Tick-borne disease risk in a forest food web.

Changes to the community ecology of hosts for zoonotic pathogens, particularly rodents, are likely to influence the emergence and prevalence of zoonotic diseases worldwide. However, the complex interactions between abiotic factors, pathogens, vectors, hosts, and both food resources and predators of hosts are difficult to disentangle. Here we (1) use 19 yr of data from six large field plots in southeastern New York to compare the effects of hypothesized drivers of interannual variation in Lyme disease risk, including the abundance of acorns, rodents, and deer, as well as a series of climate variables; and (2) employ landscape epidemiology to explore how variation in predator community structure and forest cover influences spatial variation in the infection prevalence of ticks for the Lyme disease bacterium, Borrelia burgdorferi, and two other important tick-borne pathogens, Anaplasma phagocytophilum and Babesia microti. Acorn-driven increases in the abundance of mice were correlated with a lagged increase in the abundance of questing nymph-stage Ixodes scapularis ticks infected with Lyme disease bacteria. Abundance of white-tailed deer 2 yr prior also correlated with increased density of infected nymphal ticks, although the effect was weak. Density of rodents in the current year was a strong negative predictor of nymph density, apparently because high current abundance of these hosts can remove nymphs from the host-seeking population. Warm, dry spring or winter weather was associated with reduced density of infected nymphs. At the landscape scale, the presence of functionally diverse predator communities or of bobcats, the only obligate carnivore, was associated with reduced infection prevalence of I. scapularis nymphs with all three zoonotic pathogens. In the case of Lyme disease, infection prevalence increased where coyotes were present but smaller predators were displaced or otherwise absent. For all pathogens, infection prevalence was lowest when forest cover within a 1 km radius was high. Taken together, our results suggest that a food web perspective including bottom-up and top-down forcing is needed to understand drivers of tick-borne disease risk, a result that may also apply to other rodent-borne zoonoses. Prevention of exposure based on ecological indicators of heightened risk should help protect public health.

Social and biophysical variation in regional timber harvest regimes.

In terms of adult tree mortality, harvesting is the most prevalent disturbance in northeastern United States forests. Previous studies have demonstrated that stand structure and tree species composition are important predictors of harvest. We extend this work to investigate how social factors further influence harvest regimes. By coupling the Forest Inventory and Analysis database to U.S. Census and National Woodland Owner Survey (NWOS) data, we quantify social and biophysical variation in the frequency and intensity of harvesting throughout a 20-state region in the northeastern United States. Among social factors, ownership class is most predictive of harvest frequency and intensity. The annual probability of a harvest event within privately owned forest (3%/yr) is twice as high as within publicly owned forests (1.5%/yr). Among private owner classes, the annual harvest probability on corporate-owned forests (3.6%/yr) is 25% higher than on private woodlands (2.9%/yr). Among public owner classes, the annual probability of harvest is highest on municipally owned forests (2.4%/ yr), followed by state-owned forests (1.6%/yr), and is lowest on federal forests (1%/yr). In contrast, corporate, state, and municipal forests all have similar distributions of harvest intensity; the median percentage of basal area removed during harvest events is approximately 40% in these three owner groups. Federal forests are similar to private woodlands with median harvest intensities of 23% and 20%, respectively. Social context variables, including local home prices, population density and the distance to a road, help explain the intensity, but not the frequency, of harvesting. Private woodlands constitute the majority of forest area; however, demographic data about their owners (e.g., their age, educational attainment, length of land tenure, retired status) show little relationship to aggregate harvest behavior. Instead, significant predictors for harvesting on private woodlands include live-tree basal area, forest type, and distance from roads. Just as with natural disturbance regimes, harvest regimes are predictable in terms of their frequency, intensity, and dispersion; and like their natural counterparts, these variables are determined by several important dimensions of environmental context. But in contrast to natural disturbance regimes, the important dimensions of context for harvesting include a combination of social and biophysical variables.

Nonnative forest insects and pathogens in the United States: Impacts and policy options.

