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Preliminary evaluation of the use of fast growing trees and cultures for cogongrass control on phosphate mined lands


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PRELIMINARY EVALUATION OF THE US E OF FAST GROWING TREES AND CULTURES FOR COGONGRASS CONT ROL ON PHOSPHATE MINED LANDS By ERIN N. MAEHR 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 2006

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Copyright 2006 By Erin N. Maehr

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iii ACKNOWLEDGMENTS I would like to thank my committee memb ers (Drs. Donald L. Rockwood, Greg MacDonald, Nicholas Comerford, and Larry Harri s) for their suggestions, valuable time, critical reviews, and edits of my thesis. A special thank you goes to Dr. Rockwood for his continuous guidance during data analysis and throughout my stay in the School of Forest Resources and Conservation. Much apprecia tion goes to the Florida Institute of Phosphate Research for funding this project. Another thank you is extended to Charles Cook, who always came to my aid in plant identification and supplied me with other useful advice throughout my research. I am grateful to Analytical Research Lab staff for analyzing my soil samples. Thanks go to Bijay Tamang, Brian Becker, Valerie Milmore, Jennifer OLeary, Nick Gerkin, and Mark Hotchkiss who were always willing to help me in the field despite high temperatures and missed Gator games. Thanks go to my family for showing me a better way to look at the world than just as a commodity and for just being supporters of my life. I would like to thank Jeff Kelly for his unfaltering faith in my abilities a nd assuaging any worries I had throughout the thesis writing process. Without him, I would have struggled through this long and tedious process. Jessica Kress, I do not know if I would have made it down here in a new place without thoughtful words, confidence in my abilities, and random cards that made me smile; your friendship is one that I will ch erish the rest of my life. I thank all my Gainesville friends, Samantha Pink, Jennifer OLeary, Jen D upree, Jason Liddle, Gerardo

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iv Celis, Eric Holzmueller, and Rob Robins, for making my stay an enjoyable one and lasting friendships that will endure for many years to come.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iii LIST OF TABLES............................................................................................................vii LIST OF FIGURES.............................................................................................................x ABSTRACT.......................................................................................................................xi CHAPTER 1 INTRODUCTION........................................................................................................1 2 LITERATURE REVIEW.............................................................................................6 3 METHODS.................................................................................................................16 Study Areas.................................................................................................................16 SRWC..................................................................................................................16 Natural Area........................................................................................................20 Experimental Design..................................................................................................21 SRWC..................................................................................................................21 NA.......................................................................................................................23 Analyses......................................................................................................................24 4 RESULTS AND DISCUSSION.................................................................................27 Objective 1 Effectiv eness of SRWCs.........................................................................27 Objective 2 Cultural Treatments.................................................................................32 Objective 3 Native Sp ecies Colonization...................................................................33 Herbaceous plants................................................................................................33 Shrubs..................................................................................................................43 NA trees...............................................................................................................45 Species Diversity and Site Similarity..................................................................46 Objective 4 Soil Properties.........................................................................................47 SRWC..................................................................................................................48 NA.......................................................................................................................52 Correlations.........................................................................................................53

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vi 5 CONCLUSIONS........................................................................................................55 6 FUTURE RESEARCH...............................................................................................58 APPENDIX A VEGETATION...........................................................................................................60 B SOILS.........................................................................................................................76 C COGONMASH...........................................................................................................78 REFERENCES..................................................................................................................84 BIOGRAPHICAL SKETCH.............................................................................................95

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vii LIST OF TABLES Table page 3-1 Symbols of species, plan ting date, and propagule type of species in the SRWC area...........................................................................................................................19 3-2 SRWC interplant species and their suitability..........................................................20 3-3 SRWC culture definitions........................................................................................20 4-1 Analysis of variance for January 200 6 tree height, DBH (diameter at breast height), vigor, and surviv al of all trees, includi ng borders, in SRWC study. C (culture), S (species), S*C (species*cu lture interaction, plot/slope position...........28 4-2 Average tree and shrub he ight (H, in m), vigor (V), survival (S, %), and DBH (D in cm) in January 2006 by culture and species (excluding borders)........................30 4-3 Average height (m) in January 2006 by slope position (1 at top of slope; 4 at bottom of slope) and species (excluding borders)....................................................31 4-4 Pearson correlation coefficients of all January 2006 height (H) and survival (S) data for all SRWC trees and soil variables...............................................................31 4-5 Means for all soil variables in the Natural Area and the Short Rotation Woody Crop (SRWC) sites...................................................................................................32 4-6 Analysis of variance for herbs and shrubs in the Shor t Rotation Woody Crop (SRWC) and Natureal Area (NA) sites....................................................................36 4-7 Ten greatest IVI and TSC (%) values of herbs and shrubs for each site..................38 4-8 Pearson correlation coefficients of so w thistle and cudweed IVI, TSC, and soil variables in the SRWC area.....................................................................................41 4-9 Pearson correlation coefficients for hairy indigo and cogongrass IVI, TSC, and soil variables in the SRWC area...............................................................................41 4-10 Analysis of variance for cottonwood vegetation variables......................................42 4-11 Top 5 species with the greatest TSC and IVI values in the cottonwood block. Values with the same letter ar e not different at .05 level.........................................43

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viii 4-12 Pearson correlation coefficients for Populus deltoides basal area per hectare (BAH), total plant canopy cover (TPCC) and cogongrass total species cover (TSC) on a quadrat and slope position basis............................................................43 4-13 Shannon-Weiner diversity index (H) and maximum possible diversity (Hmax) of all sites for herbs, shrubs, and NA trees...............................................................47 4-14 Jaccards community similarity index (Cj) for herbs (H) and shrub species (S) at all sites...................................................................................................................... 47 4-15 Analysis of variance for the Short rotation woody crop (SRWC) and Natural Area soil variables....................................................................................................49 4-16 Average soil means by slope position......................................................................50 A-1 Name and nativity of herb aceous species on all sites..............................................60 A-2 Name and nativity of woody species on all sites.....................................................63 A-3 Name and nativity of all tr ees found in the Natural Area........................................64 A-4 September 2005 SRWC herbaceous vegetation variables.......................................64 A-5 March 2006 SRWC herbaceous vegetation variables..............................................65 A-6 May 2006 SRWC herbaceous vegetation variables.................................................65 A-7 May 2006 NA herbaceous vegetation variables.......................................................66 A-8 March 2006 NA herbaceous vegetation variables....................................................67 A-9 September 2006 NA herbaceous vegetation variables.............................................68 A-10 March 2006 CM herbaceous vegetation variables...................................................68 A-11 May 2006 CM herbaceous vegetation variables......................................................68 A-12 September 2005 NA woody speci es vegetation variables.......................................69 A-13 March 2006 NA woody species vegetation variables..............................................70 A-14 May 2006 NA woody species vegetation variables.................................................71 A-15 Shrub frequency (%) for all sites (NA, SRWC, and CM)........................................72 A-16 Vegetation variables of all SRWC herbaceous species............................................73 A-17 Vegetation variables of NA herbaceous species......................................................74

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ix A-18 Vegetation variable s of NA woody species.............................................................75 B-1 Pearson correlation coefficients for Populus deltoides growth variables: height at 14 months (H14), 14 mo. diameter at breast height (D14), 14 mo. survival (S14), 14 mo. vigor (V14), basal area per hectare (BAH) and soil variables: organic matter (OM), bulk density (BD) of corresponding slope positions in the SRWC area...............................................................................................................76 B-2 Pearson correlation coefficients for Pinus elliottii and Taxodium distichum growth variables: 11 mo. height (H11), 11 mo. vigor (V11), and 11 mo. survival (S11) and soil variables: organic matter (OM) and bulk density (BD) of corresponding slope positions in the SRWC area....................................................76 B-3 Pearson correlation coefficients for Eucalyptus amplifolia and Eucalyptus grandis growth variables: Jan. 2006 height (H ), vigor (V), and survival (S) and soil variables: organic ma tter (OM) and bulk density (BD) of corresponding slope positions in the SRWC area............................................................................77 C-1 Analysis of variance for herbs and shrubs in the Cogon mash (CM) site.................80 C-2 Ten greatest IVI and TSC (%) values of herbs and shrubs for the CM site.............81 C-3 Analysis of variance for all soil variables in the Cogon mash study: transect (T), and quadrat (Q).........................................................................................................83 C-4 Means for all soil variables in the Cogonmash site..................................................83

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x LIST OF FIGURES Figure page 3-1 2005 Field layout for SRWC site.............................................................................17 3-2 Aerial photograph (2005) of the 0.8 ha SRWC site and the Natural Area to the east........................................................................................................................... .21 3-3 SRWC vegetation and soil core plot design.............................................................23 3-4 Natural area transects wi th three 10x10m tree plots................................................24 3-5 Natural area herb and shrub vegetation and soil sampling design...........................24 4-1 Tree height (m) for SRWCs in January 2006 by culture and species......................29 4-2 May 2006 Cogongrass TSC for all species, slope positions, and treatments in the SRWC site................................................................................................................29 4-3 Relation of SOM to cogongr ass IVI in the SRWC area...........................................40 4-4 Relation of SOM to hairy indigo IVI in the SRWC area.........................................40 4-5 Stepwise regression (0.15 level) of NA tree BAH as a function of pH by plot.......46 C-1 Cogonmash vegetation a nd soil core plot design.....................................................79

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xi 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 PRELIMINARY EVALUATION OF THE US E OF FAST GROWING TREES AND CULTURES FOR COGONGRASS CONT ROL ON PHOSPHATE MINED LANDS By Erin N. Maehr August 2006 Chair: Donald L. Rockwood Major Department: Forest Resources and Conservation Cogongrass ( Imperata cylindrica) is a threat to the restor ation of disturbed lands in central Florida, especially phosphate-mined la nds. Moreover, this invasive exotic lacks an effective control method. Fast growing trees, such as cottonwood ( Populus deltoides), slash pine ( Pinus elliottii), eucalypts ( Eucalyptus grandis and E. amplifolia ), and bald cypress ( Taxodium distichum ), were planted from February to June of 2005 on a claysettling area (CSA) at the Polk County Peace Rive r Park (PCPRP) in Florida, to evaluate their potential as a c ogongrass control strategy. In conjunction with planti ng short rotation woody crops (SRWCs), five treatments (control, herbicide, native trees, native shrubs, and mulch) were applied. A sixth treatment was initiated, mash ing of cogongrass (CM), on a 40-year-old CSA less than 1600m from the PCPRP. Vegetation sample s were collected in September 2005, March 2006, and May 2006 within the study plots to su rvey percent coverage and abundance of shrubs and herbs. Soil samples were also collected to quantify macronutrients (NO3, P,

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xii K, Ca, and Mg), soil organic matter (SOM), bulk density (BD), and pH. The vegetation and soil of a natural area (NA) in the Polk County Peace River Park were also analyzed for comparison to the SRWC and the CM site. At the SRWC site, Jan 2006 height di ffered among species (p<0.0001), but not, among treatments (p=0.8601). Populus deltoides diameter at breast height (DBH) differed among cultures (p<0.0001). Soil pH wa s significantly different between sites (p=0.0035). Nitrate differed among sites (p=0.0406). Both native and exotic species were pres ent in the understory of the 3 sites. Common herbaceous species in the SRWC area included hairy indigo ( Indigofera hirsuta), horseweed (Conzya canadensis), dogfennel ( Eupatorium capillifolium), cudweed ( Gnaphalium falcatum), sow thistle (Sonchus asper), and cogongrass The only shrub species observed in th e SRWC area were saltbush ( Baccharis halimifolia), primrose willow ( Ludwigia peruviana), and elderberry ( Sambucus canadensis). There were a total of 42 herbaceous species observed in the SRWC are, 36 in the Natural area, and 9 in the CM area. Total plant canopy c over (TPCC) was least in the mulch culture, 22%. Cogongrass had the least cover in the herbicide and mulch cultures of the SRWC site, less than 2% cover in each culture. Cogongrass and hairy indigo, a common SRWC herbaceous plant, IVI had no re lation to SOM content in the SRWC area. The CM site had a TPCC of 18% and even less cogongrass co ver, .5%, than the mulch treatment in the SRWC site. In their first year of grow th, SRWCs initiate a native plant succession, provide adequate control over cogongrass, and amend soil conditions. Based on this study, cogonmashing followed by the planting of fast-growing trees on cogongrass dominated sites is promising fo r effective cogongrass control.

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1 CHAPTER 1 INTRODUCTION Many human-dominated ecosystems are highly stressed and dysfunctional (Vitousek et al. 1997), including forests th at are managed for conservation (Noble & Dirzo 1997). Ecosystem health is a new field of study that quantifies the condition of an ecosystem. Biodiversity is one method of m easuring ecosystem health (Rapport et al. 1998). Systems unaltered by humans tend to be stable and resilie nt, but with human interference natural pr ocesses can be disrupted. Before phosphate mining occurred in central Florida, the land was free of major hu man-inflicted disturbances. However, after phosphate extraction, a return to its original conditions is unlikely at best. The successional stages following mining take approximately 40 years to reach a climax community depending on ecological conditions (Skousen et al. 1994). Without human aid, mined lands may forever st ay in a disturbed state, es pecially phosphate mine clay settling areas (CSAs). CSAs are a product of the extraction of phosphate ore 4.5-15m below the surface. Phosphate mining removes the su rface (overburden) so that th e matrix can be accessed. The matrix is 3-6m thick and consists of equal parts clay, sand, and phosphate ore. Draglines remove the matrix and place it in wells that are subjected to high pressure water guns in order to transform the mixtur e into a slurry. The sand and phosphate are separated from the mixture, with clay and wa ter pumped to CSAs. The sand is used to reclaim the extraction sites a nd the phosphate ore is furthe r processed. CSAs comprise 40% of phosphate mine sites and retain standi ng water for 15 years or more. CSAs have

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2 a very high water capacity and the impervious clays make water drainage difficult. In central Florida, there are 64,700 ha of CSAs (CPI 2003). It was previously thought that clay settling would take 20 to 30 years or more to dry sufficiently to support mechanized equipment (Stricker 2000). However, it is pos sible to employ high flotation tractors with rotary ditching plows to drain CSAs and speed land reclamation. These methods are expensive, but provide suitable land for cultivation after 3-5 years (Stricker 2000). Most phosphate mined areas were previ ously forested with flatwoods and hardwood hammock ecosystems. Typical tree s species were slash pine, longleaf pine (Pinus palustris) and oaks ( Quercus sp. ). Phosphate mining destroyed native seed banks, preventing regeneration of these communi ties. Further, phosphate mine soils are so atypical for this part of Florida that they are suitable for invasive plant species such as cogongrass Brazilian pepper, and natalgrass. Of these, cogongrass is the predominant species. Cogongrass invades many disturbed lands, in cluding phosphate mined sites. It is considered one of the top 10 most invasive pl ants in the world (Holm et al. 1997) and has allelopathic effects that deter the grow th of surrounding plants. It forms thick, impenetrable stands that make it physically difficult for othe r plants to grow. Cogongrass is found in all southern states east of New Mexico and on all continents except Antarctica. In Southeast Asia, it is the dominant vegetation on 121 million ha. On a global scale, it has invaded 200 million ha fo rest plantations and agricultural lands. Control efforts for cogongrass generally do not last more than a year multiple applications are required for effective control. Herbicide has limited success and the effects are short-lived (MacDonald et al. 2002; Willard et al. 1997). Removal of the

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3 above-ground vegetation is not an effective c ontrol method because the grass proliferates from rhizomes. A control strategy should employ removal of above and below ground biomass. Eussen (1979) found that cogongrass c ould be controlled with shade. Fastgrowing exotic species have widely been used in the reforestation of cogongrass grasslands in Asia. Early and fast growth of these species suppre sses cogongrass (Otsamo et al. 1997). Short rotation woody crops (SRWCs), such as eucalypts, provide shade that constrains cogongrass growth (Tamang 2005). Eucalypts also have the potential to remediate the soil by returning SOM to the earth through leaf and woody debris decomposition (Bernhard-Reversat and B ouillet 2001). Suggestions for cogongrass control combine repeated herb icide application with the dense canopy of fast-growing trees (MacDonald 2004; Ramsey et al. 2003; Shilling et al. 1997). Florida law mandates that mining companie s reclaim areas mined after July 1, 1975 (FL Adminstrative Code Ch62C 17). Wetlands must be reclaimed to at least the same area prior to mining and at le ast 10% of upland must be planted with native species. Since December of 2003, 63% of the land mi ned since July 1, 1975 has been reclaimed (DEP 2003). Other agencies are working to reclaim the lands mined before 1975. CSAs are not often used commercially b ecause of their poor soil structure and inability to be rapidly altered for bu ilding and farming purposes. CSAs do not voluntarily sustain native Florida plant species. There is little motiv ation to farm these areas because CSAs contain toxic elements such as radium and uranium and extremely poor water drainage. Cogongrass heartily in fests many CSAs, crea ting another obstacle

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4 for reclamation. Therefore, restoration activities on CSAs mu st control cogongrass before native plant species can be re-established. Poorly drained phosphate-mine lands in centr al Florida are able to support SRWCs such as cottonwood and eucalypts (Stricke r et al. 2000). Fast-growing trees have numerous environmental benefits such as improved water quality, soil stabilization, carbon sequestration, and wildlife habitat. A nother positive attribut e is exotic species control through the formation of a dense canopy. Eucalypts have been utilized elsewhere around the world to restore dist urbed habitats (Ashagrie et al. 2005; Callisto et al. 2002; Strauss 2001; Tyynela 2001). Other eucalypt benefits include ability to coppice, which saves repeated establishment costs. Fast-growing tree plantations can increase soil organic matter (SOM) via leaf litter, decrease bulk density (BD) and increase soil porosity via root penetration. From the inputs of above and below-ground litter, the morphology and chemical conditions of the soil are affected. Trees promote nutrient cycling and accumulation (Rhoades 1996). The soil beneath tree canopies store nu trients. Such tree farms can provide habitat for wildlife and expedite the return of native species. Eucalypts ( Eucalyptus grandis and E. amplifolia) slash pine ( Pinus elliottii ), eastern cottonwood ( Populus deltoides ), and bald cypress ( Taxodium distichum ) were planted in a cogongrass monoculture on a CSA at the Polk County Peace River Park, near Homeland in central Florida in February of 2005. This study began in the fall of 2005 with four objectives: 1. Evaluate the effectiveness of SRWCs in controlling cogongrass. 2. Assess the performance of cultural treatments in preventing the return of cogongrass.

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5 3. Monitor the return of nati ve species in a previously cogongrass infested area. 4. Assess soil properties. The hypotheses of the study were: 1. The species that grow the quickest ar e the best cogongrass control agents. 2. Mulch and the cogonmash treatment will provide the best cogongrass control. 3. More native plants will be present in the NA in comparison to the SRWC area. 4. As the fast-growing trees accrue aboveground and below-ground biomass, BD and pH will decrease and SOM will increase.

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6 CHAPTER 2 LITERATURE REVIEW Species invasions are not a new evolu tionary phenomenon, but their rate of occurrence has exploded with the spread of humans across the planet (Vitousek et al. 1996). Non-native invasive species have b ecome a global threat to biodiversity. Australia, Canada, and the U.S. support about 1500 non-indigenous, invasive plant species and Florida alone harbors approxima tely 1000 (Vitousek et al. 1996). In some ecosystems, invasives equal or surpass th e number of native plants even though only 0.1% of introduced plant species have beco me invasive (Williamson and Fitter 1996). Invasive plants have numerous effects upon ecosystems. Following the establishment of invasive plant species, native communities experience changes in species abundance, predator-prey rela tions, and allelopathy. Depending upon the invader, soil properties and nutrient concentrations change resource availability and disturbance regimes can be modified; comp etition and disease may become problematic for native residents (Cox 2004). Indigenous sp ecies may be displaced and biodiversity may decline locally and regionally (Cox 2004). Invasion resistance may be enhanced in communities with high species richness and diverse functional relations among species (Elton 1958; Lavorel et al. 1999). On the other hand, a positive feedback mechanism, termed "invasional meltdown" (Cox 2004) promotes the invasion of other alien species. This can happen when 1) aliens modify ecosystem dynamics so much that invasions of other alien species are facilitated or 2)

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7 novel species create conditions or provide resources that directly benefit other nonindigenous plants (Cox 2004). Moreover, invasive species may become more of an issue as global climate change alters biotic conditions. Gl obal warming has occurred as a tmospheric carbon dioxide and other greenhouse gases increas e in the atmosphere, creati ng a thermal blanket around the Earth (Cox 2004). Global climate change appears responsible for altered annual temperatures and precipitation, longer growing seasons at high latitudes, reduced snow cover at high latitudes and al titudes, reduced cloud cover in the moist tropics, and an increased rate of extreme weather (Cox 2004) The growing season has increased by 12 days, between 40 and 75 N, in North Amer ica over the past 20 years (Penuelas and Filella 2001). In conjunction with climat e alterations, cogongrass has likely expanded its distribution. Invaders seem capable of occupying a di verse array of ecosystems, especially disturbed areas such as clay settling areas (CSAs) of phos phate mines (MacDonald et al. 2002). Phosphate mining began in 1883 when deposits were found in Alachua County, Florida. Phosphate mining disturbs 2,000 to 2,500 ha every year in Florida (EcoImpact 1980; DEP 2003). Florida produces 75% and 25% of the United States and world phosphate requirements, respectively. Prior to mining the areas were forested with longleaf pine, slash pine, oak, and cypress. Phosphate strip mining degraded thes e landscapes to exotic plant havens. After mining, the remnant soil was an ideal habitat for invasive exotic plants, like cogongrass, natalgrass, and purple and ye llow nutsedge. Before 1975, phosphate-mined lands could

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8 be abandoned without reclamation. After 1975, however, all disturbed land had to be reclaimed within four year s after mining or as soon as possible (Partney 1998). Mining drastically alters the soil and vegetation dynamics (Bradshaw 2000). One way to restore the land is through the improveme nt of soil fertility and species diversity (Fang and Peng 1997). Natural succession restor es disturbed sites, but this process can take years and only occurs at locations with nutrient-rich soil and s eed sources that come from natural stands of healthy trees (Bradshaw 2000). Phosphatic clays are fertile, with m acronutrients, and have good water holding capacity, lessening the need for phosphatic fert ilizers and irrigation methods (Stricker et al. 2003). CSAs typically have a basic soil pH of about 8.0 with hi gh concentrations of calcium, magnesium, phosphorus, and potassium (Hochmuth et al. 2000). Unlike many terrestrial disturbed sites, CSAs are difficult for native plants to colonize. Phosphatic clay is composed of clay part icles less than 2 microns in size. The medium sized fractions of phosphatic clay are made up of apatite while montmorillonite composes the finer fractions (Stricker 2000). Phosphatic clay soil has a very high water holding capacity; 12 cm can be supplied to a growing cr op, whereas Myakka find sand, the state soil of Florida, can only hold 5cm. An even lo wer water holding capacity is found in Lakeland sand, 3 cm (Stricker 2000). This high water hold ing capacity lessens the need for irrigation of planted species. Cogongrass, tolerant of a variety of envi ronmental conditions, thrives on disturbed phosphate-mined soils (Jose et al. 2002; Shilling et al. 1997). Rhizomes grow prolifically 10 months a year and secrete an allelopathic substance, wh ich inhibits the growth of surrounding plants (MacDonald et al. 2002). Cogongrass can accumulate allelochemicals

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9 to phytotoxic levels continually secreti ng scopolin, scopoletin, a nd chlorogenic acids (Inderjit 2001). The allelochemicals inhibit growth, germination, r oot and shoot length, fresh and dry weight, and reduce fungal colonies of neighboring plants (SanchezMoreiras et al. 2003). Cogongra ss alters fire regimes (Lippincott 1997), a problematic issue facing global biodivers ity (Brooks et al. 2004). Management options for cogongrass, especia lly integrated approaches, need to be further researched (Chikoye 2004). The key to cogongrass control is the destruction of their rhizomes, which are the major means for perennation and spread (Chikoye 2004). An option that has been relatively effective in small scale farms is the flattening of cogongrass. This involves bending the stems at ground level. In Nigeria, farmers bend the vegetation at the beginning of the rainy season, immediately followed by tillage so that soil is laid upon th e downed stems to keep them flat Regrowth after mashing is 2060% less than the slashing method of contro l and is also cheaper and faster (Chikoye 2004). Flattening reduces the risk of fire and creates a suitable foundation for covercrops (Chikoye 2004). Flatte ning does not require mechanical machinery, but can be accomplished using planks, logs, or drums (Friday et al. 1999). Slashing is another management op tion, which is followed by burning to temporarily control cogongra ss (Chikoye 2004). However, for this technique to be effective, slashing has to be re peated at frequent intervals. Soerjani (1970) recommended an interval of two weeks over a period of th ree years. Slashing requires considerable effort and is not feasible for large areas (Brook 1989). Slashing al so induces flowering, which can further spread the weed.

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10 Chemical control can also be effective. Studies have been performed on paraquat, fluazifop-butyl, glufosinate-ammonia, dalapon, imazapyr, glyphosate, sulfometuron, nicosulfuron, and rimsulfuron. Some have shown effective cont rol, but repeated applications are needed (Chikoye 2004). Imazapyr and glyphosate appear to be the most effective for cogongrass control because the herbicide is tran slocated to the rhizomatous portions of the plant (Chikoye 2004). Grass-effective herbicides are limited (Wrucke and Arnold 1985). Some herbicides effectively kill cogongrass, but they al so kill all other surrounding vegetation (MacDonald et al. 2002). Fire eliminates above ground vegeta tion, but due to a high leaf concentration of silica, cogongrass burn te mperatures are too hot for much of the surrounding native vegetation to return (Jose et al. 2002). When fires are recurrent in the dry season, they can cause a loss of SOM, de grading the soil in the process (Chikoye 2004). Fire is not an ideal method fo r cogongrass control because below-ground rhizomes survive fire (Bryson and Carter 1993). Using select species and successionaltering processes that place cogongrass at a co mpetitive disadvantage might also control the weed. Eucalypts and cottonwood are fast-growing trees that have been used as bridge crops to shade out cogongrass. Besides shie lding the cogongrass from the sun, eucalypts remediate soil conditions (Bernhard-Reversat and Bouillet 2001) for other plants to establish. Cogongrass can be controlled in shady e nvironments (Eussen 1979). Cogongrass is sensitive to shading and usually weakens and dies after exposure to intensive shade. Plantations have commonly been used for ve getation recovery on mined lands (Reintam and Kaar 2002) due to their multiple uses. Polycultures are preferred because of their

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11 resistance to pest outbreak (Hartley 2002). Native plant species are favored over exotics because unforeseen problems might arise from planting an abundance of exotic species. With the help of fast-growing trees, it may take 8-10 years for cogongrass to decline and be displaced by natural forest (Dalziel and Hutchinson 1937). Therefore, the use of cover crops should be an effective method of contro l. Fallows that produce rapid shading have repeatedly shown cogongra ss suppression (Koch et al 1990; Anon. 1996; Macdicken et al 1997; Akobundu et al 2000; Chikoye et al 2001). Therefore, fast-growing trees have potential to be an effect ive cogongrass control method. Cogongrass forms monotypic stands through aggressive growth (Eussen 1979) and sprawling mat-creating rhizomes (Boonitee and Ritdhit 1984). Plants that have outcompeted cogongrass have a more penetratin g root system and/or develop a taller canopy (Eussen 1979). Cogongrass typically does not invade communities dominated by native plants. Native plant establishment may depend on a dispersal agent such as birds, or there may be a minimum age requirement before the plants start producing seeds. Viability of dispersed seeds may only last a short period of time, also hindering the possibility of germination. Seeds may only be produced every other year; many variables can confound the dispersal and establishm ent of native, neighboring species. There are two phases of seed dispersal; phase one (primary) pertains to the movement of the seed from the maternal pa rent to the ground. Phase two (secondary) dispersal concerns the subsequent movement of the seed after it has hit the ground. Secondary phase dispersal includes wind, anim als, rain, or water flow (Griffith and Forseth 2002). Wind dispersal within a forest is improbable due to wind barriers such as

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12 trees (Attenborough 1995. Wind blow n species, such as some pines, need to be on the outer edges of natural areas for wind to carry seeds to the plantation. The attainment of vegetative climax on mi ned land takes at least 40 years (Skousen et al. 1994). Succession is the vegetation ch ange in species composition through time. After a disturbance, such as phosphate mining, th e first species to colonize are those that exploit bare mineral soil and tolerate full s un. Pioneer species alter the soil conditions and facilitate the colonization of different species. Cooler soil conditions, increased SOM, and increased soil moisture make c onditions more inhabitable by shade-tolerant species (Dodson et al. 1998). Succession lead s to climax vegetation, an established community in equilibrium with the climate (Clements 1936). Once new inhabitants cease the alteration of light intensity patterns and soil moisture, succession ceases (Clements 1936). Central Florida climatic conditions influe nce native tree selection. In one study, green ash ( Fraxinus pennsylvanica) had a 98% survival rate, followed by red bay ( Persea borbonia ) 90%, sycamore ( Platanus occidentalis ) 90%, red maple ( Acer rubrum ) 83%, and sweetgum ( Liquidambar styraciflua ) 83% (Best and Erwin 1983). Survival rates in another study on phosphatic clay soils were sweetgum 66%, tupelo gum 64%, loblolly pine 63%, and bald cypress 60% (Harrell 1987). The productivity of understory vegetation is comparable to that of trees (Nilsson and Wardle 2005). Understory vegetation is often undersampled in ecological studies and can vary depending on location, season, a nd plot size (Small and McCarthy 2003). With increasing stand age, species density and richness increase slowly (Wang et al. 2004). Monoculture tree plantati ons are associated with the lowest biologi cal diversity

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13 (Kamo et al. 2002). Plantations, in close proximity to natural forests, have high understory species diversity. Diversity on phosphate mined lands is a function of distance to the seed source (McClanahan 1986). This ability of plantations to catalyze secondary succession of native species could a llow for the restoration of biodiversity in degraded lands (Kamo et al. 2002; Parrotta et al. 1997). In an Australian plantation, species diversity in a 38 to 40-year-old E. cloeziana stand was similar to native eucalypt forests (Wang et al. 2004). Understory vege tation is highly depe ndent upon the species planted, the planting density, and the landscape (P ensa et al. 2004). The first stages of succession involve native and exotic plant species as colonizers, but native species dominate in the later stages (Wang et al. 2004) The prevalence of exotic species drops as the stand ages. Another determinant of understory vegetati on is soil quality. L itter is the primary source of nutrients in natural systems. D ecomposition of litter a nd plant residues adds plant essential nutrients to the soil. Increased soil nutrients provide a better habitat where plant species can thrive. With the growth of trees, SOM increases, which changes the structure and properties of soil (Singh 1998). Soil organic carbon is added only to the upper layer (10 cm) in the initial years of pl antation establishment (Tolbert et al. 2002). Eucalyptus and cottonwood are favored for soil reclamation of disturbed lands. One of the foci of planting fast-growing tr ees on these sites is to build SOM via the inputs of above and below-ground biomass. A 45 kg eucalyptus tree may have 17 kg of roots. The introduction of tr ees can increase soil organi c matter and microbial activity, decrease soil compaction/BD, decrease soil pH and increase available nitrogen to plants. Trees are also capable of remediating the soil and removing toxins (Rockwood et al.

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14 2001). In India, cottonwood was superior to eucalyptus in soil amendments. Cottonwood produced more N, P, and K than eu calyptus (Singh et al 1989). Nutrient quality is greater in cottonwood leaves than the woody tissues. Eucal yptus litter can be more nutritious through the application of N and P fertilizer; it also increases the total N, P, K, Ca, and Mg in the lit ter (Connell and Mendham 2004). Eucalyptus and cottonwood are both allelopa thic. Cottonwood leav es and litter are abundant in phytotoxic phenols, which have b een shown to constrain the germination and growth of some winter crops in India (S ingh et al. 2001). Euca lyptus releases both volatile and nonvolatile allelochemicals; these chemicals are abundant in the soil beneath the canopy (Kohli 1998), but with depth, the soil dilutes the allelochemical concentration (Molina et al. 1991). In southeastern Brazil, an E. grandis plantation had almost the same number of species as a natural forest indicating that eucal yptus was not producing an allelopathic effect in that situation (Da Silva et al. 1995). Managed correctly, eucalyptus can be an effective instrument in the restoration of disturbed lands. Eastern cottonwood is the fa stest, commercially grow n native species in North America. Eastern cottonwood biomass pr oduction is less than eucalypt biomass production. It has been used in the restora tion of strip-mined lands (Brothers 1988). It has fair value for wildlife in cluding songbirds, upland game birds, fur-bearers and game mammals (Carey & Gill 1980). Seedling and sapling bark and leaves are consumed by field mice, rabbits, deer, and domestic livestock (Behan 1981). The native range of slash pine is from s outhern South Carolina to central Florida and west to eastern Louisiana. It is an important timber species in the southeastern United States, and its wood is excellent for construction purposes (McCune 1988). Slash

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15 pine seeds are consumed by birds and sma ll mammals, and their seedlings are often browsed by deer and cattle (Lohrey and Kossuth 1990). This pine also provides sufficient cover and shelter for many species of wildlife (Lohrey and Kossuth 1990). If soils are properly restored and vege tation established, it is assumed that reclamation provides functional, self-susta ining, ecosystem (Bloom field et al. 1982). However, a successful restoration is not a certain outcome because of uncontrollable variables such as competition with exotics, atypical alteration in soil nutrients and establishment conditions (Prober and Thiele 2005). Restoration will take many years to reach an equilibrated and stable ecosystem. W ithout further disturbance, this stage could be reached within a decade. SRWCs are re turning native plants to the study site and cogongrass is, to date, under control. Plan t diversity has greatly increased from the cogongrass monoculture present less than two years ago.

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16 CHAPTER 3 METHODS Study Areas Three areas contributed to this study: short rotation woody cr ops (SRWC), natural area (NA), and the cogonmash (CM). SRWC This study was conducted at Polk County Peace River Park, an inactive CSA in Homeland, Polk County, FL (Figure 3-1). It is open to the public and is used by horseback riders and hikers. When ab andoned, the land was invaded primarily by cogongrass ( Imperata cylindrica), which grew up to 2m in height Soil characteristics vary with elevation and de gree of inundation, depressions having high clay content and elevated areas mostly sand. Approximate pH was 6.5, and there was a considerable amount (9%) of SOM present. Associat ed vegetation includes passionflower ( Passiflora incarnata) and occasionally wax myrtle ( Myrica cerifera ). Wax myrtle has been the most prevalent species dispersed on CSAs in central Florida (McClanahan and Wolfe 1993). The park receives an average annual rainfall of 125cm, the majority falling between June and September. In 2005, the tota l rainfall for Polk County was the fourth wettest on record at 169cm (Blair 2006). Average Polk County temperatures are 15.6 C in January and 27.9 C in August (McNally 2006). In December 2004, the study area (0.809 hectares) was treated with 3.5 L/ha of imazapyr (Arsenal) to kill above-ground c ogongrass before the research started. Effective at low rates, imazapyr is absorb ed through the leaves, stems, and roots of

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17 plants,providing residual control. The site was double disked and roto-tilled to 10 cm in January 2005 prior to planting. Once imazapyr residue had reached non-injurious levels in the soil, trees and the interplant treatments were established during spring (February 2005) and summer (June 2005). Figure 3-1 2005 Field layout for SRWC site. Species: Eucalyptus grandis (EG), Eucalyptus amplifolia (EA), Populus deltoides (PD), Taxodium distichum (TD) and Pinus elliottii (PE). Ground cover control: H=herbicide, M=mulch, C=none. Intercrop: S=shrub, T=trees, N= none. Slope position: 1=top, 2, 3, or 4=bottom. Fast-growing trees included: two species of eucalypts ( E. amplifolia and E. grandis ) Populus deltoides, Pinus elliottii and Taxodium distichum (Table 3-1).

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18 Cottonwood and cypress were planted in the no rthern, less elevated and wetter portions of the field. Slash pines were planted at the same time in the southern, sandier portions of the field. Eucalypts were planted during June 2005 in the western half of the study. The dimensions of the field were 73 x 105m. The field contained 40 pl ots that were 18 x 9m. All rows were double planted with 2.4 m between rows between adjoining cultures and 2m between rows within a treatment. Native shrubs and trees were interplanted within trees and incl uded: saw palmetto, ( Serenoa repens), buttonbush ( Cephalanthus occidentalis), galberry (Ilex glabra), and wax myrtle ( Myrica cerifera) (native shrubs treatment) and swamp tupelo (Nyssa sylvatica var. biflora ) sweetgum (Liquidambar styraciflua ) red bay (Persea borbonia ) and swamp red bay (Persea palustris ) (Table 3-1) (native tree treatment). Plants were chosen based on their wildlife value (Table 3-2). The summer interplants were donated from R.S.S. Field Services and consisted of : swamp tupelo gum, loblolly bay, redbay, and sweetgum The species planted in the spring va ried between containerized seedlings and one gallon pots. Galberry, redbay, and swamp redbay were tubelings in the spring planting; the rest of the native plan ts were planted from gallon pots. All summer planted species were planted from gallon pots. Besides the native tree and shrub treatments, there were three other treatments (Table 3-3): an herbicide treatment, a mulch treatment, and a control. Each treatment had 8 plots, four in the summer pl anting and four in the spring.

