Quantcast

Biomass Allocation of the Invasive Tree Acacia Auriculiformis and Refoliation Following Hurricane-Force Winds1

November 24, 2007

By Lieurance, Deah M

DEAH M. LIEURANCE (USDA/ARS, Invasive Plant Research Laboratory, 3225 College Ave., Fort Lauderdale, FL 33314). Biomass allocation of the invasive tree Acacia auriculiformis and refoliation following hurricane-force winds. J. Torrey Bot. Soc. 134: 389-397. 2007.- Allometric equations and biomass allocation were determined for the aboveground wood, branch, twig, and leaf components of the invasive tree Acacia auriculiformis in south Florida prior to and after a major hurricane event. A destructive harvest was used and plant partitioned biomass was quantified for 35 trees prior to landfall of hurricane Wilma (October 2005), followed by an assessment of 29 hurricane impacted trees (representing all ontogeny classes) three months later. Allometric equations were developed to estimate plant partitioned biomass using diameter at base and diameter at breast height as predictors of biomass components, leaf area, leaf area ratio, and leaf weight ratio. Diameter at base was the best predictor of biomass allocation in all regression analyses. Hurricane force winds did not alter biomass of major woody components; however significant losses were observed in twig biomass and all measured leaf parameters. The replacement of damaged foliage resulted in overcompensation of leaf area and leaf area ratio. Similarly, leaf biomass, and leaf weight ratio also increased following the hurricane, but levels were lower than pre-hurricane observations. This research facilitates the prediction of A. auriculiformis biomass using non destructive sampling protocols while quantifying its resiliency and compensatory abilities following hurricane disturbance. Key words: biomass equations, dry weight estimation, earleaf acacia, hurricane, invasive species.

Plant invasions often proceed in a stepwise progression from introduction to establishment, naturalization, spread, and achievement of invasive pest status (Williamson and Fitter 1996, Myers and Bazely 2003). While the probability that an exotic plant will become weedy is small (Williamson and Fitter 1996), those that do successfully invade native communities commonly possess traits that produce community and ecosystem-level effects, including the alteration of ecosystem processes through changes in disturbance, competition, and community structure (Gordon 1998). Some attributes contributing to the success of invasive species include high aboveground growth rates, high photosynthetic rates accompanied by a broad phenotypic plasticity, and high fecundity (Bazzaz 1986, Reichard and Hamilton 1997).

Invasive plants are distributed over 40.4 million ha in the United States and spreading at a rate of 1.2 million ha per year (NISC 2001). In Florida, for example, approximately 25,000 nonindigenous plant species have been introduced, more than 1,000 of which are recorded as established (Wunderlin 1998). Considering Florida’s peninsular geography and the frost boundary to the north, the state is often described as a subtropical island with biogeographical implications of both an impoverished flora and vulnerability to invasion by non-native species (Ewel 1986, Horvitz et al. 1998, Loope and Mueller-Dombois 1989, Simberloff 1995, 1997). It is estimated that 27% of the plant species in Florida are nonindigenous and ca. half of these exotics alter ecosystem processes (Gordon 1998). Of the most ecologically damaging species in Florida, over half originate from South East Asia and Australia (Curnutt, 2000, FLEPPC 2005). The Australian native Acacia auriculiformis A. Cunn. ex Benth. (earleaf acacia), for instance, is listed as a Category I invasive exotic by the Florida Exotic Pest Plant Council (FLEPPC), a designation made for those species that alter community structure or ecological function and displace native species (Gordon 1998, Langeland and Burks 1998).

