Analyzing tropical forest tree species abundance distributions using a nonneutral model and through approximate Bayesian inference

The neutral theory of biodiversity challenges the classical niche-based view of ecological communities, where species attributes and environmental conditions jointly determine community composition. Functional equivalence among species, as assumed by neutral ecological theory, has been recurrently falsified, yet many patterns of tropical tree communities appear consistent with neutral predictions. This may mean that neutral theory is a good first-approximation theory or that species abundance data sets contain too little information to reject neutrality. Here we present a simple test of neutrality based on species abundance distributions in ecological communities. Based on this test, we show that deviations from neutrality are more frequent than previously thought in tropical forest trees, especially at small spatial scales. We then develop a nonneutral model that generalizes Hubbell's dispersal-limited neutral model in a simple way by including one additional parameter of frequency dependence. We also develop a statistical method to infer the parameters of this model from empirical data by approximate Bayesian computation. In more than half of the permanent tree plots, we show that our new model fits the data better than does the neutral model. Finally, we discuss whether observed deviations from neutrality may be interpreted as the signature of environmental filtering on tropical tree species abundance distributions.     

Age structure in neutral theory resolves inconsistencies related to reproductive-size threshold

Aims Neutral theory consists of a suite of models that assume ecological equivalence among individual organisms. They have been most commonly applied to tropical forest tree communities either as null models or as approximations. Neutral models typically only include reproductive adults; therefore, fitting to empirical tree community data requires defining a reproductive-size threshold, which for trees is usually set arbitrarily to a diameter at breast height (DBH) of 100 mm. The inevitable exclusion of some reproductive adults and inclusion of some saplings cause a non-random sampling bias in neutral model fits. Here, we investigate this problem and resolve it by introducing simple age structure into a neutral model.Methods We compared the performance and sensitivity of DBH threshold of three variants of a spatially explicit neutral model: the traditional model, a model incorporating random sampling and a model with two distinct age classes—reproductive adults and saplings. In the age-structured model, saplings are offspring from adults that disperse according to a Gaussian dispersal kernel around the adults. The only extra parameter is the ratio of adults to saplings, which is not a free parameter but directly measurable. We used species–area relationships (SARs) to explore the predicted effect of saplings on the species richness at different scales in our model. We then evaluated the three model variations to find the parameters required to maintain the observed level of species richness in the 50-ha plot on Barro Colorado Island (BCI). We repeated our analysis filtering the data at different minimum tree-size thresholds in order to find the effect this threshold has on our results. Lastly, we used empirical species–individual relationships (SIRs) to test the pre-existing hypothesis that environmental filtering is the primary cause of differences between the assemblage of saplings and that of adults on BCI.Important findings Our age-structured neutral model was characterized by SARs that were insensitive to the presence of saplings at large scales and highly sensitive to them at small scales. Both models without age structure were highly sensitive to the DBH threshold chosen in a way that could not be explained based on random samplings alone. The age-structured neutral model, which allowed for non-random sampling based on life stage, was consistent with species richness observations. Our analysis of empirical SIRs did not support environmental filtering as a dominant force, but it did show evidence for other differences between age classes. Age can now be easily incorporated into future studies of neutral models whenever there is a concern that a sample is not entirely composed of reproductive adult individuals. More generally, we suggest that modeling studies using tree data subject to a minimum size threshold should consider the sensitivity of their results to that threshold.     

Estimating and interpreting migration of Amazonian forests using spatially implicit and semi‐explicit neutral models

With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large‐scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi‐explicit simulations based on three large‐scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi‐explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi‐explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)‐neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of being an effective mechanistic parameter and spatially implicit models should be rejected as an approximation of forest dynamics.     

