration Efforts and Previous Studies......................... .... ................ 11
S tu d y O bje ctiv e s .................................................................................................... 14

2 SPEC IE S O F IN TERE ST ....................................... .......................................... 18

Introduction ........................ ..........................18
E x o tic S p e c ie s ........................................................................................................ 1 9
N u isan ce N ativ es ................................................................2 1
D e sire d A q u atic s .................................................................................................... 2 2

3 TREATMENT-SELECTION STUDY ................................................. 24

Introdu action ........................ ............... ..................................................... 24
M eth o d s ...................................................................2 6
S tu d y S ite s ............. ............... .. ........... ......................................................... 2 6
Environm ental V ariables ........................ ...... ....... .. ............................ 30
D ata A n a ly sis .......................... .................. .. .. ............................................. 3 1
R results ..... .. ....... .............................................................................................. 38
D iscu ssio n ............... ........... ..... ........... .................5
C om m unity D descriptions ................................. ....... .. .............. ..............57
Previous Studies ............................. ...... .. .. .. ..... .. ............60
M anagem ent Im plications ...........................................................................62



v









4 WHOLE-LAKE MONITORING .................................................................... 64

Introduction ................................................................................................. ....... 64
M e th o d s ..............................................................................6 5
S tu d y S ite s ...................................................................................................... 6 5
V eg etation S am p lin g ...................................................................................... 6 6
D ata A n a ly sis .................................................................................................. 6 7
R e su lts .................................................................................................................... 6 8
D iscu ssio n ................... ...................8...................4..........
Com m unity D descriptions .................................. ....... .................... ............84
P rev iou s Stu dies .............................................................87

5 S U M M A R Y ................................................................................................8 9

C o m m u n itie s ......................................................................................... .............. 8 9
Shallow G rasses and Sedges ....................................................... 90
D ense Em ergents .................................. .................. ................. 90
Cattails ................................................................................. 91
Floating-Leaved Communities ............................... ............... 92
Deep-Water Communities .................................. .................................. 92
Conclusion ...................................... ................ ........ .................. 93
Habitat-Enhancement Schedule for 2004 .......................... ........ ...............94

APPENDIX

A TREATMENT-STUDY SPECIES LIST .................................. ...............96

B WHOLE-LAKE MONITORING STUDY SPECIES LIST.....................................98

L IST O F R E F E R E N C E S ............................................................................................ 100

B IO G R A PH IC A L SK E T C H ...................................................................................... 108
















LIST OF TABLES


Table pge

3-1 Indicator values of species in the Treatment-Selection study, with values
ranging from 0-100 ........... ...... ........................................................ .. .... .. . 40

3-2 Species variance in the MRT analysis of the Treatment-Selection study ...............56

4-1 Indicator values of species in the Lake-Monitoring study, with values ranging
from 0-100........... .... ................................................ ........ 71

4-2 Tabulation of species variance for the MRT analysis of Lake-Monitoring sites.....83

A-i Most abundant species sampled in the Treatment-Selection study..........................96

A-2 Less abundant species sampled in the Treatment-Selection study...........................97

B-l Most abundant species sampled in the Whole-Lake Monitoring study ...................98

B-2 Less abundant species sampled in the Whole-Lake Monitoring study ....................99
















LIST OF FIGURES


Figure page

1-1 Location of Lake Tohopekaliga and East Lake Toho in relation to Lake
Okeechobee and the Kissimmee River........... .......................................8

1-2 Daily mean water elevations in meters (NGVD) from January 1942 until March
2 0 0 4 ............................................................ ................ 10

1-3 The formation of floating mats and subsequent organic barrier, blocking the
access of sport fish to important, shallow water spawning areas.............................13

3-1 Locations of three replicate study sites receiving various treatments....................27

3-2 Individual study sites and their assigned treatments. ........ ............... ............... 29

3-3 Percent of cumulative Importance Value (IV) for each species, with 24
comprising 95% of the total. ........ ........................................... ................... 39

3-4 Plot of mean IV's of the indicator species in each cluster over several depth
cla sse s ......... ..... ............. ..................................... ........................... 4 1

3-5 NMS ordination plot of sample units in species space, color coded by community..42

3-6 The same NMS plot shown in Figure 3-5 but with sample units labeled for
interpretative purposes. .......................... ...................... .... ...... .... ............43

3-7 Weighted average species scores overlayed onto NMS ordination plot ..................44

3-8 Importance values of Panicum repens in the sample units plotted in the NMS
ordination ...........................................................................46

3-9 Importance values ofEleocharis spp. in the sample units plotted in the NMS
o rd in atio n ......................................................................... 4 7

3-10 Importance values of Luziolafluitans in the sample units plotted in the NMS
o rd in atio n ......................................................................... 4 8

3-11 Importance values ofPontederia cordata in the sample units plotted in the
N M S ordination .................................................................... ......... 49









3-12 Percentage of organic matter in each of the sample units plotted in the NMS
ordination ...........................................................................50

3-13 Importance values ofHydrilla verticillata in the sample units plotted in the
N M S ordin action ....................................................................................... 5 1

3-14 CART model of community distribution along the measured environmental
gradients. ............................................................................52

3-15 MRT analysis, with terminal groups of species based on IV's and their
associated environm ental variables ........................................ ....... ............... 54

3-16 A hypothetical CART model to be created following years of post-treatment
data collection ........................................................................63

4-1 Five study site locations, each encompassing the 0-2 m depth zone..................66

4-2 Percent of cumulative Importance Value (IV) for each species, with 20
com uprising 95% of the total. ......................................................... ................... 70

4-3 Lake-Monitoring Study ordination plot of sample units in species space, color
coded by com m unity ......................... ....... .... .. ...... ............ 72

4-4 Weighted average species scores overlayed onto the Lake-Monitoring study
N M S ordin action ....................................................................................... 73

4-5 Importance values of Panicum repens in the Lake-Monitoring samples, as
plotted by the N M S ordination .................................................................... .. .... 74

4-6 Importance values of Luziolafluitans in the Lake-Monitoring samples, as
plotted by the N M S ordination .................................................................... .. .... 75

4-7 Importance values ofPontederia cordata in the Lake-Monitoring samples, as
plotted by the N M S ordination .................................................................... .. .... 76

4-8 Importance values ofHydrilla verticillata in the Lake-Monitoring samples, as
plotted by the N M S ordination .................................................................... .. .... 77

4-9 Importance values of Paspalidium geminatum in the Lake-Monitoring samples,
as plotted by the NM S ordination. ........................................ ....................... 78

4-10 Importance values ofNuphar luteum in the Lake-Monitoring samples, as
plotted by the N M S ordination .................................................................... .. .... 79

4-11 CART model of Lake-Monitoring community distributions along the measured
environm ental gradients ........................................ ................................. 81

4-12 Communities identified in the Lake-Monitoring study by IV's and their
associated environmental variables, using the MRT analysis..............................82















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

LITTORAL VEGETATION OF LAKE TOHOPEKALIGA: COMMUNITY
DESCRIPTIONS PRIOR TO A LARGE-SCALE FISHERIES
HABITAT-ENHANCEMENT PROJECT

By

Zachariah C. Welch

December 2004

Chair: Wiley Kitchens
Major Department: Wildlife Ecology and Conservation

An extreme dry-down and muck-removal project was conducted at Lake

Tohopekaliga, Florida, in 2003-2004, to remove dense vegetation from inshore areas and

improve habitat degraded by stabilized water levels. Vegetation was monitored from

June 2002 to December 2003, to describe the pre-existing communities in terms of

composition and distribution along the environmental gradients. Three study areas

(Treatment-Selection Sites) were designed to test the efficacy of different treatments in

enhancing inshore habitat, and five other study areas (Whole-Lake Monitoring Sites)

were designed to monitor the responses of the emergent littoral vegetation as a whole.

Five general community types were identified within the study areas by recording

aboveground biomasses and stem densities of each species. These communities were

distributed along water and soils gradients, with water depth and bulk density explaining

most of the variation. The shallowest depths were dominated by a combination of









Eleocharis spp., Luziolafluitans, and Panicum repens; while the deeper areas had

communities of Nymphaea odorata and Nuphar luteum; Typha spp.; or Paspalidium

geminatum and Hydrilla verticillata. Mineralized soils were common in both the shallow

and deep-water communities, while the intermediate depths had high percentages of

organic material in the soil. These intermediate depths (occurring just above and just

below low pool stage) were dominated by Pontederia cordata, the main species targeted

by the habitat enhancement project. This emergent community occurred in nearly

monocultural bands around the lake (from roughly 60-120 cm in depth at high pool

stage) often having more diverse floating mats along the deep-water edge. The organic

barrier these mats create is believed to impede access of sport fish to shallow-water

spawning areas, while the overall low diversity of the community is evidence of its

competitive nature in stabilized waters. With continued monitoring of these study areas

long-term effects of the restoration project can be assessed and predictive models may be

created to determine the efficacy and legitimacy of such projects in the future.














CHAPTER 1
INTRODUCTION

Florida Lakes

Historically, Florida was once much wetter than it is today, with as much as 25% of

the peninsula covered with freshwater during wet years (Tebeau 1971). Low elevation,

flat topography, and poorly drained soils support a landscape pockmarked with swamps,

lakes, and marshes, many of which were once connected. In fact, over 7700 lakes occur

in the state of Florida; most formed from gradual dissolving and collapsing of subsurface

limestone (solution processes) or from relict sea-bottom depressions that were filled with

freshwater as the oceans receded (Edmiston and Myers 1983). These lakes generally

have a large area:volume ratio as a result of the formation processes and lack of

topography in the landscape.

The largest lake in the state and third largest in the country, Lake Okeechobee, is an

example of a depression lake, with an area of 1732 km2 and an average depth of only

2.7 m. Large, shallow lakes of this nature have considerable stretches of shoreline

capable of supporting vegetation, with sections of the 400 km2 of Lake Okeechobee

marsh so large that the interior is hydrologically isolated from the lake itself. The

maximum depth to which vegetation extends into the lake generally depends on light

availability, but is closely related to water chemistry (Spence 1967, Heegard et al. 2001),

lacustrine topography (Duarte & Kalffe 1986), fluctuations in water level and depth

(Hudon et al. 2000), substrate composition (Power 1996), and interactions with other

flora and fauna (Leslie et al. 1983, Wilson and Keddy 1985). The vegetated portion of









the lake, including either emergent or submersed communities, is loosely referred to as

the littoral zone, and in many shallow lakes may include the entire water body. For the

remainder of this thesis, the littoral zone is defined as the portion of shoreline that

supports emergent or floating-leaved vegetation only; not including the deeper-water,

submersed aquatics. These areas are primary zones of productivity, driving nutrient and

oxygen cycles; preventing erosion; trapping sediment; and providing cover, substrate, and

forage for a suite of aquatic organisms ranging from microscopic zooplankton to large

vertebrate predators.

Unfortunately, these systems are vulnerable to changes in watersheds and shoreline

activities, as surrounding human populations increase. Many of Florida's lakes are facing

problems such as degraded water qualities from urban and agricultural runoff, seawall

construction, flood control and water-use demands disrupting historical hydroperiods and

stage fluctuations, substrate alterations as a result of sedimentation or organic material

accumulation, and the introduction of hundreds of exotic species of flora and fauna

competing with and displacing natives.

The most recognized and prevalent of these issues is eutrophication, the

degradation of habitat and water quality as a result of artificially increased nutrient levels

(by means of fertilizers, stormwater, sewage effluent, etc.). The term eutrophication

became more widely used in the 1940s as scientists realized that nutrients entering and

accumulating in lakes as a result of industrial activities were causing changes in a matter

of decades that would otherwise occur naturally over centuries or longer (Harper 1992).

A general theory of succession supports the idea of lakes gradually accumulating

nutrients and increasing productivity over time. This theory suggests that in early stages,









lakes have few nutrients and low productivity (oligotrophic); and gradually accumulate

nutrients through sedimentation and their own biological turnover, leading to a highly

productive state, eventually eliminating macrophytes and becoming dominated by

phytoplankton (hypereutrophic) (Lindeman 1942). This trend is considered a natural

process of lakes evolving from a clear-water state with vegetation adapted to low nutrient

levels; to an eventual muck-filled, algae-laden lake unable to support vegetation and

having turbid, high-energy water columns. Theoretically, agricultural and urban runoff

dramatically accelerates the speed and magnitude of nutrient increases, causing

noticeable changes within decades (rather than centuries).

However, some argue that increasing the level of nutrients in a lake does not

necessarily guarantee a turbid algal state, especially in shallow, warm-water lakes

(Scheffer 1998). In Florida, where growing seasons are basically year-round, and

submersed aquatics can occupy 100% of shallow-lake areas, high levels of nutrients can

be tied up in extremely productive macrophytic and epiphytic communities, reducing

wind/wave actions and limiting nutrient levels in the water column. These conditions are

unfavorable for the development of phytoplankton for several reasons (Moss et al. 1996):

calm waters within dense vegetation are not turbulent enough to keep phytoplankton

suspended, which is necessary for substantial development; the structure of the vegetation

provides cover and substrate for micro-invertebrates that graze on phytoplankton; and

through macrophytic and epiphytic uptake, the amount of nutrients in the water column is

reduced. However, large-scale vegetation removal by natural or artificial disturbances

may be enough to switch the lake to a turbid, algal state. This phenomenon of highly

eutrophic lakes existing as either algae- or macrophyte-dominated lakes is a theory









known as alternative stable states. Indeed, shallow eutrophic lakes have been shown to

switch from one state to another without any change in nutrient inputs (Blindow et al.

1993, Scheffer et al. 1993, and Moss et al. 1996). One example of such a switch is Lake

Apopka, located in central Florida.

Once renowned for its largemouth-bass fishery, Lake Apopka was almost

completely covered with submersed vegetation in the 1940s (Clugston 1963) though

sewage effluent and agricultural runoff had been increasing since the 1920s. In 1947, a

category four hurricane moved across Florida, uprooting substantial amounts of

vegetation and stirring sediments throughout the lake, resulting in large fish kills and

unvegetated areas in the lake. By 1950, all of the submersed vegetation had disappeared

and high wind events in 1951 resulted in additional fish kills, presumably due to oxygen

depletion from highly organic sediments. Since then, Lake Apopka has been in a turbid,

algal state; and all attempts at restoration, beginning as early as 1952 (US Environmental

Protection Agency 1978) have failed to reestablish vegetation.

This is a serious issue facing most water bodies in Florida, and its effects are

compounded by the disruption of historical sheet flows and hydroperiods of these

systems. Watershed development increases nutrient inputs and also increases demand for

flood control and water supply; turning naturally dynamic lakes and wetlands into

reservoirs, and meandering rivers into streamlined channels. Many of the major

hydrological changes in Florida were a result of devastating hurricanes in the 1920s and

1940s that caused large-scale losses of life and property. In the 1930s the Army Corps of

Engineers responded with aggressive plans to improve flood control and navigation,

creating a vast system of levees and canals throughout central and southern Florida.









Ultimately, results of this program were compartmentalization of the Everglades,

impoundment and isolation of Lake Okeechobee, and channelization of the Kissimmee

River (a major inflow to Okeechobee).

