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Vegetation and Soil Quality Changes Associated with Reclaiming Phosphate-Mine Clay Settling Areas with Fast-Growing Trees

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VEGETATION AND SOIL QUALITY CHANGES ASSOCIATED WITH RECLAIMING PHOSPHATE-MINE CLAY SETTLING AREAS WITH FAST-GROWING TREES By BIJAY TAMANG 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 2005

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Copyright 2005 by Bijay Tamang

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iii ACKNOWLEDGMENTS I would like to thank my committee member s (Drs. Donald L. Rockwood, Alan J. Long, and George W. Tanner) for their suggestio ns, valuable time, cr itical reviews, and edits of the manuscript. Special thanks go to Dr. Rockwood for his incessant guidance during data analysis and th roughout my stay in the School of Forest Resources and Conservation. My appreciation goes to Florida Institute of Phosphate Research for funding this project. Benefact ors of this research also include Steve Segrest of the Common Purpose Institute. Thanks go to faculties and staff in the Univ ersity for valuable suggestions and help during my difficult time with the soil samples. I am grateful to Analytical Research Lab staff and Dave Nolletti for analyzing my so il samples. Thanks go to Matt Langholtz, Brian Becker, Valerie Milmore, and Erin Maehr who were always willing to help me in the field despite high temper ature and torrential rain. My family has always been supportive of my work. I thank them all for their encouragement and prayers. Finally, I would like to thank all my friends and people at the School for making my days there comfortable.

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iv TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iii LIST OF TABLES.............................................................................................................vi LIST OF FIGURES.............................................................................................................x ABSTRACT....................................................................................................................... xi CHAPTER 1 INTRODUCTION........................................................................................................1 2 LITERATURE REVIEW.............................................................................................9 3 METHODS.................................................................................................................20 Study Area..................................................................................................................20 Experimental Design..................................................................................................23 Data Collection...........................................................................................................24 Data Analysis..............................................................................................................26 4 RESULTS AND DISCUSSION.................................................................................29 Tree Size and Survival................................................................................................29 Soil Characteristics.....................................................................................................33 Vegetation Characteristics..........................................................................................41 Species Richness.................................................................................................41 Species Diversity and Community Similarity.....................................................54 Importance Value Index (IVI).............................................................................57 5 CONCLUSIONS........................................................................................................73 6 FUTURE RESEARCH...............................................................................................75 APPENDIX A NAME AND NATIVITY OF HERBACEOUS AND SHRUB/SUBSHRUB SPECIES.....................................................................................................................77

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v B TREE SIZE AND SURVIVAL..................................................................................83 C SOIL CHARACTERISTICS......................................................................................86 D IMPORTANCE VALUE INDEX (IVI).....................................................................89 E COVER (%), FREQUENCY AN D SPECIES COMPOSITION.............................101 F MEAN SQUARES FOR COVER (%), FREQUENCY, AND SPECIES COMPOSITION.......................................................................................................115 REFERENCES................................................................................................................121 BIOGRAPHICAL SKETCH...........................................................................................134

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vi LIST OF TABLES Table page 3-1 Operational area: description, number of 15 x 15 m study plots, and associated average tree height (m), DBH (cm) density (trees/ha), basal area (m2/ha) and quadratic diameter (cm)...........................................................................................22 3-2 Clone-configuration-fertilizer study (S RWC-90): description and number of 8 x 5 m study plots...................................................................................................23 4-1 Clone-configuration-fertilizer study (SRWC-90): average 3.75-year-old tree height (m), DBH (cm), density (trees/ha), basal area (m2/ha) and quadratic diameter (cm) by treatment and species...................................................................32 4-2 Operational area: average total Kjeldahl N [TKN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and BD (gm/cm3)....................................34 4-3 Operational area: significance (* = 5% level) of Culture, Plot (Culture) and Position mean squares for TKN, P, K, Ca, Mg, SOM, pH and BD.........................35 4-4 Clone-configurationfertilizer study (SRWC-90) E. grandis and E. amplifolia plots: average total N [TN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and BD (gm/cm3)..............................................................36 4-5 Number of herbaceous and shrub/subs hrub species in the operational area and their nativity.............................................................................................................41 4-6 Major herbaceous species in the operational area: signi ficance (* = 5% level) of Culture (C), Plot (C) and Position (Pos) mean squares for cover (%), frequency, and species composition...........................................................................................43 4-7 Significant shrubs/subshrubs in the operat ional area: significan ce (* = 5% level) of Culture (C), Plot (C) and Position (Pos) mean squares for cover (%), frequency, and species composition.........................................................................45 4-8 Number of herbaceous and shrub/su bshrub species in SRWC-90 and their nativity......................................................................................................................4 6 4-9 Significant herbaceous species in E. grandis and E. amplifolia plots in SRWC-90: significance (* = 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for cover (%), frequency, and species composition.................47

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vii 4-10 Shrubs/subshrubs in E. grandis and E. amplifolia plots in SRWC-90: significance (* = 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for cover (%), freque ncy, and species composition....................................50 4-11 Herbaceous and shrub/subshrub species in the operational area: Shannon-Wiener diversity index (H'), maximum possible di versity (H'max) and relative diversity (J)............................................................................................................................ ..54 4-12 Herbaceous and shrub/subshrub spec ies in SRWC-90: Shannon-Wiener diversity index (H'), maximum possible di versity (H'max) and Relative diversity (J)............................................................................................................................ ..55 4-13 Operational area: Jaccard's community similarity index (Cj) for herbaceous (H) and shrub/subshrub (S) species................................................................................56 4-14 Clone-configuration-fertilizer study (SRW C-90): Jaccard's community similarity index (Cj) for herbaceous (H) and sh rub/subshrub (S) species................................57 4-15 Average IVI (> 5.0) of herbaceous and shrub/subshrub species in four cultures in the operational area..............................................................................................58 4-16 Average IVI (> 5.0) of herbaceous species in SRWC-90........................................62 4-17 Average IVI (> 5.0) of shr ub/subshrub species in SRWC-90..................................63 4-18 Spearman correlation coefficient (r) of herbaceous species with highest IVI in the operational area..................................................................................................68 4-19 Spearman correlation coefficient (r) of shrub/subshrub species with highest IVI in the operational area..............................................................................................69 A-1 Name and nativity of herbaceous species................................................................78 A-2 Name and nativity of shrub/subshrub species..........................................................81 B-1 Tree size and survival in the operational area: average tree height (m), DBH (cm), basal area (m2/ha), density (trees/ha) and quadratic diameter (cm)................84 B-2 Tree size and survival in SRWC-90: av erage 3.75-year-old tree height (m), DBH (cm), basal area (m2/ha), density (trees/ha) and quadratic diameter (cm)................85 C-1 Soil characteristics in the operational area: total Kjeldahl N [TKN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and bulk density (BD) on bed (B) and inter-bed (IB) positions..........................................................87 C-2 Soil characteristics in SRWC-90 E. grandis and E. amplifolia plots: total N [TN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and bulk density (BD) on bed (B) and inter-bed (IB) positions..............................................88

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viii D-1 Single-EG in the operational area: IVI of herbaceous and shrub/subshrub species......................................................................................................................90 D-2 Double-EG in the operational area: IV I of herbaceous and shrub/subshrub species......................................................................................................................92 D-3 Quadruple-EG in the operational ar ea: IVI of herbaceous and shrub/subshrub species......................................................................................................................94 D-4 Double-PD in the operational area: IVI of herbaceous and shrub/subshrub species......................................................................................................................95 D-5 Treatments* 1, 2 and 3 in SRWC-90: IVI of herbaceous and shrub/subshrub species......................................................................................................................97 D-6 Treatment* 4 in SRWC-90: IVI of herbaceous and shrub/subshrub species...........98 D-7 Treatment* 5 in SRWC-90: IVI of herbaceous and shrub/subshrub species...........99 E-1 Single-EG in the operational area: cover (%), frequency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions..........................................................................................................102 E-2 Double-EG in the operational area : cover (%), frequency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions..........................................................................................................104 E-3 Quadruple-EG in the operational ar ea: cover (%), frequency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions..........................................................................................................107 E-4 Double-PD in the operational area: cover (%), frequency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions..........................................................................................................109 E-5 Eucalyptus grandis and E. amplifolia in SRWC-90 Treatments* 1, 2 and 3: cover (%), frequency and species com position of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions......................................................111 E-6 Eucalyptus grandis and E. amplifolia in SRWC-90 Treatment* 4: cover (%), frequency and species composition of he rbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions........................................................................112 E-7 Eucalyptus grandis and E. amplifolia in SRWC-90 Treatment* 5: cover (%), frequency and species composition of he rbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions........................................................................113

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ix F-1 Herbaceous species in the operationa l area: significance (*= 5% level) of Culture (C), Plot (C) and Position (Pos) mean squares for cover (%), frequency, and species composition.........................................................................................116 F-2 Shrub/subshrub species in the operati onal area: significance (*= 5% level) of Culture (C), Plot (C) and Position (Pos) mean squares for cover (%), frequency, and species composition.........................................................................................118 F-3 Herbaceous species in E. grandis in SRWC-90 treatments#: significance (*= 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for cover (%), frequency, an d species composition.....................................................119 F-4 Herbaceous species in E. amplifolia in SRWC-90 treatments#: significance (*= 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for cover (%), frequency, an d species composition.....................................................120

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x LIST OF FIGURES Figure page 3-1 Map of study area.....................................................................................................21 3-2 Sampling schemes used for collecting he rbaceous and shrub/subshrub data in 15 x 15 and 8 x 5 m plots.........................................................................................24 4-1 Eucalyptus grandis in the operational area: correlation between total basal area per hectare and cogongrass IVI................................................................................65 4-2 Cottonwood in the operational area: co rrelation between to tal basal area per hectare and cogongrass IVI......................................................................................66 4-3 Eucalyptus grandis in SRWC-90: correlation between total basal area per hectare and cogongrass IVI...................................................................................................70 4-4 Eucalyptus amplifolia in SRWC-90: correlation be tween total basal area per hectare and cogongrass IVI......................................................................................70 4-5 Eucalyptus (E. grandis and E. amplifolia combined) in the study area: correlation between total basal area pe r hectare and cogongrass IVI.........................................71

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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 VEGETATION AND SOIL QUALITY CHANGES ASSOCIATED WITH RECLAIMING PHOSPHATE-MINE CLAY SETTLING AREAS WITH FAST-GROWING TREES By Bijay Tamang August 2005 Chair: Donald L. Rockwood Major Department: School of Fo rest Resources and Conservation Abandoned phosphate mines in central Florida are invaded by cogongrass ( Imperata cylindrica ). Native vegetation in cogongra ss-dominated areas is minimal or absent, thus complicating site restorati on. Cogongrass dominates native vegetation because of its allelopathic nature and str ong competitiveness. Adverse edaphic factors and limited nutrients in mined areas further hi nder the establishment of native vegetation. This study examined the performance of fast-growing eucalyptus ( E. grandis and E. amplifolia) and cottonwood ( Populus deltoides) in suppressing cogongrass in an old phosphate mine in Lakeland, Florida. Unders tory vegetation was studied in 2and 3-year-old E. grandis and 2-year-old cottonw ood in the operational plantations; and in a 3.75-year-old E. grandis and E. amplifolia clone-configurationfertilizer (SRWC-90) study. Soil samples were collected and analy zed for macronutrients (N, P, K, Ca, Mg), pH, soil organic matter (SOM), and bulk density (BD).

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xii Both tree height and diameter at breast height (DBH) differed significantly among single, double, and quadruple row E. grandis (Single-EG, Double-EG and Quadruple-EG, respectively) and double ro w cottonwood (Double-PD) in the operational area ( p < 0.0001). Total Kjeldahl nitrogen (T KN) ranged from 0.18% in Quadruple-EG to 0.35% in Double-PD. Quadruple-EG had the lowest SOM (3.80%), while Double-PD had the highest (6.50%). The pH ranged from 7.3 in Double-EG to 7.9 in Quadruple-EG. The TKN ( p = 0.0002), Mg ( p = 0.0481), pH ( p = 0.0321), and SOM ( p = 0.0009) differed significantly (5%) among four cultures in the operational area. Both native and introduced species we re recorded in the understory. Clematis virginiana, Bidens alba, Commelina diffusa, Phytolacca americana, and Ambrosia artemisiifolia were frequent herbaceous species. Frequent shrubs/subshrubs included Urena lobata Baccharis halimifolia, and Ludwigia peruviana Herbaceous species richness (35) was highest in Double-EG, which also had the highest shrub/subshrub richness (23). Cogongrass was still dominant in Double-PD and three treatments of SRWC-90, but well controlled in most plots in E. grandis cultures in the operational area. However, the cogongrass Importance Value Index (IVI) had a nonsi gnificant correlation with stand basal area ( r = 0.19, p = 0.4587). Cogongrass IVI al so had a nonsignificant correlation with stand ba sal area in Double-PD ( r = -0.21, p = 0.6103). In SRWC-90, cogongrass had significant negative correlation with E. grandis ( r = -0.91, p < 0.0001) and E. amplifolia ( r = -0.73, p = 0.0028) basal area. Eucalyptus grandis with good stand density seems to suppress cogongrass more effectively compared to E. amplifolia and cottonwood. Fast-growing tree plantations with good stand survival have the potential to control cogongrass and amend soil in mine lands.

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1 CHAPTER 1 INTRODUCTION Biodiversity is one indica tor of system stability (Evans 1992). Pristine ecological systems are rich in biodiversity, and their components are balanced. However, these stable systems are often disturbed and threat ened by human actions. Some of the actions are intentional; and some are unintentional, consequences of other indirect actions. Ecosystem functions are usually disturbed at various scales during resource extraction, regardless of whether the resources are located on the earth surface or beneath it. The disturbances sometimes are so severe that ecosystems take many years to recover. In central Europe, establishmen t of woody species took 20 y ears on average, depending on soil conditions (Prach 1994). When disturba nce exceeds critical levels, ecosystems lose their resilience, and irreversible changes occur. With increasing human population and industrial development, demand for resources increases daily. Natural resources such as coal, gas, water, and other raw materials located beneath the earth surface comp rise most of the resources extracted to meet human needs. Ecosystem destruction th rough mineral extracti on and other activities has been a fundamental part of development (P ensa et al. 2004). The effect on terrestrial and aquatic environments from the extraction of mineral resources is severe and usually irreversible (Rybicka 1996). Ex ternal intervention is the only way to restore such areas; however, success cannot be guaranteed. The eff ect of resource extraction can be at the extraction site or at nearby wast e disposal sites, such as clay settling areas (CSAs) in the case of phosphate mines in central Florida.

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2 Phosphate mining started in Florida in 1883, after hard rock deposits were found near Hawthorne in Alachua County. Phosphate is still actively mined in phosphate-rich central Florida. Phosphate deposits c over about 518,000 ha (1,280,006 acres) in Polk, Hillsborough, Hardee, Manatee, and DeSoto C ounties (EcoImpact 1980). In central and north Florida, from July 1975 through December 2002, phosphate was extracted from more than 69,000 ha (171,000 acres) (DEP 2003), and this area will continue to increase in the future (Segal et al. 2001). Mining currently disturbs about 2,000 to 2,500 ha (5000 to 6000 acres) of land every ye ar in Florida (DEP 2003). Florida alone contributes about 75% of the United States' phosphate requirement and 25% of the phosphate export. Typical pho sphate ore (also known as matrix) is found at a depth of 4.5 to 15 m (15 to 50 ft) below th e surface and is 3 to 6 m (10 to 20 ft) thick. Matrix consists of equal pa rts of sand, clay, and phospha te. The top layer of earth (overburden) is removed to extract the matri x, which is subjected to high-pressure water guns that turn it into a watery mixture cal led slurry. Phosphate rock and sand are separated from the slurry. Sand is later used for reclamation of the extraction sites. The by-product (the mixture of wate r and clay) is pumped into CSAs, which constitute about 40% of the phosphate-mine lands and are 10 to 20 m (30 to 60 ft) deep. They retain water for a longer period of time and take about 15 years to dewater. There are approximately 64,700 ha (160,000 acres) of thes e undeveloped CSAs in central Florida alone (CPI 2003). The north and central Florida phosphate mi ning districts were heavily forested historically, with sta nds of longleaf pine ( Pinus palustris ), slash pine ( Pinus elliottii ), oak ( Quercus sp.), and cypress ( Taxodium sp.). Phosphate strip-mining, however,

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3 significantly altered these lands capes. Disturbed soil duri ng mining made the old mined areas suitable for invasive exotics such as cogongrass, natalgrass ( Rhynchelytrum repens ), and bahiagrass ( Paspalum notatum ). Cogongrass is the most noxious exotic species that inhibits the grow th of other native plants, be cause of its de nse above-ground and below-ground growth, allelopathic eff ects, competition, and susceptibility to wildfires during dry season. It is the major problem sp ecies throughout tropical and subtropical parts of the worl d and has invaded forests, ra ngelands, reclaimed mined areas, roadsides and natural ecosystems in the sout heastern United States (MacDonald et al. 2002; Shilling et al. 1997) and occurs in almost all old CSAs. It is a shade-intolerant, fast-growing rhizomatous plant; is the dom inant vegetation in southeast Asia, covering 121 million ha (300 million acres); and has infested more than 202 million ha (500 million acres) of plantation and agricultural la nds worldwide. It spreads through seeds and rhizomes. Florida policy requires mini ng companies to reclaim areas mined after July 1, 1975. Wetlands must be reclaimed to at least the same area as before mining, and at least 10% of upland must be planted with native species. Mining companies have reclaimed significant areas of uplands and wetlands sin ce the law was enacted (Segal et al. 2001). Details of reclamation standards are gi ven in Chapter 62C-17 of the Florida Administrative Code. As of December 2003, 63% of the land mine d since July 1, 1975 has been successfully reclaimed (DEP 2003) However, this law excludes mandatory reclamation of old areas mined before 1975. Restoration of these older abandoned disturbed sites has become the sole responsib ility of government and other environmental agencies.

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4 Restoration of old phosphate-mined areas (especially cogongrass-infested CSAs) has become a major challenge. CSAs are looked upon as unproducti ve wastelands and unsuitable for development because of unstabl e clay soil. Because of their poor soil quality, CSAs do not support good growth of native species. In addition, high establishment costs discourage using the ar eas for crop production. Reclamation of CSAs is difficult because of competition, a llelopathy, soil degradation, compaction, and fire susceptibility (D ela Cruz 1986; Ohta 1990a). Theref ore, the presence of invasive exotics (like cogongrass) hinders successful reclamation of disturbed sites, and also threatens replanted native species. Native species must overcome the adverse edaphic conditions while competing with cogongrass fo r limited available nutrients. Restoration activities on such sites theref ore should have the dual purpos es of removing the invasive species as well as replanting the area with native species. One major problem in controlling cogongra ss has been the limited knowledge of its ecology, physiology, and management. Studies conducted in the United States (Ramsey et al. 2003; Shilling et al. 1997) and in c ogongrass' native range (Otsamo et al. 1995a; Otsamo 1998a; Peet et al. 1999; Turvey 1996) provided valuable information on the ecology and management of cogongrass. Use of herbicide, the widely practiced method to control weeds, has limited success on this noxious weed, and the effect is temporary (MacDonald et al. 2002; Willard et al. 1997; Willa rd et al. 1996). Multiple applications are required for long-term cont rol. Removal of the above-g round biomass is not effective as it grows back from the rhizomes. Ther efore, a control strategy should incorporate removal of above-ground biomass and removal of the underground rhizomes. Disking alone controls the species for a short dur ation. However, the combination of double

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5 disking and split applications of imazapyr [2-(4-isopropyl-4-methyl-5-oxo-2-imidazolin2-yl)nicotinic acid] can c ontrol cogongrass regrowth (up to 96%) 12 months after treatment (Shilling et al. 1997). Better understanding of the ecology of cogongr ass has given rise to innovative and effective ideas for its control. Since it is a heavy shade-intolerant species, researchers suggest using repeated application of herb icide and introducing fa st-growing trees that form a dense canopy, for effective and long-term control (Ramsey et al. 2003; Shilling et al. 1997). Use of plantations to catalyze th e restoration of degraded lands has been widely discussed and practiced throughout the world (Fimbel and Fimbel 1996; Lamb 1998; Lugo 1992; Parrotta 1992, 1993; Parrotta et al. 1997; Singh et al. 2002). However, priority must be given to building SOM, esse ntial plant nutrients, and vegetation cover to facilitate and enhance the regeneration and growth of native species. Different approaches have been used to restore aba ndoned old mined areas. Some used organic enrichment techniques to build soil qualit y and supply nutrients to native vegetation (Lunt and Hedger 2003; Sydnor and Redente 2002) Others have used tree plantations (Glenn et al. 2001; Parrotta and Knowles 1999; Pensa et al. 2004), w ith both native and exotic species as nurse crops. In some cas es, both approaches have been incorporated (Parrotta and Knowles 1999). Though it is always beneficial to use na tive species to rest ore degraded lands, noninvasive exotic species can be used to re habilitate badly degraded areas where native species cannot grow (Lamb 1998). They can late r be replaced with native species when site conditions have improved. Appropriate e xotics can also be used to assist native biodiversity conservation (N orton and Miller 2000).

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6 Flatwoods and poorly drained phosphate-mine lands in central Florida are capable of supporting both native and exotic short-rotation woody crops (SRWCs) like cottonwood, eucalyptus, leucaena ( Leucaena leucocephala ), slash pine, and castor bean ( Ricinus communis ) (Stricker et al. 2000). These provi de multiple environmental benefits including improved water qual ity, soil stabili zation, atmospheric carbon sequestration, and wildlife habitat. Ongoing resear ch indicates that restoration of cogongrass-dominated phosphate-mined areas ca n also be achieved using fast-growing SRWCs like eucalyptus and cottonwood. In spit e of increasing ecol ogical and technical skills, restoration success, however, is limited (Geist and Galatowitsch 1999). Different species of eucalyptus have b een used in plantations worldwide for biomass production and restoration of degrad ed sites due to their fast growth and short-rotation cycles (Ashagri e et al. 2005; Bone et al. 1997 ; Callisto et al. 2002; Fabio et al. 2002; Geldenhuys 1997; Loumeto and Huttel 1997; Nzila et al. 200 1; Ribeiro et al. 2002; Sicardi et al. 2004; Strauss 2001; T yynel 2001). In addition, their coppicing ability can significantly reduce repeated esta blishment costs. In the United States, eucalypts are mostly used for mulch produc tion. However, eucalypt plantations have produced mixed reactions worldwide. Monocul tures may adversely affect soil fertility, water cycles, wildlife (Loumeto and Huttel 1997), biodiversity, local vegetation, and use more water than other tree species. Eucal yptus plantations do not provide shelter and food for the native biodiversity in Brazil (Cout o and Betters 1995). Most of the concerns about eucalyptus are re lated to depletion of soil nutrie nts and allelopathy caused by the litter, which is said to exert an antibiotic effect on soil microorganisms. However, eucalypts can amend soil by penetrating re latively impermeable layers and drawing

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7 nutrients from deep layers when planted in degraded areas (Poore and Fries 1985). Eucalypts are also capable of suppressing dom inant grass and providing habitat for seed dispersers (Bone et al. 1997). Cottonwood is the fastest growing native sp ecies in North America. It is a deciduous bottomland hardwood species. Seve ral varieties of cottonwood have been studied and used for biomass production (Gar diner et al. 2001; Jo slin and Schoenholtz 1997; Knowe et al. 1998; Lee and Jose 2003; Lockaby 1986; Thornton et al. 1998; Twedt et al. 1999). However, biomass production is less than nonnative eucalyptus species (Stricker et al. 2000). It has also been used as a nurse cr op for restoration of degraded lands (Gardiner et al. 2001; Gardin er et al. 2004; Sher et al. 2000). Conversion of degraded lands like CSAs to SRWC farms may provide habitat for wildlife and facilitate the growth of na tive species. Compared with multi-species plantations, single-species SRWC farms may, ho wever, reduce the avai lability of diverse food and shelter for local wild life. SRWCs mostly affect species that u tilize habitat consisting of old trees due to short-ro tation. While accumulating above-ground and below-ground biomass, SRWCs have the pot ential to stabilize soil, increase SOM through leaf litter, decrease BD and increas e soil porosity through root penetration. Noninvasive eucalyptus ( E. grandis and E. amplifolia ), cottonwood, cypress and slash pine hybrids were plan ted in a 50 ha cogongrass-dominated CSA (Kent site) near Lakeland in central Florida. Planting bega n in 2000 with an objective to use these SRWCs for energywood and other commercial products. Initial results showed that the growth of shade-intolerant cogongrass was well controlled in eucalyptus stands. Native species such as climbing dayflower ( C. diffusa ), kunth’s maiden fern ( Thelypteris

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8 kunthii ), shyleaf ( Aeschynomene americana ), saltbush (B. halimifolia ), oak ( Quercus sp.) and red maple ( Acer rubrum ) were observed in the SRWC (Tamang et al. 2004). This study began in 2004 to evaluate th e performance of SRWCs in controlling cogongrass and making the site suitable for nati ve flora. The study focused on assessing different understory vegetation growing in the stands and docume nting changes in soil characteristics. The specific objectives were Objective 1: Study the performance of E. grandis E. amplifolia and cottonwood in controlling cogongrass. Objective 2: Document the regeneration of native species at the site. Objective 3: Document changes in SOM, BD, pH and macronutrients (N, P, K, Ca and Mg) on and between beds in SRWCs. The hypotheses of the study were Hypothesis 1: Species that grow comparativel y fast and form a dense canopy will perform well in controlling cogongrass. Hypothesis 2: Understory vegetation diversity is higher in old stands than in younger stands. Hypothesis 3: As the SRWCs accumulate above-ground and below-ground biomass, BD and pH decrease and SOM increase. Hypothesis 4: Soil characteristics, especially BD and nutrients, differ between bed and interbed positions.

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9 CHAPTER 2 LITERATURE REVIEW Restoring degraded sites is a challenging task and it take s time to achieve desired goals. Restoring sites back to reference sy stems is practically not achievable; however, increasing habitat suitability, native species diversity, and controlli ng exotic species can often be the primary goals (Pr ober and Thiele 2005). Restorat ion activities can even have negative impacts on the system during initial ye ars, mostly in places where intensive site preparation is required. Species richness of the site may decrease in the beginning; however, it may then increase in subsequent ye ars. Reduction in number of plant species was observed a year after restoration of Florida sandhills by harvesting Pinus clausa, but species number increased in later years (Provencher et al. 2000). Restoration of mine lands requires building SOM, esse ntial plant nutrients and vegetation cover to accelerate na tural recovery processes. Both native and exotic tree species are widely used in the restoration of de graded sites. Tree plan tations are useful in increasing SOM, essential plant nutrients, decreasing soil BD, increasing soil aeration and ameliorating microclimatic conditions. Trees are also capable of removing toxic substances from the so il (Rockwood et al. 2001). Vegetation growth is sparse in mined lands due to nutrient deficiencies (Singh et al. 2002). However, minimizing nutrient and wate r limitations during the early phase can accelerate the revegetation process. Rather than using exotic species, using native species that are well adapted to such stress conditions could be benefi cial (Clemente et al. 2004). However, success of restoration effo rts cannot be guaranteed due to competition

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10 with exotics, changes in so il nutrients and establishment conditions (Prober and Thiele 2005). Mining creates intensive disturbance to soil and vegetation (Bradshaw 2000). Recovery of such extremely degraded ecosy stem is possible only through improving soil fertility and species divers ity (Fang and Peng 1997). Natu ral succession plays a crucial role in the restoration of degr aded sites but may take centuries to complete. Restoration of degraded sites through na tural succession is only succes sful at sites that have nutrient-rich soil and are located near healthy natural stands that serve as seed sources (Bradshaw 2000). In situations where hab itat conditions are extreme, the process is retarded (Prach and Pysek 2001). Extreme ha bitat conditions require external input to build soil quality and aid the immigration of seeds and plants. However, success of restoration through external input largely de pends on knowledge of the systems present at the site before disturbance and available seed source in nearby vicin ity, which help define strategic plans to achieve restoration goals. Plantations have been widely used to recover vegetation on mined lands (Reintam and Kaar 2002); mostly because of their multiple uses. Trees modify the microclimate, nutrient availability, shelter and food supply for many of the fore st biota. Plantations are mostly tree monocultures; pol ycultures however, are generally favored due to their resistance to pest outbreak (Hartley 2002). Native species are ge nerally preferred over exotics. In forests where exotic species become established, ecological restoration treatments may create a forest health problem that is as undesirable as the pretreatment condition (Wagner et al. 2000). Though planting in rows is easier, planting trees without rows makes reforested sites look more natural (Allen 1997)

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11 Understory vegetation comprises one of the most important elements of biodiversity both within planta tions and natural stands. It is often the single best predictor of animal diversit y. Understory vegetation is frequently undersampled in ecological studies. Composition, abundance an d diversity vary across location, season and plot size (Small and McCarthy 2003). Factors like habitat heterogeneity, quality, disturbance, climate, planting density and proximity to natural forest are important in the species diversity in plantations. Species diversity expands quickly after vegetation recovers in a degraded ecosystem and occurs faster in the early and middle stages of the process of vegetation development. With increasing stand age, native vegetation colonizes gradually into the planted co mmunities (Fang and Peng 1997; Pande et al. 1988; Wang et al. 2004). Species density a nd richness increase gr adually (Halpern and Spies 1995; Pande et al. 1988; Wang et al. 2004) depending on soil quality, climate and type of species planted. Stand maturity positively influenced de nsity and species ri chness in Dehra Dun, India (Pande et al. 1988). Both herbaceous and shrubby species richne ss were higher in a Pinus roxburghii plantation followed by Shorea robusta and Tectona grandis, which were planted in 1926. Herbaceous and shrubby species richness was the lowest in a eucalyptus planted in 1972. Comm unities in three former plantations were similar to one another, while a eucalyptus plantation was di fferent. However, differences in species richness, diversity, and evenness values were not noted in different aged hardwood stands in the Appalachian Mountains of northern Georgia (Ford et al. 2000). Though plantations generally have low speci es diversity and richness compared to natural stands, species diversity in an old (38 to 40.5 year) messmate ( E. cloeziana )

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12 plantation in Australia was sim ilar to that of native eucalyp t forests (Wang et al. 2004). Though understory sapling density was comparat ively lower in plantations in Estonia, total stand richness was equal, both in natural and a European black alder ( Alnus glutinosa ) stands. Species composition of natural stands was more diverse compared to plantations (Pensa et al. 2004) Type of species planted has a direct influence on the microenvironment which ultimately affects species diversity (Pande et al. 1988). Allelopathy, which is exhibi ted by a large number of trees, affects understory vegetation succession (Kohli 1998). Establishment of di verse ground vegetation therefore depends on the species planted, planting density, th e time the site is exposed to species immigration, and the diverse la ndscape (Pensa et al. 2004). Floral diversity was invers ely related to crown cover in Ulumba Mountain site, Malawi (Bone et al. 1997). Therefore, gaps in the plantation have th e potential to change species richness. The number of naturally regenerated seedlings increased from 14 to 21 and saplings from 2 to 24 after 23 months of gap creation in an Acacia mangium plantation in Indonesia (Otsamo 2000a). After plantations are harvested, dormant seeds of pioneer species get the opportunity to ge rminate. Climax species are replaced and pioneer species start to coloni ze. Open canopies might serve as one of the driving forces for the increase in species diversity. Woody and herbaceous species diversity was significantly higher in 1-year-old E. camaldulensis coppice plots than in control and plantation stands in the Ulumba Mountain, Ma lawi. Even the numbe r of tree and shrub species was also significantly higher in coppice plots. Coppice sites had the largest number of herb specie s (Bone et al. 1997).

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13 Both native and exotic species colonize in the beginning of vegetation succession. However, native species dominate in the late r stages (Prach and Pysek 2001; Wang et al. 2004), and the number of exotic species decreases with the increasing age of the stand. Plantations can also serve as a suitable habitat for threatened species in the later stages as observed in southeast Queensland, Australia. Two vulnerable and one rare species were recorded in the plantation (Wang et al. 2004) Both rare and endangered species were also recorded from restored sites in the Czech Republic in the la ter successional stage (Prach and Pysek 2001). Native species are threatened when inva sive exotics such as cogongrass start appearing. Cogongrass coloni zes forest clearings with subsequent fire-based maintenance (Otsamo 2000a). It produces alle lopathic chemicals that inhibit the growth of native species. Its rhizome leachate is comparatively more inhibitory than leaf leachate (Inderjit and Dakshini 1991). Pe rformance of slow-growing woody species is poor in reclaiming cogongrass-dominated grassl ands. However, these grasslands have the potential to support shortrotation woody species. Fast-growing exotic species have widely been used in the reforestation of c ogongrass grasslands in Asia. Early and fast growth of these species suppre sses cogongrass (Otsamo et al. 1997). Intensive site preparation must be done to suppress the grass at least for a year even when fast-growing species are used. Glyphosphate [isopropylamine salt of N-(phosphonomethyl) glycine] has been wide ly used to control cogongrass; however, imazapyr also has the potential to control. Integration of reforest ation and conservation tillage can prove to be beneficial for soil fertility and productivity of such grasslands (Terry et al. 1996). Several pl ant species have been used to control cogongrass. Density

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14 of cogongrass was reduced by 67% and 51% using gliricidia ( Gliricidia sepium ) and leucaena, respectively, in Nigeria. Rhizomes were reduced by 96% in gliricidia and 90% in leucaena plots, with rhizome mortality sign ificantly higher in gliricidia plots compared to leucaena and control plots (Anoka et al. 1991). Herbaceous cover crops belonging to genera Calapogonium, Crotoleria, Mucuna and Pueraria have also been effective in suppressing cogongrass (MacD icken et al. 1996). Combining forest plantations with moderate to high tillage, weeding and fertilizer inputs have been successful. Fast-growi ng tree species control cogongrass and amend soil physical and chemical properties at the same time (MacDicken et al. 1996). Two species of fast-growing velvet beans ( Mucuna pruriens var. utilis and M. deeringiana ) were also effective in shading cogongrass when the cover was retained for a longer period. However, performance was less eff ective when topsoil was lost by erosion (Hairiah et al. 1993). Tillage is an importa nt factor for sustai nable crop production in cogongrass-infested areas. Crop productions in such areas ha ve been successful where animal or tractor draft power is available. However, investment increases and return decreases in later years when the weed in tensity increases and soil quality decreases (Noordwijk et al. 1996). In Indonesia, 14 speci es of fast-growing eucalyptus with narrow crown and open canopies planted in a mechani cally prepared site performed worse in cogongrass-dominated grassland (Otsamo et al. 1995b). Soil quality is another crucial factor that supports species diversity. Poor soils generally support fewer species than good soils The relationship between vegetation and soil at the site can therefore be an important tool to assess site quality (Zas and Alonso 2002). Priority should therefore be given to soil amendment in the restoration of

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15 degraded sites. Litter is the primary source of nutrients in natu ral systems. It is the major input in the nutrient cycle and decomposer food chain. Plant esse ntial nutrients are continuously added to soil from the decom position of litter and pl ant residues. In contrast, litter addition in plantations is shortterm and is discontinued after each harvest, at least for sometime. Residual logging slash is the main source of carbon after the harv est in plantations. Slash enhances soil physical a nd chemical properties. Slash occupied 40 to 60% of the harvest area in sawlog treatment in South Carolina (Johnson et al. 2002). Forest harvest on average increases soil C (Johnson and Curtis 2001). However, the effect of harvesting on soil C depends on the harvest type. Sa wlog harvesting increases soil C up to 18%, while whole-tree harvesting decreases it by 6% In some cases, harvesting has little lasting effect on soil C (Johnson et al. 2002). The rate of nutrient removal is higher in short-rotation plantations due to frequent harvest (Corbeels et al. 2003). This has b ecome a major concern of nutrient management in short-rotation planta tions. Though harvest residues are us ually added to soil, nutrient deficiencies may occur due to discontinue d litter addition, degradation of SOM and nutrients during site preparati on. Nutrients trapped in plant tissues are removed from the site along with the harvest. Whole-tree harvesting reduced 50% of the above-ground biomass and nutrients in Gmelina arborea plantation (Agus et al. 2004). Soil organic matter added to soil in plantati ons with the growth of trees changes the structure and properties of soil (Singh 1998). Plant residues c ontinuously added to soil in natural systems maintain and increase SOM. However, in plantations, harvesting limits the continual addition of the pl ant parts. Changes in land use and management alter soil

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16 structure, soil organic carbon and nutrients. It is widely believed that soil nutrients are degraded when natural forests are converted in to monoculture plantations. Priority must be given to the management of SOM in planta tions to ensure a continuous supply of plant nutrients. Soil organic matter acts as a store house for large quantitie s of plant nutrients and provides cation exchange and waterholding capacities (Brady and Weil 2001). Compared to plantations, more organic matter is added to soil in primary forests every year due to higher decomposition rate. Soil carbon decreases in the initial years of plantation establishment and increases over time (Hansen 1993; Makesc hin 1994). However, organic carbon and nutrients were less in a 40-year-old eucalypt us plantation compared to Juniperus procera plantation. It was also lower than in adjacent natural forest (Michelsen et al. 1993). Another study in Ethiopia showed the reduction of soil organic carbon, N and S after 25 years of conversion of natural forest in to plantations (Solomon et al. 2002). Similar results were found when native Brazilian forest was converted into eucalyptus plantations (Zinn et al. 2002). However, conversion of natural fo rest to eucalyptus plantation did not significantly change soil organi c carbon, N, S concentrations and BD in Ethiopia. Loss of organic carbon, N and S were comparatively higher in sand and silt particles compared to clay. Clay-associated organic carbon, N and S were more stable (Ashagrie et al. 2005) due to less leaching. Soil organic carbon is added only to the upper layer (10 cm) in the initial years of planta tion establishment (Tolbert et al 2002). Areas invaded by exotics have less litter, thin or ganic horizons and high pH (Kourtev et al. 1998). Nitrogen is one of the nutrients that is usually scarce in opera tional plantations due to its high demand during tree growth. S upply of N through litter decomposition and

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17 mineralization vary in plantations of th e same species and depend on clones (Singh 1998). Nitrogen is available in plants in or ganic form and is not released until organic matter is decomposed through biological proce sses. Use of legumes can help overcome N deficiency and supply organic matter in plan tations (Agus et al. 2004). However, the rate of N supply depends on the legume speci es (Corbeels et al. 2003). Leaves always constitute largest fraction of litter than bark and small branches, and have higher concentration of macronutri ents (Shammas et al. 2003). Both litterfall and its decomposition rates are higher in primary fore sts than in plantations, with the highest levels of N in primary forests (Martius et al. 2004). Soil disturba nce increases available N, encouraging the growth of nitrogen loving an nual exotics. These, in turn, increase available soil N through breakdown of dead pl ant material (Prober and Thiele 2005). Soil in cogongrass-dominated s ites is generally less fertil e. Decomposition rates of cogongrass leaf litter are very slow and N content in the l eaf is low. Cogongrass leaf litter also immobilizes N (Harte mink and O'Sullivan 2001). Soil in cogongrass-dominated areas is ge nerally low in available P a nd N. It is possible to reclaim such sites for food and tree crops using legume cover crops to enhance soil fertility (Santoso et al. 1996). Using trees in restoration of degraded site s to improve soil quality may change both chemical and physical properties of soil. However, some properties might be limiting depending on the type of species used. Cottonwood planted in agricultural land in Mississippi has been effective in reducing penetration resi stance, infiltration and BD (Tolbert et al. 2002). Among 20 native trees us ed in restoration of degraded lands in

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18 Brazil, only four species had more positive effects on soil properties (Montagnini et al. 1995). As trees grow and develop root syst em, these effects become more pronounced. Fast-growing eucalyptus and cottonwood are preferred for reclamation of degraded sites such as cogongrass-dominated areas. In India, cottonwood was superior to eucalyptus in amending soil. Cottonwood pr oduced more litter than eucalyptus every year. Cottonwood litter contained comparatively more N, P and K than eucalyptus litter (Singh et al. 1989). Another study on three clones of cott onwood showed that nutrient concentration was higher in leaf tissue comp ared to woody tissue. However, nutrient addition to soil from leaf decomposition was less than the leaf tissue content due to retranslocation. Leaf litter quality, its decomposition and nutrient release differ in different clones, even in the same species (Singh 1998). Litterfall in eucalyptus can be increased by the application of N and P fertilizer It also increases the total N, P, K, Ca and Mg in the litter (C onnell and Mendham 2004). Monoculture eucalyptus has been critic ized throughout the world due to its antisocial nature (Kohli 1987) Allelopathy in eucalyptus affects composition and structure of plantation unders tories (Molina et al. 1991). Eucalyptus releases both volatile and nonvolatile allelochem icals that are added to soil regularly. These chemicals are rich in soil beneath the canopy (Kohli 1998), but soil neutralizes/dilutes these allelochemicals with increasi ng depth (Molina et al. 1991). A study in Spain showed that allelopathy is due mainly from leaf litter rath er than aerial leachates (Molina et al. 1991). Allelopathy has also been observed in cott onwood in India. Le aves and litter of cottonwood are rich in phytotoxic phenols, wh ich reduce the germination and growth of some winter crops (Singh et al. 2001). Sp ecies diversity, species richness and evenness

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19 in cottonwood were less compared to Albizzia lebbeck and Dalbergia sissoo plantations in north India (Kohli et al. 1996). Less understory vegetation was observed in monoculture eucalyptus plantations than in plantations of other species in India (Singh et al. 1993). It also did not provide shelter and food for native fauna (Couto a nd Betters 1995). However, a study in a E. grandis plantation in southeastern Brazil found almost an equal number of species as in natural forest, indicating th at eucalyptus did not show any allelopathic effect in that situation (da Silva et al. 1995). In additi on, native eucalypt species provided shelter and food for animals in Australia (Strauss 2001) However, richness of ground-dwelling and arboreal fauna differed among eucalypt species in another study in southeastern Australia (Cork and Catling 1996). Well managed eucalypt sp ecies thus can be an effective tool to restore degraded sites and to control invasive light depe ndent species like cogongrass, thereby providing suitable habita t for some native flora and fauna.

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20 CHAPTER 3 METHODS Study Area This study began in summer of 2004 at Kent site (2800.99798'N and 8152.13770'W) near Lakeland in Polk County in central Florida (Figure 3-1). Kent is bordered by natural vegetation towards the east, west and north, with Saddle Creek in the east. It is a 50 ha CSA where phosphate wa s last mined in the 1940s. Prior to 2000, the site was dominated by cogongrass up to 2 m (6 ft) tall and had a hi story of catastrophic wildfires that destroyed the little natural vege tation in the area. Soil was highly compact, 100% heavy clay with pH of about 8.0, deficien t in N and contained a negligible amount of organic matter (CPI 2003). The climate is semitropical. Total annual rainfall recorded at Lakeland Linder Regional Airport was 1653.2 mm (66.1 in) in 2004. Rainfall occurred regularly through the year with more than 70% of the precipitation falling between June and September. Average monthly temperatur e ranged from 15.5C ( 59.9F) in January to 27.8C (82.1F) in both July and August. Roundup ProTM, a widely used herbicide, was applied at the site to control above-ground cogongrass. Soil was then doubl e disked to disturb under-ground rhizomes and was bedded. Native species such as cypr ess, cottonwood, slash pine and two species of noninvasive eucalyptus ( E. grandis and E. amplifolia ) were planted beginning in year 2000 (Figure 3-1). Plantings in cluded a separate operational area, a clone-configurationfertilizer study (SRWC-90), a cottonwood cl onal nursery and a demonstration site. However, this study focused only on the operational area and SRWC-90.

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21 Figure 3-1. Map of study area.