Analysis of spatial patterns informs community assembly and sampling requirements for Collembola in forest soils

The relative importance of niche separation, non-equilibrial and neutral models of community assembly has been a theme in community ecology for many decades with none appearing to be applicable under all circumstances. In this study, Collembola species abundances were recorded over eleven consecutive years in a spatially explicit grid and used to examine (i) whether observed beta diversity differed from that expected under conditions of neutrality, (ii) whether sampling points differed in their relative contributions to overall beta diversity, and (iii) the number of samples required to provide comparable estimates of species richness across three forest sites. Neutrality could not be rejected for 26 of the forest by year combinations. However, there is a trend toward greater structure in the oldest forest, where beta diversity was greater than predicted by neutrality on five of the eleven sampling dates. The lack of difference in individual- and sample-based rarefaction curves also suggests randomness in the system at this particular scale of investigation. It seems that Collembola communities are not spatially aggregated and assembly is driven primarily by neutral processes particularly in the younger two sites. Whether this finding is due to small sample size or unaccounted for environmental variables cannot be determined. Variability between dates and sites illustrates the potential of drawing incorrect conclusions if data are collected at a single site and a single point in time.     

Modes of speciation and the neutral theory of biodiversity

Hubbell's neutral theory of biodiversity has generated much debate over the need for niches to explain biodiversity patterns. Discussion of the theory has focused on its neutrality assumption, i.e. the functional equivalence of species in competition and dispersal. Almost no attention has been paid to another critical aspect of the theory, the assumptions on the nature of the speciation process. In the standard version of the neutral theory each individual has a fixed probability to speciate. Hence, the speciation rate of a species is directly proportional to its abundance in the metacommunity. We argue that this assumption is not realistic for most speciation modes because speciation is an emergent property of complex processes at larger spatial and temporal scales and, consequently, speciation rate can either increase or decrease with abundance. Accordingly, the assumption that speciation rate is independent of abundance (each species has a fixed probability to speciate) is a more natural starting point in a neutral theory of biodiversity. Here we present a neutral model based on this assumption and we confront this new model to 20 large data sets of tree communities, expecting the new model to fit the data better than Hubbell's original model. We find, however, that the data sets are much better fitted by Hubbell's original model. This implies that species abundance data can discriminate between different modes of speciation, or, stated otherwise, that the mode of speciation has a large impact on the species abundance distribution. Our model analysis points out new ways to study how biodiversity patterns are shaped by the interplay between evolutionary processes (speciation, extinction) and ecological processes (competition, dispersal).     

Non‐zero‐sum neutrality test for the tropical rain forest community using long‐term between‐census data

For community ecologists, “neutral or not?” is a fundamental question, and thus, rejecting neutrality is an important first step before investigating the deterministic processes underlying community dynamics. Hubbell''s neutral model is an important contribution to the exploration of community dynamics, both technically and philosophically. However, the neutrality tests for this model are limited by a lack of statistical power, partly because the zero‐sum assumption of the model is unrealistic. In this study, we developed a neutrality test for local communities that implements non‐zero‐sum community dynamics and determines the number of new species (N _sp) between observations. For the non‐zero‐sum neutrality test, the model distributed the expected N _sp, as calculated by extensive simulations, which allowed us to investigate the neutrality of the observed community by comparing the observed N _sp with distributions of the expected N _sp derived from the simulations. For this comparison, we developed a new “non‐zero‐sum N _sp test,” which we validated by running multiple neutral simulations using different parameter settings. We found that the non‐zero‐sum N _sp test rejected neutrality at a near‐significance level, which justified the validity of our approach. For an empirical test, the non‐zero‐sum N _sp test was applied to real tropical tree communities in Panama and Malaysia. The non‐zero‐sum N _sp test rejected neutrality in both communities when the observation interval was long and N _sp was large. Hence, the non‐zero‐sum N _sp test is an effective way to examine neutrality and has reasonable statistical power to reject the neutral model, especially when the observed N _sp is large. This unique and simple approach is statistically powerful, even though it only employs two temporal sequences of community data. Thus, this test can be easily applied to existing datasets. In addition, application of the test will provide significant benefits for detecting changing biodiversity under climate change and anthropogenic disturbance.     

Comparing Allee effect-based and dispersal-based neutral models for species abundance distribution patterns

Dispersal is important for biodiversity maintenance in both neutral and niche theories. However, little is known about the potential role of Allee effect at the community level. In the present study, we developed neutral models for quantifying the separate and joint influences of the Allee effect and dispersal process, respectively, on species abundance distribution (SAD) patterns. Tree census data from Barro Colorado Island (BCI), Panama were used as the case to compare different neutral SAD models. Results showed that Allee effects were not detected in the BCI tree SAD curve. By contrast, the neutral models with the incorporation of dispersal process (including both immigration and emigration) can remarkably improve the fitting power of neutral models on the BCI tree SAD curve. Finally, even though the influence is not detectable, the Allee effect-based SAD models still might be alternative SAD models for model comparison and null hypothesis testing.     