Lake Okeechobee was completely encircled by levees in the 1960s, isolating it

from much of its historical littoral zone (although levee construction early in the 20th

century gradually lowered water levels, and allowed the current littoral zone to develop

over the past 100 years) (Davis 1943). Upon impoundment in the 1960s, water levels

were regulated to minimize flooding during the wet season (May-October) and to

maximize water storage for the dry season (November-April), raising the average lake

level from 4.3-5.0 m (14.3-16.4 ft) above sea level (Ager and Kerce 1970). Vegetation

studies in 1969 (Ager and Kerce 1970) documented a doubling of cattail (Typha spp.)

populations in deeper water and a tripling of torpedo grass (Panicum repens) populations

in shallower water since the late 1950s (Sincock 1957). In 1978, the water-regulation

schedule was raised by 0.5 m and substantial decreases in the diversity of community

types and willow (Salix caroliniana) were noted, with further increases in cattail and

torpedo grass; the latter displacing diverse, native communities of rushes (Eleocharis spp.

and Rhynchospora spp.) (Pesnell and Brown 1977, Milleson 1987). By the early 1990s,

more than 60 km2 of shallow, native marsh had been displaced by torpedo grass (Schardt

1994).

A general decrease in specific diversity or structural complexity of communities

after water-level stabilization (Keddy 1983, Wilson and Keddy 1988, Wilcox and Meeker

1991) or eutrophication (Seddon 1972, Lachavanne 1985, Harper 1992) has been well

documented. Additionally, the degree of spatial or structural heterogeneity of plant









communities affects the diversities of other organisms that are more or less vegetation

dependent (Juge and Lachavanne 1997), including associated microflora (Wetzel 1975),

invertebrates (Anderson and Day 1986, Giudicelli and Bournard 1996), and fish (Tonn

and Magnuson 1982). Declines in fisheries were noticed after habitat degradation

(Wegener and Williams 1974) and consequently, habitat restoration became a priority for

agencies in charge of Florida lake management. In addition to implementing pollution

controls to limit nutrient inputs, the need to more closely mimic natural hydrological

patterns was also recognized. Although watershed development eliminated the

possibility of reaching historical flood levels, mimicking historical droughts was possible.

Artificial dry downs were performed to counteract the effects of prolonged impoundment,

by exposing organic substrates to oxidation and sparking seed germination and vegetative

propagation of stressed plant populations. While successful in expanding the lakeward

extent of the littoral zone, reestablishing native flora, and consolidating organic substrates

(Wegener and Williams 1974), the benefits of these projects seemed to diminish as the

systems became further removed from their pre-impoundment state. Over time, more

aggressive, competitive species became established under stable-water conditions; and

extremely infrequent dry downs became ineffective at reducing the abundance of these

competitive species. As the benefits of dry downs became more short-lived, efforts to

prolong and increase their impacts were developed.

To expedite the natural removal processes of organic substrates and to assist the

establishment of desirable species, managers began using bulldozers and other heavy

equipment to mechanically remove muck and unwanted vegetation from shorelines

during artificial dry downs. This process was first performed in 1987 on a large lake in









central Florida, called Lake Tohopekaliga. Though many lakes have undergone such

treatment since (Lake Kissimmee, Lake Istokpoga, Alligator Chain of Lakes, Lake

Jackson, Orange Lake, etc.), effects of this type of disturbance are still not fully

understood even in terms of the fisheries they are supposed to benefit (Allen et al. 2003).

In spite of the uncertainty, this practice is commonly used, and another larger scale muck

removal project was scheduled for Lake Tohopekaliga in 2004. The remainder of this

paper will detail the history of the lake, the specifics of this project and the studies

designed to monitor its effects.

Lake Tohopekaliga

Lake Tohopekaliga (hereafter referred to as Lake Toho) is one of several large

lakes located in the Upper Kissimmee River Basin, collectively draining thousands of

square kilometers into the Kissimmee River and ultimately Lake Okeechobee (Figure

1-1). Lake Toho and an adjacent sister lake, East Lake Toho, are the northernmost lakes

in the basin, lying between the Orlando and Mount Dora Ridges in the Osceola Plain.

This plain consists mainly of poorly drained, clayey sediments with poor groundwater

recharge, having over 73 lakes at least 3.2 ha in size (HDR Engineering 1989). Most of

the lakes in this region were formed from solution activities and are precipitation driven.

Lake Toho is the largest lake in the Osceola Plain, covering an area of 8,176 ha at

an average depth of 2.1 m at maximum pool (16.75 m NGVD) (HDR Engineering 1989,

Remetrix LLC 2003). The immediate watershed is 340 km2, though an additional 686

km2 of East Lake Toho watershed ultimately drains into Lake Toho through canal C-31

(HDR Engineering 1989). Nearly half of these 1334 km2 are drained primarily by two

main stream systems: Shingle Creek, located north of Lake Toho and flowing directly

into the northwest side of the lake; and Boggy Creek, northeast of Lake Toho and flowing









into East Lake Toho. Depending on precipitation and the operation of control structures

on C-31 (drainage canal from East Lake Toho to Lake Toho) either Shingle Creek or the

discharge from East Lake Toho can account for as much as 50% of the inflow to Lake

Toho (Fan and Lin 1984, HDR Engineering 1989).




Lake Tohopekaliga




East Lake Toho
FlOsce ola Countyrida




'Lake Okeechobee EastLakeToho


Figurange 1-1. Location of Lake Tohopekaliga and East Lake Toho in relation to Lake
Osceola County


Kissimmee River


Lake Okeechobee


Figure 1-1. Location of Lake Tohopekaliga and East Lake Toho in relation to Lake
Okeechobee and the Kissimmee River

Considered a eutrophic lake, the water is slightly stained from upland tannins and

relatively free of algal blooms, with visibility ranging from 0.5-1.5 m. The mixed

emergent littoral vegetation covers roughly 25% of the lake's area (Remetrix LLC 2003),

supporting highly productive fisheries, large populations of wintering migratory birds,

significant nesting of endangered and threatened species (Snail Kite, Rostrhamus

sociabilis, and Sandhill Crane, Grus canadensis ) and dozens of species of reptiles and









amphibians. Like most water bodies in Florida, however, constant vigil and intervention

is required to maintain productivity or natural habitats in the face of watershed

development and exotic species introductions. Below is a brief summary of the history of

Lake Toho and the challenges of balancing flood control and water storage capacities,

recreational and economical benefits, and quality habitat for native faunal communities.

History of Lake Tohopekaliga

Historically, much of the watershed in the Upper Kissimmee River Basin was

dominated by wetlands, with lakes bordered and interconnected by large wet prairie

sloughs, including the connection of Lake Toho and East Lake Toho by Fennel and Cross

Prairies (HDR Engineering 1989). This network of water bodies flowed south primarily

through the Kissimmee River, virtually connecting waters of interior central Florida to

Lake Okeechobee.

As early as the 1850s, pioneers began to modify the hydrology of the system and

by 1884 a navigable waterway was opened from Kissimmee all the way to Fort Myers

(HDR Engineering 1989). After the Florida Legislature passed the General Drainage Act

in 1913 (Chap. 298, FS), a reported 108 km (67 mi) of canals were dug throughout the

Shingle and Boggy Creek Basins (Blackman 1973). Catastrophic hurricanes in the 1940s

sparked several flood control projects with major changes occurring in the Upper

Kissimmee River Basin by 1957. These projects were designed to construct levees and

control structures on the south ends of the larger lakes, to improve channels to

downstream lakes, and for regulation of upper lake levels within a 0.6-1.2 m range (HDR

Engineering 1989, U.S. Army Corps of Engineers 1956). Water control structures and

canals regulating flows to and from Lake Toho were completed in 1964 (Blake 1980),

marking the end of natural water level fluctuations. This resulted in a reduction in the











range of stage levels from at least 3.2 m to a maximum of 1.1 m (Wegener et al. 1973).

Figure 1-2 shows the sharp contrast between the dynamic, astatic condition of the lake

prior to impoundment in 1964 and the stabilization that has occurred since.


18.00


17.50

a
> 17.00
Z
5 16.50
E
c
16.00
0

0) 15.50


15.00


14.50


1950 1960 1970 1980 1990 2000


Figure 1-2. Daily mean water elevations in meters (NGVD) from January 1942 until
March 2004. The vertical black line represents the approximate time of
impoundment in 1964 while the blue lines indicate artificial dry downs. The
natural drought in 1962 was the lowest on record at that point.

Sewage treatment plants began pumping effluent into the Shingle and Boggy Creek

basins as early as the 1940s, and by 1986 an estimated 113 million liters per day (30

million gallons) were being discharged into these systems (Wegener et al. 1973). Though

water quality problems were recognized and attributed to these plants in 1969, discharges

were not completely eliminated until 1988. By this point nutrient loading and water level

stabilization had noticeably affected the littoral habitats, water qualities, and fish

populations, sparking a new era in lake restoration by management agencies.


II Artificial Dry Downs
I I Im4 ----
















Impoundment| I
__ I II









Restoration Efforts and Previous Studies

In 1969, the Florida Fish and Wildlife Conservation Commission recommended

that all effluent discharges into Lake Toho be stopped and that an artificial dry down be

performed in hopes of sparking seed germination and recolonization of desired species

(Wegener 1969). The first managed drawdown of the lake took place in 1971, lowering

the water from a high pool stage of 16.75 m to 14.65 m (55-48 ft) NGVD (National

Geodetic Vertical Datum). The lake was held there for nearly six months and drought

conditions further extended the refilling to high pool stage until March of 1973. During

this period the FFWCC conducted studies on fish, invertebrates, vegetation, soils, algae,

and water chemistry. Vegetation studies consisted of fixed sampling along line transects

established perpendicular to the shore, ranging from above high pool stage to the

lakeward extent of emergent vegetation. Frequencies of occurrence of species were

recorded based on a form of line intercept method using a five-pointed rake (Sincock et

al. 1957). At that time the only vegetation considered a nuisance was water hyacinth

(Eichhornia crassipes) and the overall expansion of littoral communities into the lake by

16% was hailed as a success (Wegener and Williams 1974).

Another drawdown was performed in 1979 based on the successes of the previous

effort. Sport-fish populations increased to a maximum by 1982 and then gradually

declined to the lowest level since 1972. Based on these data it was assumed the habitat

had degraded substantially and would no longer support maximum fish densities. No

vegetation studies were conducted.

In 1987, the discharge of effluent to the lake was almost eliminated and another dry

down was performed. Contrary to the others, which were performed to increase the

density and area of the littoral zone in general, the purpose of this project was to









eliminate dense, monocultural stands of vegetation (Polygonum spp. and Pontederia

cordata) that had formed an organic barrier from accumulated organic matter; isolating

many shallow areas of littoral zone to the point of blocking access of sport fish to

important spawning grounds. This process occurs as stable, high water levels cause a

buildup of gases in the root mats of senescing vegetation and as organic debris are

deposited by wind and wave actions; eventually causing the mat to become buoyant

enough to release from the substrate and create a floating mat of organic matter and root

material. Over time, wind and wave actions act to push back, break apart, or fold over

the deep water edge of these mats (Kahl 1993), creating progressively thicker mats that

can eventually support woody vegetation (Mallison et al. 2001) (Figure 1-3).

The goal of the 1987 dry down was to reestablish native grasses in place of the

dense, monocultural stands of unwanted vegetation. This marked the first mechanical

muck-removal project, scraping approximately 172,000 m3 of muck and vegetation from

the southeastern shorelines. After just two years, however, line transect studies

established in 1986 showed an almost complete rebound of the vegetation targeted for

removal (Pontederia cordata), though several grass species increased in frequency as

well (Moyer et al. 1989).

A natural drought in 1991 gave lake managers another opportunity to remove some

of the unwanted vegetation and two removal experiments were performed, one involving

mowing the vegetation to a maximum height of 15 cm and the other, uprooting and

removing it. It was found that Pontederia rebounded in both treatments, though at a

slower rate after uprooting. Herbicide applications were also made in hopes of

minimizing the regrowth of Pontederia, but were only effective at slowing regrowth.










A

\f-.


Wave Actions Fold Rool Mal
4*-"


Figure 1-3. The formation of floating mats and subsequent organic barrier, blocking the
access of sport fish to important, shallow water spawning areas. The process
occurs as follows: A) Stabilized water levels begin to drown emergent
vegetation at the deeper end of its depth tolerance, causing senescence and a
buildup of gases in the root mat B) Gas buildup reaches a point that causes
floatation, pulling the root mat from the organic layer beneath it C) Wave
actions fold over the thinner, leading edges of the floating root mat
D) Prolonged folding and the presence of the floating edge act to build
organic material under and within the root mat, forming a thicker, drier mat
E) Eventually the mat supports woodier and shorter hydroperiod vegetation,
forming an organic barrier that limits access of sport fish to shallow water
spawning areas. All line drawings of plants used in these figures were copied
with permission from Aquatic Plants in Pen and Ink (IFAS Pub. No. SP233).


__~f~'hf_









D Thicker, Drier Mat


',fl LWater Level












Muck and Detritus
,, '' .















E 3 Organic Barrier

+ ',,'[ / ; Water Level



Muck and Detritus"


Figure 1-3. Continued

In 2004, the largest and most comprehensive muck removal project to date was

implemented on Lake Toho. Upon dropping lake levels roughly 2 m below high pool

stage, nearly 7,000,000 m3 of muck and vegetation were removed from over 80% of the

shoreline. The remainder of this paper will focus on the studies designed to monitor the

effects of this project.

Study Objectives

Sampling methods implemented in earlier studies have focused on the frequency of

species occurrence along water depth gradients, comparing pre- and post-restoration data.

These methods reveal inundation tolerances of individual species and are effective in









monitoring shifts in their locations along the measured gradient. However, they are

primarily exploratory methods, not generally used to test hypotheses or to make inference

to any area other than that occupied by the line transect. In this respect, previous studies

have not quantitatively measured the response of vegetation to restoration efforts, nor

have they attempted to monitor the response of the littoral communities as a whole (rather

than on an individual species basis). Kershaw and Looney (1985) stated that to

understand vegetative dynamics of a system, species composition, distribution, and the

relative degree of abundance of each must be described. Differences in structural and

specific diversities can have profound effects on organisms relying on that habitat for

food, cover, or substrate (Wetzel 1975, Giudicelli and Boumaud 1996), on rate of

nutrient uptake or immobilization (Mitsch and Gosselink 1993, Sorrell et al. 1997, Van

der Nat and Middelburg 1998), on quality and quantity of detritus, rate of organic

accumulation in the soil (Wilson and Keddy 1988), erosion control, wave energies, and

so on. To fully comprehend treatment effects applied to the littoral communities of Lake

Toho, quantitative measurements of successional responses are critical. Densities and

biomasses are more stringent measures of the spatial and architectural complexity of the

habitats targeted for restoration than frequency of occurrence, as recorded in previous

studies. Defining the pre-existing communities and monitoring their response at a

multi-species level will provide insight to the effects and efficacy of these restoration

efforts.

The ultimate goal of this project is therefore to establish long-term monitoring sites

and protocols to address the following questions:

S At a community level, what are the effects of different habitat restoration
techniques in terms of vegetation succession? Essentially, are both muck removal









and herbicide application necessary to establish historical, grassy habitats or are
either of them effective by themselves?

* On a lake-wide scale, how will the littoral vegetative communities respond to this
restoration project?