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22 The operational area was located in the eas tern side. Two species of eucalyptus and cottonwood were planted at different dates and densities (Table 3-1): E. grandis in single row/bed (Single-EG), double row/ bed (Double-EG), quadruple row/bed (Quadruple-EG) and cottonwood in double ro w/bed (Double-PD). Trees in the operational area, except Quadruple-EG, we re planted on beds spaced 3.5 m (11 ft) centers. Spacing between trees on a bed was 0.9 m (3 ft). Four rows of trees were planted on beds spaced 7 m (23 ft) ce nters in the Quadruple-EG culture. Table 3-1. Operational area: descrip tion, number of 15 x 15 m study plots, and associated average tree height (m), DB H (cm), density (trees/ha), basal area (m2/ha) and quadratic diameter (cm). Culture Description Single-EGDouble-EGQuadruple-EG Double-PD Planting date Jun. 2001Jul. 2001Jun. 2002 Feb. 2002 Planting density (trees/ha) 4,8369,7737,487 9,773 No. of plots 754 8 14.6a11.5b8.8c 7.0dHeight (m) (0.9)(1.8)(0.6) (0.7) 12.0a8.6b7.0c 4.9dDBH (cm) (0.9)(1.4)(0.7) (0.3) 814b886b1747b 3175aDensity (trees/ha) (248)(344)(231) (950) 13.4a8.1a11.0a 9.0aTotal basal area (m2/ha) (4.3)(2.5)(0.6) (3.3) 14.4a10.9b9.0c 6.0dQuadratic diameter (cm) (0.8)(1.7)(0.7) (0.4) Standard deviations in pare ntheses; Means in the same row with same letter are not significantly differe nt at 5% level. Cottonwood, E. grandis and E. amplifolia each represented by five or six genotypes, were planted in SRWC-90 in two planting configurations (single or double row/bed) with two fertilizer treatments (0 or 100 pounds ammonium n itrate per acre) in a split-plot design (Table 3-2). Initial planting was done in March 2001, and the fertilizer was applied in June 2002. Spacings between the beds and trees were similar to respective

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23 cultures in the operational ar eas. However, a large gap measuring 7.1 m wide existed between each treatment in SRWC-90. Table 3-2. Clone-configurati on-fertilizer study (SRWC-90): de scription and number of 8 x 5 m study plots. Description Treat. 1Treat. 2Treat. 3Treat. 4 Treat. 5 Culture SingleDoubleSingleDouble Double Fertilizer* 0011 0 Planting density (trees/ha) 4,8369,7734,8369,773 9,773 No. of plots# 4448 8 Planted in March 2001; *0 – unf ertilized, 1 – fertilized; #Equal number of plots in E. grandis and E. amplifolia subplots Experimental Design Four stands were selected in the opera tional area based on sp ecies culture, i.e., Single-EG, Double-EG, Quadruple-EG and Doub le-PD stand. A representative bed in each stand was identified and a series of 15 x 15 m plots were systematically established along the row at 35 m intervals, with the repr esentative bed in the middle of the plot (Table 3-1, Figure 3-2). The dist ance to the first plot was 50 m from the stand edge. Five beds and four interbed spaces were inside each plot in Single-EG and Double-EG cultures, whereas only three beds and two interbed spaces were inside Quadruple-EG culture. Understory shrubs/subshrubs and he rbaceous species with in the plots were quantified using 1 x 4 m and 1 x 1 m quadrats, respectively. In SRWC-90, 8 x 5 m plots were established taking E. grandis and E. amplifolia subplots as individual plots (Table 3-2, Figur e 3-2). Only four plots, two each in E. grandis and E. amplifolia were taken in Treatments 1 through 3, as cogongrass was dominant and native vegetations were minima l. In Treatments 4 and 5, where the trees were dominant, plots were established in all ei ght subplots of both the eucalyptus species.

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24 Cottonwood subplots were not incl uded in this study. Sin ce each treatment had four beds, the middle interbed space was taken as the middle of the subplots to exclude a border row on either side of the plot. There were only two beds and three interbed spaces in each plot. Understory shrub/subshrub and herbaceous species were quantified using 1 x 4 m and 1 x 1 m quadrats, respectively. Figure 3-2. Sampling schemes used for collec ting herbaceous and shrub/subshrub data in 15 x15 and 8 x 5 m plots. Data Collection Height and DBH of all trees within th e plots were measured. Trees in the operational area were measured in August 2004 and those in SRWC-90 in January 2005. Vegetation sampling in the operational ar ea and SRWC-90 was done in August 2004 and April 2005, respectively. Heights were meas ured using Haglof Vertex III Hypsometer

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25 (Haglof Inc., Sweden). Herbaceous and sh rub/subshrub vegetation cover by species was measured using foliar ocular observation in 1 x 1 m and 1 x 4 m quadrats, respectively. Modified Daubenmire scale (trace, 1 to 5%, 6 to 10%, 11 to15%, 16 to 26%, 27 to 49%, 50 to 80%, 81 to 95% or 96 to 100%) was us ed to quantify cover (Daubenmire 1959). Both understory herbs and shrubs/subshrubs were quantified separately for bed and interbed positions. Since all hardwood species present were in sapling stage, they were all included in the shrubs/shr ubs. The number of individual trees inside each 15 x 15 m and 8 x 5 m plots was counted while herbs a nd shrub/subshrub were counted in 1 x 1 m and 1 x 4 m quadrats, respectively. Only th e species rooted inside the quadrat were included. Individual shoots or stems we re counted in case of rhizomatous and stoloniferous plants. The whole clump was c ounted as an individual in case of plants growing in clumps. The canopy of each speci es was included in the cover estimates regardless of any overlap w ith other species. Canopy exte nding over the quadrat was also included in cover estimati on, even if the plants were not rooted in the quadrat. Six bed and six interbed quadrats, both fo r herbaceous and shrub/subshrub species, were taken in each plot in three cultures of eucalyptus in the operational area, while only four bed and four interbed quadrats were taken in the cottonwood stand. In SRWC-90, two bed and three interbed quadrats each fo r herbaceous and shrub/subshrub vegetation were taken (Figure 3-2). Sin ce canopy cover could not be measured for the trees due to hurricane damage on the stand, tree basal area was used instead of canopy cover for correlation. Estimated cover of herbaceous and shrub/subshrub species was used to calculate percent cover and species composition.

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26 Soil cores (15 cm deep) were taken in th e middle of each herbaceous quadrat in the operational area using a soil core r (10 cm diameter). Due to small plot size, only a bed and an interbed samples were taken in the middle of the SRWC-90 plots. Samples were air dried, ground and sieved with a 2 mm scree n. All bed and interbed samples from the same plot in the operational area were mixe d, homogenized and composited separately to prepare a bed and an interbed sample per pl ot. The samples were tested for SOM, N, macronutrients (Ca, Mg, P, K) and pH at the An alytical Research Lab at the University of Florida. Soil organic matter was determined using the loss-on-ignition method and total N by Kjeldahl Method. Metals were extracted using Mehlich 3 solution. Since the Kjeldahl Method could not be us ed in SRWC-90 samples because of high carbonate content, total N was estimated using NCS 2500 Elemental Analyzer (CE Instruments, Milan, Italy) using Dumas combustion. Samples were combusted yielding a gas mixture in which N was detected by a thermoconductivity detector. A large volume of water was used to extract nutrients in SRWC-90 soil sa mples as Mehlich 3 could not be used because of high carbonate content. Data Analysis Means of tree and soil parameters were tested using Tukey's multiple comparison procedure. Percent coverage, frequency and species composition were calculated separately for individual herbs and shrub/ subshrub using the Daubenmaire (1959) scale estimates. All three variables were analy zed separately using SAS (Version 8.2) with cultures and position as two main factors and plots nested w ithin cultures generalized linear model (PROC GLM) in Equation 3-1.

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27 yijk = + i + ik + j + ( )ij + ijk (3-1) i = 1, 2, 3, 4; j = 1, 2; k = 1, 2, . n i = effect of ith culture ik = effect of plot k nested within the ith culture j = effect of jth position ( )ij = effect of interaction between culture and position ijk = experimental error The Shannon-Wiener diversity index (S hannon and Wiener 1963) was calculated for each species culture in the operational area using the formulae: S 1 i H'pi ln pi (3-2) where H' = diversity index, s = number of species, pi = proportion of total sample belonging to ith species; H'max = LogS (3-3) max H' H' J (3-4) where H'max = maximum possible diversity, S = No. of species, J = Relative diversity The same was calculated for each species subplot in SRWC-90. The Jaccard index (Jaccard 1912) was calculated to see commun ity similarity between different species cultures using the formulae: Cj = j b a j (3-5) where Cj = Jaccard index, j = number of comm on species to both sites, a = number of species in site A, and b = number of species in site B. Importance Value Index (IVI), the function of cover, density and frequency, was calculated for each species as the sum of re lative cover, relative density and relative frequency. Therefore, the valu e of IVI ranged from 0 to 300. IVI = Relative cover + Relativ e frequency + Relative densit y (3-6) Relative cover = [(Total cover of one species)/ (Total cover of all species)] x 100

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28 Relative frequency = [(Frequency of one species)/ (Total frequency of all species)] x 100 Relative density = [(No. of individuals of one species)/ (Total number of individu als of all sp ecies)] x 100 Correlation analyses between IVI of the fi ve species with the highest IVI in each culture with stand basal area were done to find the relationship between tree dominance and the vegetation parameter at a 5% significance level.

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29 CHAPTER 4 RESULTS AND DISCUSSION Tree Size and Survival Average tree height differed significantly among cultures (p < 0.0001), ranging from 7.0 m for Double-PD to 14.6 m for SingleEG in the operational area (Table 3-1). Similarly, DBH differed significantly among cultures (p < 0.0001), as Single-EG was the greatest while that of Double-PD was the smallest. Single-EG had the lowest tree density (Tab le 3-1). Though the planting density of Double-EG was the highest (9773 trees/ha) among three eucalyptus cultures, their densities in August 2004, were not significantly different. Density of Double-PD was the highest and was significan tly different from the three eucalyptus cultures. Single-EG had the highest average total basal area (13.4 m2/ha); the smallest was for Double-EG. However, average total ba sal area was not signifi cantly different among the different cultures of eu calyptus and cottonwood. Th e high total basal area in Single-EG was due to larger diameter trees. Higher total basal area in Quadruple-EG and Double-PD compared to Double-EG, however, wa s due to the higher stand density rather than tree diameter. Quadratic diameter wa s the largest for Single-EG, while it was the smallest for Double-PD. It was significan tly different between different cultures of eucalyptus and cottonwood (p < 0.0001). Growth rate of eucalyptus was comparativ ely greater than that of cottonwood. Eucalyptus grandis grew up to 6.7 m in 2.5 years whereas cottonwood grew up to 1.3 m, when planted in single row (CPI 2003), with an average annual yield of 36.1 Mg/ha and

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30 19.9 Mg/ha for E. grandis and cottonwood, respectively (Str icker et al. 2000). Except in Single-EG, both DBH and total basal area in two other cultures are within the range of 3-year-old E. grandis plantation in Australia treated with different effluent rates (Myers et al. 1996). Early planting of Single-EG and Double-EG contri buted to larger height and DBH. Both were planted a year earlier than QuadrupleEG and about 8 months earlier than Double-PD (Table 3-1). Though Singl e-EG and Double-EG were planted about a month apart, Single-EG had si gnificantly greater height than Double-EG. Frequent occurrence of cogongrass in Si ngle-EG had less effect on gr owth. In spite of later planting date and higher planting density, height of Quadruple-EG was greater than that of Double-PD by 1.8 m. The diffe rence in the height can be a ttributed to the fast growth rate of E. grandis. Tree mortality was high in the operational area. Average survival in Single-EG was about 16% and in Double-EG was about 9%. Only 3 rows of trees were present in most Quadruple-EG plots. The survival wa s 23% in Quadruple-EG, while it was 32% in Double-PD. Low survival in all the sta nds might be due to the adverse edaphic conditions such as limited nutrients, low SOM, drought and periodic stand ponding. Rainfall in the area was below normal for three months following planting beginning October through December 2001. Total rainfall re corded at Lakeland Linder Airport was 17.8, 13.5 and 31.2 mm for October, Nove mber and December, respectively. Total rainfall of 241.2 and 341.7 mm for August a nd September, however, were above normal. Though clay soils retain more moisture, its surface loses water qui ckly during summer and creates air pockets around the root mass. This creates severe st ress to newly planted seedlings. Planting followed by packing/closi ng planting holes has pr oven to be essential

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31 for seedling survival. Though these factor s were taken into consideration during planting, they might have played significant role in the death of seedlings at the study site. Replanting was not done in the operational area. In SRWC-90, Treatment 4 had the largest E. grandis and E. amplifolia trees with average height of 11.4 and 10.4 m, and DBH of 7.8 and 7.6 cm, respectively (Table 4-1). Eucalyptus grandis was shortest (7.3 m) in Treatment 2 and E. amplifolia in Treatment 1 (5.2 m). Eucalyptus grandis was taller than E. amplifolia except in Treatment 3. Stand density was well maintained in SRWC-90. Dead seedlings were replaced within a few months after the initial planting. Density for E. grandis ranged from 3800 trees/ha in Treatment 3 to 8542 trees/ha in Treatment 2. Similarly, Treatment 2 had the highest E. amplifolia density (8958 trees/ha). Total basal area for E. amplifolia ranged from 8.5 m2/ha in Treatment 1 to 46.7 m2/ha in Treatment 4. For E. grandis, it ranged from 14.6 m2/ha in Treatment 3 to 32.9 m2/ha in Treatment 4. Calculated quadrati c diameter was the highest (8.7 cm) for E. grandis in Treatment 4, while it was the lowest (4.6 cm) for E. amplifolia in Treatment 2. Treatments 3, 4 and 5 had larger trees (h eight and DBH) compared to the same species and culture in Treatme nts 1 and 2, except that of E. grandis in Treatment 1, which was greater than that in Treatment 3 (Table 4-1). Ammonium nitrate applied to both Treatments 3 and 4 a year after planting had a positive effect in tree responses. Eucalyptus grandis leaf area, volume and biomass accumulation were comparatively higher for higher effluent treatment rate s in Australia (Mye rs et al. 1996).

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32Table 4-1. Clone-configurationfertilizer study (SRWC-90): average 3.75-year-old tree height (m), DBH (cm), density (trees/ha) basal area (m2/ha) and quadratic diameter (cm) by treatment and species. Treatment* Response 123 45 EG (n = 2) EA (n = 2) EG (n = 2) EA (n = 2) EG (n = 4) EA (n = 4) EG (n = 4) EA (n = 4) EG (n = 4) EA (n = 4) Height 8.8ad (2.5) 5.2cd (1.3) 7.3bcd (1.1) 6.1bd (0.5) 7.6bcd (1.4) 8.7ab (0.7) 11.4a (0.9) 10.4a (0.9) 9.8ac (1.1) 9.3ac (0.7) DBH 6.6ab (2.7) 4.6b (0.9) 4.3b (0.7) 4.3b (0.8) 5.7ab (0.9) 7.1a (0.1) 7.8a (0.3) 7.6a (0.8) 6.3ab (1.1) 6.9a (0.7) Density 4200bc (848) 4200b (282) 8542a (883) 8958a (883) 3800bc (282) 4600b (282) 5500ab (1000) 8700a (683) 6800ac (1758) 8600a (692) Total basal area 16.7b (10.2) 8.5b (2.2) 15.3b (6.8) 14.6b (2.3) 14.6b (6.3) 19.4bc (0.2) 32.9a (5.1) 46.7a (12.6) 27.2ab (1.3) 37.8ac (5.1) Quadratic diameter 7.1ab (2.9) 5.1b (0.5) 4.7b (0.8) 4.6b (0.6) 6.9ab (1.3) 7.3a (0.2) 8.7a (0.4) 8.2a (0.8) 7.3ab (1.1) 7.5a (0.7) EG = E. grandis, EA = E. amplifolia; Standard deviation in parenthese s; Means in each row with the same letter in same species group are not significantly different at 5% level; *See Table 3-2 for treatment descriptions.

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33 Regardless of the fertilizer application in Treatment 3, only the height and DBH of E. amplifolia was significantly different from that of E. amplifolia in Treatment 1 (Table 4-1). Treatments 1, 2 and 3 were highly dominated by cogongrass, where the IVI value was as high as 300 (Table 4-16). Treatments 2 and 5 were identical to Treatment 4 except that the latter had th e fertilizer treatment (Table 3-2). Tree responses (both E. grandis and E. amplifolia), except density, in Treatment 4 were significantly different when compared to Treatment 2. In Treatme nt 4, the highest av erage IVI of cogongrass was 201.7 and was 53.4 in Treatment 5 (Tab le 4-16). Though tree size in Treatment 4 was comparatively larger, it was not significan tly different when compared to Treatment 5. Tree responses in Treatments 4 and 5 s uggest that presence of cogongrass hinders tree growth, regardless of the treatment. Though Treatments 2 and 5 were identical, Treatment 5 had comparatively higher tree responses. Soil Characteristics Average TKN ranged from 0.18% in Quadruple-EG to 0.35% in Double-PD in the operational area (Table 4-2). The lowest was 0.11% for the interbed space in Quadruple-EG (Table C-1). Total Kjeldahl nitrogen in Quadruple-EG was significantly different from other cultures of eucalyptus and cottonwood. Phosphorus was highest in Double-EG and lowest in Doubl e-PD. It was also the high est in both bed and interbed positions in Double-EG (Table C-1). Pota ssium decreased from southeast (Double-EG) to north (Single-EG) in eucalyptus culture s (Table 4-2, Figure 3-1). However, concentration of Ca increased in eucalyptus cult ures from southeast to north. It decreased to the lowest concentration of 10448 mg/kg in Double-PD. Soil organic matter was highest in Double-PD and lowest in Quadruple-EG. It was highest (6.70%) on the bed in Double-EG a nd lowest (2.85%) in interbed position in

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34 Quadruple-EG (Table C-1). Average pHs in Single-EG and Quadruple-EG were still quite high and Double-EG had the lowest (7.3 ). Bulk density was slightly higher in subsurface (3 to 6 cm), except in Double-PD. Table 4-2. Operational area : average total Kjeldahl N [T KN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and BD (gm/cm3). Culture Response Single-EG (n = 4) Double-EG (n = 4) Quadruple-EG (n = 4) Double-PD (n = 4) TKN 0.29a(0.03) 0.32a(0.04) 0.18b(0.07) 0.35a(0.05) P 4098.0a(197.9) 4209.5a(83.5) 4126.0a(156.2) 3777.5a(794.2) K 187.4a(36.7) 234.8a(52.9) 211.7a(56.1) 210.5a(99.8) Ca 11049.0a(197.7) 10820.5a(1006.2) 10852.5a(824.5) 10448.0a(1687.94) Mg 1256.6a(79.6) 1169.2a(55.1) 1277.1a(86.0) 1109.3a(35.0) SOM 5.52a(0.50) 5.65a(1.60) 3.80b(1.20) 6.50a(1.14) pH 7.8ab(0.2) 7.3b(0.3) 7.9a(0.3) 7.5ab(0.3) BD (0 to 3 cm) 0.66a(0.07) 0.67a(0.11) 0.66a(0.22) 0.77a(0.13) (3 to 6 cm) 0.71ab(0.06) 0.67b(0.12) 0.79a(0.08) 0.71ab(0.16) Standard deviation is parenthe ses; Means in the same row w ith the same letter are not significantly different at 5% level. Soil parameters were variously influenced by cultures, plot locations and positions. Total Kjeldahl nitrogen was significantly different in plots within cultures (p = 0.0159) and the interaction between cultures and positions (p = 0.0011) (Table 4-3). Potassium was significantly different onl y in plots within culture (p = 0.0072) and between the positions (p = 0.0017). Magnesium, SOM and pH we re significantly different between the cultures. In addition, SOM was si gnificantly different between positions (p = 0.0130), pH between cultures an d in plots within cultures (p = 0.0451).

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35 Table 4-3. Operational area: significance (* = 5% level) of Culture, Plot (Culture) and Position mean squares for TKN, P, K, Ca, Mg, SOM, pH and BD. Response CulturePlot (Culture)Position Culture*Position TKN 0.04*2x10-3*0.01* 0.01* P 281081.4198326.4214462.8 155482.4 K 1654.06119.8*21900.6* 3900.5 Ca 500849.4969100.32569858.5 380760.0 Mg 49132.1*13867.54526.6 3353.9 SOM 10.2*0.97.6* 2.9 pH 0.6*0.1*0.01 0.03 BD (0 to 3 cm) 0.020.0110-5 0.1 (3 to 6 cm) 0.02*0.013x10-3 0.01 In SRWC-90, total nitrogen (TN) was slightly higher in all E. amplifolia treatments, except in 5 (Table 4-4). Total nitrogen ranged from 0.28% in Treatment 3 in E. grandis to 0.39% in Treatment 4 in E. amplifolia and Treatment 5 in E. grandis. Phosphorus ranged from 130.3 to 162.5 mg/kg in E. grandis. Postassium was the lowest (81.9 mg/kg) in Treatment 3 in E. grandis. Eucalyptus amplifolia had both the highest (Treat ment 1) and the lowest (Treatment 3) Ca, which was more or less similar in E amplifolia and E. grandis. Magnesium ranged from 494.4 mg/kg in E. grandis (Treatment 2) to 646.4 mg/kg in E. amplifolia (Treatment 5). Soil organic matter ranged from 7.96% in Treatment 3 to 9.76% in Treatment 2 in E. amplifolia. In E. grandis, SOM ranged from 7.75% in Treatment 3 to 9.69% in Treatment 5. In both E. amplifolia and E. grandis, pH was almost neutral, ranging from 6.8 to 7.3 in E. amplifolia and from 6.9 to 7.2 in E. grandis. Subsurface (3 to 6 cm) BD was slightly higher in E. amplifolia, except in Treatment 5. However, the surface (0 to 3 cm) BD was slightly higher in E. grandis, except in Treatment 1. None of the average soil responses were significantly different. However, surface BDs in E. amplifolia were significantly different between in terbed positions (Table C-2).

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36 Table 4-4. Clone-configurat ion-fertilizer study (SRWC-90) E. grandis and E. amplifolia plots: average total N [TN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and BD (gm/cm3). Response Treatment 1* (n = 2) Treatment 2 (n = 2) Treatment 3 (n = 2) Treatment 4 (n = 4) Treatment 5 (n = 4) E. grandis: TN 0.29a(0.07) 0.33a(0.10) 0.28a(0.08) 0.36a(0.12) 0.39a(0.13) P 146.1a(34.1) 139.6a(38.3) 162.5a(34.2) 145.8a(22.3) 130.3a(29.0) K 106.5a(15.1) 108.9a(23.9) 81.9a(7.5) 86.6a(14.4) 101.1a(23.2) Ca 1821.2a(51.5) 1832.0a(172.9) 1785.0a(108.1) 1777.6a(92.3) 1801.0a(182.6) Mg 514.4a(11.1) 494.4a(14.2) 567.9a(56.2) 603.8a(48.9) 643.3a(69.4) SOM 8.08a(1.69) 9.27a(2.96) 7.75a(2.22) 8.72a(2.56) 9.69a(3.12) pH 7.2a(0.2) 7.0a(0.2) 7.2a(0.2) 7.1a(0.3) 6.9a(0.4) BD (0 to 3 cm) 0.71a(0.11) 0.77a(0.12) 0.77a(0.08) 0.84a(0.07) 0.76a(0.14) (3 to 6 cm) 0.73a(0.05) 0.74a(0.13) 0.75a(0.09) 0.78a(0.06) 0.74a(0.05) E. amplifolia: TN 0.35a(0.04) 0.34a(0.08) 0.29a(0.05) 0.39a(0.08) 0.33a(0.08) P 141.7a(7.5) 144.1a(31.0) 146.1a(21.2) 131.2a(22.6) 140.6a(21.6) K 88.7a(10.1) 120.5a(50.6) 99.9a(9.6) 85.0a(7.8) 96.0a(15.7) Ca 1858.0a(32.1) 1848.2a(69.8) 1641.5a(4.7) 1774.8a(122.0) 1771.6a(88.6) Mg 571.3a(6.0) 537.5a(32.2) 523.1a(14.8) 599.1a(51.0) 646.4a(79.6) SOM 9.68a(1.49) 9.76a(2.98) 7.96a(1.91) 9.67a(1.82) 8.17a(1.85) pH 7.3a(0.2) 7.2a(0.2) 6.8a(0.1) 7.0a(0.3) 6.9a(0.3) BD (0 to 3 cm) 0.63a(0.07) 0.64a(0.06) 0.71a(0.05) 0.82a(0.08) 0.88a(0.10) (3 to 6 cm) 0.76a(0.07) 0.70a(0.04) 0.72a(0.07) 0.84a(0.03) 0.82a(0.12) Standard deviation in parenthe ses; Means in the same row w ith the same letter are not significantly different at 5% level; *See Table 3-2 for treatment descriptions.

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37 Across species, planting dens ities and ages, few soil properties were significantly different in the operational area. Similar resu lts have been observed in different aged stands (Albert and Barnes 1987; Archer 2003; Gilliam and Turrill 1993 ). Nitrogen and pH in both the operational area and SRWC-90 we re higher than in sandy and loamy soil in 0-30-year-old pine stands (Archer 2003). Phosphatic clay is highly fertile and has high amounts of P, Ca, Mg and K. Application of N is the only requirement for nonlegume crops (Stricker 2000). Amount of P and Ca in this study was more than 6 and 1.5 times, respectively, that recorded by Stricker. Howeve r, levels of Mg and K were lower. Even the concentrations of N, Ca, Mg and K in the study area were greater than in the overburden of reclaimed phosphate-mined areas (Segal et al. 2001). High exchangeable Ca and Mg and moderate to high exchangeable K have also been observed in cogongrass grasslands with montmorillonite clay due to the presence of carbonates such as calcite (CaCO3) and dolomite (Ca(MgCO3)2 – feldspar (Ca, K), and mica (Ca, Mg, K) in the Philippines. Cogongrass grassland soils in the area had less soil organic carbon and N compared to soils under well-develope d woody canopy (Snelder 2001). Due to mineralization and tree growth, N content a nd SOM in eucalyptus stand decreased with age (Loumeto and Bernhard-Reversat 2001). There was no distinct trend in the differe nce in nutrient level between the planting age, planting density and the species in the operational area, except th at the concentration of P decreased from Double-EG to Double-PD (Table 4-2). In SRWC-90, there was no significant difference in nutrients between fer tilized and nonfertilized treatments (Table 4-4). In E. grandis, concentration of Mg increased cons iderably from Treatment 2 to 5.

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38 Other nutrients (P, K, Ca and Mg) in SRWC -90, however, were far less than in the operational area. Different extracting solutions were used for the operational area and SRWC-90: the widely used Mehlich 3 for the operationa l area and water for SRWC-90 due to high carbonate content. Each medi um extracts nutrients at diffe rent levels. Mehlich 3 is superior to others in extracti ng nutrients. Mehlich 3 extrac ts more K compared to water (Woods et al. 2005). Mehlich 3 extracts 6 to 8% more Mg and 28% more Ca than ammonium acetate (Mehlich 1984). It also extr acts more P than Olsen method and 2 to 3 times more Ca and Mg than ammonium chlori de (Monterroso et al 1999). Presence of CaCO3 in calcareous soil also reduces the am ount of soluble P (T orbert et al. 2002), which can reduce the amount in water extraction. The northern section of the study area seems to have lower nutrient concentrations. Concentration of nutrients recorded in study SRWC-89 (near SRWC-90) was less (P = 1028.9, K = 175.1, Ca = 4663 and Mg = 1001.3 mg/kg) (Morse 2003) than in the operational area, but higher than in SRWC90. The northern section has comparatively lower elevation. Parts of the northern section remain under water most of the year which may lead to nutrient leaching. Soil organic matter in the operational area was almost similar to that of mineral soil, with the highest of 6. 50% in Double-PD (Table 4-2) Single-EG and Double-EG also had higher SOM than Quadruple-EG In SRWC-90, SOM was higher in all treatments than in mineral soil. Howeve r, both the operational area and SRWC-90 had lower SOM than SRWC-89 (Morse 2003). Ea rlier study done in the area showed that SOM under E. grandis stand was 215% higher compared to soil in cogongrass-dominated

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39 area (Wullschleger et al. 2004). Soil organic ma tter in this study was more than 130% in all the cultures when compared to Wullschlege r et al. Leaf litter is the main source of SOM. Litterfall was generally lower in eucalyptus compared to N-fixing species (Parrotta 1999) and increased with the age of the plantation (Jaiye oba 1998). Compared to 6-year-old first rotation, a 13-year-old coppice stand (6 years of coppice) had higher leaf litterfall (Bernha rd-Reversat et al. 2001). In anot her study, litterfall and litter accumulation however, were greater in first ro tation eucalyptus than in coppice (Loumeto and Bernhard-Reversat 2001). However, litter decomposition rate was slower in tropical eucalypt and pine plantations (O'Connell and Sankaran 1997). Though pH in the operational area was higher, pH in SRWC-90 was similar to SRWC-89 (Morse 2003). Soil pH depends on the presence of SOM. Accumulation of SOM acidifies soil and forms soluble complexes with nutrients such as Ca and Mg, leading to their loss through leaching (Brady an d Weil 2001). This partly explains lower nutrient concentration a nd pH value in northern section of the study area. Compared to pH (8 to 8.2) recorded before trees were pl anted in the area, pH recorded in this study support the hypothesis that pH decrea sed as trees increased in size. Bulk density is related to soil texture and SOM content. However, BD in this study was far less than that of mineral soil. In SRWC-90, BD of surface (0 to 3 cm) soil increased slightly from Treatment 1 to 5, while there was no specific trend in the operational area. Due to the expanding and sh rinking nature of clay soil (Brady and Weil 2001), large cracks develop on the surface during dry periods. Large volumes of water enter these cracks in the beginning of a wet peri od. When the soil is saturated, the cracks are closed due to swelling. Because of this characteristic BD of montmorillonite clay

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40 soil undergoes periodic changes with the amount of water available. The expansion of the clay may be the reason behind the low BD in the study area. Eff ect of tree on the BD couldn't be verified due to unstable nature of clay. Plant nutrients and organic matter are lost in surface runoff. Alternate contraction and swelling of clay, however, prevents the loss to some extent and helps in translocation of organic matter in clay soil. This compen sates for the movement of organic matter in the soil which is usually retard ed due to decreased infiltration after the soil is saturated (Snelder 2001). During the dr y season, litter enters these cr acks. In the beginning of the wet season, water conveys the surface orga nic matter through cracks. Both organic matter and litter are trapped in the soil profile after the expansion of clay. Distinct signs of organic matter trapped along the cracks coul d be seen in the soil. Without this property of clay soil, transloc ation of organic matter in the lower soil profile in CSAs would otherwise be impossible. Due to plantation age and limited translocation of organic matter in the soil profile, organic matter was mostly confined to the t op 15 cm of the soil in the study area. In some instances, organic matter was limited to depth less than that, with only the clay content below it. This corresponds with th e observation made in the Philippines where organic matter was distinct only in the surface soil in cogongrass grasslands and decreased rapidly with depth (Snelder 2001). Similar observations were made in the initial years of bioenergy cr op production in areas converted from traditional agriculture where organic matter was confined to only th e top 10 cm of soil (T olbert et al. 2002).

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41 Vegetation Characteristics Species Richness A total of 57 herbaceous species belongi ng to 23 families were recorded from the study area (Table A-1). Out of these 57, 40 (~70%) were native and eight (~14%) were introduced. Eight species were not identified, and the nativity of Carex sp. could not be identified at the species level. A total of 54 species belonging to 23 families were recorded from the operational area: 33, 35, 26 and 27 for Single-EG, D ouble-EG, Quadruple-EG and Double-PD, respectively (Table 4-5). Double-EG had the highest (25) number of native species. Table 4-5. Number of herbaceous and shrub/ subshrub species in the operational area and their nativity Nativity Single-EGDouble-EG Quadruple-EG Double-PD Herbaceous: Native Introduced Unidentified 25 4 4 25 4 6 20 3 3 22 4 1 Total 333526 27 Shrub/subshrub: Native Introduced Unidentified 7 4 0 17 3 3 6 2 0 7 2 0 Total 11238 9 Among identified species in the operational area, Stylisma patens, Typha latifolia, Desmodium trifolium, Chamaesyce hypericifolia, Panicum repens, Verbena scabra, Colloinsonia serotina, Krigia virginica, Calystegia sepium, Cucumis melo and Erechtites hieraciifolia were infrequent and occurred only once in 256 quadrats. Native species such as C. virginiana, B. alba, C. diffusa, P. americana, T. kunthii, A. americana and A. artemisiifolia were common. Apart from I. cylindrica, introduced species such as Cynodon dactylon and Lygodium japonicum occurred frequently.

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42 Of 54 herbaceous species in the operational area, 34 were significantly different (p < 0.05) in at least one category (percent cover, frequency and species composition) between cultures, plots within cultures, be tween positions and the interaction between cultures and positions (Table 4-6 and Table F-1) Percent cover of native species such as C. diffusa, T. kunthii, P. americana, B. alba, A. americana, A. artemisiifolia and S. parviflora were significantly different between cultures. However, C. virginiana, Phyla nodiflora, Andropogon virginicus, Cony za canadensis, P. americana, B. alba, Eupatorium serotinum, Hydrocotyle umbellata and Melothria pendula were significantly different among plots within the cultures. Ambrosia artemisiifolia, C. dactylon, P. americana and Salvia riperia had significantly different percent cover between positions. Though percent cover, frequency and species composition of I. cylindrica were not significantly different between the cultures, they were, however, significantly different among plots within cultures (T able 4-6). Its percent c over, frequency and species composition did not differ significantly between positions. Frequencies of 17 species were significantly different be tween cultures, while those of 21 species were significantl y different in plots within th e cultures. Frequencies of C. canadensis, P. americana, Lepidium virginicum and S. riperia were significantly different between positions (Table F-1). Co mpositions of only 9, 13 and 4 species were significantly different between cu ltures, plots within cultures and positions, respectively.

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43Table 4-6. Major herbaceous sp ecies in the operational area: significance (* = 5% level) of Culture (C), Plot (C) and Position (Pos) mean squares for cover (%), frequency, and species composition. Species Cover Frequency Species composition C P(C)PosC*PosCP(C)Pos C*PosCP(C)PosC*Pos Aeschynomene americana 0.9* 0.10.60.21457.1*423.2121.1 393.88.713.76.88.7 Ambrosia artemisiifolia 9.5* 2.714.4*7.01054.6400.5*365.8 588.4*2x10-3*3x10-42x10-3*10-3* Andropogon virginicus 152.2 78.0*26.033.4707.2319.8*0.6 15.90.020.01*2x10-33x10-3Bidens alba 288.1* 90.6*0.0216.82224.3*651.3*72.2 126.40.1*0.0210-33x10-3Clematis virginiana 251.0 113.0*17.319.34060.8*1352.6*292.9 426.60.10.03*0.020.01 Commelina diffusa 48.9* 11.722.318.14920.9*1214.9*53.0 36.70.02*4x10-30.010.01 Conyza canadensis 0.8 0.5*0.30.2111.552.4*81.7* 31.32x10-410-4*10-44x10-5Cynodon dactylon 177.6 243.0*291.0*94.51159.51439.5*36.7 393.40.030.04*0.1*0.02* Eupatorium capillifolium 6.7 4.90.25.2955.7*176.032.6 444.8*2x10-310-33x10-510-3Eupatorium serotinum 16.8 8.2*0.041.05801.2*819.0*122.2 250.60.013x10-3*5x10-55x10-4Hydrocotyle umbellata 0.2 0.3*0.040.1192.8160.3*0.4 19.510-410-4*10-52x10-5Imperata cylindrica 715.8 1440.6*0.105.52062.21866.6*24.7 51.00.10.2*0.020.01 Lepidium virginicum 0.6 0.40.10.6417.9*75.1*71.3* 103.1*10-33x10-42x10-44x10-4Lygodium japonicum 3.6* 0.80.030.21227.2439.1461.6 123.310-32x10-42x10-510-4Lythrum alatum 0.7 0.50.31.179.2138.3*28.8 138.710-410-42x10-510-4Macroptilium lathyroides 5.0 2.10.13.65414.3*498.4*26.4 121.03x10-310-34x10-53x10-3Melothria pendula 1.8 2.3*0.20.233.567.2*21.1 7.62x10-410-4*2x10-52x10-5Passiflora incarnata 1.4 1.11.00.6155.266.78.3 99.6*2x10-410-44x10-510-4Phyla nodiflora 9.1 9.2*0.62.2705.1*209.1*7.7 7.32x10-32x10-3*10-310-3Phytolacca americana 142.9* 15.4*62.0*18.2*8174.0*518.0*1534.3* 471.0*0.1*0.010.03*0.01 Polygonum hydropiperoides 0.7 0.40.21.0514.5*136.3349.8 387.23x10-4*10-42x10-410-4* Rhynchosia cinerea 6.9 4.56.86.4469.1*119.4*31.0 29.32x10-310-32x10-32x10-3Setaria parviflora 86.0* 22.312.43.93383.9*497.6*61.2 78.10.03*0.013x10-310-3

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44 A total of 26 shrubs/subshrubs (19 native and 4 introduced ) belonging to 14 families were recorded from the study area (Table A-2). Nativity of 3 species could not be determined. All 26 species were also re corded in the operati onal area. Double-EG had the highest species richne ss (23) followed by Single-EG (T able 4-5). Quadruple-EG and Double-PD had 8 and 9 species, respectivel y. Number of introduced species was the highest (4) in Single-EG followed by 3 in Double-EG and 2 each in Quadruple-EG and Double-PD. Urena lobata was the dominant and most freque nt species with highest percent cover, frequency and species composition in Single-EG, Double-EG and Quadruple-EG (Tables E-1, E-2, and E-3). In Double-PD, B. halimifolia had the highest frequency and species composition. However, percent cover of U. lobata (2%) was slightly higher than that of B. halimifolia (1.2%) (Table E-4). Species such as Celtis occidentalis, Triadica sebifera, Toxidendron radicans, Quercus virginiana, Ulmus americana, Rubus argutus, Lantana camara, Sida rhombifolia and Callicarpa americana were infrequent and recorded only once from the operational area. Introduced species such as L. peruviana, Schinus terebinthifolius, Solanum diphyllum and T. sebifera were found in the operational area. Percent cover, frequency and species co mposition of native species such as U. lobata and Quercus laurifolia were significantly different between cultures (Table 4-7). Percent cover of 8 species, viz., U. lobata, L. peruviana, Sambucus canadensis, R. argutus, S. diphyllum, L. camara, T. sebifera and B. angustifolia, were significantly different in plots within cultures. Similarl y, frequency and species composition of 9 and 5 species were significantly diffe rent in plots within cultures.

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45Table 4-7. Significant shrubs/subs hrubs in the operational area: significance (* = 5% level) of Culture (C), Plot (C) and Posi tion (Pos) mean squares for cover (%), frequency, and species composition. Species Cover Frequency Species composition CP(C)PosC*PosCP(C)PosC*PosCP(C)PosC*Pos Acer rubrum 0.010.0110-30.02456.5195.4203.331.32x10-3*10-32x10-410-3 Baccharis angustifolia 10-310-3*0034.754.7*0010-42x10-4*10-510-5Baccharis halimifolia 5.0*1.21.01.73824.9*225.1434.6554.745.653.427.432.7 Lantana camara 5.84.4*1.71.666.050.0*7.77.32x10-32x10-3*10-310-3Ludwigia peruviana 217.9*65.9*7.710.2869.11092.7*1313.3*225.90.2*0.1*10-30.1 Parthenocissus quinquefolia 0.5*0.10.30.2431.5*77.6*6.88.710-4*10-510-4*4x10-5* Quercus laurifolia 0.01*2x10-33x10-310-3320.3*61.9106.859.110-5*2x10-63x10-610-6Rubus argutus 0.60.4*0.020.01183.3138.9*7.77.34x10-43x10-42x10-52x10-5Sambucus canadensis 15.39.3*9.97.7*195.1236.3*43.315.90.020.030.040.01 Solanum diphyllum 180.7*13.1*18.4*21.7*7110.2*454.0*18.325.50.03*3x10-3*10-30.01* Triadica sebifera 0.30.4*0018.723.8*002x10-42x10-4*3x10-64x10-6Urena lobata 4438.9*304.8*61.340.98415.3*1501.5*0.0321.80.4*0.10.030.1

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46 In SRWC-90, 20 herbaceous species belongi ng to 11 families were recorded (Table A-1). Out of 20, 15 were native species wh ile the rest were introduced. The highest number of species (17) was found in Treatment 5, with th e lowest both in Treatments 2 and 3. Treatments 2 and 3 did not have any other herbaceous species except cogongrass. Within SRWC-90, E. amplifolia in Treatment 5 had the highest number of native species (Table 4-8). Table 4-8: Number of herb aceous and shrub/subshrub speci es in SRWC-90 and their nativity Nativity Treat. 1* Treat. 2 Treat. 3 Treat. 4 Treat. 5 EG EAEGEAEGEAEG EA EGEA Herbaceous: Native Introduced Unidentified 1 2 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 7 4 0 4 3 0 6 5 0 12 4 0 Sub Total 3 1111111 7 1116 Total 3 1 1 13 17 Shrub/subshrub: Native Introduced Unidentified 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 6 1 0 10 1 0 8 1 0 Sub Total 3 100007 7 119 Total 4 0 0 9 13 EG – E. grandis, EA – E. amplifolia; *See Table 3-2 for treatment descriptions Three species (Medicago lupulina, Verbena brasiliensis and Vicia acutifolia) recorded in SRWC-90 were not found in the operational area. In troduced species in SRWC-90 were C. dactylon, I. cylindrica, L. japonicum, M. lupulina and V. brasiliensis. Compared to E. grandis plots, E. amplifolia plots had more species that had significantly different percent c over and frequency in plots with in treatments (Table 4-9). Even the frequency of six species was signi ficantly different between treatments as compared to only two in E. grandis.

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47Table 4-9. Significant herbaceous species in E. grandis and E. amplifolia plots in SRWC-90: signifi cance (* = 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squa res for cover (%), frequency, and species composition. Species Cover Frequency Species composition T P (T)PosT*PosTP (T) PosT*PosTP (T)PosT*Pos E. grandis: Andropogon virginicus 128.7 76.7*3.74.43076.6922.1* 212.7130.20.1*0.020.010.01 Bidens alba 101.2 70.432.646.68953.4*1157.4* 17.424.80.03*0.010.010.01 Clematis virginiana 90.9 82.124.416.84291.91647.4* 39.11583.6*0.030.022x10-310-3 Imperata cylindrica 7552.2* 1618.7*69.68.38298.6*1219.1* 156.384.30.70.2*10-310-3 Medicago lupulina 0.5 1.30.30.4761.41473.8* 277.8136.42x10-410-34x10-52x10-4 Thelypteris kunthii 0.1 0.10.10.1347.2239.2* 049.62x10-510-510-510-5 Vicia acutifolia 2.9 2.110-410-44381.22326.4* 4.36.210-310-3*2x10-510-5 E. amplifolia: Andropogon virginicus 206.1 111.6*28.340.54520.1*1338.8* 39.155.80.10.02*10-32x10-3 Bidens alba 367.6 146.9*3.85.55958.6*1493.1* 4.36.20.10.1*10-310-3 Cirsium horridulum 0.01 0.01*00223.2416.7* 002.3x10-64x10-6*6x10-89x10-8 Cynodon dactylon 3.1 2.3*0.20.32864.6*640.4* 434.0*811.0*10-310-310-410-3 Imperata cylindrica 11291.4* 1697.5*21.728.310125.3*1 122.7* 212.795.51.2*0.1*0.010.01 Lygodium japonicum 0.9* 0.30.10.12922.9*443.7 351.6155.05x10-42x10-42x10-42x10-4 Medicago lupulina 0.6 1.00.10.2155.0289.4* 4.36.22x10-410-310-410-4 Passiflora incarnata 9.2 17.15.27.4396.8740.7* 69.499.20.020.030.010.01 Vicia acutifolia 0.8 0.4*0.010.019303.1*825.6* 017.410-32x10-310-310-3

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48 Percent cover and frequency of I. cylindrica were significantly different between treatments and plots within treatments in both E. grandis and E. amplifolia plots. Species composition was also significantly different in plots within the treatments in both the species plots. However, its species com position was significantly different between treatments only in E. amplifolia plots. Position did not have any si gnificant effect on percent c over, frequency and species composition of I. cylindrica in both E. grandis and E. amplifolia plots. Percent cover and frequency of A. virginicus was significantly different in plots within treatments in both E. grandis and E. amplifolia. However, species compositi on was significantly different only between treatments in E. grandis. Frequency of other na tive species such as T. kunthii, V. acutifolia and B. alba were significantly different in plots within the treatment in E. grandis plots. Thirteen shrubs/subshrubs were recorded in SRWC-90 (Table 4-8). Treatment 5 had the highest (13) species richness. Four a nd nine species were recorded in Treatments 1 and 4, respectively. More species were recorded in E. grandis than in E. amplifolia, in Treatments 1 and 5. Treatments 2 and 3 did not have any shrubs/subshrubs. Only one introduced species, S. terebinthifolius was recorded from SRWC-90. Urena lobata occurred quite frequently in SRWC -90. It had the highest average percent cover, frequency and species composition in E. amplifolia plots in Treatments 4 and 5 (Table E-6, E-7), and E. grandis plots in Treatment 4 (Table E-6). It had the second highest percent cover (3.7%), frequenc y (60.4) and species composition (0.2) in E. grandis plots in Treatment 5. Acer rubrum had the highest percent cover (1%), frequency (50%) and spec ies composition (0.5) in E. grandis plot in Treatment 1 (Table

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49 E-5). Similarly, B. halimifolia had the highest percent cove r (7.0%), frequency (62.5%) and species composition (0.5) in E. grandis plots in Treatment 5 (Table E-7). Percent cover, frequency and species composition of Ampelopsis arborea were significantly different in plots within treatment in E. amplifolia (Table 4-10). Similarly, percent cover, frequency and species composition of B. halimifolia were also significantly different in plots within treatment. In E. grandis, percent cover and frequency of R. argutus were significantly different in pl ots within treatment. Frequency and species composition of U. lobata were also significantly di fferent in plots within treatment in E. amplifolia. Only the species composition of A. rubrum was significantly different in plots within treatment in E. grandis (p < 0.0001). General characteristics of both disturbed si tes and new plantations were obvious in the study area. Characteristic spec ies of disturbed sites such as B. alba, P. americana, S. diphyllum, E. capillifolium, E. serotinum and A. artemissiifolia (Taylor 1992) occurred frequently. Species such as C. diffusa, S. diphyllum, A. ar temissiifolia, C. canadensis, B. halimifolia and S. canadensis are characteristic of mois t habitat and new plantations (Miller and Miller 1999). Clay soils are widely known for retaining more water. The current study area seems to be suitable habita t for such species due to nutrient rich and moist soil. Wind and animals play major roles in transporting seeds of these species. Treatments 1, 2 and 3 in SRWC-90 reflect cogongrass dominated grasslands in terms of species richness. Native species ar e hardly present in cogongrass grasslands. Regeneration of native species is slow or almost prohibited due to fire and intensive competition, lack of soil seed bank and adverse growing conditions for seedling establishment (Otsamo 2000b).