Acacia auriculiformis is native to the northern coast of Queensland in Australia, Papua New Guinea, and Indonesia (Morton 1985, Langeland and Burks 1998). The earliest reports of the tree’s importation outside its native range was 1931, when A. auriculiformis was used for landscaping in recreational areas and gardens of Malaysia (Morton 1985). It was later planted in India, Southeast Asia, and Africa for pulp and fuelwood production, due in part for the tree’s ability to grow well on marginal lands (i.e., mine spoils, abandoned fly ash ponds, and savannahs) (Langeland and Burks 1998, Selvam and Mahadevan 2002, Dutta and Agrawal 2003, Hossain et al. 2004). A. auriculiformis was also introduced as an ornamental into Florida in the early 1930s (Gordon and Thomas 1997, Langeland and Burks 1998). The fast growing tree was frequently planted along streets and was valued for its aesthetic qualities, but it was noted that the tremendous amount of long lasting litterfall (up to 33,600 kg ha^sup -1^ yr^sup -1^) was a nuisance (Morton 1985, Gordon 1998, Langeland and Burks 1998). Subsequently, the tree has naturalized and today A. auriculiformis is common not only in disturbed areas but also in fragile ecosystems such as scrub areas, pinelands, and hammocks in south Florida (Langeland and Burks 1998).

Acacia auriculiformis is an evergreen, often multi-stemmed tree which forms a modified flattened petiole or phyllode that expands and functions like a leaf (Ratnasabapathy 1974). Trees achieve high growth rates and commonly reach heights up to 28 m. The trees are well adapted to high rainfall (150 to 200 cm yr^sup -1^) but are also considered drought resistant, thriving under low nutrient conditions through mycorrhizal and bacterial associations (Osonubi et al. 1991, Langeland and Burks 1998). The seeds of A. auriculiformis possess brightly colored tendrils which attract birds, including the European starling, which results in broad dispersal (Morton 1985, Langeland and Burks 1998). The herbivore mediated dispersal combined with high germination success rates (up to 75%) has resulted in the persistence and widespread distribution of A. auriculiformis in the state of Florida (Ratnasabapathy 1974). These characteristics contribute to the competitive superiority of A. auriculiformis over, and displacement of, native vegetation, including the rare Lechea cernua Small (scrub pineweed) in Florida (Morton 1985, Langeland and Burks 1998). Considering the low nitrogen levels of Florida’s soils, invasion of the nitrogen-fixing A. auriculiformis may have serious ecosystem level implications through the addition of nitrogen and other nutrients to the nutrient poor system (Gordon 1998).

Hurricanes and tropical storms have significant, although localized, impacts on floral communities of Florida (Snyder et al. 1990, Horvitz and Koop 2001). These storms cause landscape level natural disturbances with intense winds, storm surge, and heavy rainfall (Tanner et al. 1991). Hurricane winds lead to canopy thinning through the loss of leaves, breakage of branches, and felling of trees, thereby transferring substantial biomass and nutrients to the forest floor (Van Bloem et al. 2005). The thinning canopy reduces leaf area and creates gaps, which increases light penetration and temperature while decreasing relative humidity (Tanner et al. 1991, Horvitz et al. 1998). The impacts of storm winds and the creation of canopy gaps are likely to influence competitive interaction among native and exotic species. The degree to which one species benefits from impacts of intense winds on competitors is dependent, in part, on the relative ability and rate at which these species replace damaged tissues. The impacts of hurricane-force winds and the recovery of damaged tissues are poorly known for most plant species, particularly invasive weeds.

Poorter and Remkes (1990) demonstrated that relative growth rate (RGR) is more closely correlated to the morphological than the physiological characteristics of a plant despite that it is a product of net assimilation rate (photosynthesis) and leaf area ratio (LAR). It can be interpreted that the more resources invested in a plant’s leaf area, the higher the carbon gain for the whole plant. In the event of a major defoliating disturbance, the rate at which plants can replace this leaf area is of utmost importance. Therefore, rapid increases in leaf mass per area (LMA), leaf weight ratios (LWR), and LAR following defoliation would facilitate higher fitness and competitive ability in a hurricane prone region.