We review and synthesize information on invasions of nonnative forest insects and diseases in the United States, including their ecological and economic impacts, pathways of arrival, distribution within the United States, and policy options for reducing future invasions. Nonnative insects have accumulated in United States forests at a rate of ~2.5 per yr over the last 150 yr. Currently the two major pathways of introduction are importation of live plants and wood packing material such as pallets and crates. Introduced insects and diseases occur in forests and cities throughout the United States, and the problem is particularly severe in the Northeast and Upper Midwest. Nonnative forest pests are the only disturbance agent that has effectively eliminated entire tree species or genera from United States forests within decades. The resulting shift in forest structure and species composition alters ecosystem functions such as productivity, nutrient cycling, and wildlife habitat. In urban and suburban areas, loss of trees from streets, yards, and parks affects aesthetics, property values, shading, stormwater runoff, and human health. The economic damage from nonnative pests is not yet fully known, but is likely in the billions of dollars per year, with the majority of this economic burden borne by municipalities and residential property owners. Current policies for preventing introductions are having positive effects but are insufficient to reduce the influx of pests in the face of burgeoning global trade. Options are available to strengthen the defenses against pest arrival and establishment, including measures taken in the exporting country prior to shipment, measures to ensure clean shipments of plants and wood products, inspections at ports of entry, and post-entry measures such as quarantines, surveillance, and eradication programs. Improved data collection procedures for inspections, greater data accessibility, and better reporting would support better evaluation of policy effectiveness. Lack of additional action places the nation, local municipalities, and property owners at high risk of further damaging and costly invasions. Adopting stronger policies to reduce establishments of new forest insects and diseases would shift the major costs of control to the source and alleviate the economic burden now borne by homeowners and municipalities.

Interspecific variation in growth responses to climate and competition of five eastern tree species.

Climate and competition are often presented from two opposing views of the dominant driver of individual tree growth and species distribution in temperate forests, such as those in the eastern United States. Previous studies have provided abundant evidence indicating that both factors influence tree growth, and we argue that these effects are not independent of one another and rather that interactions between climate, competition, and size best describe tree growth. To illustrate this point, we describe the growth responses of five common eastern tree species to interacting effects of temperature, precipitation, competition, and individual size using maximum likelihood estimation. Models that explicitly include interactions among these four factors explained over half of the variance in annual growth for four out of five species using annual climate. Expanding temperature and precipitation analyses to include seasonal interactions resulted in slightly improved models with a mean R2 of 0.61 (SD 0.10). Growth responses to individual factors as well their interactions varied greatly among species. For example, growth sensitivity to temperature for Quercus rubra increased with maximum annual precipitation, but other species showed no change in sensitivity or slightly reduced annual growth. Our results also indicate that three-way interactions among individual stem size, competition, and temperature may determine which of the five co-occurring species in our study could have the highest growth rate in a given year. Continued consideration and quantification of interactions among climate, competition, and individual-based characteristics are likely to increase understanding of key biological processes such as tree growth. Greater parameterization of interactions between traditionally segregated factors such as climate and competition may also help build a framework to reconcile drivers of individual-based processes such as growth with larger-scale patterns of species distribution.

Interspecific variation in growth responses to climate and competition of five eastern tree species.

Climate and competition are often presented from two opposing views of the dominant driver of individual tree growth and species distribution in temperate forests, such as those in the eastern United States. Previous studies have provided abundant evidence indicating that both factors influence tree growth, and we argue that these effects are not independent of one another and rather that interactions between climate, competition, and size best describe tree growth. To illustrate this point, we describe the growth responses of five common eastern tree species to interacting effects of temperature, precipitation, competition, and individual size using maximum likelihood estimation. Models that explicitly include interactions among these four factors explained over half of the variance in annual growth for four out of five species using annual climate. Expanding temperature and precipitation analyses to include seasonal interactions resulted in slightly improved models with a mean R2 of 0.61 (SD 0.10). Growth responses to individual factors as well their interactions varied greatly among species. For example, growth sensitivity to temperature for Quercus rubra increased with maximum annual precipitation, but other species showed no change in sensitivity or slightly reduced annual growth. Our results also indicate that three-way interactions among individual stem size, competition, and temperature may determine which of the five co-occurring species in our study could have the highest growth rate in a given year. Continued consideration and quantification of interactions among climate, competition, and individual-based characteristics are likely to increase understanding of key biological processes such as tree growth. Greater parameterization of interactions between traditionally segregated factors such as climate and competition may also help build a framework to reconcile drivers of individual-based processes such as growth with larger-scale patterns of species distribution.