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50Table 4-10. Shrubs/subshrubs in E. grandis and E. amplifolia plots in SRWC-90: si gnificance (* = 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for co ver (%), frequency, and species composition. Species Cover Frequency Species composition T P(T)PosT*PosTP(T)Pos T*PosTP(T)PosT*Pos E. grandis: Acer rubrum 1.0 0.60.040.024053.81493.1108.5 155.00.20.1*2x10-310-3 Ampelopsis arborea 0.02 0.040.030.0284.3231.5156.3 84.310-32x10-310-310-3 Baccharis halimifolia 66.8 12.80.84.04469.3*324.11406.3 302.60.3*0.1*5x10-30.01 Parthenocissus quinquefolia 36.6 55.940.019.53875.33159.7*351.6 155.00.020.030.020.01 Quercus laurifolia 0.1 0.10.020.1381.9262.417.4 441.510-32x10-34x10-42x10-3 Rubus argutus 0.6 1.1*0.10.1303.8567.1*4.3 6.210-32x10-33x10-44x10-4 Sambucus canadensis 4.2 3.81.32.4545.6185.20 69.40.10.020.010.02 Schinus terebinthifolius 5.6 8.81.041.5892.91049.4*0 00.010.0100 Toxicodendron radicans 0.02 0.040.010.0224.846.317.4 24.810-34x10-310-32x10-3 Urena lobata 18.1 13.20.71.024491.61381.2*156.3 116.60.20.1*10-410-3 Vitis sp. 0.1 0.30.20.129.892.669.4 29.85x10-510-410-45x10-5 E. amplifolia: Acer rubrum 0.4 0.70.30.31777.0922.14.3 5.310-310-310-42x10-3 Ampelopsis arborea 0.01 0.01*10-40.001502.2451.4*4.3 26.40.210.01*2x10-5x10-5 Baccharis halimifolia 2.0 2.9*1.20.81892.41597.2*69.4 47.10.10.1*4x10-34x10-3 Celtis occidentalis 0.5 0.50.30.5223.2169.8156.3 223.210-410-410-410-4 Parthenocissus quinquefolia 30.0 9.79.012.53860.4*490.0734.0 527.00.02*2x10-34x10-30.01 Quercus laurifolia 0.1 0.10.030.04527.0304.839.1 28.15x10-4x10-42x10-43x10-4 Quercus virginiana 0.02 0.040.010.0224.846.317.4 24.810-53x10-510-510-5 Sambucus canadensis 0.2 0.30.10.1155.0104.24.3 6.20.030.040.010.02 Schinus terebinthifolius 0.7 1.00.10.2665.9706.0108.5 398.12x10-44x10-44x10-52x10-4 Urena lobata 943.2 988.7*20.839.49113.4*2480.7*4.3 6.20.70.2*4x10-32x10-3 Vitis sp. 3x10-3 2x10-34x10-33x10-3133.969.4156.3 133.95x10-73x10-76x10-75x10-7

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51 In phosphate mines, cogongrass mostly appe ars in wetter areas with high clay content (Segal et al. 2001). Clayey soil and the a llelopathic nature of cogongrass further impact the survival of native species in these grasslands. Low species richness in cogongrass dominated SRWC-90 treatments is therefore, not surprising. Cogongrass litter decomposes very slowly and its allelopa thic nature suppresses the growth of native species. Seedlings that germinate in the cogongrass finally die due to high competition. Species richness in cogongrass dominated SR WC-90 treatments was similar to that recorded in other areas. In Indonesia, only four seedling/sapling species were found in cogongrass grassland as compared to 22 species in riverine forest (Otsamo 2000b). In the southeastern US, the advancing border of cogongrass had 41 native species (Brewer and Cralle 2003). Fast-growing trees can suppress cogongr ass, amend soil, add organic matter through litter and create suitable microclimate for seed germination for shade tolerant species. Use of N-fixing species can also in crease biological activity in the soil and supply essential nutrients, such as N, for plant growth. These rapid changes in the understory and lack of competition with grass make the plantations suitable for native seed germination and seedling development (Parrotta et al. 1997). Cogongrass might benefit from the supply of N, because in the southeastern US longleaf pine (P. palustris) savannah, addition of N-fertilizer made cogongrass leaves comparatively greener. However, the astonishing finding was that the addition of P reduced cogongrass clonal growth and aboveground mass (B rewer and Cralle 2003). Multiple disking in this study has shown vari able results in controlling cogongrass. All planted sites were treated with herbicide and double disked prior to planting. A small

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52 area between Double-EG and Quadruple-EG was disked thrice and abandoned (Steve Segrest pers. comm.) without planting trees. However, cogongrass is completely absent in the area. Similar types of intensive site preparation were done to restore cogongrass dominated grasslands in I ndonesia. Sites were disked twice and harrowed with a rotavator before planting (Otsamo et al. 1995a ). Disking cuts underground rhizomes into smaller pieces and exposes them to direct s unlight, which ultimately kills the rhizomes. Rigorous site preparation, weeding (first 2 years) and early canopy closure suppresses cogongrass, but doesn't necessarily eliminate it (Otsamo 2000b). Exotic tree species have been used in pl antations worldwide due to short-rotation cycle. With the increasing interest in na tive species, use of exotic species has been criticized widely. The issue becomes pronounced in the case of exotic species such as eucalyptus because of possible allelopathy. It is clear from this study that intensive site preparation and well maintained eucalyptus ar e effective in contro lling cogongrass. Once cogongrass is controlled, native species could be introduced in to these exotic plantations after the first rotation (ITTO 1993). However, the species used should have the potential to amend soil and create suitable environments for native species. Species such as A. mangium are also capable of improving physi cal and chemical soil properties, including microclimatic c onditions and biological activ ity on cogongrass grasslands (Fisher 1995; Ohta 1990b). Acacia mangium encourages high seedling/sapling density and species richness, and good stand growth increases native species regeneration (Otsamo 2000b). In the Congo, species richne ss was higher in secondary fo rest than exotic species plantations. Within the eucalyptus plantati ons, species richness was higher in older

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53 plantation (26-years). Dist urbance intensity was anothe r factor for higher species richness. Disturbed sites had more species than undisturbed site. High plantation density and proximity to natural forest also had pos itive effects on species richness (Huttel and Loumeto 2001). Rather than planting density, stand age and proximity of Double-EG to natural area in this study had significant effect in species richness. Higher numbers of herbs and shrubs were found in Double-EG, which wa s a year older than Quadruple-EG and Double-PD. Because a larger area of Double-EG is adjacent to the natural area, there is higher potential for nativ e species to seed into Double-EG Single-EG was also planted at the same time with Double-EG. Its dist ance from the natural area might have slowed species recruitment rate. Similarly in Indonesia, 4-year-old A. mangium, Paraserianthes falcataria and G. arborea stands in cogongrass grasslands ha d fewer species regenerate (Otsamo 2000b). Even in SRWC-90, treatments with high density planting (Treatments 4 and 5) both had higher number of herbaceous species and shrubs. Regardless of high density planting, Treatment 2, however, had only one herbaceous species and no shrub/subshrub, probably due to the effect of cogongrass. Type of species planted also affects speci es recruitment in the stand. Abundant natural regeneration has been observed in the understory of N-fixing fast-growing species such as A. mangium and P. falcataria (Kuusipalo et al. 1995; Otsamo 2000b). Nitrogen-fixing species increase available N in addition to su ppressing cogongrass, whereas the species used in th is study only shade cogongrass.

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54 Species Diversity and Community Similarity Shannon-Wiener diversity indices for he rbaceous species were the same for Single-EG, Double-EG and D ouble-PD in the operational area (Table 4-11). Quadruple-EG had the lowest (0.9) diversity index. Double-EG and Double-PD had the highest (0.5) species diversity for shrub/s ubshrub, while Single-EG and Quadruple-EG had equal (0.2) diversity. Table 4-11. Herbaceous a nd shrub/subshrub species in the operational area: Shannon-Wiener diversity index (H'), maximum possible diversity (H'max) and relative diversity (J). Variable Vegetation type SingleEGDouble-EGQuadruple-EG Double-PD H' Herbaceous 1.01.00.9 1.0 Shrub/subshrub 0.20.50.2 0.5 H'max Herbaceous 1.51.61.4 1.5 Shrub/subshrub 1.01.30.9 0.9 J Herbaceous 0.70.70.6 0.7 Shrub/subshrub 0.20.40.3 0.5 Double-EG had the maximum possible divers ity of 1.6 for herbaceous species. The lowest was 1.4 in Quadruple-EG. Both Quadruple-EG and Double-PD had the same (0.9) maximum possible diversity for shr ub/subshrub. The highest was 1.3 in Double-EG. Relative diversity for herbace ous species was the highest (0.7) in Single-EG, Double-EG and D ouble-PD, and the lowest (0 .6) in Quadruple-EG. Double-PD had relative diversity of 0.5 for shrub/subshrub species. In SRWC-90, Treatment 5 had the highest diversity index of 0.9 for herbaceous species followed by Treatment 4 (0.7) (Tab le 4-12). Treatment 1 had the highest diversity index (0.4) for shrub/subshrub species. Maximum possible diversity was the highest in Treatment 5 for both herbaceous and shrub/subshrub species. Relative di versity for shrub/subs hrub species was the highest in Treatment 1 and lowe st in Treatments 4 and 5.

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55 Table 4-12. Herbaceous and shrub/subshrub species in SRWC-90: Shannon-Wiener diversity index (H'), maximum possi ble diversity (H'max) and Relative diversity (J). Variable Vegetation type Trt. 1Trt. 2Trt. 3Trt. 4 Trt. 5 H' Herbaceous 0.1000.7 0.9 Shrub/subshrub 0.4000.2 0.3 H'max Herbaceous 0.6001.2 1.3 Shrub/subshrub 0.5000.9 1.0 J Herbaceous 0.2000.6 0.7 Shrub/subshrub 0.9000.3 0.3 Results of species diversity in this study partly support th e second hypothesis. Rather than just the stand age, stand de nsity and planted species appears to have influenced the diversity in the study area. Though Double-PD was planted a year later, its diversity was similar to that of Single -EG and Double-EG, which were planted a year earlier. Disturbance plays a major role in species diversity. Diversity is high in communities with intermediate levels (intens ity) of disturbance (van der Maarel 1993). Species richness decreases at high or low fre quency disturbance either due to extinction of disturbance intolerant species or elimination by dominant species (Jobidon et al. 2004). However, herbaceous diversity increased in heavily harvested areas (Elliott and Knoepp 2005). Marked change in species diversity does not occur in initial stages of succession in plantations. However, it increases with ti me and soon reaches the maximum, which can take place as early as 3 years (Ohtsuka 1999) Tree plantations in degraded areas bring dramatic improvement in environmental cond itions, changing forest microclimate and soil. Fire is also less frequent in planta tions. These ultimately increase the understory diversity in plantations. Understory biodi versity in eucalyptus plantation is lower compared to acacia and pine (Ber nhard-Reversat and Huttel 2001).

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56 Communities at the study site are less diverse compared to real communities, where Shannon-Wiener diversity index fall between 1.5 and 3.5. This might be due to young stand age and the competiti on of native species with cogongrass. Allelopathy of eucalyptus also might have affected the species recruitment rate. Table 4-13. Operational area: Jacc ard's community similarity index (Cj) for herbaceous (H) and shrub/subshrub (S) species. Culture Double-EGQuadruple-EG Double-PD HSHS H S Single-EG H 0.4--0.5-0.5 -S --0.4--0.6 -0.6 Double-EG H ----0.4-0.4 -S ------0.4 -0.3 Quadruple-EG H -------0.5 -S --------0.6 None of the cultures in the operational ar ea were similar. The highest community similarity index (0.5) for herbaceous speci es in the operational area was between Single-EG and Quadruple-EG, Single-EG and Double-PD, and Quadruple-EG and Double-PD (Table 4-13). For shrub/subshr ub species, it was the hi ghest (0.6) between Single-EG and Quadruple-EG, Single-EG and Double-PD, and Quadruple-EG and Double-PD. The lowest similarity wa s between Double-EG and Double-PD for shrub/subshrub species. Though, herbaceous species diversity in Treatments 2 and 3 in SRWC-90 was zero (Table 4-12), they however showed the highest community similarity (1.0) indicating the two treatments were similar (Table 4-14). It was followed by Treatments 4 and 5 for both herbaceous and shrub/subshrub species Community similarity indices for herbaceous species between Treatments 2 and 4, 2 and 5, 3 and 4, and 3 and 5 were equal (0.1), but very low, suggesting minimal similarity between the treatments.

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57 Regardless of species planted, plantations of equal age had the same community in India (Pande et al. 1988). Different unde rstory species composition in plantations compared to that of nearby forest has also been observed elsewhere (Bernhard-Reversat and Huttel 2001), leading to difference in communities. Table 4-14. Clone-configuration-fertili zer study (SRWC-90): Jaccard's community similarity index (Cj) for herbaceous (H) and shrub/subshrub (S) species. Treatment 2 3 4 5 H SHSHS H S 1 H 0.3 --0.3--0.3-0.2 -S -0--0--0.4 -0.3 2 H ---1.0--0.1-0.1 -S -----0--0 -0 3 H -------0.1-0.1 -S ---------0 -0 4 H ----------0.6 -S -----------0.6 Importance Value Index (IVI) In the operational area, average IVI ranged from 0.2 for Eupatorium capillifolium in Double-PD (Table D-4) to 75.2 for I. cylindrica in Single-EG (Table 4-15) for herbaceous species. The second highest (74.8) was also for I. cylindrica in Double-PD followed by 52.7 for C. dactylon in Double-EG (Table 4-15). In Single-EG, average IVI ranged from 0.3 for Verbena scabra to 75.2 for I. cylindrica (Table D-1). Importance value index of I. Cylindrica ranged from 0 in Plot 1 to 161.7 in Plot 7. Three introduced species, viz., I. cylindrica, C. dactylon and L. japonicum, were among the 10 species with hi ghest average IVI. Among native species, C. virginiana had the highest IVI in Plot 1. However, average IVI was slightly lower than that of T. kunthii (Table 4-15).

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58 Average IVI value ranged from 1.2 to 214.7 for Celtis occidentalis and U. lobata in Single-EG, respectively. Sambucus canadensis had the second highest IVI (26.1). Importance value index of introduced species L. peruviana and S. diphyllum were 19.6 and 12.3, respectively. Table 4-15. Average IVI (> 5.0) of herb aceous and shrub/subshrub species in four cultures in the operational area. Species Single-EG (n = 7) Double-EG (n = 5) Quadruple-EG (n = 4) Double-PD (n = 8) Herbaceous: Aeschynomene americana 16.2 (11.5)2.3 (3.1)20.2 (5.6) 12.7 (6.2) Ambrosia artemisiifolia 1.2 (2.0)010.2 (7.6) 2.5 (3.8) Andropogon virginicus 14.1 (21.9)2.4 (3.6)0 0 Aristida purpurascens 03.9 (8.6)0 13.7 (21.9) Bidens alba 2.3 (3.9)27.3 (29.7)5.6 (8.7) 39.5 (21.4) Carex sp. 1.8 (3.1)8.4 (9.5)0.7 (1.4) 0 Clematis virginiana 29.1 (34.3)52.6 (28.0)14.4 (7.7) 25.0 (34.3) Commelina diffusa 20.6 (8.9)14.3 (10.0)40.7 (18.2) 7.7 (7.9) Cynodon dactylon 29.1 (33.6)52.7 (52.1)50.7 (32.0) 32.7 (33.6) Eupatorium capillifolium 4.3 (7.9)11.0 (9.7)7.2 (4.1) 0.2 (1.2) Eupatorium serotinum 9.3 (5.6)00 20.6 (13.2) Imperata cylindrica 75.2 (59.9)48.1 (75.9)42.1 (84.1) 74.8 (59.9) Lepidium virginicum 0.4 (1.1)06.8 (7.4) 0 Lygodium japonicum 11.1 (6.2)3.3 (3.7)1.0 (2.0) 5.0 (11.1) Macroptilium lathyroides 2.5 (3.8)0.4 (0.9)4.8 (8.0) 18.0 (11.5) Phyla nodiflora 4.2 (11.1)12.6 (14.7)0 0.8 (5.4) Phytolacca americana 22.5 (13.2)4.3 (1.7)40.4 (18.8) 0.7 (2.0) Polygonum hydropiperoides 0.6 (1.7)0.4 (0.9)5.4 (6.3) 0.3 (1.7) Rhynchosia cinerea 07.8 (11.4)0 0 Setaria parviflora 0.7 (1.7)03.6 (4.9) 19.2 (8.9) Thelypteris kunthii 31.7 (21.4)5.8 (6.8)11.8 (14.6) 8.6 (5.6) Shrub/subshrub: Acer rubrum 4.2 (3.7)3.7 (5.6)1.2 (2.4) 21.8 (8.8) Ampelopsis arborea 2.4 (2.0)7.8 (7.5)4.5 (5.3) 2.2 (3.7) Baccharis halimifolia 16.6 (11.6)11.7 (11.7)8.2 (7.7) 131.7 (36.9) Lantana camara 07.0 (15.5)0 0 Ludwigia peruviana 19.6 (13.8)60.6 (59.3)16.8 (19.9) 19.9 (5.8) Quercus laurifolia 2.6 (3.0)10.9 (8.6)0 0 Rubus argutus 09.5 (21.2)0 0 Sambucus canadensis 26.1 (19.8)2.2 (4.9)9.7 (11.2) 8.9 (8.7) Schinus terebinthifolius 3.4 (3.3)6.9 (6.8)0 2.0 (6.5) Solanum diphyllum 12.3 (6.2)7.4 (9.0)47.6 (27.8) 0 Urena lobata 214.8 (63.9)162.4 (77.5)211.8 (14.6) 103.6 (24.5) Standard deviation in parentheses

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59 In Double-EG, C. dactylon ranked first with average IVI of 52.7 (Table 4-15). Imperata cylindrica was third with aver age IVI of 48.1. Clematis virginiana was second with average IVI of 52.6, almost equal to that of C. dactylon. Imperata cylindrica was absent in Plots 1, 4 and 5. The lowest IVI was for Oxalis corniculata (Table D-2). Urena lobata had the highest IVI in Doubl e-EG followed by introduced L. peruviana (Table 4-15). Average IVI of U. lobata was 162.4 and that of L. peruviana was 60.6. The lowest IVI was 0.4 for Vitis sp. (Table D-2). Cynodon dactylon and I. cylindrica were first and second in Quadruple-EG (Table 4-15). Imperata cylindrica was absent in Plots 1, 2 and 3 (Table D-3). Importance value index of C. diffusa and P. americana were almost equal. At plot level, C. diffusa had the highest IVI (59.2) in Plot 3 after C. dactylon and I. cylindrica. The lowest IVI (0.4) was for Ampelaster carolinianus (Table D-3). Urena lobata had the highest IVI (211.7) w ith the lowest IVI of 1.1 for Diospyros virginiana (Table D-3). Introduced species S. diphyllum and L. peruviana had the second and third highest IVI (Table 415). Among other native species, S. canadensis and B. halimifolia had IVI of 9.7 and 8.2, respectively. Imperata cylindrica was present in all the plots in Double-PD (Table D-4). It had the highest average IVI (74.7) followed by B. alba (39.5). The lowest IVI (0.2) was for E. capillifolium. Importance value index of I. cylindrica ranged from 3.3 in Plot 8 to 177.8 in Plot 6. Double-PD was dominated by B. halimifolia with an IVI of 131.7 (Table D-4). Urena lobata had the second highest IVI of 103.6. Double-PD is the only culture in the

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60 operational area where native shrub/subshrub spec ies have the three highest IVI values. Acer rubrum was third with the IVI of 21.8. In SRWC-90, I. cylindrica was the dominant herbaceous species and had the highest IVI in all treatments except Treat ment 5, in which the IVI was 2.8 in E. amplifolia (Table 4-16). It had the highest possible IVI in Treatments 2 and 3 in E. grandis and Treatment 1 in E. amplifolia. Its IVI was almost 300 in Treatments 2 and 3 in E. amplifolia. There were no other herbaceous species in Treatments 2 and 3, both in E. grandis and E. amplifolia. Treatment 1 of SRWC-90 had four nativ e shrubs/subshrubs (Table 4-17). Acer rubrum had the highest average IVI value (127.3) However, its plot level IVI was 254.6 in Plot 1 (Table D-5). Both Treatments 2 and 3 did not have any shrub/subshrub species. In Treatment 4, I. cylindrica had the highest IVI both in E. grandis and E. amplifolia (Table 4-16). Among native species, C. virginiana had the highest average IVI of 51.3 in E. amplifolia followed by C. virginiana (28.4) in E. grandis. The lowest average IVI value was 1.1 for P. americana and A. virginicus in E. grandis. Treatment 4 had only nine sh rub/subshrub species with U. lobata highest with IVI of 146.8 and 114.3 in E. grandis and E. amplifolia, respectively (Table 4-17). Acer rubrum was second highest in E. amplifolia with IVI 13.7 and S. canadensis in E. grandis with IVI 41.7. The lowest was for S. terebinthifolius in E. amplifolia. Imperata cylindrica had the highest IVI in Treatment 5 followed by B. alba in E. grandis (Table 4-16). In E. amplifolia, B. alba had the highest IVI followed by V. acutifolia. Imperata cylindrica was present only in Plot 2 in E. grandis and Plots 3 and 4 in E. amplifolia. Its IVI ranged from 3.6 in E. amplifolia to 213.7 in E. grandis.

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61 Lowest average IVI was 0.9 for T. kunthii in E. grandis and 0.8 for A. artemisiifolia, Melothria pendula and Macroptilium lathyroides in E. amplifolia (Table D-7). In Treatment 5, native shrub/subshrub sp ecies occupied the first three positions in both eucalyptus species (Table 417). Importance value index of U. lobata was 100.5 in E. grandis and 195.3 in E. amplifolia. Baccharis halimifolia and A. rubrum had second and third highest average IVI in E. grandis while B. halimifolia and P. quinquefolia in E. amplifolia. Quercus virginiana had the lowest IVI (2.0) in E. amplifolia. It was absent in E. grandis. At the plot level, E. grandis was better than cottonw ood in suppressing cogongrass in the operational area. Cogongrass was absent in Plot 1 in Single-EG (Table D-1) and three plots each in Double-EG (Table D-2) a nd Quadruple-EG (Table D-3). However, it was present in all eight plots in Double-PD (Table D-4). Stands with good growth and early canopy closures are necessary for s uppressing cogongrass and to enhance secondary succession. In uneven stands, cogongrass wi ll dominate and will slow the secondary succession (Otsamo 2000b). However, the Single-EG does not support th e finding. In Single-EG, IVI of I. cylindrica increased from Plots 2 to 7, except in Plot 5 where its value decreased to 10.8 and then increased again. Imperata cylindrica was absent in Plot 1. Plots 3, 4 and 7 had the highest tree density of 1075, 1003 and 1003 trees/ha, respectively (Table B-1). Total basal area was also in the highest range within the culture with 15.3 m2/ha, 17.9 m2/ha and 15.4 m2/ha in Plots 3, 4 and 7, respective ly. In Plot 1, the density was 681 trees/ha with total basal area of 11.0 m2/ha. Despite low density and basal area, I. cylindrica was well suppressed in Plot 1.

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62Table 4-16. Average IVI (> 5.0) of herbaceous species in SRWC-90. Species Treatment 1* Treatment 2 Treatment 3 Treatment 4 Treatment 5 EG (n = 2) EA (n = 2) EG (n = 2) EA (n = 2) EG (n = 2) EA (n = 2) EG (n = 4) EA (n = 4) EG (n = 4) EA (n = 4) Andropogon virginicus 00000000 38.5 (23.1) 32.9 (27.3) Bidens alba 00000000 48.0 (24.3) 66.8 (61.8) Clematis virginiana 000000 28.4 (19.7) 51.3 (37.4) 45.2 (29.5) 37.0 (21.5) Cynodon dactylon 000000 7.2 (14.3) 23.2 (46.4) 21.7 (16.4) 31.4 (20.9) Eupatorium serotinum 000000 21.0 (26.7) 000 Imperata cylindrica 266.7 (47.1) 300.0 (0.0) 300.0 (0.0) 296.7 (4.7) 300.0 (0.0) 299.9 (0.1) 201.7 (98.9) 169.4 (128.1) 53.4 (106.8) 2.8 (3.6) Lygodium japonicum 17.3 (24.4) 00000 7.3 (9.9) 8.6 (10.7) 5.3 (7.8) 16.1 (4.5) Medicago lupulina 000000 6.4 (12.8) 0 7.9 (10.6) 3.5 (7.0) Passiflora incarnata 000000 020.9 (41.8) 00 Thelypteris kunthii 16.0 (22.7) 00000 05.3 (10.5) 0.9 (1.9) 16.7 (20.5) Vicia acutifolia 000000 20.9 (41.7) 13.0 (26.0) 41.5 (24.9) 42.6 (20.1) Standard deviation in parentheses; *S ee Table 3-2 for treatment descriptions

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63Table 4-17. Average IVI (> 5.0) of shrub/subshrub sp ecies in SRWC-90 Species Treatment 1* Treatment 2 Treatment 3 Treatment 4 Treatment 5 EG (n = 2) EA (n = 2) EG (n = 2) EA (n = 2) EG (n = 2) EA (n = 2) EG (n = 4) EA (n = 4) EG (n = 4) EA (n = 4) Acer rubrum 127.3 (180.0) 0000 00 13.7 (21.7) 44.3 (30.7) 19.9 (5.0) Ampelopsis arborea 00000 0 6.1 (12.2) 0 5.4 (10.8) 7.5 (10.8) Baccharis halimifolia 12.9 (18.3) 0000 0 18.9 (22.4) 10.6 (13.5) 94.0 (49.9) 41.8 (50.1) Celtis occidentalis 00000 0000 6.0 (7.7) Parthenocissus quinquefolia 00000 0 31.4 (36.6) 3.3 (6.5) 31.0 (26.9) 37.4 (18.1) Quercus laurifolia 00000 0 7.7 (9.5) 5.8 (11.5) 12.6 (10.9) 11.9 (6.4) Rubus argutus 00000 000 7.0 (14.1) 0 Sambucus canadensis 00000 0 41.7 (29.1) 2.8 (5.6) 4.5 (9.0) 0 Schinus terebinthifolius 00000 00 2.6 (5.1) 17.0 (24.5) 14.3 (16.5) Toxicodendron radicans 00000 000 8.6 (17.3) 0 Urena lobata 9.8 (13.9) 0000 0 146.8 (108.0) 114.3 (132.3) 100.5 (57.8) 195.3 (45.8) Vitis sp. 0 15.1 (21.3) 000 0 1.61 (3.2) 01.5 (2.9) 0 Standard deviation in parentheses; *S ee Table 3-2 for treatment descriptions

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64 In Double-EG, I. cylindrica was well controlled in Plot s 1, 4 and 5 (Table D-2). Plot 1 had the highest density (1477 tr ees/ha) and total basal area (10.6 m2/ha) followed by Plot 4 (Table B-1). Though Plot 5 had the lowest density (612 trees /ha), its total basal area (7.9 m2/ha) was higher than that of Plots 2 and 3. Plot 2 had higher density (792 trees/ha), but its total basal area was smaller than that of Plot 3. Importance value index of cogongrass in Plot 2 (66.8) is less than that of Plot 3 (173.6). Tree dominance expressed either as basal area or density seem s to be effective. A similar conclusion can be made in the case of Quadruple-EG. C ogongrass was present only in Plot 4 which had the least density (1430 trees/ha). However, tota l basal area was slightly greater than that of Plot 2 and smaller than that of Plot 1 and 3 (Table B-1). In Double-PD, total basal area decreased considerably from Plot 1 (13.2 m2/ha) to Plot 6 (6.0 m2/ha) and increased slightly in Plot 7 (6.6 m2/ha) (Table B-1). It however, decreased again in Plot 8 (5.4 m2/ha). Tree density did not s how any particular trend. However, IVI of I. cylindrica was considerably lower in plots with higher total basal area, except in Plot 8. Plot 8 had the lowe st IVI (3.3) (Table D-4), whereas it had both the lowest total basal area and density (2054 trees/ha). Double-PD also had decreasing I. cylindrica IVI with increasing total basal area. Both E. grandis and cottonwood suppress cogongra ss. Though cottonwood forms dense canopy as early as E. grandis, its defoliating nature may give cogongrass an opportunity to come back in th e understory. In contrast, E. grandis forms permanent canopy. Frequent occurrence of I. cylindrica in Double-PD in the present study was also largely due to edge effect. There was only a thin strip of cottonwood (5 rows) where the study plots were established a nd cogongrass was dominant on either side of the stand.

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65 Due to edge effect, cogongrass advanced in the understory from either side. Though cogongrass appears on the edges, some areas in the middle part of the stand were free from cogongrass. Regardless of above observations, the corr elation between tota l basal area and cogongrass IVI in three E. grandis cultures in the operational area was not significant (r = 0.19, p = 0.4587) (Figure 4-1, Table 4-18). This may however, be due to nonlinear data and small sample size (n = 16). Thelypteris kunthii, C. dactylon, C. virginiana, P. Americana, B. Alba, C. diffusa and E. capillifolium had negative associations with cogongrass. The relationship was significant in C. dactylon (r = -0.50, p = 0.0437), C. virginiana (r = -0.58, p = 0.0187) and C. diffusa (r = -0.50, p = 0.0468). Thelypteris kunthii had significant positive relationship (r = 0.51, p = 0.0420) and B. alba had significant negative relationship (r = -0.58, p = 0.0177) with stand basal area. 0 20 40 60 80 100 120 140 160 180 200 0.005.0010.0015.0020.00 E. grandis TBAHCogongrass IVI Figure 4-1. Eucalyptus grandis in the operational area: correlation between total basal area per hectare and cogongrass IVI. Urena lobata, S. canadensis, S. diphyllum and A. rubrum were positively correlated with stand basal area in three E. grandis cultures (Table 4-19). Ludwigia peruviana,

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66 B. halimifolia, Q. laurifolia and R. argutus had nonsignificant correlations. Urena lobata and L. peruviana had significant negative correlation (r = -0.72, p = 0.0015). Regardless of cogongrass presence in all the plots in Double-PD, cogongrass had nonsignificant correlation with stand basal area (r = -0.21, p = 0.6103) (Figure 4-2, Table 4-18). Thelypteris kunthii, C. dactylon, C. virginiana, B. alba, C. diffusa and E. capillifolium also had negative correl ation with cogongrass. There was a significant negative correlation between B. halimifolia and L. peruviana in Double-PD (r = -0.71, p = 0.0488) (Table 4-19). Bidens alba and L. peruviana did not have any correlations with stand basal area (r = 0, p = 1.000). 0 50 100 150 200 250 300 0.002.004.006.008.0010.0012.0014.0016.00 Cottonwood TBAHCogongrass IVI Figure 4-2. Cottonwood in th e operational area: co rrelation between total basal area per hectare and cogongrass IVI. In SRWC-90, IVI for cogongrass was as high as 300 in both E. grandis and E. amplifolia in Treatments 1, 2 and 3 (Table 416). Importance value index decreased with increasing tree basal area only in the case of E. amplifolia in Treatment 4. It did not have any distinct pattern in ot her treatments. However, ther e was a considerable decrease

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67 in average IVI in Treatments 4 and 5 compared to the first three treatments. Treatments 4 and 5 had comparatively higher total basal area (Table 4-1). One of the main reasons for cogongrass dominance in SRWC-90 was edge effect. A large gap (7.1 m wide) existed between each treatment, originally designed for watering the trees. Because of the large gap, cogongra ss moved into the stands. However, cogongrass had significan t negative correlation with both E. grandis (r = -0.91, p < 0.0001) and E. amplifolia (r = -0.73, p = 0.0028) basal area in SRWC-90 (Figures 4-3 and 4-4). It also was negativ ely correlated with eucalyptus (both operational and SRWC-90 combined) sp ecies in the study area (r = -0.52, p = 0.0004) (Figure 4-5). Correlation was highly significant in E. grandis (Figure 4-3) compared to E. amplifolia (Figure 4-4). It was not significant in cottonwood (Figure 4-2). Eucalypts species are apparently superior to cottonwood in suppressing cogongrass. Among eucalyptus species, E. grandis seems to perform better than E. amplifolia. Removing overstory canopy may not have significant effect on cogongrass regrowth in controlled areas. During so il sampling, cogongrass rhizomes were not observed where cogongrass was controlled, indi cating less chance of reinvasion from the rhizome. Wind-borne seeds and spread fr om current patches are the only potential sources. However, seeds are less likely to germinate if the groundcover remains intact. In a fast-growing A. mangium plantation in Indonesia, ca nopy removal to enhance the growth of underplanted Anisoptera marginata did not result in cogongrass regrowth in the gaps (Otsamo 1998b). Similar result wa s found in the gaps created in another A. mangium plantation in cogongrass grassland (Otsamo 2000a).

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68Table 4-18. Spearman correlation coeffici ent (r) of herbaceous species with hi ghest IVI in the operational area TBAH IC TK CYD CV PA BA CD AA EC TBAH --0.19 (0.4587) 0.51 (0.0420) -0.5 (0.0486) -0.17 (0.5382) 0.44 (0.0895) -0.58 (0.0177) 0.07 (0.8034) 0.46 (0.0694) -0.27 (0.3098) IC -0.21 (0.6103) ---0.05 (0.8384) -0.50 (0.0437) -0.58 (0.0187) -0.17 (0.5318) -0.33 (0.2146) -0.50 (0.0468) 0.05 (0.8600) -0.39 (0.1323) TK -0.21 (0.6103) -0.17 (0.6932) ---0.39 (0.1328) 0.26 (0.3200) 0.30 (0.2478) -0.31 (0.2342) 0.16 (0.5557) 0.38 (0.1410) -0.14 (0.6059) CYD 0.23 (0.5702) -0.31 (0.5702) -0.76 (0.0280) --0.05 (0.8540) -0.10 (0.7044) 0.26 (0.3198) 0.22 (0.4117) -0.39 (0.1294) 0.33 (0.2136) CV -0.24 (0.5702) -0.02 (0.9554) 0.45 (0.2604) -0.57 (0.1390) ---0.30 (0.7044) 0.18 (0.5008) 0.19 (0.4778) -0.20 (0.4455) 0.27 (0.3026) PA 0.08 (0.8461) 0.25 (0.5546) -0.58 (0.1340) 0.08 (0.8461) 0.25 (0.5546 ---0.19 (0.4781) 0.63 (0.0090) 0.58 (0.0183) -0.36 (0.1746) BA 0 (1.000) -0.31 (0.4556) 0.38 (0.3518 -0.12 (0.7789) -0.33 (0.4198) -0.58 (0.1340) ---0.26 (0.3385) -0.32 (0.2270) 0.12 (0.6646) CD 0.24 (0.5604) -0.63 (0.0912) -0.24 (0.5604) 0.27 (0.5204) 0.24 (0.5604) 0.42 (0.2969) -0.41 (0.3069) --0.16 (0.5614) 0.06 (0.6646) AA 0 (1.000) 0.07 (0.8665) -0.76 (0.0280) 0.81 (0.0149) -0.33 (0.4198) 0.41 (0.3100) -0.45 (0.2604) 0.12 (0.7735) ---0.24 (0.3624) EC 0.58 (0.1340) -0.08 (0.8461) 0.41 (0.3100) -0.41 (0.3100) -0.57 (0.1340) -0.14 (0.7358) -0.08 (0.8461 0.08 (0.8423) -0.41 (0.3100) --Coefficients above the diagonal for combin ed Single-EG, Double-EG and Quadruple-EG, and below the diagonal for Double-PD; P-value in parentheses; TBAH: Total basal area per hectare, IC: I. cylindrica, TK: T. kunthii, CYD: C. dactylon, PA: P. americana, BA: B. alba, CD: C. diffusa, AA: A. americana, EC: E. capillifolium

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69Table 4-19. Spearman correlation coeffici ent (r) of shrub/subshrub species with highest IVI in the operational area TBAH UL SC LP BH SD QL AR RA TBAH --0.29 (0.2790) 0.27 (0.3020) -0.37 (0.1603) -0.17 (0.5243) 0.21 (0.4306) -0.25 (0.3463) 0.32 (0.2253) -0.36 (0.1657) UL -0.05 (0.9108) ---0.43 (0.0972) -0.72 (0.0015) -0.08 (0.7688) 0.35 (0.1808) 0.14 (0.6050) -0.43 (0.0942) -0.42 (0.1052) SC -0.25 (0.5546) -0.41 (0.3100) --0.25 (0.3502) -0.22 (0.4206) -0.18 (0.5099) -0.17 (0.5284) 0.49 (0.0558) -0.17 (0.5284) LP 0 (1.0000) 0.38 (0.3505) -0.28 (0.4963) ---0.14 (0.6024) -0.54 (0.0300) -0.26 (0.3248) 0.33 (0.2147) 0.44 (0.0893) BH -0.21 (0.6103) -0.48 (0.2329) 0.41 (0.3100) -0.71 (0.0488) --0.003 (0.9909) 0.38 (0.1465) -0.39 (0.1317) 0.20 (0.4471) SD _ _ --0.03 (0.9168) -0.22 (0.4028) -0.31 (0.2383) QL _ _ _ ---0.19 (0.4737) -0.07 (0.8062) AR 0.05 (0.9103) 0.18 (0.9103) -0.49 (0.2093) -0.59 (0.1237) 0.24 (0.5678) _ --0.22 (0.4016) RA _ _ _ _ --Coefficients above the diagonal for combin ed Single-EG, Double-EG and Quadruple-EG, and below the diagonal for Double-PD; P-value in parentheses; TBAH: Total basal area per hectare, UL: U. lobata, SC: S. canadensis, LP: L. peruviana, BH: B. halimifolia, SD: S. diphyllum, QL: A. laurifolia, AR: A. rubrum, RA: R. argutus

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70 0 50 100 150 200 250 300 350 400 0.005.0010.0015.0020.0025.00E. grandis TBAHCogongrass IVI Figure 4-3. Eucalyptus grandis in SRWC-90: correlation between total basal area per hectare and cogongrass IVI. 0 50 100 150 200 250 300 350 0.0010.0020.0030.0040.0050.00E. amplifolia TBAHCogongrass IVI Figure 4-4. Eucalyptus amplifolia in SRWC-90: correlation between total basal area per hectare and cogongrass IVI.

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71 0 50 100 150 200 250 300 350 010203040 TBAH ( E. grandis & E. amplifolia )Cogongrass IVI Figure 4-5. Eucalyptus (E. grandis and E. amplifolia combined) in the study area: correlation between total basal ar ea per hectare and cogongrass IVI. It appears that fast-gro wing tree plantations have the potential to suppress cogongrass on CSAs in central Florida. Sim ilar observations have been made in Asia using fast-growing trees (Awang and Taylor 1993; Otsamo et al. 1997). However, initial intensive management is necessary to suppr ess cogongrass (Otsamo et al. 1995a), before the trees can establish in the plantation. Both planting fast-growing trees and intensive site preparation reduce cogongrass rh izomes (Brook 1989; Soerjani 1970). Despite the positive results, there were however some limitations of the study. Sufficient details on vegetation and soil change could not be achieved from this study as it was done in a limited time. There were some difficulties in designing statistically valid sampling design due to small study area. Statis tically valid tests could not be made due to small sample size. Seasonal vegetation a nd soil quality evaluation was limited since data collection was done only once. Enough details could not be collected on the effectiveness of fast-growing trees on cogongrass control due to stand damage by

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72 hurricanes. Problems with metal extraction in SRWC-90 soil samples limited the comparison of soil nutrients between the operational area and SRWC-90.

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73 CHAPTER 5 CONCLUSIONS Both tree height and DB H differed significantly (p < 0.0001) by species and cultures in the operational area. Height a nd DBH of Single-EG and Double-EG in the operational area were larger than for the same trees in the same cultures in SRWC-90, probably due to less competition with cogongrass. Stand density was comparatively lower in E. grandis cultures in the operational area. Si ngle-EG had the highest total basal area. Tree density was low in E. grandis stands in the operational area due to low survival. Clone-configuration-fertilizer study had higher tree density. Presence of cogongrass seems to hinder tree grow th, regardless of treatment. The generally fertile soil at the site had few significant differences in soil characteristics in the operational area. Tota l Kjeldahl nitrogen was significantly different between cultures (p = 0.0002), plots within cultures (p = 0.0159) and positions (p = 0.0028). Soil nutrients in SRWC-90 were lower than that in the operational area, which might be due to different extraction methods used. pH was almost neutral in SRWC-90, but was quite high in the operational area. So il organic matter was higher than in mineral soils, both in operational area and SRWC-90. Potassium was significantly different only in plots within culture (p = 0.0072) and between the positions (p = 0.0017) in the operational ar ea. Magnesium, SOM and pH were significantly different between the cultures. Soil organic matter was also significantly different between positions (p = 0.0130) and pH in plots within cultures (p = 0.0451).

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74 Both native and exotic species were f ound in the study area. The most abundant species such as B. alba, P. americana, S. diphyllum and E. capillifolium were characteristic of disturbed sites. Other freque nt species characteristic of moist habitat and new plantations included C. diffusa, C. canadensis, B. halimifolia and S. canadensis. Species richness and diversity were the hi ghest in Double-EG, which had 35 herbaceous and 23 shrubs/subshrubs. Cogongrass was the dominant understory species in Double-PD and first three treatments of SRWC-90. While edge effect played a significant role in the invasion of cogongr ass, both eucalyptus and cottonwood suppressed cogongrass. Cogongrass IVI had nonsigni ficant correlation with stand basal area in E. grandis (r = 0.19, p = 0.4587) and cottonwood (r = -0.21, p = 0.6103) in the operational area. However, it had significant negative co rrelation with stand basal area in both E. grandis (r = -0.91, p < 0.0001) and E. amplifolia (r = -0.73, p = 0.0028) in SRWC-90. Dominant canopy and good stand density are essential to suppress cogongrass. Eucalyptus with good survival performs bette r than cottonwood in controlling cogongrass because the deciduous nature of cottonw ood provides opportunity for cogongrass to regrow in the understory. Fa st-growing evergreen tree speci es combined with initial intensive site preparation have the pote ntial to control c ogongrass and convert phosphate-mined lands such as CSAs into productive sites.

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75 CHAPTER 6 FUTURE RESEARCH Better understanding of ecology and phys iology of cogongrass has revealed alternate ways to control it. Fast-growing sp ecies in this study have shown the potential to control cogongrass. Though herbicide can control cogongrass for short duration, combination of herbicide, intensive site prep aration and use of fast-growing tree species have been effective for longer period in other parts of the world. However, studies on the use of fast-growing species is limited and mos tly confined to Asia. Its study across the globe can generate more relevant information on the management and control of cogongrass in different edaphic and climatic conditions. Because of the short-rotation of fast-g rowing trees, their long-term role in controlling cogongrass is still unclear. Cogongrass might invade the area once the trees are harvested. Long-term study is necessary to understand the effectiveness of these trees. Continual monitoring of the existing pl ots and the edges of the cogongrass patches can give information on cogongr ass reinvasion and its rate. Seasonal monitoring can provide information on the recruitment of seasonal vegetation in the area. Fast-growing trees are vulnerable to na tural calamities, such as storms and hurricanes. Other perennial species that form dense ground cover might be effective in areas where storm and hurricane are frequent. Some N-fi xing ground covers have been effective in other parts of the world. Th ese can increase N supply at the same time, which is deficient in phosphate-mine soil.