These questions were addressed with the designation of two separate study areas;

the first hereafter referred to as the Treatment-Selection study and the second called the

Whole-Lake Monitoring study. Long-term effects of these treatments will not be known

until years of post-treatment data have been collected and analyzed. Chapters 3 and 4

will detail the design, establishment and monitoring protocols of these study areas,

respectively, that are essential to estimating those effects. However, as no restoration

efforts had yet been performed during the period of this study, the bulk of these chapters

and the majority of this paper will focus on the description of the lake's littoral

communities before the treatment was applied. These questions are addressed for each

study area:

* What vegetative communities were present before the project and how were they
distributed?

* What were the underlying gradients associated with those compositions and
distributions?

* Based on this pre-treatment information, what inferences can be made about the
littoral communities within the lake?

Brief discussions of the findings in each study area are included at the end of

Chapters 3 and 4 with comparisons to several previous studies, and Chapter 5 includes a

summated, cumulative discussion of the communities identified in these chapters. Before

presenting these results, basic descriptions of several of the important species

encountered on Lake Toho are provided in Chapter 2. Most of these species will be






17


continually referred to in the following chapters and an understanding of their growth

forms, life histories and physical characteristics will aid interpretation.














CHAPTER 2
SPECIES OF INTEREST

Introduction

Habitat management of any type, aquatic or terrestrial, ultimately leads to the

classification of frequently encountered species as native, natural, desirable or invasive,

exotic, nuisance, aggressive, and so on. Typically, managers have a target habitat

consisting of a suite of desirable native species, usually an approximation of the historic

or natural habitat, and are faced with the elimination or constant invasion of species that

are considered disruptive to that habitat. In Florida, non-native or exotic species are

assigned labels according to their potential to spread, invade, or otherwise dominate,

alter, and disrupt natural habitats. A list of these aggressive, invasive exotics is posted by

the Florida Exotic Pest Plant Council (www.fleppc.org).

The most well known exotics in Florida include water hyacinth (Eichhornia

crassipes) and hydrilla (Hydrilla verticillata). Both of these plants have the remarkable

ability to completely dominate water bodies, displacing practically every other species if

left unmanaged. Hundreds of millions of dollars have been spent in attempts to control

the spread and abundance of these two species alone since their introductions. At present

there are at least 35 exotic species in Florida's aquatic systems and over $70 million a

year is spent in fighting their spread or abundance.

In attempting to restore a system to some historical state, eliminating exotic species

is only a small part of the process. The biggest challenge usually lies with identifying the

causal mechanisms that altered the system to begin with. Changes in water qualities,









nutrient levels, depth and duration of flooding, etc. have major impacts on species

compositions and distributions, resulting in undesirable changes in native vegetation as

well. One of the best cases of such habitat alterations and vegetation response is the

expansion of cattail (Typha spp.) into the Everglades Water Conservation Areas as a

result of high phosphorous levels in receiving waters (SFWMD 1992, Davis 1994). The

historically oligotrophic Everglades and the vegetation adapted to those conditions are

unable to compete with species like cattail at higher nutrient levels, and alterations to

natural hydroperiods, sheet flow, and fire frequencies compound these effects. The

problems facing many of Florida's lakes are quite similar.

As a result of decreased flood stages, water level stabilization, and increased

nutrient inputs, exotics and several native species have become problematic to lake

managers in the restoration of historical habitat. Listed below is a brief description of

important species on Lake Toho, including invasive exotics, nuisance natives, and the

desired species that comprise the target habitat of the lake restoration project.

Exotic Species

S Hydrilla (Hydrilla verticillata): experts argue whether hydrilla or water hyacinth is
the most invasive and disruptive exotic plant in Florida. Hydrilla is a submersed
aquatic brought to the US from Asia through Florida as an aquarium plant, most
likely in the 1950s, through Miami or Tampa Bay ports. It was first discovered in
the 1960s in Miami and Crystal River (Blackburn et al. 1969) and by the 1970s
occurred in all major water bodies in all drainage basins. It out competes most
native submersed species with rapid growth of up to 2.5 cm per day (Langeland
1996) and extensive branching at the water surface, up to one half of its standing
crop occurring in the top 0.5 m of water (Haller and Sutton 1975). An exceptional
tolerance to low light conditions allows its establishment in depths beyond most
other submersed species, and as such can be found in up to 15 m in depth in spring-
fed Crystal River and regularly occurring at 3 m in most lakes (Langeland 1996).
Vegetative and asexual reproduction are most common, forming new plants from
any whorl of leaves broken off or from turions produced on tubers and in leaf axils.
Subterranean turions can remain viable after several days out of water and for up to
4 years in undisturbed sediments (Van and Steward 1990), surviving herbicide
applications and ingestion by waterfowl. This makes the plant easy to spread









between water bodies on boats and boat trailers, fishing lures and bird legs. After
30 years of herbicide applications, more resistant strains of Hydrilla are much more
common. Non-target, native species that used to be unaffected by the low levels of
herbicides used to kill Hydrilla, are now being affected by the need for higher
concentrations. Without constant herbicide application and mechanical removal by
management agencies statewide, Hydrilla would quickly fill most water bodies in
Florida from substrate to water surface. Thus far, no methods have been effective
at killing the roots of the plant, with rapid regrowth occurring from tubers
immediately following decreased herbicide concentrations in the water column. A
leaf-mining fly (Hydrelliapakistanae) has been established in Florida as a
biological control, but its efficacy is as of yet unknown (Buckingham et al. 1989).

* Water hyacinth (Eichhornia crassipes): arguably the most invasive and disruptive
exotic plant in Florida. A free floating plant, it is attached to mother and daughter
plants by floating stolons, creating dense mats of vegetation capable of completely
covering most water bodies. It was introduced to the United States in 1884 at an
exposition in New Orleans and reached Florida in 1890 (Gopal and Sharma 1981).
By the late 1950s it occupied about 51,000 ha of Florida's waterways (Schmitz et
al. 1993). Its growth rates exceed any other tested vascular plant (Wolverton and
McDonald 1979), doubling its populations in as little as 6-18 days (Mitchell 1976).
Large mats degrade water quality by depleting oxygen levels, shading out
submersed species, rapidly producing organic matter, crowding out and crushing
emergent species and blocking access to the air-water interface essential to many
aquatic organisms (Gowanloch 1944, Penfound and Earle 1948). After 100 years
of effort, populations are finally under control through constant maintenance and
herbicide applications.

* Torpedo grass (Panicum repens): A very competitive grass with stems to 1 m tall,
growing from sharp-tipped (torpedo like) floating or creeping rhizomes. It was first
collected in the US in Alabama in 1876 (Beal 1896) and introduced to Florida for
cattle forage in 1926 (Tarver 1979). By 1992 it was established in over 70% of
Florida's public waters, displacing 6000 ha of native marsh in Lake Okeechobee
(Schardt 1994). It will grow in upland areas but thrives in wet, sandy soils,
stimulated by tilling and fertilization (Hodges and Jones 1950), rapidly colonizing
disturbed shorelines by rhizome extension and fragmentation (Holm et al. 1977).

* Para grass (Brachiaria mutica also Urochloa mutica): A rapidly growing grass
with stems from 1-4 m long, with floating stems up to 6 m long (Handley and
Eckern 1981). The lengthy and extremely dense stems fall over and lay on top of
one another, creating horizontal mats up to 1 m thick (Holm et al. 1977). It
aggressively competes with other plants by high productivity and allelopathic
qualities that enable the formation of dense monocultural stands (Chang-Hung
1977, Handley et al. 1989). It was most likely introduced to Florida as early as the
late 1870s (Austin 1978) and was recommended for pasturage here in 1919
(Thompson 1919). This grass occurred in up to 52% of Florida's public water
bodies in 1986 but decreased to 46% by 1994 (Schardt 1997). Grazing remains a
highly effective method of control.









* Water lettuce (Pistia stratiotes): Experts argue whether this plant is native or
exotic but is included in this list due to its potentially invasive and highly
competitive nature. Like water hyacinth, it is a free floating plant connected by
short stolons to mother and daughter plants. William Bartram first reported it in
1756, describing it as blocking waterways and preventing boat access. While the
effects of dense floating mats are the same as hyacinth, including shading
submersed species, decreasing oxygen levels and crowding out emergents, its
slower growth rate has kept it from becoming as big a problem. Through regular
removal and herbicide applications, and with several biological insect controls
successfully established, water lettuce populations remain under control.

* Alligator weed (Alternantheraphiloxeroides): An emergent perennial with
hollow stems able to form large, dense mats, occasionally floating. This species
was problematic when its populations reached a high in the 1960s before the first
biological insect control (Agasicles hygrophila) for an exotic plant was released.
With unprecedented success, by the 1980s its populations were severely limited
and no longer posed a threat. Though still very frequent in Florida lakes and water
bodies, insect damage can easily be seen on most plants, constantly keeping its
populations in check.

Nuisance Natives

While each of the species listed below may be desirable in many situations and

certainly have high value to wildlife under many circumstances, their potential to form

dense, monocultural stands or floating mats and to produce massive amounts of organic

litter often leads to their classification as a nuisance. Typically, dense vegetation and

high amounts of organic matter are considered to impede sport-fish reproduction, block

recreational access and eventually create the same problems in terms of diversity and

habitat as the aforementioned invasive exotics. For these reasons the native species listed

below are frequently sprayed with herbicides to keep their abundance and distribution

under control.

* Pickerel weed (Pontederia cordata): A stout, broadleaf, emergent plant with stems
up to 1 m in height. Large, highly aerenchymous rhizomes form dense mats,
capable of lifting off the substrate and becoming buoyant with rising water levels.
Provides good habitat for macroinvertebrates, reptiles, amphibians and small fish
when not floating, and nesting substrate for several birds (common moorhen,
Gallinula chloropus; purple gallinule, Porphyrula martinica; sandhill crane, Grus
canadensis) when floating. Pickerelweed is highly productive, out-competes many









species in stable environments and contributes large amounts of organic material to
the substrate, capable of forming nearly monocultural stands around shorelines of
lakes.

* Smartweed (Polygonum spp.): Another broadleaf emergent plant, with stems up
to 1.5 m in length. In deeper water, P. densiflorum forms floating mats with long
horizontal stems. It is highly competitive, especially in shallow, disturbed
shorelines and is usually among the first to colonize such areas. Capable of
forming dense, monocultural stands, producing large amounts of litter.

* Cattails (Typha spp.): A tall, robust, emergent species, growing to over 3 m in
height and covering large areas of wetlands, lakes and rivers. One of the most
common aquatic and wetland plants anywhere in the world, capable of forming
monocultural stands of only one or two individuals due to prolific rhizominous
reproduction. Occasionally, floating mats may form in large colonies if high water
levels persist. Each seed head contains tens of thousands of wind and water
dispersed seeds, rapidly colonizing recently disturbed or early successional
wetlands. While providing excellent cover and nesting substrate for many animals
and birds, their tremendous amounts of litter production and dense growth habit
occasionally makes them problematic to lake managers.

Desired Aquatics

Though not specifically more useful to wildlife than many of the nuisance native

vegetation, the relatively sparse growth patterns of the species listed below lends to

higher diversities, lower litter production, increased oxygen levels, and better access for

anglers. These plants are also more typical of oligotrophic systems where a lack of

productivity contributes to sandier substrates and clearer water. The association of these

species to oligotrophic conditions leads to their preference over species more typical of

eutrophic, highly productive systems that accumulate organic material and have turbid

water. The following are a few species generally thought to be representative of a more

natural, historic system before higher nutrient levels and water level stabilization affected

their ability to compete.

* Egyptian paspalidium (commonly called Knot Grass) (Paspalidium
geminatum): A tall species of grass with stems reaching heights of 3 m. It
typically grows on sandy substrates and is generally thought to be good sport fish
habitat. Though capable of forming monocultural stands, it often coincides with









submersed species in deeper water. Grows to depths of at least 2 m but generally is
out competed in shallow waters without significant efforts to establish it there.

* Maidencane (Panicum hemitomon): Another deep water grass species that forms
thin stands among submersed species. Relies solely on vegetative reproduction
through rhizomes unless seeds are exposed during drought conditions. Grows to
depths of 3 m in clear water and on sandy substrates. Also thought to be good sport
fish habitat.

* Southern watergrass (Luziolafluitans Synonymy: Hyrdochloa caroliniensis
Beauv.): A perennial grass that forms dense colonies in many water bodies in
Florida, occurring in shallow water or on normally flooded shorelines. Its leaves
can be underwater (to 1 m), floating, or emergent to 20 cm in height and on stems
to 1 m long. When occurring on moist soils, stems act as runners and leaves are
attached to the soil, creating a dense carpet of small, fragile leaves (7.4 mm wide to
7 cm long). Upon flooding, the stems become erect and the leaf blades densely
cover the surface of the water, giving the appearance of a firm substrate. This grass
tends to be more common in disturbed areas, especially on grazed shorelines where
herbivory limits the height of competing vegetation.

* Giant bulrush (Scirpus californicus): A large species of rush, stems reaching
heights over 3 m. Typically grows on sandy substrates with vegetative rhizome
reproduction. Dense stands provide nesting substrates for some bird species,
though generally occurs in higher energy environments and deeper water (2 m).
Lack of any leaf cover permits growth of submersed aquatics within dense stands.
Also thought to be good sport fish habitat.

The aforementioned species are a select few of interest to those managing aquatic

habitats within the state of Florida. All of these species occur on Lake Toho, some

constantly managed against and others physically planted for establishment. The

manipulation of species and habitats requires monitoring programs to assess the

responses and effectiveness of the treatments and strategies applied. The scale and

intensity of the habitat management project on Lake Toho provides an excellent

opportunity for discerning both the immediate and long-term effects of the commonly

applied treatments, as well as experimental combinations of treatments. The following

chapters detail the distributions and abundances of the species and communities found on


Lake Toho prior to the treatments, including the species listed above.














CHAPTER 3
TREATMENT-SELECTION STUDY

Introduction

To counteract the effects of impoundment, eutrophication, and invasion of exotic

species on aquatic habitats, lake restoration efforts have become higher priority and

increasingly disruptive in nature. In 1971, for example, the artificial dry down of Lake

Toho was considered a 'drastic' move and the removal of 172,000 m3 of muck in 1987,

unprecedented (HDR Engineering 1989). These projects pale in comparison to the 2004

dry down and removal of 7,000,000 m3 of muck. With the exception of three study sites

on the lake, virtually every significant stretch of shoreline is scheduled to be scraped,

leaving sandy beaches from roughly 30-120 cm in depth at high water. These depth

zones targeted for removal are generally occupied by dense, monocultural stands of

species like Pontederia cordata or Typha spp., and often create floating mats either

within or on the deep-water edge of these communities. As described in Chapter 1, these

mats can become progressively thicker as wind and wave actions fold the leading edge

over and onto itself and deposit drifting organic materials.

The purpose of the 1987 muck removal project was to remove the mats and dense

vegetation that were blocking fish spawning and nursery utilization of the shallower

reaches of the littoral zone, as well as impeding navigation of anglers. Habitat diversity

was also believed to be much lower in dense stands of Pontederia than native grassy

communities that once occupied the shorelines, before impoundment and eutrophication.

Since Pontederia had become extremely dominant in the shallower zones and was









thought to be at least partially responsible for the creation of organic barriers, mechanical

scraping for the 2004 project was scripted to remove this entire community. Literally, the

shoreward and lakeward extent of the Pontederia community was marked with PVC

poles, and bulldozers removed everything in between.