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19 Table 3-1 Symbols of species, planting date, and propagule type of species in the SRWC area Short Rotation Woody CropsSymbol Planting DatePropagule Type Eucalyptus amplifolia EA 6-2005 Containerized seedlings Eucalyptus grandis EG 6-2005 Containerized seedlings Pinus elliottii PE 2-2005 Containerized seedlings Populus deltoides PD 2-2005 Unrooted cuttings Taxodium distichum TD 6-2005 Containerized seedlings Interplant Native Shrub Culture Cephalanthus occidentalis CO 2-2005 6-2005 Containerized seedlings 1 Gallon Pots Ilex glabra IG 2-2005 6-2005 Containerized seedlings 1 Gallon Pots Myrica cerifera MC 2-2005 6-2005 Containerized seedlings 1 Gallon Pots Serenoa repens SR 2-2005 6-2005 Containerized seedlings 1 Gallon Pots Interplant Native Tree Culture Gordonia lasianthus GL 6-2005 1 Gallon Pots Liquidambar styraciflua LS 2-2005 6-2005 Containerized seedlings 1 Gallon Pots Nyssa sylvatica var. biflora NS 2-2005 6-2005 Containerized seedlings 1 Gallon Pots Persea borbonia PB 2-2005 6-2005 Containerized seedlings 1 Gallon Pots Persea palustris PP 2-2005 Containerized seedlings

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20 Table 3-2 SRWC interplant species and their suitability Interplant Species Categories Scientific Name Common Name Family pH Preference Seed Dispersal Shade Tolerance Soil Texture Preference Food Source Persea palustris Swamp Bay Lauraceae Acidic Neutral Animal Shade tolerant Clay, Loam, Sand Yes Persea borbonia Red Bay Lauraceae Acidic Alkaline Animal Shade tolerant Clay, Loam, Sand Yes Nyssa sylvatica var. biflora Swamp Tupelo Cornaceae Acidic Animal, Gravity, Water Shade intolerant Clay, Loam, Sand Yes Liquidambar styraciflua Sweetgum Hamamelidace ae Acidic Alkaline Wind Shade intolerant Clay, Loam, Sand Yes Gordonia lasianthus Loblolly Bay Theaceae Acidic Wind Shade tolerant Clay, Loam Yes Myrica cerifera Wax myrtle Myricaceae Acidic Alkaline Birds Shade intolerant Clay, Loam, Sand Yes Cephalanthus occidentalis Buttonbush Rubiaceae Acidic Alkaline Animals, Gravity Med to High light req Sand, Loam, Clay Yes Serenoa repens Saw palmetto Arecaceae Acidic Alkaline Animals Med to High light req Clay, Sand, Loam Yes Ilex glabra Galberry Aquifoliaceae Acidic Animals Shade tolerant Sand, Loam, Clay Yes Table 3-3 SRWC culture definitions Treatment Definition Control (C) No interplants planted, no mulch applied, and no herbicide was sprayed Shrub Interplants (S) Four native shrub species planted in two double rows between the fast growing trees Tree Interplants (T) Four native tree species planted in two double rows between the fast growing trees Herbicide (H) Herbicide applied to these pl ots when deemed necessary Mulch (M) 6 in of hurricane debris mulch distribute d over each plot, around fast-growing trees Cogonmash (CM) Cogongrass flattened with a tractor, sprayed at 3 weeks, and again at 6 weeks with 6% glyphosate at 2.4 L/ha (2.5qt/ha) Natural Area The natural study area (Figure 3-2), east of the SRWC Area was part of the IMCPeace River Park natural area composed of ~6 ha, which is within 607 ha of riparian strips between Bartow and Homeland. Cogongrass has invaded the western perimeter of

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21 this area. The forest cover is mixed wetland forest with some cypress forest. Many of the species utilized as interplants in the SR WC were also present in the Natural Area, including: saw palmetto tupelo gum buttonbush sweetgum and wax myrtle Figure 3-2 Aerial photograph ( 2005) of the 0.8 ha SRWC site and the Natural Area to the east. Cogonmash The CM was a minor component of this study: appendix C displays the setup and the results. Experimental Design Vegetation and soil analyses were conduc ted in the SRWC, NA, and CM (appendix C) in the Polk County Peace River Park. SRWC In the planted area, each tr eatment had eight plots, four in the summer planting and four in the spring. Although a pilot study revealed that the ideal sample size for each plot/tree species/treatment was five, due to limited resources, only four 1x1m quadrats were established for herbaceous species and a 1x4m quadrat for shrub species. Each plot had two quadrats placed on the center row, 6 m from each end to avoid edge effects. Two adjacent, sister quadrats were placed to the left for comparison to plots without SRWCs; for a total of four quadrats/plot (Figure 3-3). In th e center of one of the

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22 1x1m herbaceous quadrats, a soil core was take n with a 10 cm diameter soil corer to a depth of 24 cm. Each soil core sample was placed in a plastic bag, homogenized, air-dried, and sieved through a 2 mm screen, and analyzed by the Analytical Research Lab at the University of Florida for pH, NO3-N, SOM, and macronutrients (Ca, P, K, and Mg). SOM was determined using the Loss-on-Ignition method because SOM was greater than 6%. Macronutrients were extracte d using the Mehlich 3 solution. Surface BD was collected to a depth of 3 cm and subsurface BD from 3 to 6 cm. The total weight of each soil sample was r ecorded. The sample was oven-dried for 24 hours at 110 C to determine moisture conten t. BD was calculated based on dry weight. Vegetation samples were collected in September 2005, March 2006, and May 2006. Herbaceous and shrub covers by species were measured using foliar ocular observation in 1x1 m and 1x4 m qua drats, respectively. A modi fied Daubenmire scale (0 to 1%, 1 to 5%, 6 to 10%, 11 to 25%, 26 to 50%, 51 to 75%, 76 to 95%, or 96 to 100%) was used to quantify cover (Daubenmire 1959) Canopy coverage was estimated for each species regardless of overlap with other spec ies. The number of individual herbaceous plants and shrubs was counted within each 1x1 m and 1x4 m quadrats, respectively. Only species rooted inside quadrats were in cluded in the count; those species rooted outside the quadrat were included in the ca nopy coverage data, but not the total species count. In the case of rhizomatous and stoloni ferous plants, indivi dual shoots or stems were counted. For those plants growing in clumps, a whole clump was designated as one individual. Estimated cover of herbaceous and shrub species was used to calculate percent cover and species composition.

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23 Height, DBH, and vigor of all fast grow ing tree species in the SRWC area were recorded in January 2006 and Populus deltoides again in late Apr il 2006. Height poles and diameter calipers were used to m easure height and DBH, respectively. Figure 3-3 SRWC vegetation and soil core plot design. Numbers 1 and 3 are quadrats placed under trees; numbers 2 a nd 4 are place between trees. NA The NA (Figure 3-4), starting at the paved road east of the berm/CSA, consisted of two transects, 55 m in length, and three 10x10m tree plots placed along the transect at alternating north and south positions. The firs t 10x10m plot was 6 m fr om the start of the Natural area to avoid edge effects, the mi ddle 10x10m plot was established 14 m from the first plot, and the last 10x10m plot started 14m from the middle plot. Within the 10x10m tree plots were two vegetati on plots (Figure 35) 1x1m for herbaceous cover and 1x4m for woody species, on opposite corners. Tree assessment included species, count, height, and DBH. Soil cores were taken within th e 1x1m herb quadrat. These quadrats were demarcated by a less noticeable marker such as a pin flag in one corner of the quadrat. The NA was sampled on September 2005, March 2006, and May 2006. Soil samples were collected once in December 2005. Soils were analyzed using the same methodology as the soils of the SRWC area.

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24 55m 10m 10 m = 10 x 10 m tree plot & two veg. plots Figure 3-4 Natural area transect s with three 10x10m tree plots. Figure 3-5 Natural area herb and sh rub vegetation and soil sampling design. Analyses A modified Daubenmire (1959) method was us ed for cover estimation. Analysis of variance was used to test tree growth, vegetation, and soil m eans. Duncans means test was used to distinguish among tree, soil, a nd vegetation means. Percent coverage was

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25 calculated separately for indi vidual herbs and shrubs usi ng the Daubenmire (1959) scale estimates. Percent coverage was analyzed sepa rately using SAS analysis of variance with cultures and species as two main f actors for the SRWC site (3-1). SRWC Model Yij = i + j + ( )ij + ( )ijk + ijkl (3-1) i=1, 2, 3, 4 5; j= 1, 2, 3, 4, 5; k= 1, 2, 3, 4 i = the effect of the ith species j = the effect of the jth culture ( )ij= the effect of the interaction between the ith species and the jth culutre ( )ijk= the effect of the kth slope position nested within the interaction between the ith species and the jth culture ijkl = experimental error Pearson correlation coefficients compared the relationship between tree growth data: height, survival, DBH, and BAH and soil or vegetation variables. Pearson correlation was also used to compare IVI a nd TSC of hairy indigo and cogongrass to soil data. Linear regression was also run on th e IVI of cogongrass and hairy indigo to SOM. Analysis of variance was run for the NA m odel (3-2) with transects and plots as 2 main factors. NA Model Yij = i + j + ( )ij + ij (3-2) i = the effect of the ith transect j = the effect of the jth plot ( )ij = the effect of the interaction between the jth plot and the ith transect ij = experimental error Stepwise regression was used for the NA BAH as a function of vegetation data (TSC, TPCC, IVI, and TF) and as a function of soil data (pH, SOM, P, K, Ca, Mg, NO3) An Importance Value Index (IVI) was calcula ted as the sum of relative cover, relative frequency (RF), and rela tive density (RD). Relative cover is the ratio of total cover of one species to the tota l cover of all species. RF is the ratio of the frequency of

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26 one species to the frequency of all species. RD is the ratio of th e number of individuals of one species to the total number of individuals of all species. The Shannon-Wiener diversity index (S hannon and Weaver 1963) was calculated for shrubs and herb at each site using the formula: i s i ip p H 1ln (3-3) where H' = diversity index, s = number of species, pi = proportion of total sample belonging to ith species; H'max = LogS max ' H H J (3-4) where H'max = maximum possible diversity, S = No. of species, J = Relative diversity. The Jaccard (1912) index was calculated to quantify community similarity for herbs and shrubs among sites. ) ( j b a j Cj (3-5) where Cj = Jaccard index, j = number of common speci es to both sites, a = number of species in site A, and b = nu mber of species in site B.

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27 CHAPTER 4 RESULTS AND DISCUSSION Objective 1 Effect iveness of SRWCs Hypothesis 1 stated that the tree species th at grew the quickest would be the best candidate for cogongrass control. Tree he ight in January 2006 was different among species (p<0.0001) (Table 4-1). Cottonwood was the fastest growing species, reaching upwards of 4m in the first year (Figure 41). On another CSA in central FL, cottonwood grew up to 7.5 m after 2.5 years (Tamang 2005). E. grandis and E. amplifolia, at the SRWC site, grew to heights of 0.9m and 1. 1m, respectively (Table 4-2), but eucalypts were planted in the summer (June 2005), four months after all othe r fast growing trees were planted. E. grandis grew the tallest in the most nor thern slope position (Table 4-3) where water and nutrients were not limited. Height of all trees combined had a significant positive correlation to SOM (Table 44). SOM is greater in soils of high clay content in comparison to sandy soils (Brady and Weil 2002). The soils with great clay content did have high SOM. E. grandis planted on the same CSA in Lakeland, grew 15m in three years (Tamang 2005). E.s grandis with good stand density was able to suppress cogongrass better than E. amplifolia and cottonwood (Tamang 2005). Bald cypress grew upwards of 0.8m and slash pine to 0.3m. Even though, cottonwood was the fastestgrowing species, it failed to be the best species for cogongrass cont rol. Cottonwood is a deciduous species and loses its canopy in the wi nter months. This lack of a canopy could be allowing enough light to reach the forest floor, reviving cogongrass. The eucalypts had the least cogongrass cover and, though this was not tested for, eucalypts could be

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28 exerting an allelopathic eff ect on cogongrass. Other studies have documented eucalypts preventing understorey vegetation (Poore a nd Fries 1985; Abbasi and Vinithan 1997; Bouvet 1998). Eucalypts also have a persiste nt canopy cover, mainta ining their foliage throughout the year. Cypress had no cogongrass present in any of its plots. However, cypress was planted where clay soils were most preval ent and cogongrass cover was greatest in the sandy soils of the SRWC site. Sandy soils (slope positions 1 & 2) were less nutrient and organic matter rich than the clay soils (Table 4-5). The soils where cogongrass was more abundant in the SRWC site were more acidic; this has also been a trend in other Florida cogongrass studies where cogongrass prefers acid ic soils (Collins 2005). Other studies have shown cogongrass grows best in acidic pH, low fertility, and low organic matter soils (MacDonald 2004). So it is not surpri sing that the cypress block had the least cogongrass cover. Table 4-1 Analysis of variance for Janua ry 2006 tree height, DBH (diameter at breast height), vigor, and survival of all trees, including borders, in SRWC study. C (culture), S (species), S*C (species*cu lture interaction, plot/slope position. Response C S S*C Plot(S*C) Height 0.8601 <0.0001*0.0111*<0.0001* Vigor 0.4069 0.0019* 0.0133*<0.0001* Survival 0.5875 0.2650 0.0003*<0.0001* DBH <0.0001*

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29 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 ControlHerbicideMulchShrubsTrees CultureHeight (m) Eucalyptus amplifolia Eucalyptus grandis Populus deltoides Pinus elliottii Taxodium distichum Figure 4-1 Tree height (m) for SRWCs in January 2006 by culture and species. 0 10 20 30 40 50 60 70 80 90 PEPDEGEATD1234CSTMH SRWC VariablesCogongrass TSC (% ) Figure 4-2 May 2006 Cogongrass TSC for all species, slope positions, and treatments in the SRWC site.

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30 Table 4-2 Average tree and shrub height (H, in m), vigor (V), survival (S, %), and DBH (D in cm) in January 2006 by culture and species (excluding borders). Standard deviations in parentheses. Values with the same letter are not different (p=0.05) among cultures within a species. Response Combined average across cultures Species H V S D Eucalyptus amplifolia 0.9C (.5) 3.0B (1) 63A (48) Eucalyptus grandis 1.1B (.5) 2.7C (1) 59A (49) Populus deltoides 3.5A (.9) 2.1D (1) 60A (49) 2.61 (1) Pinus elliottii 0.3D (.2) 3.2A (.9) 40A (49) Taxodium distichum 0.8C (.2) 2.5D (.8) 87A (34) Control Eucalyptus amplifolia .49b (.2) 4a (.5) 20c (40) Eucalyptus grandis 1.0ab (.5) 3.0abc (1.1)64b (48) Populus deltoides 4.1a (.8) 2.2bc (1.1) 79a (41) 3.22a (1.1) Pinus elliottii .3a (.1) 2.7bc (1) 40c (49) Taxodium distichum .89a (.3) 2.3a (1) 73b (45) Herbicide Eucalyptus amplifolia 0.5b (.2) 4a(.3) 28b (45) Eucalyptus grandis 0.93bc (.5)3.3abc (1) 53c (50) Populus deltoides 3.8b (.9) 1.7c (1) 74a (44) 2.9b (1) Pinus elliottii 0.16a (.2) 2.7cd (.9) 49b (50) Taxodium distichum 0.92a (.2) 2.4a (.8) 93ab (26) Mulch Eucalyptus amplifolia 0.9a (.5) 3.1c (1.1) 80b (40) Eucalyptus grandis 1.0a (.5) 2.6abc (1.1)84a (36) Populus deltoides 3.2c (.7) 2.3a (1.2) 53b (50) 2.32c (.8) Pinus elliottii 0.35a (.2) 2.3d (1) 73a (44) Taxodium distichum 0.8a (.2) 2.1a (.8) 96a (19) Shrubs Eucalyptus amplifolia 1.2a (.5) 2.7c (1) 93c (24) Eucalyptus grandis 1.2ab (.5) 2.6abc (1.2)47a (50) Populus deltoides 2.9c (.7) 2.7ab (1) 60b (49) 2.31c (.82) Pinus elliottii 0.31 a (.2) 3.2ab (.6) 16d (37) Cephalanthus occidentalis 0.71 a (.3) 1.9b (.9) 58bc (49) Ilex glabra 0.4 b (.1) 2.0 b (1) 38 c (49) Myrica cerifera 0.51 b (.2) 2. 4ab (1) 84 a (37) Serenoa repens 0.21 c (.1) 2.5 a (.9) 73 ab (44) Trees Eucalyptus amplifolia 0.8a (.4) 3.3b (.8) 92c (28) Eucalyptus grandis 0.9c (.5) 3abc (1) 46a (50) Populus deltoides 2.8c (.6) 3.2a (1) 39c (49) 2.04d (.7) Pinus elliottii 0.3a (.2) 3.5a (.6) 21d (41) Gordonia lasianthus 0.9 b (.3) 1.9 b (.3) 94 a (23) Liquidambar styraciflua 1.2 a (.4) 1.5 bc (.5) 94 a (24) Nyssa sylvatica 1.3 a (.3) 1.3 c (.5) 97 a (16) Persea borbonia 0.9 b (.9) 1.8 bc (.6) 61 b (49) Persea palustris .4 c (.4) 2.5 a (.7) 24 c (43)

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31 Table 4-3 Average height (m) in January 2006 by slope position (1 at top of slope; 4 at bottom of slope) and species (excluding borde rs). Values with the same letter are not different (p=0.05) among slopes within a species. Species Slope 1 2 3 4 Eucalyptus amplifolia 0.94 Eucalyptus grandis 1.1b 0.85c 1.23a Populus deltoides 3.7a 3.1b Pinus elliottii 0.28b 0.36a Taxodium distichum .83 Cephalanthus occidentalis 0.6b 0.8a 0.7ab 0.7ab Ilex glabra 0.4a 0.4a 0.4a 0.4a Myrica cerifera 0.6a 0.4b 0.5b 0.6a Serenoa repens 0.2a 0.2a 0.2a 0.2a Gordonia lasianthus 0.9a 1.0a 0.8a 1.0a Liquidambar styraciflua 1.1b 1.1b 1.3a 1.4a Nyssa sylvatica 1.2b 1.5a 1.3b 1.3b Persea borbonia 0.9a 1.1a 0.8a 0.8a Persea palustris 0 0.2b 0.4a 0.3ab Table 4-4 Pearson correlation coefficients of all January 2006 height (H) and survival (S) data for all SRWC trees and soil variables. H S OM pH NO3 BD0 BD1 P K Ca Mg H 1 0.19 0.43* 0.43* 0.10 0.37* -0.36* -0.07 -0.01 -0.13 -0.20 S 0.88* 1 0.16 0.35* -0.3 -0.07 -0.2 0.03 0.07 -0.03 -0.04 OM 0.046 0.09 1 0.53* 0.34* 0.62* -0.73* 0.12 0.10 0.06 0.02 pH 0.37 0.30 0.54* 1 0.19 0.39* -.37* .16 -.00 .03 -.01 NO3 -0.11 -0.11 0.56* 0.07 1 -0.25 -0.29 -0.22 -0.29 -0.2 -0.18 BD0 0.06 0.22 -0.22 -0.46* -0.37 1 0.71* -0.14 -0.05 -0.03 0.00 BD1 -0.06 -0.10 -0.55* -0.39 -0.56* 0.25 1 -0.18 -0.04 -0.05 -0.05 P -0.30 -0.14 -0.12 -0.09 -0.25 0.01 -0.08 1 0.74* 0.90* 0.88* K -0.10 0.04 0.13 -0.13 -0.16 0.002 -0.07 0.67* 1 0.81* 0.78* Ca -0.32 -0.17 -0.01 -0.12 -0.25 0.07 -0.02 0.92* 0.81* 1 0.98* Mg -0.35 -0.17 -0.03 -0.16 -0.20 0.11 -0.06 0.92* 0.77* 0.99* 1 Coefficients above the diagonal for all SRWC trees combined and below the diagonal for all eucalypt trees combined. Values with a indicate a Pearson correlation at the .05 level.

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32 Table 4-5 Means for all soil variables in th e Natural Area and the Short Rotation Woody Crop (SRWC) sites. Surface BD (BD0), subsurface BD (BD1), transect (T), mixed wetland forest (MW), cypress fore st (C), SRWC control culture (C), herbicide culture (H), mulch culture (M ), native shrub culture (S), and native tree culture (T). Values with the same le tter are not different at the .05 level. Trt OM pH BD0 BD1 NO3 P K Ca Mg Natural Area Ave 5.6 6.15 0.699 0.902 5 531 104 2496 864 T1 4.5a 6.4a 0.79a 0.96a 6a 494a 125a 2632a 960a T2 6.7a 5.9a 0.57a 0.81a 4a 567a 84a 2360a 768a MW 5.8a 6.1a 0.72a 0.96a 5a 523a 89a 2470a 850a C 5a 6.4a 0.55a 0.81a 5a 555a 151a 2572a 906a 1 3.9a 6.2a 0.92a 1.05a 8a 510a 81a 2315a 728a 2 4.2a 6.1a 0.78a 0.93a 3a 552a 115a 2803a 1088a 3 8.7a 6.2a 0.35a 0.78a 4a 529a 117a 2370a 777a SRWC Ave 5.4 6.43 .717 0.832 11 527 256 3189 1257 EA 5.7a 6.3b 0.6a 0.81a 9a 611a 256a 3908a 1554a EG 4.6 6.3b 0.68a 0.92a 7a 472a 157a 2749a 913b PD 7.8a 6.7a 0.53a 0.71a 14a 526a 154a 2985a 979ab PE 4.1a 6.4b 0.92a 0.98a 14a 535a 168a 3190a 1184ab TD 8a 7a 0.54a 0.69a 15a 682a 216a 3789a 1352ab C 6.3a 6.6a 0.65a 0.79b 12a 575a 190a 3269a 1125ab H 5.5a 6.6a 0.66a 0.79b 10a 601a 171a 3747a 1423a M 4.7a 6.6a 0.79a 0.94ab 11a 476a 137a 2649a 914ab S 5.4a 6.3a 0.63a 0.78b 13a 407a 131a 2198a 686b T 6.2a 6.4a 0.69a 0.99a 11a 585a 243a 3641a 1313a 1 1.7b 6.2c 0.70b 0.93a 8a 454a 145a 2709a 930a 2 6.5a 6.3bc 0.99a 1.07a 13a 622a 216a 3797a 1430a 3 6.8a 6.5b 0.55b 0.75b 10a 535a 197a 3187a 1150a 4 7.3a 6.8a 0.55b 0.71b 14a 530a 152a 2939a 971a Objective 2 Cultural Treatments Cogongrass had been suppressed by a dens e canopy cover on CSAs in central Florida (Tamang 2005). An impenetrable layer of mulch or cogonmash should theoretically constrai n cogongrass growth by providing c over. Cogongrass cover in the SRWC site was significantly different among cultures (p=0.0113) (Figure 4-2). The mulch and the herbicide treatment had less than 2% cogongrass cover in May 2006 (Figure 4-2). The herbicide applied twice in the SRWC site to the herbicide block was

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33 2,4-D at 1.1 kg Ai/ha. 2,4-D is mainly us ed for broadleaf species but in this study it seems to have constrained cogongrass. The cogonmash had 0.5% cogongrass cover and was the most effective at constraining cogongrass. However, the c ogonmash study only began in September 2005. More time is needed to accurately come to any sort of conclusions about how effective a cogonmash treatment might be. Other studies have shown cogonmash to have 20 to 60% less cogongrass than the cogongrass contro l method of slashing (Chikoye 2001). The control was positioned on the edges of the field and this position is first to be invaded by cogongrass from the surrounding cogo ngrass areas. Like cogongrass TSC, TPCC was significantly differe nt among cultures (p=0.0290). TPCC was greatest for the native tree treatment at 58%. The best treatment for all cogongrass control and TPCC was the mulch culture. Mulch creates an e ffective barrier that obstructs the sun. Objective 3 Native Species Colonization Herbaceous plants The flora of the SRWC site consisted of, primarily, herbaceous species of the Asteraceae family. The SRWC area is ideal for wind dispersal because the site is surrounded by open fields, which are conduciv e to continuous wind movement. There are no thick forests to obstruct the path of the seed. Many early colonists of abandoned fields are winter and summer annual herbs. Plants of the Asteraceae, with weightless achenes (single-seeded dry fruit) are a bundant (Bazzaz 1979). Achenes of sow thistle have been collected by aircraft on a sc reen 2000ft above Tallula, LA (Glick 1939). Dogfennel are surrounded with hairs allowi ng effective dispersa l by wind (Ferrell and MacDonald 2005). Another frequent herb in the SRWC area, Canadian horseweed, can

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34 produce over 200,000 small, wind-dispersed seed s per plant in late summer (Keever, 1950). In the SRWC site, herbaceous species of the Fabaceae were also common. Hairy indigo, an exotic legume, had the greates t TSC, 54%, and was observed in 140 quadrats out of a possible 160 (88%). This species grew only in fall 2005. It is a nitrogen fixer and alters soil conditions to make the soil more suitable for other vegetation species. Hairy indigo can fill the ecological nich e provided by cogongrass (Gaffney 1996). Nitrogen deficiency is a common barrier to plant growth on mine spoils (Bradshaw and Chadwick 1980). The development of a stable ecosystem is reliant upon the colonization by nitrogen fixing species on mine spoils (Robe rts et al. 1981) and ha iry indigo facilitates the establishment of future pl ants. There were an abundance of nitrogen fixing species in the first growing season; four were presen t in Sept. 2005 and only one in March and May of 2006. Hairy indigo was typically growing with only one other plant species. This could be attributed to the thick canopy cove r hairy indigo provides. This species had a high IVI value of 214. A total of 42 species were observed in the SRWC area during three growing seasons. Of that 42, 8 herbaceous species were unidentified. Of these 8, 4 were classified to the family level: the Fabaceae, the Euphorbiaceae, and two in the Poaceae family. Of the 34 plants that were identif ied in the SRWC area, 15 (44%) were exotics and 19 (56%) were native, belonging to 18 fam ilies. Eight were not identified to the species level; therefore, nativity could not be determined. Other successional studies on phosphate mined areas have observed that ex otic weed species dominate in primary succession, but their numbers are replaced by native plants (Manner et al. 1984).

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35 Among identified species in the SRWC area, Aster elliottii, Cirsium horridulum,, Commelina diffusa, Cyperus rotundus, Geranium carolinianum, Sesbania exaltata, Lepidium virginicum and three of the uni dentified species app eared only once in 160 quadrats. Native species such as Boehmaria cylindrica, Conzya canadensis, Eupatorium capillifolium, Gnaphalium falcatum and Passiflora incarnata were common. Apart from cogongrass, introduced species such as hairy indigo and sow thistle occurred frequently. The absence of many species in the SRWC area that were found in the Natural area is due in part to the stressful environmental conditions and poor disp ersal abilities of the native herbaceous species. The absence of the Natural area species might also be attributed to the lack of canopy cover in the SRWC area. NA TPCC does not include the tree and shrub canopy above the herbaceous specie s. In addition, if Natural area natives successfully disperse into the SRWC area, it wi ll be more difficult for the native species to compete with the introduced species. Trends in herbaceo us vegetation suggest an even greater presence of native plants than what wa s seen after the first year of SRWC growth. Manner et al. (1984) noticed the same trends on Nauru Island. Of the 32 herbaceous species observed in the NA, only three were introduced species. This trend is typical of most natu ral areas. According to Manner (1984), most exotics do not penetrate into established communities unl ess new niches are made available by direct disturbance. While the st udied Natural area is frequently visited by humans, people walk on an elevated boardwalk and leave the area re latively undisturbed. Cogongrass had an average TSC of 28% in May 2006 and was found growing in all cultures, most prolifically in the native tree and shrub cu ltures (Figure 4-2). Cogongrass TSC was 25% for the native tree culture and 27% for the native shrub culture. The TSC

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36 of the control was high, 85%, but this is mi sleading. Cogongrass was one of the top five species found growing in the SR WC area with an IVI value of 135. Native tree and shrub cultures are not effective met hods to control cogongrass re growth. The native culture species are slow growing and therefore do not provide ample canopy cover to constrain cogongrass growth. TPCC failed to differ within species (p =0.1100) (Table 4-6). It differed among cultures (p=0.0290). TPCC was greatest for the native tree treatment at 58%. The best treatment with the least TPCC was the mulc h treatment at 23%. Mulch creates an effective barrier that obstructs the rays of the sun to prevent much photosynthesis from occurring. TPCC was greatest in the most southern, sandiest slope position (1) in the field, 60%. TSC was greatest for hairy indi go, with 54%. Cogongrass had a high TSC of 21%. TSC and TPCC were highest in the cypr ess block at 13% and the slash pine block at 65%, respectively and lowest in the Eucalyptus grandis block with a TSC of 8% and in the Eucalyptus amplifolia block with a TPCC of 27%. Table 4-6 Analysis of variance for herbs and shrubs in the Sh ort Rotation Woody Crop (SRWC) and Natureal Area (NA) sites. Values with a differ at the .05 level. Species (S), slope position/plots (P), culture (C), and transect (T). Variable TPCC SRWC Herbs SRWC Shrubs Species 0.1100 0.0577 Culture 0.0290* 0.3294 Slope positions 0.1243 0.4309 S*C 0.0005* 0.6816 P(S*C) <0.0001* <0.0001* NA Herbs NA Shrubs Transect 0.3690 0.3357 Plot 0.2571 0.1170 T*P 0.4274 0.0857 The 10 greatest IVIs and TSCs (Table 4-7) were analyzed to reveal the differences for cultures, species, and slope positions. TSC was different (p=0.0193) within treatments for ragweed. The native tr ee culture had the greatest TSC, 15%, than

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37 any of the other four cultures. TSC was di fferent for cudweed within treatments; the greatest TSC was observed in the native tree culture. The IVI value of sow thistle was different within cultures (p<0.0001) and species (p=0. 0450). The culture with the greatest IVI was the mulc h culture with an IVI value of 216. Species Eucalyptus amplifolia and Eucalyptus grandis had similar IVI values for sow thistle, 142 and 122, respectively. Cogongrass TSC differed among species (p =0.0112) and cultures (p=0.0113) (Figure 4-2). The control had the greatest TSC, 55%, while the herbicide and mulch treatments had the least TSC, less than 2% each. Pinus elliottii also had the greatest TSC value for all fast growing tree species, 32%. Taxodium distichum had no cogongrass present and Eucalyptus amplifolia had minimal cover, 1%. Both eucalypts had low cogongrass cover and perhaps th e eucalypts are exerting an al lelopathic effect. Other studies have documented eucalypts preventi ng understorey vegetation (Poore and Fries 1985; Abbasi and Vinithan 1997; Bouvet 1998). The control treatmen t is located on the eastern and western edges of the SRWC study area, which may explain why cogongrass TSC is greatest in this treat ment; cogongrass may be invading from outside the study area in the control blocks.

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38 Table 4-7 Ten greatest IVI and TSC (%) valu es of herbs and shrubs for each site. SRWC Herbs IVI TSCShrubs IVI TSC Boehmaria cylindrica 221 53 Baccharis halimifolia 222 5 Indigofera hirsuta 214 54 Sambucus canadensis 200 5 Imperata cylindrica 135 21 Ludwigia peruviana 53 0.5 Gnaphalium falcatum 118 9 Sonchus asper 110 3 Aeschynomene indica 103 8 Conzya canadensis 99 2 Unk SRWC7 97 8 Cirsium horridulum 95 3 Sesbania exaltata 93 18 Medicago lupulina 84 10 Ambrosia artemissiifolia 74 10 Physalis pruinosa 67 9 NA Herbs IVI TSCShrubs IVI TSC Hydrocotyle umbellata 117 7 Ulmus americana 155 17 Cicuta maculata 112 53 Baccharis halimifolia 132 34 Thelypteris kunthii 107 21 Urena lobata 120 13 Oxalis corniculata 104 1 Itea virginica 115 11 Dicanthelium commutatum 98 3 Acer rubrum 104 8 Ptilimnium capillaceum 94 1 Parthenocissus quinquefolia 104 1 NA Herbs IVI TSCShrubs IVI TSC Unk NA2 92 7 Carpinus caroliniana 96 24 Viola sororia 90 1 Cornus foemenia 96 38 Sambucus canadensis 89 3 Serenoa repens 87 31 Samolus ebracteatus 85 3 Clematis crispa 85 6 Salvia lyrata 79 2 Sabal palmetto 55 28 Oplismensus hirtellus 86 1 Sabal minor 58 14 Boehmaria cylindrica 77 1 Ludwigia peruviana 61 11 The herbaceous species, hairy indigo, with the greatest TSC and high IVI value, grew in all treatments, with all species, and in all slope positions. However, there were no differences among any of the parameters for TSC and IVI. All treatments had a TSC value above 50% and IVI values were well above 150 for all treatments. Eucalyptus amplifolia had the greatest TSC, 67%, while cypress had the least at 29%.

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39 A field untended for a year is covered by populations of mainly annual and biennial herbaceous species; a few tree and shrub species may be present (Bard 1952; Egler 1954; Keever 1979; Oosting 1942). Initially, comp etition is minimal at newly disturbed, open sites. Soon, however, ground cover become s dense and successive appearance of herbaceous species in abandoned fields is re liant on competitive in teractions (Davis & Cantlon 1969). A study at a CSA in Lakeland, Florida identified 57 herbaceous species in the understory of eucalypt and cottonw ood trees after four years (Tamang 2005). Forty of these species were native. Sixteen were also present at the SRWC study area. There is good evidence that much of the vege tation trends seen at the Lakeland site will occur in the SRWC study area, except that more native speci es may return to the SRWC site because SOM is greater and pH is more acidic than that of the Lakeland site, creating better conditions for FL natives. As successi on proceeds, P, Mg, and Ca available to plants in the soil will be gra dually depleted within reach of the root. However, K should increase. As shrubs invade the field, nutrients increase in the topsoil; this is attributed to the attainment of nutrients from greater depths and their return to the upper soil layers by recycling (Burrows 1990). The increase of diversity over time is caused by microhabitat diversification, arising from local change s in soil properties around individual plants (Mellinger and McNaughton 1975; Zinke 1962). At the Lakeland site CSA, cogongrass had the greatest IVI of all herbaceous species (Tamang 2005). Cogongrass did not ha ve the greatest IVI in the SRWC study area, but it was one of the top five IVI values It is possible in 3 years that cogongrass will have the greatest IVI value due its vigorous rhizome growth (MacDonald et al. 2002).

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40 Regression comparing SOM to cogongrass IVI by slope positions (Figure 4-3) indicated that SOM is currently not an im portant variable in determining whether cogongrass will be present (r2=0.0106). 0 50 100 150 200 250 0.002.004.006.008.0010.00 OM (%)Cogongrass IVI Figure 4-3 Relation of SOM to cogongrass IVI in the SRWC area. SOM was also compared with hairy indigo in the SRWC study area. Again, it was not an important factor in whether hairy indigo was pr esent on a plot (r2=0.0041) (Figure 4-4). 0 50 100 150 200 250 300 350 024681012 OM (%)Hairy indigo IVI Figure 4-4 Relation of SOM to hair y indigo IVI in the SRWC area. Pearson correlations was run for the herb aceous species with the greatest IVI values. IVI and TSC were correlated with soil variables to see if any trends were occurring that could be used to predic t vegetation pattern (Table 4-8; 4-9).

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41 Table 4-8 Pearson correlation coefficients of sow thistle and cudweed IVI, TSC, and soil variables in the SRWC area. TSC IVI OM pH NO3-N P K Ca Mg BD0 BD1 TSC 1 0.27 -0.03 0.35* -0.09 -0.08 -0.09 -0.11 -0.13 -0.17 -0.19 IVI 0.80* 1 -0.18 -0.01 -0.23 -0.16 -0.18 -0.16 -0.14 0.09 -0.08 OM -0.54* -0.41* 1 0.47* 0.27 0.16 0.13 0.11 0.07 -0.06 -0.14 pH -0.24 -0.24 0.40* 1 0.07 0.09 -0.05 -0.06 -0.10 -0.17 -0.27 NO3-N -0.08 -0.06 0.21 -0.00 1 -0.22 -0.28 -0.18 -0.15 0.09 -0.08 P -0.05 -0.06 0.08 0.08 -0.31 1 0.70* 0.88* 0.85* 0.14 0.21 K -0.04 0 0.12 0.002 -0.34 0.67* 1 0.78* 0.75* 0.05 0.16 Ca -0.07 -0.03 0.10 0.01 -0.19 0.88* 0.75* 1 0.98* 0.17 0.27 Mg -0.05 -0.03 0.05 -0.02 -0.16 0.86* 0.72* 0.98* 1 0.24 0.32* BD0 -0.10 0.05 -0.12 -0.10 -0.00 0.09 -0.03 0.11 0.13 1 0.79* BD1 0.31 0.26 -0.20 -0.23 -0.24 0.20 0.09 0.22 0.23 .73* 1 Coefficients above the diagonal for sow thistle and below the diagonal for cudweed. Values with a indicate a Pearson correlation at the .05 level. Table 4-9 Pearson correlation coefficients for hairy indigo and cogongrass IVI, TSC, and soil variables in the SRWC area. TSC IVI OM pH NO3-N P K Ca Mg BD0 BD1 TSC 1 0.75* -0.10 -0.23 0.47* -0.09 -0.14 0.05 -0.02 0.14 0.07 IVI 0.51* 1 -0.20 -0.34 0.18 -0.05 -0.08 0.04 0.01 0.37 0.31 OM -0.25 0.01 1 0.29 0.31 -0.23 -0.11 -0.29 -0.27 -0.72* -0.75 pH -0.35* -0.02 0.48* 1 0.05 -0.32 -0.38 -0.50* -0.46* -0.21 -0.34 NO3-N 0.01 -0.10 0.32* 0.13 1 -0.22 -0.34 -0.12 -0.18 -0.26 -0.38 P 0.13 -0.06 0.20 0.17 -0.15 1 0.70* 0.85* 0.86* 0.04 0.13 K -0.01 -0.14 0.18 0.01 -0.22 0.73* 1 0.80* 0.80* 0.03 0.16 Ca 0.17 -0.05 0.17 0.06 -0.10 0.89* 0.80* 1 0.98* 0.14 0.29 Mg 0.21 -0.03 0.14 0.02 -0.07 0.87* 0.77* 0.98* 1 0.14 0.29 BD0 0.26 0.06 -0.10 -0.19 0.06 0.13 0.05 0.15 0.22 1 0.77* BD1 0.27 0.12 -0.22 -0.33* -0.15 0.19 0.14 0.23 0.28 0.80* 1 Coefficients above the diagonal for cogongrass and below the diagonal for hairy indigo. Values with a indicate a Pearson correlation at the .05 level. Vegetation variables were analyzed for the cottonwood block since growth was greatest for this species. The culture-s lope position interaction was significant (p=0.0053) for TPCC (Table 4-10). Like all SRWCs, cottonwood had the least TPCC in the mulch treatment (20%), further proving that it is the most effective culture for vegetation growth prevention. The native tree and shrub cultures had the greatest TPCC. Hairy indigo had the greatest TSC and IVI value in the Populus deltoides block (Table 411). Two shrub species were present in the cottonwood block, saltbush and elderberry

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42 Saltbush had a TSC of 0.5% and elderberry 5%. IVIs were 222 for saltbush and 200 for elderberry Pearson correlation was performed by qua drat for the cottonwood block for the TPCC, cogongrass TSC, and BAH (scaled up from the quadrat unit). The worst cottonwood growth was in the native shrub and tree cultures and thes e cultures also had the greatest TPCC and cogongrass TSC, whic h could explain such poor growth. The cottonwoods had to compete harder with c ogongrass and understory vegetation than the control, herbicide, and mulch cultures. TPCC was negatively correlated to BAH on a quadrat basis (p=0.0007) (Table 4-12). Pearson correlation was also done on a cottonwood plot basis for TPCC, cogongrass TSC, and BAH. There were no correlations except for cogongrass TSC positively correlated to TPCC (p=0.0059) (Table 4-12). Table 4-10 Analysis of variance for cottonwood vegetation variables: total species cover (TSC), total plant canopy cover (TPCC) and importance value index (IVI). P-values with a differ at the .05 level. Herbs Response C P C*P TSC 0.4359 0.9102 0.2091 TPCC 0.2011 0.9330 0.0053* IVI 0.2595 0.9489 0.1348 Shrubs Response C P C*P TSC 0.7742 0.4200 TPCC 0.7901 0.5000 IVI 0.8139 0.3949 Shrub C*P was not testable.