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76 Natural succession is a slow process and may take decades to centuries. Regeneration of native species in disturbed sites largely depe nds on seed supply. Further, seeds introduced in the area are unable to ge rminate due to adverse edaphic and climatic conditions. Interplantin g native species that quickly produc e seed with fast-growing trees at the same time might shorten the rate of native species recruitment. Creating canopy gaps after some years can provide opportunity for pioneer species to grow in the area. Eucalyptus species have been criticize d throughout the world due to possible allelopathy. Though their invasiveness is not documented, it needs to be investigated. Using other fast-growing species might increas e the recruitment rate and the growth of native species. Success of fast-growing trees to control cogongrass largely depends on their canopy coverage. Permanent canopy is crucial to suppress cogongrass. Close spacing is very important. Dense plan ting in edges can reduce edge effect. Effect of multiple disking is still quite unclear. Results in this study area where only the multiple disking was done have show n the need of further study on its role. Including multiple disking as a separate tr eatment in future studies might provide information on its effectiveness.

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APPENDIX A NAME AND NATIVITY OF HERBACEOUS AND SHRUB/SUBSHRUB SPECIES

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78 Table A-1. Name and nativ ity of herbaceous species. Species Common name Nativity OPA*SRWC-90 Family: Apiaceae Hydrocotyle umbellate L. Manyflower marshpennywortN X Family: Asclepiadaceae Morrenia odorata (Hook. & Arn.) Lindl.Latexplant I X Family: Asteraceae Ambrosia artemisiifolia L. Annual ragweed N X X Ampelaster carolinianus (Walt.) Nesom Climbing aster N X Bidens alba (L.) DC. Spanish needles N X X Cirsium horridulum Michx. Yellow thistle N X X Conyza canadensis (L.) Cronq. Canadian horseweed N X Erechtites hieraciifolia (L.) Raf. Ex DC.American burnweed N X Eupatorium capillifolium (Lam.) Small Dogfennel N X X Eupatorium serotinum Michx. Lateflowering thoroughwort N X X Krigia virginica (L.) Willd. Virginia dwarfdandelion N X Family: Brassicaceae Lepidium virginicum L. Virginia pepperweed N X Family: Commelinaceae Commelina diffusa Burm. f. Climbing dayflower N X Family: Convolvulaceae Calystegia sepium (L.) R. Br. Hedge flase binweed N X Ipomoea purpurea (L.) Roth Tall morning-glory I X Stylisma patens (Desr.) Myint Costalplain dawnflower N X Family: Cucurbitaceae Cucumis melo L. Cantaloupe I X Melothria pendula L. Gaudeloupe cucumber N X X Family: Cyperaceae Carex sp. L. Sedge X Oxycaryum cubense (Poepp. & Kunth) Lye Cuban bulrush N X Family: Euphorbiaceae Chamaesyce hypericifolia (L.) Millsp. Graceful sandmat N X

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79 Table A-1 continued. Species Common name Nativity OPA*SRWC-90 Family: Fabaceae Aeschynomene americana L. Shyleaf N X Desmodium triflorum (L.) DC. Threeflower ticktrefoil N X Macroptilium lathyroides (L.) Urban Wild bushbean N X X Medicago lupulina L Black medick I X Rhynchosia cinerea Nash Brownhair snoutbean N X Vicia acutifolia Ell. Fourleaf vetch N X Family: Lamiaceae Collinsonia serotina Walt. Blue ridge horsebalm N X Salvia riparia Kunth Florida Keys sage N X Family: Lygodiaceae Lygodium japonicum (Thunb. ex Murr.) Sw. Japanese climbing fern I X X Family: Lythraceae Lythrum alatum Pursh Winged lythrum N X Family: Oxiladiceae Oxalis corniculata L. Common yellow woodsorrel N X X Family: Passifloraceae Passiflora incarnata L. Purple passionflower N X X Family: Phytolaccaceae Phytolacca americana L. American pokeweed N X X Family: Poaceae Andropogon virginicus L. Broomsedge bluestem N X X Aristida purpurascens Poir. Arrowfeather threeawn N X Cynodon dactylon (L.) Pers. Burmuda grass I X X Digitaria ciliaris (Retz.) Koel. Southern crabgrass N X Imperata cylindrica (L.) Beauv. Cogongrass I X X Panicum repens L. Torpedo grass N X Setaria parviflora (Poir.) Kerbulen Marsh bristlegrass N X X Family: Polygonaceae Polygonum hydropiperoides Michx. Swamp smartweed N X Family: Ranunculaceae Clematis virginiana L. Devil's darning needles N X X Family: Rubiaceae Galium tinctorium L. Stiff marsh bedstraw N X

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80 Table A-1 continued. Species Common name Nativity OPA*SRWC-90 Family: Thelypteridaceae Thelypteris kunthii (Desv.) Morton Kunth's maiden fern N X X Family: Typhaceae Typha latifolia L. Broadleaf cattail N X Family: Verbenaceae Phyla nodiflora (L.) Greene Turkey tangle forfruit N X Verbena brasiliensis Vell. Brazil vervain I X Verbena scabra Vahl Sandpaper vervain N X Family: UIH01 X UIH02 X UIH03 X UIH04 X UIH05 X UIH06 X UIH07 X UIH08 X *Operational area; N= native; I= Introduced

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81 Table A-2. Name and nativity of shrub/subshrub species. Species Common name Nativity OPA* SRWC-90 Family: Aceraceae Acer rubrum L. Red maple N X X Family: Anacardiaceae Rhus copallinum L. Sumac N X Schinus terebinthifolius Raddi Brazilian peppertree I X X Toxicodendron radicans (L.) Kuntze Eastern poison ivy N X X Family: Asteraceae Baccharis angustifolia Michx. Saltwater false willow N X Baccharis halimifolia L. Saltbush N X X Family: Caprifoliaceae Sambucus canadensis (L.) R. Bolli Common elderberry N X X Family: Ebenaceae Diospyros virginiana L. Common persimmon N X Family: Euphorbiaceae Triadica sebifera (L.) Small Chinese tallow I X Family: Fagaceae Quercus laurifolia Michx. Laurel oak N X X Quercus virginiana P. Mill. Live oak N X X Family: Malvaceae Sida rhombifolia L. Cuban jute N X Urena lobata L. Ceaserweed N X X Family: Onagraceae Ludwigia peruviana (L.) Hara Peruvian primrosewillow I X Family: Rosaceae Rubus argutus Link Sawtooth blackberry N X X Family: Solanaceae Solanum diphyllum L. Twoleaf nightshade I X Family: Ulmaceae Celtis occidentalis L. Common hackberry N X X Ulmus americana L. American elm N X Family: Verbenaceae Callicarpa americana L. American beautyberry N X Lantana camara L. Lantana N X

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82 Table A-2 continued. Species Common name Nativity OPA* SRWC-90 Family: Vitaceae Ampelopsis arborea (L.) Koehne Pepper vine N X X Parthenocissus quinquefolia (L.) Planch.Virginia creeper N X X Vitis sp. L. Wild foxgrape N X X Family: UIS01 X UIS02 X UIS03 X *Operational area; N= native; I= Introduced

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APPENDIX B TREE SIZE AND SURVIVAL

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84 Table B-1. Tree size and survival in the ope rational area: average tree height (m), DBH (cm), basal area (m2/ha), density (trees/ha) a nd quadratic diameter (cm). Culture Plot HeightDBH Basal area Density Quad. diameter 1 14.4 11.8 11.0 681 14.3 2 13.5 10.8 5.0 358 13.3 3 14.2 11.5 15.3 1075 13.5 Single-EG (3-year-old) 4 15.5 13.0 17.9 1003 15.1 5 16.0 13.5 15.3 824 15.4 6 14.7 12.1 13.7 752 15.2 7 14.2 11.6 15.4 1003 14.0 1 10.0 7.4 10.6 1477 9.6 2 9.4 7.0 5.0 792 8.9 Double-EG (3-year-old) 3 11.6 9.0 6.5 685 11.0 4 13.4 9.8 10.5 865 12.4 5 13.2 9.9 7.9 613 12.8 1 8.2 6.3 11.0 1919 8.5 Quadruple-EG (2-year-old) 2 8.4 6.5 10.5 1919 8.3 3 9.2 7.4 11.9 1724 9.4 4 9.5 7.7 10.9 1431 9.8 1 7.7 5.2 13.2 4072 6.4 2 7.9 5.1 13.0 4180 6.3 3 7.6 5.1 11.3 3748 6.2 Double-PD (2.5-year-old) 4 6.9 4.6 10.3 4144 5.6 5 6.9 5.1 6.3 2090 6.2 6 6.4 4.3 6.0 2703 5.3 7 6.3 4.8 6.6 2414 5.9 8 6.2 4.7 5.4 2054 5.8

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85 Table B-2. Tree size and survival in SRWC90: average 3.75-year-old tree height (m), DBH (cm), basal area (m2/ha), density (trees/ha) and quadratic diameter (cm). Treatment* Species Plot Hei ght DBH Basal areaDensity Quad. diameter 1 EG 1 10.5 8.5 14.9 3600 7.3 1 EG 2 7.0 4.6 6.0 4800 4.0 1 EA 1 4.3 3.9 4.4 4000 3.7 1 EA 2 6.2 5.2 6.3 4400 4.3 2 EG 1 6.6 3.8 6.6 7917 3.2 2 EG 2 8.1 4.9 12.5 9167 4.2 2 EA 1 6.5 4.9 9.8 8333 3.9 2 EA 2 5.8 3.8 7.8 9583 3.2 3 EG 1 6.6 5.0 6.4 3600 4.7 3 EG 2 8.5 6.3 11.9 4000 6.2 3 EA 1 9.2 7.1 12.2 4800 5.7 3 EA 2 8.2 7.2 12.0 4400 5.9 4 EG 1 11.8 7.8 23.1 6800 6.8 4 EG 2 12.4 8.3 21.7 5200 7.3 4 EG 3 10.8 7.6 15.9 4400 6.8 4 EG 4 10.5 7.7 21.5 5600 7.0 4 EA 1 10.7 7.1 22.4 8000 6.0 4 EA 2 11.2 8.5 38.4 9600 7.1 4 EA 3 10.6 8.1 33.0 8800 6.9 4 EA 4 9.1 6.8 22.9 8400 5.9 5 EG 1 10.9 7.8 18.2 4800 7.0 5 EG 2 10.1 5.7 16.4 7600 5.2 5 EG 3 8.3 5.3 16.8 8800 4.9 5 EG 4 9.7 6.5 16.6 6000 5.9 5 EA 1 10.2 7.9 26.5 7600 6.7 5 EA 2 9.5 6.7 21.4 8800 5.6 5 EA 3 8.6 6.3 20.4 8800 5.4 5 EA 4 8.9 6.7 26.2 9200 6.0 EG: E. grandis EA: E. amplifolia; *See Table 3-2 for treatment descriptions.

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APPENDIX C SOIL CHARACTERISTICS

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87Table C-1. Soil characteristics in the operational area: total Kjeldahl N [TKN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/ kg), SOM (%), pH and bulk density (BD) on bed (B) and inter-bed (IB) positions. Culture Response Single-EG (n=4)Double-EG (n=4 )Quadruple-EG (n=4)Double-PD (n=4) B IBBIBB IBBIB TKN 0.28a 0.29a0.34a0.30a0.24a 0.11b0.34a0.35a P 4103.0a 4093.0a4219.0a4196.0a4173.0a 4079.0a4073.0a3482.0aK 188.1a 186.7a265.8a193.5a260.9a 162.5a227.2a193.7aCa 11038.0a 11060.0a11210.0a7767.6a11133.0a 10572.0a10935.0a9961.0aMg 1266.2a 1247.0a1199.2a1129.3a1262.0a 1292.2a1126.7a1092.0aSOM 5.58a 5.46a6.70a4.59ab4.74a 2.85b6.38a6.61apH 7.9ab 7.7a7.3b7.4a8.0a 7.9a7.5ab7.5aBD (0-3 cm) 0.69ab 0.63a0.59b0.75a0.78a 0.54a0.70ab0.85a (3-6 cm) 0.68a 0.75a0.62a0.72a0.84a 0.74a0.70a0.72a Means in the same row with the same letter are not significant at 5% level

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88Table C-2. Soil characteristics in SRWC-90 E. grandis and E. amplifolia plots: total N [TN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and bulk density (B D) on bed (B) and inter-bed (IB) positions. Treatment* Response 1 (n=2) 2 (n=2) 3 (n=2) 4 (n=4) 5 (n=4) B IBBIBBIB BIBBIB E. grandis: TN 0.34a 0.24a0.29a0.36a0.32a0.23a 0.40a0.31a0.41a0.38a P 119.0a 173.2a160.3a118.9a153.9a171.1a 141.6a150.1a123.8a136.8a K 106.8a 106.2a124.5a93.3a85.8a78.0a 89.9a83.1a95.7a106.4a Ca 1818.5a 1824.0a1728.0a1936.0a1720.0a1850.0a 1783.5a1771.7a1777.5a1824.5a Mg 511.8a 517.0a489.6a499.2a540.8a595.0a 609.5a598.2a633.4a653.2a SOM 9.44a 6.74a8.41a10.13a9.12a6.38a 9.62a7.83a10.06a9.32a pH 7.0a 7.3a7.0a6.9a7.0a7.4a 6.9a7.1a6.8a7.0a BD (0-3 cm) 0.78a 0.63a0.83a0.72a0.76a0.77a 0.81a0.87a0.68a0.83a (3-6 cm) 0.74a 0.72a0.83a0.65a0.70a0.80a 0.80a0.77a0.72a0.75a E. amplifolia: TN 0.38a 32.00a0.41a0.28a0.32a0.26a 0.40a0.39a0.37a0.30a P 144.4a 138.8a136.3a151.9a137.1a155.1a 132.5a129.9a135.0a146.2a K 82.5a 94.8a147.5a93.5a93.9a105.9a 84.5a85.5a90.5a101.5a Ca 1840.0a 1876.0a1822.5a1874.0a1644.5a1638.5a 1769.0a1780.7a1766.2a1777.0a Mg 566.8a 575.8a514.4a560.6a512.4a533.8a 599.3a599.0a639.5a653.3a SOM 10.92a 8.43a12.24a7.27a8.94a6.97a 9.75a9.59a9.00a7.34a pH 7.2a 7.3a7.0a7.4a6.8a6.9a 7.0a7.0a6.9a6.9a BD (0-3 cm) 0.67a 0.58c0.64a0.63c0.71a0.71bc 0.79a0.86ab0.84a0.92a (3-6 cm) 0.82a 0.70a0.71a0.70a0.76a0.69a 0.81a0.86a0.80a0.84a Means in the same row with same letter are not significant at 5% level; *See Table 3-2 fo r treatment descriptions.

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APPENDIX D IMPORTANCE VALUE INDEX (IVI)

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90 Table D-1. Single-EG in the operational ar ea: IVI of herbaceous and shrub/subshrub species. Species Plot 1 (n=12) Plot 2 (n=12) Plot 3 (n=12) Plot 4 (n=12) Plot 5 (n=12) Plot 6 (n=12) Plot 7 (n=12) Average Herbaceous: Imperata cylindrica 040.094.798.410.8120.7 161.775.2 Thelypteris kunthii 30.613.548.931.069.68.0 20.231.7 Cynodon dactylon 19.271.812.8013.182.7 4.229.1 Clematis virginiana 92.18.230.116.156.90 029.1 Phytolacca americana 19.717.45.642.433.129.5 9.822.5 Commelina diffusa 33.222.217.123.123.022.2 3.520.6 Aeschynomene americana 7.420.220.425.432.30 7.716.2 Andropogon virginicus 042.703.33.20 49.214.1 Lygodium japonicum 13.311.99.413.521.83.6 4.511.1 Eupatorium serotinum 15.33.75.618.59.66.3 5.89.3 Eupatorium capillifolium 2.12.622.0003.5 04.3 Phyla nodiflora 29.300000 04.2 Melothria pendula 000000 23.63.4 Macroptilium lathyroides 09.93.3000 4.72.5 Bidens alba 7.48.60000 02.3 Cirsium horridulum 4.605.02.92.40 02.1 Lythrum alatum 0000014.3 02.0 Carex sp. 08.103.600 01.7 Ambrosia artemisiifolia 04.70003.5 01.2 Ipomoea purpurea 04.62.6000 01.0 Morrenia odorata 000000 5.10.7 Oxalis corniculata 2.102.5000 00.7 Setaria parviflora 04.60000 00.7 Polygonum hydropiperoides 4.500000 00.6 UIH08 000004.4 00.6 Hydrocotyle umbellata 0004.200 00.6 Passiflora incarnata 03.60000 00.5 Erechtites hieraciifolia 00003.20 00.5 Lepidium virginicum 002.8000 00.4 Collinsonia serotina 00002.80 00.4 UIH07 002.5000 00.4 UIH02 2.300000 00.3 Verbena scabra 02.00000 00.3

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91 Table D-1 continued. Species Plot 1 (n=12) Plot 2 (n=12) Plot 3 (n=12) Plot 4 (n=12) Plot 5 (n=12) Plot 6 (n=12) Plot 7 (n=12) Average Shrub/subshrub: Urena lobata 241.3215.5204.7277.7237.8207.2 118.6214.7 Sambucus canadensis 0051.1000 131.726.1 Ludwigia peruviana 15.555.517.1000 49.219.6 Baccharis halimifolia 0009.913.392.9 016.6 Solanum diphyllum 7.4015.139.424.50 012.3 Acer rubrum 009.806.60 13.04.2 Schinus terebinthifolius 12.404.906.20 03.4 Quercus laurifolia 6.400011.60 02.6 Ampelopsis arborea 17.000000 02.4 Triadica sebifera 017.00000 02.4 Celtis occidentalis 0008.700 01.2

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92 Table D-2. Double-EG in the operational ar ea: IVI of herbaceous and shrub/subshrub species. Species Plot 1 (n=12) Plot 2 (n=12) Plot 3 (n=12) Plot 4 (n=12) Plot 5 (n=12) Average Herbaceous: Cynodon dactylon 15.087.74.030.8 125.9 52.7 Clematis virginiana 91.447.515.664.7 43.7 52.6 Imperata cylindrica 066.8173.60 0 48.1 Bidens alba 0039.470.9 26.0 27.3 Commelina diffusa 23.825.05.713.5 3.3 14.3 Phyla nodiflora 35.417.700 10.1 12.6 Eupatorium capillifolium 13.58.9026.1 6.5 11.0 Carex sp. 22.911.200 8.1 8.4 Rhynchosia cinerea 001.926.5 10.8 7.8 Thelypteris kunthii 15.53.4010.0 0 5.8 Phytolacca americana 4.53.24.66.8 2.4 4.3 UIH04 019.300 0 3.9 Aristida purpurascens 0000 19.3 3.9 Lygodium japonicum 9.601.92.8 1.9 3.2 Conyza canadensis 2.40013.7 0 3.2 Passiflora incarnata 000.06.8 9.2 3.2 Lythrum alatum 10.04.400 0 2.9 UIH02 2.30011.6 0 2.8 Andropogon virginicus 8.203.70 0 2.4 Aeschynomene americana 0005.0 6.3 2.3 Oxycaryum cubense 5.93.100 0 1.8 Lepidium virginicum 0000 8.8 1.8 Galium tinctorium 4.43.200 0 1.5 UIH03 5.1000 0 1.0 Ampelaster carolinianus 2.0000 2.1 0.8 Stylisma patens 3.9000 0 0.8 Morrenia odorata 3.7000 0 0.7 UIH05 003.70 0 0.7 UIH01 3.1000 0 0.6 Typha latifolia 02.900 0 0.6 Desmodium triflorum 2.3000 0 0.5 Chamaesyce hypericifolia 0000 2.1 0.4 Macroptilium lathyroides 2.0000 0 0.4 Polygonum hydropiperoides 2.0000 0 0.4 Oxalis corniculata 0000 1.7 0.3

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93 Table D-2 continued. Species Plot 1 (n=12) Plot 2 (n=12) Plot 3 (n=12) Plot 4 (n=12) Plot 5 (n=12) Average Shrub/subshrub: Urena lobata 108.469.1154.5252.7 227.1 162.4 Ludwigia peruviana 94.5133.774.80 0 60.6 Baccharis halimifolia 015.715.80 27.2 11.7 Quercus laurifolia 12.05.414.80 22.4 10.9 Rubus argutus 047.500 0 9.5 Ampelopsis arborea 10.411.416.90 0 7.8 Solanum diphyllum 0022.16.8 9.0 7.4 Lantana camara 00034.7 0 7.0 Schinus terebinthifolius 11.8014.90 7.6 6.9 Parthenocissus quinquefolia 0010.05.9 6.6 4.5 Acer rubrum 12.55.900 0 3.7 Diospyros virginiana 9.2005.0 0 2.8 Sambucus canadensis 10.9000 0 2.2 Sida rhombifolia 9.4000 0 1.9 Callicarpa americana 8.2000 0 1.7 Ulmus americana 0000 8.0 1.6 Quercus virginiana 0000 7.6 1.5 UIS02 05.900 0 1.2 Toxicodendron radicans 5.4000 0 1.1 UIS01 05.400 0 1.1 Rhus copallinum 4.1000 0 0.8 UIS03 4.1000 0 0.8 Vitis sp. 0000 1.9 0.4

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94 Table D-3. Quadruple-EG in the operationa l area: IVI of herbaceous and shrub/subshrub species. Species Plot 1 (n=12) Plot 2 (n=12) Plot 3 (n=12) Plot 4 (n=12) Average Herbaceous: Cynodon dactylon 71.558.869.03.4 50.7 Imperata cylindrica 000168.3 42.1 Commelina diffusa 37.949.059.216.7 40.7 Phytolacca americana 39.548.858.614.7 40.4 Aeschynomene americana 20.213.021.126.6 20.2 Clematis virginiana 12.425.213.07.0 14.4 Thelypteris kunthii 7.133.206.8 11.8 Ambrosia artemisiifolia 19.92.07.011.8 10.2 Eupatorium capillifolium 12.64.73.57.8 7.2 Lepidium virginicum 06.717.23.4 6.8 Bidens alba 18.34.000 5.6 Polygonum hydropiperoides 10.611.200 5.4 Macroptilium lathyroides 2.4016.70 4.8 Cirsium horridulum 5.22.02.75.2 3.8 Setaria parviflora 10.44.000 3.6 Lythrum alatum 00011.7 2.9 Salvia riparia 2.402.70 1.3 Passiflora incarnata 0005.2 1.3 Conyza canadensis 0004.2 1.0 Lygodium japonicum 04.000 1.0 UIH02 0003.4 0.9 Panicum repens 03.000 0.7 UIH06 2.9000 0.7 Carex sp. 02.900 0.7 Digitaria ciliaris 02.000 0.5 Ampelaster carolinianus 1.6000 0.4 Shrub/subshrub: Urena lobata 228.9196.8202.9218.4 211.7 Solanum diphyllum 66.662.055.36.4 47.6 Ludwigia peruviana 0028.039.1 16.8 Sambucus canadensis 018.4020.2 9.7 Baccharis halimifolia 011.63.917.3 8.2 Ampelopsis arborea 07.810.20 4.5 Acer rubrum 4.8000 1.2 Diospyros virginiana 04.300 1.1

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95Table D-4. Double-PD in the operational area: IVI of herbaceous and shrub/subshrub species. Species Plot 1 (n=8) Plot 2 (n=8) Plot 3 (n=8) Plot 4 (n=8) Plot 5 (n=8) Plot 6 (n=8) Plot 7 (n=8) Plot 8 (n=8) Average Herbaceous: Imperata cylindrica 32.96.966.621.7151.5 177.8137.23.374.7 Bidens alba 32.623.084.274.44.6 37.84.255.539.5 Cynodon dactylon 2.954.227.983.642.9 0.033.116.932.7 Clematis virginiana 58.54.53.211.715.1 28.232.546.025.0 Eupatorium serotinum 33.748.925.46.70.0 29.99.010.920.6 Setaria parviflora 30.228.716.811.912.3 0.739.213.419.2 Macroptilium lathyroides 22.331.07.416.618.5 6.226.016.018.0 Aristida purpurascens 2.58.78.242.230.0 5.20.012.813.7 Aeschynomene americana 8.712.010.615.920.2 6.217.610.512.7 Thelypteris kunthii 12.74.87.22.85.0 8.7027.48.6 Commelina diffusa 6.829.702.50 011.510.77.7 Lygodium japonicum 7.64.802.80 05.618.85.0 Hydrocotyle umbellata 24.609.000 0004.2 Ambrosia artemisiifolia 9.94.73.200 002.42.5 Cirsium horridulum 2.64.803.40 0001.4 Oxalis corniculata 004.200 06.101.3 Phyla nodiflora 06.7000 0000.8 Cucumis melo 00000 005.60.7 Phytolacca americana 00000 05.400.7 Krigia virginica 005.300 0000.7 Salvia riparia 3.30000 0000.4 Calystegia sepium 0002.80 0000.6 Melothria pendula 00000 002.70.3 Polygonum hydropiperoides 02.5000 0000.3 UIH02 00000 002.40.3 Digitaria ciliaris 02.3000 0000.3 Eupatorium capillifolium 1.890000 0000.2

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96Table D-4 continued. Species Plot 1 (n=8) Plot 2 (n=8) Plot 3 (n=8) Plot 4 (n=8) Plot 5 (n=8) Plot 6 (n=8) Plot 7 (n=8) Plot 8 (n=8) Average Shrub/subshrub: Baccharis halimifolia 133.956.6110.9117.1189.6 271.2117.157.1131.7 Urena lobata 110.798.7104.2149.339.6 0137.0189.0103.6 Acer rubrum 39.6021.716.80 28.946.021.221.8 Ludwigia peruviana 0119.3016.80 0023.219.9 Sambucus canadensis 000070.8 0008.9 Baccharis angustifolia 027.9000 0003.5 Ampelopsis arborea 0017.500 0002.2 Schinus terebinthifolius 15.80000 0002.0 Parthenocissus quinquefolia 00000 003.30.4

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97 Table D-5. Treatments* 1, 2 and 3 in SR WC-90: IVI of herbaceous and shrub/subshrub species. E. grandis E. amplifolia Species Plot 1 (n=5) Plot 2 (n=5) Average Plot 1 (n=5) Plot 2 (n=5) Average Herbaceous: Treatment 1: Imperata cylindrica 233.4300.0266.7300.0300.0 300.0 Lygodium japonicum 34.6017.300 0 Thelypteris kunthii 32.1016.000 0 Treatment 2: Imperata cylindrica 300.0300.0300.0300.0293.3 296.7 Treatment 3: Imperata cylindrica 300.0300.0300.0300.0299.9 299.9 Shrub/subshrub: Treatment 1: Acer rubrum 254.60127.300 0 Baccharis halimifolia 25.9012.900 0 Urena lobata 19.609.800 0 Vitis sp. 000030.2 15.1 *See Table 3-2 for treatment descriptions.

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98Table D-6. Treatment* 4 in SRWC-90: IVI of herbaceous and shrub/subshrub species. E. grandis E. amplifolia Species Plot 1 (n=5) Plot 2 (n=5) Plot 3 (n=5) Plot 4 (n=5) Average Plot 1 (n=5) Plot 2 (n=5) Plot 3 (n=5) Plot 4 (n=5) Average Herbaceous: Imperata cylindrica 285.3247.4214.259.8201.7 245.516.0116.2300.0169.4 Clematis virginiana 45.231.6036.928.4 47.376.781.2051.3 Eupatorium serotinum 028.555.6021.0 00000 Vicia acutifolia 00.083.520.9 052.00013.0 Lygodium japonicum 021.008.47.3 012.222.208.6 Cynodon dactylon 0028.707.2 0092.9023.2 Medicago lupulina 00025.66.4 00000 Eupatorium capillifolium 0007.81.9 00000 Cirsium horridulum 0007.41.9 00000 Andropogon virginicus 0004.21.1 00000 Phytolacca americana 0004.21.1 00000 Thelypteris kunthii 00000 21.00005.3 Passiflora incarnata 00000 083.60020.9 Shrub/subshrub: Urena lobata 0253.8191.1142.3146.8 0217.1240.10114.3 Acer rubrum 00000 045.69.3013.7 Baccharis halimifolia 0032.243.618.9 013.928.4010.6 Quercus laurifolia 0011.219.67.7 0023.005.8 Parthenocissus quinquefolia 0057.268.431.4 013.1003.3 Sambucus canadensis 046.253.167.141.6 011.2002.8 Schinus terebinthifolius 00000 010.2002.6 Ampelopsis arborea 00024.46.1 00000 Vitis sp 0006.51.6 00000 *See Table 3-2 for treatment descriptions.

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99Table D-7. Treatment* 5 in SRWC-90: IVI of herbaceous and shrub/subshrub species. E. grandis E. amplifolia Species Plot 1 (n=5) Plot 2 (n=5) Plot 3 (n=5) Plot 4 (n=5) Average Plot 1 (n=5) Plot 2 (n=5) Plot 3 (n=5) Plot 4 (n=5) Average Herbaceous: Bidens alba 51.013.756.870.448.0 140.2035.291.666.8 Vicia acutifolia 74.515.432.443.841.5 23.971.138.236.942.5 Clematis virginiana 18.127.684.350.645.2 11.458.450.627.737.0 Andropogon virginicus 41.411.034.667.038.5 20.6053.057.532.8 Cynodon dactylon 30.618.837.5021.7 29.933.556.75.631.4 Thelypteris kunthii 3.70000.9 044.42.420.016.7 Lygodium japonicum 16.504.705.3 19.210.019.815.316.1 Medicago lupulina 9.4022.307.9 0014.003.5 Imperata cylindrica 0213.60053.4 003.67.62.8 Setaria parviflora 00000 011.2002.8 Cirsium horridulum 00000 00.09.002.3 Oxalis corniculata 00000 010.2002.5 Eupatorium capillifolium 00000 06.1001.5 Ambrosia artemisiifolia 008.88.84.4 003.000.8 Melothria pendula 00000 003.000.8 Macroptilium lathyroides 00000 003.000.8 Verbena brasiliensis 0006.01.5 00000 Shrub/subshrub: Urena lobata 131.7165.040.265.2100.5 224.7221.8207.1127.5195.3 Baccharis halimifolia 46.6114.6154.560.394.0 07.450.7109.141.8 Acer rubrum 26.610.270.969.744.3 16.115.921.126.419.9 Parthenocissus quinquefolia 53.8016.953.331.0 46.753.812.336.937.4 Schinus terebinthifolius 52.00016.117.0 29.128.00014.3 Quercus laurifolia 14.49.8026.312.6 6.811.021.18.711.9 Toxicodendron radicans 0034.608.6 00000

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100Table D-7 continued. E. grandis E. amplifolia Species Plot 1 (n=5) Plot 2 (n=5) Plot 3 (n=5) Plot 4 (n=5) Average Plot 1 (n=5) Plot 2 (n=5) Plot 3 (n=5) Plot 4 (n=5) Average Rubus argutus 28.10007.0 00000 Ampelopsis arborea 00021.65.4 7.00022.87.5 Sambucus canadensis 00018.04.5 00000 Vitis sp. 5.90001.5 00000 Celtis occidentalis 00000 8.116.0006.0 Quercus virginiana 00000 8.10002.0 *See Table 3-2 for treatment descriptions

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APPENDIX E COVER (%), FREQUENCY AND SPECIES COMPOSITION

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102Table E-1. Single-EG in the operational area: cover (%), fr equency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions. Species Cover Frequency Species composition B (n=42) IB (n=42) Average B (n=42) IB (n=42) Average B (n=42) IB (n=42) Average Herbaceous: Imperata cylindrica 33.233.333.347.645.246.40.380.360.37 Thelypteris kunthii 8.515.011.840.847.644.20.130.190.16 Phytolacca americana 7.64.35.947.640.544.10.100.060.08 Commelina diffusa 0.21.70.938.133.335.70.080.020.05 Clematis virginiana 8.77.28.031.033.332.10.110.100.10 Cynodon dactylon 6.74.95.835.723.829.80.070.050.07 Lygodium japonicum 1.41.01.221.435.728.60.020.010.02 Aeschynomene americana 0.40.40.433.323.828.60.010.010.01 Eupatorium serotinum 1.52.11.819.121.420.20.020.030.03 Andropogon virginicus 3.710.06.814.316.815.50.040.100.07 Macroptilium lathyroides 0.10.40.27.19.58.310-34x10-33x10-3 Cirsium horridulum 0.20.010.111.92.47.12x10-310-410-3 Eupatorium capillifolium 1.80.21.09.52.46.00.022x10-30.01 Lythrum alatum 0.20.10.17.12.44.82x10-310-32x10-3 Bidens alba 0.31.50.92.47.14.83x10-30.020.01 Ipomoea purpurea 0.010.10.12.44.83.610-410-310-3 Carex sp. 0.20.10.22.44.83.62x10-310-32x10-3 Melothria pendula 1.00.50.84.82.43.60.010.010.01 Phyla nodiflora 0.91.51.22.42.42.40.010.020.02 Oxalis corniculata 0.0200.014.802.42x10-4010-4 Ambrosia artemisiifolia 0.010.90.52.42.42.410-40.015x10-3 Setaria parviflora 0.010.10.12.42.42.410-410-36x10-4 Lepidium virginicum 0.1000.12.401.210-305x10-4 Morrenia odorata 00.20.102.41.2010-45x10-5 Polygonum hydropiperoides 0.500.32.401.20.0105x10-3 Passiflora incarnata 00.50.302.41.204x10-32x10-3

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103Table E-1 continued. Species Cover Frequency Species composition B (n=42)IB (n=42)AverageB (n=42)IB (n=42)AverageB (n=42)IB (n=42)Average Verbena scabra 00.10.102.41.2010-35x10-4 Hydrocotyle umbellata 00.015x10-302.41.2010-35x10-4 Collinsonia serotina 00.10.102.41.2010-35x10-4 UIH02 00.015x10-302.41.2010-45x10-5 UIH07 0.0105x10-32.401.210-405x10-5 UIH08 00.10.0302.41.2010-35x10-4 Erechtites hieraciifolia 0.100.032.401.22x10-3010-3 Shrub/subshrub: Urena lobata 21.619.320.566.766.766.70.80.620.71 Ludwigia peruviana 1.13.02.011.914.313.10.030.130.1 Solanum diphyllum 0.20.60.411.99.510.70.010.020.02 Sambucus canadensis 1.71.81.711.97.19.50.10.070.1 Acer rubrum 0.020.10.14.84.84.810-30.010.01 Baccharis halimifolia 0.11.40.84.84.84.80.010.130.1 Quercus laurifolia 0.010.020.022.44.83.63x10-410-310-3 Schinus terebinthifolius 0.020.90.54.82.43.610-30.020.01 Ampelopsis arborea 0.50.010.32.42.42.40.012x10-40.01 Triadica sebifera 0.30.30.32.42.42.40.010.010.01 Celtis occidentalis 0.100.042.401.23x10-302x10-3

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104Table E-2. Double-EG in the operational area: cover (%), fre quency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions. Species Cover Frequency Species composition B (n=30)IB (n=30)AverageB (n=30)IB (n=30)AverageB (n=30)IB (n=30)Average Herbaceous: Clematis virginiana 11.514.713.166.773.370.00.20.30.2 Cynodon dactylon 10.517.014.243.350.046.70.10.20.2 Commelina diffusa 0.41.71.030.033.331.70.010.040.03 Eupatorium capillifolium 1.51.71.626.716.721.70.030.030.03 Conyza canadensis 0.80.30.610.033.321.70.010.010.01 Bidens alba 9.96.28.020.023.321.70.10.10.1 Imperata cylindrica 18.519.318.920.020.020.00.20.20.2 Phyla nodiflora 2.61.11.916.719.117.90.10.020.04 Thelypteris kunthii 0.61.10.816.710.013.30.010.020.02 Rhynchosia cinerea 3.20.11.616.710.013.30.110-30.03 Phytolacca americana 0.50.10.313.310.011.70.012x10-30.01 Lygodium japonicum 0.30.20.310.010.010.00.013x10-30.01 Carex sp. 2.21.41.86.710.08.30.10.030.04 Aeschynomene americana 0.10.030.0410.06.78.310-34x10-410-3 UIH02 0.10.40.36.710.08.32x10-30.010.01 Passiflora incarnata 0.90.70.813.33.38.30.010.010.01 Aristida purpurascens 1.41.01.26.76.76.70.020.010.02 Andropogon virginicus 0.30.10.26.73.35.00.012x10-30.01 Lythrum alatum 0.400.210.005.00.0100.01 Ampelaster carolinianus 0.0300.026.703.310-3010-3 Oxycaryum cubense 0.020.10.13.33.33.32x10-43x10-32x10-3 Galium tinctorium 0.10.020.13.33.33.32x10-32x10-410-3 Lepidium virginicum 0.40.020.23.33.33.30.012x10-40.01 UIH03 0.020.020.023.33.33.34x10-42x10-44x10-4 UIH04 1.30.71.03.33.33.30.020.010.02 Macroptilium lathyroides 0.0200.013.301.74x10-402x10-4

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105Table E-2 continued. Species Cover Frequency Species composition B (n=30)IB (n=30)AverageB (n=30)IB (n=30)AverageB (n=30)IB (n=30)Average Morrenia odorata 00.10.103.31.702x10-310-3 Desmodium triflorum 0.0200.013.301.74x10-402x10-4 Stylisma patens 0.300.13.301.70.0100.01 Typha latifolia 00.020.0103.31.702x10-410-4 Polygonum hydropiperoides 0.0200.013.301.72x10-4010-4 Chamaesyce hypericifolia 0.0200.013.301.72x10-4010-4 Oxalis corniculata 00.020.0103.31.702x10-410-4 UIH01 00.020.0103.31.702x10-410-4 UIH05 0.0200.013.301.710-3010-3 Shrub/subshrub: Urena lobata 17.121.219.160.056.758.30.50.60.6 Ludwigia peruviana 11.19.310.226.733.330.00.40.20.3 Parthenocissus quinquefolia 0.70.20.413.313.313.30.0110-30.01 Quercus laurifolia 0.00.10.16.716.711.710-32x10-32x10-3 Baccharis halimifolia 0.10.90.510.010.010.00.010.030.02 Ampelopsis arborea 0.10.030.110.06.78.34x10-32x10-33x10-3 Rubus argutus 0.50.40.56.710.08.30.020.020.02 Schinus terebinthifolius 0.10.30.26.76.76.70.010.010.01 Acer rubrum 0.10.020.0410.03.36.710-34x10-410-3 Diospyros virginiana 0.030.020.036.73.35.010-34x10-410-3 Solanum diphyllum 0.020.50.23.36.75.04x10-40.030.02 Lantana camara 0.72.31.53.36.75.00.010.050.03 Sambucus canadensis 0.10.10.13.33.33.34x10-32x10-33x10-3 Sida rhombifolia 00.10.103.31.702x10-310-3 Taxicodendron radicans 00.020.0103.31.704x10-42x10-4 Rhus copallinum 0.0200.013.301.710-3010-3 Vitis sp. 00.100.103.31.7010-310-3

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106Table E-2 continued. Species Cover Frequency Species composition B (n=30)IB (n=30)AverageB (n=30)IB (n=30)AverageB (n=30)IB (n=30)Average Callicarpa americana 0.100.13.301.74x10-302x10-3 Ulmus americana 00.020.0103.31.7010-310-3 Quercus virginiana 0.0200.013.301.710-3010-3 UIS01 0.100.13.301.73x10-302x10-3 UIS02 0.0200.013.301.74x10-302x10-3 UIS03 0.0200.013.301.710-3010-3

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107Table E-3. Quadruple-EG in the operati onal area: cover (%), frequency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions. Species Cover Frequency Species composition B (n=24)IB (n=24)AverageB (n=24)IB (n=24)AverageB (n=24)IB (n=24)Average Herbaceous: Commelina diffusa 0.83.92.379.275.077.10.20.10.1 Phytolacca americana 9.43.76.574.841.758.20.30.10.2 Cynodon dactylon 4.49.06.754.254.254.20.10.20.2 Aeschynomene americana 0.41.20.825.041.733.30.010.020.01 Clematis virginiana 1.04.82.912.533.322.90.030.10.1 Ambrosia artemisiifolia 0.44.02.28.337.522.90.010.10.03 Imperata cylindrica 15.015.815.416.725.020.80.20.20.2 Polygonum hydropiperoides 0.021.10.64.229.216.710-30.020.01 Bidens alba 0.21.40.812.520.816.70.010.020.02 Eupatorium capillifolium 0.52.41.54.225.014.60.020.040.03 Thelypteris kunthii 5.50.83.116.712.514.60.10.020.1 Lepidium virginicum 0.20.90.58.320.814.60.010.030.02 Cirsium horridulum 0.20.10.112.512.512.53x10-32x10-33x10-3 Macroptilium lathyroides 0.041.00.58.312.510.42x10-30.030.02 Setaria parviflora 0.32.71.54.24.24.20.010.040.03 Lygodium japonicum 00.040.0208.34.202x10-310-3 Lythrum alatum 01.20.608.34.200.010.01 Salvia riparia 0.0400.028.304.22x10-3010-3 Carex sp. 00.10.104.22.100.010.01 Ampelaster carolinianus 00.020.0104.22.103x10-42x10-4 Conyza canadensis 0.100.14.202.12x10-3010-3 Passiflora incarnata 00.90.404.22.100.010.01 Digitaria ciliaris 00.020.0104.22.1010-35x10-4 Panicum repens 00.020.0104.22.1010-35x10-4 UIH02 00.020.0104.22.102x10-410-4 UIH06 0.0200.014.202.110-305x10-4

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108 Table E-3 continued. Species Cover Frequency Species composition B (n=24)IB (n=24)AverageB (n=24)IB (n=24)AverageB (n=24)IB (n=24)Average Shrub/subshrub: Urena lobata 48.655.251.9100.0100.0100.00.70.80.8 Solanum diphyllum 12.26.29.258.362.560.40.20.10.1 Ludwigia peruviana 0.53.31.98.333.320.80.010.10.04 Baccharis halimifolia 0.21.20.712.512.512.54x10-30.020.01 Sambucus canadensis 4.30.62.48.38.38.30.10.020.04 Ampelopsis arborea 0.90.10.58.38.38.30.0110-30.01 Acer rubrum 0.0200.014.202.12x10-4010-4 Diospyros virginiana 00.020.0104.22.102x10-410-4

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109Table E-4. Double-PD in the operational area: cover (%), fr equency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions. Species Cover Frequency Species composition B (n=32)IB (n=32)AverageB (n=32)IB (n=32)AverageB (n=32)IB (n=32)Average Herbaceous: Macroptilium lathyroides 2.10.61.450.040.645.30.10.010.03 Eupatorium serotinum 2.72.02.353.137.545.30.10.040.1 Imperata cylindrica 28.226.327.240.640.640.60.50.30.4 Cynodon dactylon 0.711.05.834.446.940.60.020.20.1 Clematis virginiana 3.42.83.143.834.739.30.10.10.1 Bidens alba 9.310.810.037.531.334.40.20.20.2 Aeschynomene americana 0.20.30.328.137.532.83x10-33.11.6 Setaria parviflora 4.36.15.237.528.132.80.10.10.1 Commelina diffusa 0.90.40.628.125.026.60.030.010.02 Thelypteris kunthii 0.81.51.228.121.925.00.020.030.03 Aristida purpurascens 0.27.03.621.921.921.94x10-30.100.1 Lygodium japonicum 0.10.10.115.618.717.210-34x10-33x10-3 Ambrosia artemisiifolia 0.10.10.115.69.412.52x10-310-32x10-3 Hydrocotyle umbellata 0.40.10.29.46.37.80.012x10-30.01 Cirsium horridulum 0.10.030.16.36.36.32x10-310-32x10-3 Phyla nodiflora 0.10.020.13.13.13.13x10-32x10-42x10-3 Oxalis corniculata 00.10.106.23.102x10-310-3 Cucumis melo 00.20.106.23.104x10-32x10-3 Eupatorium capillifolium 00.020.0103.11.602x10-410-4 Polygonum hydropiperoides 00.020.0103.11.602x10-410-4 Salvia riparia 0.0200.013.101.63x10-402x10-4 Digitaria ciliaris 0.0200.013.101.64x10-402x10-4 Melothria pendula 0.0200.013.101.610-3010-3 Krigia virginica 0.100.13.101.610-3010-3

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110Table E-4 continued. Species Cover Frequency Species composition B (n=32)IB (n=32)AverageB (n=32)IB (n=32)AverageB (n=32)IB (n=32)Average UIH02 00.020.0103.11.603x10-410-4 Phytolacca americana 0.100.13.101.610-3010-3 Calystegia sepium 0.0200.013x10-302x10-32x10-4010-4 Shrub/subshrub: Baccharis halimifolia 1.81.21.553.128.140.60.60.50.5 Urena lobata 1.52.52.031.334.833.00.30.40.4 Acer rubrum 0.10.10.118.812.515.60.040.020.03 Ludwigia peruviana 0.10.60.36.315.610.90.030.10.1 Baccharis angustifolia 0.020.020.023.13.13.14x10-30.010.01 Sambucus canadensis 0.100.13.101.60.100.1 Ampelopsis arborea 0.0200.013.101.60.0100.01 Schinus terebinthifolius 0.0200.013.101.62x10-3010-3 Parthenocissus quinquefolia 0.0200.013.101.610-303x10-4