Countervailing effects on pine and oak leaf litter decomposition in human-altered Mediterranean ecosystems.

Species affect the dynamics of litter decay through the intrinsic properties of their litter, but also by influencing the environmental conditions imposed by their canopy, roots, and litter layers. We examined how human-induced changes in the relative abundances of two dominant Mediterranean trees-Pinus halepensis and Quercus calliprinos-impact leaf litter decomposition. A reciprocal transplant experiment tested decomposition of pine, oak, and mixed leaf litter in oak woodland and pine forest ecosystems with different relative abundances of pine and oak. Using likelihood methods, we tested the importance and magnitude of the environmental effects of local species abundance, litter layer composition, and soil properties on litter mass loss. Oak litter decomposition was slower than pine, and had an antagonistic effect on mixed litter decay. These results differ from other reported pine-oak associations, and are probably associated with a higher content of tannins and phenols in oak compared to pine litter in our study sites. The environmental effects of the two species were opposite to their litter decomposition dynamics. An increased proportion of pine in the oak woodlands and a higher content of pine needles in the litter layer of pine forests reduced decay rates. The presence of more oak and broadleaf litter in the litter layer accelerated decomposition in pine forests. Our results highlight the importance of considering multidimensional species effects mediated by both chemical and physical properties, and imply that man-made changes in the composition and configuration of plant communities may result in complex unpredicted consequences to ecosystem biogeochemistry.

An integrative analysis of the dynamics of landscape- and local-scale colonization of Mediterranean woodlands by Pinus halepensis.

Afforestation efforts have resulted in extensive plantations of either native or non-native conifers, which in many regions has led to the spread of those conifers into surrounding natural vegetation. This process of species colonization can trigger profound changes in both community dynamics and ecosystem processes. Our study disentangled the complexity of a process of colonization in a heterogeneous landscape into a simple set of rules. We analyzed the factors that control the colonization of natural woodland ecosystems by Pinus halepensis dispersing from plantations in the Mediterranean region of Israel. We developed maximum-likelihood models to explain the densities of P. halepensis colonizing natural woodlands. Our models unravel how P. halepensis colonization is controlled by factors that determine colonization pressure by dispersing seeds and by factors that control resistance to colonization of the natural ecosystems. Our models show that the combination of different seed arrival processes from local, landscape, and regional scales determine pine establishment potential, but the relative importance of each component varied according to seed source distribution. Habitat resistance, determined by abiotic and biotic conditions, was as important as propagule input in determining the density of pine colonization. Thus, despite the fact that pine propagules disperse throughout the landscape, habitat heterogeneity within the natural ecosystems generates significant variation in the actual densities of colonized pine. Our approach provides quantitative measures of how processes at different spatial scales affect the distribution and densities of colonizing species, and a basis for projection of expected distributions. Variation in colonization rates, due to landscape-scale heterogeneity in both colonization pressure and resistance to colonization, can be expected to produce a diversity of new ecosystems. This work provides a template for understanding species colonization processes, especially in light of anthropogenic impacts, and predicting future transformation of natural ecosystems by species invasion.

Occurrence and transmission efficiencies of Borrelia burgdorferi ospC types in avian and mammalian wildlife.

Borrelia burgdorferi s.s., the bacterium that causes Lyme disease in North America, circulates among a suite of vertebrate hosts and their tick vector. The bacterium can be differentiated at the outer surface protein C (ospC) locus into 25 genotypes. Wildlife hosts can be infected with a suite of ospC types but knowledge on the transmission efficiencies of these naturally infected hosts to ticks is still lacking. To evaluate the occupancy and detection of ospC types in wildlife hosts, we adapted a likelihood-based species patch occupancy model to test for the occurrence probabilities (ψ - "occupancy") and transmission efficiencies (ε - "detection") of each ospC type. We detected differences in ospC occurrence and transmission efficiencies from the null models with HIS (human invasive strains) types A and K having the highest occurrence estimates, but both HIS and non-HIS types having high transmission efficiencies. We also examined ospC frequency patterns with respect to strains known to be invasive in humans across the host species and phylogenetic groups. We found that shrews and to a lesser extent, birds, were important host groups supporting relatively greater frequencies of HIS to non-HIS types. This novel method of simultaneously assessing occurrence and transmission of ospC types provides a powerful tool in assessing disease risk at the genotypic level in naturally infected wildlife hosts and offers the opportunity to examine disease risk at the community level.