Herein, our objectives were to 1) develop an allometric equation for estimating aboveground biomass of the invasive tree Acacia auriculiformis and 2) assess the influence of hurricane-force winds on this species. To meet these objectives, we investigated the resource allocation of A. auriculiformis over a range in tree sizes and developed regression equations to estimate the aboveground biomass in a nondestructive manner. In addition, we assessed changes in aboveground biomass and measured the regenerative potential of A. auriculiformis from LAR and leaf weight ratios (LWR) following Hurricane Wilma.

Methods. SITE DESCRIPTION. We sampled individual Acacia auriculiformis trees from three study sites located within an area of ca. 15 km2 in Broward County, Florida (26.08 N, 80.24 W; 26.07 N, 80.27 W; and 26.22 N, 80.29 W). The study sites were characterized as disturbed, marginal habitats that were dominated by A. auriculiformis. A total of 35 trees were destructively harvested during August 2005. Hurricane Wilma made landfall on 24 October 2005 near Naples, Florida as a category 3 storm (on the Saffir/Simpson hurricane scale) and weakened to a category 2 with sustained wind speeds ranging from 201.16 km h^sup -1^ to 160.93 km h^sup -1^ as it passed through Palm Beach and Broward counties (NCDC 2005). An additional 29 trees were harvested in January 2005 approximately three months after the hurricane event to determine how the trees recovered after this major wind disturbance. SAMPLING AND ANALYSIS. The diameter at breast height (DBH = 1.3 m), diameter at base (DAB; soil level), total tree height, height of canopy, and width of canopy were measured for each tree. Trees were then cut at soil level. The total aboveground fresh biomass was weighed and separated by major components: trunk, branch (diameter >/= 2 cm), twig, and phyllodes (referred to as leaves hereafter). Trees with DBH of 1.5 to 2.0 cm^sup 2^ or greater were subsampled using methods described in lieurance (2004) to insure an unbiased subsample of approximately 10% of the tree. The fresh weight of the subsample was recorded in the field. The subsample was then transported to the laboratory and separated into the different components, dried to a constant weight at 70[degrees]C and weighed. The fresh weight to dry weight ratio obtained from the subsamples was used to calculate the total dry biomass of trees.

Leaf area and dry weights from prehurricane, hurricane-impacted, and post-hurricane generated leaves were measured and leaf mass per area (LMA) was calculated for each tree. The post-hurricane leaves were clearly separated from the regrowth following disturbance by visual examination. In addition to being visibly damaged, leaves that survived the disturbance were fully expanded, lignified, and a darker green in appearance while the regrowth leaves were expanding, succulent, and light green. Total leaf area was calculated using a no intercept linear regression model where leaf area was the dependent variable and leaf mass was the independent variable (R^sup 2^ = 0.37 pre-hurricane, R^sup 2^ = 0.80 post-hurricane damaged, and R^sup 2^ = 0.92 post-hurricane regrowth). The total dry leaf weight for each tree was multiplied by the regression coefficient (slope) from each equation. Leaf area ratio (LAR) was calculated by dividing total leaf area by total dry biomass per tree. Leaf weight ratio (LWR) was calculated by dividing total dry leaf weight by total dry biomass per tree.

Dry weights for partitioned components of each tree, as well as the corresponding explanatory variables, were log transformed (double-sided natural logarithm) to account for non-constant variance (In (n +5)), thereby converting the exponential model to a linear relationship (Baskerville 1972, Sprugel 1983, SPSS 1999). Other researchers have noted (Sprugel 1983, Clough et al. 1997, Rayachhetry et al. 2001) that an inherent bias occurs when a linear regression is applied to the Intransformed data and the predicted values are converted to arithmetic units. Sprugel (1983) suggested the integration of a correction factor to the biomass equation as a means of removing the systematic bias introduced through transformation. Therefore, the backtransformed (anti-ln(y)) data were multiplied by the correction factor anti-ln(standard error)^sup 2/2^ to adjust for inherent biases of the transformation as per Sprugel (1983). Linear regression and coefficients of determination (R^sup 2^) were used to compare the predictability of independent variables. Differences in plant partitioned biomass among pre- and posthurricane treatments were compared with ANCOVA, with DAB as the covariate and Bonferroni post-hoc testing was used to determine significant differences between treatments (SAS 1990).