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43 Table 4-11 Top 5 species with the greatest TS C and IVI values in the cottonwood block. Values with the same letter are not different at .05 level. Response Species TSC IVI Indigofera hirsuta 42a 212a Sesbania virgata 38ab 121abc Imperata cylindrica 23abc 156ab Lactuca graminifolia 10abc 126abc Aeschynomene indica 6bc 129abc Table 4-12 Pearson correlation coefficients for Populus deltoides basal area per hectare (BAH), total plant canopy cover (TPCC) and cogongrass total species cover (TSC) on a quadrat and slope position ba sis. Coefficients with a are different at the .05 level. BAH TPCC Cogongrass TSC BAH 1 -0.5540*-0.3320 TPCC -0.5040 1 0.6500* Cogongrass TSC -0.2970 0.7960* 1 Coefficients above the diagonal are on a quadrat basis; below are on a slope position basis. Shrubs Both sites combined had a total of 34 di fferent shrub species. No woody species went unidentified. Swamp dogwood had th e highest TSC value, 38%, and the other species with the top five TSCs were all f ound in the Natural area. IVI was highest for saltbush in the SRWC site, 222, because it was the most preval ent shrub species. However, its TSC was always less than 1% for saltbush in the SRWC site. Besides herbaceous plants, some of the immi grant seeds in the field will be from perennial woody species of nearby shrub and or forest stands, dispersed by wind, birds, or mammals (Burrows 1990). No shrubs we re present in September 2005. Only three shrub species were observed in the SRWC ar ea. And the majority of the observations were saltbush/groundsel tree and all were seedlings. There were a total of 98 observations of shrub species, 96% of these obser vations were saltbush; observed in 65 of

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44 160 quadrats (41%). Elderberry was observed in one quadrat with a frequency of less than 1%. Primrose willow was present in two quadrats. TPCC was greatest in the herbicide culture with an obs erved value of 1.6%. All other treatments observed TPCC of 1% or less. TPCC was highest in the most southern slope position (1) of the field with a TPCC of 1.5%. Amongst fast-growing tr ee species, cottonwood had the greatest TPCC at 1.7%. Cypress had the leas t with zero shrubs observed. Shrubs are slow to populate an abandone d field for various reasons: 1) their propagules are not dispersed as quickly or as far as those of herbs, 2) seed banks and vegetative propagules of woody species are near ly or completely lacking in cultivated fields, 3) biotic and abiotic conditions ar e not favorable enough in open, cultivated ground for juveniles of woody species, and 4) herbaceous populations exclude the woody plants by rapid growth (Burrows 1990). A study on forested central Florida phosphate mined lands found the distance to a seed source was the best predictor (R2=0.85) of the regeneration of the later successional species and a good predictor of species diversity. Both the IVI of the later successional species and the diversity index decreased with the distance from the seed source (McClanahan 1986). The Natural area had 32 shrubs, of which onl y four were introduced species. IVI was greatest for American elm with a va lue of 155, followed by saltbush with 132, caesarweed with 120, Virginia sweetspire with 115, and red maple at 104 (Table 4-7). Swamp dogwood dominated in TSC with a hi gh value of 38%. Saltbush had TSC of 34%; saw palmetto with 31%, cabbage palm a TSC of 28%, and American hornbeam 24%. The shrub with the greatest frequency was American elm; it was observed in 8 of

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45 the 12 plots (67%). Red maple American hornbeam saltbush laurel oak, and caesarweed all observed a frequency of 5 of the 12 plots (42%). NA trees Trees were only found in the Natural area A total of 148 trees were observed, composed of 13 species. Height and DB H were measured during September 2005. Height differed among transects (p=0.0373) a nd among species (p=0.0203). Height for transect 1 averaged 16.3 m and 13.2 m for tran sect 2. DBH was also greater on transect 1, 24.7cm, than on transect 2, 15.8 cm. Plot 3 with the tallest trees has many bald cypress trees. Likewise, DBH was greatest in plot 3, 24.1cm. No significant differences were found for DBH or BAT/BAH. Cypress was the ta llest at 24m and the most frequent with 40 observations. Stepwise regression was run for BAH in the NA as a function of soil variables (OM, pH, NO3, P, K, Ca, Mg, BD0, and BD1). Only one variable had an effect on BAH: pH (p=0.0193, r2 =0.7819) (Figure 4-5). The greates t BAH were found on plots with the greatest pH. Transect 1 had a greater pH (Table 4-5) than transect 2 and, therefore greater BAH. Stepwise regression was also run for NA BAH as a function of vegetation data (TSC, TPCC, TF, and IVI) but none of thos e variables fit a model and therefore, had no effect on the BAH of the NA plots. The variables were run at the 0.1500 level.

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46 0 20 40 60 80 100 120 140 5.75.85.966.16.26.36.46.56.6 pHNA BAH Figure 4-5 Stepwise regression (0.15 level) of NA tree BAH as a function of pH by plot. Species Diversity and Site Similarity The SRWC was much less diverse comp ared to natural communities, where Shannon-Wiener diversity index falls between 1.5 and 3.5. This might be due to young stand age and the competition of plants with cogongrass. Allelopathy of eucalypts and cottonwood also might have affected the spec ies recruitment rate in the SRWC area. Shannon Weiner diversity index for herbs in the SRWC area was 0.69, compared to 1.13 for the Natural area (Table 4-13). The Natura l area had the greatest index value, but is still not typical of most natural forests. This could be attributed to a sample size that was too small to get accurate represen tation of all herbaceous species. For shrubs, the Natural area had the great est Shannon-Weiner index value at 1.29 (Table 4-18). The SRWC area had a very low index of 0.086 since only three shrub species were present in this site.

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47 Only the Natural area had trees present as part of the vegetation surveys and they had a Shannen-Weiner index of 0.9 (Table 4-13 ). Hmax was 1.04. Again this value may be low due to a small sample size. Table 4-13 Shannon-Weiner di versity index (H) and ma ximum possible diversity (Hmax) of all sites for herbs, shrubs, and NA trees. SRWC NA CM Herbs H' 0.69 1.13 0.5 Hmax 1.25 1.3 0.7 Shrubs H' 0.086 1.29 0 Hmax 0.47 1.4 0 Trees H' 0 0.9 0 Hmax 0 1.04 0 The Natural area and the SRWC sites had a Jaccard index of 0.07 and the Natural area had a Jaccard index of 0.05 (Table 4-14). Table 4-14 Jaccards community similarity index (Cj) for herbs (H) and shrub species (S) at all sites. Site NA CM SRWC H 0.07 0.2 S 0.09 0.33 CM H 0.05 S 0.03 The SRWC area and the Natural area had a shrub Jaccard community similarity index of 0.09 (Table 4-14). The SRWC area is in its very early stage of succession and with time more shrub species will volunt arily make their way to this site. Objective 4 Soil Properties The initial 9% SOM, collected in February 2005 decreased to 5.4% (Table 4-5) in December 2005 because the soil collected in February 2005 had just been rotovated into the soil a month prior, contribu ting to the high SOM. Similar trends have been seen with SOM amounts dropping as mineralization and tr ee growth occurs in eucalyptus stands

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48 (Loumeto and Bernhard-Reversat 2001). Soils high in clay are generally high in SOM (Brady and Weil 2002). Finer textured soils am ass more SOM because 1) they typically produce more plant biomass, 2) the soils are less well aerated and lose less SOM, and 3) more of the organic material is shielded from decomposition because it is bound by clayhumus complexes (Brady and Weil 2002). The soil in the NA had a pH of 6.15. Th e soil series of the NA, Nittaw, are known to have neutral to slightly acidic pH (P olk County Soil Survey, US Dept. of Ag, Soil Cons. Service 1990). The SRWC site had the most NO3-N, 11 mg/kg (Table 4-5). In the SRWC area, there was a high frequency of N2 fixing species in the first sampling, mainly hairy indigo. Hairy indigo can contribute 31 kg N/ha (Okito 2004). In other studies, carried out on mining clay wastes in China, a great prevalence of legumes contributed to the nitrogen economy of the vegetation (Mar rs et al. 1980). The development of a functioning nitrogen cycle has shown to be crucial for the successful restoration of derelict land (Bradshaw and Chadwick 1980). Gains in soil N are contributed to the soil from rainwater in the form of NH3 and NO3. Microorganisms also play a great role, through the fixation of N2, in N soil gains. Ample SOM is needed by free-living bacteria to fix N (Stevenson 1986). Surface BD was less than subsurface BD for all sites. BD samples taken deeper in the soil profile are typically greater due to reasons, which include: lower SOM, less aggregation, fewer roots and other soil organi sms, and compaction due to the weight of the overlying layers (Brady and Weil 2002). SRWC Soils of the SRWC CSA are of the soil series, Haplaquents. These soils are colloidal clays, composed of mainly montmor illonite. They are highly fertile soils (Polk

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49 County Soil Survey, US Dept. of Ag, Soil Cons. Service 1990). SOM was different (p=0.0008) along the slope (Table 4-5). SOM might be so low in slope 1 because of a high sand consistency. Typically, less SO M is found in sandy so ils (Brady and Weil 2002). Likewise, pH, NO3-N, P, Ca, and Mg were also lowest in slope position 1. Soil p (Table 4-15; 4-16)). Soil pH was also different (p=0.0090) among slope positions and among species (p=0.0425). Mg differed among species (p=0.0337) and cultures (p=0.0321) (Table 4-8). Surface BD was di fferent among slope positions (p=0.0034). Subsurface BD differed among slope positions (p=0.0173) and cultures (p=0.0084). Table 4-15 Analysis of variance for the S hort rotation woody crop (SRWC) and Natural Area soil variables: species (S), culture (C), slope position (P), transect (T), and quadrat (Q). Values with a are different at the .05 level. SRWC S C P P(C*S) OM 0.3622 0.5649 0.0008* pH 0.0425* 0.1190 0.0090* NO3-N 0.0864 0.8194 0.2745 P 0.2078 0.1775 0.1075 K 0.3432 0.4033 0.3178 Ca 0.0754 0.0580 0.1259 Mg 0.0337* 0.0321* 0.0914 BD0 0.7608 0.1371 0.0034* BD1 0.3880 0.0084* 0.0173* Natural Area Habitat T P T*P OM 0.8014 0.6972 0.4798 0.6831 pH 0.8814 0.1986 0.2913 0.8687 NO3-N 0.8914 0.5190 0.1257 0.0713 P 0.5158 0.3597 0.7868 0.9126 K 0.5103 0.9695 0.8329 0.9674 Ca 0.5393 0.5565 0.5939 0.8010 Mg 0.4701 0.4383 0.4336 0.7093 BD0 0.5005 0.2287 0.2113 0.6802 BD1 0.8757 0.5124 0.8393 0.6669 SRWC P(C*S) was not testable.

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50 Table 4-16 Average soil means by slope position (1 at top of slope sand; 4 at bottom of slope-clay). Values with the same le tter are not different (p=0.05) among slope positions. Slope OM pH NO3-N P K Ca Mg BD0 BD1 1 1.7b 6.2c 8.4a 454a 145a 2709a930a 0.70b 0.93a 2 6.5a 6.3bc 12.5a 622a 216a 3797a1430a0.99a 1.07a 3 6.8a 6.5b 9.8a 535a 197a 3187a1150a0.55b 0.75b 4 7.3a 6.8a 14a 530a 152a 2939a971a 0.55b 0.71b A greater BD is typically observed on sandi er soils than clay soils because solid particles of the fine-textured soils typically ar e structured in porous granules, even more so when SOM is present in high amounts. Th ese aggregated soils have pores that exist between and within granules (Brady and Weil 2002). NO3 is prone to leaching since its anionic form is not tightly held to the negatively charged clay and SOM. The mulch treatment had the lowest SOM. This could be due to the gradual breakdown of mulch and insufficient time for decomposition into SOM Greater SOM should occur with time due to the tree bioma ss. Mulch decomposition takes 1 to 2 years (Black et al. 1994) depending on species, wood size, numbers and types of soil decomposing microorganisms, moisture, temperat ure, and other climatic variables. After a year, some types of mulch have only decomposed 3 to 7% (Duryea et al. 1999), depending on the lignin conten t. In other studies, mulc h treatments increased SOM (Borland 1990; Black et al. 1994). The mulc h treatment also had the least TPCC for herbaceous species, which could contribute to a lower SOM. The pH in CSAs usually ranges from 7 to 8.3 (Stricker 2000). In this st udy it was lower. This could be attributed to the litter contributed from the thick ca nopy of herbaceous species, primarily hairy indigo, which dominated the site in Sept ember 2005. Accumulation of SOM acidifies soil and forms soluble complexes with nutrien ts such as Ca and Mg (Brady and Weil 2002).

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51 SOM was greatest in the cypress block, which is at the bottom of the slope. Cypress had a similar Duncans grouping as cottonwood for SOM, but differed from E. amplifolia, E. grandis and Pinus elliottii This could be attributed to the fact that slash pine and E. grandis are planted in the sandier, more elevated portions of the field. Cypress and cottonwood also had the highest pH and NO3 levels. NO3 levels were not abnormally high in the SRWC area. NO3 is weakly held by soils and readily leaches, unless there is a high anion exchange capacity (Sparks 2003). Cottonwood had less Ca and Mg than most other short rotation woody crops ( E. grandis had slightly less), and grew the fastest. Poplars are characterize d as nutrient demanding species due to their fast-growing nature (Bergez et al 1989), which explains why cottonwood had less Ca and Mg in the soils. Soils at the SRWC site have the same characteristics of sites that grow cottonwood best: BD less than 1.4 g/cm3, pH of 5.5 to 7.5, and greater than 2% SOM (Baker and Broadfoot 1979). Phosphatic clay naturally ha s high levels of phosphorus, calcium, magnesium, a nd potassium (Stricker 2000). Slash pine had the overall greatest surf ace and subsurface BD and cypress and cottonwood had the lowest, these bulk densities can be attributed to the slope position in the study area and therefore, due to the consistency of the soil at that location. Due to the expanding and shrinking nature of clay so il (Brady and Weil 2002), large breaks form on the surface during dry periods. Large volumes of water enter these cracks in the beginning of a wet period; upon soil saturation, the cracks are closed due to swelling. Because of this characteristic, BD of montmorillonite clay soil experiences fluctuations with the amount of water available. This clay expansion could attri bute to a low BD in the cottonwood and cypress study area. Among species and cultures, few soil properties

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52 were significantly different. Similar results were observed at the Lakeland site across species (Tamang 2005). In comparison to another CSA fast-growing tree farm in the central Florida area, pH was 7.5 +/0.3 (Tamang 2005). Soil pH in the SRWC area was ~6.5. Soil pH of the state soil of Florida (Myakka fine sand) is 5.7 (Alva et al., 2000). Lower pHs may facilitate the return of native plants to the site. SOM in the SRWC site (5.4%) was similar to the Lakeland site (5.37%). This value is expected to decrease with stand maturity. As time progresses in eucalypt st ands, SOM drops as mineralization and tree growth occurs (Loumeto and Bernhard-R eversat 2001); fast-growing trees at the Lakeland site have been growing for ~ 4 y ears. The SRWC area has slightly greater SOM and this may be due to a lower pH. Soil pH depends upon the presence of SOM. Accumulation of SOM acidifies soil (Bra dy and Weil 2002). Phosphorus was much lower in the SRWC site (527 mg/kg) than at the Lakeland operational area site (4053 mg/kg) (Tamang 2005). However in the Lakela nd SRWC-90 site, extracted with water, P was ~150 mg/kg (Tamang 2005). With ample mi cronutrients, SOM, and a slightly acidic pH, this soil environment may catalyze the return of native plants to the site better than the Lakeland site CSA. NA SOM was 5.6% in the natural area (Table 4-5). Values of P were very high in the NA; this could be attributed to the nature of Nittaw soils, particulate matter dispersed through the air and P runoff from the SRWC site Nittaw soils are sandy clay loams; they are poorly drained floodplains. These soils are enriched with phosphate (Polk County Soil Survey, US Dept. of Ag, Soil Cons. Service 1990). High P levels may be due to mining being carried out to the edges of the Peace River flood plain. The mining process

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53 sends particulate matter in the atmosphere, wh ich can land on nearby areas, like the NA. 2:1 clays, like montmorillonite clay, have re latively little capacity to bind phosphorus (Brady and Weil 2002). In mineral soils, phosphat e fixation is at its lowest when soil pH is maintained from 6.0 to 7.0 (Brady and We il 2002), as is present at the SRWC site. Once P translocated to the NA, a higher water table may have prevented element leaching. Wet sites have higher concentrations of P (Marois and Ewel 1983). Correlations Correlations were run for individual SR WCs (Appendix B), all SRWCs combined, and eucalypts combined (Table 4-5). So me trends were found between soil and tree growth variables in the SRWC area (Table 4-5). For Eucalyptus grandis was positively correlated to pH (p=0.0202). For cypress, vigor was positively correlated to NO3-N (p=0.0312) and K (p=0.0150). No correlati ons were found between growth and soil variables in the Myrtaceae family (eucalypts). Pearson correlation coefficients for all SRWCs measured in January 2006 suggested that SOM and pH are positively correlated to height (0.43) (Table 4-5). Height was positively correlated with survival (0. 35) and negatively correlated with surface and subsurface BD (-0.37 and -0.35, respectively) Root growth is constrained as BD increases (Brady and Weil 2002). Macronutrients were highly correlated to one another (Table 4-5). P was positively correlated with Ca, Mg, and K for each species but cypress. Same macronutrient trends were seen with all the trees combined. P was positively correlated with K (0.74), Ca (0.90), and Mg (0.88). K was positively correl ated with Ca (0.81) and Mg (0.78). Ca was also positively correlated with Mg (0.98). CSAs are fertile and nutrient rich lands (Stricker 2000; Tamang 2005). Average pH of the SRWC area was 6.4; a pH value of

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54 5.5 to 7 usually provides optimal conditions fo r plant nutrient levels. If P is readily available at a pH of 6.4, the other plant nut rients, if present in ample amounts, will be satisfactorily available for most plants (Bra dy and Weil 2002). P had high concentrations in the SRWC area (P. Bohlen, Archbold Biol ogical Station, persona l communication June 2006), so nutrients are not likely lacking. Soil pH was positively correlated to SOM in the eucalypts (Table 4-5). SOM was also positively correlated with NO3 (0.56). Most soil nitrogen occurs as part of organic molecules (Brady and Weil 2002). P and K (0.67) P and Ca (0.92), P and Mg (0.92), Ca and K (0.81), K and Mg (0.77), and Ca and Mg (0.99) had highly significant correlated values above 0.65. Ca, Mg, and K should ha ve highly correlated values because these elements are involved in the cation exchange th at occurs readily in montmorillonite clay (Brady and Weil 2002). These positively charged minerals are made available to plants when hydrogen ions in the soil displace th e mineral ions from clay particles.

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55 CHAPTER 5 CONCLUSIONS Cottonwood was the fastest growing SR WC, but, it did not have the least cogongrass present in the unders tory. Cottonwood had a cog ongrass TSC value of 19%. Both species of eucalypts had less cogongrass TSC than cottonwood. Slash pine was the slowest growing species and had the greatest cogongrass TSC. There are multiple reasons for cogongrass growing so well in the cottonwood block, even though cottonwood was the fastest growing (4.5m in the fi rst year). This may be attributed to the deciduous nature of cottonwoods. Eucalypts keep their foliage year round reducing light penetration. Cottonwoods facilitate cogongrass regrowth, by allowing light to filter to the forest floor in the winter months and stimulating the cogongrass rhizomes. Fast-growing tree species need a canopy cove r that is not lost annually; otherwise cogongrass is likely to return. Trees with a spreading and full ca nopy appear to reduce the growth and spread of cogongrass as seen at th e Lakeland CSA (Tamang 2005). The mulch culture constrained vegetativ e growth, likely because little sun penetrated the thick mulch layer. The mulch treatment had the lowest TPCC value, 20%. TSC of cogongrass was least in the herbicid e and mulch treatment. This may indicate that cogongrass needs ample light to stimulate its rhizome growth. A disadvantage of the mulch culture is that it does not discrimi nate among the species affected. The mulch culture in the SRWC area had the lowest quadrat diversity; only two species were observed in each quadrat. However, the CM site had lower TPCC than even the mulch culture in the SRWC area and even less cogongr ass TSC. Nonetheless, the CM study has

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56 not been studied as long as the SRWC study and with time, TPCC and cogongrass TSC could be greater. More natives were present at the natura l area than the SRWC area, but this was expected because it was relativ ely undisturbed. The SRWC area is a disturbed ecosystem and has only begun the primary stages of succession, characterized by many herbaceous, shade-intolerant species. A voiding disturbance helps to prev ent exotic species invasion (Stylinski and Allen 1999). Only three herb aceous species, three shrub species, and one tree species were introduced species in the NA. Natives are lacking in the SRWC area because dispersal means are poor, and a thick canopy likely obstructed much of the di spersal pathways. If NA natives disperse into the SRWC area, there is the obstacle of overcoming the presence of exotic species, competition with cogongrass, and atypical Florida soil conditions. If all lands infested by cogongrass in Florid a were converted to naturally vegetated communities through the employment of fast-growing trees, these phosphate mined lands could be used as corridors connecting importa nt lands for the native flora and fauna of Florida. This conversion would provide i nvaluable landscape linkages, some 200,000 to 400,000 ha of land added to the Florida ecologi cal network. These converted lands could effectively conserve biological diversity in the presence of an encroaching human population and habitat fragmentation. Nationa l parks are not enough to protect viable populations of sensitive species and biodivers ity as a whole (Noss and Harris 1986). A large scale, connected reserv e network is a crucial component for conserving the states biological diversity (Hoctor 2000). An ecol ogical network will prot ect vital ecological

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57 functions and biotic movement more than the current, isolated cons ervation areas (Harris et al. 1996).

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58 CHAPTER 6 FUTURE RESEARCH Although this study has provided some insi ght into the control of cogongrass, additional work will be necessary to make re storation of infested areas effective. Cogonmashing, which can be done cheaply w ith minimal machinery, can constrain the growth of cogongrass. Fast-growing eucalyp ts have the ability to catalyze plant succession and reduce the time it takes to reve rt mined lands to more diverse natural ecosystems. Fast-growing tree species in conjunction with cogonmashing may be the most effective combination of methods curren tly available in the effort to eradicate cogongrass and initiate a natura l succession of native plants. However, it is still not known what lasting effects would be observed. If trees are harvested, the cogonmash would need to pr ovide adequate control of cogongrass. Overtime, the cogonmash will be recycled back into the soil and a dense understory of native vegetation should prolong the control of cogongr ass while eucalypts or other fastgrowing trees regenerate. Ongoing studies must measure the outcomes of these fastgrowing tree plantations. Tree harvest may allow cogongrass to return, but this also needs to be explored. Whethe r or not it makes a difference if the understory is composed of mainly native vegetation would be anothe r topic that could be further examined. Native ecosystems tend to resist invasion by exotics due to each niche already being fulfilled. Upon disturbance, native ecosyste ms are much more vulnerable to introduced species. Invasion would be most apparent at the borders of tree plantations.

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59 It seems sufficient to reassess each site twice a year for vegetation. Few plants were different between March and May 2006. A fall and spring sampling of the vegetation should collectively assess all plants that establish in the sites. The influence of native species on cogongrass control will be si gnificant, but whether to allow natural succession to occur or to facilitate it through the planting of native plants is a question that needs to be addressed. The primary stages of succession usually yield many exotic species, but with time these numbers dwindle and are replaced by beneficial natives. However, the act of planting native plants has many uncertainties, such as survival. The planted natives might fare better if they were treated with nutrients, especially nitrogen, which tends to be limited on phosphate mined soils. More studies that explore which native species are suitable for these clay se ttling areas would provide insight for future reclamation and would likely enhanc e survival of well-adapted species. Because cottonwoods and eucalyp ts are allelopathic, altern atives to these species may be sought. Reducing allelopathy shoul d promote the establishment of a more diverse plant community. Another aspect that should be examined is to observe these fast-growing tree plantations on a number of clay settling areas so any trends in soils or vegetation could be identified. It would also prove benefici al to quantify what seeds are dispersed into the SRWC area. This could be accomplished through the use of seed traps distributed throughout the research site. Dispersal studies are few and not much present data discuss the distances specific species are able to disperse. This information would inform managers of the distance the restoration sites shou ld be from natural areas so that the benefits of natural dispersal could be realized.

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60 APPENDIX A VEGETATION Table A-1 Name and nativity of herbaceous species on all sites: short rotation woody crop (SRWC), natural area (NA) and cogonmash (CM). Herbs Scientific Name Common Name Nativity Family Sites Aeschynomene indica Indian jointvetch Exotic Fabaceae SRWC Ambrosia artemissiifolia Common Ragweed Native Asteraceae SRWC, CM Aster elliottii Elliott's Aster Native Asteraceae SRWC Boehmeria cylindrica False Nettle Native Urticaceae SRWC, NA Carex albolutescens Green White Sedge Native Cyperaceae NA Chenopodium ambrosioides Mexican tea Exotic Amaranthaceae SRWC Chamaesyce hypericifolia Graceful Sandmat Native Euphorbiaceae SRWC Cirsium horridulum Purple thistle Native Asteraceae SRWC, CM Cicuta maculata Spotted Water Hemlock Native Apiaceae NA Conzya canadensis Canadian Horsweed Native Asteraceae SRWC, CM Commelina diffusa Common Dayflower Exotic Commelinaceae SRWC, NA Crotolaria spectabilis Showy Rattlebox Exotic Fabaceae SRWC Cyperus esculentus Yellow Nutsedge Exotic Cyperaceae SRWC, CM Cyperus rotundus Nutgrass Exotic Cyperaceae SRWC Dichanthelium commutatum Variable Witchgrass Native Poaceae NA Drymaria cordata I ndian Chickweed Native Caryophyllaceae NA Eclipta alba False Daisy Native Asteraceae NA Eleusine indica Indian goosegrass Exotic Poaceae SRWC Emilia fosbergii Florida tasselflower Exotic Asteraceae SRWC Erechtites hieraciifolius American Burnweed Native Asteraceae NA Eupatorium capillifolium Dogfennel Native Asteraceae SRWC, NA, CM Galium tinctorum Stiff Marsh Bedstraw Native Rubiaceae NA Table A-1 Continued

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61 Herbs Scientific Name Common Name Nativity Family Sites Geranium carolinianum Carolina Geranium Native Geraniaceae SRWC Gnaphalium falcatum Cudweed Native Asteraceae SRWC Habenaria repens Waterspider False Reinorchid Native Orchidaceae NA Heterotheca subaxillaris Camphorweed Native Asteraceae SRWC Hypoxis juncea Fringed Yellow Stargrass Native Hypoxidaceae NA Hydrocotyle umbellata Marshpennywort Native Araliaceae NA Imperata cylindrical Cogongrass Exotic Poaceae SRWC, CM Indigofera hirsuta Hairy Indigo Exotic Fabaceae SRWC Lactuca graminifolia Michx. Grassleaf Lettuce Native Asteraceae SRWC Lepidium virginicum Virginia Pepperweed Native Brassicaceae SRWC Lycopus americanus American waterhorehound Native Lamiaceae NA Medicago lupulina Black medick Exotic Fabaceae SRWC, CM Melothria pendula Creeping Cucumber Native Cucurbitaceae NA Oplismensus hirtellus Basketgrass Native Poaceae NA Oxalis corniculata Yellow Wood Sorrel Native Oxalidaceae SRWC, NA, CM Parietaria floridana Florida pellitory Native Urticaceae NA Passiflora incarnate Purple Passionflower Native Passifloraceae SRWC Phytolacca americana American Pokeweed Native Phytolaccaceae SRWC Physalis pruinosa Ground Cherry Native Solanaceae SRWC Ptilimnium capillaceum Herbwilliam Native Apiaceae SRWC, NA Richardia brasiliensis Mexican clover Exotic Rubiaceae SRWC Sanicula canadensis Canadian Blacksnakeroot Native Apiaceae NA Samolus ebracteatus Water pimpernel Native Primulaceae NA Salvia lyrata Lyre leaf sage Native Lamiaceae NA

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62 Table A-1 Continued Herbs Scientific Name Common Name Nativity Family Sites Sesbania exaltata Hemp sebania Native Fabaceae SRWC Senecio vulgaris Common groundsel Exotic Asteraceae NA Sesbania virgata Wand riverhemp Exotic Fabaceae SRWC Sonchus asper Spiny sow thistle Exotic Asteraceae SRWC, CM Striga gesnerioides Cowpea witchweed Exotic Orobanchaceae SRWC Thelypteris kunthii Southern shield fern Native Thelypteridaceae NA Triodanis perfiolata Clasping Venus's Lookingglass Native Campanulaceae SRWC Vicia ludoviciana Deerpea Vetch Native Fabaceae NA Viola sororia Common Blue Violet Native Violaceae NA Unk NA1 Asteraceae NA Unk NA 2 Carex Cyperaceae NA Unk NA 3 Ipomoea Convolvulaceae NA Unk NA 4 Orchidaceae NA Unk NA 5 Rorippa Brassicaceae NA Unk NA 6 Solanum Solanaceae NA Unk NA 7 NA Unk SRWC 1 Euphorbiaceae SRWC Unk SRWC 2 Fabaceae SRWC Unk SRWC 3 Poaceae SRWC Unk SRWC 4 Poaceae SRWC Unk SRWC 5 SRWC Unk SRWC 6 SRWC Unk SRWC 7 SRWC Unk SRWC 8 SRWC

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63 Table A-2 Name and nativity of woody species on all sites: sh ort rotation woody crop (SRWC), natural area (NA), and cogonmash (CM). Shrubs Scientific Common Nativity Family Sites Acer rubrum Red Maple Native Sapindaceae NA Ampelopsis arborea Peppervine Native Vitaceae NA Apios americana Groundnut Native Fabaceae NA Baccharis halimifolia Saltbush/Groundsel Tree Native Asteraceae SRWC, NA, CM Carpinus caroliniana American Hornbeam Native Betulaceae NA Campsis radicans Trumpetcreeper Native Bignoniaceae NA Celtis laevigata Sugarberry Native Celtidaceae NA Cephalanthus occidentalis Buttonbush Native Rubiaceae NA Clematis crispa Swamp Leatherflower Native Ranunculaceae NA Cornus foemenia Swamp dogwood Native Cornaceae NA Fraxinus caroliniana Pop Ash Native Oleaceae NA Hyptis mutabilis Tropical Bushmint Exotic Lamiaceae NA Itea virginica Virginia Sweetspire Native Iteaceae NA Lantana camara Lantana Exotic Verbenaceae NA Liquidambar styraciflua Sweetgum Native Altingiaceae NA Ludwigia peruviana Peruvian Primrose Willow Exotic Onagraceae SRWC, NA Morus rubra Red Mulberry Native Moraceae NA Myrica cerifera Wax Myrtle Native Myricaceae NA Parthenocissus quinquefolia Virginia Creeper Native Vitaceae NA Quercus laurifolia Laurel Oak Native Fagaceae NA Quercus nigra Water Oak Native Fagaceae NA Quercus virginiana Live Oak Native Fagaceae NA Rubus argutus Sawtooth Blackberry Native Rosaceae NA Sambucus canadensis Elderberry Native Adoxaceae SRWC, NA Sabal minor Dwarf Palmetto Native Arecaceae NA Sabal palmetto Cabbage Palm Native Arecaceae NA Serenoa repens Saw Palmetto Native Arecaceae NA Smilax auriculata Earleaf Greenbriar Native Smilaceae NA Toxicodendrons radicans Poison Ivy Native Anacardiaceae NA Ulmus americana American Elm Native Ulmaceae NA Urena lobata Caesarweed Exotic Malvaceae NA Vitis rotundifolia Muscadine Native Vitaceae NA

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64 Table A-3 Name and nativity of a ll trees found in the Natural Area. Table A-4 September 2005 SRWC herbaceous ve getation variables: TSC (total species cover), F (frequency), TPCC (total pl ant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Aeschynomene indica 22 7.7 2.2 73.5 103.2 Ambrosia artemissiifolia 3 18.9 2.0 100.3 80.1 Chamaesyce hypericifolia 2 1.0 2.0 76.6 64.7 Commelina diffusa 1 2.5 1.0 68.8 62.0 Crotolaria spectabilis 8 7.4 1.5 75.9 60.5 Cyperus esculentus 7 5.0 1.9 93.6 93.3 Cyperus rotundus 1 0.5 2.0 86.0 60.6 Eleusine indica 4 5.3 1.5 98.9 64.2 Emilia fosbergii 1 0.5 1.0 94.0 30.5 Eupatorium capillifolium 3 3.3 1.7 43.8 79.0 Imperata cylindrica 14 14.1 2.5 88.7 107.5 Indigofera hirsuta 41 53.9 3.4 75.3 213.6 Passiflora incarnata 11 11.3 1.8 74.1 92.0 Phytolacca americana 1 12.5 2.0 94.0 68.3 Physalis pruinosa 2 8.8 2.0 94.5 67.3 Richardia brasiliensis 2 0.5 1.5 21.8 116.3 Sesbania exaltata 1 17.5 1.0 56.5 92.7 Sesbania virgata 3 19.2 1.0 100.2 68.9 Sonchus asper 3 7.5 1.0 48.7 72.0 Striga gesnerioides 5 7.2 1.4 96.8 60.2 Unk SRWC1 3 0.5 1.0 85.7 32.2 Unk SRWC2 1 7.5 2.0 95.5 69.4 Unk SRWC3 1 2.5 1.0 76.0 33.8 Unk SRWC 6 1 2.5 1.0 85.0 40.1 Unk SRWC 7 1 7.5 3.0 87.0 97.4 Trees Scientific Name Common Persimmon Nativity Family Acer rubrum Red Maple Native Sapindaceae Carpinus caroliniana American Hornbeam Native Betulaceae Carya glabra Pignut Hickory Native Juglandaceae Celtis laevigata Sugarberry Native Celtidaceae Citrus aurantium Sour Orange Exotic Rutaceae Diospyros virginiana Common Persimmon Native Ebenaceae Liquidambar styraciflua Sweetgum Native Altingiaceae Quercus laurifolia Laurel Oak Native Fagaceae Quercus nigra Water Oak Native Fagaceae Quercus virginana Live Oak Native Fagaceae Sabal palmetto Cabbage Palm Native Arecaceae Taxodium distichum Bald Cypress Native Cupressaceae Ulmus americana American Elm Native Ulmaceae

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65 Table A-5 March 2006 SRWC herbaceous vege tation variables: TSC (total species cover), F (frequency), TPCC (total pl ant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Ambrosia artemissiifolia 11 8.9 1.8 55.1 82.6 Boehmaria cylindrica 1 85.0 2.0 91.0 286.0 Chamaesyce hypericifolia 7 1.9 1.9 57.2 69.6 Conzya canadensis 37 1.5 2.5 29.2 94.5 Cyperus esculentus 7 1.3 1.6 30.6 56.8 Emilia fosbergii 2 0.5 1.0 14.2 33.8 Eupatorium capillifolium 19 1.3 1.9 19.2 73.0 Geranium carolinianum 1 0.5 1.0 11.0 33.9 Gnaphalium falcatum 23 9.0 2.4 25.9 120.2 Imperata cylindrica 16 22.3 2.6 36.1 138.2 Lactuca graminifolia 18 3.9 2.0 35.7 76.4 Medicago lupulina 1 10.0 2.0 61.0 83.9 Oxalis corniculata 11 1.1 1.6 28.5 59.5 Passiflora incarnata 15 2.3 2.0 41.1 83.2 Phytolacca americana 2 2.0 1.5 33.7 56.4 Ptilimnium capillaceum 5 2.0 2.0 56.3 82.5 Richardia brasiliensis 4 4.0 1.3 36.4 61.4 Sonchus asper 37 3.0 2.9 28.3 125.0 Triodanis perfiolata 2 0.5 1.0 10.1 38.4 Unk SRWC 4 2 1.5 1.0 31.2 47.0 Unk SRWC 8 2 2.5 2.0 15.6 79.4 Table A-6 May 2006 SRWC herbaceous vegetation variables: TSC (total species cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Ambrosia artemissiifolia 11 7.6 1.5 52.0 64.0 Aster elliottii 1 2.5 1.0 8.0 63.9 Boehmaria cylindrica 2 38.1 2.0 46.6 189.1 Chamaesyce hypericifolia 4 9.1 2.8 57.8 101.7 Cirsium horridulum 1 2.5 1.0 5.5 95.5 Conzya canadensis 38 2.3 2.6 28.6 102.6 Cyperus esculentus 5 1.3 1.2 51.5 39.1 Emilia fosbergii 3 1.2 1.3 7.7 61.3 Eupatorium capillifolium 27 1.3 1.9 24.0 84.8 Gnaphalium falcatum 20 9.6 2.2 27.2 115.7 Heterotheca subaxillaris 6 4.7 1.2 46.5 57.9 Imperata cylindrica 14 24.9 2.8 37.6 159.1 Lactuca graminifolia 26 3.5 1.9 25.6 75.8 Lepidium virginicum 1 0.5 1.0 58.0 28.4 Oxalis corniculata 8 2.6 1.8 24.0 68.1 Passiflora incarnata 16 3.3 2.0 40.6 78.8 Phytolacca americana 2 9.5 1.5 29.5 83.4 Ptilimnium capillaceum 4 1.3 1.8 35.7 87.5 Richardia brasiliensis 5 3.7 2.4 51.1 86.8 Sonchus asper 20 0.9 1.9 20.6 87.8 Unk SRWC 5 3 0.5 1.3 4.7 60.9