Landscape-scale density-dependent recruitment of oaks in planted forests: more is not always better.

Plant colonization studies usually address density-dependent processes in the narrow sense of recruitment constraints due to negative density-dependent seed and seedling mortality. However, complex density-dependent effects may be involved in additional stages of the recruitment process. We hypothesized that seed arrival and seedling establishment are influenced by density dependence acting at small scales at the site of colonization, and at larger scales as a function of the colonizing species' landscape abundance. These hypotheses were tested in a study of colonization of pine forests by oaks in a heterogeneous Mediterranean landscape. Maximum-likelihood models show that density effects switch from positive to negative along the range of landscape-scale oak seed source abundance. Contrary to expectations, high seed source densities limited oak recruitment, suggesting a landscape-scale Janzen-Connell effect. We propose a range of mechanisms that generate positive or negative density dependence during colonization, resulting in nonlinear density-dependent feedbacks that can generate unexpected colonization patterns.

Regional variation in forest harvest regimes in the northeastern United States.

Logging is a larger cause of adult tree mortality in northeastern U.S. forests than all other causes of mortality combined. We used Forest Inventory and Analysis (FIA) data to develop statistical models to quantify three different aspects of aggregate regional forest harvest regimes: (1) the annual probability that a plot is logged, as a function of total aboveground tree biomass, (2) the fraction of adult tree basal area removed if a plot was logged, and (3) the probability that an individual tree within a plot was removed, as a function of the fraction of basal area removed at the plot level, the species of tree, and its size. Results confirm that relatively frequent partial harvesting dominates the logging regimes, but with significant variation among different parts of the region and different forest types. The harvest regimes have similarities with natural disturbance regimes in imposing spatially and temporally dynamic mortality that varies predictably as a function of stand structure as well as tree species and size.

Interactive effects of land use history and natural disturbance on seedling dynamics in a subtropical forest.

Human-impacted forests are increasing in extent due to widespread regrowth of secondary forests on abandoned lands. The degree and speed of recovery from human disturbance in these forests will determine their value in terms of biodiversity conservation and ecosystem function. In areas subject to periodic, severe natural disturbances, such as hurricanes, it has been hypothesized that human and natural disturbance may interact to either erase or preserve land use legacies. To increase understanding of how interactions between human and natural disturbance influence forest regeneration and recovery, we monitored seedlings in a human- and hurricane-impacted forest in northeastern Puerto Rico over a approximately 10-yr period and compared seedling composition and dynamics in areas that had experienced high- and low-intensity human disturbance during the first half of the 20th century. We found that land use history significantly affected the composition and diversity of the seedling layer and altered patterns of canopy openness and seedling dynamics following hurricane disturbance. The area that had been subject to high-intensity land use supported a higher density, but lower diversity, of species. In both land use history categories, the seedling layer was dominated by the same two species, Prestoea acuminata var. montana and Guarea guidonia. However, seedlings of secondary-successional species tended to be more abundant in the high-intensity land use area, while late-successional species were more abundant in the low-intensity area, consistent with patterns of adult tree distributions. Seedlings of secondary-forest species showed greater increases in growth and survival following hurricane disturbance compared to late-successional species, providing support for the hypothesis that hurricanes help preserve the signature of land use history. However, the increased performance of secondary-forest species occurred predominantly in the low-intensity land use area, suggesting that hurricanes act to homogenize differences in species composition between areas with differing land use histories by increasing secondary-forest species regeneration in areas that experienced little direct human disturbance. Our results suggest that, through effects on seedling dynamics, hurricanes may extend the signature of land use history beyond the average recovery time of forests not subject to intense natural disturbance events.

Frequency, not relative abundance, of temperate tree species varies along climate gradients in eastern North America.

There have been many attempts to model the impacts of climate change on the distributions of temperate tree species, but empirical analyses of the effects of climate on the distribution and abundance of tree species have lagged far behind the models. Here, we used forest inventory data to characterize variation in adult tree abundance along climate gradients for the 24 most common tree species in the northeastern United States. The two components of our measure of species abundance--local frequency vs. relative abundance--showed dramatically different patterns of variation along gradients of mean annual temperature and precipitation. Local frequency (i.e., the percentage of plots in a given climate in which a species occurred) varied strongly for all 24 species, particularly as a function of temperature. Relative abundance when present in a plot, on the other hand, was effectively constant for most species right up to their estimated climatic range limits. Although the range limits for both temperature and precipitation were quite broad for all of the species, the range of climates within which a species was common (i.e., high frequency) was much narrower. Because frequency in sites within a given climate shows a strong sensitivity to temperature, at least, this suggests that the processes determining canopy tree recruitment on new sites also vary strongly with climate.