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111Table E-5. Eucalyptus grandis and E. amplifolia in SRWC-90 Treatments* 1, 2 and 3: cove r (%), frequency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions E. grandis E. amplifolia Species Cover Frequency Sps. composition Cover Frequency Sps. composition B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. Herbaceous: Treatment 1: Imperata cylindrica 95.5 92.5 94.0100.0100.0100.01.00.10.698.0 96.397.2100.0100.0100.01.01.01.0 Lygodium japonicum 0.1 0.1 0.125.016.720.810-310-310-30 00000000 Thelypteris kunthii 0.8 0.1 0.425.016.720.80.0100.010 00000000 Treatment 2: Imperata cylindrica 98.0 98.0 98.0100.0100.0100.01.01.01.098.0 98.098.0100.0100.0100.01.01.01.0 Treatment 3: Imperata cylindrica 98.0 94.7 96.3100.0100.0100.01.01.01.098.0 98.098.0100.0100.0100.01.01.01.0 Shrub/subshrub: Treatment 1: Acer rubrum 0.9 1.1 1.050.050.050.00.50.40.50 00000000 Urena lobata 0 0.1 0.1016.78.300.030.020 00000000 Baccharis halimifolia 0 0.1 0.1016.78.300.030.020 00000000 Vitis sp. 0 0 00000000.1 00.125.0012.52x10-302x10-3 *See Table 3-2 for treatment descriptions

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112Table E-6. Eucalyptus grandis and E. amplifolia in SRWC-90 Treatment* 4: cover (%), frequency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions. E. grandis E. amplifolia Species Cover Frequency Sps. composition Cover Frequency Sps. Composition B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. Herbaceous: Imperata cylindrica 70.8 67.369.0100.083.391.70.80.90.8 47.8 56.852.362.575.068.80.50.70.6 Lygodium japonicum 0.1 0.30.212.58.310.400.020.01 0 0.50.3016.78.300.020.01 Clematis virginiana 0.4 2.81.612.558.335.40.010.040.03 1.2 1.51.350.041.745.80.040.10.1 Cynodon dactylon 0 0.010.0108.34.2010-310-3 0.1 0.040.112.58.310.40.0300.02 Eupatorium capillifolium 0.7 00.38.304.20.0100.01 0 00000000 Medicago lupulina 0.1 1.20.612.525.018.800.020.01 0 00000000 Vicia acutifolia 0.8 0.80.825.025.025.00.020.010.02 0.1 0.10.112.516.714.63x10-34x10-34x10-3 Andropogon virginicus 0 0.30.108.34.200.010.01 0 00000000 Cirsium horridulum 0.1 00.112.506.310-310-310-3 0 00000000 Phytolacca americana 0 0.30.108.34.200.015x10-3 0 00000000 Eupatorium serotinum 0.4 0.30.412.516.714.60.20.020.1 0 00000000 Thelypteris kunthii 0 00000000 0 0.50.3016.78.300.015x10-3 Passiflora incarnata 0 00000000 4.8 0.32.525.08.316.70.20.010.1 Shrub/subshrub: Urena lobata 1.8 3.42.637.550.043.80.40.50.4 25.8 15.720.750.050.050.00.50.40.4 Sambucus canadensis 3.0 0.51.825.016.720.80.30.10.2 0.1 0.70.412.58.310.40.30.020.1 Baccharis halimifolia 0 1.00.5033.316.700.10.1 0.4 1.00.712.525.018.80.010.020.02 Quercus laurifolia 0 0.10.1025.012.500.020.01 0.1 0.040.112.58.310.410-310-310-3 Ampelopsis arborea 0 0.30.108.34.200.050.02 0 00000000 Acer rubrum 0 00000000 0.1 1.00.512.533.322.910-30.030.02 Schinus terebinthifolius 0 00000000 0 0.70.308.34.200.020.01 Vitis sp 0 0.70.308.34.200.010.01 0 00000000 Parthenocissus quinquefolia 6.2 1.43.850.033.341.70.20.030.1 0.1 00.0312.506.33x10-302x10-3 *See Table 3-2 for treatment descriptions

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113Table E-7. Eucalyptus grandis and E. amplifolia in SRWC-90 Treatment* 5: cover (%), frequency and species composition of herbaceous and shrub/subshrub species on bed (B) and interbed (IB) positions. E. grandis E. amplifolia Species Cover Frequency Sps. composition Cover Frequency Sps. composition B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. Herbaceous: Imperata cylindrica 20.4 13.617.025.016.720.80.20.20.2 02.01.0016.78.300.020.01 Lygodium japonicum 0.1 0.30.212.516.714.62x10-30.010.01 0.80.90.937.558.347.90.020.020.02 Thelypteris kunthii 0 0.040.0208.34.202x10-310-3 013.26.6058.329.200.20.1 Clematis virginiana 4.8 12.28.575.041.758.30.10.20.1 2.26.94.562.550.056.30.20.10.2 Cynodon dactylon 0 5.82.9033.316.700.10.1 1.11.91.525.070.847.90.020.040.03 Eupatorium capillifolium 0 00000000 00.30.108.34.200.013x10-3 Medicago lupulina 0.4 0.40.412.533.322.90.020.010.02 1.00.30.612.58.310.40.024x10-30.01 Vicia acutifolia 1.6 1.51.662.558.360.40.040.030.04 0.70.80.887.583.385.40.10.010.1 Andropogon virginicus 7.8 11.39.537.558.347.90.20.30.3 6.717.312.062.550.056.30.20.20.2 Cirsium horridulum 0 00000000 0.10.10.112.512.512.52x10-310-310-3 Bidens alba 14.1 2.78.475.083.379.20.20.10.2 18.014.116.062.566.764.60.030.30.2 Ambrosia artemisiifolia 0.1 0.30.212.58.310.42x10-30.010.01 00.040.0208.34.2010-310-3 Verbena brasiliensis 0 0.30.108.34.200.010.01 000000000 Oxalis corniculata 0 00000000 00.30.108.34.200.010.01 Setaria parviflora 0 00000000 00.40.2012.56.2300.010.01 Melothria pendula 0 00000000 00.040.0208.34.2010-310-3 Macroptilium lathyroides 0 00000000 00.040.0208.34.2010-32x10-3 Shrubs/subshrubs: Baccharis halimifolia 8.4 5.67.050.075.062.50.50.40.5 0.52.11.337.541.739.60.10.30.2 Urena lobata 3.8 3.73.762.558.360.40.30.20.2 25.126.025.687.583.385.40.70.70.7 Acer rubrum 0.5 0.70.637.558.347.90.10.10.1 0.30.30.350.025.037.50.10.010.03 Schinus terebinthifolius 3.0 1.02.025.025.025.00.10.10.1 0.80.70.737.58.322.90.020.010.01 Quercus laurifolia 0.4 0.040.225.08.316.70.12x10-30.1 0.40.10.325.016.720.80.030.010.02 Vitis sp. 0 0.30.108.34.200.010.01 000000000 Parthenocissus quinquefolia 9.1 1.35.262.541.752.10.20.030.1 7.61.64.675.033.354.20.20.040.1

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114Table E-7 continued. E. grandis E. amplifolia Species Cover Frequency Sps. composition Cover Frequency Sps. composition B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. B (n=2) IB (n=3) Avg. Rubus argutus 0.4 0.9 0.712.516.714.60.010.10.03 0 00000000 Ampelopsis arborea 0 0.1 0.1016.78.300.020.01 0.01 0.10.112.516.714.60.010.010.01 Sambucus canadensis 0 0.3 0.108.34.200.10.02 0 00000000 Toxicodendron radicans 0 0.3 0.108.34.200.10.1 0 00000000 Celtis occidentalis 0 0 0000000 0 1.20.6025.012.500.020.01 Quercus virginiana 0 0 0000000 0 0.30.108.34.200.015x10-3 *See Table 3-2 for treatment descriptions.

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APPENDIX F MEAN SQUARES FOR COVER (%), FREQ UENCY, AND SPECIES COMPOSITION

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116Table F-1. Herbaceous species in the opera tional area: significance (*= 5% level) of Culture (C), Plot (C ) and Position (Pos) mean squares for cover (%), frequenc y, and species composition. Species Cover Frequency Species composition C P(C)PosC*PosCP(C)Pos C*PosCP(C)PosC*Pos Aeschynomene americana 0.9* 0.10.60.21457.1*423.2121.1 393.88.713.76.88.7 Ambrosia artemisiifolia 9.5* 2.714.4*7.01054.6400.5*365.8 588.4*2x10-3*3x10-42x10-3*10-3* Ampelaster carolinianus 10-3 3x10-410-410-331.313.54.4 46.72x10-710-78.5x10-83x10-7* Andropogon virginicus 152.2 78.0*26.033.4707.2319.8*0.6 15.90.020.01*2x10-33x10-3Aristida purpurascens 39.7 27.628.242.31494.6*237.30 00.014x10-34x10-30.01 Bidens alba 288.1* 90.6*0.0216.82224.3*651.3*72.2 126.40.1*0.0210-33x10-3Calystegia sepium 2x10-4 3x10-410-32x10-38.713.76.8 8.76x10-89x10-84.3x10-86x10-8Carex sp. 8.2* 2.20.40.5146.358.7868.0 10.13x10-3*10-310-42x10-4Chamaesyce hypericifolia 2x10-4 10-42x10-42x10-47.35.67.7 7.33x10-82x10-82.8x10-83x10-8Cirsium horridulum 0.02 0.020.10.01238.1117.163.2 75.010-510-52x10-52x10-6Clematis virginiana 251.0 113.0*17.319.34060.8*1352.6*292.9 426.60.10.03*0.020.01 Collinsonia serotina 0.004 0.013x10-34x10-34.76.04.0 4.710-62x10-610-610-6Commelina diffusa 48.9* 11.722.318.14920.9*1214.9*53.0 36.70.02*4x10-30.010.01 Conyza canadensis 0.8 0.5*0.30.2111.552.4*81.7* 31.32x10-410-4*10-44x10-5Cucumis melo 0.03 0.040.020.0334.754.727.2 34.710-510-510-510-5Cynodon dactylon 177.6 243.0*291.0*94.51159.51439.5*36.7 393.40.030.04*0.05*0.02* Desmodium triflorum 2x10-4 10-42x10-42x10-47.35.67.7 7.310-78x10-810-710-7Digitaria ciliaris 3x10-4 4x10-410-510-312.518.90.6 24.15x10-74.9x10-73x10-79x10-7Erechtites hieraciifolia 4x10-3 0.014x10-34x10-34.76.04.0 4.72x10-63x10-62x10-62x10-6Eupatorium capillifolium 6.7 4.90.25.2955.7*176.032.6 444.8*2x10-310-33x10-510-3Eupatorium serotinum 16.8 8.2*0.041.035801.2*819.0*122.2 250.60.013x10-3*10-45x10-4Galium tinctorium 0.01 0.010.010.0129.3*8.30 03x10-62x10-62x10-62x10-6Hydrocotyle umbellata 0.20 0.3*0.040.1192.8160.2*0.4 19.510-410-4*10-52x10-5Imperata cylindrica 715.8 1440.6*0.15.52062.21866.6*24.7 51.00.10.22*0.020.01 Ipomoea purpurea 0.01 0.010.0034x10-342.225.8*4.0 4.710-610-64x10-74x10-7Krigia virginica 0.01 0.010.010.018.913.76.8 8.710-62x10-610-610-6Lepidium virginicum 0.6 0.40.10.6417.9*75.1*71.3* 103.1*10-33x10-42x10-44x10-4Lygodium japonicum 3.6* 0.80.030.21227.2439.1461.6 123.310-32x10-42x10-510-4

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117Table F-1 continued. Species CoverFrequency Species composition C P(C)PosC*PosCP(C)Pos C*PosCP(C)PosC*Pos Lythrum alatum 0.7 0.50.31.179.2138.3*28.8 138.710-410-42x10-510-4 Macroptilium lathyroides 5.0* 2.10.13.65414.3*498.4*26.4 121.03x10-310-34x10-53x10-3Melothria pendula 1.8 2.3*0.20.233.567.2*21.1 7.62x10-42x10-4*2x10-52x10-5Morrenia odorata 0.03 0.040.10.038.211.522.7 8.25x10-64x10-66x10-65x10-6Oxalis corniculata 0.01 0.010.010.0118.438.916.2 80.110-63x10-610-62x10-6Oxycaryum cubense 0.01 0.010.010.0129.3*8.30 010-54x10-610-510-5Panicum repens 2x10-4 10-42x10-42x10-49.75.212.1 9.76x10-73x10-710-66x10-7Passiflora incarnata 1.4 1.11.00.6155.266.78.3 99.6*2x10-410-44x10-510-4Phyla nodiflora 9.1 9.2*0.62.2705.1*209.1*7.7 7.32x10-32x10-3*10-310-3Phytolacca americana 142.9* 15.4*62.0*18.2*8174.0*518.0*1534.3* 471.0*0.1*0.010.03*0.01 Polygonum hydropiperoides 0.7 0.40.21.0514.5*136.3349.8 387.24x10-4*10-42x10-44x10-4* Rhynchosia cinerea 6.8 4.56.86.4469.1*119.4*31.0 29.32x10-30.0012x10-32x10-3Salvia riparia 10-3 10-32x10-3*10-335.720.691.5* 35.710-7*3x10-72x10-6*10-6* Setaria parviflora 86.0* 22.312.45.03383.9*497.6*61.2 78.10.03*0.013x10-310-3Stylisma patens 0.1 0.040.10.17.35.67.7 7.32x10-510-52x10-52x10-5Thelypteris kunthii 355.1* 50.06.556.72405.3*738.768.8 142.90.1*0.02*10-70.01 Typha latifolia 2x10-4 10-42x10-42x10-47.35.67.7 7.33x10-82x10-83x10-83x10-8UIH01 10-4 10-42x10-42x10-47.35.67.7 7.310-78x10-810-710-7UIH02 0.2 0.1*0.10.04123.3108.2117.8 1.410-45x10-5*3x10-52x10-5UIH03 10-3 10-3*0029.322.2*0 04x10-73x10-7*00 UIH04 2.6 1.9*0.20.229.322.2*0 04x10-44x10-4*10-410-4UIH05 10-4 10-42x10-42x10-47.35.67.7 7.310-610-610-610-6UIH06 2x10-4 10-43x10-42x10-49.75.212.1 9.63x10-72x10-74x10-73x10-7UIH07 10-4 10-410-410-44.76.04.0 4.72x10-82.1x10-810-82x10-8UIH08 4x10-3 0.013x10-34x10-34.76.04.0 4.74x10-75x10-74x10-74x10-7Verbena scabra 4x10-3 0.013x10-34x10-34.76.04.0 4.74x10-75x10-74x10-74x10-7

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118Table F-2. Shrub/subshrub species in the operational area: significance (*= 5% level) of Culture (C), Plot (C) and Position (P os) mean squares for cover (%), frequenc y, and species composition. Species Cover Frequency Species composition C P(C)PosC*PosCP(C)Pos C*PosCP(C)PosC*Pos Acer rubrum 0.01 0.0110-30.02456.5195.4203.3 31.32x10-3*10-32x10-410-3 Ampelopsis arborea 0.5 0.50.40.4154.793.029.1 10.23x10-52x10-410-34x10-5Baccharis angustifolia 10-3 10-3*0034.754.7*0 010-42x10-4*10-510-5Baccharis halimifolia 5.0* 1.21.01.73824.9*225.1434.6 554.745.653.427.432.7 Callicarpa americana 0.01 0.010.010.017.35.67.7 7.310-510-510-510-5Celtis occidentalis 4x10-3 0.013x10-30.0044.76.04.0 4.710-510-510-510-5Diospyros virginiana 2x10-3 10-310-510-364.027.40.5 20.82x10-610-64x10-78x10-7Lantana camara 5.8 4.4*1.71.666.050.0*7.3 7.32x10-32x10-3*10-310-3Ludwigia peruviana 217.9* 65.9*7.710.2869.11092.7*1313.3* 225.90.2*0.06*10-30.1 Parthenocissus quinquefolia 0.5* 0.10.30.2431.5*77.6*6.8 8.710-4*10-510-4*4x10-5* Quercus laurifolia 0.01* 2x10-33x10-310-3320.3*61.9106.8 59.110-5*2x10-63x10-610-6Quercus virginiana 2x10-4 10-42x10-42x10-47.35.67.8 7.32x10-72x10-73x10-72x10-7Rhus copallinum 2x10-4 10-42x10-42x10-47.35.57.7 7.34x10-73x10-74x10-74x10-7Rubus argutus 0.6 0.4*0.020.01183.3138.9*7.7 7.34x10-43x10-42x10-52x10-5Sambucus canadensis 15.3 9.3*9.97.7*195.1236.3*43.3 15.90.020.030.040.01 Schinus terebinthifolius 0.6 0.90.70.681.345.021.1 7.62x10-44x10-42x10-43x10-4Sida rhombifolia 0.01 0.010.010.017.35.67.7 7.33x10-62x10-63x10-63x10-6Solanum diphyllum 180.7* 13.1*18.4*21.7*7110.2*454.0*18.3 25.50.03*3x10-3*10-36x10-3* Taxicodendron radicans 10-4 10-42x10-42x10-47.35.67.7 7.310-78x10-810-710-7Triadica sebifera 0.3 0.4*0018.723.8*0 02x10-42x10-4*3x10-64x10-6UIS01 0.01 0.010.010.017.35.67.8 7.310-54x10-65x10-55x10-5UIS02 2x10-4 10-42x10-42x10-47.35.67.8 7.310-78x10-810-710-7UIS03 2x10-4 10-42x10-42x10-47.35.67.8 7.34x10-73x10-75x10-74x10-7Ulmus americana 2x10-4 10-42x10-42x10-47.35.67.8 7.32x10-72x10-73x10-72x10-7Urena lobata 4438.9* 304.8*61.340.98415.3*1501.5*0.03 21.80.4*0.10.030.1 Vitis sp. 0.01 0.010.010.017.35.67.7 7.37x10-75x10-77x10-77x10-7

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119Table F-3. Herbaceous species in E. grandis in SRWC-90 treatments#: significance (*= 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for cover (% ), frequency, and species composition. Species Cover Frequency Species composition T P(T)PosT*PosTP(T)PosT*PosTP(T)PosT*Pos Ambrosia artemisiifolia 0.03 0.040.010.01155.0104.24.36.22x10-510-52x10-63x10-6 Andropogon virginicus 128.7 76.7*3.74.43076.6922.1*212.7130.20.10*0.020.010.01 Bidens alba 101.2 70.432.646.68953.4*1157.4*17.424.80.03*0.010.010.01 Cirsium horridulum 10-3 2x10-310-310-355.8104.239.155.88x10-710-66x10-78x10-7Clematis virginiana 90.9 82.124.416.84291.91647.4*39.11583.6*0.030.022x10-310-3Cynodon dactylon 11.7 18.88.411.7342.3169.8434.0342.33x10-33x10-32x10-33x10-3Eupatorium capillifolium 0.2 0.30.10.224.846.317.424.85x10-510-44x10-55x10-5Eupatorium serotinum 0.2 0.102x10-32x10-3303.8196.84.36.20.010.020.010.01 Imperata cylindrica 7552.2* 1618.7*69.68.38298.6*1219.1*156.384.30.70.2*10-310-3Lygodium japonicum 0.04 0.10.030.02359.6555.617.432.210-44x10-42x10-410-4Medicago lupulina 0.5 1.30.30.4761.41473.8*277.8136.42x10-410-34x10-52x10-4Phytolacca americana 0.02 0.040.010.0224.846.317.424.88x10-610-56x10-68x10-6Thelypteris kunthii 0.1 0.10.10.10347.2239.20*049.62x10-510-510-510-5Verbena brasiliensis 0.02 0.040.010.0224.846.317.424.810-52x10-510-510-5Vicia acutifolia 2.9 2.110-410-44381.22326.4*4.36.210-310-3*2x10-510-5 #See Table 3-2 for treatment descriptions

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120Table F-4. Herbaceous species in E. amplifolia in SRWC-90 treatments#: significance (*= 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for cover (% ), frequency, and species composition. Species Cover Frequency Species composition T P(T)PosT*PosTP(T)Pos T*PosTP(T)PosT*Pos Ambrosia artemisiifolia 10-3 10-34x10-410-324.846.317.4 24.82x10-74x10-710-72x10-7 Andropogon virginicus 206.1 111.6*28.340.54520.1*1338.7*39.1 55.80.10.02*10-32x10-3Bidens alba 367.6 146.9*3.85.55958.6*1493.1*4.3 6.20.10.1*10-310-3Cirsium horridulum 0.01 0.01*00223.2416.7*0 02.3x10-64x10-6*6x10-89x10-8Clematis virginiana 25.0 28.86.27.54574.71724.5108.5 50.80.030.022x10-35x10-3Cynodon dactylon 3.1 2.3*0.20.32864.6*640.4*434.0* 811.0*10-310-310-410-3Eupatorium capillifolium 0.02 0.040.020.0224.846.317.4 24.810-53x10-510-510-5Imperata cylindrica 11291.4* 1697.5*21.728.310125.3*1122.7*212.7 95.51.2*0.1*0.010.01 Lygodium japonicum 0.9* 0.30.10.12922.9*443.7351.6 155.010-32x10-42x10-42x10-4Macroptilium lathyroides 10-3 10-34x10-410-324.846.317.4 24.82x10-74x10-710-72x10-7Medicago lupulina 0.6 1.040.140.2155.0289.4*4.3 6.22x10-410-310-410-4Melothria pendula 10-3 10-34x10-410-324.846.317.4 24.82x10-74x10-710-72x10-7Oxalis corniculata 0.02 0.040.010.0224.846.317.4 24.810-52x10-510-510-5Passiflora incarnata 9.2 17.15.27.4396.8740.7*69.4 99.20.020.030.010.01 Setaria parviflora 0.1 0.100.030.155.8104.239.1 55.83x10-510-42x10-53x10-5Thelypteris kunthii 60.5 38.547.060.51036.7601.91406.3 1036.70.020.020.010.02 Vicia acutifolia 0.8 0.4*0.010.019303.1*825.6*0 17.42x10-32x10-310-310-3 #See Table 3-2 for treatment descriptions

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134 BIOGRAPHICAL SKETCH Bijay Tamang was born on March 24, 1974 in Kathmandu, the capital of Nepal. He earned his bachelor's degree in biol ogy from Tribhuvan University, Kathmandu in 1995; and his master's degree in zoology from th e same institution (with specialization in ecology) in 1998. After his introduction to natural resources during his master’s research, his interest grew in natural re sources management and conservation. He conducted several studies (w ith his teammates) on endangered Bengal Florican (Houbaropsis bengalensis) and Lesser Florican (Sypheotides indica) in the protected areas of Nepal from 1998-2001. He also did research on the population and breeding success of the White-rumped Vulture (Gyps bengalensis) in 2002-2003. The species status is now Critical because of its population decline in Asia. He was an active member of Bird Conservation Nepal, and was involve d in promoting bird conservation. He served on several committees of the organizatio n. He also worked with the International Bible Society in Nepal from 1996-2003. He entered his master’s program at the University of Florida in the School of Fore st Resources and Conservation, in 2003, to study the performance of fast-growing tree sp ecies in the restoration of old phosphate mines in central Florida. He is interest ed in pursuing in-depth knowledge on ecological processes including conservation and management of natural resources.


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Title: Vegetation and Soil Quality Changes Associated with Reclaiming Phosphate-Mine Clay Settling Areas with Fast-Growing Trees
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Material Information

Title: Vegetation and Soil Quality Changes Associated with Reclaiming Phosphate-Mine Clay Settling Areas with Fast-Growing Trees
Physical Description: Mixed Material
Copyright Date: 2008

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Source Institution: University of Florida
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VEGETATION AND SOIL QUALITY CHANGES ASSOCIATED WITH
RECLAIMING PHOSPHATE-MINE CLAY SETTLING AREAS
WITH FAST-GROWING TREES















By

BIJAY TAMANG


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


2005

































Copyright 2005

by

Bijay Tamang















ACKNOWLEDGMENTS

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

Long, and George W. Tanner) for their suggestions, valuable time, critical reviews, and

edits of the manuscript. Special thanks go to Dr. Rockwood for his incessant guidance

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

Conservation. My appreciation goes to Florida Institute of Phosphate Research for

funding this project. Benefactors of this research also include Steve Segrest of the

Common Purpose Institute.

Thanks go to faculties and staff in the University for valuable suggestions and help

during my difficult time with the soil samples. I am grateful to Analytical Research Lab

staff and Dave Nolletti for analyzing my soil samples. Thanks go to Matt Langholtz,

Brian Becker, Valerie Milmore, and Erin Maehr who were always willing to help me in

the field despite high temperature and torrential rain.

My family has always been supportive of my work. I thank them all for their

encouragement and prayers. Finally, I would like to thank all my friends and people at

the School for making my days there comfortable.
















TABLE OF CONTENTS



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

LIST OF TABLES .......... ... ............ ......... ...................... vi

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

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

CHAPTER

1 IN TRODU CTION ................................................. ...... .................

2 LITERATURE REVIEW ........................................................................9

3 M E T H O D S ........................................................................................................... 2 0

S tu d y A rea ................................................................2 0
E xperim mental D design ........................ .. ........................ .. ........ .. ...... .... .. 23
D ata C o lle ctio n ..................................................................................................... 2 4
D ata A nalysis................................................... 26

4 RESULTS AND DISCU SSION ........................................... .......................... 29

T ree Size and Survival .......................................................... .. ........ ..... 29
Soil C characteristics ...................... .................. .............. ............. ... 33
V egetation Characteristics .............................................. ....... ....................... 41
Species R richness ......................... ... ....................4 1
Species Diversity and Community Similarity ...............................................54
Im portance V alue Index (IV I) .................................. .............................. ....... 57

5 C O N C L U SIO N S ..................... .... .......................... ........ ........ ...... ........... 73

6 FU TU R E R E SEA R CH ......................................................................... .............75

APPENDIX

A NAME AND NATIVITY OF HERBACEOUS AND SHRUB/SUBSHRUB
S P E C IE S ...................................... .................................................. 7 7










B TR EE SIZE A N D SU R V IV A L .................................................................................83

C SO IL C H A R A C TER ISTIC S ........................................................... .....................86

D IMPORTANCE VALUE INDEX (IVI) ........................................ .....................89

E COVER (%), FREQUENCY AND SPECIES COMPOSITION.............................101

F MEAN SQUARES FOR COVER (%), FREQUENCY, AND SPECIES
COM PO SITION .................. ............................. ...... .............. ... 115

REFERENCES ..................................... ................ .............121

BIOGRAPHICAL SKETCH ............................................................. ...............134









































v
















LIST OF TABLES


Table page

3-1 Operational area: description, number of 15 x 15 m study plots, and associated
average tree height (m), DBH (cm), density (trees/ha), basal area (m2/ha) and
quadratic diam eter (cm ). ............................................... ............... 22

3-2 Clone-configuration-fertilizer study (SRWC-90): description and number of
8 x 5 m study plots. ....................................... .......................23

4-1 Clone-configuration-fertilizer study (SRWC-90): average 3.75-year-old tree
height (m), DBH (cm), density (trees/ha), basal area (m2/ha) and quadratic
diam eter (cm ) by treatm ent and species. ..................................... ........... ....32

4-2 Operational area: average total Kjeldahl N [TKN (%)], P (mg/kg), K (mg/kg),
Ca (mg/kg), Mg (mg/kg), SOM (%), pH and BD (gm/cm3). ................................34

4-3 Operational area: significance (* = 5% level) of Culture, Plot (Culture) and
Position mean squares for TKN, P, K, Ca, Mg, SOM, pH and BD. .....................35

4-4 Clone-configuration-fertilizer study (SRWC-90) E. grandis and E. amplifolia
plots: average total N [TN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg
(mg/kg), SOM (%), pH and BD (gm/cm3). ........................................ ............ 36

4-5 Number of herbaceous and shrub/subshrub species in the operational area and
their nativity .......................................................41

4-6 Major herbaceous species in the operational area: significance (* = 5% level) of
Culture (C), Plot (C) and Position (Pos) mean squares for cover (%), frequency,
and species com position. ......................................................... 43

4-7 Significant shrubs/subshrubs in the operational area: significance (* = 5% level)
of Culture (C), Plot (C) and Position (Pos) mean squares for cover (%),
frequency, and species com position. ...................................................... 45

4-8 Number of herbaceous and shrub/subshrub species in SRWC-90 and their
nativity ...................................... ................................... ........ 46

4-9 Significant herbaceous species in E. grandis and E. amplifolia plots in
SRWC-90: significance (* = 5% level) of Treatment (T), Plot (T) and Position
(Pos) mean squares for cover (%), frequency, and species composition. .............47


5% level) of Treatment (T), Plot (T) and Position
(Pos) mean squares for cover (%), frequency, and species composition. ................47









4-10 Shrubs/subshrubs in E. grandis and E. amplifolia plots in SRWC-90:
significance (* = 5% level) of Treatment (T), Plot (T) and Position (Pos) mean
squares for cover (%), frequency, and species composition. ................................50

4-11 Herbaceous and shrub/subshrub species in the operational area: Shannon-Wiener
diversity index (H'), maximum possible diversity (H'max) and relative diversity
(J).............. ..................... ............................................. ...... 54

4-12 Herbaceous and shrub/subshrub species in SRWC-90: Shannon-Wiener
diversity index (H'), maximum possible diversity (H'max) and Relative diversity
(J).............. ..................... ............................................. ...... 55

4-13 Operational area: Jaccard's community similarity index (Cj) for herbaceous (H)
and shrub/subshrub (S) species. ........................................ ......................... 56

4-14 Clone-configuration-fertilizer study (SRWC-90): Jaccard's community similarity
index (Cj) for herbaceous (H) and shrub/subshrub (S) species ..............................57

4-15 Average IVI (> 5.0) of herbaceous and shrub/subshrub species in four cultures
in the operational area. ....................................... ........................ 58

4-16 Average IVI (> 5.0) of herbaceous species in SRWC-90. ............. ...................62

4-17 Average IVI (> 5.0) of shrub/subshrub species in SRWC-90..............................63

4-18 Spearman correlation coefficient (r) of herbaceous species with highest IVI in
the operational area ......................... ........................ .. .. ........ ........... 68

4-19 Spearman correlation coefficient (r) of shrub/subshrub species with highest IVI
in the operational area ...................... ................ .......................... 69

A-i Name and nativity of herbaceous species. ............ ................................................78

A-2 Name and nativity of shrub/subshrub species. .................. ........................ 81

B-l Tree size and survival in the operational area: average tree height (m), DBH
(cm), basal area (m2/ha), density (trees/ha) and quadratic diameter (cm)...............84

B-2 Tree size and survival in SRWC-90: average 3.75-year-old tree height (m), DBH
(cm), basal area (m2/ha), density (trees/ha) and quadratic diameter (cm)...............85

C-l Soil characteristics in the operational area: total Kjeldahl N [TKN (%)], P
(mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and bulk density
(BD) on bed (B) and inter-bed (IB) positions. ................................. ............... 87

C-2 Soil characteristics in SRWC-90 E. grandis and E. amplifolia plots: total N [TN
(%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg), SOM (%), pH and bulk
density (BD) on bed (B) and inter-bed (IB) positions..............................88









D-1 Single-EG in the operational area: IVI of herbaceous and shrub/subshrub
sp e cie s. ........................................................... ................ 9 0

D-2 Double-EG in the operational area: IVI of herbaceous and shrub/subshrub
sp e cie s. ........................................................... ................ 9 2

D-3 Quadruple-EG in the operational area: IVI of herbaceous and shrub/subshrub
sp e cie s. ........................................................... ................ 9 4

D-4 Double-PD in the operational area: IVI of herbaceous and shrub/subshrub
sp e cie s. ........................................................... ................ 9 5

D-5 Treatments* 1, 2 and 3 in SRWC-90: IVI of herbaceous and shrub/subshrub
sp e cie s. ........................................................... ................ 9 7

D-6 Treatment* 4 in SRWC-90: IVI of herbaceous and shrub/subshrub species..........98

D-7 Treatment* 5 in SRWC-90: IVI of herbaceous and shrub/subshrub species..........99

E-1 Single-EG in the operational area: cover (%), frequency and species
composition of herbaceous and shrub/subshrub species on bed (B) and interbed
(IB ) positions .............................................. .................. .... 102

E-2 Double-EG in the operational area: cover (%), frequency and species
composition of herbaceous and shrub/subshrub species on bed (B) and interbed
(IB ) positions............................................................................................ 104

E-3 Quadruple-EG in the operational area: cover (%), frequency and species
composition of herbaceous and shrub/subshrub species on bed (B) and interbed
(IB ) positions............................................................................................ 107

E-4 Double-PD in the operational area: cover (%), frequency and species
composition of herbaceous and shrub/subshrub species on bed (B) and interbed
(IB ) positions............................................................................................ 109

E-5 Eucalyptus grandis and E. amplifolia in SRWC-90 Treatments* 1, 2 and 3:
cover (%), frequency and species composition of herbaceous and shrub/subshrub
species on bed (B) and interbed (IB) positions ................................... ................111

E-6 Eucalyptus grandis and E. amplifolia in SRWC-90 Treatment* 4: cover (%),
frequency and species composition of herbaceous and shrub/subshrub species on
bed (B) and interbed (IB) positions .................. ................................. 112

E-7 Eucalyptus grandis and E. amplifolia in SRWC-90 Treatment* 5: cover (%),
frequency and species composition of herbaceous and shrub/subshrub species on
bed (B) and interbed (IB) positions ................................................ ............... 113









F-l Herbaceous species in the operational area: significance (*= 5% level) of
Culture (C), Plot (C) and Position (Pos) mean squares for cover (%), frequency,
and species com position .................................................................................. 116

F-2 Shrub/subshrub species in the operational area: significance (*= 5% level) of
Culture (C), Plot (C) and Position (Pos) mean squares for cover (%), frequency,
and species com position .................................................................................. 118

F-3 Herbaceous species in E. grandis in SRWC-90 treatments#: significance
(*= 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for
cover (%), frequency, and species composition............... ..... ..................119

F-4 Herbaceous species in E. amplifolia in SRWC-90 treatments#: significance
(*= 5% level) of Treatment (T), Plot (T) and Position (Pos) mean squares for
cover (%), frequency, and species composition............... ..... ..................120
















LIST OF FIGURES


Figure page

3-1 M ap of study area. ..................................... .. .. ........ ......... ...... 21

3-2 Sampling schemes used for collecting herbaceous and shrub/subshrub data in
15 x 15 and 8 x 5 m plots. .................................. ......................... 24

4-1 Eucalyptus grandis in the operational area: correlation between total basal area
per hectare and cogongrass IV I ..................................................... ............. 65

4-2 Cottonwood in the operational area: correlation between total basal area per
hectare and cogongrass IVI. ...... ........................... ......................................66

4-3 Eucalyptus grandis in SRWC-90: correlation between total basal area per hectare
and cogongrass IVI................... ........................ ......... 70

4-4 Eucalyptus amplifolia in SRWC-90: correlation between total basal area per
hectare and cogongrass IVI. ...... ........................... ......................................70

4-5 Eucalyptus (E. grandis and E. amplifolia combined) in the study area: correlation
between total basal area per hectare and cogongrass IVI.................. .......... 71















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

VEGETATION AND SOIL QUALITY CHANGES ASSOCIATED WITH
RECLAIMING PHOSPHATE-MINE CLAY SETTLING AREAS
WITH FAST-GROWING TREES

By

Bijay Tamang

August 2005

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

Abandoned phosphate mines in central Florida are invaded by cogongrass

(Imperata cylindrica). Native vegetation in cogongrass-dominated areas is minimal or

absent, thus complicating site restoration. Cogongrass dominates native vegetation

because of its allelopathic nature and strong competitiveness. Adverse edaphic factors

and limited nutrients in mined areas further hinder the establishment of native vegetation.

This study examined the performance of fast-growing eucalyptus (E. grandis and

E. amplifolia) and cottonwood (Populus deltoides) in suppressing cogongrass in an old

phosphate mine in Lakeland, Florida. Understory vegetation was studied in 2- and

3-year-old E. grandis and 2-year-old cottonwood in the operational plantations; and in a

3.75-year-old E. grandis and E. amplifolia clone-configuration-fertilizer (SRWC-90)

study. Soil samples were collected and analyzed for macronutrients (N, P, K, Ca, Mg),

pH, soil organic matter (SOM), and bulk density (BD).










Both tree height and diameter at breast height (DBH) differed significantly

among single, double, and quadruple row E. grandis (Single-EG, Double-EG and

Quadruple-EG, respectively) and double row cottonwood (Double-PD) in the operational

area (p < 0.0001). Total Kjeldahl nitrogen (TKN) ranged from 0.18% in Quadruple-EG

to 0.35% in Double-PD. Quadruple-EG had the lowest SOM (3.80%), while Double-PD

had the highest (6.50%). The pH ranged from 7.3 in Double-EG to 7.9 in Quadruple-EG.

The TKN (p = 0.0002), Mg (p = 0.0481), pH (p = 0.0321), and SOM (p = 0.0009)

differed significantly (5%) among four cultures in the operational area.

Both native and introduced species were recorded in the understory. Clematis

virginiana, Bidens alba, Commelina diffusa, Phytolacca americana, and Ambrosia

artemisiifolia were frequent herbaceous species. Frequent shrubs/subshrubs included

Urena lobata, Baccharis halimifolia, and Ludwigiaperuviana. Herbaceous species

richness (35) was highest in Double-EG, which also had the highest shrub/subshrub

richness (23). Cogongrass was still dominant in Double-PD and three treatments of

SRWC-90, but well controlled in most plots in E. grandis cultures in the operational area.

However, the cogongrass Importance Value Index (IVI) had a nonsignificant correlation

with stand basal area (r = 0.19, p = 0.4587). Cogongrass IVI also had a nonsignificant

correlation with stand basal area in Double-PD (r = -0.21,p = 0.6103). In SRWC-90,

cogongrass had significant negative correlation with E. grandis (r = -0.91, p < 0.0001)

and E. amplifolia (r = -0.73, p = 0.0028) basal area. Eucalyptus grandis with good stand

density seems to suppress cogongrass more effectively compared to E. amplifolia and

cottonwood. Fast-growing tree plantations with good stand survival have the potential to

control cogongrass and amend soil in mine lands.














CHAPTER 1
INTRODUCTION

Biodiversity is one indicator of system stability (Evans 1992). Pristine ecological

systems are rich in biodiversity, and their components are balanced. However, these

stable systems are often disturbed and threatened by human actions. Some of the actions

are intentional; and some are unintentional, consequences of other indirect actions.

Ecosystem functions are usually disturbed at various scales during resource extraction,

regardless of whether the resources are located on the earth surface or beneath it. The

disturbances sometimes are so severe that ecosystems take many years to recover. In

central Europe, establishment of woody species took 20 years on average, depending on

soil conditions (Prach 1994). When disturbance exceeds critical levels, ecosystems lose

their resilience, and irreversible changes occur.

With increasing human population and industrial development, demand for

resources increases daily. Natural resources such as coal, gas, water, and other raw

materials located beneath the earth surface comprise most of the resources extracted to

meet human needs. Ecosystem destruction through mineral extraction and other activities

has been a fundamental part of development (Pensa et al. 2004). The effect on terrestrial

and aquatic environments from the extraction of mineral resources is severe and usually

irreversible (Rybicka 1996). External intervention is the only way to restore such areas;

however, success cannot be guaranteed. The effect of resource extraction can be at the

extraction site or at nearby waste disposal sites, such as clay settling areas (CSAs) in the

case of phosphate mines in central Florida.









Phosphate mining started in Florida in 1883, after hard rock deposits were found

near Hawthorne in Alachua County. Phosphate is still actively mined in phosphate-rich

central Florida. Phosphate deposits cover about 518,000 ha (1,280,006 acres) in Polk,

Hillsborough, Hardee, Manatee, and DeSoto Counties (Ecolmpact 1980). In central and

north Florida, from July 1975 through December 2002, phosphate was extracted from

more than 69,000 ha (171,000 acres) (DEP 2003), and this area will continue to increase

in the future (Segal et al. 2001). Mining currently disturbs about 2,000 to 2,500 ha (5000

to 6000 acres) of land every year in Florida (DEP 2003).

Florida alone contributes about 75% of the United States' phosphate requirement

and 25% of the phosphate export. Typical phosphate ore (also known as matrix) is found

at a depth of 4.5 to 15 m (15 to 50 ft) below the surface and is 3 to 6 m (10 to 20 ft) thick.

Matrix consists of equal parts of sand, clay, and phosphate. The top layer of earth

(overburden) is removed to extract the matrix, which is subjected to high-pressure water

guns that turn it into a watery mixture called slurry. Phosphate rock and sand are

separated from the slurry. Sand is later used for reclamation of the extraction sites. The

by-product (the mixture of water and clay) is pumped into CSAs, which constitute about

40% of the phosphate-mine lands and are 10 to 20 m (30 to 60 ft) deep. They retain

water for a longer period of time and take about 15 years to dewater. There are

approximately 64,700 ha (160,000 acres) of these undeveloped CSAs in central Florida

alone (CPI 2003).

The north and central Florida phosphate mining districts were heavily forested

historically, with stands of longleaf pine (Pinuspalustris), slash pine (Pinus elliottii), oak

(Quercus sp.), and cypress (Taxodium sp.). Phosphate strip-mining, however,









significantly altered these landscapes. Disturbed soil during mining made the old mined

areas suitable for invasive exotics such as cogongrass, natalgrass (Rhynchelytrum

repens), and bahiagrass (Paspalum notatum). Cogongrass is the most noxious exotic

species that inhibits the growth of other native plants, because of its dense above-ground

and below-ground growth, allelopathic effects, competition, and susceptibility to

wildfires during dry season. It is the major problem species throughout tropical and

subtropical parts of the world and has invaded forests, rangelands, reclaimed mined areas,

roadsides and natural ecosystems in the southeastern United States (MacDonald et al.

2002; Shilling et al. 1997) and occurs in almost all old CSAs. It is a shade-intolerant,

fast-growing rhizomatous plant; is the dominant vegetation in southeast Asia, covering

121 million ha (300 million acres); and has infested more than 202 million ha (500

million acres) of plantation and agricultural lands worldwide. It spreads through seeds

and rhizomes.

Florida policy requires mining companies to reclaim areas mined after July 1, 1975.

Wetlands must be reclaimed to at least the same area as before mining, and at least 10%

of upland must be planted with native species. Mining companies have reclaimed

significant areas of uplands and wetlands since the law was enacted (Segal et al. 2001).

Details of reclamation standards are given in Chapter 62C-17 of the Florida

Administrative Code. As of December 2003, 63% of the land mined since July 1, 1975

has been successfully reclaimed (DEP 2003). However, this law excludes mandatory

reclamation of old areas mined before 1975. Restoration of these older abandoned

disturbed sites has become the sole responsibility of government and other environmental

agencies.









Restoration of old phosphate-mined areas (especially cogongrass-infested CSAs)

has become a major challenge. CSAs are looked upon as unproductive wastelands and

unsuitable for development because of unstable clay soil. Because of their poor soil

quality, CSAs do not support good growth of native species. In addition, high

establishment costs discourage using the areas for crop production. Reclamation of

CSAs is difficult because of competition, allelopathy, soil degradation, compaction, and

fire susceptibility (Dela Cruz 1986; Ohta 1990a). Therefore, the presence of invasive

exotics (like cogongrass) hinders successful reclamation of disturbed sites, and also

threatens replanted native species. Native species must overcome the adverse edaphic

conditions while competing with cogongrass for limited available nutrients. Restoration

activities on such sites therefore should have the dual purposes of removing the invasive

species as well as replanting the area with native species.

One major problem in controlling cogongrass has been the limited knowledge of its

ecology, physiology, and management. Studies conducted in the United States (Ramsey

et al. 2003; Shilling et al. 1997) and in cogongrass' native range (Otsamo et al. 1995a;

Otsamo 1998a; Peet et al. 1999; Turvey 1996) provided valuable information on the

ecology and management of cogongrass. Use of herbicide, the widely practiced method

to control weeds, has limited success on this noxious weed, and the effect is temporary

(MacDonald et al. 2002; Willard et al. 1997; Willard et al. 1996). Multiple applications

are required for long-term control. Removal of the above-ground biomass is not effective

as it grows back from the rhizomes. Therefore, a control strategy should incorporate

removal of above-ground biomass and removal of the underground rhizomes. Disking

alone controls the species for a short duration. However, the combination of double









disking and split applications of imazapyr [2-(4-isopropyl-4-methyl-5-oxo-2-imidazolin-

2-yl)nicotinic acid] can control cogongrass regrowth (up to 96%) 12 months after

treatment (Shilling et al. 1997).