Results. Sampled trees represented all ontogeny classes (seedling, sapling, adult), of Acacia” auriculiformis ranging in height from 28.5 cm to 922.5 cm. The mean DAB, DBH, and tree height was 4.69 cm^sup 2^ (+- 0.67, n = 63), 2.91 cm^sup 2^ (+- 0.48, n = 50), and 287.2 cm (+- 25.95, n = 63), respectively.

Table 1. Coefficients of determination (R^sup 2^) for two-sided In-transformed equations of independent variables (DAB = diameter at base, DBH = diameter at 1.3 m) and biomass allocation of Acacia auriculiformis in Florida, USA.

The coefficient of determination for the relationship of single and/or combined independent variables (DBH, DAB, and tree height) for dry weight of the major tree components are presented in Table 1. All independent variables explained >/= 89% of the variation in biomass components (leaf, twig, and trunk) and plant architecture (total height, canopy height, and canopy volume), with the exception of branch biomass. The coefficient of determination for all regressions using DAB as the independent variable were consistently higher than those with DBH. R^sup 2^ values for branch biomass were lower than other measured variables and were greatest for DAB (0.80) only, with DBH and height or their combination explaining /= 2 cm was relatively small (n = 8). The linear relationship between the biomass of aboveground components of Acacia auriculiformis and DAB is:

ln(y) = y^sub 0^ + a ln(DAB),

where y is the dry weight of a given plant component, y^sub 0^ is the intercept, a is the slope, and DAB is the tree diameter at stem base. The regression coefficients for predicting plant partitioned biomass based on DAB is presented in Table 2. Due in part to its broad use in the literature, Table 2 also contains the regression parameters for predicting dry weights based on DBH.

Hurricane force winds did not alter biomass of major woody components, including trunk (F = 0.16, P = 0.69), branch (F = 0.32, P = 0.59), or total tree biomass (F = 0.01, P = 0.90). However, twig biomass was significantly lower following the hurricane (F = 290.64, P

Discussion. The use of a single, easily obtained plant parameter for the prediction of plant biomass or size has broad application in various disciplines of plant biology (Niklas 2004). This research establishes the ability to estimate aboveground dry biomass and leaf area for standing Acacia auriculiformis trees through non- destructive methods using allometric equations as developed through one time destructive sampling. The extrapolation of these biometric relationships to the management of exotic plants is also applicable, although these kinds of applications have received less attention in the scientific literature. After comparing predictability of an assortment of variables, for example, Rayamajhi et al. (2002) determined that DBH was an accurate predictor for biomass allocation of Melaleuca quinquenervia (Cav.) Blake in Florida. DBH has subsequently been used to predict M. quinquenervia removal costs, carrying capacity for herbivores, and natural enemy mediated alterations in plant partitioned biomass (Pratt et al. 2004, Laroche and McKim 2004, Pratt et al. 2005). However, DAB was found to be a better predictor of A. auriculiformis biomass fractions herein. In addition to greater accuracy, DAB also offers the advantage of including all individuals regardless of their relative stature. In contrast, DAB may not be as easily quantified as DBH due to possible difficulties in measuring tree base in situations of heavy understory vegetation or standing water.

Table 2. Parameters for estimating total aboveground biomass and the component biomass for Acacia auriculiformis growing in Florida, USA. Values represent least square means (standard errors) from twosided In-transformed regression. Trees were harvested before the hurricane event (n = 34).