The 1987 project revealed that muck removal had only temporary effects, as

Pontederia and Polygonum species quickly reestablished and out competed most others

upon reflooding. The solution was thought to lie in monitoring and managing littoral

succession with cocktails of herbicides to control which species rebound and flourish.

Unfortunately, several broad applications must be made in order to impede the growth of

unwanted vegetation and to establish more desirable species, leaving the scraped areas

relatively barren during this period. These practices, combined with muck removal at

such a large scale, greatly increase the uncertainty of desired outcomes since both the

intensity and temporal extent of the disturbance are increased. With only small

percentages of the shoreline left unscraped, and the regrowth process slowed and limited,

monitoring the effects of this disturbance is imperative to making decisions about future,

similar projects.

The ultimate goal of this study was to establish and test a robust sampling design to

compare the differential vegetation responses to three separate shoreline-restoration

practices performed during an artificial dry down. These treatments will be tested in

another study at a later date and include

* Mechanical removal of muck and vegetation with unrestricted succession (i.e., no
herbicide management) during dry down.

* Mechanical removal during dry down, followed by herbicide application to aid
establishment of desirable species.









* Aggressive herbicide application during and following dry down, with the goal of
eliminating unwanted species without any mechanical removal of substrates or
vegetation.

* No treatment (control), other than artificial dry down.

These treatments were not applied during the term of this study, with the dry down and

muck removal process beginning several months after sampling concluded.

The primary objective of this study was to collect baseline data for the experiment

prior to dry down and treatment application. This included 1) defining pre-existing

littoral communities and their compositions, 2) identifying the underlying environmental

gradients associated with littoral distributions, and 3) using these baseline data to

construct a predictive vegetation model as an example of a future management tool in

lake restoration.

Methods

Study Sites

The littoral zone of Lake Toho is highly variable in terms of slope, communities,

wave actions, shoreline use, and so on. To minimize inter- and intra-site variation that

would confound treatment comparisons, yet provide robust spatial inference, we chose

three replicate areas (study sites) with similar slopes, an absence of physical anomalies

such as coves, stream outflows or abrupt changes in topography, and areas with similar

grazing pressures, all bordered by cattle ranches (Figure 3-1). Cattle ranches are the

predominant land use practice for the southern two-thirds of the lake, with most ungrazed

or substantially developed shorelines occurring on the northern end.

The sites all contained fairly dense stands of Pontederia and occupied a depth zone

of roughly 0-135 cm (0-53 in) in water depth at a maximum pool stage of 16.75 m









N
* E
S
[] 0 0 14 ft depth classes


Figure 3-1. Locations of three replicate study sites receiving various treatments. Site one
is located just south of Brown's Point on the south western shoreline of the
lake, site two is located on South Steer Beach on the southeastern stretch of
shoreline and site three is located in Goblet's Cove on the east shore.

(55 ft) NGVD. Each study site stretched 1600 m (approx. 1 mi) of shoreline, composed

of the four previously described treatment blocks of 400 m each (Figure 3-2). Maximum

water depth of the plots, or their lakeward extent from the shoreline, was delimited by the

approximate maximum water depth to be mechanically scraped during a dry down and

extended just beyond the deep water extent of the Pontederia community. The total area

of each treatment block varied slightly then, as each was 400 m in shoreline length but

the lakeward extent determined by slope and community type. A 25 m spray buffer was

established around each 1600 m study site to minimize the effects of routine herbicide

applications in other areas of the lake. Due to the extremely invasive nature of water









hyacinth (Eichhornia crassipes) and water lettuce (Pistia stratiotes) and given the

problems they have caused on Lake Toho historically, occasional spraying of small

groups of these species was allowed when and if they appeared. Additionally, study sites

were unable to be isolated from lake-wide applications of floridone treatments, which

were applied systemically in the constant management of the nuisance submersed

aquatic, Hydrilla. All other applications, however, including the periodic spraying of

cattails or floating mats was eliminated.

Digital Orthographic Quarter Quads (DOQQ's) taken in 1999 at 1-m2 resolution

were layered with a bathymetric map (Remetrix LLC 2003) of the lake using Arcview

GIS 3.2 software. Eight random sample points were selected in each treatment block,

stratified by four depth classes. The locations of these points were restricted to areas with

a maximum slope of 0.3 m over 30 m. This was accomplished by overlaying a 30x30 m

grid onto the bathymetric GIS (Geographical Information Systems) layer and restricting

point selection to the contour lines that were at least one grid cell apart. Two of the grid

cells were randomly selected from each depth class and the coordinates of their centroids

were located in the field with a Global Positioning System. This procedure resulted in 32

random sample locations per study site, eight per treatment block and two per depth class,

all located a minimum of 30-m apart and on similar slope gradients.

Sampling was initiated in June of 2002, providing two years of pretreatment habitat

descriptions. All three study areas were sampled in their entirety twice a year, in June

and December of 2002 and May and December of 2003. These sampling times coincided

with low pool (summer) and high pool (winter) water stages as well as growing and































B

N

















Figure 3-2. Individual study sites and their assigned treatments. A) Site 1. B) Site 2.
C) Site 3. White is designated as a control plot, Orange is an aggressive
herbicide treatment, Green is muck removal without herbicide follow-up and
Blue is muck removal followed by repeated herbicide application.

































Figure 3-2. Continued

non-growing seasons. For temporal analyses, one site was randomly selected for

sampling each month, resulting in 11 months of 32 samples in the period of our study.

Environmental Variables

Vegetation samples were collected using a 0.25-m2 quadrat, cutting all standing

vegetation at the substrate level and placing it in plastic bags where it was transported to

the University of Florida for sorting. The numbers of stems were counted for each

species in each quadrat and the species were then oven dried to a constant weight to

determine dry biomass. Importance values were calculated for each species in each

quadrat with the formula:

(Relative Biomass + Relative Density)/2 *100

This value gives a good estimate of species importance within a given quadrat and

is not biased towards large, few-stemmed (e.g., Typha spp.) or small, numerous-stemmed









species (e.g., Eleocharis spp.) (McCune and Grace 2002). This calculation also

relativizes the dataset, eliminating the need for transformations typically applied to

density or biomass data that can vary by orders of magnitude between species and

samples.

Soil cores were collected from each sampling location in June 2003, using

cylindrical aluminum corers. These corers measured 7 cm in diameter and were used to

extract the top 10 cm of substrate (Blake and Hartge 1986). Samples were packed in

Ziploc bags and placed on ice until moved to a freezer at the University of Florida. After

being oven dried to constant weight bulk densities were determined (Blake and Hartge

1986). Percent of organic content in the samples was calculated by loss on ignition

(Chapman and Pratt 1961, Jacobs 1971).

Hydrological variables were all collected based on the lake stage as recorded by

water control structure S-61 H on the south end of the lake. The average of at least four

water depths taken at each sampling location was referenced to the lake stage on that day,

giving a rough estimate of elevation for each sample. All depths were computed based

on high pool stage (16.75 m NGVD). Hydroperiods were then calculated for each

location based on the number of days flooded over the two year period of October 2001

to October 2003.

Data Analysis

The four sampling periods during the winter and summer of 2002-2003 yielded

four repeated measures of the 96 sampling locations. Plant species densities and

biomasses in each quadrat were summed from those sampling periods and then

relativized and their Importance Values (IV) computed. This gave an estimate of the

relative importance of each species in each quadrat over the four sample periods. For









example, the stem counts and biomasses of species one (Spi) in quadrat one (Qi) were

added together for the four sampling periods. Assuming the species occurred in all four

samples, the formula would look like

(SpiQiTi+ SpiQiT2 + SpiQiT3 + SpiQiT4)= Importance Value

The IV's of all species were added together and a percentage of the total

cumulative IV was calculated for each species. To reduce noise from rare species, only

those with cumulative IV's composing 95% of the total were retained for analysis.

Typically, species that occur in <5% of the samples are deleted (McCune and Grace

2002) but we used 5% of the total IV. This method is more representative of the actual

importance of a species throughout the sample for the same reason IV's are more

representative of a species' abundance than frequency.

The resultant matrix consisted of 96 samples by 24 species, reduced from the 66

species encountered throughout the study. All analyses of this matrix, unless otherwise

specified, were performed using PCORD software (McCune and Mefford 1999).

Outlier samples were tested for using an Outlier Analysis, which creates a

frequency distribution of average Sorenson distances of each sample from every other

sample in species space. At a cutoff level of 2.0 standard deviations from the grand mean

(McCune and Grace 2002), no outliers were detected.

A hierarchical, agglomerative Cluster Analysis was performed to find groups (or

communities) of similar species compositions. Flexible beta (-0.25) linkage and

Sorenson distance measures were chosen for their space conserving properties,

compatibilities with each other, and their advantages with non-normal data (McCune and









Grace 2002). This analysis grouped similar sample units based on species IV's, using

multiple species as a basis for deciding on the fusion of additional groups.

An Indicator Species Analysis was performed for two reasons: 1) to determine the

optimum number of clusters for further analysis and 2) to define those clusters in terms of

representative species. This analysis uses the proportional IV and frequency of a

particular species in a particular cluster relative to its IV and frequency in all other

clusters (Dufrene and Legendre 1997). The results are expressed as a percentage, or

Indicator Value, which is a measure of how representative a species is of a particular

group. A value of 100 would indicate a perfect representative, a species that was always

present in that group and never occurred in any other group. The statistical significance

of that value is then evaluated with a Monte Carlo test (1000 permutations), with the null

hypothesis being that the value is no larger than expected by chance (McCune and Grace

2002). The corresponding p-values of each species were the basis for the decision on

how many clusters to choose (i.e., the level of clustering that produced the most species

with p-values <0.05) (McCune and Grace 2002). The species with low p-values and high

indicator values were used as the community descriptors (cluster labels) in future

analyses.

The mean IV's of the indicator species at several depths were tallied for each

cluster and plotted against water depth. This was done as a simple, direct gradient

analysis to show a preliminary distribution of communities as related to depth.

A Nonmetric Multidimensional Scaling (NMS) ordination was used to assess the

dimensionality of our dataset (see following paragraph). This method of ordination

works well with typical heterogeneous community datasets that are laden with zeros and









have non-normal distributions. Generally, in a species by sample unit matrix there may

be a large proportion of zeros, or many species with few occurrences (high beta-

diversity). The broader the range of environment covered by the study, the more sparse

the matrix. This creates problems in many ordinations as zeros can be interpreted as

shared values or positive relationships and are grouped together. This is referred to as the

"zero-truncation problem" (Beals 1984 and McCune and Grace 2002). NMS is less

affected by this problem because of its use of ranked distances. Additionally, NMS

avoids assumptions of linear relationships among variables unlike other, more common

ordination methods like PCA and CCA.

The purpose of the ordination was exploratory in nature to assess the

dimensionality of the dataset (i.e., to see how well the data were structured). Too many

dimensions are difficult to interpret and would be representative of a very complex

dataset. The goal of the ordination is to examine the data in as few dimensions as

possible, without losing the structure inherent in the data. Each dimension, or axis, is

synthetic and represents measured or unmeasured environmental variables along which

samples are distributed. The amount of variance explained by the ordination and how it

is distributed along the primary axes is reported as a coefficient of determination (r2)

between distances in the ordination space and the original space. Pearson and Kendall

correlations of the measured environmental variables are also calculated to show which,

if any variables are related to the synthetic axes. The overall structure, or how well the

dataset was able to be grouped, is reported as a stress value and instability measure.

McCune and Grace (2002) state that stress values for community data typically lie









between 10 and 20 and instabilities around 0.0001. Clarke (1993) and McCune and

Grace (2002) give more information on NMS.

Ordination results are shown in a graph of sample units plotted in species space in

the number of dimensions (axes) suggested, grouping samples with similar species

compositions and separating those with differences. This plot shows the relationship of

each sample to one another; the larger the distance between samples, the more dissimilar

their compositions. To show the distribution of samples along the measured

environmental gradients, joint plots of correlated variables (r2>0.30) were overlayed onto

the ordination diagram, with length and direction representative of their correlation to the

axes. The sample units were color coded according to the groups formed by the Cluster

Analysis to show community distribution along the gradients.

A Classification And Regression Tree (CART) model (S-Plus Tree Library, De'ath

2002) was then used to predict the communities identified by the cluster analysis using

the measured environmental variables alone. These models have been applied most often

to classify habitats or vegetation communities based on environmental characteristics,

resulting in an overall description of how different the groups are, which variables

distinguish the groups and a predictive model that can classify new samples into those

groups (Urban 2002). This procedure works by recursively partitioning the

multidimensional dataset into subsets that are more homogeneous in terms of the

response variable, in this case, cluster or community membership (Vayssieres et al.

2000). The heterogeneity of each subset is measured as an impurity, calculated in our

model using the Gini index (Breiman et al. 1984, Crawley 2002, Venables and Ripley

2002). The goal of each split is to maximize the reduction in impurity. The model









identifies a single variable (and its threshold value) as the indicator for each branch of the

tree, as opposed to groups being distinguished along multivariate axes as in discriminant

analysis or logistic regression. This approach allows the inclusion of non-linear species

responses and is unaffected by interactions among variables (Vayssieres et al. 2000,

McCune and Grace 2002).

Once the largest possible tree has been grown, a process of eliminating superfluous

branches begins, called "pruning back to an honest tree" (Breiman et al. 1984). This is

done by testing each subtree for its error rate based on data that were not used to grow the

largest tree. Using cross validation, which acts as a test sample while extracting

information for all the cases of a data set, the final tree is constructed from all of the data,

using the best tree size (Vaysieres et al. 2000). The performance of the model is

measured by a misclassification rate, while the amount of variation explained by the tree

is reported as 1-Relative Error, or more strictly, 1-Cross Validated Error.

The final output is a pruned tree with barplots under each leaf showing the

composition of the final groups, as well as the number of samples in that leaf. Threshold

values of the variables determining the splits are shown at each node and the length of the

branches between nodes indicates the strength of the split. Several combinations of the

variables water depth, hydroperiod, percent organic and bulk density were used as

continuous predictors, while site and whether or not the sample occurred on a floating

mat were used as categorical variables. The final tree incorporated water depth, bulk

density, study site, and floating mat variables.

A Multivariate Regression Tree (MRT) analysis was conducted to identify

communities based on species IV's and where they occurred along environmental









gradients, and to compare the resultant communities (leaves of the tree) with those

formed in the cluster analysis and CART model. This was done with the same Tree

Library in S-Plus as our CART analysis, which is somewhat limited in terms of distance

measure options. This software only allows for Euclidian distance measures with MRT

analyses, which is not typically used with non-normal data. De'ath (2002) and Urban

(2002) suggested ideally using a distance-based MRT (db-MRT) for data of this type, but

since we were primarily interested in MRT as an independent comparison to the other

analyses, we opted for a practical rather than ideal solution and employed the Euclidian

distance measure provided in the software. This method uses the sum of squared

Euclidian distances about the multivariate mean of samples as an impurity measure of

each node, and each split is made to maximize this sum of squares between nodes and to

minimize it within nodes (De'ath 2002). Each leaf is then characterized by the

multivariate mean of its samples, the number of samples within that leaf and their

defining environmental variables. The percent of variation explained by the tree is

reported as 1-Relative Error, or more strictly 1-Cross Validated Error. Species variances

are tabulated to show the contributions of individual species at each split and how well

the tree explains their variations, as well as the percent of variation explained by each

split. In short, this technique partitions the samples into communities using both species

IV's as well as the associated environmental variables, and provides the threshold values

for each partitioning variable. The resultant communities are defined not just by species

compositions but where they occurred on the environmental gradients as well, providing

a more detailed, inclusive description than those defined by the Cluster Analysis.