Better understanding of the ecology of cogongrass has given rise to innovative and

effective ideas for its control. Since it is a heavy shade-intolerant species, researchers

suggest using repeated application of herbicide and introducing fast-growing trees that

form a dense canopy, for effective and long-term control (Ramsey et al. 2003; Shilling et

al. 1997). Use of plantations to catalyze the restoration of degraded lands has been

widely discussed and practiced throughout the world (Fimbel and Fimbel 1996; Lamb

1998; Lugo 1992; Parrotta 1992, 1993; Parrotta et al. 1997; Singh et al. 2002). However,

priority must be given to building SOM, essential plant nutrients, and vegetation cover to

facilitate and enhance the regeneration and growth of native species. Different

approaches have been used to restore abandoned old mined areas. Some used organic

enrichment techniques to build soil quality and supply nutrients to native vegetation

(Lunt and Hedger 2003; Sydnor and Redente 2002). Others have used tree plantations

(Glenn et al. 2001; Parrotta and Knowles 1999; Pensa et al. 2004), with both native and

exotic species as nurse crops. In some cases, both approaches have been incorporated

(Parrotta and Knowles 1999).

Though it is always beneficial to use native species to restore degraded lands,

noninvasive exotic species can be used to rehabilitate badly degraded areas where native

species cannot grow (Lamb 1998). They can later be replaced with native species when

site conditions have improved. Appropriate exotics can also be used to assist native

biodiversity conservation (Norton and Miller 2000).









Flatwoods and poorly drained phosphate-mine lands in central Florida are capable

of supporting both native and exotic short-rotation woody crops (SRWCs) like

cottonwood, eucalyptus, leucaena (Leucaena leucocephala), slash pine, and castor bean

(Ricinus communis) (Stricker et al. 2000). These provide multiple environmental benefits

including improved water quality, soil stabilization, atmospheric carbon sequestration,

and wildlife habitat. Ongoing research indicates that restoration of

cogongrass-dominated phosphate-mined areas can also be achieved using fast-growing

SRWCs like eucalyptus and cottonwood. In spite of increasing ecological and technical

skills, restoration success, however, is limited (Geist and Galatowitsch 1999).

Different species of eucalyptus have been used in plantations worldwide for

biomass production and restoration of degraded sites due to their fast growth and

short-rotation cycles (Ashagrie et al. 2005; Bone et al. 1997; Callisto et al. 2002; Fabido

et al. 2002; Geldenhuys 1997; Loumeto and Huttel 1997; Nzila et al. 2001; Ribeiro et al.

2002; Sicardi et al. 2004; Strauss 2001; Tyynela 2001). In addition, their coppicing

ability can significantly reduce repeated establishment costs. In the United States,

eucalypts are mostly used for mulch production. However, eucalypt plantations have

produced mixed reactions worldwide. Monocultures may adversely affect soil fertility,

water cycles, wildlife (Loumeto and Huttel 1997), biodiversity, local vegetation, and use

more water than other tree species. Eucalyptus plantations do not provide shelter and

food for the native biodiversity in Brazil (Couto and Betters 1995). Most of the concerns

about eucalyptus are related to depletion of soil nutrients and allelopathy caused by the

litter, which is said to exert an antibiotic effect on soil microorganisms. However,

eucalypts can amend soil by penetrating relatively impermeable layers and drawing









nutrients from deep layers when planted in degraded areas (Poore and Fries 1985).

Eucalypts are also capable of suppressing dominant grass and providing habitat for seed

dispersers (Bone et al. 1997).

Cottonwood is the fastest growing native species in North America. It is a

deciduous bottomland hardwood species. Several varieties of cottonwood have been

studied and used for biomass production (Gardiner et al. 2001; Joslin and Schoenholtz

1997; Knowe et al. 1998; Lee and Jose 2003; Lockaby 1986; Thornton et al. 1998; Twedt

et al. 1999). However, biomass production is less than nonnative eucalyptus species

(Stricker et al. 2000). It has also been used as a nurse crop for restoration of degraded

lands (Gardiner et al. 2001; Gardiner et al. 2004; Sher et al. 2000).

Conversion of degraded lands like CSAs to SRWC farms may provide habitat for

wildlife and facilitate the growth of native species. Compared with multi-species

plantations, single-species SRWC farms may, however, reduce the availability of diverse

food and shelter for local wildlife. SRWCs mostly affect species that utilize habitat

consisting of old trees due to short-rotation. While accumulating above-ground and

below-ground biomass, SRWCs have the potential to stabilize soil, increase SOM

through leaf litter, decrease BD and increase soil porosity through root penetration.

Noninvasive eucalyptus (E. grandis and E. amplifolia), cottonwood, cypress and

slash pine hybrids were planted in a 50 ha cogongrass-dominated CSA (Kent site) near

Lakeland in central Florida. Planting began in 2000 with an objective to use these

SRWCs for energywood and other commercial products. Initial results showed that the

growth of shade-intolerant cogongrass was well controlled in eucalyptus stands. Native

species such as climbing dayflower (C. diffisa), kunth's maiden fern (Thelypteris









kunthii), shyleaf (Aeschynomene americana), saltbush (B. halimifolia), oak (Quercus sp.)

and red maple (Acer rubrum) were observed in the SRWC (Tamang et al. 2004).

This study began in 2004 to evaluate the performance of SRWCs in controlling

cogongrass and making the site suitable for native flora. The study focused on assessing

different understory vegetation growing in the stands and documenting changes in soil

characteristics. The specific objectives were

* Objective 1: Study the performance of E. grandis, E. amplifolia and cottonwood in
controlling cogongrass.

* Objective 2: Document the regeneration of native species at the site.

* Objective 3: Document changes in SOM, BD, pH and macronutrients (N, P, K, Ca
and Mg) on and between beds in SRWCs.

The hypotheses of the study were

* Hypothesis 1: Species that grow comparatively fast and form a dense canopy will
perform well in controlling cogongrass.

* Hypothesis 2: Understory vegetation diversity is higher in old stands than in
younger stands.

* Hypothesis 3: As the SRWCs accumulate above-ground and below-ground
biomass, BD and pH decrease and SOM increase.

* Hypothesis 4: Soil characteristics, especially BD and nutrients, differ between bed
and interbed positions.














CHAPTER 2
LITERATURE REVIEW

Restoring degraded sites is a challenging task and it takes time to achieve desired

goals. Restoring sites back to reference systems is practically not achievable; however,

increasing habitat suitability, native species diversity, and controlling exotic species can

often be the primary goals (Prober and Thiele 2005). Restoration activities can even have

negative impacts on the system during initial years, mostly in places where intensive site

preparation is required. Species richness of the site may decrease in the beginning;

however, it may then increase in subsequent years. Reduction in number of plant species

was observed a year after restoration of Florida sandhills by harvesting Pinus clausa, but

species number increased in later years (Provencher et al. 2000).

Restoration of mine lands requires building SOM, essential plant nutrients and

vegetation cover to accelerate natural recovery processes. Both native and exotic tree

species are widely used in the restoration of degraded sites. Tree plantations are useful in

increasing SOM, essential plant nutrients, decreasing soil BD, increasing soil aeration

and ameliorating microclimatic conditions. Trees are also capable of removing toxic

substances from the soil (Rockwood et al. 2001).

Vegetation growth is sparse in mined lands due to nutrient deficiencies (Singh et al.

2002). However, minimizing nutrient and water limitations during the early phase can

accelerate the revegetation process. Rather than using exotic species, using native

species that are well adapted to such stress conditions could be beneficial (Clemente et al.

2004). However, success of restoration efforts cannot be guaranteed due to competition









with exotics, changes in soil nutrients and establishment conditions (Prober and Thiele

2005).

Mining creates intensive disturbance to soil and vegetation (Bradshaw 2000).

Recovery of such extremely degraded ecosystem is possible only through improving soil

fertility and species diversity (Fang and Peng 1997). Natural succession plays a crucial

role in the restoration of degraded sites but may take centuries to complete. Restoration

of degraded sites through natural succession is only successful at sites that have

nutrient-rich soil and are located near healthy natural stands that serve as seed sources

(Bradshaw 2000). In situations where habitat conditions are extreme, the process is

retarded (Prach and Pysek 2001). Extreme habitat conditions require external input to

build soil quality and aid the immigration of seeds and plants. However, success of

restoration through external input largely depends on knowledge of the systems present at

the site before disturbance and available seed source in nearby vicinity, which help define

strategic plans to achieve restoration goals.

Plantations have been widely used to recover vegetation on mined lands (Reintam

and Kaar 2002); mostly because of their multiple uses. Trees modify the microclimate,

nutrient availability, shelter and food supply for many of the forest biota. Plantations are

mostly tree monocultures; polycultures however, are generally favored due to their

resistance to pest outbreak (Hartley 2002). Native species are generally preferred over

exotics. In forests where exotic species become established, ecological restoration

treatments may create a forest health problem that is as undesirable as the pretreatment

condition (Wagner et al. 2000). Though planting in rows is easier, planting trees without

rows makes reforested sites look more natural (Allen 1997)









Understory vegetation comprises one of the most important elements of

biodiversity both within plantations and natural stands. It is often the single best

predictor of animal diversity. Understory vegetation is frequently undersampled in

ecological studies. Composition, abundance and diversity vary across location, season

and plot size (Small and McCarthy 2003). Factors like habitat heterogeneity, quality,

disturbance, climate, planting density and proximity to natural forest are important in the

species diversity in plantations. Species diversity expands quickly after vegetation

recovers in a degraded ecosystem and occurs faster in the early and middle stages of the

process of vegetation development. With increasing stand age, native vegetation

colonizes gradually into the planted communities (Fang and Peng 1997; Pande et al.

1988; Wang et al. 2004). Species density and richness increase gradually (Halpern and

Spies 1995; Pande et al. 1988; Wang et al. 2004) depending on soil quality, climate and

type of species planted.

Stand maturity positively influenced density and species richness in Dehra Dun,

India (Pande et al. 1988). Both herbaceous and shrubby species richness were higher in a

Pinus roxburghii plantation followed by \/inhi robusta and Tectona grandis, which

were planted in 1926. Herbaceous and shrubby species richness was the lowest in a

eucalyptus planted in 1972. Communities in three former plantations were similar to one

another, while a eucalyptus plantation was different. However, differences in species

richness, diversity, and evenness values were not noted in different aged hardwood stands

in the Appalachian Mountains of northern Georgia (Ford et al. 2000).

Though plantations generally have low species diversity and richness compared to

natural stands, species diversity in an old (38 to 40.5 year) messmate (E. cloeziana)










plantation in Australia was similar to that of native eucalypt forests (Wang et al. 2004).

Though understory sapling density was comparatively lower in plantations in Estonia,

total stand richness was equal, both in natural and a European black alder (Alnus

glutinosa) stands. Species composition of natural stands was more diverse compared to

plantations (Pensa et al. 2004). Type of species planted has a direct influence on the

microenvironment which ultimately affects species diversity (Pande et al. 1988).

Allelopathy, which is exhibited by a large number of trees, affects understory vegetation

succession (Kohli 1998). Establishment of diverse ground vegetation therefore depends

on the species planted, planting density, the time the site is exposed to species

immigration, and the diverse landscape (Pensa et al. 2004).

Floral diversity was inversely related to crown cover in Ulumba Mountain site,

Malawi (Bone et al. 1997). Therefore, gaps in the plantation have the potential to change

species richness. The number of naturally regenerated seedlings increased from 14 to 21

and saplings from 2 to 24 after 23 months of gap creation in an Acacia mangium

plantation in Indonesia (Otsamo 2000a). After plantations are harvested, dormant seeds

of pioneer species get the opportunity to germinate. Climax species are replaced and

pioneer species start to colonize. Open canopies might serve as one of the driving forces

for the increase in species diversity. Woody and herbaceous species diversity was

significantly higher in 1-year-old E. camaldulensis coppice plots than in control and

plantation stands in the Ulumba Mountain, Malawi. Even the number of tree and shrub

species was also significantly higher in coppice plots. Coppice sites had the largest

number of herb species (Bone et al. 1997).









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.

Plantations can also serve as a suitable habitat for threatened species in the later stages as

observed in southeast Queensland, Australia. Two vulnerable and one rare species were

recorded in the plantation (Wang et al. 2004). Both rare and endangered species were

also recorded from restored sites in the Czech Republic in the later successional stage

(Prach and Pysek 2001).

Native species are threatened when invasive exotics such as cogongrass start

appearing. Cogongrass colonizes forest clearings with subsequent fire-based

maintenance (Otsamo 2000a). It produces allelopathic chemicals that inhibit the growth

of native species. Its rhizome leachate is comparatively more inhibitory than leaf

leachate (Inderjit and Dakshini 1991). Performance of slow-growing woody species is

poor in reclaiming cogongrass-dominated grasslands. However, these grasslands have

the potential to support short-rotation woody species. 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).

Intensive site preparation must be done to suppress the grass at least for a year even

when fast-growing species are used. Glyphosphate [isopropylamine salt of

N-(phosphonomethyl) glycine] has been widely used to control cogongrass; however,

imazapyr also has the potential to control. Integration of reforestation and conservation

tillage can prove to be beneficial for soil fertility and productivity of such grasslands

(Terry et al. 1996). Several plant species have been used to control cogongrass. Density









of cogongrass was reduced by 67% and 51% using gliricidia (Gliricidia sepium) and

leucaena, respectively, in Nigeria. Rhizomes were reduced by 96% in gliricidia and 90%

in leucaena plots, with rhizome mortality significantly higher in gliricidia plots compared

to leucaena and control plots (Anoka et al. 1991). Herbaceous cover crops belonging to

genera Calapogonium, Crotoleria, Mucuna and Pueraria have also been effective in

suppressing cogongrass (MacDicken et al. 1996).

Combining forest plantations with moderate to high tillage, weeding and fertilizer

inputs have been successful. Fast-growing tree species control cogongrass and amend

soil physical and chemical properties at the same time (MacDicken et al. 1996). Two

species of fast-growing velvet beans (Mucunapruriens var. utilis and M. deeringiana)

were also effective in shading cogongrass when the cover was retained for a longer

period. However, performance was less effective when topsoil was lost by erosion

(Hairiah et al. 1993). Tillage is an important factor for sustainable crop production in

cogongrass-infested areas. Crop productions in such areas have been successful where

animal or tractor draft power is available. However, investment increases and return

decreases in later years when the weed intensity increases and soil quality decreases

(Noordwijk et al. 1996). In Indonesia, 14 species of fast-growing eucalyptus with narrow

crown and open canopies planted in a mechanically prepared site performed worse in

cogongrass-dominated grassland (Otsamo et al. 1995b).

Soil quality is another crucial factor that supports species diversity. Poor soils

generally support fewer species than good soils. The relationship between vegetation and

soil at the site can therefore be an important tool to assess site quality (Zas and Alonso

2002). Priority should therefore be given to soil amendment in the restoration of









degraded sites. Litter is the primary source of nutrients in natural systems. It is the major

input in the nutrient cycle and decomposer food chain. Plant essential nutrients are

continuously added to soil from the decomposition of litter and plant residues. In

contrast, litter addition in plantations is short-term and is discontinued after each harvest,

at least for sometime.

Residual logging slash is the main source of carbon after the harvest in plantations.

Slash enhances soil physical and chemical properties. Slash occupied 40 to 60% of the

harvest area in sawlog treatment in South Carolina (Johnson et al. 2002). Forest harvest

on average increases soil C (Johnson and Curtis 2001). However, the effect of harvesting

on soil C depends on the harvest type. Sawlog harvesting increases soil C up to 18%,

while whole-tree harvesting decreases it by 6%. In some cases, harvesting has little

lasting effect on soil C (Johnson et al. 2002).

The rate of nutrient removal is higher in short-rotation plantations due to frequent

harvest (Corbeels et al. 2003). This has become a major concern of nutrient management

in short-rotation plantations. Though harvest residues are usually added to soil, nutrient

deficiencies may occur due to discontinued litter addition, degradation of SOM and

nutrients during site preparation. Nutrients trapped in plant tissues are removed from the

site along with the harvest. Whole-tree harvesting reduced 50% of the above-ground

biomass and nutrients in Gmelina arborea plantation (Agus et al. 2004).

Soil organic matter added to soil in plantations with the growth of trees changes the

structure and properties of soil (Singh 1998). Plant residues continuously added to soil in

natural systems maintain and increase SOM. However, in plantations, harvesting limits

the continual addition of the plant parts. Changes in land use and management alter soil









structure, soil organic carbon and nutrients. It is widely believed that soil nutrients are

degraded when natural forests are converted into monoculture plantations. Priority must

be given to the management of SOM in plantations to ensure a continuous supply of plant

nutrients. Soil organic matter acts as a storehouse for large quantities of plant nutrients

and provides cation exchange and water-holding capacities (Brady and Weil 2001).

Compared to plantations, more organic matter is added to soil in primary forests every

year due to higher decomposition rate.

Soil carbon decreases in the initial years of plantation establishment and increases

over time (Hansen 1993; Makeschin 1994). However, organic carbon and nutrients were

less in a 40-year-old eucalyptus plantation compared to Juniperusprocera plantation. It

was also lower than in adjacent natural forest (Michelsen et al. 1993). Another study in

Ethiopia showed the reduction of soil organic carbon, N and S after 25 years of

conversion of natural forest into plantations (Solomon et al. 2002). Similar results were

found when native Brazilian forest was converted into eucalyptus plantations (Zinn et al.

2002). However, conversion of natural forest to eucalyptus plantation did not

significantly change soil organic carbon, N, S concentrations and BD in Ethiopia. Loss

of organic carbon, N and S were comparatively higher in sand and silt particles compared

to clay. Clay-associated organic carbon, N and S were more stable (Ashagrie et al. 2005)

due to less leaching. Soil organic carbon is added only to the upper layer (10 cm) in the

initial years of plantation establishment (Tolbert et al. 2002). Areas invaded by exotics

have less litter, thin organic horizons and high pH (Kourtev et al. 1998).

Nitrogen is one of the nutrients that is usually scarce in operational plantations due

to its high demand during tree growth. Supply of N through litter decomposition and









mineralization vary in plantations of the same species and depend on clones (Singh

1998). Nitrogen is available in plants in organic form and is not released until organic

matter is decomposed through biological processes. Use of legumes can help overcome

N deficiency and supply organic matter in plantations (Agus et al. 2004). However, the

rate of N supply depends on the legume species (Corbeels et al. 2003). Leaves always

constitute largest fraction of litter than bark and small branches, and have higher

concentration of macronutrients (Shammas et al. 2003). Both litterfall and its

decomposition rates are higher in primary forests than in plantations, with the highest

levels of N in primary forests (Martius et al. 2004). Soil disturbance increases available

N, encouraging the growth of nitrogen loving annual exotics. These, in turn, increase

available soil N through breakdown of dead plant material (Prober and Thiele 2005).

Soil in cogongrass-dominated sites is generally less fertile. Decomposition rates of

cogongrass leaf litter are very slow and N content in the leaf is low. Cogongrass leaf

litter also immobilizes N (Hartemink and O'Sullivan 2001). Soil in

cogongrass-dominated areas is generally low in available P and N. It is possible to

reclaim such sites for food and tree crops using legume cover crops to enhance soil

fertility (Santoso et al. 1996).

Using trees in restoration of degraded sites to improve soil quality may change both

chemical and physical properties of soil. However, some properties might be limiting

depending on the type of species used. Cottonwood planted in agricultural land in

Mississippi has been effective in reducing penetration resistance, infiltration and BD

(Tolbert et al. 2002). Among 20 native trees used in restoration of degraded lands in









Brazil, only four species had more positive effects on soil properties (Montagnini et al.

1995). As trees grow and develop root system, these effects become more pronounced.

Fast-growing eucalyptus and cottonwood are preferred for reclamation of degraded

sites such as cogongrass-dominated areas. In India, cottonwood was superior to

eucalyptus in amending soil. Cottonwood produced more litter than eucalyptus every

year. Cottonwood litter contained comparatively more N, P and K than eucalyptus litter

(Singh et al. 1989). Another study on three clones of cottonwood showed that nutrient

concentration was higher in leaf tissue compared to woody tissue. However, nutrient

addition to soil from leaf decomposition was less than the leaf tissue content due to

retranslocation. Leaf litter quality, its decomposition and nutrient release differ in

different clones, even in the same species (Singh 1998). Litterfall in eucalyptus can be

increased by 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).

Monoculture eucalyptus has been criticized throughout the world due to its

antisocial nature (Kohli 1987). Allelopathy in eucalyptus affects composition and

structure of plantation understories (Molina et al. 1991). Eucalyptus releases both

volatile and nonvolatile allelochemicals that are added to soil regularly. These chemicals

are rich in soil beneath the canopy (Kohli 1998), but soil neutralizes/dilutes these

allelochemicals with increasing depth (Molina et al. 1991). A study in Spain showed that

allelopathy is due mainly from leaf litter rather than aerial leachates (Molina et al. 1991).

Allelopathy has also been observed in cottonwood in India. Leaves and litter of

cottonwood are rich in phytotoxic phenols, which reduce the germination and growth of

some winter crops (Singh et al. 2001). Species diversity, species richness and evenness









in cottonwood were less compared to Albizzia lebbeck and Dalbergia sissoo plantations

in north India (Kohli et al. 1996).

Less understory vegetation was observed in monoculture eucalyptus plantations

than in plantations of other species in India (Singh et al. 1993). It also did not provide

shelter and food for native fauna (Couto and Betters 1995). However, a study in a

E. grandis plantation in southeastern Brazil found almost an equal number of species as

in natural forest, indicating that eucalyptus did not show any allelopathic effect in that

situation (da Silva et al. 1995). In addition, native eucalypt species provided shelter and

food for animals in Australia (Strauss 2001). However, richness of ground-dwelling and

arboreal fauna differed among eucalypt species in another study in southeastern Australia

(Cork and Catling 1996). Well managed eucalypt species thus can be an effective tool to

restore degraded sites and to control invasive light dependent species like cogongrass,

thereby providing suitable habitat for some native flora and fauna.














CHAPTER 3
METHODS

Study Area

This study began in summer of 2004 at Kent site (28000.99798'N and

81052.13770'W) near Lakeland in Polk County in central Florida (Figure 3-1). Kent is

bordered by natural vegetation towards the east, west and north, with Saddle Creek in the

east. It is a 50 ha CSA where phosphate was last mined in the 1940s. Prior to 2000, the

site was dominated by cogongrass up to 2 m (6 ft) tall and had a history of catastrophic

wildfires that destroyed the little natural vegetation in the area. Soil was highly compact,

100% heavy clay with pH of about 8.0, deficient in N and contained a negligible amount

of organic matter (CPI 2003). The climate is semitropical. Total annual rainfall recorded

at Lakeland Linder Regional Airport was 1653.2 mm (66.1 in) in 2004. Rainfall occurred

regularly through the year with more than 70% of the precipitation falling between June

and September. Average monthly temperature ranged from 15.5C (59.9F) in January to

27.80C (82. 1F) in both July and August.

Roundup ProT, a widely used herbicide, was applied at the site to control

above-ground cogongrass. Soil was then double disked to disturb under-ground rhizomes

and was bedded. Native species such as cypress, cottonwood, slash pine and two species

of noninvasive eucalyptus (E. grandis and E. amplifolia) were planted beginning in year

2000 (Figure 3-1). Plantings included a separate operational area, a clone-configuration-

fertilizer study (SRWC-90), a cottonwood clonal nursery and a demonstration site.

However, this study focused only on the operational area and SRWC-90.













Kent site Studles
nd Operational Areas


Legend
N
Studies:
SSRWC-87 W E
SRWC-94 s
Cottonwood Clone Bank
Cypress SRWC-88
I-- ',. i.I

Operational Areas:

Ee



I '" -a, T r M,1

I III


Figure 3-1. Map of study area.









The operational area was located in the eastern side. Two species of eucalyptus

and cottonwood were planted at different dates and densities (Table 3-1): E. grandis in

single row/bed (Single-EG), double row/bed (Double-EG), quadruple row/bed

(Quadruple-EG) and cottonwood in double row/bed (Double-PD). Trees in the

operational area, except Quadruple-EG, were planted on beds spaced 3.5 m (11 ft)

centers. Spacing between trees on a bed was 0.9 m (3 ft). Four rows of trees were

planted on beds spaced 7 m (23 ft) centers in the Quadruple-EG culture.

Table 3-1. Operational area: description, number of 15 x 15 m study plots, and
associated average tree height (m), DBH (cm), density (trees/ha), basal area
(m2/ha) and quadratic diameter (cm).
Description Culture
Single-EG Double-EG Quadruple-EG Double-PD
Planting date Jun. 2001 Jul. 2001 Jun. 2002 Feb. 2002
Planting density (trees/ha) 4,836 9,773 7,487 9,773
No. of plots 7 5 4 8
Height (m) 14.6a 11.5b 8.8c 7.0d
(0.9) (1.8) (0.6) (0.7)
DBH (cm) 12.0a 8.6b 7.0c 4.9d
(0.9) (1.4) (0.7) (0.3)
Density (trees/ha) 814b 886b 1747b 3175a
(248) (344) (231) (950)
Total basal area (m2/ha) 13.4a 8.1a 11.0a 9.0a
(4.3) (2.5) (0.6) (3.3)
Quadratic diameter (cm) 14.4a 10.9b 9.0c 6.0d
(0.8) (1.7) (0.7) (0.4)
Standard deviations in parentheses; Means in the same row with same letter are not
significantly different at 5% level.

Cottonwood, E. grandis, and E. amplifolia, each represented by five or six

genotypes, were planted in SRWC-90 in two planting configurations (single or double

row/bed) with two fertilizer treatments (0 or 100 pounds ammonium nitrate per acre) in a

split-plot design (Table 3-2). Initial planting was done in March 2001, and the fertilizer

was applied in June 2002. Spacings between the beds and trees were similar to respective









cultures in the operational areas. However, a large gap measuring 7.1 m wide existed

between each treatment in SRWC-90.

Table 3-2. Clone-configuration-fertilizer study (SRWC-90): description and number of
8 x 5 m study plots.
Description Treat. 1 Treat. 2 Treat. 3 Treat. 4 Treat. 5
Culture Single Double Single Double Double
Fertilizer* 0 0 1 1 0
Planting density
(trees/ha) 4,836 9,773 4,836 9,773 9,773
No. of plots 4 4 4 8 8
Planted in March 2001; *0 unfertilized, 1 fertilized; 4Equal number of plots in E.
grandis and E. amplifolia subplots

Experimental Design

Four stands were selected in the operational area based on species culture, i.e.,

Single-EG, Double-EG, Quadruple-EG and Double-PD stand. A representative bed in

each stand was identified and a series of 15 x 15 m plots were systematically established

along the row at 35 m intervals, with the representative bed in the middle of the plot

(Table 3-1, Figure 3-2). The distance to the first plot was 50 m from the stand edge. Five

beds and four interbed spaces were inside each plot in Single-EG and Double-EG

cultures, whereas only three beds and two interbed spaces were inside Quadruple-EG

culture. Understory shrubs/subshrubs and herbaceous species within the plots were

quantified using 1 x 4 m and 1 x 1 m quadrats, respectively.

In SRWC-90, 8 x 5 m plots were established taking E. grandis and E. amplifolia

subplots as individual plots (Table 3-2, Figure 3-2). Only four plots, two each in E.

grandis and E. amplifolia were taken in Treatments 1 through 3, as cogongrass was

dominant and native vegetations were minimal. In Treatments 4 and 5, where the trees

were dominant, plots were established in all eight subplots of both the eucalyptus species.










Cottonwood subplots were not included in this study. Since each treatment had four

beds, the middle interbed space was taken as the middle of the subplots to exclude a

border row on either side of the plot. There were only two beds and three interbed spaces

in each plot. Understory shrub/subshrub and herbaceous species were quantified using

1 x 4 m and 1 x 1 m quadrats, respectively.


Single-EG and Double-EG













Double-PD


Quadruple-EG






SRWC-90

I I Bed
0 Soil sample
E 1Im2 quadrat
I 4m2 quadrat


Figure 3-2. Sampling schemes used for collecting herbaceous and shrub/subshrub data in
15 x15 and 8 x 5 m plots.

Data Collection

Height and DBH of all trees within the plots were measured. Trees in the

operational area were measured in August 2004 and those in SRWC-90 in January 2005.

Vegetation sampling in the operational area and SRWC-90 was done in August 2004 and

April 2005, respectively. Heights were measured using Haglof Vertex III Hypsometer









(Haglof Inc., Sweden). Herbaceous and shrub/subshrub vegetation cover by species was

measured using foliar ocular observation in 1 x 1 m and 1 x 4 m quadrats, respectively.

Modified Daubenmire scale (trace, 1 to 5%, 6 to 10%, 11 tol5%, 16 to 26%, 27 to 49%,

50 to 80%, 81 to 95% or 96 to 100%) was used to quantify cover (Daubenmire 1959).

Both understory herbs and shrubs/subshrubs were quantified separately for bed and

interbed positions. Since all hardwood species present were in sapling stage, they were

all included in the shrubs/shrubs. The number of individual trees inside each 15 x 15 m

and 8 x 5 m plots was counted while herbs and shrub/subshrub were counted in 1 x 1 m

and 1 x 4 m quadrats, respectively. Only the species rooted inside the quadrat were

included. Individual shoots or stems were counted in case of rhizomatous and

stoloniferous plants. The whole clump was counted as an individual in case of plants

growing in clumps. The canopy of each species was included in the cover estimates

regardless of any overlap with other species. Canopy extending over the quadrat was

also included in cover estimation, even if the plants were not rooted in the quadrat.

Six bed and six interbed quadrats, both for herbaceous and shrub/subshrub species,

were taken in each plot in three cultures of eucalyptus in the operational area, while only

four bed and four interbed quadrats were taken in the cottonwood stand. In SRWC-90,

two bed and three interbed quadrats each for herbaceous and shrub/subshrub vegetation

were taken (Figure 3-2). Since canopy cover could not be measured for the trees due to

hurricane damage on the stand, tree basal area was used instead of canopy cover for

correlation. Estimated cover of herbaceous and shrub/subshrub species was used to

calculate percent cover and species composition.









Soil cores (15 cm deep) were taken in the middle of each herbaceous quadrat in the

operational area using a soil corer (10 cm diameter). Due to small plot size, only a bed

and an interbed samples were taken in the middle of the SRWC-90 plots. Samples were

air dried, ground and sieved with a 2 mm screen. All bed and interbed samples from the

same plot in the operational area were mixed, homogenized and composite separately to

prepare a bed and an interbed sample per plot. The samples were tested for SOM, N,

macronutrients (Ca, Mg, P, K) and pH at the Analytical Research Lab at the University of

Florida. Soil organic matter was determined using the loss-on-ignition method and total

N by Kjeldahl Method. Metals were extracted using Mehlich 3 solution.

Since the Kjeldahl Method could not be used in SRWC-90 samples because of high

carbonate content, total N was estimated using NCS 2500 Elemental Analyzer (CE

Instruments, Milan, Italy) using Dumas combustion. Samples were combusted yielding a

gas mixture in which N was detected by a thermoconductivity detector. A large volume

of water was used to extract nutrients in SRWC-90 soil samples as Mehlich 3 could not

be used because of high carbonate content.

Data Analysis

Means of tree and soil parameters were tested using Tukey's multiple comparison

procedure. Percent coverage, frequency and species composition were calculated

separately for individual herbs and shrub/subshrub using the Daubenmaire (1959) scale

estimates. All three variables were analyzed separately using SAS (Version 8.2) with

cultures and position as two main factors and plots nested within cultures generalized

linear model (PROC GLM) in Equation 3-1.









yijk = I + ai + R7ik + Pj + (ap)ij + ijk (3-1)
i=1,2,3,4; j =1,2; k= 1,2,...,n
ai = effect of ith culture
7ik = effect of plot k nested within the ith culture
Pj = effect ofjth position
(ap)ij = effect of interaction between culture and position
Sijk = experimental error

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

for each species culture in the operational area using the formulae:

S
H'= pi In pi (3-2)
1=i
where H'= diversity index, s = number of species, pi = proportion of total sample
belonging to ith species;
H'max = LogS (3-3)
J = (3-4)
H' max
where H'max = maximum possible diversity, S = No. of species, J = Relative
diversity

The same was calculated for each species subplot in SRWC-90. The Jaccard index

(Jaccard 1912) was calculated to see community similarity between different species

cultures using the formulae:


Cj = (3-5)
a+b-j
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.

Importance Value Index (IVI), the function of cover, density and frequency, was

calculated for each species as the sum of relative cover, relative density and relative

frequency. Therefore, the value of IVI ranged from 0 to 300.

IVI = Relative cover + Relative frequency + Relative density (3-6)

Relative cover
= [(Total cover of one species)/
(Total cover of all species)] x 100






28


Relative frequency
= [(Frequency of one species)/
(Total frequency of all species)] x 100

Relative density
= [(No. of individuals of one species)/
(Total number of individuals of all species)] x 100

Correlation analyses between IVI of the five species with the highest IVI in each

culture with stand basal area were done to find the relationship between tree dominance

and the vegetation parameter at a 5% significance level.














CHAPTER 4
RESULTS AND DISCUSSION

Tree Size and Survival

Average tree height differed significantly among cultures (p < 0.0001), ranging

from 7.0 m for Double-PD to 14.6 m for Single-EG in the operational area (Table 3-1).

Similarly, DBH differed significantly among cultures (p < 0.0001), as Single-EG was the

greatest while that of Double-PD was the smallest.

Single-EG had the lowest tree density (Table 3-1). Though the planting density of

Double-EG was the highest (9773 trees/ha) among three eucalyptus cultures, their

densities in August 2004, were not significantly different. Density of Double-PD was the

highest and was significantly different from the three eucalyptus cultures.

Single-EG had the highest average total basal area (13.4 m2/ha); the smallest was

for Double-EG. However, average total basal area was not significantly different among

the different cultures of eucalyptus and cottonwood. The high total basal area in

Single-EG was due to larger diameter trees. Higher total basal area in Quadruple-EG and

Double-PD compared to Double-EG, however, was due to the higher stand density rather

than tree diameter. Quadratic diameter was the largest for Single-EG, while it was the

smallest for Double-PD. It was significantly different between different cultures of

eucalyptus and cottonwood (p < 0.0001).

Growth rate of eucalyptus was comparatively greater than that of cottonwood.

Eucalyptus grandis grew up to 6.7 m in 2.5 years whereas cottonwood grew up to 1.3 m,

when planted in single row (CPI 2003), with an average annual yield of 36.1 Mg/ha and









19.9 Mg/ha for E. grandis and cottonwood, respectively (Stricker et al. 2000). Except in

Single-EG, both DBH and total basal area in two other cultures are within the range of

3-year-old E. grandis plantation in Australia treated with different effluent rates (Myers

et al. 1996). Early planting of Single-EG and Double-EG contributed to larger height and

DBH. Both were planted a year earlier than Quadruple-EG and about 8 months earlier

than Double-PD (Table 3-1). Though Single-EG and Double-EG were planted about a

month apart, Single-EG had significantly greater height than Double-EG. Frequent

occurrence of cogongrass in Single-EG had less effect on growth. In spite of later

planting date and higher planting density, height of Quadruple-EG was greater than that

of Double-PD by 1.8 m. The difference in the height can be attributed to the fast growth

rate of E. grandis.

Tree mortality was high in the operational area. Average survival in Single-EG

was about 16% and in Double-EG was about 9%. Only 3 rows of trees were present in

most Quadruple-EG plots. The survival was 23% in Quadruple-EG, while it was 32% in

Double-PD. Low survival in all the stands might be due to the adverse edaphic

conditions such as limited nutrients, low SOM, drought and periodic stand ponding.

Rainfall in the area was below normal for three months following planting beginning

October through December 2001. Total rainfall recorded at Lakeland Linder Airport was

17.8, 13.5 and 31.2 mm for October, November and December, respectively. Total

rainfall of 241.2 and 341.7 mm for August and September, however, were above normal.

Though clay soils retain more moisture, its surface loses water quickly during summer

and creates air pockets around the root mass. This creates severe stress to newly planted

seedlings. Planting followed by packing/closing planting holes has proven to be essential









for seedling survival. Though these factors were taken into consideration during

planting, they might have played significant role in the death of seedlings at the study

site. Replanting was not done in the operational area.

In SRWC-90, Treatment 4 had the largest E. grandis and E. amplifolia trees with

average height of 11.4 and 10.4 m, and DBH of 7.8 and 7.6 cm, respectively (Table 4-1).

Eucalyptus grandis was shortest (7.3 m) in Treatment 2 and E. amplifolia in Treatment 1

(5.2 m). Eucalyptus grandis was taller than E. amplifolia except in Treatment 3. Stand

density was well maintained in SRWC-90. Dead seedlings were replaced within a few

months after the initial planting. Density for E. grandis ranged from 3800 trees/ha in

Treatment 3 to 8542 trees/ha in Treatment 2. Similarly, Treatment 2 had the highest

E. amplifolia density (8958 trees/ha).

Total basal area for E. amplifolia ranged from 8.5 m2/ha in Treatment 1 to 46.7

m2/ha in Treatment 4. For E. grandis, it ranged from 14.6 m2/ha in Treatment 3 to 32.9

m2/ha in Treatment 4. Calculated quadratic diameter was the highest (8.7 cm) for

E. grandis in Treatment 4, while it was the lowest (4.6 cm) for E. amplifolia in Treatment

2.

Treatments 3, 4 and 5 had larger trees (height and DBH) compared to the same

species and culture in Treatments 1 and 2, except that of E. grandis in Treatment 1,

which was greater than that in Treatment 3 (Table 4-1). Ammonium nitrate applied to

both Treatments 3 and 4 a year after planting had a positive effect in tree responses.

Eucalyptus grandis leaf area, volume and biomass accumulation were comparatively

higher for higher effluent treatment rates in Australia (Myers et al. 1996).










Table 4-1. Clone-configuration-fertilizer study (SRWC-90): average 3.75-year-old tree height (m), DBH (cm), density (trees/ha),
basal area (m2/ha) and quadratic diameter (cm) by treatment and species.
Treatment*
Response 1 2 3 4 5
EG EA EG EA EG EA EG EA EG EA
(n =2) (n =2) (n = 2) (n = 2) (n = 4) (n = 4) (n = 4) (n = 4) (n = 4) (n = 4)


Height


DBH

Density

Total basal area

Quadratic diameter


8.8ad
(2.5)
6.6ab
(2.7)
4200bc
(848)
16.7b
(10.2)
7.1 ab
(2.9)


5.2cd
(1.3)
4.6 b
(0.9)
4200b
(282)
8.5b
(2.2)
5.1b
(0.5)


7.3 bed
(1.1)
4.3b
(0.7)
8542a
(883)
15.3b
(6.8)
4.78b
(0.8)


6.1bd
(0.5)
4.3b
(0.8)
8958a
(883)
14.6b
(2.3)
4.6b
(0.6)


7.6b
(1.4)
5.7ab
(0.9)
3800bc
(282)
14.6b
(6.3)
6.9ab
(1.3)


8.7ab
(0.7)
7. 1
(0.1)
4600b
(282)
19.4bc
(0.2)
7.3a
(0.2)


11.4
(0.9)
7.8a
(0.3)
5500ab
(1000)
32.9
(5.1)
8.7
(0.4)


10.4
(0.9)
7.6
(0.8)
8700a
(683)
46.7
(12.6)
8.2a
(0.8)


9.8ac
(1.1)
6.3ab
(1.1)
6800"a
(1758)
27.2ab
(1.3)
7.3ab
(1.1)


9.3"c
(0.7)
6.9a
(0.7)
8600a
(692)
37.8ac
(5.1)
7.5a
(0.7)


EG = E. grandis, EA = E. amplifolia; Standard deviation in parentheses; Means in each row with the same letter in same species group
are not significantly different at 5% level; *See Table 3-2 for treatment descriptions.









Regardless of the fertilizer application in Treatment 3, only the height and DBH of

E. amplifolia was significantly different from that ofE. amplifolia in Treatment 1 (Table

4-1). Treatments 1, 2 and 3 were highly dominated by cogongrass, where the IVI value

was as high as 300 (Table 4-16). Treatments 2 and 5 were identical to Treatment 4

except that the latter had the fertilizer treatment (Table 3-2). Tree responses (both

E. grandis and E. amplifolia), except density, in Treatment 4 were significantly different

when compared to Treatment 2. In Treatment 4, the highest average IVI of cogongrass

was 201.7 and was 53.4 in Treatment 5 (Table 4-16). Though tree size in Treatment 4

was comparatively larger, it was not significantly different when compared to Treatment

5. Tree responses in Treatments 4 and 5 suggest that presence of cogongrass hinders tree

growth, regardless of the treatment. Though Treatments 2 and 5 were identical,

Treatment 5 had comparatively higher tree responses.

Soil Characteristics

Average TKN ranged from 0.18% in Quadruple-EG to 0.35% in Double-PD in the

operational area (Table 4-2). The lowest was 0.11% for the interbed space in

Quadruple-EG (Table C-l). Total Kjeldahl nitrogen in Quadruple-EG was significantly

different from other cultures of eucalyptus and cottonwood. Phosphorus was highest in

Double-EG and lowest in Double-PD. It was also the highest in both bed and interbed

positions in Double-EG (Table C-1). Potassium decreased from southeast (Double-EG)

to north (Single-EG) in eucalyptus cultures (Table 4-2, Figure 3-1). However,

concentration of Ca increased in eucalyptus cultures from southeast to north. It decreased

to the lowest concentration of 10448 mg/kg in Double-PD.

Soil organic matter was highest in Double-PD and lowest in Quadruple-EG. It was

highest (6.70%) on the bed in Double-EG and lowest (2.85%) in interbed position in










Quadruple-EG (Table C-1). Average pHs in Single-EG and Quadruple-EG were still

quite high and Double-EG had the lowest (7.3). Bulk density was slightly higher in

subsurface (3 to 6 cm), except in Double-PD.

Table 4-2. Operational area: average total Kjeldahl N [TKN (%)], P (mg/kg), K (mg/kg),
Ca (mg/kg), Mg (mg/kg), SOM (%), pH and BD (gm/cm3).
Culture
Response Single-EG Double-EG Quadruple-EG Double-PD
(n = 4) (n = 4) (n = 4) (n = 4)
TKN 0.29a 0.32a 0.18b 0.35a
(0.03) (0.04) (0.07) (0.05)
P 4098.0a 4209.5a 4126.0a 3777.5a
(197.9) (83.5) (156.2) (794.2)
K 187.4a 234.8a 211.7a 210.5a
(36.7) (52.9) (56.1) (99.8)
Ca 11049.0a 10820.5a 10852.5a 10448.0a
(197.7) (1006.2) (824.5) (1687.94)
Mg 1256.6a 1169.2a 1277.1a 1109.3a
(79.6) (55.1) (86.0) (35.0)
SOM 5.52a 5.65a 3.80b 6.50a
(0.50) (1.60) (1.20) (1.14)
pH 7.8ab 7.3b 7.9a 7.5ab
(0.2) (0.3) (0.3) (0.3)
BD (0 to 3 cm) 0.66a 0.67a 0.66a 0.77a
(0.07) (0.11) (0.22) (0.13)
(3 to 6 cm) 0.71a 0.67b 0.79a 0.71ab
(0.06) (0.12) (0.08) (0.16)
Standard deviation is parentheses; Means in the same row with the same letter are not
significantly different at 5% level.

Soil parameters were variously influenced by cultures, plot locations and positions.

Total Kjeldahl nitrogen was significantly different in plots within cultures (p = 0.0159)

and the interaction between cultures and positions (p = 0.0011) (Table 4-3). Potassium

was significantly different only in plots within culture (p = 0.0072) and between the

positions (p = 0.0017). Magnesium, SOM and pH were significantly different between

the cultures. In addition, SOM was significantly different between positions

(p = 0.0130), pH between cultures and in plots within cultures (p = 0.0451).









Table 4-3. Operational area: significance (* = 5% level) of Culture, Plot (Culture) and
Position mean squares for TKN, P, K, Ca, Mg, SOM, pH and BD.
Response Culture Plot (Culture) Position Culture*Position
TKN 0.04* 2x10-3* 0.01* 0.01*
P 281081.4 198326.4 214462.8 155482.4
K 1654.0 6119.8* 21900.6* 3900.5
Ca 500849.4 969100.3 2569858.5 380760.0
Mg 49132.1* 13867.5 4526.6 3353.9
SOM 10.2* 0.9 7.6* 2.9
pH 0.6* 0.1* 0.01 0.03
BD (0 to 3 cm) 0.02 0.01 10-5 0.1
(3 to 6 cm) 0.02* 0.01 3x10-3 0.01

In SRWC-90, total nitrogen (TN) was slightly higher in all E. amplifolia

treatments, except in 5 (Table 4-4). Total nitrogen ranged from 0.28% in Treatment 3 in

E. grandis to 0.39% in Treatment 4 in E. amplifolia and Treatment 5 in E. grandis.

Phosphorus ranged from 130.3 to 162.5 mg/kg in E. grandis. Postassium was the lowest

(81.9 mg/kg) in Treatment 3 in E. grandis.