Our research represents the first assessment of plant partitioned biomass for a wide range of Acacia auriculiformis tree sizes in Florida. Previous research in Hawaii on A. auriculiformis investigated biomass of planted seedlings versus coppice regrowth and suggested that wood-biomass and leaf area allometric equations did not differ with the age or growth form of the plant (Harrington and Fownes 1993). These allometric relationships for A. auriculiformis trees grown in Hawaii fell within the size class range of trees studied herein. We compared these previously published equations with those reported for woody biomass and leaf area in this study using ANCOVA, with DAB as the covariate. These analyses indicate that the slope for both leaf area (F = 9.10, P = 0.0037) and woody biomass (F = 19.19, P

A paucity of data exists on the species specific impacts of hurricane force winds, due in part to the intermittent and unpredictable nature of their occurrence (Spiller et al. 1998, Conner et al. 2002). These findings offer insight into the effects of wind damage on aboveground biomass of Acacia auriculiformis as well as its ability to recover from a major landscape level disturbance. For trees with DAB between 6 to 16 cm2 for instance, we observed 24% and 40% decrease in leaf (phyllode) biomass and area as a result of Hurricane Wilma (Table 2). These differences decreased concomitantly with decreasing DAB (Fig. 1). The LAR and LWR also reflected these trends. Generally, increases in LAR and LWR indicate greater biomass allocation to photosynthetic surfaces and any reduction in these ratios are expected to affect the productivity (RGR) of this invasive exotic (Harrington et al. 1989), Sturdier, woody components were more resistant to high winds and provided the framework for rapid regrowth and recovery of photosynthetic tissues. These findings underscore the vulnerability of leaf and twig components to wind disturbance, specifically for dominant individuals. It should also be noted that we did not observe any trees blown over in our study sites.

FIG. 1. A comparison between leaf weight, total leaf area, LAR (leaf area ratio), LWR (leaf weight ratio), and DAB (diameter at soil) for Acacia auriculiformis populations before and after Hurricane Wilma. Black circle-solid line represent pre-hurricane values, white circle-long dash line represent post-hurricane without regrowth values, and grey circle-dot dash line represent post- hurricane with regrowth values.

Plants may compensate (e.g., maintenance of equivalent biomass or fitness) for the effects of foliar damage, especially under favorable growing conditions, limited competition, and minimal top- down regulation (Belsky 1987). These conditions characterize many disturbed habitats dominated by introduced plants, implying that exotic, invasive weeds in these systems should exhibit strong compensatory responses (Pratt et al. 2005). Herein we quantified the resiliency and compensatory abilities of Acacia auriculiformis following hurricane disturbance. Three months after the hurricane, leaf area and LAR of damaged trees had surpassed pre-hurricane levels. There was also an increase in leaf weight and LWR, but these values did not exceed pre-hurricane measures. This difference can be attributed to newer foliage having lower LMA and therefore thinner leaves. Previous research suggests that mass and area based measures of photosynthesis decline for multiple species with increasing leaf lifespan (Lambers et al. 1998). It may be inferred, therefore, that these new, thinner leaves are more productive than the older leaves that survived the disturbance (Reich et al. 1992). From these data it is apparent that A. auriculiformis reallocates resources to production and maintenance of photosynthetic tissues to compensate for the impacts of wind damage. This finding is thus consistent with the hypothesis that highly competitive invasive plants can compensate for foliar impacts. However, it remains unclear if this compensation comes at cost to other performance measures or reproduction.

Considering the frequency of intense hurricanes striking the Florida peninsula, studies addressing vegetation resiliency are important for understanding interspecific competition following hurricanes in the greater Everglades ecosystem. One might hypothesize that due in part to their larger, dominant stature (Fowler et al. 1996, Willis et al. 1999) invasive plants are more susceptible to impacts from hurricane-force winds as compared to their native analogues of smaller statures. In contrast, exotic weeds may be predicted to readily compensate, or overcompensate, for reductions in canopy biomass (Pratt et al. 2005). While it has been suggested that hurricanes are not the direct cause of the high abundance of invasive species in southern Florida, they do impact the relative abundance and life-historystage structures of natives and exotic plant species (Horvitz et al. 1998). Additional research investigating plant performance of Acacia auriculiformis versus native species following hurricanes may provide insights to disturbance-mitigated competition and management of this invasive species.