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66 Table A-7 May 2006 NA herbaceous vegetation va riables: TSC (total species cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Boehmaria cylindrica 5 1.1 1.2 23.5 78.9 Carex albolutescens 1 0.5 1.0 154.5 52.2 Cicuta maculata 1 85.0 1.0 154.5 123.7 Dicanthelium commutatum 3 3.7 1.7 71.3 103.6 Drymaria cordata 1 0.5 1.0 154.5 52.2 Eclipta alba 1 0.5 1.0 7.0 69.6 Erechtites hieraciifolius 2 0.5 1.0 29.5 61.2 Eupatorium capillifolium 2 0.5 1.0 29.5 61.2 Galium tinctorum 1 0.5 1.0 154.5 54.1 Hypoxis juncea 1 0.5 1.0 52.0 52.8 Hydrocotyle umbellata 4 10.3 1.3 64.4 125.0 Lycopus americana 1 0.5 1.0 31.5 54.2 Melothria pendula 1 0.5 1.0 7.5 64.1 Oplismensus hirtellus 2 0.5 1.5 87.0 94.4 Oxalis corniculata 1 0.5 2.0 52.0 104.6 Parietaria floridana 1 0.5 1.0 154.5 52.2 Ptilimnium capillaceum 2 1.0 1.5 29.5 94.3 Samolus ebracteatus 1 2.5 1.0 31.5 83.9 Salvia lyrata 2 1.5 1.0 81.0 78.9 Thelypteris kunthii 3 27.5 1.0 68.5 113.3 Vicia ludoviciana 2 0.5 1.5 103.3 77.5 Viola sororia 2 1.0 1.5 19.5 103.8 Unk NA2 3 8.5 1.3 68.5 103.4 Unk NA6 1 0.5 1.0 7.5 64.1

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67 Table A-8 March 2006 NA herbaceous vegetation va riables: TSC (total species cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance value index). Species TSCF TPCCIVI Boehmaria cylindrica 51.1 1.223.5 78.7 Carex albolutescens 10.5 1.0154.5 52.2 Cicuta maculata 185.0 1.0154.5 123.7 Dicanthelium commutatum 33.7 1.771.3 103.3 Drymaria cordata 10.5 1.0154.5 52.2 Eclipta alba 10.5 1.07.0 69.6 Erechtites hieraciifolius 20.5 1.029.5 61.1 Eupatorium capillifolium 20.5 1.029.5 61.1 Galium tinctorum 10.5 1.0154.5 54.1 Hypoxis juncea 10.5 1.052.0 52.5 Hydrocotyle umbellata 410.3 1.364.4 126.9 Lycopus americana 10.5 1.031.5 54.4 Melothria pendula 10.5 1.07.5 64.1 Oplismensus hirtellus 20.5 1.587.0 94.4 Oxalis corniculata 10.5 2.052.0 104.0 Parietaria floridana 10.5 1.0154.5 52.2 Ptilimnium capillaceum 21.0 1.529.5 94.1 Samolus ebracteatus 12.5 1.031.5 85.7 Salvia lyrata 21.5 1.081.0 78.9 Thelypteris kunthii 327.5 1.068.5 113.4 Vicia ludoviciana 20.5 1.5103.3 77.3 Viola sororia 21.0 1.519.5 103.8 Unk NA2 38.5 1.368.5 101.3 Unk NA6 10.5 1.07.5 64.1

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68 Table A-9 September 2006 NA herbaceous vege tation variables: TSC (total species cover), F (frequency), TPCC (total pl ant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Boehmaria cylindrica 2 1.5 1.0 25.0 67.6 Cicuta maculata 2 20.0 1.0 47.8 99.8 Commelina diffusa 1 0.5 1.0 27.0 54.0 Dicanthelium commutatum 4 2.4 1.3 27.4 89.1 Drymaria cordata 1 2.5 1.0 68.5 78.6 Habenaria repens 1 0.5 1.0 68.5 53.9 Hydrocotyle umbellata 5 1.3 1.2 18.2 103.7 Melothria pendula 2 1.5 1.0 47.8 55.4 Oplismensus hirtellus 3 2.5 1.0 39.5 74.1 Parietaria floridana 2 0.5 1.0 7.0 80.7 Sambucus canadensis 1 2.5 1.0 12.0 88.7 Thelypteris kunthii 4 11.3 1.0 32.6 96.4 Viola sororia 2 1.5 1.0 19.5 62.4 Unk NA1 1 0.5 1.0 12.0 61.3 Unk NA2 2 2.5 1.0 47.8 59.1 Unk NA3 1 0.5 1.0 12.0 57.7 Unk NA4 1 0.5 1.0 68.5 53.9 Unk NA5 1 0.5 1.0 27.0 58.2 Unk NA7 1 0.5 1.0 27.0 54.0 Table A-10 March 2006 CM herbaceous vegetation variables: TSC (tot al species cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Cirsium horridulum 1 17.5 1.0 25.5 101.2 Eupatorium capillifolium 2 2.0 1.5 14.0 77.8 Imperata cylindrica 2 0.5 3.5 14.0 117.8 Oxalis corniculata 2 1.5 1.0 14.0 49.5 Sonchus asper 1 2.5 1.0 25.5 42.3 Table A-11 May 2006 CM herbaceo us vegetation variables: TS C (total species cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Ambrosia artemissiifolia 1 0.5 1.0 8.5 30.8 Cirsium horridulum 1 17.5 1.0 24.3 98.2 Conzya canadensis 1 2.5 1.0 8.5 54.3 Cyperus esculentus 1 0.5 1.0 8.5 30.8 Eupatorium capillifolium 2 3.4 2.5 16.4 79.9 Imperata cylindrica 2 0.5 5.0 16.4 142.7 Medicago lupulina 1 0.5 1.0 24.3 28.3 Oxalis corniculata 2 1.5 1.0 16.4 33.6 Sonchus asper 1 0.5 1.0 24.3 28.3

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69 Table A-12 September 2005 NA wo ody species vegetation variab les: TSC (total species cover), F (frequency), TPCC (total pl ant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Acer rubrum 2 2.5 1.5 85.0 91.4 Apios americana 1 0.5 1.0 112.5 52.9 Baccharis halimifolia 3 23.3 1.3 103.7 98.0 Carpinus caroliniana 2 32.5 1.0 83.0 84.1 Campsis radicans 2 1.5 1.0 116.0 55.6 Celtis laevigata 2 10.0 1.0 116.0 60.6 Cepahalanthus occidentalis 1 0.5 1.0 108.5 50.5 Clematis crispa 3 6.5 1.3 114.8 79.8 Hyptis mutabilis 2 2.5 1.0 99.3 59.3 Itea virginica 1 17.5 1.0 108.5 150.7 Liquidambar styraciflua 1 7.5 1.0 112.5 59.2 Ludwigia peruviana 2 20.0 1.0 85.0 100.6 Parthenocissus quinquefolia 1 0.5 2.0 141.0 102.4 Quercus laurifolia 2 1.0 1.5 126.8 84.4 Quercus nigra 2 5.0 1.0 99.8 54.8 Quercus virginiana 1 2.5 1.0 112.5 59.7 Rubus argutus 2 1.5 1.0 126.8 58.6 Sambucus canadensis 1 17.5 1.0 141.0 66.6 Sabal minor 3 14.2 1.0 102.3 71.8 Sabal palmetto 1 7.5 1.0 91.0 58.2 Serenoa repens 1 37.5 1.0 91.0 115.2 Smilax auriculata 1 2.5 1.0 57.5 79.3 Ulmus americana 4 15.3 1.5 83.5 138.3 Urena lobata 3 29.7 1.3 114.8 132.1 Vitis rotundifolia 1 0.5 2.0 141.0 102.4

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70 Table A-13 March 2006 NA woody sp ecies vegetation variables: TSC (total species cover), F (frequency), TPCC (total pl ant canopy cover), and IVI (importance value index). Species TSC F TPCC IVI Acer rubrum 3 11.3 1.7 87.5 107.6 Ampelopsis arborea 4 1.0 1.0 94.9 56.4 Apios americana 1 7.5 1.0 90.5 66.6 Baccharis halimifolia 3 39.8 1.7 89.5 143.5 Carpinus caroliniana 4 25.0 1.5 111.5 104.2 Campsis radicans 2 0.5 1.0 75.8 58.0 Celtis laevigata 1 9.0 2.0 117.0 108.8 Cephalanthus occidentalis 1 2.5 1.0 111.0 57.3 Clematis crispa 2 6.3 1.5 103.8 89.2 Cornus foemenia 1 37.5 1.0 111.0 93.8 Fraxinus caroliniana 1 2.5 1.0 61.0 58.4 Itea virginica 1 7.5 1.0 111.0 96.8 Lantana camara 1 0.5 1.0 117.0 51.5 Liquidambar styraciflua 1 7.5 1.0 90.5 60.0 Ludwigia peruviana 2 5.0 1.0 75.8 72.2 Morus rubra 1 0.5 1.0 137.0 52.3 Myrica cerifera 1 2.5 1.0 111.0 57.3 Parthenocissus quinquefolia 1 1.5 2.0 117.0 103.4 Quercus laurifolia 3 1.5 1.7 106.2 88.3 Quercus nigra 2 5.0 1.0 103.8 57.9 Quercus virginiana 2 10.0 1.0 127.0 58.9 Rubus argutus 2 1.5 1.0 103.8 54.8 Sambucus canadensis 1 0.5 1.0 90.5 52.2 Sabal palmetto 1 37.5 1.0 137.0 79.3 Serenoa repens 1 17.5 1.0 137.0 62.8 Smilax auriculata 3 1.2 1.0 105.0 54.5 Toxicodendrons radicans 4 2.0 1.0 113.9 59.4 Ulmus americana 3 18.3 1.7 58.8 165.3 Urena lobata 4 4.6 1.3 120.4 100.9 Vitis rotundifolia 1 2.5 1.0 117.0 55.3

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71 Table A-14 May 2006 NA woody species vegetation variables: TS C (total species cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance value index). Species N TSC F TPCC IVI Acer rubrum 3 11.3 1.7 81.2 108.7 Ampelopsis arborea 4 1.0 1.0 90.4 56.4 Apios americana 1 7.5 1.0 90.0 66.7 Baccharis halimifolia 3 39.8 1.7 87.2 153.3 Carpinus caroliniana 3 17.2 1.3 90.3 93.0 Campsis radicans 2 0.5 1.0 71.8 58.1 Celtis laevigata 1 9.0 2.0 118.0 108.5 Cephalanthus occidentalis 1 2.5 1.0 100.0 57.5 Clematis crispa 2 6.3 1.5 104.0 88.7 Cornus foemenia 1 37.5 1.0 100.0 97.5 Fraxinus caroliniana 1 2.5 1.0 53.5 59.0 Itea virginica 1 7.5 1.0 100.0 97.5 Lantana camara 1 0.5 1.0 118.0 51.3 Liquidambar styraciflua 1 7.5 1.0 90.0 60.0 Ludwigia peruviana 1 2.5 1.0 90.0 56.1 Morus rubra 1 0.5 1.0 117.5 54.0 Myrica cerifera 1 2.5 1.0 100.0 57.5 Parthenocissus quinquefolia 1 2.5 2.0 118.0 104.9 Quercus laurifolia 4 1.3 1.3 106.5 66.5 Quercus nigra 2 5.0 1.0 104.0 57.9 Quercus virginiana 2 10.0 1.0 117.8 60.8 Rubus argutus 2 1.5 1.0 104.0 54.5 Sambucus canadensis 1 0.5 1.0 90.0 52.2 Sabal palmetto 1 37.5 1.0 117.5 85.5 Serenoa repens 1 37.5 1.0 117.5 81.9 Smilax auriculata 3 1.2 1.0 96.3 55.6 Toxicodendrons radicans 4 2.0 1.0 106.4 60.1 Ulmus americana 3 16.5 1.7 54.5 166.5 Urena lobata 3 5.7 1.7 108.5 133.9 Vitis rotundifolia 1 2.5 1.0 118.0 54.9

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72 Table A-15 Shrub frequency (%) for all s ites (NA, SRWC, and CM). Frequencies calculated according to total number of plots found within 12 quadrats (NA), 160 (SRWC), and 12 quadrats (CM), respectively. Shrubs NA F SRWC F CM F Acer rubrum 42 Ampelopsis arborea 33 Apios Americana 8 Baccharis hamilifolia 42 42 25 Carpinus caroliniana 42 Campsis radicans 33 Celtis laevigata 25 Cephalanthus occidentalis 17 Clematis crispa 33 Cornus foemenia 8 Fraxinus caroliniana 8 Hyptis mutabilis 17 Itea virginica 8 Lantana camara 8 Liquidambar styraciflua 8 Ludwigia peruviana 25 17 Morus rubra 8 Myrica cerifera 8 Parthenocissus quinquefolia 17 Quercus laurifolia 42 Quercus nigra 33 Quercus virginiana 25 Rubus argutus 17 Sambucus canadensis 17 1 Sabal minor 25 Sabal palmetto 8 Serenoa repens 8 Smilax auriculata 33 Toxicodendrons radicans 33 Ulmus americana 67 Urena lobata 42 Vitis rotundifolia 17

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73 Table A-16 Vegetation variables of all SRWC herbaceous species. Total species cover (TSC), frequency (F) of 4 quadrats, density (D), total plant canopy cover (TPCC), and importance value index (IVI). Species N TSC F D TPCC IVI Aeschynomene indica 22 7.66 2.23 2.60 73.52 103.2 Ambrosia artemissiifolia 25 9.55 1.68 6.95 59.18 74.14 Aster elliottii 1 2.50 1.00 2.00 8.00 63.94 Boehmeria cylindrica 3 53.75 2.00 90.33 61.42 221.4 Chenopodium ambrosioides 11 4.48 2.18 7.83 57.38 81.28 Chamaesyce hypericifolia 2 1.00 2.00 2.75 76.63 64.75 Cirsium horridulum 1 2.50 1.00 1.00 5.50 95.45 Conzya canadensis 75 1.91 2.53 3.16 28.90 98.59 Commelina diffusa 1 2.50 1.00 1.00 68.75 61.97 Crotolaria spectabilis 8 7.42 1.50 1.66 75.94 60.54 Cyperus esculentus 19 2.68 1.58 7.39 59.28 65.6 Cyperus rotundus 1 0.50 2.00 1.50 86.00 60.58 Eleusine indica 4 5.25 1.50 4.17 98.94 64.16 Emilia fosbergii 6 0.83 1.17 1.58 24.23 47.02 Eupatorium capillifolium 49 1.44 1.90 3.17 23.35 79.9 Geranium carolinianum 1 0.50 1.00 1.00 11.00 33.94 Gnaphalium falcatum 43 9.24 2.30 13.53 26.51 118.1 Heterotheca subaxillaris 6 4.67 1.17 1.25 46.50 57.9 Imperata cylindrica 44 20.52 2.61 10.74 53.29 135.1 Indigofera hirsuta 41 53.90 3.39 5.63 75.29 213.6 Lactuca graminifolia Michx. 44 3.67 1.93 6.55 29.73 76.01 Lepidium virginicum 1 0.50 1.00 1.00 58.00 28.43 Medicago lupulina 1 10.00 2.00 10.50 61.00 83.89 Oxalis corniculata 19 1.73 1.68 2.76 26.58 63.13 Passiflora incarnata 42 5.03 1.95 2.80 49.53 83.82 Phytolacca americana 5 7.10 1.60 4.90 44.06 69.56 Physalis pruinosa 2 8.75 2.00 1.00 94.50 67.35 Ptilimnium capillaceum 9 1.69 1.89 6.67 47.14 84.74 Richardia brasiliensis 11 3.20 1.82 3.52 40.41 82.93 Sesbania exaltata 1 17.50 1.00 1.00 56.50 92.74 Sesbania virgata 3 19.17 1.00 1.33 100.17 68.87 Sonchus asper 60 2.48 2.43 3.76 26.78 110 Striga gesnerioides 5 7.20 1.40 3.73 96.75 60.24 Triodanis perfiolata 2 0.50 1.00 1.00 10.05 38.38 Unk SRWC1 3 0.50 1.00 1.00 85.67 32.22 Unk SRWC2 1 7.50 2.00 1.50 95.50 69.39 Unk SRWC3 1 2.50 1.00 1.00 76.00 33.85 Unk SRWC4 4 1.50 1.00 1.75 31.20 47.06 Unk SRWC5 3 0.50 1.33 1.33 4.67 60.94 Unk SRWC6 1 2.50 1.00 1.00 85.00 40.06 Unk SRWC7 1 7.50 3.00 1.00 87.00 97.41 Unk SRWC8 2 2.50 2.00 5.50 15.60 79.44

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74 Table A-17 Vegetation variable s of NA herbaceous species. Total species cover (TSC), standard deviation (SD), total plan t canopy cover (TPCC), and importance value index (IVI). Species N TSC SD TPCC SD IVI SD Boehmaria cylindrica 12 1.2 0.9 24 16 77 20.9 Carex albolutescens 2 0.5 0 155 0 52 0 Cicuta maculata 4 52.5 40.2 101 64 112 32.7 Commelina diffusa 1 0.5 0 27 0 54 0 Dicanthelium commutatum 10 3.2 3.3 54 58 98 37.7 Drymaria cordata 3 1.2 1.2 126 50 61 15.3 Eclipta alba 2 0.5 0 7 0 70 0 Erechtites hieraciifolius 4 0.5 0 30 26 61 9.8 Eupatorium capillifolium 4 0.5 0 30 26 61 9.8 Galium tinctorum 2 0.5 0 155 0 54 0 Habenaria repens 1 0.5 0 69 0 54 0 Hypoxis juncea 2 0.5 0 52 0 53 0.2 Hydrocotyle umbellata 13 6.8 13.7 47 49.8 117 47.2 Lycopus americana 2 0.5 0 32 0 54 0.13 Melothria pendula 4 1 1 28 28.8 60 5.1 Oplismensus hirtellus 7 1.4 1.1 67 62.4 86 18.4 Oxalis corniculata 4 0.5 0 30 0 84 0.4 Parietaria floridana 4 0.5 0 81 85.2 66 20.9 Ptilimnium capillaceum 4 1 0.6 30 26 94 13.9 Samolus ebracteatus 2 2.5 0 32 0 85 1.3 Salvia lyrata 4 1.5 1.2 81 84.9 79 30.8 Sambucus canadensis 1 2.5 0 12 0 89 0 Thelypteris kunthii 10 21 22.9 54 55.0 107 36.7 Vicia ludoviciana 4 0.5 0 103 59.2 77 28.6 Viola sororia 6 1.2 0.8 20 11.7 90 49.2 Unk NA 1 2 0.5 0 7 7.1 81 22.3 Unk NA 2 Carex 8 7 9.6 63 58 92 53.8 Unk NA 3 Ipomoea 1 0.5 0 12 0 58 0 Unk NA 4 1 0.5 0 68.5 0 54 0 Unk NA 5 Rorippa 1 0.5 0 27 0 58 0 Unk NA 6 Solanum 2 0.5 0 8 0 64 0 Unk NA 7 1 .5 0 27 0 54 0

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75 Table A-18 Vegetation variab les of NA woody species. To tal species cover (TSC), standard deviation (SD), total plan t canopy cover (TPCC), and importance value index (IVI). Species N TSC SD TPCC SD IVI SD Acer rubrum 8 9.13 5.77 84.50 24.01 103.97 30.32 Ampelopsis arborea 8 1.00 0.93 92.63 24.41 56.43 4.79 Apios americana 3 5.17 4.04 97.67 12.85 62.08 7.91 Baccharis halimifolia 9 34.33 20.72 93.44 31.11 131.63 45.63 Carpinus caroliniana 9 24.06 20.15 98.11 32.97 96.00 33.75 Campsis radicans 6 0.83 0.82 87.83 30.81 57.26 5.43 Celtis laevigata 4 9.50 6.15 116.75 20.43 84.64 27.91 Cephalanthus occidentalis 3 1.83 1.15 106.50 5.77 55.07 3.99 Clematis crispa 7 6.36 5.60 108.57 19.18 85.02 24.69 Cornus foemenia 2 37.50 0.00 105.50 7.78 95.64 2.63 Fraxinus caroliniana 2 2.50 0.00 57.25 5.30 58.73 0.41 Hyptis mutabilis 2 2.50 0.00 99.25 59.04 59.31 1.82 Itea virginica 3 10.83 5.77 106.50 5.77 115.00 30.96 Lantana camara 2 0.50 0.00 117.50 0.71 51.42 0.11 Liquidambar styraciflua 3 7.50 0.00 97.67 12.85 59.71 0.47 Ludwigia peruviana 5 10.50 15.25 82.30 22.95 80.36 39.59 Morus rubra 2 0.50 0.00 127.25 13.79 53.12 1.23 Myrica cerifera 2 2.50 0.00 105.50 7.78 57.38 0.18 Parthenocissus quinquefolia 3 1.50 1.00 125.33 13.58 103.57 1.22 Quercus laurifolia 9 1.28 0.83 110.89 15.88 77.74 28.30 Quercus nigra 6 5.00 2.74 102.50 13.56 56.88 2.48 Quercus virginiana 5 8.50 8.22 120.40 9.54 59.82 6.86 Rubus argutus 6 1.50 1.10 111.50 19.22 55.97 4.67 Sambucus canadensis 3 6.17 9.81 107.17 29.30 57.01 8.29 Sabal minor 3 14.17 5.77 102.33 42.09 71.77 8.78 Sabal palmetto 3 27.50 17.32 115.17 23.09 74.33 14.28 Serenoa repens 3 30.83 11.55 115.17 23.09 86.63 26.53 Smilax auriculata 7 1.36 1.07 94.50 35.51 58.53 9.26 Toxicodendrons radicans 8 2.00 0.93 110.13 15.94 59.77 4.88 Ulmus americana 10 16.55 6.29 67.40 36.00 154.84 103.08 Urena lobata 10 12.45 18.95 115.15 19.64 120.15 47.69 Vitis rotundifolia 3 1.83 1.15 125.33 13.58 70.88 27.33

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76 APPENDIX B SOILS Table B-1 Pearson correlation coefficients for Populus deltoides growth variables: height at 14 months (H14), 14 mo. diameter at breast height (D14), 14 mo. survival (S14), 14 mo. vigor (V14), basal area per hectare (BAH) and soil variables: organic matter (OM), bulk density (B D) of corresponding slope positions in the SRWC area. H14 D14 S14 V14 BAH OM pH NO3-N P K Ca Mg BD H14 1 0.96* 0.95* -0.72* 0.97* -0.03 0.30 -0.56 0.15 -0.05 -0.03 -0.08 -0.56 D14 1 0.91* -0.61 0.94* -0.01 0.52 -0.51 0.22 0.00 0.04 0.01 -0.31 S14 1 -0.53 0.97* -0.05 0.24 -0.55 -0.04 -0.16 -0.18 -0.23 -0.41 V14 1 -0.68* -0.13 0.01 0.55 -0.34 -0.13 -0.24 -0.18 -0.41 BAH 1 -0.08 0.27 -0.56 0.05 -0.09 -0.08 -0.12 -0.16 OM 1 -0.18 -0.26 0.44 0.31 0.48 0.46 -0.56 pH 1 -0.09 0.43 0.32 0.16 0.20 -0.08 NO3-N 1 -0.38 -0.49 -0.26 -0.24 0.51 P 1 0.89* 0.91* 0.89* -0.21 K 1 0.81* 0.81* -0.26 Ca 1 0.99* -0.08 Mg 1 -0.05 BD 1 Table B-2 Pearson correlation coefficients for Pinus elliottii and Taxodium distichum growth variables: 11 mo. height (H11), 11 mo. vigor (V11), and 11 mo. survival (S11) and soil variables: or ganic matter (OM) and bulk density (BD) of corresponding slope positions in the SRWC area. H11 V11 S11 OM pH NO3-N P K Ca Mg BD H11 1 -0.85* 0.69* 0.47 0.37 -0.08 0.10 0.20 0.10 0.22 -0.49 V11 0.98 1 -0.90* -0.10 -0.58 0.29 0.05 -0.02 -0.04 -0.14 0.09 S11 -0.07 0.14 1 -0.05 0.56 -0.50 0.14 0.13 0.16 0.24 0.08 OM 0.55 0.36 -0.87 1 0.20 0.33 0.26 0.06 0.06 0.13 -0.98* pH 0.91 0.98 0.34 0.16 1 -0.15 0.05 0.14 0.14 0.22 -0.16 NO3-N 0.99 0.99* 0.09 0.41 0.97 1 -0.33 -0.39 -0.27 -0.23 -0.39 P 0.89 0.78 -0.51 0.87 0.63 0.81 1 0.79* 0.92* 0.90* -0.33 K 0.98 0.99* 0.11 0.39 0.97 0.99* 0.80 1 0.82* 0.80* -0.18 Ca 0.38 0.56 0.90 -0.57 0.72 0.52 -0.08 0.54 1 0.98* -0.17 Mg 0.30 0.49 0.93 -0.63 0.67 0.45 -0.16 0.47 1.00 1 -0.25 BD 0.00 0.21 0.99* -0.84 0.41 0.16 -0.45 0.18 0.93 0.95 1 Pinus elliottii correlation coefficients above the diagonal and Taxodium distichum below the diagonal. Coefficients with a are si gnificant at the .05 level.

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77 Table B-3 Pearson correlation coefficients for Eucalyptus amplifolia and Eucalyptus grandis growth variables: Jan. 2006 height (H), vigor (V), and survival (S) and soil variables: organic matter (OM) and bulk density (BD) of corresponding slope positions in the SRWC area. H V S OM pH NO3-N P K Ca Mg BD H 1 -0.93* 0.94* 0.20 0.59* 0.08 -0.26 -0.19 -0.28 -0.30 0 V -0.98* 1 -0.96* -0.03 -0.42 0.13 0.17 0.15 0.20 0.21 -0.14 S 0.96* -0.90* 1 0.12 0.49 0.02 -0.22 -0.20 -0.25 -0.25 0.11 OM -0.28 0.38 -0.04 1 0.63* 0.80* -0.19 0.14 -0.08 -0.13 -0.56* pH -0.09 -0.03 -0.17 0.20 1 0.37 -0.16 -0.23 -0.22 -0.23 -0.52* NO3-N -0.45 0.50 -0.44 -0.32 -0.79 1 -0.37 -0.19 -0.35 -0.38 -0.51* P 0.13 -0.19 0.07 -0.10 0.26 -0.30 1 0.70* 0.91* 0.92* 0.03 K 0.82 -0.81 0.79 -0.18 0.06 -0.46 -0.38 1 0.88* 0.83* 0.03 Ca -0.08 0.03 -0.08 0.24 0.49 -0.46 0.92* -0.47 1 0.99* 0.10 Mg -0.26 0.32 -0.17 0.20 -0.34 0.32 0.66 -0.74 0.61 1 0.12 BD 0.16 0.00 0.41 0.74 -0.34 -0.09 0.08 -0.03 0.17 0.49 1 Eucalyptus grandis correlation coefficients above and Eucalyptus amplifolia coefficients below the diagonal. Coefficients with a are significant at the .05 level.

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78 APPENDIX C COGONMASH Methods The cogonmash (CM) is located on th e property of the Department of Environmental Protection in Homeland, Flor ida. Cogongrass was continuously growing for five years, reaching 2m in height, on consolidated waste phosphatic clays from a 1970s reclamation project. The entire CM area, which entails mashing cogongrass with medium sized John Deere farm tractor wheels in August of 2005, is 1.2 ha. Only 318 m2 were used in this research, however. The area was sprayed at three weeks post mashing and again at six weeks with 6% glyphosate at 2.4 L/ha. Experimental Design The CM area consisted of 318 m2 rectangular plot with two transects, six plots on each transect, 8m apart. The site contained two elevations. Six plots were placed at the greater elevation and six at th e lower elevation, three on ea ch transect (Figure C-1). Vegetation surveys were performed in Marc h and May 2006. The CM site had 12 24 cm deep soil cores taken in the winter. Four cogonmash samples were combined to make four composite samples; samples were combin ed based on their north or south orientation in the two transects. Soils were analyzed in the lab usi ng the same methodology as the SRWC and the NA sites.

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79 6 m53m 1x1m herbaceous plot Soil core Figure C-1 Cogonmash vegetation and soil core plot design. Analyses CM Model Yij = i + j + ( )ij + ij (C-1) i = the effect of the ith transect j = the effect of the kth plot ( )ij= the effect of the kth plot nested within the ith transect ij = experimental error Analysis of variance was run for the CM model (C-1) with transects and plots being two main factors. An IVI was calculated as the sum of relative cover, relative frequency (RF), and relative density (RD). Relative cover is the ratio of total cover of one species to the total cover of all species. RF is the ratio of the frequency of one species to the frequency of all species. RD is the ratio of the number of individuals of one species to the total number of individuals of all species. The diversity indices were calculated acco rding to equations 3-4, 3-5, and 3-6. Results and Discussion Objective 2 Cultural treatments The cogonmash treatment at the CM site had the least cogongrass cover of all treatments. The cogonmash had .5% cover of co gongrass, even less than the 2% cover in

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80 the mulch treatment in the SRWC site. In cluding cogongrass, there were 9 herbaceous species; all were properly identified. All the species observed in the CM were also present in the SRWC area. CM, to date, is the most effective method to control cogongrass; though multiple applications may be required. The CM study area had the least TPCC. However, treatment applicati on of the CM area and the SRWC area were applied at different times within the year which may have an effect on the present vegetation. The CM study began in Sept. 2005 and the SRWC study in Feb. 2005. More time is needed before recommendations can be made about the effectiveness of the CM treatment. Objective 3 Native species colonization Herbaceous plants Of the 9 species present in the CM site, fi ve were native species. With time, native species diversity will increase and exotic sp ecies numbers will be phased out slowly. Both native and exotic species colonize in the beginning of ve getation succession. However, native species dominate in the late r stages (Prach and Pysek 2001; Wang et al. 2004), and the number of exotic species decreas es with the increasing age of the stand. Table C-1 Analysis of variance for herbs and shrubs in the Cogonmash (CM) site. Values with a differ at the .05 leve l. Transect (T) and quadrat (Q). CM Herbs Transect 0.3055 Quadrat 0.2064 Q(T) <0.0001*

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81 Table C-2 Ten greatest IVI and TSC (%) valu es of herbs and shrubs for the CM site. CM Herbs IVI TSCShrubs IVI TSC Imperata cylindrical 130 .5 Baccharis halimifolia 34 .5 Cirsium horridulum 100 18 Eupatorium capillifolium 79 3 Conzya canadensis 54 3 Oxalis corniculata 42 2 Sonchus asper 35 2 Ambrosia artemisiifolia 31 .5 Cyperus esculentus 31 .5 Medicago lupulina 28 .5 Shrubs There were no differences in the CM area. There was only a single shrub species present in the CM, saltbush (Table C-2), and it was f ound in 3 of the 12 plots. Species Diversity and Site Similarity The CM and SRWC were most similar to one another out of the three sites (Table 4-13). The CM and SRWC had an herb Ja ccard community similarity index of 0.2 (Table 4-14). Conditions are similar between the CM and SRWC sites: light is abundant, nutrients are high, and pH is nearly neutra l, which could lend to similar vegetational communities. Again, the shrubs of the CM and the SRWC were most similar to one another, being that these are both mainly mont morillonite soils and their soils contain an abundance of cogongrass rhizomes. Objective 4 Soil properties Soil pH (p=0.0066), Ca (p=0.0097), and Mg (p=0.0250) differed between transects (Table C-3). Likewise, also differed between transects. Ca was lower on the western transect than the eastern transect. Mg was also lower in the west ern transect than the eastern transect. The only differences among quadrats were found in NO3-N. It is possible that nutrients had leached from the more elevated quadrats, slopes ranging from

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82 1 to 5% on these Arent soil series (US Dept. of Ag, Soil Conservation Service 1990). NO3 is a negatively charged mineral and does not readily bond to the negatively charged monmorillonite clay; nitrate is easily leach ed (Campbell et al. 1999). Great differences between nutrients are likely due to a small sample size than anything else. However Arent soils lack fertility (U S Dept. of Ag, Soil Conserva tion Service 1990), which may contribute to such low macronut rient levels. Arent soils have no orderly soil profile sequence and the water table is within 133 cm of the surface throughout 6 months of the year (US Dept. of Ag, Soil Conservation Se rvice 1990). BD values were similar to SRWC BD values which could be attributed to the natural shrinking and swelling pattern of the clay soils. SOM was lower than the SRWC area and the pH was higher. This more alkaline pH in the CM site could explain why the SOM is lower. The pH might be more alkaline because there was less canopy cover in the CM s ite and less plant material contributing to SOM. SOM was confined to the top layer of the soil in the CM site, likely from the decomposing cogongrass mash. This has been seen before in the surface soil of a Philippine cogongrass grassland, where SOM was obvious only in the surface soil and decreased rapidly with depth (Snelder 2001). The shrinking and swelli ng nature of clay aids in the translocation of SOM. During the dry season, litter enters the cracks in the clay. Upon arrival of the wet season, water moves the SOM into the cracks. Both SOM and litter are trapped in the soil profile af ter clay expansion. Without shrinking and swelling of clay, SOM in the lower soil prof iles of CSAs would be unlikely (Tamang 2005).

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83 Table C-3 Analysis of variance for all soil variables in the Cogon mash study: transect (T), and quadrat (Q). Values with a are different at the .05 level. Cogonmash T L L(T) OM 0.4719 pH 0.0066* N03 0.0506 P 0.2029 K 0.0787 Ca 0.0097* Mg 0.0250* BD0 0.3041 0.4308 BD1 0.0977 0.3749 L and L(T) were not testable. Table C-4 Means for all soil variables in the Cogonmash site. Surface BD (BD0), subsurface BD (BD1), transect (T), mixed wetland forest (MW), cypress forest (C), SRWC control culture (C), herbicide culture (H), mulch culture (M), native shrub culture (S), and nativ e tree culture (T). Values with the same letter are not different at the .05 level. CogonMash Ave 5.4 6.95 0.603 0.86 4 215 49 2715 879 1 5.7a 6.95a 0.71a 0.89a 7a 158a 76.9a 3226a 1039a 2 5.7a 6.95a 0.65a 0.99a 7a 158a 76.9a 3226a 1039a 3 5.7a 6.95a 0.57a 0.88a 7a 158a 76.9a 3226a 1039a 4 5a 6.95a 0.61a 0.90a 2b 272a 21a 2203a 718a 5 5a 6.95a 0.57a 0.73a 2b 272a 21a 2203a 718a 6 5a 6.95a 0.52a 0.8a 2b 272a 21a 2203a 718a T1 5.3a 7.05a 0.63a 0.80a 3a 168a 83.5a 4098a 1380a T2 5.5a 6.85b 0.57a 0.93a 6a 262a 14.4a 1332b 377b

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84 REFERENCES Abbasi, S.A., and S. Vinithan. 1997. Ec ological impacts of ecualypts myths and realities. Indian Forester 123: 710-739. Akobundu, I.O., U.E. Udensi, D. Chikoye. 2000. Velvetbean ( Mucuna spp.) suppresses speargrass ( Imperata cylindrica (L.) Raeuschel) and increases maize yield. International Journal of Pest management 46: 103-108. Alva, A.K., B. Huant, S. Paramasivam. 2000. Soil pH affects copper fractionation and phytotoxicity. Soil Science of America Journal 64: 955-962. Anonymous. 1996. Imperata management for sm allholders: An extensionists guide to rational Imperata management for smallholders Indonesian Rubber Research Institute, Bogor, Indonesia, and Natural Resources Institute, United Kingdom. 56 pp. Ashagrie, Y., W. Zech, G. Guggenb erger. 2005. Transformation of a Podocarpus falcatus dominated natural forest into a monoculture Eucalyptus globulus plantation at Munesa, Ethiopi a: soil organic C, N, and S dynamics in primary particle and aggregate-size fractions. Agriculture, Ecosystems & Environment 106:89-98. Attenborough, D. 1995. The private life of plants. Princeton University Press. Princeton, New Jersey 08540. Baker, J.B., and W.M. Broadfoot. 1979. A pract ical field method of site evaluation for commercially important southern hard woods. USDA Forest Service, General Technical Report SO-26. Southern Forest Experiment Station, New Orleans, LA. 51 p. Bard, G. E. 1952. Secondary succession on the Piedmont of New Jersey. Ecological Monographs 22: 195-215. Bazzaz, F.A., 1979. The physiological ecology of plant succession. Annual Review of Ecology and Systematics 10: 351-371. Behan, M. 1981. The Missouris stately cottonwoods: How can we save them? Montana Magazine Sept.: 76-77. Bergez, J., D. Auclair, L. Bouvarel. 1989. Fi rst-year growth of hybrid poplar shoots from cutting or coppice origin. Forest Science 35: 1105-1113.

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95 BIOGRAPHICAL SKETCH Life, ironically, began in Gainesville. I spent a few unmemorable years here in east Gainesville and relocated to Naples, Florida, in 1986, where I spent the bulk of my young life. At the age of 15, my family again packed everything up and moved to Lexington, Kentucky, which turned out to be nothing like I anticipated. Here I fell in love with the liberal, horse town and decided to pursue my undergraduate biology degree and swim throughout my four years at th e historical Transylvania University. The summer of my senior year, I had an internship at the Univer sity of Florida, studying invasive plants with Dr. Alison Fox of the Agronomy Department. While there, I explored the different biological departments and met Dr. Donald Rockwood, who was open to the possibility of taking on a new graduate st udent. Within half a year of correspondence with him and acceptable GRE scores and grades, he welcomed me as his graduate student for the fall of 2004. My undergraduate biology degree was pur sued in four unforgettable years and I left my friends and family within a week after my graduation from Transylvania University. I began the next pha se of my life in my birth-town of Gainesville, Florida. I worked at the Florida Natural History Museum, while in graduate school, as an Ichthyology Collections Assistant from Dece mber 2004 until the present. I will be conducting vegetation surveys in northern Washington this summer for the Forest Service.


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PRELIMINARY EVALUATION OF THE USE OF FAST GROWING TREES AND
CULTURES FOR COGONGRASS CONTROL ON PHOSPHATE MINED LANDS














By

ERIN N. MAEHR


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


2006





























Copyright 2006

By

Erin N. Maehr















ACKNOWLEDGMENTS

I would like to thank my committee members (Drs. Donald L. Rockwood, Greg

MacDonald, Nicholas Comerford, and Larry Harris) for their suggestions, valuable time,

critical reviews, and edits of my thesis. A special thank you goes to Dr. Rockwood for his

continuous guidance during data analysis and throughout my stay in the School of Forest

Resources and Conservation. Much appreciation goes to the Florida Institute of

Phosphate Research for funding this project. Another thank you is extended to Charles

Cook, who always came to my aid in plant identification and supplied me with other

useful advice throughout my research.

I am grateful to Analytical Research Lab staff for analyzing my soil samples.