Eucalyptus amplifolia had both the highest (Treatment 1) and the lowest

(Treatment 3) Ca, which was more or less similar in E amplifolia and E. grandis.

Magnesium ranged from 494.4 mg/kg in E. grandis (Treatment 2) to 646.4 mg/kg in

E. amplifolia (Treatment 5). Soil organic matter ranged from 7.96% in Treatment 3 to

9.76% in Treatment 2 in E. amplifolia. In E. grandis, SOM ranged from 7.75% in

Treatment 3 to 9.69% in Treatment 5.

In both E. amplifolia and E. grandis, pH was almost neutral, ranging from 6.8 to

7.3 in E. amplifolia and from 6.9 to 7.2 in E. grandis. Subsurface (3 to 6 cm) BD was

slightly higher in E. amplifolia, except in Treatment 5. However, the surface (0 to 3 cm)

BD was slightly higher in E. grandis, except in Treatment 1. None of the average soil

responses were significantly different. However, surface BDs in E. amplifolia were

significantly different between interbed positions (Table C-2).










Table 4-4. Clone-configuration-fertilizer study (SRWC-90) E. grandis and E. amplifolia
plots: average total N [TN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg
(mg/kg), SOM (%), pH and BD (gm/cm3).
Treatment 1* Treatment 2 Treatment 3 Treatment 4 Treatment 5
Respo(n = 2) (n = 2) (n = 2) (n = 4) (n = 4)


E. grandis:
TN


P

K

Ca

Mg

SOM

pH

BD (0 to 3 cm)

(3 to 6 cm)


E. amplifolia:
TN

P

K

Ca

Mg

SOM

pH

BD (0 to 3 cm)

(3 to 6 cm)

Standard deviation


0.29a
(0.07)
146.1a
(34.1)
106.5a
(15.1)
1821.2a
(51.5)
514.4a
(11.1)
8.08a
(1.69)
7.2a
(0.2)
0.71a
(0.11)
0.73a
(0.05)


0.33a
(0.10)
139.6a
(38.3)
108.9a
(23.9)
1832.0a
(172.9)
494.4a
(14.2)
9.27a
(2.96)
7.0a
(0.2)
0.77a
(0.12)
0.74a
(0.13)


0.35a 0.34a
(0.04) (0.08)
141.7a 144.1a
(7.5) (31.0)
88.7a 120.5a
(10.1) (50.6)
1858.0a 1848.2a
(32.1) (69.8)
571.3a 537.5a
(6.0) (32.2)
9.68a 9.76a
(1.49) (2.98)
7.3a 7.2a
(0.2) (0.2)
0.63a 0.64a
(0.07) (0.06)
0.76a 0.70a
(0.07) (0.04)
in parentheses; Means in the


0.28a
(0.08)
162.5a
(34.2)
81.9a
(7.5)
1785.0a
(108.1)
567.9a
(56.2)
7.75a
(2.22)
7.2a
(0.2)
0.77a
(0.08)
0.75a
(0.09)


0.29a
(0.05)
146.1a
(21.2)
99.9a
(9.6)
1641.5a
(4.7)
523.1a
(14.8)
7.96a
(1.91)
6.8a
(0.1)
0.71a
(0.05)
0.72a
(0.07)


0.36a
(0.12)
145.8a
(22.3)
86.66a
(14.4)
1777.6a
(92.3)
603.8a
(48.9)
8.72a
(2.56)
7.1a
(0.3)
0.84a
(0.07)
0.78a
(0.06)


0.39a
(0.08)
131.2a
(22.6)
85.0a
(7.8)
1774.8a
(122.0)
599.1a
(51.0)
9.67a
(1.82)
7.0a
(0.3)
0.82a
(0.08)
0.84a
(0.03)


0.39a
(0.13)
130.3a
(29.0)
101.1a
(23.2)
1801.0a
(182.6)
643.3a
(69.4)
9.69a
(3.12)
6.9a
(0.4)
0.76a
(0.14)
0.74a
(0.05)


0.33a
(0.08)
140.6a
(21.6)
96.0a
(15.7)
1771.6a
(88.6)
646.4a
(79.6)
8.17a
(1.85)
6.9a
(0.3)
0.88a
(0.10)
0.82a
(0.12)


same row with the same letter are not


significantly different at 5% level; *See Table 3-2 for treatment descriptions.









Across species, planting densities and ages, few soil properties were significantly

different in the operational area. Similar results have been observed in different aged

stands (Albert and Barnes 1987; Archer 2003; Gilliam and Turrill 1993). Nitrogen and

pH in both the operational area and SRWC-90 were higher than in sandy and loamy soil

in 0-30-year-old pine stands (Archer 2003). Phosphatic clay is highly fertile and has high

amounts of P, Ca, Mg and K. Application of N is the only requirement for nonlegume

crops (Stricker 2000). Amount of P and Ca in this study was more than 6 and 1.5 times,

respectively, that recorded by Stricker. However, levels of Mg and K were lower. Even

the concentrations of N, Ca, Mg and K in the study area were greater than in the

overburden of reclaimed phosphate-mined areas (Segal et al. 2001). High exchangeable

Ca and Mg and moderate to high exchangeable K have also been observed in cogongrass

grasslands with montmorillonite clay due to the presence of carbonates such as calcite

(CaCO3) and dolomite (Ca(MgCO3)2 feldspar (Ca, K), and mica (Ca, Mg, K) in the

Philippines. Cogongrass grassland soils in the area had less soil organic carbon and N

compared to soils under well-developed woody canopy (Snelder 2001). Due to

mineralization and tree growth, N content and SOM in eucalyptus stand decreased with

age (Loumeto and Bernhard-Reversat 2001).

There was no distinct trend in the difference in nutrient level between the planting

age, planting density and the species in the operational area, except that the concentration

of P decreased from Double-EG to Double-PD (Table 4-2). In SRWC-90, there was no

significant difference in nutrients between fertilized and nonfertilized treatments (Table

4-4). In E. grandis, concentration of Mg increased considerably from Treatment 2 to 5.









Other nutrients (P, K, Ca and Mg) in SRWC-90, however, were far less than in the

operational area.

Different extracting solutions were used for the operational area and SRWC-90: the

widely used Mehlich 3 for the operational area and water for SRWC-90 due to high

carbonate content. Each medium extracts nutrients at different levels. Mehlich 3 is

superior to others in extracting nutrients. Mehlich 3 extracts more K compared to water

(Woods et al. 2005). Mehlich 3 extracts 6 to 8% more Mg and 28% more Ca than

ammonium acetate (Mehlich 1984). It also extracts more P than Olsen method and 2 to 3

times more Ca and Mg than ammonium chloride (Monterroso et al. 1999). Presence of

CaCO3 in calcareous soil also reduces the amount of soluble P (Torbert et al. 2002),

which can reduce the amount in water extraction.

The northern section of the study area seems to have lower nutrient concentrations.

Concentration of nutrients recorded in study SRWC-89 (near SRWC-90) was less

(P = 1028.9, K = 175.1, Ca = 4663 and Mg = 1001.3 mg/kg) (Morse 2003) than in the

operational area, but higher than in SRWC-90. The northern section has comparatively

lower elevation. Parts of the northern section remain under water most of the year which

may lead to nutrient leaching.

Soil organic matter in the operational area was almost similar to that of mineral

soil, with the highest of 6.50% in Double-PD (Table 4-2). Single-EG and Double-EG

also had higher SOM than Quadruple-EG. In SRWC-90, SOM was higher in all

treatments than in mineral soil. However, both the operational area and SRWC-90 had

lower SOM than SRWC-89 (Morse 2003). Earlier study done in the area showed that

SOM under E. grandis stand was 215% higher compared to soil in cogongrass-dominated









area (Wullschleger et al. 2004). Soil organic matter in this study was more than 130% in

all the cultures when compared to Wullschleger et al. Leaf litter is the main source of

SOM. Litterfall was generally lower in eucalyptus compared to N-fixing species

(Parrotta 1999) and increased with the age of the plantation (Jaiyeoba 1998). Compared

to 6-year-old first rotation, a 13-year-old coppice stand (6 years of coppice) had higher

leaf litterfall (Bernhard-Reversat et al. 2001). In another study, litterfall and litter

accumulation however, were greater in first rotation eucalyptus than in coppice (Loumeto

and Bernhard-Reversat 2001). However, litter decomposition rate was slower in tropical

eucalypt and pine plantations (O'Connell and Sankaran 1997).

Though pH in the operational area was higher, pH in SRWC-90 was similar to

SRWC-89 (Morse 2003). Soil pH depends on the presence of SOM. Accumulation of

SOM acidifies soil and forms soluble complexes with nutrients such as Ca and Mg,

leading to their loss through leaching (Brady and Weil 2001). This partly explains lower

nutrient concentration and pH value in northern section of the study area. Compared to

pH (8 to 8.2) recorded before trees were planted in the area, pH recorded in this study

support the hypothesis that pH decreased as trees increased in size.

Bulk density is related to soil texture and SOM content. However, BD in this study

was far less than that of mineral soil. In SRWC-90, BD of surface (0 to 3 cm) soil

increased slightly from Treatment 1 to 5, while there was no specific trend in the

operational area. Due to the expanding and shrinking nature of clay soil (Brady and Weil

2001), large cracks develop on the surface during dry periods. Large volumes of water

enter these cracks in the beginning of a wet period. When the soil is saturated, the cracks

are closed due to swelling. Because of this characteristic, BD of montmorillonite clay









soil undergoes periodic changes with the amount of water available. The expansion of

the clay may be the reason behind the low BD in the study area. Effect of tree on the BD

couldn't be verified due to unstable nature of clay.

Plant nutrients and organic matter are lost in surface runoff. Alternate contraction

and swelling of clay, however, prevents the loss to some extent and helps in translocation

of organic matter in clay soil. This compensates for the movement of organic matter in

the soil which is usually retarded due to decreased infiltration after the soil is saturated

(Snelder 2001). During the dry season, litter enters these cracks. In the beginning of the

wet season, water conveys the surface organic matter through cracks. Both organic

matter and litter are trapped in the soil profile after the expansion of clay. Distinct signs

of organic matter trapped along the cracks could be seen in the soil. Without this

property of clay soil, translocation of organic matter in the lower soil profile in CSAs

would otherwise be impossible.

Due to plantation age and limited translocation of organic matter in the soil profile,

organic matter was mostly confined to the top 15 cm of the soil in the study area. In

some instances, organic matter was limited to depth less than that, with only the clay

content below it. This corresponds with the observation made in the Philippines where

organic matter was distinct only in the surface soil in cogongrass grasslands and

decreased rapidly with depth (Snelder 2001). Similar observations were made in the

initial years of bioenergy crop production in areas converted from traditional agriculture

where organic matter was confined to only the top 10 cm of soil (Tolbert et al. 2002).









Vegetation Characteristics


Species Richness

A total of 57 herbaceous species belonging to 23 families were recorded from the

study area (Table A-i). Out of these 57, 40 (-70%) were native and eight (-14%) were

introduced. Eight species were not identified, and the nativity of Carex sp. could not be

identified at the species level.

A total of 54 species belonging to 23 families were recorded from the operational

area: 33, 35, 26 and 27 for Single-EG, Double-EG, Quadruple-EG and Double-PD,

respectively (Table 4-5). Double-EG had the highest (25) number of native species.

Table 4-5. Number of herbaceous and shrub/subshrub species in the operational area and
their nativity
Nativity Single-EG Double-EG Quadruple-EG Double-PD
Herbaceous:
Native 25 25 20 22
Introduced 4 4 3 4
Unidentified 4 6 3 1
Total 33 35 26 27

Shrub/subshrub:
Native 7 17 6 7
Introduced 4 3 2 2
Unidentified 0 3 0 0
Total 11 23 8 9

Among identified species in the operational area, Stylismapatens, Typha latifolia,

Desmodium trifolium, Chamaesyce hypericifolia, Panicum repens, Verbena scabra,

Colloinsonia serotina, Krigia virginica, Calystegia sepium, Cucumis melo and Erechtites

hieraciifolia were infrequent and occurred only once in 256 quadrats. Native species

such as C. virginiana, B. alba, C. diffusa, P. americana, T. kunthii, A. americana and

A. artemisiifolia were common. Apart from I. cylindrica, introduced species such as

Cynodon dactylon and Lygodiumjaponicum occurred frequently.









Of 54 herbaceous species in the operational area, 34 were significantly different

(p < 0.05) in at least one category (percent cover, frequency and species composition)

between cultures, plots within cultures, between positions and the interaction between

cultures and positions (Table 4-6 and Table F-l). Percent cover of native species such as

C. diffusa, T kunthii, P. americana, B. alba, A. americana, A. artemisiifolia and

S. parviflora were significantly different between cultures. However, C. virginiana,

Phyla nodiflora, Andropogon virginicus, Conyza canadensis, P. americana, B. alba,

Eupatorium serotinum, Hydrocotyle umbellata and Melothria pendula were significantly

different among plots within the cultures. Ambrosia artemisiifolia, C. dactylon,

P. americana and Salvia riperia had significantly different percent cover between

positions.

Though percent cover, frequency and species composition of cylindrica were not

significantly different between the cultures, they were, however, significantly different

among plots within cultures (Table 4-6). Its percent cover, frequency and species

composition did not differ significantly between positions.

Frequencies of 17 species were significantly different between cultures, while those

of 21 species were significantly different in plots within the cultures. Frequencies of

C. canadensis, P. americana, Lepidium virginicum and S. riperia were significantly

different between positions (Table F-l). Compositions of only 9, 13 and 4 species were

significantly different between cultures, plots within cultures and positions, respectively.












Table 4-6. Major herbaceous species in the operational area: significance (* = 5% level) of Culture (C), Plot (C) and Position (Pos)
mean squares for cover (%), frequency, and species composition.
Species Cover Frequency Species composition
C P(C) Pos C*Pos C P(C) Pos C*Pos C P(C) Pos C*Pos


Aeschynomene americana
Ambrosia artemisiifolia
Andropogon virginicus
Bidens alba
Clematis virginiana
Commelina diffusa
Conyza canadensis
Cynodon dactylon
Eupatorium capillifolium
Eupatorium serotinum
Hydrocotyle umbellata
Imperata cylindrica
Lepidium virginicum
Lygodiumjaponicum
Lythrum alatum
Macroptilium lathyroides
Melothria pendula
Passiflora incarnata
Phyla nodiflora
Phytolacca americana
Polygonum hydropiperoides
Rhynchosia cinerea
Setaria parviflora


0.9*
9.5*
152.2
288.1*
251.0
48.9*
0.8
177.6
6.7
16.8
0.2
715.8
0.6
3.6*
0.7
5.0
1.8
1.4
9.1
142.9*
0.7
6.9
86.0*


0.1
2.7
78.0*
90.6*
113.0*
11.7
0.5*


0.6
14.4*
26.0
0.02
17.3
22.3
0.3


243.0* 291.0*


4.9
8.2*
0.3*
1440.6*
0.4
0.8
0.5
2.1
2.3*
1.1
9.2*
15.4*
0.4
4.5
22.3


0.2
0.04
0.04
0.10
0.1
0.03
0.3
0.1
0.2
1.0
0.6
62.0*
0.2
6.8
12.4


0.2
7.0
33.4
16.8
19.3
18.1
0.2
94.5
5.2
1.0
0.1
5.5
0.6
0.2
1.1
3.6
0.2
0.6
2.2
18.2*
1.0
6.4
3.9


1457.1*
1054.6
707.2
2224.3*
4060.8*
4920.9*
111.5
1159.5
955.7*
5801.2*
192.8
2062.2
417.9*
1227.2
79.2
5414.3*
33.5
155.2
705.1*
8174.0*
514.5*
469.1*
3383.9*


423.2
400.5*
319.8*
651.3*
1352.6*
1214.9*
52.4*
1439.5*
176.0
819.0*
160.3*
1866.6*
75.1*
439.1
138.3*
498.4*
67.2*
66.7
209.1*
518.0*
136.3
119.4*
497.6*


121.1
365.8
0.6
72.2
292.9
53.0
81.7*
36.7
32.6
122.2
0.4
24.7
71.3*
461.6
28.8
26.4
21.1
8.3
7.7
1534.3*
349.8
31.0
61.2


393.8
588.4*
15.9
126.4
426.6
36.7
31.3
393.4
444.8*
250.6
19.5
51.0
103.1*
123.3
138.7
121.0
7.6
99.6*
7.3
471.0*
387.2
29.3
78.1


8.7
2x10-3*
0.02
0.1*
0.1
0.02*
2x10-4
0.03
2x10-3
0.01
10-4
0.1
10-3
10-3
10-4
3x10-3
2x10-4
2x10-4
2x10-3
0.1*
3x10-4*
2x10-3
0.03*


13.7
3x10-4
0.01*
0.02
0.03*
4x10-3
10-4*
0.04*
10-3
3x10-3*
10-4*
0.2*
3x10-4
2x10-4
10-4
10-3
10-4*
10-4
2x10-3*
0.01
10-4
10-3
0.01


6.8
2x10-3*
2x10-3
10-3
0.02
0.01
10-4
0.1*
3x10-5
5x10-5
10-5
0.02
2x10-4
2x10-5
2x10-5
4x10-5
2x10-5
4x10-5
10-3
0.03*
2x10-4
2x10-3
3x10-3


8.7
10-3*
3x10-3
3x10-3
0.01
0.01
4x10-5
0.02*
10-3
5xl0-4
2x10-5
0.01
4x10-4
10-4
10-4
3x10-3
2x10-5
10-4
10-3
0.01
10-4*
2x10-3
10-3









A total of 26 shrubs/subshrubs (19 native and 4 introduced) belonging to 14

families were recorded from the study area (Table A-2). Nativity of 3 species could not

be determined. All 26 species were also recorded in the operational area. Double-EG

had the highest species richness (23) followed by Single-EG (Table 4-5). Quadruple-EG

and Double-PD had 8 and 9 species, respectively. Number of introduced species was the

highest (4) in Single-EG followed by 3 in Double-EG and 2 each in Quadruple-EG and

Double-PD.

Urena lobata was the dominant and most frequent species with highest percent

cover, frequency and species composition in Single-EG, Double-EG and Quadruple-EG

(Tables E-l, E-2, and E-3). In Double-PD, B. halimifolia had the highest frequency and

species composition. However, percent cover of U. lobata (2%) was slightly higher than

that of B. halimifolia (1.2%) (Table E-4). Species such as Celtis occidentalis, Triadica

sebifera, Toxidendron radicans, Quercus virginiana, Ulmus americana, Rubus argutus,

Lantana camera, Sida rhombifolia and Callicarpa americana were infrequent and

recorded only once from the operational area. Introduced species such as L. peruviana,

Schinus terebinthifolius, Solanum diphyllum and T. sebifera were found in the operational

area.

Percent cover, frequency and species composition of native species such as

U. lobata and Quercus laurifolia were significantly different between cultures (Table

4-7). Percent cover of 8 species, viz., U. lobata, L. peruviana, Sambucus canadensis,

R. argutus, S. diphyllum, L. camera, T. sebifera and B. angustifolia, were significantly

different in plots within cultures. Similarly, frequency and species composition of 9 and

5 species were significantly different in plots within cultures.










Table 4-7. Significant shrubs/subshrubs in the operational area: significance (* = 5% level) of Culture (C), Plot (C) and Position (Pos)
mean squares for cover (%), frequency, and species composition.
Species Cover Frequency Species composition
C P(C) Pos C*Pos C P(C) Pos C*Pos C P(C) Pos C*Pos
Acer rubrum 0.01 0.01 10-' 0.02 456.5 195.4 203.3 31.3 2x103* 10-3 2x10-4 10-3
Baccharis o,,,.-.i, i,.i.'l, 10-3 10-3* 0 0 34.7 54.7* 0 0 10-4 2x10-4* 10-5 10-5
Baccharis halimifolia 5.0* 1.2 1.0 1.7 3824.9* 225.1 434.6 554.7 45.6 53.4 27.4 32.7
Lantana camera 5.8 4.4* 1.7 1.6 66.0 50.0* 7.7 7.3 2x10-3 2x10-3* 10-3 10-3
Ludwigiaperuviana 217.9* 65.9* 7.7 10.2 869.1 1092.7* 1313.3* 225.9 0.2* 0.1* 10-3 0.1
Parthenocissus quinquefolia 0.5* 0.1 0.3 0.2 431.5* 77.6* 6.8 8.7 10-4* 105 104* 4x105*
Quercus laurifolia 0.01* 2x10-3 3x10-3 10-3 320.3* 61.9 106.8 59.1 105* 2x10-6 3\11i 10-6
Rubus argutus 0.6 0.4* 0.02 0.01 183.3 138.9* 7.7 7.3 4x10-4 3x10-4 2x105 2x105
Sambucus canadensis 15.3 9.3* 9.9 7.7* 195.1 236.3* 43.3 15.9 0.02 0.03 0.04 0.01
Solanum diphyllum 180.7* 13.1* 18.4* 21.7* 7110.2* 454.0* 18.3 25.5 0.03* 3x10l3* 10-3 0.01*
Triadica sebifera 0.3 0.4* 0 0 18.7 23.8* 0 0 2x10-4 2x10-4* 3\111i 4\llle
Urena lobata 4438.9* 304.8* 61.3 40.9 8415.3* 1501.5* 0.03 21.8 0.4* 0.1 0.03 0.1









In SRWC-90, 20 herbaceous species belonging to 11 families were recorded (Table

A-1). Out of 20, 15 were native species while the rest were introduced. The highest

number of species (17) was found in Treatment 5, with the lowest both in Treatments 2

and 3. Treatments 2 and 3 did not have any other herbaceous species except cogongrass.

Within SRWC-90, E. amplifolia in Treatment 5 had the highest number of native species

(Table 4-8).

Table 4-8: Number of herbaceous and shrub/subshrub species in SRWC-90 and their
nativity
Nativity Treat. 1* Treat. 2 Treat. 3 Treat. 4 Treat. 5
EG EA EG EA EG EA EG EA EG EA
Herbaceous:
Native 1 0 0 0 0 0 7 4 6 12
Introduced 2 1 1 1 1 1 4 3 5 4
Unidentified 0 0 0 0 0 0 0 0 0 0
Sub Total 3 1 1 1 1 1 11 7 11 16
Total 3 1 1 13 17

Shrub/subshrub:
Native 3 1 0 0 0 0 7 6 10 8
Introduced 0 0 0 0 0 0 0 1 1 1
Unidentified 0 0 0 0 0 0 0 0 0 0
Sub Total 3 1 0 0 0 0 7 7 11 9
Total 4 0 0 9 13
EG E. grandis, EA E. amplifolia; *See Table 3-2 for treatment descriptions

Three species (Medicago lupulina, Verbena brasiliensis and Vicia acutifolia)

recorded in SRWC-90 were not found in the operational area. Introduced species in

SRWC-90 were C. dactylon, I. cylindrica, L. japonicum, M. lupulina and V brasiliensis.

Compared to E. grandis plots, E. amplifolia plots had more species that had

significantly different percent cover and frequency in plots within treatments (Table 4-9).

Even the frequency of six species was significantly different between treatments as

compared to only two in E. grandis.










Table 4-9. Significant herbaceous species in E. grandis and E. amplifolia plots in SRWC-90: significance (* = 5% level) of
Treatment (T), Plot (T) and Position (Pos) mean squares for cover (%), frequency, and species composition.
Species Cover Frequency Species composition
T P (T) Pos T*Pos T P (T) Pos T*Pos T P (T) Pos T*Pos
E. grandis:
Andropogon virginicus 128.7 76.7* 3.7 4.4 3076.6 922.1* 212.7 130.2 0.1* 0.02 0.01 0.01
Bidens alba 101.2 70.4 32.6 46.6 8953.4* 1157.4* 17.4 24.8 0.03* 0.01 0.01 0.01
Clematis virginiana 90.9 82.1 24.4 16.8 4291.9 1647.4* 39.1 1583.6* 0.03 0.02 2x103 10-3
Imperata cylindrica 7552.2* 1618.7* 69.6 8.3 8298.6* 1219.1* 156.3 84.3 0.7 0.2* 10-3 10-3
AMedicago lupulina 0.5 1.3 0.3 0.4 761.4 1473.8* 277.8 136.4 2x10-4 10' 4x10-5 2x10-4
Thelypteris kunthii 0.1 0.1 0.1 0.1 347.2 239.2* 0 49.6 2x10-5 10-5 10-5 10-5
Vicia acutifolia 2.9 2.1 10-4 10-4 4381.2 2326.4* 4.3 6.2 1033 10'* 2x10-5 10-5

E. amplifolia:
Andropogon virginicus 206.1 111.6* 28.3 40.5 4520.1* 1338.8* 39.1 55.8 0.1 0.02* 10-3 2x103
Bidens alba 367.6 146.9* 3.8 5.5 5958.6* 1493.1* 4.3 6.2 0.1 0.1* 10-3 10-3
Cirsium horridulum 0.01 0.01* 0 0 223.2 416.7* 0 0 2.3\11|1" 4\1'e 6x108 9x10 8
Cynodon dactylon 3.1 2.3* 0.2 0.3 2864.6* 640.4* 434.0* 811.0* 10-3 10-3 10-4 10-3
Imperata cylindrica 11291.4* 1697.5* 21.7 28.3 10125.3* 1122.7* 212.7 95.5 1.2* 0.1* 0.01 0.01
Lygodiumjaponicum 0.9* 0.3 0.1 0.1 2922.9* 443.7 351.6 155.0 5x10-4 2x10-4 2x10-4 2x10-4
AMedicago lupulina 0.6 1.0 0.1 0.2 155.0 289.4* 4.3 6.2 2x10-4 10-3 10-4 10-4
Passiflora incarnata 9.2 17.1 5.2 7.4 396.8 740.7* 69.4 99.2 0.02 0.03 0.01 0.01
Vicia acutifolia 0.8 0.4* 0.01 0.01 9303.1* 825.6* 0 17.4 10-3 2x103 10-3 10-3









Percent cover and frequency of cylindrica were significantly different between

treatments and plots within treatments in both E. grandis and E. amplifolia plots. Species

composition was also significantly different in plots within the treatments in both the

species plots. However, its species composition was significantly different between

treatments only in E. amplifolia plots.

Position did not have any significant effect on percent cover, frequency and species

composition of cylindrica in both E. grandis and E. amplifolia plots. Percent cover and

frequency of A. virginicus was significantly different in plots within treatments in both

E. grandis and E. amplifolia. However, species composition was significantly different

only between treatments in E. grandis. Frequency of other native species such as

T. kunthii, V acutifolia and B. alba were significantly different in plots within the

treatment in E. grandis plots.

Thirteen shrubs/subshrubs were recorded in SRWC-90 (Table 4-8). Treatment 5

had the highest (13) species richness. Four and nine species were recorded in Treatments

1 and 4, respectively. More species were recorded in E. grandis than in E. amplifolia, in

Treatments 1 and 5. Treatments 2 and 3 did not have any shrubs/subshrubs. Only one

introduced species, S. terebinthifolius was recorded from SRWC-90.

Urena lobata occurred quite frequently in SRWC-90. It had the highest average

percent cover, frequency and species composition in E. amplifolia plots in Treatments 4

and 5 (Table E-6, E-7), and E. grandis plots in Treatment 4 (Table E-6). It had the

second highest percent cover (3.7%), frequency (60.4) and species composition (0.2) in

E. grandis plots in Treatment 5. Acer rubrum had the highest percent cover (1%),

frequency (50%) and species composition (0.5) in E. grandis plot in Treatment 1 (Table









E-5). Similarly, B. halimifolia had the highest percent cover (7.0%), frequency (62.5%)

and species composition (0.5) in E. grandis plots in Treatment 5 (Table E-7).

Percent cover, frequency and species composition of Ampelopsis arborea were

significantly different in plots within treatment in E. amplifolia (Table 4-10). Similarly,

percent cover, frequency and species composition of B. halimifolia were also

significantly different in plots within treatment. In E. grandis, percent cover and

frequency of R. argutus were significantly different in plots within treatment. Frequency

and species composition of U. lobata were also significantly different in plots within

treatment in E. amplifolia. Only the species composition of A. rubrum was significantly

different in plots within treatment in E. grandis (p < 0.0001).

General characteristics of both disturbed sites and new plantations were obvious in

the study area. Characteristic species of disturbed sites such as B. alba, P. americana,

S. diphyllum, E. capillifolium, E. serotinum and A. artemissiifolia (Taylor 1992) occurred

frequently. Species such as C. diffusa, S. diphyllum, A. artemissiifolia, C. canadensis,

B. halimifolia and S. canadensis are characteristic of moist habitat and new plantations

(Miller and Miller 1999). Clay soils are widely known for retaining more water. The

current study area seems to be suitable habitat for such species due to nutrient rich and

moist soil. Wind and animals play major roles in transporting seeds of these species.

Treatments 1, 2 and 3 in SRWC-90 reflect cogongrass dominated grasslands in

terms of species richness. Native species are hardly present in cogongrass grasslands.

Regeneration of native species is slow or almost prohibited due to fire and intensive

competition, lack of soil seed bank and adverse growing conditions for seedling

establishment (Otsamo 2000b).











Table 4-10. Shrubs/subshrubs in E. grandis and E. amplifolia plots in SRWC-90: significance (* = 5% level) of Treatment (T),
Plot (T) and Position (Pos) mean squares for cover (%), frequency, and species composition.
Species Cover Frequency Species composition


T P(T) Pos T*Pos T P(T) Pos T*Pos T P(T) Pos T*Pos


Acer rubrum 1.0
Ampelopsis arborea 0.02
Baccharis halimifolia 66.8
Parthenocissus quinquefolia 36.6
Quercus laurifolia 0.1
Rubus argutus 0.6
Sambucus canadensis 4.2
Schinus terebinthifolius 5.6
Toxicodendron radicans 0.02
Urena lobata 18.1
Vitis sp. 0.1

E. amplifolia:
Acer rubrum 0.4
Ampelopsis arborea 0.01
Baccharis halimifolia 2.0
Celtis occidentalis 0.5
Parthenocissus quinquefolia 30.0
Quercus laurifolia 0.1
Quercus virginiana 0.02
Sambucus canadensis 0.2
Schinus terebinthifolius 0.7
Urena lobata 943.2
Vitis sp. 3x103


0.6 0.04 0.02 4053.8 1493.1
0.04 0.03 0.02 84.3 231.5
12.8 0.8 4.0 4469.3* 324.1
55.9 40.0 19.5 3875.3 3159.7*
0.1 0.02 0.1 381.9 262.4
1.1* 0.1 0.1 303.8 567.1*
3.8 1.3 2.4 545.6 185.2
8.8 1.04 1.5 892.9 1049.4*
0.04 0.01 0.02 24.8 46.3
13.2 0.7 1.02 4491.6 1381.2*
0.3 0.2 0.1 29.8 92.6


0.7 0.3 0.3 1777.0 922.1
0.01* 10-4 0.001 502.2 451.4*
2.9* 1.2 0.8 1892.4 1597.2*
0.5 0.3 0.5 223.2 169.8
9.7 9.0 12.5 3860.4* 490.0
0.1 0.03 0.04 527.0 304.8
0.04 0.01 0.02 24.8 46.3
0.3 0.1 0.1 155.0 104.2
1.0 0.1 0.2 665.9 706.0
988.7* 20.8 39.4 9113.4* 2480.7*
2x10-3 4x10-3 3x10-3 133.9 69.4


108.5 155.0 0.2 0.1* 2x10-3 10-3
156.3 84.3 10-3 2x10-3 10-3 10-3
1406.3 302.6 0.3* 0.1* 5x10-3 0.01
351.6 155.0 0.02 0.03 0.02 0.01
17.4 441.5 10-3 2x10-3 4x10-4 2x10-3
4.3 6.2 10-3 2x10-3 3x10-4 4x10-4
0 69.4 0.1 0.02 0.01 0.02
0 0 0.01 0.01 0 0
17.4 24.8 10-3 4x10-3 10-3 2x10-3
156.3 116.6 0.2 0.1* 10-4 10-3
69.4 29.8 5x10-5 10-4 10-4 5x10-5


4.3 5.3 10-3 10-3 10-4 2x10-3
4.3 26.4 0.21 0.01* 2x10-5 x10-5
69.4 47.1 0.1 0.1* 4x10-3 4x10-3
156.3 223.2 10-4 10-4 10-4 10-4
734.0 527.0 0.02* 2x10-3 4x10-3 0.01
39.1 28.1 5x10-4 x10-4 2x10-4 3x10-4
17.4 24.8 10-5 3x10-5 10-5 10-5
4.3 6.2 0.03 0.04 0.01 0.02
108.5 398.1 2x10-4 4x10-4 4x10-5 2x10-4
4.3 6.2 0.7 0.2* 4x10-3 2x10-3
156.3 133.9 5x107 3x10-7 6x10-7 5xl0-7









In phosphate mines, cogongrass mostly appears in wetter areas with high clay

content (Segal et al. 2001). Clayey soil and the allelopathic nature of cogongrass further

impact the survival of native species in these grasslands. Low species richness in

cogongrass dominated SRWC-90 treatments is, therefore, not surprising. Cogongrass

litter decomposes very slowly and its allelopathic nature suppresses the growth of native

species. Seedlings that germinate in the cogongrass finally die due to high competition.

Species richness in cogongrass dominated SRWC-90 treatments was similar to that

recorded in other areas. In Indonesia, only four seedling/sapling species were found in

cogongrass grassland as compared to 22 species in riverine forest (Otsamo 2000b). In the

southeastern US, the advancing border of cogongrass had 41 native species (Brewer and

Cralle 2003).

Fast-growing trees can suppress cogongrass, amend soil, add organic matter

through litter and create suitable microclimate for seed germination for shade tolerant

species. Use ofN-fixing species can also increase biological activity in the soil and

supply essential nutrients, such as N, for plant growth. These rapid changes in the

understory and lack of competition with grass make the plantations suitable for native

seed germination and seedling development (Parrotta et al. 1997). Cogongrass might

benefit from the supply of N, because in the southeastern US longleaf pine (P. palustris)

savannah, addition of N-fertilizer made cogongrass leaves comparatively greener.

However, the astonishing finding was that the addition ofP reduced cogongrass clonal

growth and aboveground mass (Brewer and Cralle 2003).

Multiple disking in this study has shown variable results in controlling cogongrass.

All planted sites were treated with herbicide and double disked prior to planting. A small









area between Double-EG and Quadruple-EG was disked thrice and abandoned (Steve

Segrestpers. comm.) without planting trees. However, cogongrass is completely absent

in the area. Similar types of intensive site preparation were done to restore cogongrass

dominated grasslands in Indonesia. Sites were disked twice and harrowed with a

rotavator before planting (Otsamo et al. 1995a). Disking cuts underground rhizomes into

smaller pieces and exposes them to direct sunlight, which ultimately kills the rhizomes.

Rigorous site preparation, weeding (first 2 years) and early canopy closure suppresses

cogongrass, but doesn't necessarily eliminate it (Otsamo 2000b).

Exotic tree species have been used in plantations worldwide due to short-rotation

cycle. With the increasing interest in native species, use of exotic species has been

criticized widely. The issue becomes pronounced in the case of exotic species such as

eucalyptus because of possible allelopathy. It is clear from this study that intensive site

preparation and well maintained eucalyptus are effective in controlling cogongrass. Once

cogongrass is controlled, native species could be introduced into these exotic plantations

after the first rotation (ITTO 1993). However, the species used should have the potential

to amend soil and create suitable environments for native species. Species such as

A. mangium are also capable of improving physical and chemical soil properties,

including microclimatic conditions and biological activity on cogongrass grasslands

(Fisher 1995; Ohta 1990b). Acacia mangium encourages high seedling/sapling density

and species richness, and good stand growth increases native species regeneration

(Otsamo 2000b).

In the Congo, species richness was higher in secondary forest than exotic species

plantations. Within the eucalyptus plantations, species richness was higher in older









plantation (26-years). Disturbance intensity was another factor for higher species

richness. Disturbed sites had more species than undisturbed site. High plantation density

and proximity to natural forest also had positive effects on species richness (Huttel and

Loumeto 2001).

Rather than planting density, stand age and proximity of Double-EG to natural area

in this study had significant effect in species richness. Higher numbers of herbs and

shrubs were found in Double-EG, which was a year older than Quadruple-EG and

Double-PD. Because a larger area of Double-EG is adjacent to the natural area, there is

higher potential for native species to seed into Double-EG. Single-EG was also planted

at the same time with Double-EG. Its distance from the natural area might have slowed

species recruitment rate.

Similarly in Indonesia, 4-year-old A. mangium, Paii%\,ci inn1ihe%\falcataria and

G. arborea stands in cogongrass grasslands had fewer species regenerate (Otsamo

2000b). Even in SRWC-90, treatments with high density planting (Treatments 4 and 5)

both had higher number of herbaceous species and shrubs. Regardless of high density

planting, Treatment 2, however, had only one herbaceous species and no shrub/subshrub,

probably due to the effect of cogongrass.

Type of species planted also affects species recruitment in the stand. Abundant

natural regeneration has been observed in the understory of N-fixing fast-growing species

such as A. mangium and P. falcataria (Kuusipalo et al. 1995; Otsamo 2000b).

Nitrogen-fixing species increase available N in addition to suppressing cogongrass,

whereas the species used in this study only shade cogongrass.









Species Diversity and Community Similarity

Shannon-Wiener diversity indices for herbaceous species were the same for

Single-EG, Double-EG and Double-PD in the operational area (Table 4-11).

Quadruple-EG had the lowest (0.9) diversity index. Double-EG and Double-PD had the

highest (0.5) species diversity for shrub/subshrub, while Single-EG and Quadruple-EG

had equal (0.2) diversity.

Table 4-11. Herbaceous and shrub/subshrub species in the operational area:
Shannon-Wiener diversity index (H'), maximum possible diversity (H'max)
and relative diversity (J).
Variable Vegetation type Single-EG Double-EG Quadruple-EG Double-PD
H' Herbaceous 1.0 1.0 0.9 1.0
Shrub/subshrub 0.2 0.5 0.2 0.5
H'max Herbaceous 1.5 1.6 1.4 1.5
Shrub/subshrub 1.0 1.3 0.9 0.9
J Herbaceous 0.7 0.7 0.6 0.7
Shrub/subshrub 0.2 0.4 0.3 0.5

Double-EG had the maximum possible diversity of 1.6 for herbaceous species. The

lowest was 1.4 in Quadruple-EG. Both Quadruple-EG and Double-PD had the same

(0.9) maximum possible diversity for shrub/subshrub. The highest was 1.3 in

Double-EG. Relative diversity for herbaceous species was the highest (0.7) in

Single-EG, Double-EG and Double-PD, and the lowest (0.6) in Quadruple-EG.

Double-PD had relative diversity of 0.5 for shrub/subshrub species.

In SRWC-90, Treatment 5 had the highest diversity index of 0.9 for herbaceous

species followed by Treatment 4 (0.7) (Table 4-12). Treatment 1 had the highest

diversity index (0.4) for shrub/subshrub species.

Maximum possible diversity was the highest in Treatment 5 for both herbaceous

and shrub/subshrub species. Relative diversity for shrub/subshrub species was the

highest in Treatment 1 and lowest in Treatments 4 and 5.









Table 4-12. Herbaceous and shrub/subshrub species in SRWC-90: Shannon-Wiener
diversity index (H'), maximum possible diversity (H'max) and Relative
diversity (J).
Variable Vegetation type Trt. 1 Trt. 2 Trt. 3 Trt. 4 Trt. 5
H' Herbaceous 0.1 0 0 0.7 0.9
Shrub/subshrub 0.4 0 0 0.2 0.3
H'max Herbaceous 0.6 0 0 1.2 1.3
Shrub/subshrub 0.5 0 0 0.9 1.0
J Herbaceous 0.2 0 0 0.6 0.7
Shrub/subshrub 0.9 0 0 0.3 0.3

Results of species diversity in this study partly support the second hypothesis.

Rather than just the stand age, stand density and planted species appears to have

influenced the diversity in the study area. Though Double-PD was planted a year later,

its diversity was similar to that of Single-EG and Double-EG, which were planted a year

earlier. Disturbance plays a major role in species diversity. Diversity is high in

communities with intermediate levels (intensity) of disturbance (van der Maarel 1993).

Species richness decreases at high or low frequency disturbance either due to extinction

of disturbance intolerant species or elimination by dominant species (Jobidon et al. 2004).

However, herbaceous diversity increased in heavily harvested areas (Elliott and Knoepp

2005).

Marked change in species diversity does not occur in initial stages of succession in

plantations. However, it increases with time and soon reaches the maximum, which can

take place as early as 3 years (Ohtsuka 1999). Tree plantations in degraded areas bring

dramatic improvement in environmental conditions, changing forest microclimate and

soil. Fire is also less frequent in plantations. These ultimately increase the understory

diversity in plantations. Understory biodiversity in eucalyptus plantation is lower

compared to acacia and pine (Bernhard-Reversat and Huttel 2001).









Communities at the study site are less diverse compared to real communities, where

Shannon-Wiener diversity index fall between 1.5 and 3.5. This might be due to young

stand age and the competition of native species with cogongrass. Allelopathy of

eucalyptus also might have affected the species recruitment rate.

Table 4-13. Operational area: Jaccard's community similarity index (Cj) for herbaceous
(H) and shrub/subshrub (S) species.
Culture Double-EG Quadruple-EG Double-PD
H S H S H S
Single-EG H 0.4 -- 0.5 -- 0.5 --
S -- 0.4 -- 0.6 -- 0.6
Double-EG H -- 0.4 -- 0.4 --
S -- -- 0.4 -- 0.3
Quadruple-EG H -- -- 0.5 --
S -- -- -- -- -- 0.6

None of the cultures in the operational area were similar. The highest community

similarity index (0.5) for herbaceous species in the operational area was between

Single-EG and Quadruple-EG, Single-EG and Double-PD, and Quadruple-EG and

Double-PD (Table 4-13). For shrub/subshrub species, it was the highest (0.6) between

Single-EG and Quadruple-EG, Single-EG and Double-PD, and Quadruple-EG and

Double-PD. The lowest similarity was between Double-EG and Double-PD for

shrub/subshrub species.

Though, herbaceous species diversity in Treatments 2 and 3 in SRWC-90 was zero

(Table 4-12), they however showed the highest community similarity (1.0) indicating the

two treatments were similar (Table 4-14). It was followed by Treatments 4 and 5 for

both herbaceous and shrub/subshrub species. Community similarity indices for

herbaceous species between Treatments 2 and 4, 2 and 5, 3 and 4, and 3 and 5 were equal

(0.1), but very low, suggesting minimal similarity between the treatments.









Regardless of species planted, plantations of equal age had the same community in

India (Pande et al. 1988). Different understory species composition in plantations

compared to that of nearby forest has also been observed elsewhere (Bernhard-Reversat

and Huttel 2001), leading to difference in communities.

Table 4-14. Clone-configuration-fertilizer study (SRWC-90): Jaccard's community
similarity index (Ci) for herbaceous (H) and shrub/subshrub (S) species.
Treatment 2 3 4 5
H S H S H S H S
1 H 0.3 -- 0.3 -- 0.3 -- 0.2 --
S -- 0 -- 0 -- 0.4 -- 0.3
2 H -- 1.0 -- 0.1 -- 0.1 --
S -- -- 0 -- 0 -- 0
3 H -- -- 0.1 -- 0.1 --
S -- -- -- 0 -- 0
4 H -- -- -- 0.6 --
S -- -- -- -- 0.6

Importance Value Index (IVI)

In the operational area, average IVI ranged from 0.2 for Eupatorium capillifolium

in Double-PD (Table D-4) to 75.2 for I. cylindrica in Single-EG (Table 4-15) for

herbaceous species. The second highest (74.8) was also for cylindrica in Double-PD

followed by 52.7 for C. dactylon in Double-EG (Table 4-15).

In Single-EG, average IVI ranged from 0.3 for Verbena scabra to 75.2 for

/. cylindrica (Table D-l). Importance value index of Cylindrica ranged from 0 in Plot

1 to 161.7 in Plot 7. Three introduced species, viz., cylindrica, C. dactylon and

L. japonicum, were among the 10 species with highest average IVI. Among native

species, C. virginiana had the highest IVI in Plot 1. However, average IVI was slightly

lower than that of T kunthii (Table 4-15).










Average IVI value ranged from 1.2 to 214.7 for Celtis occidentalis and U. lobata in

Single-EG, respectively. Sambucus canadensis had the second highest IVI (26.1).