1 The author would like to thank Paul Pratt, Min Rayamajhi, and J. Scott Blackwood who assisted in many phases of this work. Allen Dray for assistance with statistical analyses. Donna Ban and Robyn Chiareli for assistance with fieldwork. Finally, the USDA ARS Invasive Plant Research Laboratory for support and cooperation in this research.

Literature Cited

BASKERVILLE, G. L. 1972. Use of logarithmic regression in the estimation of plant biomass. Can. J. For. 2: 49-53.

BAZZAZ, F. A. 1986. Life history of colonizing plants: some demographic, genetic, and physiological features, p. 96-110. In H. A. Mooney and J. A. Drake [eds.], Ecology of biological invasions of North America and Hawaii. SpringerVerlag, New York, NY.

BELSKY, A. J. 1987. The effects of grazing: confounding ecosystem, community, and organism scales. Am. Nat. 129: 870-892.

CLOUGH, B. F., P. DIXON, AND O. HALHAUS. 1997. Allometric relationships for estimating biomass in multi-stemmed mangrove trees. Aust. J. Bot. 45: 1023-1031.

CONNER, W. H., L. MIHALIA, AND J. WOLFE. 2002. Tree community structure and changes from 1987 to 1999 in three Louisiana and three South Carolina forested wetlands. Wetlands 22: 58-70.

CURNUTT, J. L. 2000. Host-area specific climaticmatching: similarity breeds exotics. Biol. Conserv. 94: 341-351.

DUTTA, R. K. AND M. AGRAWAL. 2003. Restoration of opencast coal mine spoil by planting exotic tree species: a case study in dry tropical region. Ecol. Eng. 21: 143-151.

EWEL, J. J. 1986. Invasibility: lessons from South Florida, p. 214-230. In H. A. Mooney and J. A.

Drake [eds.], Ecology of biological invasions of North America and Hawaii. Springer-Verlag, New York, NY.

FLORIDA EXOTIC PEST PLANT COUNCIL (FLEPPC). 2005. List of Florida’s Invasive Species, retrieved June 1, 2006 from Florida Exotic Pest Plant Council, <>

FOWLER, S. V., H. M. HARMAN, J. MEMMOTT, Q. PAYNTER, R. SHAW, A. W. SHEPPARD, AND P. SYRETT. 1996. Comparing the population dynamics of broom, Cytisus scoparius, as a native plant in the United Kingdom and France and as an invasive alien weed in Australia and New Zealand, p. 19-26. In V. C. Moran and J. H. Hoffmann [eds.], Proceedings of the IX International Symposium on Biological Control of Weeds. Stellenbosch, South Africa. University of Cape Town, South Africa.

GORDON, D. R. AND K. P. THOMAS. 1997. Florida’s invasion by nonindigenous plants: history, screening, and regulation, p. 21-37. In D. S. Simberloff, D. C. Schmitz, and T. C. Brown [eds.], Strangers in paradise: impact and management of nonindigenous species in Florida. Island Press, Washington, DC.

GORDON, D. R. 1998. Effects of invasive, nonindigenous plant species on ecosystem processes: lessons from Florida. Ecol. Appl. 8: 975-989.

HARRINGTON, R. A., B. J. BROWN, AND P. A. REICH. 1989. Ecophysiology of exotic and native shrubs in Southern Wisconsin II. Annual growth and carbon gain. Oecologia 80: 368-373.

HARRINGTON, R. A. AND J. H. FOWNES. 1993. Allometry and growth of planted versus coppice stands of 4 fast-growing tropical tree species. For. Ecol. Manage. 56: 315-327.

HORVITZ, C. C. AND A. KOOP. 2001. Removal of nonnative vines and post-hurricane recruitment in tropical hardwood forests of Florida. Biotropica 33: 268-281.