Results

Of the 66 species recorded over the four sampling periods, 24 comprised the top

95% of the cumulative importance values (Figure 3-3, Appendix A). The summed

dataset resulted in 96 samples by 24 species, which was divided into five communities

based on the cluster analysis. The number of clusters was chosen based on the ISA,

where the group with the highest number of species with indicator values greater than

expected by chance was selected. With five groups, 17 of the 24 species had p-values

<0.05 (Table 3-1). The ISA identified the following species as strong indicators of

community type (clusters):

* Luziolafluitans: (LUZFL) also known as Hydrochloa caroliniensis

* Nuphar luteum and Nymphaea odorata: (NUPLU NYMOD) Nuphar luteum is
currently being reclassified as Nuphar advena

* Pontederia cordata and Alternanthera philoxeroides: (PONCOALTPH)

* Hydrilla verticillata, Lymnobium spongia, and Ceratophyllum spp.:
(HYDVELYMSP_CERSP)

* Panicum repens and Eleocharis spp.: (PANREELESP)

These groups are hereafter referred to by species code, which consists of the first

three letters of genus and the first two of specific epithet (e.g., Luziolafluitans = LUZFL)

(Appendix A).

The approximate distributions of these clusters were preliminarily displayed by

simply plotting the mean IV's of each of the indicator species in each cluster against

water depth (Figure 3-4). This plot showed the PANREELESP community occurred in

the shallowest depth zones, exhibiting a bimodal distribution with LUZFL occurring at

intermediate depths. The PONCOALTPH community completely dominated depths









ranging from roughly 0.6-1.2 m in depth, while the HYDVE_LYMSP_CERSP and

NYMOD NUPLU communities occurred at deeper water depths.
rr-----------
II 95% '-,
66 Total Species ,, I
2| 124 Species "

SI II I"
II0I
0-- ---I I .





30

2E

2C
v I --------------------------,---- -----,-.------,--------------| 3 5



S-,------------------------- 1 5





Species

Figure 3-3. Percent of cumulative Importance Value (IV) for each species, with 24
comprising 95% of the total. Appendix A lists these 24 and the 42 less
common species.

The NMS ordination resulted in three dimensions, cumulatively explaining 78% of

the information in the dataset. Axis 1 explained the majority (41%) and bulk density and

percent organic were most correlated (Pearson and Kendall) to this axis (r2 = 0.54 and

0.27, respectively). Water depth and hydroperiod were most correlated to Axis 2

(r2= 0.55 and 0.48, respectively), but this axis explained the least amount of variation

(17%). Axis 3 was the second most important axis, explaining 21%, suggesting some of

the structure in species composition remains unexplained by our measured variables.







40


Figure 3-5 is a plot of sample units in species space, showing the two dimensions

most correlated to our measured environmental variables. By overlaying cluster

Table 3-1. Indicator values of species in the Treatment-Selection study, with values
ranging from 0-100.


Group


P-value
0.001
0.001
0.188
0.043
0.047
0.001
0.001
0.024
0.051
0.499
0.001
0.001
0.001
0.023
0.023
0.001
0.001
0.001
0.03
0.001
0.045
0.001


1


I


I


I


Spp code

AXOFU
BRAMU
HYDSP
LUDRE

PANRE
UNPAS
BACCA
POLHY
EICCR
LYMSP

PANHE
LUDSP
CERSP
HYDVE
ELESP
UTRSP

TYPSP


I


I


I


I


Cluster
1
19
2
2
1
8

6
33
0
6
0
0
10
0
0
0
0
0
0
ol
0
o


2

0
0
0
1
2
0
3
0
9
37
1
0o
31
0
8
0
0
33

0


0.388 SAGLN
0.481 ELEQU


3

0
19
26
0
0
1
2
1
14
0
0

1
24
0
0
0
2
0
20
0
8
0


Species with high indicator values are highlighted accordingly and are used
as community descriptors for each group.


membership onto the ordination, we see the distribution of the communities along these

axes and their relation to one another.

Shallow water communities are located at the top of the graph and deeper water

communities at the bottom. Those associated with highly organic soils are on the left and

those with high bulk densities (mineral, low organic) are on the right. This figure also

shows the obvious interactions between hydroperiod and water depth as well as between

bulk density and percent organic, and their orthogonality to each other. Figure 3-6 is the


I NYfMO


1


Group











same diagram but with the plots labeled, showing a clear grouping of Site 1 in the deepest

water zone. Nearly the entire HYDVELYMSP_CERSP community comprised Site 1

samples, while the deeper samples of Site 2 and 3 lie within the PONCOALTPH

community. The labels assigned to each sample indicate the site first (1-2-3), the

treatment plot second (A-B-C-D), the depth class third (1-2-3-4) and which of two

samples it represents from that depth class last (A-B).


100
--LUZFL
--NUPLU/NYMOD
S --PONCO/ALTPH
80 /HYDVE/LYMSP/CERSP
6 PANRE/ELESP







a 40-



20




0 0.2 0.4 0.6 0.8 1 1.2 1.4
Water Depth (meters)


Figure 3-4. Plot of mean IV's of the indicator species in each cluster over several depth
classes

Plotting the weighted average species scores onto the ordination diagram shows the

average position of each species along each ordination axis (McCune and Meoff 1999).

Figure 3-7 shows all 24 species and their relative positions to the measured gradients,

with the indicator species from each cluster highlighted accordingly. The species

occupying the upper right corner of the graph, in the shallow water and with high bulk







42



densities are mostly grassy species, including Eleocharis spp., Axonopusfurcatus,


Panicum repens, Luziola fluitans, Eleocharis quadrangulata, and a small, succulent


V V
V V 0 0


v VfV Pct Organi





Hydropeod
Hydroperiod v


Cluster
* LUZFL
o NUPLU NYMOD
V PONCO ALTPH
HYDVE LYMSP
PANRE ELESM


*
*
S
0
* *

mo Bulk Density Axis 1


*Depth


Figure 3-5. NMS ordination plot of sample units in species space, color coded by
community. Distances between samples is representative of the dissimilarities
in species compositions. Joint plots of correlated environmental variables are
displayed as red vectors, based on Pearson and Kendall correlation coefficients.
The direction and length of the vector is representative of the direction and
strength of the variable's relationship to the corresponding axis.








43




3A1B

X 3D1B

Cluster 1C1A 3C1A 2A1B
L L 1B1A 1B1B 3B1A 3
LUZFL 112B1 B
2B1B
o NUPLU NYMOD
v PONCO ALTPH 1C1B 3D1A 2C1B
HYDVE LYMSP CERSP 2D1B
PANRE ELESM 2B1A
3A3A
1D1A 3C2B
3BA A
,f 3B1B
3A1A 22
1D1B0
OlA1B 1A1A
2B2B A1B WA
2D2A 1C3B 2B A SC2A
V V 102B 1B2A 2A
2B3B 2D2B 1A2E, .,,,
3B2A 2DIA
2A4A V 2 B 2A3A 4A 024B BulkDensity Axis 1
._... V 3A3B 2B4B A i
2D3A2C3 D 2B 3 B
2 A.2CA 2 pt Organic 2A4B
3D2A 23 B 3 3A
3C3A D2BA3A
2D3B 23 1C4A 1B2B
V 311838 V
SI1D2A
3D3B 3B3B
DA2D4
/V 1c 1D4A
2C4B
Hydroperio 1B4B

Water 14pth 1D3B

2B4A

1C4B
1D3A

1D4B1A4B
1 A4A

1 C4A






Figure 3-6. The same NMS plot shown in Figure 3-5 but with sample units labeled for
interpretative purposes.
























PANHE
+


3SAGLN + PctOr
SAGLN +-
+ POLHY
STYPSP +

LUDSP
+ + HYDSP

Hydroperiod


+AXOFU

ELESM


LUDRE
+


PANRE


ELEQU


+ lml


UNPAS


Bulk Density


Axis 1


+ BACCA
+ EICCR


,UTRSP


Depth


LYMSP


CERSP


HYDVE


Figure 3-7. Weighted average species scores overlayed onto NMS ordination plot.
Indicator species are highlighted and color coded according to cluster
(community) membership. Locations are representative of each species'
average location along the measured environmental gradients.

Ludwigia repens. As the samples increased in depth, the bulk densities generally

decreased. The species with the lowest bulk densities and organic matter were

Pontederia, Sagittaria lancifolia and Typha spp. The deepest water samples had higher

bulk densities and consisted of mostly submersed or free floating species, including

Hydrilla, Utricularia spp., Ceratophyllum spp., and Lymnobium spongia.


Cluster
* LUZFL
o NUPLU NYMOD
* PONCO ALTPH
HYDVE LYMSP CERSP
PANRE ELESM









We can also show the distribution of our indicator species in relation to these

gradients by scaling the symbols of the sample units they occurred in according to their

IV's; the larger the symbol, the higher the IV in that sample. There was considerable

overlap between samples with high values of Panicum repens and Eleocharis spp.,

justifying the grouping of these species into a single community (Figures 3-8 and 3-9).

Luziolafluitans was also important in several of the PANREELESP samples, though

highest values occurred in slightly deeper water (Figure 3-10).

Dominance of Pontederia is evident in Figure 3-11, though some overlap occurs

with the LUZFL community at shallower depths and higher bulk densities, representing

the transitional area between dense Pontederia and shallower, grassy communities. The

high values of percent organic matter associated with this community is easily displayed

by scaling the sample symbols according to their soil percentages, instead of their species

IV's. Clearly, there is a strong relationship between samples with high IV's of

Pontederia and those with highly organic soils (Figure 3-12). Figure 3-13 shows the

distribution of Hydrilla along the gradients.

The CART model produced a tree pruned to six leaves, with four of the five

communities represented (Figure 3-14). The NYMOD NUPLU community was not

delineated at this level of branching, while the LUZFL and the PANREELESP

communities were found at varying levels of dominance depending on soil characteristics

and water depth. Essentially, the PANREELESP community was completely dominant

at less than 18 cm (7 in) in water depth but overlapped with LUZFL from 28-57 cm (11-

22 in). LUZFL, meanwhile, was dominant between 18-28 cm (7-11 in) and was the

most dominant community at less than 57 cm (22 in) when bulk densities were low.







46




Community PANRE
LUZFL <
o NUPLU NYMOD
PONCO ALTPH
HYDVE LYMSPCERSP
PANRE ELESM






*



S Axis 1

























Figure 3-8. Importance values ofPanicum repens in the sample units plotted in the NMS
ordination. Larger symbols represent large IV's within that sample. Samples
are colored according to community.







47



Community L
LUZFL ELE
o NUPLU NYMOD
V PONCO ALTPH
HYDVE LYMSP CERSP
PANRE ELESM











Axis 1

























Figure 3-9. Importance values ofEleocharis spp. in the sample units plotted in the NMS
ordination. Larger symbols represent large IV's within that sample. Samples
are colored according to community.









Community
LUZFL
NUPLU NYMOD
PONCO ALTPH
HYDVE LYMSP CERSP
PANRE ELESM






0
". *
*4


*S


Axis 1


Figure 3-10. Importance values of Luziolafluitans in the sample units plotted in the NMS
ordination. Larger symbols represent large IV's within that sample. Samples
are colored according to community.


I


I LUZFL


lee









Community
LUZFL
NUPLU NYMOD
PONCO ALTPH
HYDVE LYMSP CERSP
PANRE ELESM


V
ve-V V


y*V


'VT


Axis 1


Figure 3-11. Importance values of Pontederia cordata in the sample units plotted in the
NMS ordination. Larger symbols represent large IV's within that sample.
Samples are colored according to community.


PONCO












Community
* LUZFL
o NUPLU NYMOD
V PONCO ALTPH
HYDVE LYMSP CERSP
PANRE ELESM


Percent
Organic


0


04
*3


V


V
vo


Axis 1


Figure 3-12. Percentage of organic matter in each of the sample units plotted in the NMS
ordination. Larger symbols represent percentages of organic material within
that sample.







51



Community
LUZFL
o NUPLU NYMOD
V PONCO ALTPH
HYDVE LYMSP CERSP
PANRE ELESM











SAxis 1




HYDVE


















Figure 3-13. Importance values of Hydrilla verticillata in the sample units plotted in the
NMS ordination. Larger symbols represent large IV's within that sample.
Samples are colored according to community.













HYDVE CERSP LYMSP Importance of
ILUZFL Predictor Variables
NUPLU NYMOD
PANRE-ELESP
SPONCOCALTPH Bulk Dens 100
Water Dpth 95.6
Floating 31.6
Site 9.5





Bulk Dens <0.79 Bulk Dens>0.79 Bulk Dens >0.93 Bulk Dens <0.93



Water >18cm (7") Water <18cm (7")

|* Water <28cm (11") Water >28cm (11)"
LUZFL
(9)
PANREELESP
(6)
HYDVE_CERSP_LYMSP PONCO_ALTPH
0(10) (53)
LUZFL PANREELESP
(5) (13)
Error 0364 CV Error (pick) 0618 SE 00852
Missclass rates Null = 0 573 Model= 0 208 CV= 0.354


Figure 3-14. CART model of community distribution along the measured environmental
gradients. This model was pruned from a maximum tree size of 12 branches
to six, based on a cost complexity pruning curve, selecting the smallest tree
within one standard error of the best. The numbers of samples in each leaf are
shown in parentheses below each bargraph, which shows the compositions of
communities within each leaf (e.g. nearly all of 53 samples in the right-most
leaf are the PONCO_ALTPH community).

On the deeper water side of the tree, two leaves were formed based on bulk

densities. The PONCO_ALTPH community had lower bulk densities (<0.93g/cm3)

while more mineral soils had HYDVE LYMSP CERSP communities. The number in

parentheses below the PONCO_ALTPH community shows the complete dominance of

this group over all others in the tree, with 53 of the 96 total samples occurring in this

group. Bulk density was slightly more important in determining community distribution

in the model than water depth, while site and floating mat categorical variables were the









least important. The misclassification rate of the model was 35% and the amount of

variation explained was 64% (1-Relative Error). These values are well within range

considering the dynamic and complex system this dataset represents.

The confirmatory MRT was pruned to eight leaves with very similar groups as the

CART model (Figure 3-15). Water depth was only slightly more important than bulk

density in leaf formation, while site differences did account for one split in the tree. The

first split was at 48 cm (19 in) in water depth, with Panicum repens, Luziolafluitans, and

Eleocharis spp. comprising the shallower groups, very similar to the CART model.

Below 18 cm (7 in) in water depth, Eleocharis was common, while between 18 and

28 cm (7 and 11 in) Luziola was extremely dominant. From 28-48 cm (11-19 in),

however, there was a considerable mix of all three species, Panicum repens, Luziola

fluitans and Eleocharis spp. This overlap between communities was also evident in the

NMS diagram.