Multi-model analysis of tree competition along environmental gradients in southern New England forests.

Robust predictions of competitive interactions among canopy trees and variation in tree growth along environmental gradients represent key challenges for the management of mixed-species, uneven-aged forests. We analyzed the effects of competition on tree growth along environmental gradients for eight of the most common tree species in southern New England and southeastern New York using forest inventory and analysis (FIA) data, information theoretic decision criteria, and multi-model inference to evaluate models. The suite of models estimated growth of individual trees as a species-specific function of average potential diameter growth, tree diameter at breast height, local environmental conditions, and crowding by neighboring trees. We used ordination based on the relative basal area of species to generate a measure of site conditions in each plot. Two ordination axes were consistent with variation in species abundance along moisture and fertility gradients. Estimated potential growth varied along at least one of these axes for six of the eight species; peak relative abundance of less shade-tolerant species was in all cases displaced away from sites where they showed maximum potential growth. Our crowding functions estimate the strength of competitive effects of neighbors; only one species showed support for the hypothesis that all species of competitors have equivalent effects on growth. The relative weight of evidence (Akaike weights) for the best models varied from a low of 0.207 for Fraxinus americana to 0.747 for Quercus rubra. In such cases, model averaging provides a more robust platform for prediction than that based solely on the best model. We show that predictions based on the selected best models dramatically overestimated differences between species relative to predictions based on the averaged set of models.

Climate, deer, rodents, and acorns as determinants of variation in lyme-disease risk.

Risk of human exposure to vector-borne zoonotic pathogens is a function of the abundance and infection prevalence of vectors. We assessed the determinants of Lyme-disease risk (density and Borrelia burgdorferi-infection prevalence of nymphal Ixodes scapularis ticks) over 13 y on several field plots within eastern deciduous forests in the epicenter of US Lyme disease (Dutchess County, New York). We used a model comparison approach to simultaneously test the importance of ambient growing-season temperature, precipitation, two indices of deer (Odocoileus virginianus) abundance, and densities of white-footed mice (Peromyscus leucopus), eastern chipmunks (Tamias striatus), and acorns (Quercus spp.), in both simple and multiple regression models, in predicting entomological risk. Indices of deer abundance had no predictive power, and precipitation in the current year and temperature in the prior year had only weak effects on entomological risk. The strongest predictors of a current year's risk were the prior year's abundance of mice and chipmunks and abundance of acorns 2 y previously. In no case did inclusion of deer or climate variables improve the predictive power of models based on rodents, acorns, or both. We conclude that interannual variation in entomological risk of exposure to Lyme disease is correlated positively with prior abundance of key hosts for the immature stages of the tick vector and with critical food resources for those hosts.

Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling.

Advances in computing power in the past 20 years have led to a proliferation of spatially explicit, individual-based models of population and ecosystem dynamics. In forest ecosystems, the individual-based models encapsulate an emerging theory of "neighborhood" dynamics, in which fine-scale spatial interactions regulate the demography of component tree species. The spatial distribution of component species, in turn, regulates spatial variation in a whole host of community and ecosystem properties, with subsequent feedbacks on component species. The development of these models has been facilitated by development of new methods of analysis of field data, in which critical demographic rates and ecosystem processes are analyzed in terms of the spatial distributions of neighboring trees and physical environmental factors. The analyses are based on likelihood methods and information theory, and they allow a tight linkage between the models and explicit parameterization of the models from field data. Maximum likelihood methods have a long history of use for point and interval estimation in statistics. In contrast, likelihood principles have only more gradually emerged in ecology as the foundation for an alternative to traditional hypothesis testing. The alternative framework stresses the process of identifying and selecting among competing models, or in the simplest case, among competing point estimates of a parameter of a model. There are four general steps involved in a likelihood analysis: (1) model specification, (2) parameter estimation using maximum likelihood methods, (3) model comparison, and (4) model evaluation. Our goal in this paper is to review recent developments in the use of likelihood methods and modeling for the analysis of neighborhood processes in forest ecosystems. We will focus on a single class of processes, seed dispersal and seedling dispersion, because recent papers provide compelling evidence of the potential power of the approach, and illustrate some of the statistical challenges in applying the methods.