HORVITZ, C. C, J. B. PASCARELLA, S. MCMANN, A. FREEDMAN, AND R. H. HOFSTETTER. 1998. Functional roles of invasive non-indigenous plants in hurricane-affected subtropical hardwood forests. Ecol. Appl. 8: 947-974.

HOSSAIN, M. K., M. S. HOSSAIN, AND B. KOIRALA. 2004. Acacia auriculiformis provenances for large-scale planting in degraded hilly areas of Bangladesh. J. Trop. For. Sci. 16: 265-267.

LAMBERS, H., F. S. CHAPIN III, AND T. L. PONS. 1998. Plant Physiological Ecology. Springer-Verlag, New York, NY. 540 p.

LANGELAND, K. A. AND K. C. BURKS. 1998. Identification and Biology of Non-Native Plants in Florida’s Natural Areas. UF/IFAS Distribution, Gainsville, FL. 165 p.

LAROCHE, F. B. AND J. MCKIM. 2004. Cost comparison of Melaleuca treatment methods. Wildland Weeds 7: 12-15.

LIEURANCE, D. M. 2004. Leaf phenology, fecundity, and biomass allocation of the invasive shrub Lonicera maackii (Rupr.) Maxim in contrasting light environments. Master’s thesis. Ohio University, Athens, OH. 52 p.

LOOPE, L. L. AND D. MUELLER-DOMBOIS. 1989. Characteristics of invaded islands, p. 257-280. In J. A. Drake, H. A. Mooney, F. di Castri, R. H. Groves, F. J. Kruger, M. Rejmanek, and M. Williamson [eds.], Ecology of Biological Invasions: a Global Synthesis. John Wiley & Sons, Chichester, U.K.

MORTON, J. F. 1985. The earleaf acacia, a fastgrowing, brittle, exotic “weed” tree in Florida. Proc. of the Florida State Horticultural Society 98: 309-314.

MYERS, J. H. AND D. R. BAZELY. 2003. Ecology and Control of Introduced Plants. Cambridge University Press, Cambridge, UK. 313 p.

NATIONAL CLIMATIC DATA CENTER (NCDC). 2005. Climate of 2005 Summary of Hurricane Wilma. N. C. D. Center. Dept. of Commerce, Ashville, NC, U.S. 7 p.

NATIONAL INVASIVE SPECIES COUNCIL (NISC). 2001. Meeting the Invasive Species Challenge: National Invasive Species Management Plan. NISC. Washington, DC. 89 p. NIKLAS, K. J. 2004. Plant allometry: is there a grand unifying theory? Biol. Rev. 79: 871- 889.

OSONUBI, O., K. MULONGOY, O. O. AWOTOYE, M. O. ATAYESE, AND D. U. U. OKALI. 1991. Effects of ectomycorrhizal and vesicular-arbuscular mycorrhizal fungi on drought tolerance of 4 leguminous woody seedlings. Plant and Soil 136: 131-143.

POORTER, H. AND C. REMKES. 1990. Leaf area and net assimilation rate of 24 wild species differing in relative growth rate. Oecologia 83: 553-559.

PRATT, P. D., V. QUEVEDO, L. BERNIER, J. SUSTACHE, AND T. D. CENTER. 2005. Invasions of Puerto Rican wetlands by the Australian tree Melaleuca quinquenervia. Carib. J. Sci. 41: 42-54.

PRATT, P. D., M. B. RAYAMAJHI, T. K. VAN, AND T. D. CENTER. 2004. Modeling the influence of resource availability on population densities of Oxyops vitiosa (Coleoptera: Curculionidae), a biological control agent of the invasive tree Melaleuca quinquenervia. Biocontrol Sci. Techn. 14: 51-61.

RATNASABAPATHY, M. 1974. Acacia auriculaeformis and Casuarina equisetifolia-the urban invaders. Malayan Nat. J. 28: 16-21.