On the deeper water side of the tree, between 48 and 61 cm (19 and 24 in), a mix of

Luziola and Pontederia is found representing the border between the shallower grassy

communities and the dominant zone of Pontederia. The dense, monocultural zone of

Pontederia occurred between 61 and 108 cm (24 and 42.5 in) with 36 of the 96 total

samples representing this group. At water depths greater than 108 cm (42.5 in), however,

there were three groups depending on site and soil characteristics. Site 1 had very

dominant Hydrilla and Lymnobium spp., while Sites 2 and 3 had Nymphaea odorata at

higher bulk densities and a Pontederia/Hydrocotyle spp. community at low bulk

densities. The occurrence ofHydrocotyle spp. with Pontederia at that water depth and








54



ALTPH
AXOFU Water <48cm (19") Water >48cm (19")
HYDSP
LUDRE Importance of
PANRE Predictor Variables
UNPAS
BACCA
POLHY Water Depth 100
EICCR
LYMSP Bulk Dens 98.5
PONCO
PANHE Site 58.9
LUESP Floating 16.9
HYDVE
SELESP
UTRSP
NUPLU
TYPSP
NYMOD Water >18cm (7") Water <18cm (7") Water >108cm (42.5") Water <108cm (42.5")
SAGLN
ELEQU
Water >28cm (11") Water <28cm (11")


S I > (8)
ELESP Site: 2,3 Site: 1 Water <61cm (24") Water >61cm (24")
(13) (6)
PANRELUZFLELESP LUZFL

Bulk.Dens >0.24 Bulk.Dens <0.24 II
(12) (36)
--- LUZFL PONCO PONCO
(9)
SI HYDVE_LYMSP
(5) (7)
NYMOD PONCOHYDSP
Error 0.456 CVError (pick) 08 SE 00819



Figure 3-15. MRT analysis, with terminal groups of species based on IV's and their
associated environmental variables. This confirmatory analysis shows species
groupings and distributions along environmental gradients, independent of the
cluster analysis. The numbers of samples in each leaf are shown in
parentheses below each bargraph, which shows the compositions of species
within each leaf.


low bulk densities is indicative of a floating mat community. This difference between


sites in the deep water was also evident in the NMS diagram (Figure 3-6).


Table 3-2 details the nodes of the tree, showing the contributions of each species at


each split and the variance explained for each species. For example, PONCO comprises


27.8% of the total species variance, of which 19.8% is explained by the tree, 8.7% by the


first split. LUZFL, also responsible for the first split, comprises 19.9% of the total


species variance, 10.7% of which is explained by the tree, with 5.6% in the first split.









The second split of 18cm is determined by LUZFL (1.2 %) and ELESP (1.2%), and the

third by LUZFL (2.8%) and PANRE (1.1%). The fifth split in the tree, separating Sites 2

and 3 from Site 1 is determined by HYDVE (5.5%). These five species, PONCO,

LUZFL, PANRE, ELESP, and HYDVE comprise 75.3% of the total species variance,

with 47.6% of it explained by the tree. Cumulatively, then, these species comprise 87.5%

of the variance explained by the tree (47.6% of 54.4%). This confirms their importance

as species representative of structure in our dataset, as suggested by the Indicator Species

Analysis.

The importance of the environmental variables is also displayed by Table 3-2, with

the summed total of each column representing the tree variation explained by that

threshold value of the variable in the split. The first split of 48 cm in water depth was by

far the most important, accounting for 36.4% of the variation explained by the tree

(19.81% of 54.43%). This suggests the largest differences in communities and the most

obvious structural variations occurred at roughly 48 cm in water depth. The second most

important split was at 108 cm in water depth, accounting for 21.4% (11.65% of 54.43%)

of the variation. These two splits represent the shallow and deep water extent of the

PONCO community, respectively, and outline the two primary community transitional

zones in terms of species compositions and distributions along the water depth gradient.

Discussion

In vegetation science, the concept of the plant community is absolutely

fundamental. It is at the community level that populations and individuals of a plant

species can be identified and grouped together to characterize the vegetation of an area of

a few square meters to several square kilometers. It is also at this level that the effects of











Table 3-2. Species variance in the MRT analysis of the Treatment-Selection study.


Species
ALTPH
AXOFU
BRAMU
HYDSP
LUDRE


Water
<48cm
0.18
0.2
0
0.08
0.02


Water
>18cm
0
0.65
0
0
0.01


Water
>28cm
0.01
0
0
0
0


Water
>108cm
0.41
0
0
0.03
0
0.26
0.05
0.01
0.02
0
0.03
0.3

0.05
0.02
0.07
3.48
0
0.01
0.04
0.01
0.32
0.01
0
11.65


Column totals represent the contribution of each split to the amount of variation explained
by the tree. Row totals represent the amount of species variance explained by the tree (tree
total) and the contribution of each species to total species variance, respectively.

allogenic factors are more easily examined and quantified, as interactions between

species affect the responses of individual species (Kent and Coker 1992). No studies on

Lake Toho in the past have approached vegetation description from a community level,

nor have any documented quantitative measures of individuals. This study provides the

first detailed description of the littoral communities targeted by restoration efforts,

explains their distributions along environmental gradients, and implements a sampling

design for the development of predictive management tools in lake restoration.


Site:
2,3
0.02
0
0
0.12
0
0
0
0
0
0
0.06
0.59
0.7
0.08
0.03
0
5.45
0
0.02
0.09
0
0.38
0
0
7.56


PANRE
UNPAS
BACCA
POLHY
EICCR
LYMSP


PANHE
LUDSP
CERSP
HYDVE
ELESP
UTRSP
NUPLU
TYPSP
NY' NIOD
SAGLN
ELEQU
Total


Bulk
dens>0.24
0.03
0
0
0.22
0
0
0
0
0.01
0
0.1
0.02

0.17
0.05
0.06
0.06
0
0.06
0.22
0
1 25
0
0
3.67


1.39
0
0
0
0
0.16


0
0.01
0.01
0.51
2.78
0
0.05
0.01
0.05
0.01
0
19.81


Water Tree
<61cm total
0.1 0.76
0 0.86
0 0.01
0.04 0.49
0 0.04
0.9 10.73
0.15 2.96
0.06 0.08
0 0.04
0.02 0.03
0.03 0.29
0.05 1.12
2.43 19.81
0 0.32
0 0.11
0 0.14
0 9.52
0.03 4.54
0 0.1
0.02 0.43
0 0.02
0 2.01
0.01 0.03
0.01 0.01
3.87 54.43


0.3
0.01
0
0
0.01
0
0.02
0
0
0
0
1.16
0
0
0
0
0
0
3.38


Spp total
2.64
1.92
0.1
1.93
0.26

7.24
0.39
0.23
0.18
2.51
4.9

1.06
0.3
0.47
12.82
7.57
0.2
3.2
0.49
2.77
0.98
0.17
100


1.07
0
0
0
0.06
0
0.03
0
0
0
0
0.56
0
0
0
0
0
0
4.5


LUZF 56 12 2.


PONCO 8.72









Community Descriptions

The Cluster Analysis, the NMS ordination, the CART and the confirmatory MRT

analyses all described the dominance of the PONCO_ALTPH community. NMS

ordination diagrams clearly showed the differences in soil characteristics for this group,

having the lowest average bulk density (0.27 g/cm3) and highest average percent organic

matter (51.6%) of any community. The CART model showed that regardless of site

differences, 53 of 63 samples taken in over 57 cm (22 in) of water were dominated by

PONCOALTPH. The confirmatory MRT produced very similar results, with 55 of 69

samples in over 48 cm (19 in) of water composed primarily of Pontederia, only

substantially occurring with other individuals at the shallower (48-61 cm) and deeper

(>108 cm) ends of its range.

The three groups identified by the MRT at depths greater than 108 cm (42.5 in)

consisted of Nymphaea odorata, Pontederia and Hydrocotyle spp., or Hydrilla and

Lymnobium. The presence of Hydrocotyle spp. with Pontederia suggests that the

community is floating at that depth, indicative of the deep-water extent of the Pontederia

community, transitioning to either floating leaved or submersed species, depending on

the site. At this transitional zone, habitats ranged from dense, organic floating mats to

sparsely vegetated, sandy soils over the distance of as little as one meter. The factors

determining community composition in this area were probably more related to storm

events and wave energies than actual water depths. With calm, stable water levels the

floating edge of the PONCO_ALTPH community would most likely march lakeward,

while periods of high wave energies would work to push back, break apart and even fold

over the floating mat edge (Figure 1-3, Chapter 1). Some of the most diverse samples in

this study occurred on thick floating mats, with as many as 18 species in one quadrat.









The small groups identified in this study containing Nymphaea and Hydrilla (14

of 96) were not representative of their overall presence in the littoral zone, but rather a

result of their more frequent occurrence in deeper water beyond the study sites. The

Whole-Lake Monitoring study detailed information regarding compositions and

distributions of communities beyond 130 cm in depth (Chapter 4).

The transition from dominant Pontederia to shallower, grassy species was

represented by the Luziolafluitans and Pontederia mixed group formed between 48 and

61 cm (19 and 24 in) in depth by the MRT. From there, groups were formed with

varying levels of Panicum repens, Eleocharis spp., and Luziola as depths decreased. The

same patterns were evident in the CART model, the NMS ordination, and the plot of IV's

vs. depth, showing a general, dominant mixture of these species in shallow water. The

highest average species richness was in the PANREELESP and the LUZFL

communities, averaging 12.4 and 7.7 species per sample, respectively. As water depths

increased, richness decreased, going from 6.0 species per sample in the PONCO_ALTPH

community to 5.9 and 5.3 in the NYMOD NUPLU and HYDVELYMSPCERSP

communities, respectively. However, if the floating mat samples were excluded from the

PONCOALTPH community, two of which had 14 and 18 species in a single quadrat,

the average richness fell to 5.1 species per sample, the lowest average of any community.

These results show the highly competitive nature of Pontederia and its associated

community in shallow water habitats and its ability to accumulate organic material with

its high productivity and densities. However, our data do not provide any information as

to the extent of organic accumulation in this community as we only collected the top 10

cm of substrate for our soils analyses. Based on several deeper cores taken for









photograph purposes, however, it is our belief that Site 3 had the deepest organic soils but

still rarely in excess of 20 cm. This would be logical since Site 3 occurs in a narrow,

isolated cove on the east side of the lake with presumably much lower energies than Sites

1 and 2. Additionally, this cove is the receiving point for canal C-31, which directly

drains East Lake Toho and is most likely a source of elevated nutrient levels. In

retrospect, peat depths in addition to our measured properties would have been useful for

comparative reasons, but our focus was on the soil characteristics in the zone of highest

root/rhizome activity.

Regardless of the actual depths of organic material on the lake, there is good

evidence that the majority of the littoral zone has very sandy substrates both shoreward

and lakeward of the Pontederia community. With the exception of the

NYMOD NUPLU community (21.3%), no other group had an average organic soil

content of more than 11%, as compared to 51.6% in PONCOALTPH. In fact, the

sandiest soils occurred in the HYDVELYMSP_CERSP community, with an average of

only 3.6% organic material. These data highlight the concerns of the lake managers,

showing that much of the shallow reaches of littoral zone on Lake Toho are densely

vegetated and dominated by Pontederia communities, having low diversities, highly

organic soils and occasionally forming floating mats. These communities are located

primarily between 57 and 108 cm (22 and 42.5 in) in water depth at maximum pool,

beyond which lie sandy substrates and several communities of floating leaved and

submersed aquatics.

The formation of such distinct zones of vegetation is no doubt aided by the stable

water levels maintained since the lake was impounded in 1964. For example, lake stage









data for the 10 years prior to the dry down initiated in November of 2003, show that the

present dense zone of Pontederia was flooded 82-100% of the time. The highest water

levels over this period covered the shallow edge of this community with up to 0.88 m of

water, while the lowest water levels never exposed the deep edge, remaining flooded at a

minimum depth of 60 cm. However, if we look at the stage data for a 10-year period

prior to the impoundment (1950-1960), this same zone had a hydroperiod of 66%-90%,

drying out much more frequently than at present. In fact, the lowest water levels dropped

below even the deepest edge of this community by nearly 0.5 m. The biggest contrast,

however, between historic and present day water levels, were the flood stages. The

highest water levels over the historical 10-year period would have flooded even the

shallowest edge of this community by almost 2 m. Such an astatic environment would

surely limit the ability of species like Pontederia to dominate large sections of shoreline,

with droughts encouraging germination of grass species and flood waters ripping loose

floating mats. It is clear from the results of this study that the Pontederia community has

benefited from the stabilized lake levels and has increased its shoreward and possibly

lakeward extent since impoundment.

Previous Studies

Vegetation studies in the early 1970s (Holcomb and Wegener 1971) and late 1950s

(Sincock et al. 1957) recorded species frequencies along transects that ran perpendicular

to shore and spanned the entire extent of the littoral zone, providing indundation

tolerances or distributional ranges of each species. The only previous study that

compared pre and post muck-removal habitats in 1986 (Moyer et al. 1989) also looked at

individual species responses by recording their frequency of occurrence along four

transects. These data were presented as the frequency of several common species and









gave no reports of how they were distributed along depth gradients. No quantitative

measures were recorded and evidence of increased/decreased densities or changes in

structural habitat characteristics could not be identified.

Though these three studies were conducted in different areas of the lake and used

different techniques, a general trend in habitat change is still evident. The earliest study,

prior to the impoundment of the lake in 1964, showed a higher diversity of grassy species

in the zones now targeted for restoration, most of which no longer occur. However,

Panicum repens and Luziolafluitans were among the most frequent in shallow areas even

then. In the early 1970's, Pontederia cordata and Polygonum spp. had appeared at low

frequencies and were described as occurring in narrow bands just below the low pool

line. It was reported that Luziola and Panicum were the dominant plants in the zones of

periodic inundation and together with Pontederia served as good spawning habitat for

sport fish, including largemouth bass. By the 1986 study, however, Pontederia,

Polygonum and Alternanthera philoxeroides were among the most frequently

encountered species, along with Luziola, Panicum repens and Bracharia mutica. These

findings were more similar to the results of this study, though no quantitative

comparisons can be made. While Panicum repens and Luziola still dominate the

shallower areas, it appears that Pontederia has moved shoreward from the mean low pool

level into the zone of periodic inundation. One reason for this may have been the dry

down in 1987 that coincided with the muck removal. Wegener et al. (1973) suggested

there were substantial increases in both the densities and expansion of Pontederia

following the 1971 dry down, and similar results probably occurred after the 1979 and

1987 dry downs. Even the transects located in scraped areas showed an almost complete









rebound of Pontederia in just two years after the 1987 muck removal project (Moyer et

al. 1989) and an even quicker response probably occurred in the unscraped areas.

Management Implications

The results of this study will help to more accurately determine Pontederia

community responses to dry down and several other treatments. By measuring structural

characteristics of the habitat targeted for restoration and defining the communities in

terms of specific densities and biomasses, the effects of the various treatments will be

quantified and much less cryptic than in previous studies. The CART model used in this

study on the pretreatment data was able to predict which communities occurred in the

targeted areas, given several environmental conditions. The MRT analysis was

extremely supportive of those predictions and community definitions, as well as their

distributions among water depths, soil types and site locations. Using the same CART

and MRT analyses on data collected in the future, predictive models can be used to

determine community types and responses to given treatments. For example, Figure 3-16

shows a hypothetical CART model that predicts communities based on several factors

(type of treatment applied, water depth, time since application, etc.) that would provide

managers with a valuable tool in lake restoration. These models will be applicable to

future restoration efforts on Lake Toho as well as other similar lakes in the region. With

the framework implemented in this study, the long-term monitoring programs necessary

to determine the effects of these large-scale restoration efforts are now in place.