Thanks go to Bijay Tamang, Brian Becker, Valerie Milmore, Jennifer O'Leary, Nick

Gerkin, and Mark Hotchkiss who were always willing to help me in the field despite high

temperatures and missed Gator games.

Thanks go to my family for showing me a better way to look at the world than just

as a commodity and for just being supporters of my life. I would like to thank Jeff Kelly

for his unfaltering faith in my abilities and assuaging any worries I had throughout the

thesis writing process. Without him, I would have struggled through this long and

tedious process. Jessica Kress, I do not know if I would have made it down here in a new

place without thoughtful words, confidence in my abilities, and random cards that made

me smile; your friendship is one that I will cherish the rest of my life. I thank all my

Gainesville friends, Samantha Pink, Jennifer O'Leary, Jen Dupree, Jason Liddle, Gerardo









Celis, Eric Holzmueller, and Rob Robins, for making my stay an enjoyable one and

lasting friendships that will endure for many years to come.
















TABLE OF CONTENTS



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

LIST OF TA BLES .............. .......................................... ....................... vii

LIST OF FIGURES ................................. .. ... .. ..................x

ABSTRACT .............. .......................................... xi

CHAPTER

1 IN TR O D U C TIO N ......................................................................... .... .. ........

2 L ITER A TU R E R E V IEW .................................................................... ....................6

3 M E T H O D S .......................................................................................................1 6

Stu dy A reas.................................................. 16
S R W C ..................................................................................................... 1 6
N atu ral A rea ................................................................2 0
E xperim mental D design .............................................................2 1
S R W C .....................................................................................................2 1
N A ..............................................................................2 3
A nalyses.................................................... 24

4 RESULTS AND DISCUSSION .............................. ..................... 27

Objective 1 Effectiveness of SRW Cs ...................................... .........................27
Objective 2 Cultural Treatm ents............................................. 32
Objective 3 Native Species Colonization .......................................33
H erb ace o u s p lan ts ........................................................................................... 3 3
S h ru b s ................................................... .......................................... ........ ...... 4 3
NA trees...................................................45
Species Diversity and Site Similarity ................................... ............. 46
Objective 4 Soil Properties ............................................................... ..............47
S R W C ............................................................................... 4 8
N A ..............................................................................5 2
C o rre latio n s .................................................................................................... 5 3




v









5 C O N C L U SIO N S ........................ .... .... .................... .. .. ........ .... ... .......55

6 FU TU R E R E SEA R CH .......................................................................... .............58

APPENDIX

A V EG ETA TIO N .................. .............................. ........ .. .......... .............. 60

B S O IL S ...........................................................7 6

C COGONM A SH ..................................................... ............ .. ............ 78

REFERENCES ......................... ........... ...... ................... 84

B IO G R A PH IC A L SK E T C H ...................................................................... ..................95
















LIST OF TABLES


Table page

3-1 Symbols of species, planting date, and propagule type of species in the SRWC
a r e a ........................................................................................ 1 9

3-2 SRWC interplant species and their suitability ......................................................20

3-3 SR W C culture definitions .............................................. .............................. 20

4-1 Analysis of variance for January 2006 tree height, DBH (diameter at breast
height), vigor, and survival of all trees, including borders, in SRWC study. C
(culture), S (species), S*C (species*culture interaction, plot/slope position..........28

4-2 Average tree and shrub height (H, in m), vigor (V), survival (S, %), and DBH (D
in cm) in January 2006 by culture and species (excluding borders) ......................30

4-3 Average height (m) in January 2006 by slope position (1 at top of slope; 4 at
bottom of slope) and species (excluding borders)..................................................31

4-4 Pearson correlation coefficients of all January 2006 height (H) and survival (S)
data for all SRW C trees and soil variables.............. ............................................ 31

4-5 Means for all soil variables in the Natural Area and the Short Rotation Woody
C rop (SR W C ) sites............ ... ...................................... ................ ........ .............. 32

4-6 Analysis of variance for herbs and shrubs in the Short Rotation Woody Crop
(SRWC) and Natureal Area (NA) sites...............................................................36

4-7 Ten greatest IVI and TSC (%) values of herbs and shrubs for each site..................38

4-8 Pearson correlation coefficients of sow thistle and cudweed IVI, TSC, and soil
variables in the SRW C area. ............................................ ............................ 41

4-9 Pearson correlation coefficients for hairy indigo and cogongrass IVI, TSC, and
soil variables in the SRW C area ...................................................... ... .......... 41

4-10 Analysis of variance for cottonwood vegetation variables ....................................42

4-11 Top 5 species with the greatest TSC and IVI values in the cottonwood block.
Values with the same letter are not different at .05 level.......................................43









4-12 Pearson correlation coefficients for Populus deltoides basal area per hectare
(BAH), total plant canopy cover (TPCC), and cogongrass total species cover
(TSC) on a quadrat and slope position basis .............. ...... ... ......................... 43

4-13 Shannon-Weiner diversity index (H') and maximum possible diversity (Hmax)
of all sites for herbs, shrubs, and NA trees..... ..............................47

4-14 Jaccard's community similarity index (Cj) for herbs (H) and shrub species (S) at
a ll site s ................................ ..................................... .......................4 7

4-15 Analysis of variance for the Short rotation woody crop (SRWC) and Natural
A rea soil variables .................. ..................................... .. ............ 49

4-16 Average soil means by slope position ....................................................... 50

A-i Name and nativity of herbaceous species on all sites ............................................60

A-2 Name and nativity of woody species on all sites. ............................................. 63

A-3 Name and nativity of all trees found in the Natural Area. .....................................64

A-4 September 2005 SRWC herbaceous vegetation variables ....................................64

A-5 March 2006 SRWC herbaceous vegetation variables............................................65

A-6 May 2006 SRWC herbaceous vegetation variables ...........................................65

A-7 May 2006 NA herbaceous vegetation variables.....................................................66

A-8 March 2006 NA herbaceous vegetation variables........................................67

A-9 September 2006 NA herbaceous vegetation variables...........................................68

A-10 March 2006 CM herbaceous vegetation variables. ................ .............. 68

A-11 May 2006 CM herbaceous vegetation variables. .............................................. 68

A-12 September 2005 NA woody species vegetation variables ....................................69

A-13 March 2006 NA woody species vegetation variables ...........................................70

A-14 May 2006 NA woody species vegetation variables. ..............................................71

A-15 Shrub frequency (%) for all sites (NA, SRWC, and CM)........................................72

A-16 Vegetation variables of all SRWC herbaceous species.........................................73

A-17 Vegetation variables of NA herbaceous species ............................................... 74









A-18 Vegetation variables of NA woody species .................................. .................75

B-l Pearson correlation coefficients for Populus deltoides growth variables: height
at 14 months (H14), 14 mo. diameter at breast height (D14), 14 mo. survival
(S14), 14 mo. vigor (V14), basal area per hectare (BAH) and soil variables:
organic matter (OM), bulk density (BD) of corresponding slope positions in the
SR W C area. ...........................................................................76

B-2 Pearson correlation coefficients for Pinus elliottii and Taxodium distichum
growth variables: 11 mo. height (H11), 11 mo. vigor (V11), and 11 mo. survival
(S11) and soil variables: organic matter (OM) and bulk density (BD) of
corresponding slope positions in the SRWC area. ..............................................76

B-3 Pearson correlation coefficients for Eucalyptus amplifolia and Eucalyptus
grandis growth variables: Jan. 2006 height (H), vigor (V), and survival (S) and
soil variables: organic matter (OM) and bulk density (BD) of corresponding
slope positions in the SRW C area. ........................................ ........................ 77

C-1 Analysis of variance for herbs and shrubs in the Cogonmash (CM) site.................80

C-2 Ten greatest IVI and TSC (%) values of herbs and shrubs for the CM site.............81

C-3 Analysis of variance for all soil variables in the Cogonmash study: transect (T),
an d qu ad rat (Q )................................................... ................ 8 3

C-4 M eans for all soil variables in the Cogonmash site................................................83
















LIST OF FIGURES


Figure page

3-1 2005 Field layout for SRW C site ...................................... ...................... ........... 17

3-2 Aerial photograph (2005) of the 0.8 ha SRWC site and the Natural Area to the
east ............................................................................... .......... ...... 2 1

3-3 SRW C vegetation and soil core plot design .......................................................23

3-4 Natural area transects with three 10x10m tree plots. .............................................24

3-5 Natural area herb and shrub vegetation and soil sampling design .........................24

4-1 Tree height (m) for SRWCs in January 2006 by culture and species ....................29

4-2 May 2006 Cogongrass TSC for all species, slope positions, and treatments in the
SR W C site. ............................................................................29

4-3 Relation of SOM to cogongrass IVI in the SRWC area............... ................40

4-4 Relation of SOM to hairy indigo IVI in the SRWC area. ............. ..............40

4-5 Stepwise regression (0.15 level) of NA tree BAH as a function of pH by plot.......46

C-l Cogonmash vegetation and soil core plot design. .................................................79














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

PRELIMINARY EVALUATION OF THE USE OF FAST GROWING TREES AND
CULTURES FOR COGONGRASS CONTROL ON PHOSPHATE MINED LANDS

By

Erin N. Maehr

August 2006

Chair: Donald L. Rockwood
Major Department: Forest Resources and Conservation

Cogongrass (Imperata cylindrica) is a threat to the restoration of disturbed lands in

central Florida, especially phosphate-mined lands. Moreover, this invasive exotic lacks

an effective control method. Fast growing trees, such as cottonwood (Populus deltoides),

slash pine (Pinus elliottii), eucalypts (Eucalyptus grandis and E. amplifolia), and bald

cypress (Taxodium distichum), were planted from February to June of 2005 on a clay-

settling area (CSA) at the Polk County Peace River Park (PCPRP) in Florida, to evaluate

their potential as a cogongrass control strategy.

In conjunction with planting short rotation woody crops (SRWCs), five treatments

(control, herbicide, native trees, native shrubs, and mulch) were applied. A sixth

treatment was initiated, mashing of cogongrass (CM), on a 40-year-old CSA less than

1600m from the PCPRP. Vegetation samples were collected in September 2005, March

2006, and May 2006 within the study plots to survey percent coverage and abundance of

shrubs and herbs. Soil samples were also collected to quantify macronutrients (NO3, P,









K, Ca, and Mg), soil organic matter (SOM), bulk density (BD), and pH. The vegetation

and soil of a natural area (NA) in the Polk County Peace River Park were also analyzed

for comparison to the SRWC and the CM site.

At the SRWC site, Jan 2006 height differed among species (p<0.0001), but not,

among treatments (p=0.8601). Populus deltoides diameter at breast height (DBH)

differed among cultures (p<0.0001). Soil pH was significantly different between sites

(p=0.0035). Nitrate differed among sites (p=0.0406).

Both native and exotic species were present in the understory of the 3 sites.

Common herbaceous species in the SRWC area included hairy indigo (Indigofera

hirsuta), horseweed (Conzya canadensis), dogfennel (Eupatorium capillifolium),

cudweed (Gnaphaliumfalcatum), sow thistle (Sonchus asper), and cogongrass. The only

shrub species observed in the SRWC area were saltbush (Baccharis halimifolia),

primrose willow (Ludwigiaperuviana), and elderberry (Sambucus canadensis). There

were a total of 42 herbaceous species observed in the SRWC are, 36 in the Natural area,

and 9 in the CM area. Total plant canopy cover (TPCC) was least in the mulch culture,

22%. Cogongrass had the least cover in the herbicide and mulch cultures of the SRWC

site, less than 2% cover in each culture. Cogongrass and hairy indigo, a common SRWC

herbaceous plant, IVI had no relation to SOM content in the SRWC area. The CM site

had a TPCC of 18% and even less cogongrass cover, .5%, than the mulch treatment in the

SRWC site. In their first year of growth, SRWCs initiate a native plant succession,

provide adequate control over cogongrass, and amend soil conditions. Based on this

study, cogonmashing followed by the planting of fast-growing trees on cogongrass

dominated sites is promising for effective cogongrass control.














CHAPTER 1
INTRODUCTION

Many human-dominated ecosystems are highly stressed and dysfunctional

(Vitousek et al. 1997), including forests that are managed for conservation (Noble &

Dirzo 1997). Ecosystem health is a new field of study that quantifies the condition of an

ecosystem. Biodiversity is one method of measuring ecosystem health (Rapport et al.

1998). Systems unaltered by humans tend to be stable and resilient, but with human

interference natural processes can be disrupted. Before phosphate mining occurred in

central Florida, the land was free of major human-inflicted disturbances. However, after

phosphate extraction, a return to its original conditions is unlikely at best. The

successional stages following mining take approximately 40 years to reach a climax

community depending on ecological conditions (Skousen et al. 1994). Without human

aid, mined lands may forever stay in a disturbed state, especially phosphate mine clay

settling areas (CSAs).

CSAs are a product of the extraction of phosphate ore 4.5-15m below the surface.

Phosphate mining removes the surface (overburden) so that the matrix can be accessed.

The matrix is 3-6m thick and consists of equal parts clay, sand, and phosphate ore.

Draglines remove the matrix and place it in wells that are subjected to high pressure

water guns in order to transform the mixture into a slurry. The sand and phosphate are

separated from the mixture, with clay and water pumped to CSAs. The sand is used to

reclaim the extraction sites and the phosphate ore is further processed. CSAs comprise

40% of phosphate mine sites and retain standing water for 15 years or more. CSAs have









a very high water capacity and the impervious clays make water drainage difficult. In

central Florida, there are 64,700 ha of CSAs (CPI 2003). It was previously thought that

clay settling would take 20 to 30 years or more to dry sufficiently to support mechanized

equipment (Stricker 2000). However, it is possible to employ high flotation tractors with

rotary ditching plows to drain CSAs and speed land reclamation. These methods are

expensive, but provide suitable land for cultivation after 3-5 years (Stricker 2000).

Most phosphate mined areas were previously forested with flatwoods and

hardwood hammock ecosystems. Typical trees species were slash pine, longleaf pine

(Pinuspalustris), and oaks (Quercus sp.). Phosphate mining destroyed native seed

banks, preventing regeneration of these communities. Further, phosphate mine soils are

so atypical for this part of Florida that they are suitable for invasive plant species such as

cogongrass, Brazilian pepper, and natalgrass. Of these, cogongrass is the predominant

species.

Cogongrass invades many disturbed lands, including phosphate mined sites. It is

considered one of the top 10 most invasive plants in the world (Holm et al. 1997) and has

allelopathic effects that deter the growth of surrounding plants. It forms thick,

impenetrable stands that make it physically difficult for other plants to grow. Cogongrass

is found in all southern states east of New Mexico and on all continents except

Antarctica. In Southeast Asia, it is the dominant vegetation on 121 million ha. On a

global scale, it has invaded 200 million ha forest plantations and agricultural lands.

Control efforts for cogongrass generally do not last more than a year multiple

applications are required for effective control. Herbicide has limited success and the

effects are short-lived (MacDonald et al. 2002; Willard et al. 1997). Removal of the









above-ground vegetation is not an effective control method because the grass proliferates

from rhizomes. A control strategy should employ removal of above and below ground

biomass. Eussen (1979) found that cogongrass could be controlled with shade. Fast-

growing exotic species have widely been used in the reforestation of cogongrass

grasslands in Asia. Early and fast growth of these species suppresses cogongrass (Otsamo

et al. 1997).

Short rotation woody crops (SRWCs), such as eucalypts, provide shade that

constrains cogongrass growth (Tamang 2005). Eucalypts also have the potential to

remediate the soil by returning SOM to the earth through leaf and woody debris

decomposition (Bernhard-Reversat and Bouillet 2001). Suggestions for cogongrass

control combine repeated herbicide application with the dense canopy of fast-growing

trees (MacDonald 2004; Ramsey et al. 2003; Shilling et al. 1997).

Florida law mandates that mining companies reclaim areas mined after July 1, 1975

(FL Adminstrative Code Ch62C 17). Wetlands must be reclaimed to at least the same

area prior to mining and at least 10% of upland must be planted with native species.

Since December of 2003, 63% of the land mined since July 1, 1975 has been reclaimed

(DEP 2003). Other agencies are working to reclaim the lands mined before 1975.

CSAs are not often used commercially because of their poor soil structure and

inability to be rapidly altered for building and farming purposes. CSAs do not

voluntarily sustain native Florida plant species. There is little motivation to farm these

areas because CSAs contain toxic elements such as radium and uranium and extremely

poor water drainage. Cogongrass heartily infests many CSAs, creating another obstacle









for reclamation. Therefore, restoration activities on CSAs must control cogongrass

before native plant species can be re-established.

Poorly drained phosphate-mine lands in central Florida are able to support SRWCs

such as cottonwood and eucalypts (Stricker et al. 2000). Fast-growing trees have

numerous environmental benefits such as improved water quality, soil stabilization,

carbon sequestration, and wildlife habitat. Another positive attribute is exotic species

control through the formation of a dense canopy. Eucalypts have been utilized elsewhere

around the world to restore disturbed habitats (Ashagrie et al. 2005; Callisto et al. 2002;

Strauss 2001; Tyynela 2001). Other eucalypt benefits include ability to coppice, which

saves repeated establishment costs.

Fast-growing tree plantations can increase soil organic matter (SOM) via leaf litter,

decrease bulk density (BD) and increase soil porosity via root penetration. From the

inputs of above and below-ground litter, the morphology and chemical conditions of the

soil are affected. Trees promote nutrient cycling and accumulation (Rhoades 1996). The

soil beneath tree canopies store nutrients. Such tree farms can provide habitat for wildlife

and expedite the return of native species.

Eucalypts (Eucalyptus grandis and E. amplifolia), slash pine (Pinus elliottii),

eastern cottonwood (Populus deltoides), and bald cypress (Taxodium distichum) were

planted in a cogongrass monoculture on a CSA at the Polk County Peace River Park, near

Homeland in central Florida in February of 2005. This study began in the fall of 2005

with four objectives:

1. Evaluate the effectiveness of SRWCs in controlling cogongrass.

2. Assess the performance of cultural treatments in preventing the return of
cogongrass.






5


3. Monitor the return of native species in a previously cogongrass infested area.

4. Assess soil properties.

The hypotheses of the study were:

1. The species that grow the quickest are the best cogongrass control agents.

2. Mulch and the cogonmash treatment will provide the best cogongrass control.

3. More native plants will be present in the NA in comparison to the SRWC area.

4. As the fast-growing trees accrue above-ground and below-ground biomass, BD and
pH will decrease and SOM will increase.














CHAPTER 2
LITERATURE REVIEW

Species invasions are not a new evolutionary phenomenon, but their rate of

occurrence has exploded with the spread of humans across the planet (Vitousek et al.

1996). Non-native invasive species have become a global threat to biodiversity.

Australia, Canada, and the U.S. support about 1500 non-indigenous, invasive plant

species and Florida alone harbors approximately 1000 (Vitousek et al. 1996). In some

ecosystems, invasives equal or surpass the number of native plants even though only

0.1% of introduced plant species have become invasive (Williamson and Fitter 1996).

Invasive plants have numerous effects upon ecosystems. Following the

establishment of invasive plant species, native communities experience changes in

species abundance, predator-prey relations, and allelopathy. Depending upon the

invader, soil properties and nutrient concentrations change resource availability and

disturbance regimes can be modified; competition and disease may become problematic

for native residents (Cox 2004). Indigenous species may be displaced and biodiversity

may decline locally and regionally (Cox 2004).

Invasion resistance may be enhanced in communities with high species richness

and diverse functional relations among species (Elton 1958; Lavorel et al. 1999). On the

other hand, a positive feedback mechanism, termed "invasional meltdown" (Cox 2004)

promotes the invasion of other alien species. This can happen when 1) aliens modify

ecosystem dynamics so much that invasions of other alien species are facilitated or 2)









novel species create conditions or provide resources that directly benefit other non-

indigenous plants (Cox 2004).

Moreover, invasive species may become more of an issue as global climate change

alters biotic conditions. Global warming has occurred as atmospheric carbon dioxide and

other greenhouse gases increase in the atmosphere, creating a thermal blanket around the

Earth (Cox 2004). Global climate change appears responsible for altered annual

temperatures and precipitation, longer growing seasons at high latitudes, reduced snow

cover at high latitudes and altitudes, reduced cloud cover in the moist tropics, and an

increased rate of extreme weather (Cox 2004). The growing season has increased by 12

days, between 40 and 750 N, in North America over the past 20 years (Penuelas and

Filella 2001). In conjunction with climate alterations, cogongrass has likely expanded its

distribution.

Invaders seem capable of occupying a diverse array of ecosystems, especially

disturbed areas such as clay settling areas (CSAs) of phosphate mines (MacDonald et al.

2002). Phosphate mining began in 1883 when deposits were found in Alachua County,

Florida. Phosphate mining disturbs 2,000 to 2,500 ha every year in Florida (Ecolmpact

1980; DEP 2003). Florida produces 75% and 25% of the United States and world

phosphate requirements, respectively.

Prior to mining the areas were forested with longleaf pine, slash pine, oak, and

cypress. Phosphate strip mining degraded these landscapes to exotic plant havens. After

mining, the remnant soil was an ideal habitat for invasive exotic plants, like cogongrass,

natalgrass, and purple and yellow nutsedge. Before 1975, phosphate-mined lands could









be abandoned without reclamation. After 1975, however, all disturbed land had to be

reclaimed within four years after mining or as soon as possible (Partney 1998).

Mining drastically alters the soil and vegetation dynamics (Bradshaw 2000). One

way to restore the land is through the improvement of soil fertility and species diversity

(Fang and Peng 1997). Natural succession restores disturbed sites, but this process can

take years and only occurs at locations with nutrient-rich soil and seed sources that come

from natural stands of healthy trees (Bradshaw 2000).

Phosphatic clays are fertile, with macronutrients, and have good water holding

capacity, lessening the need for phosphatic fertilizers and irrigation methods (Stricker et

al. 2003). CSAs typically have a basic soil pH of about 8.0 with high concentrations of

calcium, magnesium, phosphorus, and potassium (Hochmuth et al. 2000). Unlike many

terrestrial disturbed sites, CSAs are difficult for native plants to colonize.

Phosphatic clay is composed of clay particles less than 2 microns in size. The

medium sized fractions of phosphatic clay are made up of apatite while montmorillonite

composes the finer fractions (Stricker 2000). Phosphatic clay soil has a very high water

holding capacity; 12 cm can be supplied to a growing crop, whereas Myakka find sand,

the state soil of Florida, can only hold 5cm. An even lower water holding capacity is

found in Lakeland sand, 3 cm (Stricker 2000). This high water holding capacity lessens

the need for irrigation of planted species.

Cogongrass, tolerant of a variety of environmental conditions, thrives on disturbed

phosphate-mined soils (Jose et al. 2002; Shilling et al. 1997). Rhizomes grow prolifically

10 months a year and secrete an allelopathic substance, which inhibits the growth of

surrounding plants (MacDonald et al. 2002). Cogongrass can accumulate allelochemicals









to phytotoxic levels continually secreting scopolin, scopoletin, and chlorogenic acids

(Inderjit 2001). The allelochemicals inhibit growth, germination, root and shoot length,

fresh and dry weight, and reduce fungal colonies of neighboring plants (Sanchez-

Moreiras et al. 2003). Cogongrass alters fire regimes (Lippincott 1997), a problematic

issue facing global biodiversity (Brooks et al. 2004).

Management options for cogongrass, especially integrated approaches, need to be

further researched (Chikoye 2004). The key to cogongrass control is the destruction of

their rhizomes, which are the major means for perennation and spread (Chikoye 2004).

An option that has been relatively effective in small scale farms is the flattening of

cogongrass. This involves bending the stems at ground level. In Nigeria, farmers bend

the vegetation at the beginning of the rainy season, immediately followed by tillage so

that soil is laid upon the downed stems to keep them flat. Regrowth after mashing is 20-

60% less than the slashing method of control and is also cheaper and faster (Chikoye

2004). Flattening reduces the risk of fire and creates a suitable foundation for cover-

crops (Chikoye 2004). Flattening does not require mechanical machinery, but can be

accomplished using planks, logs, or drums (Friday et al. 1999).

Slashing is another management option, which is followed by burning to

temporarily control cogongrass (Chikoye 2004). However, for this technique to be

effective, slashing has to be repeated at frequent intervals. Soerjani (1970) recommended

an interval of two weeks over a period of three years. Slashing requires considerable

effort and is not feasible for large areas (Brook 1989). Slashing also induces flowering,

which can further spread the weed.









Chemical control can also be effective. Studies have been performed on paraquat,

fluazifop-butyl, glufosinate-ammonia, dalapon, imazapyr, glyphosate, sulfometuron,

nicosulfuron, and rimsulfuron. Some have shown effective control, but repeated

applications are needed (Chikoye 2004). Imazapyr and glyphosate appear to be the most

effective for cogongrass control because the herbicide is translocated to the rhizomatous

portions of the plant (Chikoye 2004).

Grass-effective herbicides are limited (Wrucke and Arnold 1985). Some herbicides

effectively kill cogongrass, but they also kill all other surrounding vegetation

(MacDonald et al. 2002). Fire eliminates above ground vegetation, but due to a high leaf

concentration of silica, cogongrass bur temperatures are too hot for much of the

surrounding native vegetation to return (Jose et al. 2002). When fires are recurrent in the

dry season, they can cause a loss of SOM, degrading the soil in the process (Chikoye

2004). Fire is not an ideal method for cogongrass control because below-ground

rhizomes survive fire (Bryson and Carter 1993). Using select species and succession-

altering processes that place cogongrass at a competitive disadvantage might also control

the weed. Eucalypts and cottonwood are fast-growing trees that have been used as bridge

crops to shade out cogongrass. Besides shielding the cogongrass from the sun, eucalypts

remediate soil conditions (Bernhard-Reversat and Bouillet 2001) for other plants to

establish.

Cogongrass can be controlled in shady environments (Eussen 1979). Cogongrass is

sensitive to shading and usually weakens and dies after exposure to intensive shade.

Plantations have commonly been used for vegetation recovery on mined lands (Reintam

and Kaar 2002) due to their multiple uses. Polycultures are preferred because of their









resistance to pest outbreak (Hartley 2002). Native plant species are favored over exotics

because unforeseen problems might arise from planting an abundance of exotic species.

With the help of fast-growing trees, it may take 8-10 years for cogongrass to decline and

be displaced by natural forest (Dalziel and Hutchinson 1937). Therefore, the use of cover

crops should be an effective method of control. Fallows that produce rapid shading have

repeatedly shown cogongrass suppression (Koch et al 1990; Anon. 1996; Macdicken et

al. 1997; Akobundu et al. 2000; Chikoye et al. 2001). Therefore, fast-growing trees have

potential to be an effective cogongrass control method.

Cogongrass forms monotypic stands through aggressive growth (Eussen 1979) and

sprawling mat-creating rhizomes (Boonitee and Ritdhit 1984). Plants that have

outcompeted cogongrass have a more penetrating root system and/or develop a taller

canopy (Eussen 1979). Cogongrass typically does not invade communities dominated by

native plants. Native plant establishment may depend on a dispersal agent such as birds,

or there may be a minimum age requirement before the plants start producing seeds.

Viability of dispersed seeds may only last a short period of time, also hindering the

possibility of germination. Seeds may only be produced every other year; many variables

can confound the dispersal and establishment of native, neighboring species.

There are two phases of seed dispersal; phase one (primary) pertains to the

movement of the seed from the maternal parent to the ground. Phase two (secondary)

dispersal concerns the subsequent movement of the seed after it has hit the ground.

Secondary phase dispersal includes wind, animals, rain, or water flow (Griffith and

Forseth 2002). Wind dispersal within a forest is improbable due to wind barriers such as









trees (Attenborough 1995. Wind blown species, such as some pines, need to be on the

outer edges of natural areas for wind to carry seeds to the plantation.

The attainment of vegetative climax on mined land takes at least 40 years (Skousen

et al. 1994). Succession is the vegetation change in species composition through time.

After a disturbance, such as phosphate mining, the first species to colonize are those that

exploit bare mineral soil and tolerate full sun. Pioneer species alter the soil conditions

and facilitate the colonization of different species. Cooler soil conditions, increased

SOM, and increased soil moisture make conditions more inhabitable by shade-tolerant

species (Dodson et al. 1998). Succession leads to climax vegetation, an established

community in equilibrium with the climate (Clements 1936). Once new inhabitants cease

the alteration of light intensity patterns and soil moisture, succession ceases (Clements

1936).

Central Florida climatic conditions influence native tree selection. In one study,

green ash (Fraxinuspennsylvanica) had a 98% survival rate, followed by red bay (Persea

borbonia) 90%, sycamore (Platanus occidentalis) 90%, red maple (Acer rubrum) 83%,

and sweetgum (Liquidambar styraciflua) 83% (Best and Erwin 1983). Survival rates in

another study on phosphatic clay soils were sweetgum 66%, tupelo gum 64%, loblolly

pine 63%, and bald cypress 60% (Harrell 1987).

The productivity of understory vegetation is comparable to that of trees (Nilsson

and Wardle 2005). Understory vegetation is often undersampled in ecological studies

and can vary depending on location, season, and plot size (Small and McCarthy 2003).

With increasing stand age, species density and richness increase slowly (Wang et al.

2004). Monoculture tree plantations are associated with the lowest biological diversity









(Kamo et al. 2002). Plantations, in close proximity to natural forests, have high

understory species diversity. Diversity on phosphate mined lands is a function of

distance to the seed source (McClanahan 1986). This ability of plantations to catalyze

secondary succession of native species could allow for the restoration of biodiversity in

degraded lands (Kamo et al. 2002; Parrotta et al. 1997). In an Australian plantation,

species diversity in a 38 to 40-year-old E. cloeziana stand was similar to native eucalypt

forests (Wang et al. 2004). Understory vegetation is highly dependent upon the species

planted, the planting density, and the landscape (Pensa et al. 2004). The first stages of

succession involve native and exotic plant species as colonizers, but native species

dominate in the later stages (Wang et al. 2004). The prevalence of exotic species drops

as the stand ages.

Another determinant of understory vegetation is soil quality. Litter is the primary

source of nutrients in natural systems. Decomposition of litter and plant residues adds

plant essential nutrients to the soil. Increased soil nutrients provide a better habitat where

plant species can thrive. With the growth of trees, SOM increases, which changes the

structure and properties of soil (Singh 1998). Soil organic carbon is added only to the

upper layer (10 cm) in the initial years of plantation establishment (Tolbert et al. 2002).

Eucalyptus and cottonwood are favored for soil reclamation of disturbed lands.

One of the foci of planting fast-growing trees on these sites is to build SOM via the

inputs of above and below-ground biomass. A 45 kg eucalyptus tree may have 17 kg of

roots. The introduction of trees can increase soil organic matter and microbial activity,

decrease soil compaction/BD, decrease soil pH, and increase available nitrogen to plants.

Trees are also capable of remediating the soil and removing toxins (Rockwood et al.









2001). In India, cottonwood was superior to eucalyptus in soil amendments.

Cottonwood produced more N, P, and K than eucalyptus (Singh et al. 1989). Nutrient

quality is greater in cottonwood leaves than the woody tissues. Eucalyptus litter can be

more nutritious through the application of N and P fertilizer; it also increases the total N,

P, K, Ca, and Mg in the litter (Connell and Mendham 2004).

Eucalyptus and cottonwood are both allelopathic. Cottonwood leaves and litter are

abundant in phytotoxic phenols, which have been shown to constrain the germination and

growth of some winter crops in India (Singh et al. 2001). Eucalyptus releases both

volatile and nonvolatile allelochemicals; these chemicals are abundant in the soil beneath

the canopy (Kohli 1998), but with depth, the soil dilutes the allelochemical concentration

(Molina et al. 1991). In southeastern Brazil, an E. grandis plantation had almost the

same number of species as a natural forest, indicating that eucalyptus was not producing

an allelopathic effect in that situation (Da Silva et al. 1995). Managed correctly,

eucalyptus can be an effective instrument in the restoration of disturbed lands.

Eastern cottonwood is the fastest, commercially grown native species in North

America. Eastern cottonwood biomass production is less than eucalypt biomass

production. It has been used in the restoration of strip-mined lands (Brothers 1988). It

has fair value for wildlife including songbirds, upland game birds, fur-bearers and game

mammals (Carey & Gill 1980). Seedling and sapling bark and leaves are consumed by

field mice, rabbits, deer, and domestic livestock (Behan 1981).

The native range of slash pine is from southern South Carolina to central Florida

and west to eastern Louisiana. It is an important timber species in the southeastern

United States, and its wood is excellent for construction purposes (McCune 1988). Slash









pine seeds are consumed by birds and small mammals, and their seedlings are often

browsed by deer and cattle (Lohrey and Kossuth 1990). This pine also provides

sufficient cover and shelter for many species of wildlife (Lohrey and Kossuth 1990).

If soils are properly restored and vegetation established, it is assumed that

reclamation provides functional, self-sustaining, ecosystem (Bloomfield et al. 1982).

However, a successful restoration is not a certain outcome because of uncontrollable

variables such as competition with exotics, atypical alteration in soil nutrients and

establishment conditions (Prober and Thiele 2005). Restoration will take many years to

reach an equilibrated and stable ecosystem. Without further disturbance, this stage could

be reached within a decade. SRWCs are returning native plants to the study site and

cogongrass is, to date, under control. Plant diversity has greatly increased from the

cogongrass monoculture present less than two years ago.














CHAPTER 3
METHODS

Study Areas

Three areas contributed to this study: short rotation woody crops (SRWC), natural

area (NA), and the cogonmash (CM).

SRWC

This study was conducted at Polk County Peace River Park, an inactive CSA in

Homeland, Polk County, FL (Figure 3-1). It is open to the public and is used by

horseback riders and hikers. When abandoned, the land was invaded primarily by

cogongrass (Imperata cylindrica), which grew up to 2m in height. Soil characteristics

vary with elevation and degree of inundation, depressions having high clay content and

elevated areas mostly sand. Approximate pH was 6.5, and there was a considerable

amount (9%) of SOM present. Associated vegetation includes passionflower (Passiflora

incarnata) and occasionally wax myrtle (Myrica cerifera). Wax myrtle has been the

most prevalent species dispersed on CSAs in central Florida (McClanahan and Wolfe

1993). The park receives an average annual rainfall of 125cm, the majority falling

between June and September. In 2005, the total rainfall for Polk County was the fourth

wettest on record at 169cm (Blair 2006). Average Polk County temperatures are 15.6 C

in January and 27.9 C in August (McNally 2006).

In December 2004, the study area (0.809 hectares) was treated with 3.5 L/ha of

imazapyr (Arsenal) to kill above-ground cogongrass before the research started.

Effective at low rates, imazapyr is absorbed through the leaves, stems, and roots of








17



plants,providing residual control. The site was double disked and roto-tilled to 10 cm in


January 2005 prior to planting. Once imazapyr residue had reached non-injurious levels


in the soil, trees and the interplant treatments were established during spring (February


2005) and summer (June 2005).

Field Layout for 2005 Polk Co. Peace Rivw Park Bridge Crop-Cogongrass Study

Treatmmnt Code for Tree Spcler, Rep, Ground Cover, ad Intoerrop
Spect EG~E.grandls, EA Eamplfotla, P-cottorwod, TCibaldcypres, PElatah pine
N Grond Cover Conlrol- H=Htrbidde, M=Mulch, C=None Intercmp- S=Shrub, T=Trees, N=N ne
A
II lII







II
11S.hi -s*u 83mm ->
34 31 31 2 27 25 24 22 21 18 17 14 13 11 1a 8 r 4 1






I T 4
7im 04 6 04 eE4 PD4
CG M 3cs Ca
P04 P04






ala
A












Eucalyptus amp ia(EA), Populus deltoides(P), Taodium distichum(TD













and Pinus elliottii(PE). Ground cover control: H=herbicide, M=mulch,
Cnone. Intercrop: Sshrub, Ttrees, Nnone. Slope position: top, 2, 3, or
7 m V V 4


lam E13 2 EU 2 EI 2 PE 2 PEI2 PE2





















4=bottom.
CM MM CS ca HN CH





lam EUG1 01 GO I PEI 1 PE1
C" HN C1 C" HN CN








Figure 3-1 2005 Field layout for SRWC site. Species: Eucalyptus grandis (EG),
Eucalyptus amplifolia(EA), Populus deltoides(PD), Taxodium distichum(TD),
and Pinus elliottii(PE). Ground cover control: H=herbicide, M=mulch,
C=none. Intercrop: S=shrub, T=trees, N=none. Slope position: 1=top, 2, 3, or
4=bottom.


Fast-growing trees included: two species of eucalypts (E. amplifolia and E.


grandis), Populus deltoides, Pinus elliottii, and Taxodium distichum (Table 3-1).









Cottonwood and cypress were planted in the northern, less elevated and wetter portions

of the field. Slash pines were planted at the same time in the southern, sandier portions

of the field. Eucalypts were planted during June 2005 in the western half of the study.

The dimensions of the field were 73 x 105m. The field contained 40 plots that were 18 x

9m. All rows were double planted with 2.4 m between rows between adjoining cultures

and 2m between rows within a treatment.

Native shrubs and trees were interplanted within trees and included: saw palmetto,

(Serenoa repens), buttonbush (Cephalanthus occidentalis), galberry (Ilex glabra), and

wax myrtle (Myrica cerifera) (native shrubs treatment) and swamp tupelo (Nyssa

sylvatica var. biflora), sweetgum (Liquidambar styraciflua), red bay (Persea borbonia),

and swamp red bay (Perseapalustris) (Table 3-1) (native tree treatment). Plants were

chosen based on their wildlife value (Table 3-2). The summer interplants were donated

from R.S.S. Field Services and consisted of: swamp tupelo gum, loblolly bay, redbay,

and sweetgum. The species planted in the spring varied between containerized seedlings

and one gallon pots. Galberry, redbay, and swamp redbay were tubelings in the spring

planting; the rest of the native plants were planted from gallon pots. All summer planted

species were planted from gallon pots.

Besides the native tree and shrub treatments, there were three other treatments

(Table 3-3): an herbicide treatment, a mulch treatment, and a control. Each treatment had

8 plots, four in the summer planting and four in the spring.