RAYACHHETRY, M. B., T. K. VAN, T. D. CENTER, AND F. LAROCHE. 2001. Dry weight estimation of the aboveground components of Melaleuca quinquenervia trees in southern Florida. For. Ecol. and Manage. 142: 281-290.

RAYAMAJHI, M. B., T. K. VAN, T. D. CENTER, J. A. GOOLSBY, P. D. PRATT, AND A. RACELIS. 2002. Biological attributes of the canopy- held melaleuca seeds in Australia and Florida, US. J. of Aquat. Plant Manage. 40: 87-91.

REICH, P. B., M. B. WALTERS, J. M. VOSE, C. GRESHAM, J. C. VOLIN, AND W. D. BOWMAN. 1992. Leaf life-span in relation to leaf, plant, and stand characteristics among diverse ecosystems. Ecol. Monogr. 62: 365-392.

REICHARD, S. H. AND C. W. HAMILTON. 1997. Predicting invasions of woody plants introduced into North America. Conserv. Biol. 11: 193- 203.

SAS. 1999. The SAS System for Windows, Version 8. SAS Institute Inc. Cary, North Carolina.

SELVAM, A. AND A. MAHADEVAN. 2002. Distribution of mycorrhizas in an abandoned fly ash pond and mined sites of Neyveli Lignite Corporation, Tamil Nadu, India. Basic Appl. Ecol. 3: 277-284.

SIMBERLOFF, D. 1995. Why do introduced species appear to devastate island more than mainland areas? Pac. Sci. 49: 87-97.

SIMBERLOFF, D. 1997. The biology of invasions, p. 3-17. In D. S. Simberloff, D. C. Schmitz, and T. C. Brown [eds.], Strangers in Paradise: Impact and Management of Nonindigenous Species in Florida. Island Press, Washington, DC.

SNYDER, J. R., A. HERNDON, AND W. B. ROBINSON JR. 1990. South Florida rockland, p. 230-277. In R. L. Myers and J. J. Ewel [eds.], Ecosystems of Florida. University of Central Florida Press, Orlando, FL.

SPILLER, D. A., J. B. LOSOS, AND T. W. SCHOENER. 1998. Impact of a catastrophic hurricane on island populations. Science 281: 695- 697.

SPSS. 1999. SPSS base 10.0 application guide computer program, version 10.0. By SPSS, Chicago, IL. 426 p.

SPRUGEL, D. G. 1983. Correcting for bias in logtransformed allometric equations. Ecology 64: 209-210.

TANNER, E. V. J., V. KAPOS, AND J. R. HEALEY. 1991. Hurricane effects on forest ecosystems in the Caribbean. Biotropica 23: 513- 521.

VAN BLOEM, S. J., P. G. MURPHY, A. E. LUGO, R. OSTERTAG, M. R. COSTA, I. R. BERNARD, S. M. COLON, AND M. C. MORA. 2005. The influence of hurricane winds on Caribbean dry forest structure and nutrient pools. Biotropica 37: 571-583.

WILLIAMSON, M. AND A. FITTER. 1996. The varying success of invaders. Ecology 77: 1661-1666.

WILLIS, A. J., M. B. THOMAS, AND J. H. LAWTON. 1999. Is the increased vigor of invasive weeds explained by a tradeoff between growth and herbivore resistance? Oecologia 120: 632-640.

WUNDERLIN, R. P. 1998. Guide to the Vascular Plants of Florida. University Press of Florida, Gainesville, FL. 806 p.

Deah M. Lieurance2

USDA/ARS, Invasive Plant Research Laboratory, 3225 College Ave., Fort Lauderdale, FL 33314

2 Author for correspondence: E-mail: dlieurance@ saa.ars.usda.gov

Received for publication January 5, 2007, and in revised form June 28, 2007.

Copyright Torrey Botanical Society Jul-Sep 2007

(c) 2007 Journal of the Torrey Botanical Society. Provided by ProQuest Information and Learning. All rights Reserved.




comments powered by Disqus