Importance value index of introduced species L. peruviana and S. diphyllum were 19.6

and 12.3, respectively.

Table 4-15. Average IVI (> 5.0) of herbaceous and shrub/subshrub species in four
cultures in the operational area.
s s Single-EG Double-EG Quadruple-EG Double-PD
(n = 7) (n = 5) (n = 4) (n = 8)
Herbaceous:


Aeschynomene americana
Ambrosia artemisiifolia
Andropogon virginicus
Aristida purpurascens
Bidens alba
Carex sp.
Clematis virginiana
Commelina diffusa
Cynodon dactylon
Eupatorium capillifolium
Eupatorium serotinum
Imperata cylindrica
Lepidium virginicum
Lygodium japonicum
Macroptilium lathyroides
Phyla nodiflora
Phytolacca americana
Polygonum hydropiperoides
Rhynchosia cinerea
Setaria parviflora
Thelypteris kunthii

Shrub/subshrub:
Acer rubrum
Ampelopsis arborea
Baccharis halimifolia
Lantana camera
Ludwigia peruviana
Quercus laurifolia
Rubus argutus
Sambucus canadensis
Schinus terebinthifolius
Solanum diphyllum
Urena lobata


16.2 (11.5)
1.2 (2.0)
14.1 (21.9)
0
2.3 (3.9)
1.8 (3.1)
29.1 (34.3)
20.6 (8.9)
29.1 (33.6)
4.3 (7.9)
9.3 (5.6)
75.2 (59.9)
0.4 (1.1)
11.1 (6.2)
2.5 (3.8)
4.2(11.1)
22.5 (13.2)
0.6 (1.7)
0
0.7 (1.7)
31.7(21.4)


4.2 (3.7)
2.4 (2.0)
16.6 (11.6)
0
19.6 (13.8)
2.6 (3.0)
0
26.1 (19.8)
3.4 (3.3)
12.3 (6.2)
214.8 (63.9)


2.3 (3.1)
0
2.4 (3.6)
3.9 (8.6)
27.3 (29.7)
8.4 (9.5)
52.6 (28.0)
14.3 (10.0)
52.7 (52.1)
11.0(9.7)
0
48.1 (75.9)
0
3.3 (3.7)
0.4 (0.9)
12.6 (14.7)
4.3 (1.7)
0.4 (0.9)
7.8 (11.4)
0
5.8 (6.8)


3.7 (5.6)
7.8 (7.5)
11.7 (11.7)
7.0 (15.5)
60.6 (59.3)
10.9 (8.6)
9.5 (21.2)
2.2 (4.9)
6.9 (6.8)
7.4 (9.0)
162.4 (77.5)


20.2 (5.6)
10.2 (7.6)
0
0
5.6 (8.7)
0.7 (1.4)
14.4 (7.7)
40.7 (18.2)
50.7 (32.0)
7.2 (4.1)
0
42.1 (84.1)
6.8 (7.4)
1.0 (2.0)
4.8 (8.0)
0
40.4(18.8)
5.4 (6.3)
0
3.6 (4.9)
11.8(14.6)


1.2 (2.4)
4.5 (5.3)
8.2 (7.7)
0
16.8 (19.9)
0
0
9.7 (11.2)
0
47.6 (27.8)
211.8 (14.6)


12.7 (6.2)
2.5 (3.8)
0
13.7 (21.9)
39.5 (21.4)
0
25.0 (34.3)
7.7 (7.9)
32.7 (33.6)
0.2 (1.2)
20.6 (13.2)
74.8 (59.9)
0
5.0(11.1)
18.0 (11.5)
0.8 (5.4)
0.7 (2.0)
0.3 (1.7)
0
19.2 (8.9)
8.6 (5.6)


21.8 (8.8)
2.2 (3.7)
131.7 (36.9)
0
19.9 (5.8)
0
0
8.9 (8.7)
2.0 (6.5)
0
103.6 (24.5)


Standard deviation in parentheses









In Double-EG, C. dactylon ranked first with average IVI of 52.7 (Table 4-15).

Imperata cylindrica was third with average IVI of 48.1. Clematis virginiana was second

with average IVI of 52.6, almost equal to that of C. dactylon. Imperata cylindrica was

absent in Plots 1, 4 and 5. The lowest IVI was for Oxalis corniculata (Table D-2).

Urena lobata had the highest IVI in Double-EG followed by introduced

L. peruviana (Table 4-15). Average IVI of U. lobata was 162.4 and that ofL. peruviana

was 60.6. The lowest IVI was 0.4 for Vitis sp. (Table D-2).

Cynodon dactylon and I. cylindrica were first and second in Quadruple-EG (Table

4-15). Imperata cylindrica was absent in Plots 1, 2 and 3 (Table D-3). Importance value

index of C. diffusa and P. americana were almost equal. At plot level, C. diffusa had the

highest IVI (59.2) in Plot 3 after C. dactylon and I. cylindrica. The lowest IVI (0.4) was

for Ampelaster carolinianus (Table D-3).

Urena lobata had the highest IVI (211.7) with the lowest IVI of 1.1 for Diospyros

virginiana (Table D-3). Introduced species S. diphyllum and L. peruviana had the second

and third highest IVI (Table 4-15). Among other native species, S. canadensis and

B. halimifolia had IVI of 9.7 and 8.2, respectively.

Imperata cylindrica was present in all the plots in Double-PD (Table D-4). It had

the highest average IVI (74.7) followed by B. alba (39.5). The lowest IVI (0.2) was for

E. capillifolium. Importance value index of L cylindrica ranged from 3.3 in Plot 8 to

177.8 in Plot 6.

Double-PD was dominated by B. halimifolia with an IVI of 131.7 (Table D-4).

Urena lobata had the second highest IVI of 103.6. Double-PD is the only culture in the









operational area where native shrub/subshrub species have the three highest IVI values.

Acer rubrum was third with the IVI of 21.8.

In SRWC-90, I. cylindrica was the dominant herbaceous species and had the

highest IVI in all treatments except Treatment 5, in which the IVI was 2.8 in

E. amplifolia (Table 4-16). It had the highest possible IVI in Treatments 2 and 3 in

E. grandis and Treatment 1 in E. amplifolia. Its IVI was almost 300 in Treatments 2 and

3 in E. amplifolia. There were no other herbaceous species in Treatments 2 and 3, both in

E. grandis and E. amplifolia.

Treatment 1 of SRWC-90 had four native shrubs/subshrubs (Table 4-17). Acer

rubrum had the highest average IVI value (127.3). However, its plot level IVI was 254.6

in Plot 1 (Table D-5). Both Treatments 2 and 3 did not have any shrub/subshrub species.

In Treatment 4, 1. cylindrica had the highest IVI both in E. grandis and

E. amplifolia (Table 4-16). Among native species, C. virginiana had the highest average

IVI of 51.3 in E. amplifolia followed by C. virginiana (28.4) in E. grandis. The lowest

average IVI value was 1.1 for P. americana and A. virginicus in E. grandis.

Treatment 4 had only nine shrub/subshrub species with U. lobata highest with IVI

of 146.8 and 114.3 in E. grandis and E. amplifolia, respectively (Table 4-17). Acer

rubrum was second highest in E. amplifolia with IVI 13.7 and S. canadensis in E. grandis

with IVI 41.7. The lowest was for S. terebinthifolius in E. amplifolia.

Imperata cylindrica had the highest IVI in Treatment 5 followed by B. alba in

E. grandis (Table 4-16). In E. amplifolia, B. alba had the highest IVI followed by

V. acutifolia. Imperata cylindrica was present only in Plot 2 in E. grandis and Plots 3

and 4 in E. amplifolia. Its IVI ranged from 3.6 in E. amplifolia to 213.7 in E. grandis.









Lowest average IVI was 0.9 for T kunthii in E. grandis and 0.8 for A. artemisiifolia,

Melothria pendula and Macroptilium kIl- ,,ik le in E. amplifolia (Table D-7).

In Treatment 5, native shrub/subshrub species occupied the first three positions in

both eucalyptus species (Table 4-17). Importance value index of U. lobata was 100.5 in

E. grandis and 195.3 in E. amplifolia. Baccharis halimifolia and A. rubrum had second

and third highest average IVI in E. grandis while B. halimifolia and P. quinquefolia in

E. amplifolia. Quercus virginiana had the lowest IVI (2.0) in E. amplifolia. It was

absent in E. grandis.

At the plot level, E. grandis was better than cottonwood in suppressing cogongrass

in the operational area. Cogongrass was absent in Plot 1 in Single-EG (Table D-l) and

three plots each in Double-EG (Table D-2) and Quadruple-EG (Table D-3). However, it

was present in all eight plots in Double-PD (Table D-4). Stands with good growth and

early canopy closures are necessary for suppressing cogongrass and to enhance secondary

succession. In uneven stands, cogongrass will dominate and will slow the secondary

succession (Otsamo 2000b).

However, the Single-EG does not support the finding. In Single-EG, IVI of

I. cylindrica increased from Plots 2 to 7, except in Plot 5 where its value decreased to

10.8 and then increased again. Imperata cylindrica was absent in Plot 1. Plots 3, 4 and 7

had the highest tree density of 1075, 1003 and 1003 trees/ha, respectively (Table B-l).

Total basal area was also in the highest range within the culture with 15.3 m2/ha, 17.9

m2/ha and 15.4 m2/ha in Plots 3, 4 and 7, respectively. In Plot 1, the density was 681

trees/ha with total basal area of 11.0 m2/ha. Despite low density and basal area,

L cylindrica was well suppressed in Plot 1.










Table 4-16. Average IVI (> 5.0) of herbaceous species in SRWC-90.
Species Treatment 1* Treatment 2 Treatment 3 Treatment 4 Treatment 5
EG(n=2) EA(n=2) EG(n = 2) EA(n = 2) EG(n = 2) EA(n = 2) EG(n = 4) EA(n = 4) EG(n = 4) EA(n = 4)


Andropogon virginicus


Bidens alba


Clematis virginiana

Cynodon dactylon

Eupatorium serotinum

Imperata cylindrica

Lygodium japonicum

Medicago lupulina

Passiflora incarnata

Thelypteris kunthii

Vicia acutifolia


38.5 32.9
0 (23.1) (27.3)
48.0 66.8
0 (24.3) (61.8)


28.4
0 (19.7)
7.2
0 (14.3)
21.0


0
266.7
(47.1)
17.3
(24.4)

0

0
16.0
(22.7)

0


0
300.0
(0.0)


0
300.0
(0.0)


0
296.7
(4.7)


0
300.0
(0.0)


299
(0.


51.3
(37.4)
23.2
(46.4)


0 (26.7) 0
.9 201.7 169.4
1) (98.9) (128.1)
7.3 8.6
0 (9.9) (10.7)


6
0 (12.1

0

0
20
0 (41.'


.4
8) 0
0 20.9
(41.8)
0 5.3
(10.5)
.9 13.0
7) (26.0)


45.2
(29.5)
21.7
(16.4)


0
53.4
(106.8)
5.3
(7.8)
7.9
(10.6)


0.9
(1.9)
41.5
(24.9)


Standard deviation in parentheses; *See Table 3-2 for treatment descriptions


37.0
(21.5)
31.4
(20.9)

0
2.8
(3.6)
16.1
(4.5)
3.5
(7.0)

0
16.7
(20.5)
42.6
(20.1)










Table 4-17. Average IVI (> 5.0) of shrub/subshrub species in SRWC-90
Species Treatment 1* Treatment 2 Treatment 3
EG(n=2) EA(n=2) EG(n =2) EA(n =2) EG(n =2) EA(n
Acer rubrum 127.3
(180.0) 0 0 0 0
Ampelopsis arborea
0 0 0 0 0
Baccharis halimifolia 12.9
(18.3) 0 0 0 0
Celtis occidentalis
0 0 0 0 0
Parthenocissus
quinquefolia 0 0 0 0 0
Quercus laurifolia
0 0 0 0 0
Rubus argutus
0 0 0 0 0
Sambucus canadensis
0 0 0 0 0
Schinus terebinthifolius
0 0 0 0 0
Toxicodendron radicans
0 0 0 0 0
Urena lobata 9.8
(13.9) 0 0 0 0
Vitis sp. 15.1
0 (21.3) 0 0 0
Standard deviation in parentheses; *See Table 3-2 for treatment descriptions


= 2)


Treatment 4
EG(n = 4) EA(n = 4)
13.7
0 (21.7)
6.1
(12.2) 0
18.9 10.6
(22.4) (13.5)

0 0
31.4 3.3
(36.6) (6.5)
7.7 5.8
(9.5) (11.5)

0 0
41.7 2.8
(29.1) (5.6)
2.6
0 (5.1)

0 0
146.8 114.3
(108.0) (132.3)
1.61 0
(3.2)


I


Treatment 5
EG(n = 4) EA(n = 4)
44.3 19.9
(30.7) (5.0)
5.4 7.5
(10.8) (10.8)
94.0 41.8
(49.9) (50.1)
6.0
0 (7.7)
31.0 37.4
(26.9) (18.1)
12.6 11.9
(10.9) (6.4)
7.0
(14.1) 0
4.5
(9.0) 0
17.0 14.3
(24.5) (16.5)
8.6
(17.3) 0
100.5 195.3
(57.8) (45.8)
1.5 0
(2.9)









In Double-EG, I. cylindrica was well controlled in Plots 1, 4 and 5 (Table D-2).

Plot 1 had the highest density (1477 trees/ha) and total basal area (10.6 m2/ha) followed

by Plot 4 (Table B-l). Though Plot 5 had the lowest density (612 trees/ha), its total basal

area (7.9 m2/ha) was higher than that of Plots 2 and 3. Plot 2 had higher density (792

trees/ha), but its total basal area was smaller than that of Plot 3. Importance value index

of cogongrass in Plot 2 (66.8) is less than that of Plot 3 (173.6). Tree dominance

expressed either as basal area or density seems to be effective. A similar conclusion can

be made in the case of Quadruple-EG. Cogongrass was present only in Plot 4 which had

the least density (1430 trees/ha). However, total basal area was slightly greater than that

of Plot 2 and smaller than that of Plot 1 and 3 (Table B-l).

In Double-PD, total basal area decreased considerably from Plot 1 (13.2 m2/ha) to

Plot 6 (6.0 m2/ha) and increased slightly in Plot 7 (6.6 m2/ha) (Table B-1). It however,

decreased again in Plot 8 (5.4 m2/ha). Tree density did not show any particular trend.

However, IVI of cylindrica was considerably lower in plots with higher total basal

area, except in Plot 8. Plot 8 had the lowest IVI (3.3) (Table D-4), whereas it had both

the lowest total basal area and density (2054 trees/ha). Double-PD also had decreasing

L. cylindrica IVI with increasing total basal area.

Both E. grandis and cottonwood suppress cogongrass. Though cottonwood forms

dense canopy as early as E. grandis, its defoliating nature may give cogongrass an

opportunity to come back in the understory. In contrast, E. grandis forms permanent

canopy. Frequent occurrence of cylindrica in Double-PD in the present study was also

largely due to edge effect. There was only a thin strip of cottonwood (5 rows) where the

study plots were established and cogongrass was dominant on either side of the stand.









Due to edge effect, cogongrass advanced in the understory from either side. Though

cogongrass appears on the edges, some areas in the middle part of the stand were free

from cogongrass.

Regardless of above observations, the correlation between total basal area and

cogongrass IVI in three E. grandis cultures in the operational area was not significant

(r = 0.19,p = 0.4587) (Figure 4-1, Table 4-18). This may however, be due to nonlinear

data and small sample size (n = 16). Thelypteris kunthii, C. dactylon, C. virginiana,

P. Americana, B. Alba, C. diffusa and E. capillifolium had negative associations with

cogongrass. The relationship was significant in C. dactylon (r = -0.50, p = 0.0437),

C. virginiana (r = -0.58, p = 0.0187) and C. diffusa (r = -0.50, p = 0.0468). Thelypteris

kunthii had significant positive relationship (r = 0.51, p = 0.0420) and B. alba had

significant negative relationship (r = -0.58, p = 0.0177) with stand basal area.


200
180 -
160 *
5 140
S120 *
T 100 *
0 80



20
0 -----------* --- ***-----------
0.00 5.00 10.00 15.00 20.00
E. grandis TBAH

Figure 4-1. Eucalyptus grandis in the operational area: correlation between total basal
area per hectare and cogongrass IVI.

Urena lobata, S. canadensis, S. diphyllum and A. rubrum were positively correlated

with stand basal area in three E. grandis cultures (Table 4-19). Ludwigiaperuviana,









B. halimifolia, Q. laurifolia and R. argutus had nonsignificant correlations. Urena lobata

and L. peruviana had significant negative correlation (r = -0.72, p = 0.0015).

Regardless of cogongrass presence in all the plots in Double-PD, cogongrass had

nonsignificant correlation with stand basal area (r = -0.21, p = 0.6103) (Figure 4-2, Table

4-18). Thelypteris kunthii, C. dactylon, C. virginiana, B. alba, C. diffusa and

E. capillifolium also had negative correlation with cogongrass. There was a significant

negative correlation between B. halimifolia and L. peruviana in Double-PD (r = -0.71,

p = 0.0488) (Table 4-19). Bidens alba and L. peruviana did not have any correlations

with stand basal area (r = 0,p = 1.000).


300

250

S200

a 150 *



50

50
0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00
Cottonwood TBAH

Figure 4-2. Cottonwood in the operational area: correlation between total basal area per
hectare and cogongrass IVI.

In SRWC-90, IVI for cogongrass was as high as 300 in both E. grandis and

E. amplifolia in Treatments 1, 2 and 3 (Table 4-16). Importance value index decreased

with increasing tree basal area only in the case of E. amplifolia in Treatment 4. It did not

have any distinct pattern in other treatments. However, there was a considerable decrease


ecrease









in average IVI in Treatments 4 and 5 compared to the first three treatments. Treatments 4

and 5 had comparatively higher total basal area (Table 4-1).

One of the main reasons for cogongrass dominance in SRWC-90 was edge effect.

A large gap (7.1 m wide) existed between each treatment, originally designed for

watering the trees. Because of the large gap, cogongrass moved into the stands.

However, cogongrass had significant negative correlation with both E. grandis

(r = -0.91, p < 0.0001) and E. amplifolia (r = -0.73, p = 0.0028) basal area in SRWC-90

(Figures 4-3 and 4-4). It also was negatively correlated with eucalyptus (both operational

and SRWC-90 combined) species in the study area (r = -0.52, p = 0.0004) (Figure 4-5).

Correlation was highly significant in E. grandis (Figure 4-3) compared to

E. amplifolia (Figure 4-4). It was not significant in cottonwood (Figure 4-2). Eucalypts

species are apparently superior to cottonwood in suppressing cogongrass. Among

eucalyptus species, E. grandis seems to perform better than E. amplifolia.

Removing overstory canopy may not have significant effect on cogongrass

regrowth in controlled areas. During soil sampling, cogongrass rhizomes were not

observed where cogongrass was controlled, indicating less chance of reinvasion from the

rhizome. Wind-borne seeds and spread from current patches are the only potential

sources. However, seeds are less likely to germinate if the groundcover remains intact.

In a fast-growing A. mangium plantation in Indonesia, canopy removal to enhance the

growth of underplanted Anisoptera marginata did not result in cogongrass regrowth in

the gaps (Otsamo 1998b). Similar result was found in the gaps created in another A.

mangium plantation in cogongrass grassland (Otsamo 2000a).









Table 4-18. Spearman correlation coefficient (r) of herbaceous species with highest IVI in the operational area


TI


TBAH


3AH

(0.


IC -0.21
(0.6103)
TK -0.21
(0.6103)
CYD 0.23
(0.5702)
CV -0.24
(0.5702)
PA 0.08
(0.8461)
BA 0
(1.000)
CD 0.24
(0.5604)
AA 0
(1.000)
EC 0.58
(0.1340)


IC
).19
4587) (0.

(0.


-0.17
(0.6932)
-0.31
(0.5702)
-0.02
(0.9554)
0.25
(0.5546)
-0.31
(0.4556)
-0.63
(0.0912)
0.07
(0.8665)
-0.08
(0.8461)


TK C
).51
0420) (0.(
0.05 -
8384) (0.(
(0.
(0.


-0.76
(0.0280)
0.45
(0.2604)
-0.58
(0.1340)
0.38
(0.3518
-0.24
(0.5604)
-0.76
(0.0280)
0.41
(0.3100)


YD
0.5
0486) (0.
).50
0437) (0.
).39
1328) (0.

(0.


-0.57
(0.1390)
0.08
(0.8461)
-0.12
(0.7789)
0.27
(0.5204)
0.81
(0.0149)
-0.41
(0.3100)


CV
0.17 0
5382) (0.
0.58 -
0187) (0.
0.26 0
3200) (0.
0.05 -
8540) (0.
(0.
(0.;


0.25
(0.5546
-0.33
(0.4198)
0.24
(0.5604)
-0.33
(0.4198)
-0.57
(0.1340)


PA I
1.44 -
0895) (0.(
0.17 -(
5318) (0.
1.30 -
2478) (0.
0.10 0
7044) (0.
0.30 0
7044) (0.:
(0.
(0.


-0.58
(0.1340)
0.42
(0.2969)
0.41
(0.3100)
-0.14
(0.7358)


3A
).58
0177) (0.
).33
2146) (0.
).31
2342) (0.
.26
3198) (0.
.18
5008) (0.
).19
4781) (0.

(0.


-0.41
(0.3069)
-0.45
(0.2604)
-0.08
(0.8461


CD
0.07 0
8034) (0.
0.50 0
0468) (0.:
0.16 0
5557) (0.
0.22 -
4117) (0.
0.19 -
4778) (0.
0.63 0
0090) (0.
0.26 -
3385) (0.
0
(0.


0.12
(0.7735)
0.08
(0.8423)


AA EC
1.46 -0.27
0694) (0.3098)
1.05 -0.39
8600) (0.1323)
1.38 -0.14
1410) (0.6059)
0.39 0.33
1294) (0.2136)
0.20 0.27
4455) (0.3026)
1.58 -0.36
0183) (0.1746)
0.32 0.12
2270) (0.6646)
1.16 0.06
5614) (0.6646)
-0.24
(0.3624)


-0.41
(0.3100)


Coefficients above the diagonal for combined Single-EG, Double-EG and Quadruple-EG, and below the diagonal for Double-PD;
P-value in parentheses; TBAH: Total basal area per hectare, IC: I. cylindrica, TK: T. kunthii, CYD: C. dactylon, PA: P. americana,
BA: B. alba, CD: C. diffusa, AA: A. americana, EC: E. capillifolium









Table 4-19. Spearman correlation coefficient (r) of shrub/subshrub species with highest IVI in the operational


TBAH


TBAH UL
0.29
(0.2790)


UL -0.05
(0.9108)
SC -0.25
(0.5546)
LP 0
(1.0000)
BH -0.21
(0.6103)
SD

QL

AR 0.05
(0.9103)


-0.41
(0.3100)
0.38
(0.3505)
-0.48
(0.2329)




0.18
(0.9103)


SC
0.27
(0.3020)
-0.43
(0.0972)


-0.28
(0.4963)
0.41
(0.3100)




-0.49
(0.2093)


LP
-0.37
(0.1603)
-0.72
(0.0015)
0.25
(0.3502)


-0.71
(0.0488)




-0.59
(0.1237)


BH
-0.17
(0.5243)
-0.08
(0.7688)
-0.22
(0.4206)
-0.14
(0.6024)


SD
0.21
(0.4306)
0.35
(0.1808)
-0.18
(0.5099)
-0.54
(0.0300)
0.003
(0.9909)


QL
-0.25
(0.3463)
0.14
(0.6050)
-0.17
(0.5284)
-0.26
(0.3248)
0.38
(0.1465)
0.03
(0.9168)


0.24
(0.5678)


area
AR RA
0.32 -0.36
(0.2253) (0.1657)
-0.43 -0.42
(0.0942) (0.1052)
0.49 -0.17
(0.0558) (0.5284)
0.33 0.44
(0.2147) (0.0893)
-0.39 0.20
(0.1317) (0.4471)
-0.22 -0.31
(0.4028) (0.2383)
-0.19 -0.07
(0.4737) (0.8062)
0.22
(0.4016)


Coefficients above the diagonal for combined Single-EG, Double-EG and Quadruple-EG, and below the diagonal for Double-PD;
P-value in parentheses; TBAH: Total basal area per hectare, UL: U. lobata, SC: S. canadensis, LP: L. peruviana, BH: B. halimifolia,
SD: S. diphyllum, QL: A. laurifolia, AR: A. rubrum, RA: R. argutus











400

350

300

S250
IU)
i 200


100

50

0
0.00


5.00


10.00


15.00


20.00


25.00


E. grandis TBAH

Figure 4-3. Eucalyptus grandis in SRWC-90: correlation between total basal area per
hectare and cogongrass IVI.



350


S*.*


-
200

0
o 150
00
100


0
0.00


10.00


20.00


30.00


40.00


50.00


E. amplifolia TBAH


Figure 4-4. Eucalyptus amplifolia in SRWC-90: correlation between total basal area per
hectare and cogongrass IVI.


I- w I










350

300 *

5 250 -

S200 -

S150 -
0


50 -
50


0 10 20 30 40
TBAH (E. grandis & E. amplifolia)

Figure 4-5. Eucalyptus (E. grandis and E. amplifolia combined) in the study area:
correlation between total basal area per hectare and cogongrass IVI.

It appears that fast-growing tree plantations have the potential to suppress

cogongraso on CSAs in central Florida. Similar observations have been made in Asia

using fast-growing trees (Awang and Taylor 1993; Otsamo et al. 1997). However, initial

intensive management is necessary to suppress cogongrass (Otsamo et al. 1995a), before

the trees can establish in the plantation. Both planting fast-growing trees and intensive

site preparation reduce cogongrass rhizomes (Brook 1989; Soerjani 1970).

Despite the positive results, there were however some limitations of the study.

Sufficient details on vegetation and soil change could not be achieved from this study as

it was done in a limited time. There were some difficulties in designing statistically valid

sampling design due to small study area. Statistically valid tests could not be made due

to small sample size. Seasonal vegetation and soil quality evaluation was limited since

data collection was done only once. Enough details could not be collected on the

effectiveness of fast-growing trees on cogongrass control due to stand damage by


stand damage by






72


hurricanes. Problems with metal extraction in SRWC-90 soil samples limited the

comparison of soil nutrients between the operational area and SRWC-90.














CHAPTER 5
CONCLUSIONS

Both tree height and DBH differed significantly (p < 0.0001) by species and

cultures in the operational area. Height and DBH of Single-EG and Double-EG in the

operational area were larger than for the same trees in the same cultures in SRWC-90,

probably due to less competition with cogongrass. Stand density was comparatively

lower in E. grandis cultures in the operational area. Single-EG had the highest total basal

area. Tree density was low in E. grandis stands in the operational area due to low

survival. Clone-configuration-fertilizer study had higher tree density. Presence of

cogongrass seems to hinder tree growth, regardless of treatment.

The generally fertile soil at the site had few significant differences in soil

characteristics in the operational area. Total Kjeldahl nitrogen was significantly different

between cultures (p = 0.0002), plots within cultures (p = 0.0159) and positions

(p = 0.0028). Soil nutrients in SRWC-90 were lower than that in the operational area,

which might be due to different extraction methods used. pH was almost neutral in

SRWC-90, but was quite high in the operational area. Soil organic matter was higher

than in mineral soils, both in operational area and SRWC-90.

Potassium was significantly different only in plots within culture (p = 0.0072) and

between the positions (p = 0.0017) in the operational area. Magnesium, SOM and pH

were significantly different between the cultures. Soil organic matter was also

significantly different between positions (p = 0.0130) and pH in plots within cultures

(p = 0.0451).









Both native and exotic species were found in the study area. The most abundant

species such as B. alba, P. americana, S. diphyllum and E. capillifolium were

characteristic of disturbed sites. Other frequent species characteristic of moist habitat and

new plantations included C. diffusa, C. canadensis, B. halimifolia and S. canadensis.

Species richness and diversity were the highest in Double-EG, which had 35 herbaceous

and 23 shrubs/subshrubs. Cogongrass was the dominant understory species in

Double-PD and first three treatments of SRWC-90. While edge effect played a

significant role in the invasion of cogongrass, both eucalyptus and cottonwood

suppressed cogongrass.

Cogongrass IVI had nonsignificant correlation with stand basal area in E. grandis

(r = 0.19, p = 0.4587) and cottonwood (r = -0.21, p = 0.6103) in the operational area.

However, it had significant negative correlation with stand basal area in both E. grandis

(r = -0.91, p < 0.0001) and E. amplifolia (r = -0.73, p = 0.0028) in SRWC-90.

Dominant canopy and good stand density are essential to suppress cogongrass.

Eucalyptus with good survival performs better than cottonwood in controlling cogongrass

because the deciduous nature of cottonwood provides opportunity for cogongrass to

regrow in the understory. Fast-growing evergreen tree species combined with initial

intensive site preparation have the potential to control cogongrass and convert

phosphate-mined lands such as CSAs into productive sites.














CHAPTER 6
FUTURE RESEARCH

Better understanding of ecology and physiology of cogongrass has revealed

alternate ways to control it. Fast-growing species in this study have shown the potential

to control cogongrass. Though herbicide can control cogongrass for short duration,

combination of herbicide, intensive site preparation and use of fast-growing tree species

have been effective for longer period in other parts of the world. However, studies on the

use of fast-growing species is limited and mostly confined to Asia. Its study across the

globe can generate more relevant information on the management and control of

cogongrass in different edaphic and climatic conditions.

Because of the short-rotation of fast-growing trees, their long-term role in

controlling cogongrass is still unclear. Cogongrass might invade the area once the trees

are harvested. Long-term study is necessary to understand the effectiveness of these

trees. Continual monitoring of the existing plots and the edges of the cogongrass patches

can give information on cogongrass reinvasion and its rate. Seasonal monitoring can

provide information on the recruitment of seasonal vegetation in the area.

Fast-growing trees are vulnerable to natural calamities, such as storms and

hurricanes. Other perennial species that form dense ground cover might be effective in

areas where storm and hurricane are frequent. Some N-fixing ground covers have been

effective in other parts of the world. These can increase N supply at the same time,

which is deficient in phosphate-mine soil.









Natural succession is a slow process and may take decades to centuries.

Regeneration of native species in disturbed sites largely depends on seed supply. Further,

seeds introduced in the area are unable to germinate due to adverse edaphic and climatic

conditions. Interplanting native species that quickly produce seed with fast-growing trees

at the same time might shorten the rate of native species recruitment. Creating canopy

gaps after some years can provide opportunity for pioneer species to grow in the area.

Eucalyptus species have been criticized throughout the world due to possible

allelopathy. Though their invasiveness is not documented, it needs to be investigated.

Using other fast-growing species might increase the recruitment rate and the growth of

native species. Success of fast-growing trees to control cogongrass largely depends on

their canopy coverage. Permanent canopy is crucial to suppress cogongrass. Close

spacing is very important. Dense planting in edges can reduce edge effect.

Effect of multiple disking is still quite unclear. Results in this study area where

only the multiple disking was done have shown the need of further study on its role.

Including multiple disking as a separate treatment in future studies might provide

information on its effectiveness.















APPENDIX A
NAME AND NATIVITY OF HERBACEOUS AND SHRUB/SUBSHRUB SPECIES










Table A-1. Name and nativity of herbaceous species.
Species Common name Nativity OPA* SRWC-90
Family: Apiaceae


Hydrocotyle umbellate L.


Manyflower marshpennywort


Family: Asclepiadaceae
Morrenia odorata (Hook. & Am.) Lindl. Latexplant


Family: Asteraceae
Ambrosia artemisiifolia L.
Ampelaster carolinianus (Walt.) Nesom
Bidens alba (L.) DC.
Cirsium horridulum Michx.
Conyza canadensis (L.) Cronq.
Erechtites hieraciifolia (L.) Raf. Ex DC.
Eupatorium capillifolium (Lam.) Small
Eupatorium serotinum Michx.
Krigia virginica (L.) Willd.

Family: Brassicaceae
Lepidium virginicum L.

Family: Commelinaceae
Commelina diffusa Burm. f.

Family: Convolvulaceae
Calystegia sepium (L.) R. Br.
Ipomoeapurpurea (L.) Roth
Stylismapatens (Desr.) Myint

Family: Cucurbitaceae
Cucumis melo L.
Melothria pendula L.

Family: Cyperaceae
Carex sp. L.
Oxycaryum cubense (Poepp. & Kunth)
Lye

Family: Euphorbiaceae
C /ii,,,i i!' hypericifolia (L.) Millsp.


Annual ragweed
Climbing aster
Spanish needles
Yellow thistle
Canadian horseweed
American bumweed
Dogfennel
Lateflowering thoroughwort
Virginia dwarfdandelion


Virginia pepperweed


Climbing dayflower


Hedge flase binweed
Tall morning-glory
Costalplain dawnflower


Cantaloupe
Gaudeloupe cucumber


Sedge

Cuban bulrush


Graceful sandmat


I X


N X


N X


N X


N X











Table A-1 continued.
Species Common name Nativity OPA* SRWC-90
Family: Fabaceae


Aeschynomene americana L.
Desmodium triflorum (L.) DC.
Macroptilium lathyroides (L.) Urban
Medicago lupulina L.
Rhynchosia cinerea Nash
Vicia acutifolia Ell.

Family: Lamiaceae
Collinsonia serotina Walt.
Salvia riparia Kunth

Family: Lygodiaceae
Ligotdiiii japonicum (Thunb. ex Murr.)
Sw.


Shyleaf
Threeflower ticktrefoil
Wild bushbean
Black medick
Brownhair snoutbean
Fourleaf vetch


Blue ridge horsebalm
Florida Keys sage


Japanese climbing fern


I X X


Family: Lythraceae
Lythrum alatum Pursh

Family: Oxiladiceae
Oxalis corniculata L.

Family: Passifloraceae
Passiflora incarnata L.

Family: Phytolaccaceae
Phytolacca americana L.


Family: Poaceae
Andropogon virginicus L.
Aristida purpurascens Poir.
Cynodon dactylon (L.) Pers.
Digitaria ciliaris (Retz.) Koel.
Imperata cylindrica (L.) Beauv.
Panicum repens L.
Setaria parviflora (Poir.) Kerbuelen

Family: Polygonaceae
Polygonum hydropiperoides Michx.


Family: Ranunculaceae
Clematis virginiana L.

Family: Rubiaceae
Galium tinctorium L.


Winged lythrum


Common yellow woodsorrel


Purple passionflower


American pokeweed


Broomsedge bluestem
Arrowfeather threeawn
Burmuda grass
Southern crabgrass
Cogongrass
Torpedo grass
Marsh bristlegrass


Swamp smartweed


Devil's darning needles


N X


N X X


N X X


N X X


N X


N X X


Stiff marsh bedstraw


N X










Table A-i continued.
Species Common name Nativity OPA* SRWC-90


Family: Thelypteridaceae
Thelypteris kunthii (Desv.) Morton

Family: Typhaceae
Typha latifolia L.

Family: Verbenaceae
Phyla nodiflora (L.) Greene
Verbena brasiliensis Vell.
Verbena scabra Vahl


Kunth's maiden fern


Broadleaf cattail


Turkey tangle forfruit
Brazil vervain
Sandpaper vervain


N X X


N X


Family:
UIHO1
UIH02
UIH03
UIH04
UIHO5
UIH06
UIH07
UIH08
*Operational area; N= native; I= Introduced







81


Table A-2. Name and nativity of shrub/subshrub species.
Species Common name Nativity OPA* SRWC-90


Family: Aceraceae
Acer rubrum L.


Red maple


N X X


Family: Anacardiaceae
Rhus copallinum L.
Schinus terebinthifolius Raddi
Toxicodendron radicans (L.) Kuntze

Family: Asteraceae
Baccharis i, i'n,, l,, i Michx.
Baccharis halimifolia L.

Family: Caprifoliaceae
Sambucus canadensis (L.) R. Bolli

Family: Ebenaceae
Diospyros virginiana L.

Family: Euphorbiaceae
Triadica sebifera (L.) Small

Family: Fagaceae
Quercus laurifolia Michx.
Quercus virginiana P. Mill.

Family: Malvaceae
Sida rhombifolia L.
Urena lobata L.

Family: Onagraceae
Ludwigia peruviana (L.) Hara


Family: Rosaceae
Rubus argutus Link

Family: Solanaceae
Solanum diphyllum L.

Family: Ulmaceae
Celtis occidentalis L.
Ulmus americana L.

Family: Verbenaceae
Callicarpa americana L.
Lantana camera L.


Sumac
Brazilian peppertree
Eastern poison ivy


Saltwater false willow
Saltbush


Common elderberry


Common persimmon


Chinese tallow


N X X


N X


I X


Laurel oak
Live oak


Cuban jute
Ceaserweed


Peruvian primrose-
willow


Sawtooth blackberry


Twoleaf nightshade


Common hackberry
American elm


American beautyberry
Lantana


I X


N X X


I X










Table A-2 continued.
Species Common name Nativity OPA* SRWC-90
Family: Vitaceae
Ampelopsis arborea (L.) Koehne Pepper vine N X X
Parthenocissus quinquefolia (L.) Planch. Virginia creeper N X X
Vitis sp. L. Wild foxgrape N X X

Family:
UIS01 X
UIS02 X
UIS03 X
*Operational area; N= native; I= Introduced















APPENDIX B
TREE SIZE AND SURVIVAL










Table B-1. Tree size and survival in the operational area: average tre
(cm), basal area (m2/ha), density (trees/ha) and quadratic
Basal
Culture Plot Height DBH
area


14.4
13.5
14.2
15.5
16.0
14.7
14.2


Single-EG (3-year-old)







Double-EG (3-year-old)





Quadruple-EG (2-year-old)







Double-PD (2.5-year-old)


11.8
10.8
11.5
13.0
13.5
12.1
11.6


10.0
9.4
11.6
13.4
13.2

8.2
8.4
9.2
9.5

7.7
7.9
7.6
6.9
6.9
6.4
6.3
6.2


11.0
5.0
15.3
17.9
15.3
13.7
15.4


10.6
5.0
6.5
10.5
7.9

11.0
10.5
11.9
10.9

13.2
13.0
11.3
10.3
6.3
6.0
6.6
5.4


ee height (m), DBH
diameter (cm).
Quad.
Density Quad.
Deny diameter
681 14.3
358 13.3
1075 13.5
1003 15.1
824 15.4
752 15.2
1003 14.0


1477
792
685
865
613

1919
1919
1724
1431

4072
4180
3748
4144
2090
2703
2414
2054


9.6
8.9
11.0
12.4
12.8

8.5
8.3
9.4
9.8

6.4
6.3
6.2
5.6
6.2
5.3
5.9
5.8










Table B-2. Tree size and survival in SRWC-90: average 3.75-year-old tree height (m),
DBH (cm), basal area (m2/ha), density (trees/ha) and quadratic diameter (cm).


Treatment* Species Plot Height DBH Basal area Density


EG
EG
EA
EA
EG
EG
EA
EA
EG
EG
EA
EA
EG
EG
EG
EG
EA
EA
EA
EA
EG
EG
EG
EG
EA
EA
EA
EA


10.5
7.0
4.3
6.2
6.6
8.1
6.5
5.8
6.6
8.5
9.2
8.2
11.8
12.4
10.8
10.5
10.7
11.2
10.6
9.1
10.9
10.1
8.3
9.7
10.2
9.5
8.6
8.9


14.9
6.0
4.4
6.3
6.6
12.5
9.8
7.8
6.4
11.9
12.2
12.0
23.1
21.7
15.9
21.5
22.4
38.4
33.0
22.9
18.2
16.4
16.8
16.6
26.5
21.4
20.4
26.2


3600
4800
4000
4400
7917
9167
8333
9583
3600
4000
4800
4400
6800
5200
4400
5600
8000
9600
8800
8400
4800
7600
8800
6000
7600
8800
8800
9200


Quad.
diameter
7.3
4.0
3.7
4.3
3.2
4.2
3.9
3.2
4.7
6.2
5.7
5.9
6.8
7.3
6.8
7.0
6.0
7.1
6.9
5.9
7.0
5.2
4.9
5.9
6.7
5.6
5.4
6.0


EG: E. grandis, EA: E. amplifolia; *See Table 3-2 for treatment descriptions.


J















APPENDIX C
SOIL CHARACTERISTICS












Table C-1. Soil characteristics in the operational area: total Kjeldahl N [TKN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg), Mg (mg/kg),
SOM (%), pH and bulk density (BD) on bed (B) and inter-bed (IB) positions.
Culture


Response Single-EG (n=4) Double-EG (n=4)
B IB B IB
TKN 0.28a 0.29a 0.34a 0.30a
P 4103.0a 4093.0a 4219.0a 4196.0a
K 188.1a 186.7a 265.8a 193.5a
Ca 11038.0a 11060.0a 11210.0a 7767.6a
Mg 1266.2a 1247.0a 1199.2a 1129.3a
SOM 5.58a 5.46a 6.70a 4.59ab

o pH 7.9ab 7.7a 7.3b 7.4a
BD (0-3 cm) 0.69ab 0.63a 0.59b 0.75a
(3-6 cm) 0.68a 0.75a 0.62a 0.72a
Means in the same row with the same letter are not significant at 5% level


Quadruple-EG (n=4)
B IB
0.24a 0.11b
4173.0a 4079.0a
260.9a 162.5a
11133.0a 10572.0a
1262.0a 1292.2a
4.74a 2.85b
8.0a 7.9a
0.78a 0.54a
0.84a 0.74a


Double-PD (n=4)
B IB
0.34a 0.35a
4073.0a 3482.0a
227.2a 193.7a
10935.0a 9961.0a
1126.7a 1092.0a
6.38a 6.61a
7.5ab 7.5a
0.70ab 0.85a
0.70a 0.72a










Table C-2. Soil characteristics in SRWC-90 E. grandis and E. amplifolia plots: total N [TN (%)], P (mg/kg), K (mg/kg), Ca (mg/kg),
Mg (mg/kg), SOM (%), pH and bulk density (BD) on bed (B) and inter-bed (IB) positions.
Treatment*
Response 1 (n=2) 2 (n=2) 3 (n=2) 4 (n=4) 5 (n=4)
B IB B IB B IB B IB B IB


E. grandis:
TN
P
K
Ca
Mg
SOM
pH
BD (0-3 cm)
(3-6 cm)


E. amplifolia:
TN
P
K
Ca
Mg
SOM
pH
BD (0-3 cm)
(3-6 cm)


0.34a
119.0a
106.8a
1818.5a
511.8a
9.44a
7.0a
0.78a
0.74a



0.38a
144.4a
82.5a
1840.0a
566.8a
10.92a
7.2a
0.67a
0.82a


0.24a
173.2a
106.2a
1824.0a
517.0a
6.74a
7.3a
0.63a
0.72a



32.00a
138.8a
94.8a
1876.0a
575.8a
8.43a
7.3a
0.58c
0.70a


0.29a
160.3a
124.5a
1728.0a
489.6a
8.41a
7.0a
0.83a
0.83a



0.41a
136.3a
147.5a
1822.5a
514.4a
12.24a
7.0a
0.64a
0.71a


0.36a
118.9a
93.3a
1936.0a
499.2a
10.13a
6.9a
0.72a
0.65a



0.28a
151.9a
93.5a
1874.0a
560.6a
7.27a
7.4a
0.63c
0.70a


0.32a 0.23a 0.40a
153.9a 171.1a 141.6a
85.8a 78.0a 89.9a
1720.0a 1850.0a 1783.5a
540.8a 595.0a 609.5a
9.12a 6.38a 9.62a
7.0a 7.4a 6.9a
0.76a 0.77a 0.81a


0.70a



0.32a
137.1a
93.9a
1644.5a
512.4a
8.94a
6.8a
0.71a
0.76a


0.80a



0.26a
155.1a
105.9a
1638.5a
533.8a
6.97a
6.9a
0.71bc
0.69a


0.80a



0.40a
132.5a
84.5a
1769.0a
599.3a
9.75a
7.0a
0.79a
0.81a


Means in the same row with same letter are not significant at 5% level; *See Table 3-2 for treatment descriptions.


0.31a
150.1a
83.1a
1771.7a
598.2a
7.83a
7.1a
0.87a
0.77a



0.39a
129.9a
85.5a
1780.7a
599.0a
9.59a
7.0a
0.86ab
0.86"


0.41a
123.8a
95.7a
1777.5a
633.4a
10.06a
6.8a
0.68a
0.72a



0.37a
135.0a
90.5a
1766.2a
639.5a
9.00a
6.9a
0.84a
0.80a


0.38a
136.8a
106.4a
1824.5a
653.2a
9.32a
7.0a
0.83a
0.75a



0.30a
146.2a
101.5a
1777.0a
653.3a
7.34a
6.9a
0.92a
0.84a