Quantification of the intra-plot correlation in plant abundance data: A possible test of the neutral theory

A method for summarising the degree of spatial covariance (intra-plot correlation) among different plant species using plant abundance data is presented. The method will provide an alternative test of the hypothesis of neutrality in uniform environments, and we apply it in this study to data derived from two different grasslands. There is a significant positive intra-plot correlation in both grasslands that may be due to either sampling effects or deterministic ecological effects. For the calcareous grassland, we also applied the method to a subset of plant species that are expected to be less influenced by sampling effects, and they also has a significant positive intra-plot correlation, which suggests that sampling effects are playing a minor role in the calcareous grassland as an explanation for the spatial aggregated of species. Overall, the results suggest that the deterministic ecological processes that do not contradict the neutral theory are more important than any possible deterministic ecological processes that contradict the neutral theory. Consequently, the hypothesis of neutrality could neither be rejected nor corroborated in the investigated grasslands. We suggest that the spatial aggregation in the sampled calcareous grassland is mainly caused by small local differences in abiotic factors or in the timing of gaps for recolonisation. This in turn may lead to different local niches (ecological adaptation or phenology of establishment from seeds) and possibly local exclusion of plant species by interspecific competition.     

The zero-sum assumption in neutral biodiversity theory

The neutral theory of biodiversity as put forward by Hubbell in his 2001 monograph has received much criticism for its unrealistic simplifying assumptions. These are the assumptions of functional equivalence among different species (neutrality), the assumption of point mutation speciation, and the assumption that resources are continuously saturated, such that constant resource availability implies constant community size (zero-sum assumption). Here we focus on the zero-sum assumption. We present a general theory for calculating the probability of observing a particular species-abundance distribution (sampling formula) and show that zero-sum and non-zero-sum formulations of neutral theory have exactly the same sampling formula when the community is in equilibrium. Moreover, for the non-zero-sum community the sampling formula has this same form, even out of equilibrium. Therefore, the term "zero-sum multinomial (ZSM)" to describe species abundance patterns, as coined by Hubbell [2001. The Unified Neutral Theory of Biodiversity and Biogeography, Princeton University Press, Princeton, NJ], is not really appropriate, as it also applies to non-zero-sum communities. Instead we propose the term "dispersal-limited multinomial (DLM)", thus making explicit one of the most important contributions of neutral community theory, the emphasis on dispersal limitation as a dominant factor in determining species abundances.     

Non‐neutrality in forest communities: evolutionary and ecological determinants of tree species abundance distributions

The unified neutral theory of biodiversity and biogeography provides a promising framework that can be used to integrate stochastic and ecological processes operating in ecological communities. Based on a mechanistic non‐neutral model that incorporates density‐dependent mortality, we evaluated the deviation from a neutral pattern in tree species abundance distributions and explored the signatures of historical and ecological processes that have shaped forest biomes. We compiled a dataset documenting species abundance distributions in 1168 plots encompassing 16 973 tree species across tropical, temperate, and boreal forests. We tested whether deviations from neutrality of species abundance distributions vary with climatic and historical conditions, and whether these patterns differ among regions. Non‐neutrality in species abundance distributions was ubiquitous in tropical, temperate, and boreal forests, and regional differences in patterns of non‐neutrality were significant between biomes. Species abundance evenness/unevenness caused by negative density‐dependent or abiotic filtering effects had no clear macro‐scale climatic drivers, although temperature was non‐linearly correlated with species abundance unevenness on a global scale. These findings were not significantly biased by heterogeneity of plot data (the differences of plot area, measurement size, species richness, and the number of individuals sampled). Therefore, our results suggest that environmental filtering is not universally increasing from warm tropical to cold boreal forests, but might affect differently tree species assembly between and within biomes. Ecological processes generating particularly dominant species in local communities might be idiosyncratic or region‐specific and may be associated with geography and climate. Our study illustrates that stochastic dynamical models enable the analysis of the interplay of historical and ecological processes that influence community assemblies and the dynamics of biodiversity.     