Treatment


SControl


Herbicide





Water


Bulk Dens

I 0


Scraped


No Herbicide

r
7


Water


9

10
Herbicide 11 12


8


2 5 6


Figure 3-16. A hypothetical CART model to be created following years of post-treatment
data collection. With reasonable probabilities, for example, one could predict
community compositions based on the treatment applied and the location
along the environmental gradients.














CHAPTER 4
WHOLE LAKE MONITORING

Introduction

The previous chapter dealt primarily with the pre-restoration communities lying

within the targeted areas of muck removal. The sampling techniques of that project were

designed specifically to monitor the differential successions of littoral communities

following various treatments. Therefore, inter- and intra-site variations were minimized

and the sampling efforts were restricted to depth zones receiving specific treatments.

Beyond the treatment plots, however, similar restoration efforts are planned for most of

the remaining shoreline, including muck removal and aggressive herbicide application to

control successions. These treatments will undoubtedly have an enormous impact on the

littoral communities of the lake, including those not specifically targeted by mechanical

removal or even herbicide efforts. This emphasizes the need to monitor and document

the spatial and temporal responses of the littoral zone as a whole, in addition to

determining the efficacy of specific treatments, as discussed in Chapter 3.

Previous studies of natural or artificial dry downs on Lake Toho (Wegener et al.

1973, Moyer et al. 1989) and Lake Okeechobee (Smith and Smart 2004) have

documented a rapid growth and lakeward expansion of several grass and sedge species

(Eleocharis spp., Panicum hemitomon, Panicum repens, Paspalidium geminatum,

Luziolafluitans, etc.) in response to sediment exposure. However, these studies generally

only reported increases in frequencies and gave no estimates of changes in the structures

of communities. Without such information, there is little known about the spatial and









temporal effects of such activities. For example, was the increase in grassy species

temporary or still evident years after flooding? Were the effects similar throughout the

lake and along the same depth gradients? How long, if ever, did it take for the littoral

communities to rebound to pre dry down conditions and for that matter, what were the

pre and post dry-down communities?

More questions arise as the intensity of restoration efforts increase and now include

mechanical removal and aggressive herbicide applications in addition to dry downs. The

ultimate goal of this study was to establish a long-term sampling protocol to determine

quantitatively, the spatial and temporal responses of littoral communities throughout

Lake Toho. Upon establishment, the objectives were to 1) define preexisting

communities and their compositions and 2) identify the underlying environmental

gradients associated with their distributions.

Methods

Study Sites

Lake Toho has a highly variable littoral zone in terms of slopes, wave energies,

shoreline activities, and so on, and the resultant communities differ as well. To capture

this variability, five monitoring sites were selected from the less-developed, southern

two-thirds of the lake (Figure 4-1). Sitesl, 3 and 4 were located in broad, gently sloping

areas of shoreline, presumably more sedimentary in nature and subject to lower wave

energies, while Sites 2 and 5 were located on much steeper, higher energy areas of

shoreline. Additionally, all sites were subjected to grazing pressures with the exception

of Sites 4 and 5.

The boundaries of each site were determined by placing a 60-ha rectangle on

DOQQ's with 1-m2 resolution (1999) and bathymetric (Remetrix) layers in ArcView GIS










3.2 software. The area of the rectangle stayed constant but the shape was altered such

that it encompassed the zone of 0-2 m in depth (0-6 ft) (i.e., the sites on steep slopes

were stretched along the shore while those on gentle slopes extended much farther into

the lake).


Site 3
o Sampling locations
[] 0 6 ft depth classes

s^-"--^4a~


N

S


Site 5


Site 1


Figure 4-1. Five study site locations, each encompassing the 0-2 m depth zone. Sites 4
and 5 were located on ungrazed shorelines and Sites 2 and 4 were located on
steep slopes. Each site contained 18 sample locations, stratified by six depth
classes, with two samples occurring in each.

Vegetation Sampling

Sampling locations were stratified by six depth classes and were located on

maximum slopes of 30 cm change over 30 m in distance. This was accomplished by

placing 30x30 m grids onto the same GIS bathymetry layer and randomly selecting three

grid numbers from each depth class (Chapter 3). Coordinates of the centroids were









recorded and the sample was located in the field with a GPS (Global Positioning System)

on each sampling occasion. A total of three samples per depth zone were selected,

resulting in 18 per site and 90 on the lake (Figure 4-1). These locations were sampled

twice a year during high (winter) and low (summer) water periods, in June and December

of 2003, and May and December of 2004.

Vegetation was clipped at the substrate from 0.25-m2 circular plots and sorted by

species. Stem counts and biomass were recorded on sight. Before weighing, each

sample was squeezed and shaken until residual water was removed. While giving less

accurate measures of biomass than dry weight methods, this was an efficient way to

account for the overall size of an individual and combined with its stem count, the

relative importance of a species in a particular quadrat. Importance values were

calculated using the formula:

(Relative Biomass + Relative Density)/2 *100

This value is not overly biased by large, few-stemmed species (e.g. Typha spp.) or

small, numerous-stemmed species (e.g., Eleocharis spp.). This measure had an

additional advantage since wet weights were used and undoubtedly, different species had

differential amounts of water retention, even after squeezing. The Importance Values

(IV's) were relativized to each sample, eliminating potential bias of heavier weight,

submersed species in one sample versus drier, shallow-emergent species in other

samples.

Data Analysis

The four sampling periods during the winter and summer of 2002-2003 yielded

four repeated measures of our 90 sampling locations. The densities and biomasses of the

species in each quadrat were added together from those sampling periods and then









relativized and IV's computed. This gave an estimate of the relative importance of each

species in each quadrat over the four sample occasions. For example, the stem counts

and biomasses of species one in quadrat one were added together over the four sample

times; assuming the species occurred each period, the formula would be

(SpiQiTi+ SpiQiT2 + SpiQiT3 + SpiQiT4) = Importance Value

The IV's of all species were added together and a percentage of the total

cumulative IV was calculated for each species. To reduce noise from rare species, only

those with cumulative IV's composing 95% of the total were retained for analyses.

Samples were grouped based on species compositions using an agglomerative,

hierarchical cluster analysis. The number of groups and the representative species of

those groups were identified using an Indicator Species Analysis (ISA). A Nonmetric

Multidimensional Scaling (NMS) ordination was used to illustrate the relationships

between groups and to show their distribution along the water depth gradient. Detailed

descriptions of these analyses are provided in the Methods section of Chapter 3.

A Classification And Regression Tree (CART) analysis was performed to see how

accurately the communities defined by the cluster analysis could be predicted using water

depth, study site, grazing influence and whether or not a sample occurred on a floating

mat as environmental variables. A Multivariate Regression Tree (MRT) was then created

to compare the communities defined by the cluster analysis to those defined by species

IV's and their positions along environmental gradients. Detailed descriptions of these

methods are provided in Chapter 3.

Results

Of the 52 species recorded over the four sampling periods, 20 comprised the top

95% of the cumulative importance values (Figure 4-2, Appendix B). Our summed









dataset resulted in 90 samples by 20 species, which was divided into six communities

based on the Cluster Analysis. The number of clusters was chosen based on the ISA,

where the group with the highest number of species with indicator values greater than

expected by chance was selected. With six groups, 14 of the 20 species had p-values

<0.05 (Table 4-1). The ISA identified the following species as strong indicators of those

groups:

* Luziolafluitans and Panicum repens: (LUZFLPANRE)
* Typha spp.: (TYPSP)
* Pontederia cordata: (PONCO)
* Hydrilla verticillata and Ceratophyllum spp.: (HYDVE CERSP)
* Nuphar luteum: (NUPLU)
* Paspalidium geminatum: (PASGE)

The NMS ordination resulted in a three dimensional solution, cumulatively

explaining 0.739 percent of the variation in our dataset. Axis 1 explained the majority,

0.392, with Axes 2 and 3 explaining 0.195 and 0.152, respectively. For illustrative

purposes, only the two most important dimensions were displayed. Pearson and Kendall

correlation coefficients showed a fairly strong correlation of water depth to Axis 1 (r2 =

0.576) and a slight correlation to Axis 2 (r2 = 0.307). Figure 4-3 shows a joint plot of

sample units in species space with the water depth correlation vector. The distance

between sample units is representative of the dissimilarities in their species compositions,

with like samples grouped and unlike samples separated. The correlation of water depth

to Axis 1 and the direction of the vector suggest that the samples located on the right side

of the graph occur in deeper water than those on the left. The numbers of species that

occurred in each sample before rare species were deleted was also plotted as a diversity,

or richness measure. Richness was found to be slightly correlated to Axis 2, simply







70


_--------------,
52 Total Species ii 95% of Total
I 20 Species
!I.




2----------------


20




E
p1s5
0 10








Species


Figure 4-2. Percent of cumulative Importance Value (IV) for each species, with 20
comprising 95% of the total. See Appendix B for a list of these 20 and the 32
less common species.

showing that the samples near the bottom of the graph generally had more species


than those near the top.


Additionally, the weighted average species scores were plotted along these axes,


showing the average location of each species along the measured gradient (Figure 4-4).


Keeping in mind that water depth increases from left to right along Axis 2 and diversity


increases from top to bottom along Axis 1, we can suggest that generally, the species to


the right occur in deeper water, while the species on the top of the graph occur in fairly


uniform, or even monotypic communities. This indicates that when those species


occurred, diversity tended to be lower, or they tended to dominate each quadrat they were


found in.










Table 4-1. Indicator values of species in the Lake-Monitoring study, with values ranging
from 0-100.
P-values Spp code ID Cluster 1 2 3 4 5 6
0.019 ALTPH 3 20 4 33 0 0 0
0.057 BACCA 1 23 1 0 2 1 0
0.033 BAHIA 1 25 0 0 0 0 0
0.004 ELESM 1 37 0 0 0 0 1
0.177 HYDSP 3 2 1 18 0 0 0
0.001 1 0 0 0 0 0
0.516 PANHE 1 14 0 10 3 0 0
0.001 1 0 0 1 0 0
0.38 BRAMU 6 2 0 3 0 0 14
0.001 f 3 8 40 0 0
0.001 2 0 2 0 0 0
0.537 LUDSP 6 0 0 2 0 0 9
0.002 CERSP 4 0 4 0 53 23 4
0.001 HYDVE 4 0 1 0 77 16 4
0.002 6 0 0 0 13 17
0.001 NUPLU 5 0 2 0 0 85 0
0.058 SCICA 6 0 0 0 0 0 17
0.04 NYMAQ 5 0 0 0 5 22 2
0.08 NYMOD 6 0 2 0 0 6 18
0.627 CHARA 5 0 0 0 3 5 0
Species with high indicator values are highlighted accordingly and are used as
community descriptors for each group.

The indicators species' distributions in relation to these gradients can be shown by

scaling the symbols of the sample units they occurred in according to their IV's; the

larger the symbol, the higher the IV in that sample. Figures 4-5 and 4-6, respectively,

show how Panicum repens and Luziola occur frequently and with high values in the

shallower depth zones as well as with higher diversities. Pontederia cordata, however,

shows significant occurrence in other communities as well, specifically with the

LUZFLPANRE community at the deeper end of their range (Figure 4-7). Many of the

samples in the deeper water had large amounts ofHydrilla (Figure 4-8) and a few were

dominated by Paspalidium geminatum (Figure 4-9). The grouping of the

HYDVE_CERSP and PASGE clusters and the occurrence of both species in either group

shows the similarity and spatial proximity of these two communities.







72



0 (N











Depth






V 4Axis 1
*


Diverse
*
00


Community
LUZFLPANRE
STYPSP
V PONCO
HYDVE CERSP
NUPLU
S* PASGE





Figure 4-3. Lake-Monitoring Study ordination plot of sample units in species space, color
coded by community. Distances between samples is representative of the
dissimilarities in species compositions. Joint plots of correlated
environmental variables are displayed as red vectors, based on Pearson and
Kendall correlation coefficients. The direction and length of the vector is
representative of the direction and strength of the variable's relationship to the
corresponding axis.


















NUPLU


NYMOD
+


Depth


CERSP

NYMAQ

HYDVE +


Axis 1
CHASP
+


SCICA
+



Community
LUZFL PANRE
TYPSP
PONCO
HYDVECERSP
NUPLU
PASGE


Figure 4-4. Weighted average species scores overlayed onto the Lake-Monitoring study
NMS ordination. Indicator species are highlighted and color coded according
to cluster (community) membership. Locations are representative of each
species' average location along the measured environmental gradients.


+


BRAMU
+


HYDSP


LUDSP
+
ALTPH
+


PANHE


Diversity


BACCA
+


ELESM
+

I t* 1 1 -


PASNO











Community
* LUZFL PANRE
o TYPSP
V PONCO
HYDVE CERSP
NUPLU
* PASGE


Axis 1


Figure 4-5. Importance values of Panicum repens in the Lake-Monitoring samples, as
plotted by the NMS ordination. Larger symbols represent large IV's within
that sample. Samples are colored according to community.


* S

0


I PANRE











Community
* LUZFL PANRE
o TYPSP
V PONCO
HYDVE CERSP
NUPLU
* PASGE


Axis 1


Figure 4-6. Importance values of Luziolafluitans in the Lake-Monitoring samples, as
plotted by the NMS ordination. Larger symbols represent large IV's within
that sample. Samples are colored according to community.


0'


V











Community
* LUZFL PANRE
o TYPSP
V PONCO
HYDVE CERSP
NUPLU
* PASGE


Axis 1


Figure 4-7. Importance values of Pontederia cordata in the Lake-Monitoring samples, as
plotted by the NMS ordination. Larger symbols represent large IV's within
that sample. Samples are colored according to community.


'V
V
*9
v
V


g0 0


PONCO


* *












Community
* LUZFL PANRE
o TYPSP
v PONCO
HYDVE CERSP
NUPLU
* PASGE


Axis 1


HYDVE


Figure 4-8. Importance values ofHydrilla verticillata in the Lake-Monitoring samples, as
plotted by the NMS ordination. Larger symbols represent large IV's within
that sample. Samples are colored according to community.











Community
* LUZFL PANRE
o TYPSP
V PONCO
HYDVE CERSP
NUPLU
* PASGE


Atl1


Figure 4-9. Importance values of Paspalidium geminatum in the Lake-Monitoring
samples, as plotted by the NMS ordination. Larger symbols represent large
IV's within that sample. Samples are colored according to community.


PASGE















































Figure 4-10. Importance values of Nuphar luteum in the Lake-Monitoring samples, as
plotted by the NMS ordination. Larger symbols represent large IV's within
that sample. Samples are colored according to community.

Nuphar luteum also overlaps with the HYDVECERSP community and occurs in

the TYPSP community as well (Figure 4-10). The large spread of samples in the TYPSP

community suggests Typha occurs over a broad range of water depths and occasionally

overlaps with either the PONCO or NUPLU communities. The PONCO, TYPSP and

NUPLU communities occur near the top of axis one, indicating lower diversities where

these species dominate.