Neighborhood analyses of canopy tree competition along environmental gradients in New England forests.

We use permanent-plot data from the USDA Forest Service's Forest Inventory and Analysis (FIA) program for an analysis of the effects of competition on tree growth along environmental gradients for the 14 most abundant tree species in forests of northern New England, USA. Our analysis estimates actual growth for each individual tree of a given species as a function of average potential diameter growth modified by three sets of scalars that quantify the effects on growth of (1) initial target tree size (dbh), (2) local environmental conditions, and (3) crowding by neighboring trees. Potential growth of seven of the 14 species varied along at least one of the two environmental axes identified by an ordination of relative abundance of species in plots. The relative abundances of a number of species were significantly displaced from sites where they showed maximum potential growth. In all of these cases, abundance was displaced to the more resource-poor end of the environmental gradient (either low fertility or low moisture). The pattern was most pronounced among early successional species, whereas late-successional species reached their greatest abundance on sites where they also showed the highest growth in the absence of competition. The analysis also provides empirical estimates of the strength of intraspecific and interspecific competitive effects of neighbors. For all but one of the species, our results led us to reject the hypothesis that all species of competitors have equivalent effects on a target species. Most of the individual pairwise interactions were strongly asymmetric. There was a clear competitive hierarchy among the four most shade-tolerant species, and a separate competitive hierarchy among the shade-intolerant species. Our results suggest that timber yield following selective logging will vary dramatically depending on the configuration of the residual canopy, because of interspecific variation in the magnitude of both the competitive effects of different species of neighbors and the competitive responses of different species of target trees to neighbors. The matrix of competition coefficients suggests that there may be clear benefits in managing for specific mixtures of species within local neighborhoods within stands.

Reconciling niche and neutrality: the continuum hypothesis.

In this study, we ask if instead of being fundamentally opposed, niche and neutral theories could simply be located at the extremes of a continuum. First, we present a model of recruitment probabilities that combines both niche and neutral processes. From this model, we predict and test whether the relative importance of niche vs. neutral processes in controlling community dynamics will vary depending on community species richness, niche overlap and dispersal capabilities of species (both local and long distance). Results demonstrate that niche and neutrality form ends of a continuum from competitive to stochastic exclusion. In the absence of immigration, competitive exclusion tends to create a regular spacing of niches. However, immigration prevents the establishment of a limiting similarity. The equilibrium community consists of a set of complementary and redundant species, with their abundance determined, respectively, by the distribution of environmental conditions and the amount of immigration.

Interspecific and intraspecific variation in tree seedling survival: effects of allocation to roots versus carbohydrate reserves.

We examined interspecific and intraspecific variation in tree seedling survival as a function of allocation to carbohydrate reserves and structural root biomass. We predicted that allocation to carbohydrate reserves would vary as a function of the phenology of shoot growth, because of a hypothesized tradeoff between aboveground growth and carbohydrate storage. Intraspecific variation in levels of carbohydrate reserves was induced through experimental defoliation of naturally occurring, 2-year-old seedlings of four northeastern tree species -Acer rubrum, A. saccharum, Quercus rubra, and Prunus serotina- with shoot growth strategies that ranged from highly determinate to indeterminate. Allocation to root structural biomass varied among species and as a function of light, but did not respond to the defoliation treatments. Allocation to carbohydrate reserves varied among species, and the two species with the most determinate shoot growth patterns had the highest total mass of carbohydrate reserves, but not the highest concentrations. Both the total mass and concentrations of carbohydrate reserves were significantly reduced by defoliation. Seedling survival during the year following the defoliation treatments did not vary among species, but did vary dramatically in response to defoliation. In general, there was an approximately linear relationship between carbohydrate reserves and subsequent survival, but no clear relationship between allocation to root structural biomass and subsequent survival. Because of the disproportionate amounts of reserves stored in roots, we would have erroneously concluded that allocation to roots was significantly and positively related to seedling survival if we had failed to distinguish between reserves and structural biomass in roots.