Table 3-1 Symbols of species, planting date, and propagule type of species in the SRWC
area
Short Rotation Woody Crops Symbol Planting Date Propagule Type

Eucalyptus amplifolia EA 6-2005 Containerized seedlings

Eucalyptus grandis EG 6-2005 Containerized seedlings

Pinus elliottii PE 2-2005 Containerized seedlings

Populus deltoides PD 2-2005 Unrooted cuttings

Taxodium distichum TD 6-2005 Containerized seedlings

Interplant Native Shrub Culture

Cephalanthus occidentalis CO 2-2005 Containerized seedlings
6-2005 1 Gallon Pots
Ilex glabra IG 2-2005 Containerized seedlings
6-2005 1 Gallon Pots
Myrica cerifera MC 2-2005 Containerized seedlings
6-2005 1 Gallon Pots
Serenoa repens SR 2-2005 Containerized seedlings
6-2005 1 Gallon Pots
Interplant Native Tree Culture

Gordonia lasianthus GL 6-2005 1 Gallon Pots

Liquidambar styraciflua LS 2-2005 Containerized seedlings
6-2005 1 Gallon Pots
Nyssa sylvatica var. biflora NS 2-2005 Containerized seedlings
6-2005 1 Gallon Pots
Persea borbonia PB 2-2005 Containerized seedlings
6-2005 1 Gallon Pots
Persea palustris PP 2-2005 Containerized seedlings











Table 3-2 SRWC interplant species and their suitability
Interplant Categories
Species


Scientific Name

Persea palustris

Persea
borbonia
Nyssa sylvatica
var. biflora

Liquidambar
,n i ,,,. ijt,,
Gordonia
lasianthus
Myrica cerifera

Cephalanthus
occidentalis

Serenoa repens


Common
Name
Swamp Bay

Red Bay

Swamp
Tupelo

Sweetgum

Loblolly
Bay
Wax myrtle

Buttonbush


Saw
palmetto


Family

Lauraceae

Lauraceae

Coraceae


Hamamelidace
ae
Theaceae

Myricaceae

Rubiaceae


Arecaceae


Ilex glabra Galberry Aquifoli;

Table 3-3 SRWC culture definitions

Treatment Definition

Control No interplants planted, n
(C)
Shrub Four native shrub specie
Interplants
(S)
Tree Four native tree species
Interplants
(T)
Herbicide Herbicide applied to these
(H)
Mulch 6 in of hurricane debris r
(M)
Cogonmash Cogongrass flattened wit
(CM) glyphosate at 2.4 L/ha (2


aceae


pH
Preference
Acidic -
Neutral
Acidic -
Alkaline
Acidic


Acidic -
Alkaline
Acidic

Acidic -
Alkaline
Acidic -
Alkaline

Acidic -
Alkaline

Acidic


Seed Shade
Dispersal Tolerance
Animal Shade
tolerant
Animal Shade
tolerant
Animal, Shade
Gravity, intolerant
Water
Wind Shade
intolerant
Wind Shade
tolerant
Birds Shade
intolerant
Animals, Med to
Gravity High light
req
Animals Med to
High light
req
Animals Shade
tolerant


Soil Texture
Preference
Clay, Loam,
Sand
Clay, Loam,
Sand
Clay, Loam,
Sand

Clay, Loam,
Sand
Clay, Loam

Clay, Loam,
Sand
Sand, Loam,
Clay

Clay, Sand,
Loam

Sand, Loam,
Clay


Food
Source
Yes

Yes

Yes


Yes

Yes

Yes

Yes


Yes


Yes


o mulch applied, and no herbicide was sprayed

s planted in two double rows between the fast growing trees


planted in two double rows between the fast growing trees


;e plots when deemed necessary

nulch distributed over each plot, around fast-growing trees

h a tractor, sprayed at 3 weeks, and again at 6 weeks with 6%
.5qt/ha)


Natural Area

The natural study area (Figure 3-2), east of the SRWC Area was part of the IMC-

Peace River Park natural area composed of 6 ha, which is within 607 ha of riparian

strips between Bartow and Homeland. Cogongrass has invaded the western perimeter of









this area. The forest cover is mixed wetland forest with some cypress forest. Many of

the species utilized as interplants in the SRWC were also present in the Natural Area,

including: saw palmetto, tupelo gum, buttonbush, sweetgum, and wax myrtle.







"v-A


Figure 3-2 Aerial photograph (2005) of the 0.8 ha SRWC site and the Natural Area to the
east.

Cogonmash
The CM was a minor component of this study: appendix C displays the setup and

the results.

Experimental Design

Vegetation and soil analyses were conducted in the SRWC, NA, and CM (appendix

C) in the Polk County Peace River Park.

SRWC

In the planted area, each treatment had eight plots, four in the summer planting and

four in the spring. Although a pilot study revealed that the ideal sample size for each

plot/tree species/treatment was five, due to limited resources, only four lxlm quadrats

were established for herbaceous species and a lx4m quadrat for shrub species.

Each plot had two quadrats placed on the center row, 6 m from each end to avoid

edge effects. Two adjacent, sister quadrats were placed to the left for comparison to plots

without SRWCs; for a total of four quadrats/plot (Figure 3-3). In the center of one of the









lxlm herbaceous quadrats, a soil core was taken with a 10 cm diameter soil corer to a

depth of 24 cm.

Each soil core sample was placed in a plastic bag, homogenized, air-dried, and

sieved through a 2 mm screen, and analyzed by the Analytical Research Lab at the

University of Florida for pH, NO3-N, SOM, and macronutrients (Ca, P, K, and Mg).

SOM was determined using the Loss-on-Ignition method because SOM was greater than

6%. Macronutrients were extracted using the Mehlich 3 solution.

Surface BD was collected to a depth of 3 cm and subsurface BD from 3 to 6 cm.

The total weight of each soil sample was recorded. The sample was oven-dried for 24

hours at 1100 C to determine moisture content. BD was calculated based on dry weight.

Vegetation samples were collected in September 2005, March 2006, and May

2006. Herbaceous and shrub covers by species were measured using foliar ocular

observation in lxl m and 1x4 m quadrats, respectively. A modified Daubenmire scale (0

to 1%, 1 to 5%, 6 to 10%, 11 to 25%, 26 to 50%, 51 to 75%, 76 to 95%, or 96 to 100%)

was used to quantify cover (Daubenmire 1959). Canopy coverage was estimated for each

species regardless of overlap with other species. The number of individual herbaceous

plants and shrubs was counted within each lxl m and 1x4 m quadrats, respectively.

Only species rooted inside quadrats were included in the count; those species rooted

outside the quadrat were included in the canopy coverage data, but not the total species

count. In the case of rhizomatous and stoloniferous plants, individual shoots or stems

were counted. For those plants growing in clumps, a whole clump was designated as one

individual. Estimated cover of herbaceous and shrub species was used to calculate

percent cover and species composition.









Height, DBH, and vigor of all fast growing tree species in the SRWC area were

recorded in January 2006 and Populus deltoides again in late April 2006. Height poles

and diameter calipers were used to measure height and DBH, respectively.









[ I-





Figure 3-3 SRWC vegetation and soil core plot design. Numbers 1 and 3 are quadrats
placed under trees; numbers 2 and 4 are place between trees.

NA

The NA (Figure 3-4), starting at the paved road east of the berm/CSA, consisted of

two transects, 55 m in length, and three 10x10m tree plots placed along the transect at

alternating north and south positions. The first 10x10m plot was 6 m from the start of the

Natural area to avoid edge effects, the middle O1xl0m plot was established 14 m from the

first plot, and the last 10x10m plot started 14m from the middle plot. Within the 10x10m

tree plots were two vegetation plots (Figure 3-5) Ixlm for herbaceous cover and lx4m

for woody species, on opposite corners. Tree assessment included species, count, height,

and DBH. Soil cores were taken within the Ixlm herb quadrat. These quadrats were

demarcated by a less noticeable marker such as a pin flag in one corer of the quadrat.

The NA was sampled on September 2005, March 2006, and May 2006. Soil samples

were collected once in December 2005. Soils were analyzed using the same

methodology as the soils of the SRWC area.






























Figure 3-4 Natural area transects with three 10x10m tree plots.



















Figure 3-5 Natural area herb and shrub vegetation and soil sampling design.

Analyses

A modified Daubenmire (1959) method was used for cover estimation. Analysis of

variance was used to test tree growth, vegetation, and soil means. Duncan's means test

was used to distinguish among tree, soil, and vegetation means. Percent coverage was









calculated separately for individual herbs and shrubs using the Daubenmire (1959) scale

estimates. Percent coverage was analyzed separately using SAS analysis of variance with

cultures and species as two main factors for the SRWC site (3-1).

SRWC Model
Yij = i + 3j + (ap)ij + (ap)ijk + Eijkl (3-1)
i=l, 2, 3, 4 5;j= 1, 2, 3, 4, 5; k= 1, 2, 3, 4
ai = the effect of the ith species
Pj = the effect of the jth culture
(ap)ij= the effect of the interaction between the ith species and the jth culutre
X(ap)ijk= the effect of the kth slope position nested within the interaction between the ith
species and the jth culture
ijkl = experimental error

Pearson correlation coefficients compared the relationship between tree growth

data: height, survival, DBH, and BAH and soil or vegetation variables. Pearson

correlation was also used to compare IVI and TSC of hairy indigo and cogongrass to soil

data. Linear regression was also run on the IVI of cogongrass and hairy indigo to SOM.

Analysis of variance was run for the NA model (3-2) with transects and plots as 2

main factors.

NA Model
Yij= ai+ 3j +(apij + Eij (3-2)
ai = the effect of the ith transect
Pj = the effect of the jth plot
(ap)ij = the effect of the interaction between the jth plot and the ith transect
ij = experimental error

Stepwise regression was used for the NA BAH as a function of vegetation data

(TSC, TPCC, IVI, and TF) and as a function of soil data (pH, SOM, P, K, Ca, Mg, N03)

An Importance Value Index (IVI) was calculated as the sum of relative cover,

relative frequency (RF), and relative density (RD). Relative cover is the ratio of total

cover of one species to the total cover of all species. RF is the ratio of the frequency of









one species to the frequency of all species. RD is the ratio of the number of individuals

of one species to the total number of individuals of all species.

The Shannon-Wiener diversity index (Shannon and Weaver 1963) was calculated

for shrubs and herb at each site using the formula:


H'=- p, lnp, (3-3)


where H' = diversity index, s = number of species, pi = proportion of total sample

belonging to ith species;

H'max = LogS

J = H'-H' max (3-4)

where H'max = maximum possible diversity, S = No. of species, J = Relative

diversity.

The Jaccard (1912) index was calculated to quantify community similarity for

herbs and shrubs among sites.

C= j (a+b- j) (3-5)

where Cj = Jaccard index, j = number of common species to both sites, a = number of

species in site A, and b = number of species in site B.














CHAPTER 4
RESULTS AND DISCUSSION

Objective 1 Effectiveness of SRWCs

Hypothesis 1 stated that the tree species that grew the quickest would be the best

candidate for cogongrass control. Tree height in January 2006 was different among

species (p<0.0001) (Table 4-1). Cottonwood was the fastest growing species, reaching

upwards of 4m in the first year (Figure 4-1). On another CSA in central FL, cottonwood

grew up to 7.5 m after 2.5 years (Tamang 2005). E. grandis and E. amplifolia, at the

SRWC site, grew to heights of 0.9m and 1. m, respectively (Table 4-2), but eucalypts

were planted in the summer (June 2005), four months after all other fast growing trees

were planted. E. grandis grew the tallest in the most northern slope position (Table 4-3)

where water and nutrients were not limited. Height of all trees combined had a

significant positive correlation to SOM (Table 4-4). SOM is greater in soils of high clay

content in comparison to sandy soils (Brady and Weil 2002). The soils with great clay

content did have high SOM. E. grandis planted on the same CSA in Lakeland, grew 15m

in three years (Tamang 2005). E.s grandis with good stand density was able to suppress

cogongrass better than E. amplifolia and cottonwood (Tamang 2005). Bald cypress grew

upwards of 0.8m and slash pine to 0.3m. Even though, cottonwood was the fastest-

growing species, it failed to be the best species for cogongrass control. Cottonwood is a

deciduous species and loses its canopy in the winter months. This lack of a canopy could

be allowing enough light to reach the forest floor, reviving cogongrass. The eucalypts

had the least cogongrass cover and, though this was not tested for, eucalypts could be









exerting an allelopathic effect on cogongrass. Other studies have documented eucalypts

preventing understorey vegetation (Poore and Fries 1985; Abbasi and Vinithan 1997;

Bouvet 1998). Eucalypts also have a persistent canopy cover, maintaining their foliage

throughout the year.

Cypress had no cogongrass present in any of its plots. However, cypress was

planted where clay soils were most prevalent and cogongrass cover was greatest in the

sandy soils of the SRWC site. Sandy soils (slope positions 1 & 2) were less nutrient and

organic matter rich than the clay soils (Table 4-5). The soils where cogongrass was more

abundant in the SRWC site were more acidic; this has also been a trend in other Florida

cogongrass studies where cogongrass prefers acidic soils (Collins 2005). Other studies

have shown cogongrass grows best in acidic pH, low fertility, and low organic matter

soils (MacDonald 2004). So it is not surprising that the cypress block had the least

cogongrass cover.

Table 4-1 Analysis of variance for January 2006 tree height, DBH (diameter at breast
height), vigor, and survival of all trees, including borders, in SRWC study. C
(culture), S (species), S*C (species*culture interaction, plot/slope position.
Response C S S*C Plot(S*C)
Height 0.8601 <0.0001* 0.0111* <0.0001*
Vigor 0.4069 0.0019* 0.0133* <0.0001*
Survival 0.5875 0.2650 0.0003* <0.0001*
DBH <0.0001*












5
4.5
4
3.5
Eucalyptus amplifolia
E 3 Eucalyptus grandis
2.5-- Populus deltoides
2 Pinus elliottii
1.5 Taxodium distichum
1.5

0.5


Control Herbicide Mulch Shrubs Trees
Culture

Figure 4-1 Tree height (m) for SRWCs in January 2006 by culture and species.


90
80
70
c 60 -
I-
5 50


S30 -
S20
10
0
PE PD EG EA TD 1 2 3 4 C S T M H
SRWC Variables


Figure 4-2 May 2006 Cogongrass TSC for all species, slope positions, and treatments in
the SRWC site.










Table 4-2 Average tree and shrub height (H, in m), vigor (V), survival (S, %), and DBH
(D in cm) in January 2006 by culture and species (excluding borders).
Standard deviations in parentheses. Values with the same letter are not
different (p=0.05) among cultures within a species.
Response

Combined average across cultures


Species
Eucalyptus amplifolia
Eucalyptus grandis
Populus deltoides
Pinus elliottii
Taxodium distichum

Eucalyptus amplifolia
Eucalyptus grandis
Populus deltoides
Pinus elliottii
Taxodium distichum

Eucalyptus amplifolia
Eucalyptus grandis
Populus deltoides
Pinus elliottii
Taxodium distichum

Eucalyptus amplifolia
Eucalyptus grandis
Populus deltoides
Pinus elliottii
Taxodium distichum

Eucalyptus amplifolia
Eucalyptus grandis
Populus deltoides
Pinus elliottii
Cephalanthus occidentalis
Ilex glabra
Myrica cerifera
Serenoa repens

Eucalyptus amplifolia
Eucalyptus grandis
Populus deltoides
Pinus elliottii
Gordonia lasianthus
Liquidambar styraciflua
Nyssa sylvatica
Persea borbonia
Persea palustris


H
0.9C (.5)
1.1B (.5)
3.5A (.9)
0.3D (.2)
0.8C (.2)

.49b (.2)
1.Oab (.5)
4.1 a (.8)
.3a (.1)
.89a (.3)

0.5b (.2)
0.93bc (.5)
3.8b (.9)
0.16a (.2)
0.92a (.2)

0.9a (.5)
1.0a (.5)
3.2c (.7)
0.35a (.2)
0.8a (.2)

1.2a (.5)
1.2ab (.5)
2.9c (.7)
0.31a (.2)
0.71a (.3)
0.4b (.1)
0.51b (.2)
0.21c (.1)

0.8a (.4)
0.9c (.5)
2.8c (.6)
0.3a (.2)
0.9b (.3)
1.2a (.4)
1.3a (.3)
0.9b (.9)
.4c (.4)


3.0B (1) 63A (48)
2.7C (1) 59A (49)
2.1D (1) 60A (49)
3.2A (.9) 40A (49)
2.5D (.8) 87A (34)
Control
4a (.5) 20c (40)
3.0abc (1.1) 64b (48)
2.2bc (1.1) 79a (41)
2.7bc (1) 40c (49)
2.3a (1) 73b (45)
Herbicide
4a(.3) 28b (45)
3.3abc (1) 53c (50)
1.7c(1) 74a (44)
2.7cd (.9) 49b (50)
2.4a (.8) 93ab (26)
Mulch
3.1c (1.1) 80b (40)
2.6abc (1.1) 84a (36)
2.3a (1.2) 53b (50)
2.3d (1) 73a (44)
2.1a (.8) 96a (19)
Shrubs
2.7c (1) 93c (24)
2.6abc (1.2) 47a (50)
2.7ab (1) 60b (49)
3.2ab (.6) 16d (37)
1.9b (.9) 58bc (49)
2.0b (1) 38c (49)
2.4ab (1) 84a (37)
2.5a (.9) 73ab (44)
Trees
3.3b (.8) 92c (28)
3abc (1) 46a (50)
3.2a (1) 39c (49)
3.5a (.6) 21d (41)
1.9b (.3) 94a (23)
1.5bc (.5) 94a (24)
1.3c (.5) 97a (16)
1.8bc (.6) 61b (49)
2.5a (.7) 24c (43)


D


2.61 (1)






3.22a (1.1)






2.9b (1)






2.32c (.8)






2.31c (.82)









2.04d (.7)











Table 4-3 Average height (m) in January 2006 by slope position (1 at top of slope; 4 at
bottom of slope) and species (excluding borders). Values with the same letter
are not different (p=0.05) among slopes within a species.
Species Slope 1 2 3 4


Eucalyptus
amplifolia
Eucalyptus
grandis
Populus
deltoides
Pinus elliottii
Taxodium
distichum
Cephalanthus
occidentalis
Ilex glabra
Myrica cerifera
Serenoa repens
Gordonia
lasianthus
Liquidambar

Nyssa sylvatica
Persea
borbonia
Persea palustris


1.lb 0.85c


1.23a

3.1b


0.28b 0.36a


0.6b

0.4a
0.6a
0.2a
0.9a

1.lb

1.2b
0.9a


0.8a

0.4a
0.4b
0.2a
1.0a

1.lb

1.5a
1.la


0 0.2b


0.7ab 0.7ab


0.4a
0.5b
0.2a
0.8a

1.3a

1.3b
0.8a

0.4a


0.4a
0.6a
0.2a
1.Oa
1.0a

1.4a

1.3b
0.8a

0.3ab


Table 4-4 Pearson correlation coefficients of all January 2006 height (H) and survival (S)
data for all SRWC trees and soil variables.
H S OM pH NO3 BDO BD1 P K Ca Mg


0.19 0.43* 0.43* 0.10


0.88* 1 0.16 0.35* -0.3
0.046 0.09 1 0.53* 0.34*


pH 0.37 0.30 0.54*


-0.36* -0.07 -0.01 -0.13 -0.20
0.37*


-0.07 -0.2 0.03
-0.73* 0.12
0.62*


0.07 -0.03 -0.04
0.10 0.06 0.02


0.19 -.37* .16 -.00 .03 -.01


0.39*
NO3 -0.11 -0.11 0.56* 0.07 1 -0.25 -0.29 -0.22 -0.29 -0.2 -0.18
BDO 0.06 0.22 -0.22 -0.46* -0.37 1 0.71* -0.14 -0.05 -0.03 0.00
BD1 -0.06 -0.10 -0.55* -0.39 -0.56* 0.25 1 -0.18 -0.04 -0.05 -0.05
P -0.30 -0.14 -0.12 -0.09 -0.25 0.01 -0.08 1 0.74* 0.90* 0.88*
K -0.10 0.04 0.13 -0.13 -0.16 0.002 -0.07 0.67* 1 0.81* 0.78*
Ca -0.32 -0.17 -0.01 -0.12 -0.25 0.07 -0.02 0.92* 0.81* 1 0.98*
Mg -0.35 -0.17 -0.03 -0.16 -0.20 0.11 -0.06 0.92* 0.77* 0.99* 1
Coefficients above the diagonal for all SRWC trees combined and below the diagonal for all eucalypt trees
combined. Values with a indicate a Pearson correlation at the .05 level.










Table 4-5 Means for all soil variables in the Natural Area and the Short Rotation Woody
Crop (SRWC) sites. Surface BD (BDO), subsurface BD (BD1), transect (T),
mixed wetland forest (MW), cypress forest (C), SRWC control culture (C),
herbicide culture (H), mulch culture (M), native shrub culture (S), and native
tree culture (T). Values with the same letter are not different at the .05 level.
Trt OM pH BDO BD1 NO3 P K Ca Mg
Natural Area


Ave 5.6 6.15 0.699 0.902 5
T1 4.5a 6.4a 0.79a 0.96a 6a
T2 6.7a 5.9a 0.57a 0.81a 4a
MW 5.8a 6.1a 0.72a 0.96a 5a
C 5a 6.4a 0.55a 0.81a 5a
1 3.9a 6.2a 0.92a 1.05a 8a
2 4.2a 6.1a 0.78a 0.93a 3a
3 8.7a 6.2a 0.35a 0.78a 4a
SRWC
Ave 5.4 6.43 .717 0.832 11
EA 5.7a 6.3b 0.6a 0.81a 9a
EG 4.6 6.3b 0.68a 0.92a 7a
PD 7.8a 6.7a 0.53a 0.71a 14a
PE 4.1a 6.4b 0.92a 0.98a 14a
TD 8a 7a 0.54a 0.69a 15a
C 6.3a 6.6a 0.65a 0.79b 12a
H 5.5a 6.6a 0.66a 0.79b 10a
M 4.7a 6.6a 0.79a 0.94ab 1la
S 5.4a 6.3a 0.63a 0.78b 13a
T 6.2a 6.4a 0.69a 0.99a 1la
1 1.7b 6.2c 0.70b 0.93a 8a
2 6.5a 6.3bc 0.99a 1.07a 13a
3 6.8a 6.5b 0.55b 0.75b 10a
4 7.3a 6.8a 0.55b 0.71b 14a


531 104 2496 864
494a 125a 2632a 960a
567a 84a 2360a 768a
523a 89a 2470a 850a
555a 151a 2572a 906a
510a 81a 2315a 728a
552a 115a 2803a 1088a
529a 117a 2370a 777a

527 256 3189 1257
611a 256a 3908a 1554a
472a 157a 2749a 913b
526a 154a 2985a 979ab
535a 168a 3190a 1184ab
682a 216a 3789a 1352ab
575a 190a 3269a 1125ab
601a 171a 3747a 1423a
476a 137a 2649a 914ab
407a 131a 2198a 686b
585a 243a 3641a 1313a
454a 145a 2709a 930a
622a 216a 3797a 1430a
535a 197a 3187a 1150a
530a 152a 2939a 971a


Objective 2 Cultural Treatments

Cogongrass had been suppressed by a dense canopy cover on CSAs in central

Florida (Tamang 2005). An impenetrable layer of mulch or cogonmash should

theoretically constrain cogongrass growth by providing cover. Cogongrass cover in the

SRWC site was significantly different among cultures (p=0.0113) (Figure 4-2). The

mulch and the herbicide treatment had less than 2% cogongrass cover in May 2006

(Figure 4-2). The herbicide applied twice in the SRWC site to the herbicide block was









2,4-D at 1.1 kg Ai/ha. 2,4-D is mainly used for broadleaf species, but in this study it

seems to have constrained cogongrass.

The cogonmash had 0.5% cogongrass cover and was the most effective at

constraining cogongrass. However, the cogonmash study only began in September 2005.

More time is needed to accurately come to any sort of conclusions about how effective a

cogonmash treatment might be. Other studies have shown cogonmash to have 20 to 60%

less cogongrass than the cogongrass control method of slashing (Chikoye 2001).

The control was positioned on the edges of the field and this position is first to be

invaded by cogongrass from the surrounding cogongrass areas. Like cogongrass TSC,

TPCC was significantly different among cultures (p=0.0290). TPCC was greatest for the

native tree treatment at 58%. The best treatment for all cogongrass control and TPCC

was the mulch culture. Mulch creates an effective barrier that obstructs the sun.

Objective 3 Native Species Colonization

Herbaceous plants

The flora of the SRWC site consisted of, primarily, herbaceous species of the

Asteraceae family. The SRWC area is ideal for wind dispersal because the site is

surrounded by open fields, which are conducive to continuous wind movement. There

are no thick forests to obstruct the path of the seed. Many early colonists of abandoned

fields are winter and summer annual herbs. Plants of the Asteraceae, with weightless

achenes (single-seeded dry fruit) are abundant (Bazzaz 1979). Achenes of sow thistle

have been collected by aircraft on a screen 2000ft above Tallula, LA (Glick 1939).

Dogfennel are surrounded with hairs allowing effective dispersal by wind (Ferrell and

MacDonald 2005). Another frequent herb in the SRWC area, Canadian horseweed, can









produce over 200,000 small, wind-dispersed seeds per plant in late summer (Keever,

1950).

In the SRWC site, herbaceous species of the Fabaceae were also common. Hairy

indigo, an exotic legume, had the greatest TSC, 54%, and was observed in 140 quadrats

out of a possible 160 (88%). This species grew only in fall 2005. It is a nitrogen fixer

and alters soil conditions to make the soil more suitable for other vegetation species.

Hairy indigo can fill the ecological niche provided by cogongrass (Gaffney 1996).

Nitrogen deficiency is a common barrier to plant growth on mine spoils (Bradshaw and

Chadwick 1980). The development of a stable ecosystem is reliant upon the colonization

by nitrogen fixing species on mine spoils (Roberts et al. 1981) and hairy indigo facilitates

the establishment of future plants. There were an abundance of nitrogen fixing species in

the first growing season; four were present in Sept. 2005 and only one in March and May

of 2006. Hairy indigo was typically growing with only one other plant species. This

could be attributed to the thick canopy cover hairy indigo provides. This species had a

high IVI value of 214.

A total of 42 species were observed in the SRWC area during three growing

seasons. Of that 42, 8 herbaceous species were unidentified. Of these 8, 4 were

classified to the family level: the Fabaceae, the Euphorbiaceae, and two in the Poaceae

family. Of the 34 plants that were identified in the SRWC area, 15 (44%) were exotics

and 19 (56%) were native, belonging to 18 families. Eight were not identified to the

species level; therefore, nativity could not be determined. Other successional studies on

phosphate mined areas have observed that exotic weed species dominate in primary

succession, but their numbers are replaced by native plants (Manner et al. 1984).









Among identified species in the SRWC area, Aster elliottii, Cirsium horridulum,,

Commelina diffusa, Cyperus rotundus, Geranium carolinianum, Sesbania exaltata,

Lepidium virginicum, and three of the unidentified species appeared only once in 160

quadrats. Native species such as Boehmaria cylindrica, Conzya canadensis, Eupatorium

capillifolium, Gnaphaliumfalcatum, and Passiflora incarnata were common. Apart from

cogongrass, introduced species such as hairy indigo and sow thistle occurred frequently.

The absence of many species in the SRWC area that were found in the Natural area

is due in part to the stressful environmental conditions and poor dispersal abilities of the

native herbaceous species. The absence of the Natural area species might also be

attributed to the lack of canopy cover in the SRWC area. NA TPCC does not include the

tree and shrub canopy above the herbaceous species. In addition, if Natural area natives

successfully disperse into the SRWC area, it will be more difficult for the native species

to compete with the introduced species. Trends in herbaceous vegetation suggest an even

greater presence of native plants than what was seen after the first year of SRWC growth.

Manner et al. (1984) noticed the same trends on Nauru Island.

Of the 32 herbaceous species observed in the NA, only three were introduced

species. This trend is typical of most natural areas. According to Manner (1984), most

exotics do not penetrate into established communities unless new niches are made

available by direct disturbance. While the studied Natural area is frequently visited by

humans, people walk on an elevated boardwalk and leave the area relatively undisturbed.

Cogongrass had an average TSC of 28% in May 2006 and was found growing in all

cultures, most prolifically in the native tree and shrub cultures (Figure 4-2). Cogongrass

TSC was 25% for the native tree culture and 27% for the native shrub culture. The TSC









of the control was high, 85%, but this is misleading. Cogongrass was one of the top five

species found growing in the SRWC area with an IVI value of 135. Native tree and shrub

cultures are not effective methods to control cogongrass regrowth. The native culture

species are slow growing and therefore do not provide ample canopy cover to constrain

cogongrass growth.

TPCC failed to differ within species (p=0.1100) (Table 4-6). It differed among

cultures (p=0.0290). TPCC was greatest for the native tree treatment at 58%. The best

treatment with the least TPCC was the mulch treatment at 23%. Mulch creates an

effective barrier that obstructs the rays of the sun to prevent much photosynthesis from

occurring. TPCC was greatest in the most southern, sandiest slope position (1) in the

field, 60%. TSC was greatest for hairy indigo, with 54%. Cogongrass had a high TSC of

21%. TSC and TPCC were highest in the cypress block at 13% and the slash pine block

at 65%, respectively and lowest in the Eucalyptus grandis block with a TSC of 8% and in

the Eucalyptus amplifolia block with a TPCC of 27%.

Table 4-6 Analysis of variance for herbs and shrubs in the Short Rotation Woody Crop
(SRWC) and Natureal Area (NA) sites. Values with a differ at the .05 level.
Species (S), slope position/plots (P), culture (C), and transect (T).
Variable TPCC
SRWC Herbs SRWC Shrubs
Species 0.1100 0.0577
Culture 0.0290* 0.3294
Slope positions 0.1243 0.4309
S*C 0.0005* 0.6816
P(S*C) <0.0001* <0.0001*
NA Herbs NA Shrubs
Transect 0.3690 0.3357
Plot 0.2571 0.1170
T*P 0.4274 0.0857

The 10 greatest IVI's and TSC's (Table 4-7) were analyzed to reveal the

differences for cultures, species, and slope positions. TSC was different (p=0.0193)

within treatments for ragweed. The native tree culture had the greatest TSC, 15%, than









any of the other four cultures. TSC was different for cudweed within treatments; the

greatest TSC was observed in the native tree culture. The IVI value of sow thistle was

different within cultures (p<0.0001) and species (p=0.0450). The culture with the

greatest IVI was the mulch culture with an IVI value of 216. Species Eucalyptus

amplifolia and Eucalyptus grandis had similar IVI values for sow thistle, 142 and 122,

respectively.

Cogongrass TSC differed among species (p=0.0112) and cultures (p=0.0113)

(Figure 4-2). The control had the greatest TSC, 55%, while the herbicide and mulch

treatments had the least TSC, less than 2% each. Pinus elliottii also had the greatest TSC

value for all fast growing tree species, 32%. Taxodium distichum had no cogongrass

present and Eucalyptus amplifolia had minimal cover, 1%. Both eucalypts had low

cogongrass cover and perhaps the eucalypts are exerting an allelopathic effect. Other

studies have documented eucalypts preventing understorey vegetation (Poore and Fries

1985; Abbasi and Vinithan 1997; Bouvet 1998). The control treatment is located on the

eastern and western edges of the SRWC study area, which may explain why cogongrass

TSC is greatest in this treatment; cogongrass may be invading from outside the study area

in the control blocks.









Table 4-7 Ten greatest IVI and TSC (%) values of herbs and shrubs for each site.
SRWC
Herbs IVI TSC Shrubs IVI TSC
Boehmaria cylindrica 221 53 Baccharis halimifolia 222 5
Indigofera hirsuta 214 54 Sambucus canadensis 200 5
Imperata cylindrica 135 21 Ludwigia peruviana 53 0.5
Gnaphalium falcatum 118 9
Sonchus asper 110 3
Aeschynomene indica 103 8
Conzya canadensis 99 2
Unk SRWC7 97 8
Cirsium horridulum 95 3
Sesbania exaltata 93 18
Medicago lupulina 84 10
Ambrosia artemissiifolia 74 10
Physalis pruinosa 67 9
NA
Herbs IVI TSC Shrubs IVI TSC
Hydrocotyle umbellata 117 7 Ulmus americana 155 17
Cicuta maculata 112 53 Baccharis halimifolia 132 34
Thelypteris kunthii 107 21 Urena lobata 120 13
Oxalis corniculata 104 1 Itea virginica 115 11
Dicanthelium commutatum 98 3 Acer rubrum 104 8
Ptilimnium capillaceum 94 1 Parthenocissus quinquefolia 104 1
NA
Herbs IVI TSC Shrubs IVI TSC
Unk NA2 92 7 Carpinus caroliniana 96 24
Viola sororia 90 1 Cornusfoemenia 96 38
Sambucus canadensis 89 3 Serenoa repens 87 31
Samolus ebracteatus 85 3 Clematis crispa 85 6
Salvia lyrata 79 2 Sabalpalmetto 55 28
Oplismensus hirtellus 86 1 Sabal minor 58 14
Boehmaria cylindrica 77 1 Ludwigia peruviana 61 11

The herbaceous species, hairy indigo, with the greatest TSC and high IVI value,

grew in all treatments, with all species, and in all slope positions. However, there were

no differences among any of the parameters for TSC and IVI. All treatments had a TSC

value above 50% and IVI values were well above 150 for all treatments. Eucalyptus

amplifolia had the greatest TSC, 67%, while cypress had the least at 29%.









A field untended for a year is covered by populations of mainly annual and biennial

herbaceous species; a few tree and shrub species may be present (Bard 1952; Egler 1954;

Keever 1979; Oosting 1942). Initially, competition is minimal at newly disturbed, open

sites. Soon, however, ground cover becomes dense and successive appearance of

herbaceous species in abandoned fields is reliant on competitive interactions (Davis &

Cantlon 1969). A study at a CSA in Lakeland, Florida identified 57 herbaceous species

in the understory of eucalypt and cottonwood trees after four years (Tamang 2005).

Forty of these species were native. Sixteen were also present at the SRWC study area.

There is good evidence that much of the vegetation trends seen at the Lakeland site will

occur in the SRWC study area, except that more native species may return to the SRWC

site because SOM is greater and pH is more acidic than that of the Lakeland site, creating

better conditions for FL natives. As succession proceeds, P, Mg, and Ca available to

plants in the soil will be gradually depleted within reach of the root. However, K should

increase. As shrubs invade the field, nutrients increase in the topsoil; this is attributed to

the attainment of nutrients from greater depths and their return to the upper soil layers by

recycling (Burrows 1990). The increase of diversity over time is caused by microhabitat

diversification, arising from local changes in soil properties around individual plants

(Mellinger and McNaughton 1975; Zinke 1962).

At the Lakeland site CSA, cogongrass had the greatest IVI of all herbaceous

species (Tamang 2005). Cogongrass did not have the greatest IVI in the SRWC study

area, but it was one of the top five IVI values. It is possible in 3 years that cogongrass

will have the greatest IVI value due its vigorous rhizome growth (MacDonald et al.

2002).







40



Regression comparing SOM to cogongrass IVI by slope positions (Figure 4-3)


indicated that SOM is currently not an important variable in determining whether


cogongrass will be present (r2=0.0106).


250

200

150

100

50

0
O.


4.00 6.00


8.00 10.00


OM (%)

Figure 4-3 Relation of SOM to cogongrass IVI in the SRWC area.

SOM was also compared with hairy indigo in the SRWC study area. Again, it was


not an important factor in whether hairy indigo was present on a plot (r2=0.0041) (Figure


4-4).


350
300
S250
0
.2 200
S150
S100
50
0


0 2 4 6
OM (%)


8 10 12


Figure 4-4 Relation of SOM to hairy indigo IVI in the SRWC area.

Pearson correlations was run for the herbaceous species with the greatest IVI


values. IVI and TSC were correlated with soil variables to see if any trends were


occurring that could be used to predict vegetation pattern (Table 4-8; 4-9).


* *9


-r
*
** *


00











Table 4-8 Pearson correlation coefficients of sow thistle and cudweed IVI, TSC, and soil
variables in the SRWC area.


TSC
IVI
OM
pH
NO3-N
P
K
Ca
Mg
BDO
BD1


TSC
1
0.80*
-0.54*
-0.24
-0.08
-0.05
-0.04
-0.07
-0.05
-0.10
0.31


IVI
0.27
1
-0.41*
-0.24
-0.06
-0.06
0
-0.03
-0.03
0.05
0.26


OM
-0.03
-0.18
1
0.40*
0.21
0.08
0.12
0.10
0.05
-0.12
-0.20


pH
0.35*
-0.01
0.47*
1
-0.00
0.08
0.002
0.01
-0.02
-0.10
-0.23


NO3-N
-0.09
-0.23
0.27
0.07
1
-0.31
-0.34
-0.19
-0.16
-0.00
-0.24


P
-0.08
-0.16
0.16
0.09
-0.22
1
0.67*
0.88*
0.86*
0.09
0.20


K
-0.09
-0.18
0.13
-0.05
-0.28
0.70*
1
0.75*
0.72*
-0.03
0.09


Ca
-0.11
-0.16
0.11
-0.06
-0.18
0.88*
0.78*
1
0.98*
0.11
0.22


Mg
-0.13
-0.14
0.07
-0.10
-0.15
0.85*
0.75*
0.98*
1
0.13
0.23


BDO
-0.17
0.09
-0.06
-0.17
0.09
0.14
0.05
0.17
0.24
1
.73*


Coefficients above the diagonal for sow thistle and below the diagonal for cudweed. Values with a *
indicate a Pearson correlation at the .05 level.

Table 4-9 Pearson correlation coefficients for hairy indigo and cogongrass IVI, TSC, and


TSC
IVI
OM
pH
NO3-N
P
K
Ca
Mg
BDO


soil
TSC
1
0.51*
-0.25
-0.35*
0.01
0.13
-0.01
0.17
0.21
0.26


variables in the


IVI
0.75*
1
0.01
-0.02
-0.10
-0.06
-0.14
-0.05
-0.03
0.06


OM
-0.10
-0.20
1
0.48*
0.32*
0.20
0.18
0.17
0.14
-0.10


SRWC
pH
-0.23
-0.34
0.29
1
0.13
0.17
0.01
0.06
0.02
-0.19


area.
NO3-N
0.47*
0.18
0.31
0.05
1
-0.15
-0.22
-0.10
-0.07
0.06


P
-0.09
-0.05
-0.23
-0.32
-0.22
1
0.73*
0.89*
0.87*
0.13


K
-0.14
-0.08
-0.11
-0.38
-0.34
0.70*
1
0.80*
0.77*
0.05


Ca
0.05
0.04
-0.29
-0.50*
-0.12
0.85*
0.80*
1
0.98*
0.15


Mg
-0.02
0.01
-0.27
-0.46*
-0.18
0.86*
0.80*
0.98*
1
0.22


BDO
0.14
0.37
-0.72*
-0.21
-0.26
0.04
0.03
0.14
0.14
1


BD1 0.27 0.12 -0.22 -0.33* -0.15 0.19 0.14 0.23 0.28 0.80* 1
Coefficients above the diagonal for cogongrass and below the diagonal for hairy indigo. Values with a *
indicate a Pearson correlation at the .05 level.