(N
U) NUPLU Community
X LUZFLPANRE
o TYPSP
V PONCO
O HYDVE_CERSP
NUPLU
PASGE




Axis 1



Axis 1









The CART model produced a rather complex tree, pruned to 11 groups. At this

level, 68.8% of the variation was explained by the model, with a 40% misclassification

rate. There were essentially three large groups formed; LUZFLPANRE community

occurring in <63 cm (25 in) of water, a mix of PONCO communities and transitional

groups between 63 and 127 cm (25 and 50 in) of water, and a predominantly

HYDVE_CERSP community occurring at depths greater than 127 cm (50 in) (Figure

4-11). There were several site differences delineated in the tree, most separating Sites 2

and 4 from the others. This separation occurred at both above and below 127 cm in water

depth, indicating significant site variation at several depths. Sites 2 and 4 were split from

the others at depths <127 cm due to a less robust PONCO community. The terminal

groups of these sites showed a mixture of either LUZFLPANRE or HYDVE_CERSP

with the PONCO communities, while Sites 1, 3, and 5 displayed the more typical,

moncultural PONCO group.

At depths >127 cm, Sites 2 and 4 were split from the others due to a more dominant

PASGE community, with mixes of TYPSP and HYDVE_CERSP communities occurring

at various depths. Sites 1, 3, and 5 however, all had robust HYDVE_CERSP

communities at >127 cm in water depth.

The MRT was pruned to eight leaves and produced similar results to the CART

(Figure 4-12). The four most abundant communities were Luziolafluitans at <63 cm (25

in) in water depth, a robust Pontederia community between 63 and 117 cm (25 and

46 in), dominant Hydrilla between 117 and 158 cm (46 and 62 in), and a codominant

community of Hydrilla and Paspalidium geminatum at depths >158 cm (62 in). These











results were confirmatory of the CART model, with the same dominant species occurring


at similar depth locations.


Water <63cm (251n) Water >63cm (251n)
HYDVE CERSP Importance of
LUZFL PANRE
NUPLU Predictor Variables
PASGE
PONCO
TYPSP Water Depth 100
Floating 32.8
Site 22.8





Water >127cm (501n) Water <127cm (50in)

L
LUZFL PANRE
(22)

Site 1,3,5 Site 2,4 Site 2,4 Site 1,3,5
Water >178cm (70in) Water <178cm (70n) 89cm 89cm t Ste 1
>196cm <196cm Site 2 Site 4
r <145cm >145cm
HYDVECERSP
(24) I I PONCO TYPSP
HYDVECERSP PASGE LUZFL PANRE13) (3)
(3) (3) HYDVE CERSP (4) (5)
5) --HYDVECERSP
PASGE TYPSP
(3) (5)
Error 0312 CVError(pick) 0562 SE 00726
Missclassrates Null= 0711 Model= 0222 CV= 04


Figure 4-11. CART model of Lake-Monitoring community distributions along the
measured environmental gradients. This model was pruned to 11 leaves based
on a cost complexity pruning curve, selecting the smallest tree within one
standard error of the best. The numbers of samples in each leaf are shown in
parentheses below each bargraph, which shows the compositions of
communities within each leaf (e.g., all 22 samples in the left-most leaf are the
LUZFLPANRE community).

One interesting difference between the MRT and CART model was the separation


of grazed and un-grazed sites at <63 cm in water depth in the MRT. Sites 4 and 5 had no


grazing pressures and the communities were much more diverse, with the terminal node


represented by a suite of species rather than one individual, including Eleocharis spp.,


Bacopa caroliniana, Bracharia mutica, Panicum repens, Paspalum notatum and







82



Pontederia. The other substantial site differences occurred between 117 and 158 cm (46


and 62 in) in depth, with Sites 3 and 4 having significant Nymphaea odorata and Typha


communities while Sites 1, 2, and 5 were dominated by Hydrilla.



ALTPH Water <117cm (46in) Water >117cm (46in)
BACCA
BAHIA Importance of
ELESM
HYDSP Predictor Variables
LUZFL
PANHE
PANRE Water Depth 100
BRAMU
PONCO Site 63.8
LUDSP Floating 14.9
CERSP
HYDVE
SPASGE
NUPLU
SCICA
NYMAQ
NYMOD
CHARA
Water <63cm (25in) Water >63cm (25in) Water <158cm (62in) Water >158cm (62in)


Site:1,2,5 Site:3,4



Site:4,5 Site:1,2,3 Site:2 Site:1,3,4,5 (23)
PASGEHYDVE
<145cm (57in) >145cm (57in)


L _- (11)
(8) (14) (4) (19) HYDVE
Ungrazed Diverse LUZFL HYDVEPONCO
Community PONCO (6) (5)
NYMOD TYPSP
Error 0537 CVError(pick) 0814 SE 00757



Figure 4-12. Communities identified in the Lake-Monitoring study by IV's and their
associated environmental variables, using the MRT analysis. This
confirmatory analysis shows species groupings and distributions along
environmental gradients, independent of the cluster analysis. The numbers of
samples in each leaf are shown in parentheses below each bargraph, which
shows the compositions of species within each leaf.

Table 4-2 details the species variance, amount explained by the tree, and the


species responsible for each split of the MRT. Hydrilla comprised 22.5% of the total


species variance, of which 13.03% was explained by the tree, 5.96% in the first split.


Also responsible for the first split was Pontederia, with 3.97% of its variance explained.


This simply means that the abundances of Hydrilla and Pontederia were both highly









variable among samples, and largely determined community structure as well.

Pontederia (4.14%) and Luziola (3.35%) determined the second split, while Luziola

(2.62%), Hydrilla (1.74%), Paspalidium (3.26%), Hydrilla (5.13%) and Typha (1.71%)

determined the remaining splits, consecutively. Summarily, these five species comprised

73.4% of the total species variance, 40.1% of which was explained by the tree.

Cumulatively, then, these species comprised 87% of the variance explained by the tree

(40.1 of 46.3). This supports the results of the cluster and indicator species analysis

which identified these species as indicative of the inherent community structure in our

study areas.

Table 4-2. Tabulation of species variance for the MRT analysis of Lake-Monitoring sites.
Species <117cm <63cm Site:4,5 Site:2 <158cm Site:1,2,5 <145cm Tree Spp Total
ALTPH 0.06 0.01 0 0 0 0 0 0.07 0.34
BACCA 0.01 0.04 0.04 0 0 0 0 0.1 0.7
BAHIA 0.02 0.05 0.04 0 0 0 0 0.11 1.06
ELESP 0.13 0.02 0.03 0.02 0 0 0 0.2 2.12
HYDSP 0 0 0 0 0.05 0.06 0 0.12 1.03
1.91 0.07 0 0 0 7.95
PANHE 0 0 0 0 0 0.01 0 0.02 0.47
PANRE 0.38 0.65 0.13 0 0 0.02 0 1.18 3.12
BRAMU 0.07 0.05 0.31 0.01 0 0 0 0.44 2.62
S3.9 0 0.75 0.07 0.12 0 9.05
0.04 0.87 0 0.37 0.27 0.71 3.98
LUDSP 0.02 0.04 0 0.02 0 0 0 0.07 1.52
CERSP 0.03 0 0 0.01 0 0.01 0 0.06 0.3
HYDVE 5.96 0.2 0 1.74 0 5.13 0 13.03 22.51
2.77 0 0 0 0.01 0.04 6.08 l
NUPLU 0.55 0 0 0 0.01 0.01 0.16 0.73 6.07
SCICA 0 0 0 0 0.01 0 0 0.02 0.71
NYMAQ 0.01 0 0 0 0 0 0 0.01 0.18
NYMOD 0.28 0 0 0 0.54 1.11 0.93 2.87 5.21
CHARA 0.02 0 0 0 0.03 0.07 0.11 0.22 1.17
Split total 16.25 9.42 3.17 3 4.27 7.25 2.96 46.32 100
Column totals represent the contribution of each split to the amount of variation explained by
the tree. Row totals represent the amount of species variance explained by the tree (tree
total) and the contribution of each species to total species variance, respectively.

The most important split in the tree occurred at 117 cm in water depth, accounting

for 35% (16.25% of 46.32%) of the variation explained by the tree. The second most


I









important split occurred at 63 cm in water depth, accounting for 20.3% (9.42% of

46.32%) of the variation. These two splits represent the most abrupt changes in

communities in terms of species compositions and their distribution along the depth

gradient.

Discussion

Community Descriptions

There were six distinct communities identified within the littoral zone of Lake Toho

during our study. Based on the NMS and CART analyses and confirmed by the MRT,

most of these communities were distinctly distributed along the depth gradient, with the

LUZFLPANRE community dominating between the high and low pool water lines,

dense PONCO communities occurring just above and below the low pool line, and the

deeper water generally having either HYDVE_CERSP or PASGE communities. TYPSP

and NUPLU communities were also present but were less common and more patchily

distributed in the deeper water zones.

Average species richness for each community ranged from 9.5 species per sample

in the LUZFLPANRE community to 3.5 in the HYDVE_CERSP community, following

a general decreasing trend with increasing water depths. The exception to the rule was

the NUPLU community that had the deepest average depth of any community (159 cm)

and the second highest richness, with an average of 6.0 species per sample. However,

other deep water communities (HYDVE_CERSP and PASGE) had lower average depths

than NUPLU due to their broader range of distribution, not necessarily because they

never occurred in deeper water. However, the relatively high number of species in the

few NUPLU samples is of interest and may help to explain the frequent visitation of

these habitats by anglers.









The dominant PONCO community had higher average richness than the

HYDVE_CERSP (3.5), TYPSP (3.8) and PASGE (3.8) communities, with an average of

4.8 species per sample. However, if the floating mat samples were excluded, having an

average of 7.0 species per sample, the PONCO community richness fell to 3.6, the second

lowest of all communities. The CART model found that between 63 and 127 cm (25 and

50 in ) in water depth, the PONCO community was extremely dominant in 13 of 25

samples and had a significant presence in all 25, occurring with HYDVECERSP,

LUZFLPANRE, and TYPSP communities at these depths. The MRT confirmed these

results, showing Pontederia as the single dominant species between 63 and 117 cm (25

and 46 in) in 19 of 23 samples and was still abundant in the remaining four samples,

occurring with Hydrilla. These two species do not actually occur in the same area,

spatially, but do occupy the same depths on occasion. Their grouping in both the CART

and MRT analyses is representative of the transitional zone between the dense, leading

edge of the PONCO floating communities and the open water, submersed communities,

where sharp, distinct boundaries separate the two. The fact they do not overlap spatially

is evident in the NMS diagrams of species IV's or weighted species averages. Notice that

the samples with high IV's of either species do not overlap and that the two are very

distant from each other in the ordination, showing distinctly different compositions

between samples containing either species.

Variations in communities by site were delineated in CART and confirmed in the

MRT, with each defining similar patterns. The CART model found that Sites 2 and 4 had

more dominant PASGE communities in deeper water (>127 cm) than Sites 1, 3, and 5,

which were dominated by HYDVECERSP communities. The MRT produced slightly









different terminal groups, showing a mixed community of Paspalidium and Hydrilla in

all 23 samples (100%) in depths >158 cm, regardless of site, and that site differences

occurred between 117 and 158 cm (46 and 62 in), with Hydrilla dominating those depths

at Sites 1, 2 and 5. Sites 3 and 4 were found to have Nymphaea communities between

117 and 145 cm and Typha communities between 145 and 158 cm. The NMS diagram of

species IV's shows the regular occurrence of Hydrilla and Paspalidium at the same

depths and even in the same samples (Figures 4-8 and 4-9). Additionally, the very close

proximity of the two communities in the ordination, HYDVE_CERSP and PASGE,

shows the similarities in their species compositions. It is probable that these two species

occur together more often than the CART model suggests.

Most of the deeper water site differences were a result of the clumped distributions

of the communities at those depths. While Paspalidium and Hydrilla tended to occur

throughout the deep water, the floating leaved and cattail communities were much sparser

and patchily distributed. Panicum hemitomon and Scirpus californicus were also patchy,

and did not occur frequently enough in our samples to be classified as their own

communities. While the shoreline slope dramatically affected the width of the

communities between sites, their compositions or distributions by depth did not seem to

differ consistently.

Another interesting site difference delineated by the MRT was between grazed and

ungrazed sites at depths <63 cm. While there was no substantial difference in average

species richness between the sites (9.5 and 11.7, respectively) there were no singly

dominant species throughout the shallow depths of the ungrazed areas. The bar graphs

under the terminal groups of the MRT show this difference well, as the eight samples









from the ungrazed sites had several frequently dominant species, while the 14 samples

from the grazed sites were completely dominated by Luziola (Figure 4-12). The visual

difference between the grazed and ungrazed shorelines was quite striking, with species

like Bracharia mutica, Hibiscus grandiflorus and Ludwigia spp. much more prevalent in

the ungrazed areas. Apparently, the low stature and carpet forming growth habit of

Luziola allows it to escape herbivory while benefiting from the absence of canopy grasses

eliminated by grazing. Without it, other species most likely tower above and shade out

Luziola, resulting in several taller, dominant species in the ungrazed communities.

Previous Studies

The studies conducted in the late 1950s (Sincock et al. 1957) and early 1970s

(Holcomb and Wegener 1971) suggest the littoral zone of Lake Toho has changed

substantially over the last 30 years. Though their techniques did not provide quantitative

estimates or community descriptions, general differences can be detected. Prior to lake

impoundment, for example, Pontederia did not occur in the vegetation studies and

species like Psilocarya, Stenophyllus, Echinocloa, and Fuirena were fairly common in

the seasonally inundated areas of shoreline. Hydrilla was not even documented until

1972, with species like Valisneria occurring in the deeper water. By 1970, however,

Alternantheraphiloxeroides, Polygonum spp., and Pontederia had become more

common, though still described as occurring in narrow bands below the low pool line.

Scirpus californicus was reported to exist in stands up to several acres in size in deeper

water and Paspalidium was described as abundant. These descriptions do not provide

comparable estimates of the littoral communities to our studies, but do depict major

changes.









While Panicum repens and Luziola have long been recorded in the shallow

communities, they may be more dominant today than historically. Both the 1971 and

1987 dry down studies seemed to substantially increase the frequencies of Panicum

repens (Wegner et al. 1973 and Moyer et al. 1989), an effect also documented on Lake

Okeechobee (Smith and Smart 2004). The biggest difference lies within the Pontederia

community, which has seemingly pushed the Panicum repens, Luziola, and Eleocharis

spp. communities shoreward with stabilized water levels. Whether the large-scale

removal of this community is an effective means in reestablishing grassy species in its

stead is not yet known. The implementation of long-term sampling protocols and the

detailed descriptions of pre-treatment communities provided by this study will help to

answer that question.














CHAPTER 5
SUMMARY

Communities

The vegetation samples we collected from June 2002 through December 2003

provided detailed information on the composition and distribution of plant communities

that occurred during this period. Unlike previous studies, we sought to define, analyze,

and monitor vegetation at a community level rather than by individual species and to

collect quantitative measures of habitat quality rather than frequencies or percent cover

estimates. The communities we defined were based on biomasses and densities of

species, giving strong representation of the habitat and compositions as they occurred.

The results of our two studies were very similar, showing distinct zones of vegetation

distributed along depth and soils gradients. The communities defined by the Cluster

Analyses and their predicted distributions with the CART models were well supported by

the confirmatory MRT analyses performed in both studies. Had soils data been collected

for the Lake-Monitoring study covered in Chapter 4, stronger predictions of community

distributions would have been available for areas beyond those targeted for muck

removal. These results are based on the latest multivariate community techniques, using

far more descriptive measures of the vegetation characteristics than collected previously.

Such descriptions are the first of their kind for Lake Tohopekaliga, and the resultant

predictive models may eventually be applicable to other lakes undergoing restoration

activities. The pre-treatment littoral communities defined by this study are described

below.