Vegetation variables were analyzed for the cottonwood block since growth was

greatest for this species. The culture-slope position interaction was significant

(p=0.0053) for TPCC (Table 4-10). Like all SRWCs, cottonwood had the least TPCC in

the mulch treatment (20%), further proving that it is the most effective culture for

vegetation growth prevention. The native tree and shrub cultures had the greatest TPCC.

Hairy indigo had the greatest TSC and IVI value in the Populus deltoides block (Table 4-

11). Two shrub species were present in the cottonwood block, saltbush and elderberry.


BD1
-0.19
-0.08
-0.14
-0.27
-0.08
0.21
0.16
0.27
0.32*
0.79*
1


BD1
0.07
0.31
-0.75
-0.34
-0.38
0.13
0.16
0.29
0.29
0.77*









Saltbush had a TSC of 0.5% and elderberry 5%. IVIs were 222 for saltbush and 200 for

elderberry.

Pearson correlation was performed by quadrat for the cottonwood block for the

TPCC, cogongrass TSC, and BAH (scaled up from the quadrat unit). The worst

cottonwood growth was in the native shrub and tree cultures and these cultures also had

the greatest TPCC and cogongrass TSC, which could explain such poor growth. The

cottonwoods had to compete harder with cogongrass and understory vegetation than the

control, herbicide, and mulch cultures. TPCC was negatively correlated to BAH on a

quadrat basis (p=0.0007) (Table 4-12).

Pearson correlation was also done on a cottonwood plot basis for TPCC,

cogongrass TSC, and BAH. There were no correlations except for cogongrass TSC

positively correlated to TPCC (p=0.0059) (Table 4-12).

Table 4-10 Analysis of variance for cottonwood vegetation variables: total species cover
(TSC), total plant canopy cover (TPCC), and importance value index (IVI).
P-values with a differ at the .05 level.
Herbs
Response C P C*P
TSC 0.4359 0.9102 0.2091
TPCC 0.2011 0.9330 0.0053*
IVI 0.2595 0.9489 0.1348
Shrubs
Response C P C*P+
TSC 0.7742 0.4200
TPCC 0.7901 0.5000
IVI 0.8139 0.3949
+Shrub C*P was not testable.










Table 4-11 Top 5 species with the greatest TSC and IVI values in the cottonwood block.
Values with the same letter are not different at .05 level.
Response
Species TSC IVI
Indigofera hirsuta 42a 212a
Sesbania virgata 38ab 121abc
Imperata cylindrica 23abc 156ab
Lactuca graminifolia 10abc 126abc
Aeschynomene indica 6bc 129abc

Table 4-12 Pearson correlation coefficients for Populus deltoides basal area per hectare
(BAH), total plant canopy cover (TPCC), and cogongrass total species cover
(TSC) on a quadrat and slope position basis. Coefficients with a are
different at the .05 level.
BAH TPCC Cogongrass
TSC
BAH 1 -0.5540* -0.3320
TPCC -0.5040 1 0.6500*
Cogongrass -0.2970 0.7960* 1
TSC
Coefficients above the diagonal are on a quadrat basis; below are on a slope position basis.

Shrubs

Both sites combined had a total of 34 different shrub species. No woody species

went unidentified. Swamp dogwood had the highest TSC value, 38%, and the other

species with the top five TSCs were all found in the Natural area. IVI was highest for

saltbush in the SRWC site, 222, because it was the most prevalent shrub species.

However, its TSC was always less than 1% for saltbush in the SRWC site.

Besides herbaceous plants, some of the immigrant seeds in the field will be from

perennial woody species of nearby shrub and or forest stands, dispersed by wind, birds,

or mammals (Burrows 1990). No shrubs were present in September 2005. Only three

shrub species were observed in the SRWC area. And the majority of the observations

were saltbush/groundsel tree and all were seedlings. There were a total of 98

observations of shrub species, 96% of these observations were saltbush; observed in 65 of









160 quadrats (41%). Elderberry was observed in one quadrat with a frequency of less

than 1%. Primrose willow was present in two quadrats. TPCC was greatest in the

herbicide culture with an observed value of 1.6%. All other treatments observed TPCC

of 1% or less. TPCC was highest in the most southern slope position (1) of the field with

a TPCC of 1.5%. Amongst fast-growing tree species, cottonwood had the greatest TPCC

at 1.7%. Cypress had the least with zero shrubs observed.

Shrubs are slow to populate an abandoned field for various reasons: 1) their

propagules are not dispersed as quickly or as far as those of herbs, 2) seed banks and

vegetative propagules of woody species are nearly or completely lacking in cultivated

fields, 3) biotic and abiotic conditions are not favorable enough in open, cultivated

ground for juveniles of woody species, and 4) herbaceous populations exclude the woody

plants by rapid growth (Burrows 1990). A study on forested central Florida phosphate

mined lands found the distance to a seed source was the best predictor (R2=0.85) of the

regeneration of the later successional species and a good predictor of species diversity.

Both the IVI of the later successional species and the diversity index decreased with the

distance from the seed source (McClanahan 1986).

The Natural area had 32 shrubs, of which only four were introduced species. IVI

was greatest for American elm with a value of 155, followed by saltbush with 132,

caesarweed with 120, Virginia sweetspire with 115, and red maple at 104 (Table 4-7).

Swamp dogwood dominated in TSC with a high value of 38%. Saltbush had TSC of

34%; saw palmetto with 31%, cabbage palm a TSC of 28%, and American hornbeam

24%. The shrub with the greatest frequency was American elm; it was observed in 8 of









the 12 plots (67%). Red maple, American hornbeam, saltbush, laurel oak, and

caesarweed all observed a frequency of 5 of the 12 plots (42%).

NA trees

Trees were only found in the Natural area. A total of 148 trees were observed,

composed of 13 species. Height and DBH were measured during September 2005.

Height differed among transects (p=0.0373) and among species (p=0.0203). Height for

transect 1 averaged 16.3 m and 13.2 m for transect 2. DBH was also greater on transect

1, 24.7cm, than on transect 2, 15.8 cm. Plot 3 with the tallest trees has many bald cypress

trees. Likewise, DBH was greatest in plot 3, 24.1cm. No significant differences were

found for DBH or BAT/BAH. Cypress was the tallest at 24m and the most frequent with

40 observations.

Stepwise regression was run for BAH in the NA as a function of soil variables

(OM, pH, NO3, P, K, Ca, Mg, BDO, and BD1). Only one variable had an effect on BAH:

pH (p=0.0193, r2 =0.7819) (Figure 4-5). The greatest BAH were found on plots with the

greatest pH. Transect 1 had a greater pH (Table 4-5) than transect 2 and, therefore

greater BAH. Stepwise regression was also run for NA BAH as a function of vegetation

data (TSC, TPCC, TF, and IVI) but none of those variables fit a model and therefore, had

no effect on the BAH of the NA plots. The variables were run at the 0.1500 level.











140

120

100

80

60

40

20

0 -
5.7 5.8 5.9 6 6.1 6.2 6.3 6.4 6.5 6.6
pH


Figure 4-5 Stepwise regression (0.15 level) of NA tree BAH as a function of pH by plot.

Species Diversity and Site Similarity

The SRWC was much less diverse compared to natural communities, where

Shannon-Wiener diversity index falls between 1.5 and 3.5. This might be due to young

stand age and the competition of plants with cogongrass. Allelopathy of eucalypts and

cottonwood also might have affected the species recruitment rate in the SRWC area.

Shannon Weiner diversity index for herbs in the SRWC area was 0.69, compared to 1.13

for the Natural area (Table 4-13). The Natural area had the greatest index value, but is

still not typical of most natural forests. This could be attributed to a sample size that was

too small to get accurate representation of all herbaceous species.

For shrubs, the Natural area had the greatest Shannon-Weiner index value at 1.29

(Table 4-18). The SRWC area had a very low index of 0.086 since only three shrub

species were present in this site.









Only the Natural area had trees present as part of the vegetation surveys and they

had a Shannen-Weiner index of 0.9 (Table 4-13). Hmax was 1.04. Again this value may

be low due to a small sample size.

Table 4-13 Shannon-Weiner diversity index (H') and maximum possible diversity
(Hmax) of all sites for herbs, shrubs, and NA trees.
SRWC NA CM
Herbs
H' 0.69 1.13 0.5
Hmax 1.25 1.3 0.7
Shrubs
H' 0.086 1.29 0
Hmax 0.47 1.4 0
Trees
H' 0 0.9 0
Hmax 0 1.04 0

The Natural area and the SRWC sites had a Jaccard index of 0.07 and the Natural

area had a Jaccard index of 0.05 (Table 4-14).

Table 4-14 Jaccard's community similarity index (Cj) for herbs (H) and shrub species (S)
at all sites.
Site NA CM
SRWC H 0.07 0.2
S 0.09 0.33
CM H 0.05
S 0.03

The SRWC area and the Natural area had a shrub Jaccard community similarity

index of 0.09 (Table 4-14). The SRWC area is in its very early stage of succession and

with time more shrub species will voluntarily make their way to this site.

Objective 4 Soil Properties

The initial 9% SOM, collected in February 2005 decreased to 5.4% (Table 4-5) in

December 2005 because the soil collected in February 2005 had just been rotovated into

the soil a month prior, contributing to the high SOM. Similar trends have been seen with

SOM amounts dropping as mineralization and tree growth occurs in eucalyptus stands









(Loumeto and Bernhard-Reversat 2001). Soils high in clay are generally high in SOM

(Brady and Weil 2002). Finer textured soils amass more SOM because 1) they typically

produce more plant biomass, 2) the soils are less well aerated and lose less SOM, and 3)

more of the organic material is shielded from decomposition because it is bound by clay-

humus complexes (Brady and Weil 2002).

The soil in the NA had a pH of 6.15. The soil series of the NA, Nittaw, are known

to have neutral to slightly acidic pH (Polk County Soil Survey, US Dept. of Ag, Soil

Cons. Service 1990). The SRWC site had the most N03-N, 11 mg/kg (Table 4-5). In the

SRWC area, there was a high frequency of N2 fixing species in the first sampling, mainly

hairy indigo. Hairy indigo can contribute 31 kg N/ha (Okito 2004). In other studies,

carried out on mining clay wastes in China, a great prevalence of legumes contributed to

the nitrogen economy of the vegetation (Marrs et al. 1980). The development of a

functioning nitrogen cycle has shown to be crucial for the successful restoration of

derelict land (Bradshaw and Chadwick 1980). Gains in soil N are contributed to the soil

from rainwater in the form of NH3 and NO3. Microorganisms also play a great role,

through the fixation of N2, in N soil gains. Ample SOM is needed by free-living bacteria

to fix N (Stevenson 1986).

Surface BD was less than subsurface BD for all sites. BD samples taken deeper in

the soil profile are typically greater due to reasons, which include: lower SOM, less

aggregation, fewer roots and other soil organisms, and compaction due to the weight of

the overlying layers (Brady and Weil 2002).

SRWC

Soils of the SRWC CSA are of the soil series, Haplaquents. These soils are

colloidal clays, composed of mainly montmorillonite. They are highly fertile soils (Polk










County Soil Survey, US Dept. of Ag, Soil Cons. Service 1990). SOM was different

(p=0.0008) along the slope (Table 4-5). SOM might be so low in slope 1 because of a

high sand consistency. Typically, less SOM is found in sandy soils (Brady and Weil

2002). Likewise, pH, N03-N, P, Ca, and Mg were also lowest in slope position 1. Soil p

(Table 4-15; 4-16)). Soil pH was also different (p=0.0090) among slope positions and

among species (p=0.0425). Mg differed among species (p=0.0337) and cultures

(p=0.0321) (Table 4-8). Surface BD was different among slope positions (p=0.0034).

Subsurface BD differed among slope positions (p=0.0173) and cultures (p=0.0084).

Table 4-15 Analysis of variance for the Short rotation woody crop (SRWC) and Natural
Area soil variables: species (S), culture (C), slope position (P), transect (T),
and quadrat (Q). Values with a are different at the .05 level.
SRWC
S C P P(C*S)+
OM 0.3622 0.5649 0.0008*
pH 0.0425* 0.1190 0.0090*
NO3-N 0.0864 0.8194 0.2745
P 0.2078 0.1775 0.1075
K 0.3432 0.4033 0.3178
Ca 0.0754 0.0580 0.1259
Mg 0.0337* 0.0321* 0.0914
BDO 0.7608 0.1371 0.0034*
BD1 0.3880 0.0084* 0.0173*
Natural Area
Habitat T P T*P
OM 0.8014 0.6972 0.4798 0.6831
pH 0.8814 0.1986 0.2913 0.8687
NO3-N 0.8914 0.5190 0.1257 0.0713
P 0.5158 0.3597 0.7868 0.9126
K 0.5103 0.9695 0.8329 0.9674
Ca 0.5393 0.5565 0.5939 0.8010
Mg 0.4701 0.4383 0.4336 0.7093
BDO 0.5005 0.2287 0.2113 0.6802
BD1 0.8757 0.5124 0.8393 0.6669
+SRWC P(C*S) was not testable.









Table 4-16 Average soil means by slope position (1 at top of slope sand; 4 at bottom of
slope-clay). Values with the same letter are not different (p=0.05) among
slope positions.
Slope OM pH NO3-N p K Ca Mg BDO BD1
1 1.7b 6.2c 8.4a 454a 145a 2709a 930a 0.70b 0.93a
2 6.5a 6.3bc 12.5a 622a 216a 3797a 1430a 0.99a 1.07a
3 6.8a 6.5b 9.8a 535a 197a 3187a 1150a 0.55b 0.75b
4 7.3a 6.8a 14a 530a 152a 2939a 971a 0.55b 0.71b

A greater BD is typically observed on sandier soils than clay soils because solid

particles of the fine-textured soils typically are structured in porous granules, even more

so when SOM is present in high amounts. These aggregated soils have pores that exist

between and within granules (Brady and Weil 2002). NO3 is prone to leaching since its

anionic form is not tightly held to the negatively charged clay and SOM.

The mulch treatment had the lowest SOM. This could be due to the gradual

breakdown of mulch and insufficient time for decomposition into SOM. Greater SOM

should occur with time due to the tree biomass. Mulch decomposition takes 1 to 2 years

(Black et al. 1994) depending on species, wood size, numbers and types of soil

decomposing microorganisms, moisture, temperature, and other climatic variables. After

a year, some types of mulch have only decomposed 3 to 7% (Duryea et al. 1999),

depending on the lignin content. In other studies, mulch treatments increased SOM

(Borland 1990; Black et al. 1994). The mulch treatment also had the least TPCC for

herbaceous species, which could contribute to a lower SOM. The pH in CSAs usually

ranges from 7 to 8.3 (Stricker 2000). In this study it was lower. This could be attributed

to the litter contributed from the thick canopy of herbaceous species, primarily hairy

indigo, which dominated the site in September 2005. Accumulation of SOM acidifies

soil and forms soluble complexes with nutrients such as Ca and Mg (Brady and Weil

2002).









SOM was greatest in the cypress block, which is at the bottom of the slope.

Cypress had a similar Duncan's grouping as cottonwood for SOM, but differed from E.

amplifolia, E. grandis, and Pinus elliottii. This could be attributed to the fact that slash

pine and E. grandis are planted in the sandier, more elevated portions of the field.

Cypress and cottonwood also had the highest pH and NO3 levels. NO3 levels were not

abnormally high in the SRWC area. NO3 is weakly held by soils and readily leaches,

unless there is a high anion exchange capacity (Sparks 2003). Cottonwood had less Ca

and Mg than most other short rotation woody crops (E. grandis had slightly less), and

grew the fastest. Poplars are characterized as nutrient demanding species due to their

fast-growing nature (Bergez et al. 1989), which explains why cottonwood had less Ca

and Mg in the soils. Soils at the SRWC site have the same characteristics of sites that

grow cottonwood best: BD less than 1.4 g/cm3, pH of 5.5 to 7.5, and greater than 2%

SOM (Baker and Broadfoot 1979). Phosphatic clay naturally has high levels of

phosphorus, calcium, magnesium, and potassium (Stricker 2000).

Slash pine had the overall greatest surface and subsurface BD and cypress and

cottonwood had the lowest, these bulk densities can be attributed to the slope position in

the study area and therefore, due to the consistency of the soil at that location. Due to the

expanding and shrinking nature of clay soil (Brady and Weil 2002), large breaks form on

the surface during dry periods. Large volumes of water enter these cracks in the

beginning of a wet period; upon soil saturation, the cracks are closed due to swelling.

Because of this characteristic, BD of montmorillonite clay soil experiences fluctuations

with the amount of water available. This clay expansion could attribute to a low BD in

the cottonwood and cypress study area. Among species and cultures, few soil properties









were significantly different. Similar results were observed at the Lakeland site across

species (Tamang 2005).

In comparison to another CSA fast-growing tree farm in the central Florida area,

pH was 7.5 +/- 0.3 (Tamang 2005). Soil pH in the SRWC area was -6.5. Soil pH of the

state soil of Florida (Myakka fine sand) is 5.7 (Alva et al., 2000). Lower pHs may

facilitate the return of native plants to the site. SOM in the SRWC site (5.4%) was

similar to the Lakeland site (5.37%). This value is expected to decrease with stand

maturity. As time progresses in eucalypt stands, SOM drops as mineralization and tree

growth occurs (Loumeto and Bernhard-Reversat 2001); fast-growing trees at the

Lakeland site have been growing for 4 years. The SRWC area has slightly greater

SOM and this may be due to a lower pH. Soil pH depends upon the presence of SOM.

Accumulation of SOM acidifies soil (Brady and Weil 2002). Phosphorus was much

lower in the SRWC site (527 mg/kg) than at the Lakeland operational area site (4053

mg/kg) (Tamang 2005). However in the Lakeland SRWC-90 site, extracted with water, P

was -150 mg/kg (Tamang 2005). With ample micronutrients, SOM, and a slightly acidic

pH, this soil environment may catalyze the return of native plants to the site better than

the Lakeland site CSA.

NA

SOM was 5.6% in the natural area (Table 4-5). Values of P were very high in the

NA; this could be attributed to the nature of Nittaw soils, particulate matter dispersed

through the air and P runoff from the SRWC site. Nittaw soils are sandy clay loams; they

are poorly drained floodplains. These soils are enriched with phosphate (Polk County

Soil Survey, US Dept. of Ag, Soil Cons. Service 1990). High P levels may be due to

mining being carried out to the edges of the Peace River flood plain. The mining process









sends particulate matter in the atmosphere, which can land on nearby areas, like the NA.

2:1 clays, like montmorillonite clay, have relatively little capacity to bind phosphorus

(Brady and Weil 2002). In mineral soils, phosphate fixation is at its lowest when soil pH

is maintained from 6.0 to 7.0 (Brady and Weil 2002), as is present at the SRWC site.

Once P translocated to the NA, a higher water table may have prevented element

leaching. Wet sites have higher concentrations ofP (Marois and Ewel 1983).

Correlations

Correlations were run for individual SRWCs (Appendix B), all SRWCs combined,

and eucalypts combined (Table 4-5). Some trends were found between soil and tree

growth variables in the SRWC area (Table 4-5). For Eucalyptus grandis was positively

correlated to pH (p=0.0202). For cypress, vigor was positively correlated to NO3-N

(p=0.0312) and K (p=0.0150). No correlations were found between growth and soil

variables in the Myrtaceae family (eucalypts).

Pearson correlation coefficients for all SRWCs measured in January 2006

suggested that SOM and pH are positively correlated to height (0.43) (Table 4-5). Height

was positively correlated with survival (0.35) and negatively correlated with surface and

subsurface BD (-0.37 and -0.35, respectively). Root growth is constrained as BD

increases (Brady and Weil 2002).

Macronutrients were highly correlated to one another (Table 4-5). P was positively

correlated with Ca, Mg, and K for each species, but cypress. Same macronutrient trends

were seen with all the trees combined. P was positively correlated with K (0.74), Ca

(0.90), and Mg (0.88). K was positively correlated with Ca (0.81) and Mg (0.78). Ca

was also positively correlated with Mg (0.98). CSAs are fertile and nutrient rich lands

(Stricker 2000; Tamang 2005). Average pH of the SRWC area was 6.4; a pH value of









5.5 to 7 usually provides optimal conditions for plant nutrient levels. IfP is readily

available at a pH of 6.4, the other plant nutrients, if present in ample amounts, will be

satisfactorily available for most plants (Brady and Weil 2002). P had high concentrations

in the SRWC area (P. Bohlen, Archbold Biological Station, personal communication June

2006), so nutrients are not likely lacking.

Soil pH was positively correlated to SOM in the eucalypts (Table 4-5). SOM was

also positively correlated with NO3 (0.56). Most soil nitrogen occurs as part of organic

molecules (Brady and Weil 2002). P and K (0.67), P and Ca (0.92), P and Mg (0.92), Ca

and K (0.81), K and Mg (0.77), and Ca and Mg (0.99) had highly significant correlated

values above 0.65. Ca, Mg, and K should have highly correlated values because these

elements are involved in the cation exchange that occurs readily in montmorillonite clay

(Brady and Weil 2002). These positively charged minerals are made available to plants

when hydrogen ions in the soil displace the mineral ions from clay particles.














CHAPTER 5
CONCLUSIONS

Cottonwood was the fastest growing SRWC, but, it did not have the least

cogongrass present in the understory. Cottonwood had a cogongrass TSC value of 19%.

Both species of eucalypts had less cogongrass TSC than cottonwood. Slash pine was the

slowest growing species and had the greatest cogongrass TSC. There are multiple

reasons for cogongrass growing so well in the cottonwood block, even though

cottonwood was the fastest growing (4.5m in the first year). This may be attributed to the

deciduous nature of cottonwoods. Eucalypts keep their foliage year round reducing light

penetration. Cottonwoods facilitate cogongrass regrowth, by allowing light to filter to the

forest floor in the winter months and stimulating the cogongrass rhizomes. Fast-growing

tree species need a canopy cover that is not lost annually; otherwise cogongrass is likely

to return. Trees with a spreading and full canopy appear to reduce the growth and spread

of cogongrass as seen at the Lakeland CSA (Tamang 2005).

The mulch culture constrained vegetative growth, likely because little sun

penetrated the thick mulch layer. The mulch treatment had the lowest TPCC value, 20%.

TSC of cogongrass was least in the herbicide and mulch treatment. This may indicate

that cogongrass needs ample light to stimulate its rhizome growth. A disadvantage of the

mulch culture is that it does not discriminate among the species affected. The mulch

culture in the SRWC area had the lowest quadrat diversity; only two species were

observed in each quadrat. However, the CM site had lower TPCC than even the mulch

culture in the SRWC area and even less cogongrass TSC. Nonetheless, the CM study has









not been studied as long as the SRWC study and with time, TPCC and cogongrass TSC

could be greater.

More natives were present at the natural area than the SRWC area, but this was

expected because it was relatively undisturbed. The SRWC area is a disturbed ecosystem

and has only begun the primary stages of succession, characterized by many herbaceous,

shade-intolerant species. Avoiding disturbance helps to prevent exotic species invasion

(Stylinski and Allen 1999). Only three herbaceous species, three shrub species, and one

tree species were introduced species in the NA.

Natives are lacking in the SRWC area because dispersal means are poor, and a

thick canopy likely obstructed much of the dispersal pathways. If NA natives disperse

into the SRWC area, there is the obstacle of overcoming the presence of exotic species,

competition with cogongrass, and atypical Florida soil conditions.

If all lands infested by cogongrass in Florida were converted to naturally vegetated

communities through the employment of fast-growing trees, these phosphate mined lands

could be used as corridors connecting important lands for the native flora and fauna of

Florida. This conversion would provide invaluable landscape linkages, some 200,000 to

400,000 ha of land added to the Florida ecological network. These converted lands could

effectively conserve biological diversity in the presence of an encroaching human

population and habitat fragmentation. National parks are not enough to protect viable

populations of sensitive species and biodiversity as a whole (Noss and Harris 1986). A

large scale, connected reserve network is a crucial component for conserving the state's

biological diversity (Hoctor 2000). An ecological network will protect vital ecological






57


functions and biotic movement more than the current, isolated conservation areas (Harris

et al. 1996).














CHAPTER 6
FUTURE RESEARCH

Although this study has provided some insight into the control of cogongrass,

additional work will be necessary to make restoration of infested areas effective.

Cogonmashing, which can be done cheaply with minimal machinery, can constrain the

growth of cogongrass. Fast-growing eucalypts have the ability to catalyze plant

succession and reduce the time it takes to revert mined lands to more diverse natural

ecosystems. Fast-growing tree species in conjunction with cogonmashing may be the

most effective combination of methods currently available in the effort to eradicate

cogongrass and initiate a natural succession of native plants.

However, it is still not known what lasting effects would be observed. If trees are

harvested, the cogonmash would need to provide adequate control of cogongrass.

Overtime, the cogonmash will be recycled back into the soil and a dense understory of

native vegetation should prolong the control of cogongrass while eucalypts or other fast-

growing trees regenerate. Ongoing studies must measure the outcomes of these fast-

growing tree plantations. Tree harvest may allow cogongrass to return, but this also

needs to be explored. Whether or not it makes a difference if the understory is composed

of mainly native vegetation would be another topic that could be further examined.

Native ecosystems tend to resist invasion by exotics due to each niche already being

fulfilled. Upon disturbance, native ecosystems are much more vulnerable to introduced

species. Invasion would be most apparent at the borders of tree plantations.









It seems sufficient to reassess each site twice a year for vegetation. Few plants

were different between March and May 2006. A fall and spring sampling of the

vegetation should collectively assess all plants that establish in the sites. The influence of

native species on cogongrass control will be significant, but whether to allow natural

succession to occur or to facilitate it through the planting of native plants is a question

that needs to be addressed. The primary stages of succession usually yield many exotic

species, but with time these numbers dwindle and are replaced by beneficial natives.

However, the act of planting native plants has many uncertainties, such as survival. The

planted natives might fare better if they were treated with nutrients, especially nitrogen,

which tends to be limited on phosphate mined soils. More studies that explore which

native species are suitable for these clay settling areas would provide insight for future

reclamation and would likely enhance survival of well-adapted species.

Because cottonwoods and eucalypts are allelopathic, alternatives to these species

may be sought. Reducing allelopathy should promote the establishment of a more

diverse plant community. Another aspect that should be examined is to observe these

fast-growing tree plantations on a number of clay settling areas so any trends in soils or

vegetation could be identified.

It would also prove beneficial to quantify what seeds are dispersed into the SRWC

area. This could be accomplished through the use of seed traps distributed throughout the

research site. Dispersal studies are few and not much present data discuss the distances

specific species are able to disperse. This information would inform managers of the

distance the restoration sites should be from natural areas so that the benefits of natural

dispersal could be realized.
















APPENDIX A
VEGETATION


Table A-i Name and nativity of herbaceous species on all sites: short rotation woody
crop (SRWC), natural area (NA) and cogonmash (CM).


Scientific Name
Aeschynomene
indica
Ambrosia
artemissiifolia
Aster elliottii
Boehmeria
cylindrica
Carex
albolutescens
Chenopodium
ambrosioides
Chamaesyce
hypericifolia
Cirsium
horridulum
Cicuta maculata

Conzya
canadensis
Commelina
diffusa
Crotolaria
spectabilis
Cyperus
esculentus
Cyperus rotundus
Dichanthelium
commutatum
Drymaria cordata
Eclipta alba
Eleusine indica
Emiliafosbergii
Erechtites
hieraciifolius
Eupatorium
capillifolium
Galium tinctorum


Common Name
Indian jointvetch

Common Ragweed

Elliott's Aster
False Nettle

Green White Sedge

Mexican tea

Graceful Sandmat

Purple thistle

Spotted Water
Hemlock
Canadian Horsweed

Common Dayflower

Showy Rattlebox

Yellow Nutsedge

Nutgrass
Variable Witchgrass

[ndian Chickweed
False Daisy
Indian goosegrass
Florida tasselflower
American Bumweed

Dogfennel

Stiff Marsh Bedstraw


Herbs
Nativity
Exotic


Family
Fabaceae


Native Asteraceae

Native Asteraceae
Native Urticaceae

Native Cyperaceae


Exotic


Amaranthaceae


Native Euphorbiaceae


Native


Asteraceae


Native Apiaceae


Native

Exotic


Asteraceae

Commelinaceae


Exotic Fabaceae

Exotic Cyperaceae


Exotic
Native

Native
Native
Exotic
Exotic
Native

Native

Native


Cyperaceae
Poaceae

Caryophyllaceae
Asteraceae
Poaceae
Asteraceae
Asteraceae

Asteraceae

Rubiaceae


Sites
SRWC

SRWC, CM

SRWC
SRWC, NA

NA

SRWC

SRWC

SRWC, CM

NA

SRWC, CM

SRWC, NA

SRWC

SRWC, CM

SRWC
NA

NA
NA
SRWC
SRWC
NA

SRWC, NA, CM

NA


Table A-i Continued











Scientific Name
Geranium
carolinianum
Gnaphalium
falcatum
Habenaria repens

Heterotheca
subaxillaris
Hypoxis juncea

Hydrocotyle
umbellata
Imperata
cylindrical
Indigofera hirsuta
Lactuca
graminifolia
Michx.
Lepidium
virginicum
Lycopus
americanus
Medicago
lupulina
Melothria pendula
Oplismensus
hirtellus
Oxalis corniculata
Parietaria
floridana
Passiflora
incarnate
Phytolacca
americana
Physalis pruinosa
Ptilimnium
capillaceum
Richardia
brasiliensis
Sanicula
canadensis
Samolus
ebracteatus


Common Name
Carolina Geranium

Cudweed

Waterspider False
Reinorchid
Camphorweed

Fringed Yellow
Stargrass
Marshpennywort

Cogongrass

Hairy Indigo
Grassleaf Lettuce


Virginia Pepperweed

American
waterhorehound
Black medick

Creeping Cucumber
Basketgrass

Yellow Wood Sorrel
Florida pellitory

Purple Passionflower

American Pokeweed

Ground Cherry
Herbwilliam

Mexican clover

Canadian
Blacksnakeroot
Water pimpernel


Salvia lyrata Lyre leaf sage


Herbs
Nativity Family
Native Geraniaceae


Native


Asteraceae


Native Orchidaceae

Native Asteraceae

Native Hypoxidaceae

Native Araliaceae

Exotic Poaceae

Exotic Fabaceae
Native Asteraceae


Native


Brassicaceae


Native Lamiaceae

Exotic Fabaceae


Native
Native


Cucurbitaceae
Poaceae


Native Oxalidaceae
Native Urticaceae


Native

Native


Passifloraceae

Phytolaccaceae


Native Solanaceae
Native Apiaceae

Exotic Rubiaceae

Native Apiaceae

Native Primulaceae

Native Lamiaceae


Sites
SRWC

SRWC

NA

SRWC

NA

NA

SRWC, CM

SRWC
SRWC


SRWC

NA

SRWC, CM

NA
NA

SRWC, NA, CM


SRWC

SRWC

SRWC
SRWC, NA

SRWC

NA

NA










Table A-1 Continued


Scientific Name
Sesbania exaltata
Senecio vulgaris
Sesbania virgata
Sonchus asper
Striga
gesnerioides
Thelypteris kunthii
Triodanis
perfiolata
Vicia ludoviciana
Viola sororia
Unk NA 1
Unk NA 2 Carex
Unk NA 3
Ipomoea
Unk NA 4
Unk NA 5
Rorippa
Unk NA 6
Solanum
Unk NA 7
Unk SRWC 1
Unk SRWC 2
Unk SRWC 3
Unk SRWC 4
Unk SRWC 5
Unk SRWC 6
Unk SRWC 7
Unk SRWC 8


Common Name
Hemp sebania
Common groundsel
Wand riverhemp
Spiny sow thistle
Cowpea witchweed

Southern shield fern
Clasping Venus's
Lookingglass
Deerpea Vetch
Common Blue Violet


Herbs
Nativity
Native
Exotic
Exotic
Exotic
Exotic

Native
Native


Family
Fabaceae
Asteraceae
Fabaceae
Asteraceae
Orobanchaceae

Thelypteridaceae
Campanulaceae


Native Fabaceae
Native Violaceae
Asteraceae
Cyperaceae
Convolvulaceae

Orchidaceae
Brassicaceae

Solanaceae


Euphorbiaceae
Fabaceae
Poaceae
Poaceae


Sites
SRWC
NA
SRWC
SRWC, CM
SRWC

NA
SRWC

NA
NA
NA
NA
NA

NA
NA

NA

NA
SRWC
SRWC
SRWC
SRWC
SRWC
SRWC
SRWC
SRWC







63


Table A-2 Name and nativity of woody species on all sites: short rotation woody crop
(SRWC), natural area (NA), and cogonmash (CM).
Shrubs


Scientific
Acer rubrum
Ampelopsis arborea
Apios americana
Baccharis halimifolia

Carpinus caroliniana
Campsis radicans
Celtis laevigata
Cephalanthus occidentalis
Clematis crispa

Cornus foemenia
Fraxinus caroliniana
Hyptis mutabilis
Itea virginica
Lantana camera
Liquidambar ', ... itlo,
Ludwigia peruviana

Morus rubra
Myrica cerifera
Parthenocissus quinquefolia
Quercus laurifolia
Quercus nigra
Quercus virginiana
Rubus argutus
Sambucus canadensis
Sabal minor
Sabal palmetto
Serenoa repens
Smilax auriculata
Toxicodendrons radicans
Ulmus americana
Urena lobata
Vitis rotundifolia


Common
Red Maple
Peppervine
Groundnut
Saltbush/Groundsel
Tree
American Hornbeam
Trumpetcreeper
Sugarbeny
Buttonbush
Swamp Leather-
flower
Swamp dogwood
Pop Ash
Tropical Bushmint
Virginia Sweetspire
Lantana
Sweetgum
Peruvian Primrose
Willow
Red Mulberry
Wax Myrtle
Virginia Creeper
Laurel Oak
Water Oak
Live Oak
Sawtooth Blackberry
Elderberry
Dwarf Palmetto
Cabbage Palm
Saw Palmetto
Earleaf Greenbriar
Poison Ivy
American Elm
Caesarweed
Muscadine


Nativity
Native
Native
Native
Native

Native
Native
Native
Native
Native

Native
Native
Exotic
Native
Exotic
Native
Exotic

Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Exotic
Native


Family
Sapindaceae
Vitaceae
Fabaceae
Asteraceae

Betulaceae
Bignoniaceae
Celtidaceae
Rubiaceae
Ranunculaceae

Cornaceae
Oleaceae
Lamiaceae
Iteaceae
Verbenaceae
Altingiaceae
Onagraceae

Moraceae
Myricaceae
Vitaceae
Fagaceae
Fagaceae
Fagaceae
Rosaceae
Adoxaceae
Arecaceae
Arecaceae
Arecaceae
Smilaceae
Anacardiaceae
Ulmaceae
Malvaceae
Vitaceae


Sites
NA
NA
NA
SRWC, NA, CM

NA
NA
NA
NA
NA

NA
NA
NA
NA
NA
NA
SRWC, NA

NA
NA
NA
NA
NA
NA
NA
SRWC, NA
NA
NA
NA
NA
NA
NA
NA
NA











Table A-3 Name and nativity of all trees found in the Natural Area.
Trees
Scientific Name Common Persimmon Nativity Famil
Acer rubrum Red Maple Native Sapin
Carpinus caroliniana American Hornbeam Native Betul
Carya glabra Pignut Hickory Native Juglar


y
daceae
iceae
idaceae


Celtis laevigata
Citrus aurantium
Diospyros virginiana
Liquidambar .... ithl
Quercus laurifolia
Quercus nigra
Quercus virginana
Sabal palmetto
Taxodium distichum
Ulmus americana


Sugarbeny
Sour Orange
Common Persimmon
Sweetgum
Laurel Oak
Water Oak
Live Oak
Cabbage Palm
Bald Cypress
American Elm


Native
Exotic
Native
Native
Native
Native
Native
Native
Native
Native


Celtidaceae
Rutaceae
Ebenaceae
Altingiaceae
Fagaceae
Fagaceae
Fagaceae
Arecaceae
Cupressaceae
Ulmaceae


Table A-4 September 2005 SRWC herbaceous vegetation variables: TSC (total species
cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance
value index).


Species
Aeschynomene indica
Ambrosia artemissiifolia
Chamaesyce hypericifolia
Commelina diffusa
Crotolaria spectabilis
Cyperus esculentus
Cyperus rotundus
Eleusine indica
Emiliafosbergii
Eupatorium capillifolium
Imperata cylindrica
Indigofera hirsuta
Passiflora incarnata
Phytolacca americana
Physalis pruinosa
Richardia brasiliensis
Sesbania exaltata
Sesbania virgata
Sonchus asper
Striga gesnerioides
Unk SRWC1
Unk SRWC2
Unk SRWC3
Unk SRWC 6
Unk SRWC 7


TSC
7.7
18.9
1.0
2.5
7.4
5.0
0.5
5.3
0.5
3.3
14.1
53.9
11.3
12.5
8.8
0.5
17.5
19.2
7.5
7.2
0.5
7.5
2.5
2.5
7.5


TPCC
73.5
100.3
76.6
68.8
75.9
93.6
86.0
98.9
94.0
43.8
88.7
75.3
74.1
94.0
94.5
21.8
56.5
100.2
48.7
96.8
85.7
95.5
76.0
85.0
87.0


IVI
103.2
80.1
64.7
62.0
60.5
93.3
60.6
64.2
30.5
79.0
107.5
213.6
92.0
68.3
67.3
116.3
92.7
68.9
72.0
60.2
32.2
69.4
33.8
40.1
97.4











Table A-5 March 2006 SRWC herbaceous vegetation variables: TSC (total species
cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance
value index).
Species N TSC F TPCC IVI
Ambrosia artemissiifolia 11 8.9 1.8 55.1 82.6
Boehmaria cylindrica 1 85.0 2.0 91.0 286.0
Chamaesyce hypericifolia 7 1.9 1.9 57.2 69.6
Conzya canadensis 37 1.5 2.5 29.2 94.5
Cyperus esculentus 7 1.3 1.6 30.6 56.8
Emiliafosbergii 2 0.5 1.0 14.2 33.8
Eupatorium capillifolium 19 1.3 1.9 19.2 73.0
Geranium carolinianum 1 0.5 1.0 11.0 33.9
Gnaphaliumfalcatum 23 9.0 2.4 25.9 120.2
Imperata cylindrica 16 22.3 2.6 36.1 138.2
Lactuca graminifolia 18 3.9 2.0 35.7 76.4
Medicago lupulina 1 10.0 2.0 61.0 83.9
Oxalis corniculata 11 1.1 1.6 28.5 59.5
Passiflora incarnata 15 2.3 2.0 41.1 83.2
Phytolacca americana 2 2.0 1.5 33.7 56.4
Ptilimnium capillaceum 5 2.0 2.0 56.3 82.5
Richardia brasiliensis 4 4.0 1.3 36.4 61.4
Sonchus asper 37 3.0 2.9 28.3 125.0
Triodanis perfiolata 2 0.5 1.0 10.1 38.4
Unk SRWC 4 2 1.5 1.0 31.2 47.0
Unk SRWC 8 2 2.5 2.0 15.6 79.4

Table A-6 May 2006 SRWC herbaceous vegetation variables: TSC (total species cover),
F (frequency), TPCC (total plant canopy cover), and IVI (importance value
index).
Species N TSC F TPCC IVI
Ambrosia artemissiifolia 11 7.6 1.5 52.0 64.0
Aster elliottii 1 2.5 1.0 8.0 63.9
Boehmaria cylindrica 2 38.1 2.0 46.6 189.1
Chamaesyce hypericifolia 4 9.1 2.8 57.8 101.7
Cirsium horridulum 1 2.5 1.0 5.5 95.5
Conzya canadensis 38 2.3 2.6 28.6 102.6
Cyperus esculentus 5 1.3 1.2 51.5 39.1
Emiliafosbergii 3 1.2 1.3 7.7 61.3
Eupatorium capillifolium 27 1.3 1.9 24.0 84.8
Gnaphaliumfalcatum 20 9.6 2.2 27.2 115.7
Heterotheca subaxillaris 6 4.7 1.2 46.5 57.9
Imperata cylindrica 14 24.9 2.8 37.6 159.1
Lactuca graminifolia 26 3.5 1.9 25.6 75.8
Lepidium virginicum 1 0.5 1.0 58.0 28.4
Oxalis corniculata 8 2.6 1.8 24.0 68.1
Passiflora incarnata 16 3.3 2.0 40.6 78.8
Phytolacca americana 2 9.5 1.5 29.5 83.4
Ptilimnium capillaceum 4 1.3 1.8 35.7 87.5
Richardia brasiliensis 5 3.7 2.4 51.1 86.8
Sonchus asper 20 0.9 1.9 20.6 87.8
Unk SRWC 5 3 0.5 1.3 4.7 60.9










Table A-7 May 2006 NA herbaceous vegetation variables: TSC (total species cover), F
(frequency), TPCC (total plant canopy cover), and IVI (importance value
index).
Species N TSC F TPCC IVI
Boehmaria cylindrica 5 1.1 1.2 23.5 78.9
Carex albolutescens 1 0.5 1.0 154.5 52.2
Cicuta maculata 1 85.0 1.0 154.5 123.7
Dicanthelium commutatum 3 3.7 1.7 71.3 103.6
Drymaria cordata 1 0.5 1.0 154.5 52.2
Eclipta alba 1 0.5 1.0 7.0 69.6
Erechtites hieraciifolius 2 0.5 1.0 29.5 61.2
Eupatorium capillifolium 2 0.5 1.0 29.5 61.2
Galium tinctorum 1 0.5 1.0 154.5 54.1
Hypoxisjuncea 1 0.5 1.0 52.0 52.8
Hydrocotyle umbellata 4 10.3 1.3 64.4 125.0
Lycopus americana 1 0.5 1.0 31.5 54.2
Melothria pendula 1 0.5 1.0 7.5 64.1
Oplismensus hirtellus 2 0.5 1.5 87.0 94.4
Oxalis corniculata 1 0.5 2.0 52.0 104.6
Parietariafloridana 1 0.5 1.0 154.5 52.2
Ptilimnium capillaceum 2 1.0 1.5 29.5 94.3
Samolus ebracteatus 1 2.5 1.0 31.5 83.9
Salvia lyrata 2 1.5 1.0 81.0 78.9
Thelypteris kunthii 3 27.5 1.0 68.5 113.3
Vicia ludoviciana 2 0.5 1.5 103.3 77.5
Viola sororia 2 1.0 1.5 19.5 103.8
UnkNA2 3 8.5 1.3 68.5 103.4
UnkNA6 1 0.5 1.0 7.5 64.1










Table A-8 March 2006 NA herbaceous vegetation variables: TSC (total species cover), F
(frequency), TPCC (total plant canopy cover), and IVI (importance value
index).
Species TSC F TPCC IVI
Boehmaria cylindrica 5 1.1 1.2 23.5 78.7
Carex albolutescens 1 0.5 1.0 154.5 52.2
Cicutamaculata 1 85.0 1.0 154.5 123.7
Dicanthelium commutatum 3 3.7 1.7 71.3 103.3
Drymaria cordata 1 0.5 1.0 154.5 52.2
Eclipta alba 1 0.5 1.0 7.0 69.6
Erechtites hieraciifolius 2 0.5 1.0 29.5 61.1
Eupatorium capillifolium 2 0.5 1.0 29.5 61.1
Galium tinctorum 1 0.5 1.0 154.5 54.1
Hypoxisjuncea 1 0.5 1.0 52.0 52.5
Hydrocotyle umbellata 4 10.3 1.3 64.4 126.9
Lycopus americana 1 0.5 1.0 31.5 54.4
Melothria pendula 1 0.5 1.0 7.5 64.1
Oplismensus hirtellus 2 0.5 1.5 87.0 94.4
Oxalis corniculata 1 0.5 2.0 52.0 104.0
Parietariafloridana 1 0.5 1.0 154.5 52.2
Ptilimnium capillaceum 2 1.0 1.5 29.5 94.1
Samolus ebracteatus 1 2.5 1.0 31.5 85.7
Salvialyrata 2 1.5 1.0 81.0 78.9
Thelypteris kunthii 3 27.5 1.0 68.5 113.4
Vicia ludoviciana 2 0.5 1.5 103.3 77.3
Viola sororia 2 1.0 1.5 19.5 103.8
UnkNA2 3 8.5 1.3 68.5 101.3
UnkNA6 1 0.5 1.0 7.5 64.1







68



Table A-9 September 2006 NA herbaceous vegetation variables: TSC (total species
cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance
value index).
Species N TSC F TPCC IVI
Boehmaria cylindrica 2 1.5 1.0 25.0 67.6
Cicuta maculata 2 20.0 1.0 47.8 99.8
Commelina diffusa 1 0.5 1.0 27.0 54.0
Dicanthelium commutatum 4 2.4 1.3 27.4 89.1
Drymaria cordata 1 2.5 1.0 68.5 78.6
Habenaria repens 1 0.5 1.0 68.5 53.9
Hydrocotyle umbellata 5 1.3 1.2 18.2 103.7
Melothria pendula 2 1.5 1.0 47.8 55.4
Oplismensus hirtellus 3 2.5 1.0 39.5 74.1
Parietariafloridana 2 0.5 1.0 7.0 80.7
Sambucus canadensis 1 2.5 1.0 12.0 88.7
Thelypteris kunthii 4 11.3 1.0 32.6 96.4
Viola sororia 2 1.5 1.0 19.5 62.4
Unk NA1 1 0.5 1.0 12.0 61.3
UnkNA2 2 2.5 1.0 47.8 59.1
UnkNA3 1 0.5 1.0 12.0 57.7
Unk NA4 1 0.5 1.0 68.5 53.9
UnkNA5 1 0.5 1.0 27.0 58.2
UnkNA7 1 0.5 1.0 27.0 54.0

Table A-10 March 2006 CM herbaceous vegetation variables: TSC (total species cover),
F (frequency), TPCC (total plant canopy cover), and IVI (importance value
index).
Species N TSC F TPCC IVI
Cirsium horridulum 1 17.5 1.0 25.5 101.2
Eupatorium capillifolium 2 2.0 1.5 14.0 77.8
Imperata cylindrica 2 0.5 3.5 14.0 117.8
Oxalis corniculata 2 1.5 1.0 14.0 49.5
Sonchus asper 1 2.5 1.0 25.5 42.3

Table A-11 May 2006 CM herbaceous vegetation variables: TSC (total species cover), F
(frequency), TPCC (total plant canopy cover), and IVI (importance value
index).
Species N TSC F TPCC IVI
Ambrosia artemissiifolia 1 0.5 1.0 8.5 30.8
Cirsium horridulum 1 17.5 1.0 24.3 98.2
Conzya canadensis 1 2.5 1.0 8.5 54.3
Cyperus esculentus 1 0.5 1.0 8.5 30.8
Eupatorium capillifolium 2 3.4 2.5 16.4 79.9
Imperata cylindrica 2 0.5 5.0 16.4 142.7
Medicago lupulina 1 0.5 1.0 24.3 28.3
Oxalis corniculata 2 1.5 1.0 16.4 33.6
Sonchus asper 1 0.5 1.0 24.3 28.3







69



Table A-12 September 2005 NA woody species vegetation variables: TSC (total species
cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance
value index).
Species N TSC F TPCC IVI
Acer rubrum 2 2.5 1.5 85.0 91.4
Apios americana 1 0.5 1.0 112.5 52.9
Baccharis halimifolia 3 23.3 1.3 103.7 98.0
Carpinus caroliniana 2 32.5 1.0 83.0 84.1
Campsis radicans 2 1.5 1.0 116.0 55.6
Celtis laevigata 2 10.0 1.0 116.0 60.6
Cepahalanthus occidentalis 1 0.5 1.0 108.5 50.5
Clematis crispa 3 6.5 1.3 114.8 79.8
Hyptis mutabilis 2 2.5 1.0 99.3 59.3
Itea virginica 1 17.5 1.0 108.5 150.7
Liquidambar u.... ,l,l, 1 7.5 1.0 112.5 59.2
Ludwigiaperuviana 2 20.0 1.0 85.0 100.6
Parthenocissus quinquefolia 1 0.5 2.0 141.0 102.4
Quercus laurifolia 2 1.0 1.5 126.8 84.4
Quercus nigra 2 5.0 1.0 99.8 54.8
Quercus virginiana 1 2.5 1.0 112.5 59.7
Rubus argutus 2 1.5 1.0 126.8 58.6
Sambucus canadensis 1 17.5 1.0 141.0 66.6
Sabal minor 3 14.2 1.0 102.3 71.8
Sabal palmetto 1 7.5 1.0 91.0 58.2
Serenoa repens 1 37.5 1.0 91.0 115.2
Smilax auriculata 1 2.5 1.0 57.5 79.3
Ulmus americana 4 15.3 1.5 83.5 138.3
Urena lobata 3 29.7 1.3 114.8 132.1
Vitis rotundifolia 1 0.5 2.0 141.0 102.4












Table A-13 March 2006 NA woody species vegetation variables: TSC (total species
cover), F (frequency), TPCC (total plant canopy cover), and IVI (importance
value index).
Species TSC F TPCC IVI
Acer rubrum 3 11.3 1.7 87.5 107.6
Ampelopsis arborea 4 1.0 1.0 94.9 56.4
Apios americana 1 7.5 1.0 90.5 66.6
Baccharis halimifolia 3 39.8 1.7 89.5 143.5
Carpinus caroliniana 4 25.0 1.5 111.5 104.2
Campsis radicans 2 0.5 1.0 75.8 58.0
Celtis laevigata 1 9.0 2.0 117.0 108.8
Cephalanthus occidentalis 1 2.5 1.0 111.0 57.3
Clematis crispa 2 6.3 1.5 103.8 89.2
Cornusfoemenia 1 37.5 1.0 111.0 93.8
Fraxinus caroliniana 1 2.5 1.0 61.0 58.4
Itea virginica 1 7.5 1.0 111.0 96.8
Lantana camera 1 0.5 1.0 117.0 51.5
Liquidambar u.... ,l,l, 1 7.5 1.0 90.5 60.0
Ludwigiaperuviana 2 5.0 1.0 75.8 72.2
Morus rubra 1 0.5 1.0 137.0 52.3
Myrica cerifera 1 2.5 1.0 111.0 57.3
Parthenocissus quinquefolia 1 1.5 2.0 117.0 103.4
Quercus laurifolia 3 1.5 1.7 106.2 88.3
Quercusnigra 2 5.0 1.0 103.8 57.9
Quercus virginiana 2 10.0 1.0 127.0 58.9
Rubus argutus 2 1.5 1.0 103.8 54.8
Sambucus canadensis 1 0.5 1.0 90.5 52.2
Sabal palmetto 1 37.5 1.0 137.0 79.3
Serenoa repens 1 17.5 1.0 137.0 62.8
Smilax auriculata 3 1.2 1.0 105.0 54.5
Toxicodendrons radicans 4 2.0 1.0 113.9 59.4
Ulmus americana 3 18.3 1.7 58.8 165.3
Urenalobata 4 4.6 1.3 120.4 100.9
Vitis rotundifolia 1 2.5 1.0 117.0 55.3












Table A-14 May 2006 NA woody species vegetation variables: TSC (total species cover),
F (frequency), TPCC (total plant canopy cover), and IVI (importance value
index).
Species N TSC F TPCC IVI
Acer rubrum 3 11.3 1.7 81.2 108.7
Ampelopsis arborea 4 1.0 1.0 90.4 56.4
Apios americana 1 7.5 1.0 90.0 66.7
Baccharis halimifolia 3 39.8 1.7 87.2 153.3
Carpinus caroliniana 3 17.2 1.3 90.3 93.0
Campsis radicans 2 0.5 1.0 71.8 58.1
Celtis laevigata 1 9.0 2.0 118.0 108.5
Cephalanthus occidentalis 1 2.5 1.0 100.0 57.5
Clematis crispa 2 6.3 1.5 104.0 88.7
Cornusfoemenia 1 37.5 1.0 100.0 97.5
Fraxinus caroliniana 1 2.5 1.0 53.5 59.0
Itea virginica 1 7.5 1.0 100.0 97.5
Lantana camera 1 0.5 1.0 118.0 51.3
Liquidambar ..u..l ,1,, 1 7.5 1.0 90.0 60.0
Ludwigiaperuviana 1 2.5 1.0 90.0 56.1
Morusrubra 1 0.5 1.0 117.5 54.0
Myrica cerifera 1 2.5 1.0 100.0 57.5
Parthenocissus quinquefolia 1 2.5 2.0 118.0 104.9
Quercus laurifolia 4 1.3 1.3 106.5 66.5
Quercusnigra 2 5.0 1.0 104.0 57.9
Quercus virginiana 2 10.0 1.0 117.8 60.8
Rubus argutus 2 1.5 1.0 104.0 54.5
Sambucus canadensis 1 0.5 1.0 90.0 52.2
Sabal palmetto 1 37.5 1.0 117.5 85.5
Serenoa repens 1 37.5 1.0 117.5 81.9
Smilax auriculata 3 1.2 1.0 96.3 55.6
Toxicodendrons radicans 4 2.0 1.0 106.4 60.1
Ulmus americana 3 16.5 1.7 54.5 166.5
Urena lobata 3 5.7 1.7 108.5 133.9
Vitis rotundifolia 1 2.5 1.0 118.0 54.9





Table A-15 Shrub frequency (%) for all sites (NA, SRWC, and CM). Frequencies
calculated according to total number of plots found within 12 quadrats (NA),
160 (SRWC), and 12 quadrats (CM), respectively.
Shrubs NA F SRWC F CM F
Acer rubrum 42
Ampelopsis arborea 33
Apios Americana 8
Baccharis hamilifolia 42 42 25
Carpinus caroliniana 42
Campsis radicans 33
Celtis laevigata 25
Cephalanthus occidentalis 17
Clematis crispa 33
Cornusfoemenia 8
Fraxinus caroliniana 8
Hyptis mutabilis 17
Itea virginica 8
Lantana camera 8
Liquidambar 'yh .... jtl 8
Ludwigia peruviana 25 17
Morus rubra 8
Myrica cerifera 8
Parthenocissus quinquefolia 17
Quercus laurifolia 42
Quercus nigra 33
Quercus virginiana 25
Rubus argutus 17
Sambucus canadensis 17 1
Sabal minor 25
Sabal palmetto 8
Serenoa repens 8
Smilax auriculata 33
Toxicodendrons radicans 33
Ulmus americana 67
Urena lobata 42
Vitis rotundifolia 17












Table A-16 Vegetation variables of all SRWC herbaceous species. Total species cover
(TSC), frequency (F) of 4 quadrats, density (D), total plant canopy cover
(TPCC), and importance value index (IVI).
Species N TSC F D TPCC IVI
Aeschynomene indica 22 7.66 2.23 2.60 73.52 103.2
Ambrosia artemissiifolia 25 9.55 1.68 6.95 59.18 74.14
Aster elliottii 1 2.50 1.00 2.00 8.00 63.94
Boehmeria cylindrica 3 53.75 2.00 90.33 61.42 221.4
Chenopodium ambrosioides 11 4.48 2.18 7.83 57.38 81.28
Chamaesyce hypericifolia 2 1.00 2.00 2.75 76.63 64.75
Cirsium horridulum 1 2.50 1.00 1.00 5.50 95.45
Conzya canadensis 75 1.91 2.53 3.16 28.90 98.59
Commelina diffusa 1 2.50 1.00 1.00 68.75 61.97
Crotolaria spectabilis 8 7.42 1.50 1.66 75.94 60.54
Cyperus esculentus 19 2.68 1.58 7.39 59.28 65.6
Cyperus rotundus 1 0.50 2.00 1.50 86.00 60.58
Eleusine indica 4 5.25 1.50 4.17 98.94 64.16
Emiliafosbergii 6 0.83 1.17 1.58 24.23 47.02
Eupatorium capillifolium 49 1.44 1.90 3.17 23.35 79.9
Geranium carolinianum 1 0.50 1.00 1.00 11.00 33.94
Gnaphaliumfalcatum 43 9.24 2.30 13.53 26.51 118.1
Heterotheca subaxillaris 6 4.67 1.17 1.25 46.50 57.9
Imperata cylindrica 44 20.52 2.61 10.74 53.29 135.1
Indigofera hirsuta 41 53.90 3.39 5.63 75.29 213.6
Lactuca graminifolia Michx. 44 3.67 1.93 6.55 29.73 76.01
Lepidium virginicum 1 0.50 1.00 1.00 58.00 28.43
Medicago lupulina 1 10.00 2.00 10.50 61.00 83.89
Oxalis corniculata 19 1.73 1.68 2.76 26.58 63.13
Passiflora incarnata 42 5.03 1.95 2.80 49.53 83.82
Phytolacca americana 5 7.10 1.60 4.90 44.06 69.56
Physalis pruinosa 2 8.75 2.00 1.00 94.50 67.35
Ptilimnium capillaceum 9 1.69 1.89 6.67 47.14 84.74
Richardia brasiliensis 11 3.20 1.82 3.52 40.41 82.93
Sesbania exaltata 1 17.50 1.00 1.00 56.50 92.74
Sesbania virgata 3 19.17 1.00 1.33 100.17 68.87
Sonchus asper 60 2.48 2.43 3.76 26.78 110
Striga gesnerioides 5 7.20 1.40 3.73 96.75 60.24
Triodanis perfiolata 2 0.50 1.00 1.00 10.05 38.38
Unk SRWC1 3 0.50 1.00 1.00 85.67 32.22
Unk SRWC2 1 7.50 2.00 1.50 95.50 69.39
Unk SRWC3 1 2.50 1.00 1.00 76.00 33.85
Unk SRWC4 4 1.50 1.00 1.75 31.20 47.06
Unk SRWC5 3 0.50 1.33 1.33 4.67 60.94
Unk SRWC6 1 2.50 1.00 1.00 85.00 40.06
Unk SRWC7 1 7.50 3.00 1.00 87.00 97.41
Unk SRWC8 2 2.50 2.00 5.50 15.60 79.44











Table A-17 Vegetation variables of NA herbaceous species. Total species cover (TSC),
standard deviation (SD), total plant canopy cover (TPCC), and importance
value index (IVI).


Species
Boehmaria cylindrica
Carex albolutescens
Cicuta maculata
Commelina diffusa
Dicanthelium commutatum
Drymaria cordata
Eclipta alba
Erechtites hieraciifolius
Eupatorium capillifolium
Galium tinctorum
Habenaria repens
Hypoxis juncea
Hydrocotyle umbellata
Lycopus americana
Melothria pendula
Oplismensus hirtellus
Oxalis corniculata
Parietariafloridana
Ptilimnium capillaceum
Samolus ebracteatus
Salvia lyrata
Sambucus canadensis
Thelypteris kunthii
Vicia ludoviciana
Viola sororia
Unk NA 1
Unk NA 2 Carex
Unk NA 3 Ipomoea
Unk NA 4
Unk NA 5 Rorippa
Unk NA 6 Solanum
Unk NA 7


N TSC
12 1.2
2 0.5
4 52.5
1 0.5
10 3.2
3 1.2
2 0.5
4 0.5
4 0.5
2 0.5
1 0.5
2 0.5
13 6.8
2 0.5
4 1
7 1.4
4 0.5
4 0.5
4 1
2 2.5
4 1.5
1 2.5
10 21
4 0.5
6 1.2
2 0.5
8 7
1 0.5
1 0.5
1 0.5
2 0.5
1 .5


SD TPCC
0.9 24
0 155
40.2 101
0 27
3.3 54
1.2 126
0 7
0 30
0 30
0 155
0 69
0 52
13.7 47
0 32
1 28
1.1 67
0 30
0 81
0.6 30
0 32
1.2 81
0 12
22.9 54
0 103
0.8 20
0 7
9.6 63
0 12
0 68.5
0 27
0 8
0 27


SD
16
0
64
0
58
50
0
26
26
0
0
0
49.8
0
28.8
62.4
0
85.2
26
0
84.9
0
55.0
59.2
11.7
7.1
58
0
0
0
0
0


IVI SD
77 20.9
52 0
112 32.7
54 0
98 37.7
61 15.3
70 0
61 9.8
61 9.8
54 0
54 0
53 0.2
117 47.2
54 0.13
60 5.1
86 18.4
84 0.4
66 20.9
94 13.9
85 1.3
79 30.8
89 0
107 36.7
77 28.6
90 49.2
81 22.3
92 53.8
58 0
54 0
58 0
64 0
54 0










Table A-18 Vegetation variables of NA woody species. Total species cover (TSC),
standard deviation (SD), total plant canopy cover (TPCC), and importance
value index (IVI).
Species N TSC SD TPCC SD IVI SD
Acer rubrum 8 9.13 5.77 84.50 24.01 103.97 30.32
Ampelopsis arborea 8 1.00 0.93 92.63 24.41 56.43 4.79
Apios americana 3 5.17 4.04 97.67 12.85 62.08 7.91
Baccharis halimifolia 9 34.33 20.72 93.44 31.11 131.63 45.63
Carpinus caroliniana 9 24.06 20.15 98.11 32.97 96.00 33.75
Campsis radicans 6 0.83 0.82 87.83 30.81 57.26 5.43
Celtis laevigata 4 9.50 6.15 116.75 20.43 84.64 27.91
Cephalanthus occidentalis 3 1.83 1.15 106.50 5.77 55.07 3.99
Clematis crispa 7 6.36 5.60 108.57 19.18 85.02 24.69
Cornusfoemenia 2 37.50 0.00 105.50 7.78 95.64 2.63
Fraxinus caroliniana 2 2.50 0.00 57.25 5.30 58.73 0.41
Hyptis mutabilis 2 2.50 0.00 99.25 59.04 59.31 1.82
Itea virginica 3 10.83 5.77 106.50 5.77 115.00 30.96
Lantana camera 2 0.50 0.00 117.50 0.71 51.42 0.11
Liquidambar styraciflua 3 7.50 0.00 97.67 12.85 59.71 0.47
Ludwigiaperuviana 5 10.50 15.25 82.30 22.95 80.36 39.59
Morusrubra 2 0.50 0.00 127.25 13.79 53.12 1.23
Myrica cerifera 2 2.50 0.00 105.50 7.78 57.38 0.18
Parthenocissus 3 1.50 1.00 125.33 13.58 103.57 1.22
quinquefolia
Quercus laurifolia 9 1.28 0.83 110.89 15.88 77.74 28.30
Quercusnigra 6 5.00 2.74 102.50 13.56 56.88 2.48
Quercus virginiana 5 8.50 8.22 120.40 9.54 59.82 6.86
Rubus argutus 6 1.50 1.10 111.50 19.22 55.97 4.67
Sambucus canadensis 3 6.17 9.81 107.17 29.30 57.01 8.29
Sabalminor 3 14.17 5.77 102.33 42.09 71.77 8.78
Sabalpalmetto 3 27.50 17.32 115.17 23.09 74.33 14.28
Serenoa repens 3 30.83 11.55 115.17 23.09 86.63 26.53
Smilax auriculata 7 1.36 1.07 94.50 35.51 58.53 9.26
Toxicodendrons radicans 8 2.00 0.93 110.13 15.94 59.77 4.88
Ulmus americana 10 16.55 6.29 67.40 36.00 154.84 103.08
Urenalobata 10 12.45 18.95 115.15 19.64 120.15 47.69
Vitis rotundifolia 3 1.83 1.15 125.33 13.58 70.88 27.33

















APPENDIX B
SOILS

Table B-1 Pearson correlation coefficients for Populus deltoides growth variables: height
at 14 months (H14), 14 mo. diameter at breast height (D14), 14 mo. survival
(S14), 14 mo. vigor (V14), basal area per hectare (BAH) and soil variables:
organic matter (OM), bulk density (BD) of corresponding slope positions in


H14
D14
S14
V14
BAH
OM
pH
NO3-N


the SRWC area.
H14 D14 S14 V14
1 0.96* 0.95* -0.72*
1 0.91* -0.61
1 -0.53
1


BAH
0.97*
0.94*
0.97*
-0.68*
1


0'
-0.0
-0.0
-0.0
-0.1
-0.0


A p]
3 0.3
1 0.5
5 0.2
3 0.0
8 0.2
1 -0.1


H NO3-
0 -0.5
2 -0.5
4 -0.5
1 0.5
7 -0.5
8 -0.2
1 -0.0


N
;6 0.1
;1 0.2
;5 -0.0
5 -0.3
;6 0.0
:6 0.4
)9 0.4
1 -0.3


P
5 -0.0
2 0.0
4 -0.1
4 -0.1
5 -0.0
4 0.3
3 0.3
8 -0.4
1 0.89


K C
5 -0.0
0 0.0
6 -0.1
3 -0.2
9 -0.0
1 0.4
2 0.1
9 -0.2
'* 0.91
1 0.81


?a Mg
'3 -0.08
14 0.01
8 -0.23
4 -0.18
,8 -0.12
.8 0.46
6 0.20
26 -0.24
* 0.89*
* 0.81*
1 0.99*
1


BD
-0.56
-0.31
-0.41
-0.41
-0.16
-0.56
-0.08
0.51
-0.21
-0.26
-0.08
-0.05


Table B-2 Pearson correlation coefficients for Pinus elliottii and Taxodium distichum
growth variables: 11 mo. height (H11), 11 mo. vigor (V11), and 11 mo.
survival (S 11) and soil variables: organic matter (OM) and bulk density (BD)
of corresponding slope positions in the SRWC area.


Hll
V11
Sll
OM
pH
NO3-N
P
K
Ca
Mg
BD


Hll
1
0.98
-0.07
0.55
0.91
0.99
0.89
0.98
0.38
0.30
0.00


VI1
-0.85*
1
0.14
0.36
0.98
0.99*
0.78
0.99*
0.56
0.49
0.21


Sll
0.69*
-0.90*
1
-0.87
0.34
0.09
-0.51
0.11
0.90
0.93
0.99*


OM
0.47
-0.10
-0.05
1
0.16
0.41
0.87
0.39
-0.57
-0.63
-0.84


pH
0.37
-0.58
0.56
0.20
1
0.97
0.63
0.97
0.72
0.67
0.41


NO3-N
-0.08
0.29
-0.50
0.33
-0.15
1
0.81
0.99*
0.52
0.45
0.16


P
0.10
0.05
0.14
0.26
0.05
-0.33
1
0.80
-0.08
-0.16
-0.45


K
0.20
-0.02
0.13
0.06
0.14
-0.39
0.79*
1
0.54
0.47
0.18


Ca
0.10
-0.04
0.16
0.06
0.14
-0.27
0.92*
0.82*
1
1.00
0.93


Mg
0.22
-0.14
0.24
0.13
0.22
-0.23
0.90*
0.80*
0.98*
1
0.95


Pinus elliottii correlation coefficients above the diagonal and Taxodium distichum below the diagonal.
Coefficients with a are significant at the .05 level.


BD
-0.49
0.09
0.08
-0.98*
-0.16
-0.39
-0.33
-0.18
-0.17
-0.25
1










Table B-3 Pearson correlation coefficients for Eucalyptus amplifolia and Eucalyptus
grandis growth variables: Jan. 2006 height (H), vigor (V), and survival (S)
and soil variables: organic matter (OM) and bulk density (BD) of
corresponding slope positions in the SRWC area.
H V S OM pH N03-N P K Ca Mg BD
H 1 -0.93* 0.94* 0.20 0.59* 0.08 -0.26 -0.19 -0.28 -0.30 0
V -0.98* 1 -0.96* -0.03 -0.42 0.13 0.17 0.15 0.20 0.21 -0.14
S 0.96* -0.90* 1 0.12 0.49 0.02 -0.22 -0.20 -0.25 -0.25 0.11
OM -0.28 0.38 -0.04 1 0.63* 0.80* -0.19 0.14 -0.08 -0.13 -0.56*
pH -0.09 -0.03 -0.17 0.20 1 0.37 -0.16 -0.23 -0.22 -0.23 -0.52*
N03-N -0.45 0.50 -0.44 -0.32 -0.79 1 -0.37 -0.19 -0.35 -0.38 -0.51*
P 0.13 -0.19 0.07 -0.10 0.26 -0.30 1 0.70* 0.91* 0.92* 0.03
K 0.82 -0.81 0.79 -0.18 0.06 -0.46 -0.38 1 0.88* 0.83* 0.03
Ca -0.08 0.03 -0.08 0.24 0.49 -0.46 0.92* -0.47 1 0.99* 0.10
Mg -0.26 0.32 -0.17 0.20 -0.34 0.32 0.66 -0.74 0.61 1 0.12
BD 0.16 0.00 0.41 0.74 -0.34 -0.09 0.08 -0.03 0.17 0.49 1
Eucalyptus grandis correlation coefficients above and Eucalyptus amplifolia coefficients below the
diagonal. Coefficients with a are significant at the .05 level.














APPENDIX C
COGONMASH

Methods

The cogonmash (CM) is located on the property of the Department of

Environmental Protection in Homeland, Florida. Cogongrass was continuously growing

for five years, reaching 2m in height, on consolidated waste phosphatic clays from a

1970s reclamation project. The entire CM area, which entails mashing cogongrass with

medium sized John Deere farm tractor wheels in August of 2005, is 1.2 ha. Only 318 m2

were used in this research, however. The area was sprayed at three weeks post mashing

and again at six weeks with 6% glyphosate at 2.4 L/ha.

Experimental Design

The CM area consisted of 318 m2 rectangular plot with two transects, six plots on

each transect, 8m apart. The site contained two elevations. Six plots were placed at the

greater elevation and six at the lower elevation, three on each transect (Figure C-l).

Vegetation surveys were performed in March and May 2006. The CM site had 12 24 cm

deep soil cores taken in the winter. Four cogonmash samples were combined to make

four composite samples; samples were combined based on their north or south orientation

in the two transects. Soils were analyzed in the lab using the same methodology as the

SRWC and the NA sites.
























m ] 1x1m herbaceous plot
a Sol core
Figure C-l Cogonmash vegetation and soil core plot design.

Analyses

CM Model

Yij ai + + (a)ij + ij (C-l)
ai = the effect of the ith transect
Pj = the effect of the kth plot
P(a)ij= the effect of the kth plot nested within the ith transect
ij = experimental error

Analysis of variance was run for the CM model (C-l) with transects and plots

being two main factors. An IVI was calculated as the sum of relative cover, relative

frequency (RF), and relative density (RD). Relative cover is the ratio of total cover of

one species to the total cover of all species. RF is the ratio of the frequency of one

species to the frequency of all species. RD is the ratio of the number of individuals of

one species to the total number of individuals of all species.

The diversity indices were calculated according to equations 3-4, 3-5, and 3-6.

Results and Discussion

Objective 2 Cultural treatments

The cogonmash treatment at the CM site had the least cogongrass cover of all

treatments. The cogonmash had .5% cover of cogongrass, even less than the 2% cover in









the mulch treatment in the SRWC site. Including cogongrass, there were 9 herbaceous

species; all were properly identified. All the species observed in the CM were also

present in the SRWC area. CM, to date, is the most effective method to control

cogongrass; though multiple applications may be required. The CM study area had the

least TPCC. However, treatment application of the CM area and the SRWC area were

applied at different times within the year, which may have an effect on the present

vegetation. The CM study began in Sept. 2005 and the SRWC study in Feb. 2005. More

time is needed before recommendations can be made about the effectiveness of the CM

treatment.

Objective 3 Native species colonization

Herbaceous plants

Of the 9 species present in the CM site, five were native species. With time, native

species diversity will increase and exotic species numbers will be phased out slowly.

Both native and exotic species colonize in the beginning of vegetation succession.

However, native species dominate in the later stages (Prach and Pysek 2001; Wang et al.

2004), and the number of exotic species decreases with the increasing age of the stand.

Table C-l Analysis of variance for herbs and shrubs in the Cogonmash (CM) site.
Values with a differ at the .05 level. Transect (T) and quadrat (Q).
CM Herbs
Transect 0.3055
Quadrat 0.2064
Q(T) <0.0001*










Table C-2 Ten greatest IVI and TSC (%) values of herbs and shrubs for the CM site.
CM
Herbs IVI TSC Shrubs IVI TSC
Imperata cylindrical 130 .5 Baccharis halimifolia 34 .5
Cirsium horridulum 100 18
Eupatorium capillifolium 79 3
Conzya canadensis 54 3
Oxalis corniculata 42 2
Sonchus asper 35 2
Ambrosia artemisiifolia 31 .5
Cyperus esculentus 31 .5
Medicago lupulina 28 .5
Shrubs

There were no differences in the CM area. There was only a single shrub species

present in the CM, saltbush (Table C-2), and it was found in 3 of the 12 plots.

Species Diversity and Site Similarity

The CM and SRWC were most similar to one another out of the three sites (Table

4-13). The CM and SRWC had an herb Jaccard community similarity index of 0.2

(Table 4-14). Conditions are similar between the CM and SRWC sites: light is abundant,

nutrients are high, and pH is nearly neutral, which could lend to similar vegetational

communities. Again, the shrubs of the CM and the SRWC were most similar to one

another, being that these are both mainly montmorillonite soils and their soils contain an

abundance of cogongrass rhizomes.

Objective 4 Soil properties

Soil pH (p=0.0066), Ca (p=0.0097), and Mg (p=0.0250) differed between transects

(Table C-3). Likewise, also differed between transects. Ca was lower on the western

transect than the eastern transect. Mg was also lower in the western transect than the

eastern transect. The only differences among quadrats were found in N03-N. It is

possible that nutrients had leached from the more elevated quadrats, slopes ranging from









1 to 5% on these Arent soil series (US Dept. of Ag, Soil Conservation Service 1990).

NO3 is a negatively charged mineral and does not readily bond to the negatively charged

monmorillonite clay; nitrate is easily leached (Campbell et al. 1999). Great differences

between nutrients are likely due to a small sample size than anything else. However

Arent soils lack fertility (US Dept. of Ag, Soil Conservation Service 1990), which may

contribute to such low macronutrient levels. Arent soils have no orderly soil profile

sequence and the water table is within 133 cm of the surface throughout 6 months of the

year (US Dept. of Ag, Soil Conservation Service 1990). BD values were similar to

SRWC BD values which could be attributed to the natural shrinking and swelling pattern

of the clay soils.

SOM was lower than the SRWC area and the pH was higher. This more alkaline

pH in the CM site could explain why the SOM is lower. The pH might be more alkaline

because there was less canopy cover in the CM site and less plant material contributing to

SOM. SOM was confined to the top layer of the soil in the CM site, likely from the

decomposing cogongrass mash. This has been seen before in the surface soil of a

Philippine cogongrass grassland, where SOM was obvious only in the surface soil and

decreased rapidly with depth (Snelder 2001). The shrinking and swelling nature of clay

aids in the translocation of SOM. During the dry season, litter enters the cracks in the

clay. Upon arrival of the wet season, water moves the SOM into the cracks. Both SOM

and litter are trapped in the soil profile after clay expansion. Without shrinking and

swelling of clay, SOM in the lower soil profiles of CSAs would be unlikely (Tamang

2005).










Table C-3 Analysis of variance for all soil variables in the Cogonmash study: transect
(T), and quadrat (Q). Values with a are different at the .05 level.
Cogonmash
T L+ L(T) +
OM 0.4719
pH 0.0066*
NO3 0.0506
P 0.2029
K 0.0787
Ca 0.0097*
Mg 0.0250*
BDO 0.3041 0.4308
BD1 0.0977 0.3749
+ L and L(T) were not testable.

Table C-4 Means for all soil variables in the Cogonmash site. Surface BD (BDO),
subsurface BD (BD 1), transect (T), mixed wetland forest (MW), cypress
forest (C), SRWC control culture (C), herbicide culture (H), mulch culture
(M), native shrub culture (S), and native tree culture (T). Values with the
same letter are not different at the .05 level.
CogonMash
Ave 5.4 6.95 0.603 0.86 4 215 49 2715 879
1 5.7a 6.95a 0.71a 0.89a 7a 158a 76.9a 3226a 1039a
2 5.7a 6.95a 0.65a 0.99a 7a 158a 76.9a 3226a 1039a
3 5.7a 6.95a 0.57a 0.88a 7a 158a 76.9a 3226a 1039a
4 5a 6.95a 0.61a 0.90a 2b 272a 21a 2203a 718a
5 5a 6.95a 0.57a 0.73a 2b 272a 21a 2203a 718a
6 5a 6.95a 0.52a 0.8a 2b 272a 21a 2203a 718a
T1 5.3a 7.05a 0.63a 0.80a 3a 168a 83.5a 4098a 1380a
T2 5.5a 6.85b 0.57a 0.93a 6a 262a 14.4a 1332b 377b
















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