Liana Abundance,Diversity, and Distribution on Barro Colorado Island,Panama

Lianas are a key component of tropical forests; however, most surveys are too small to accurately quantify liana community composition, diversity, abundance, and spatial distribution – critical components for measuring the contribution of lianas to forest processes. In 2007, we tagged, mapped, measured the diameter, and identified all lianas ≥1 cm rooted in a 50-ha plot on Barro Colorado Island, Panama (BCI). We calculated liana density, basal area, and species richness for both independently rooted lianas and all rooted liana stems (genets plus clones). We compared spatial aggregation patterns of liana and tree species, and among liana species that varied in the amount of clonal reproduction. We also tested whether liana and tree densities have increased on BCI compared to surveys conducted 30-years earlier. This study represents the most comprehensive spatially contiguous sampling of lianas ever conducted and, over the 50 ha area, we found 67,447 rooted liana stems comprising 162 species. Rooted lianas composed nearly 25% of the woody stems (trees and lianas), 35% of woody species richness, and 3% of woody basal area. Lianas were spatially aggregated within the 50-ha plot and the liana species with the highest proportion of clonal stems more spatially aggregated than the least clonal species, possibly indicating clonal stem recruitment following canopy disturbance. Over the past 30 years, liana density increased by 75% for stems ≥1 cm diameter and nearly 140% for stems ≥5 cm diameter, while tree density on BCI decreased 11.5%; a finding consistent with other neotropical forests. Our data confirm that lianas contribute substantially to tropical forest stem density and diversity, they have highly clumped distributions that appear to be driven by clonal stem recruitment into treefall gaps, and they are increasing relative to trees, thus indicating that lianas will play a greater role in the future dynamics of BCI and other neotropical forests.     

Time-dependent solutions of the spatially implicit neutral model of biodiversity

Previous research into the neutral theory of biodiversity has focused mainly on equilibrium solutions rather than time-dependent solutions. Understanding the time-dependent solutions is essential for applying neutral theory to ecosystems in which time-dependent processes, such as succession and invasion, are driving the dynamics. Time-dependent solutions also facilitate tests against data that are stronger than those based on static equilibrium patterns. Here I investigate the time-dependent solutions of the classic spatially implicit neutral model, in which a small local community is coupled to a much larger metacommunity through immigration. I present explicit general formulas for the eigenvalues, left eigenvectors and right eigenvectors of the models’s transition matrix. The time-dependent solutions can then be expressed in terms of these eigenvalues and eigenvectors. Some of these results are translated directly from existing results for the classic Moran model of population genetics (the Moran model is equivalent to the spatially implicit neutral model after a reparameterization); others of the results are new. I demonstrate that the asymptotic time-dependent solution corresponding to just these first two eigenvectors can be a good approximation to the full time-dependent solution. I also demonstrate the feasibility of a partial eigendecomposition of the transition matrix, which facilitates direct application of the results to a biologically relevant example in which a newly invading species is initially present in the metacommunity but absent from the local community.     

Selection and Biased Gene Conversion in a Multigene Family: Consequences of Interallelic Bias and Threshold Selection

In a previous paper, I investigated the interactions in a gene family of additive selection and biased gene conversion in a finite population when conversion events are rare. Here I extend my "weak-conversion limit" model by allowing biased interallelic conversion (conversion between alleles at the same locus) of arbitrary frequency and various threshold selection schemes for rare interlocus conversion events. I suggest that it is not unreasonable for gene families to experience threshold fitness functions, and show that certain types of thresholds can greatly constrain the rate at which advantageous alleles are fixed as compared to other fitness schemes, such as additive selection. It is also shown that the double sampling process operating on a gene family in a finite population (sampling over the number of genes in the gene family and over the number of individuals in the population) can have interesting consequences. For selectively neutral alleles that experience interallelic bias, the probability of fixation at each single locus may be essentially neutral, but the cumulative effects on the entire gene family of small departures from neutrality can be significant, especially if the gene family is large. Thus, in some situations, gene families can respond to directional forces that are weak in comparison to drift at single loci.     

Constant tree species richness along an elevational gradient of Mt. Bokor,a table-shaped mountain in southwestern Cambodia

Some previous studies along an elevational gradient on a tropical mountain documented that plant species richness decreases with increasing elevation. However, most of studies did not attempt to standardize the amount of sampling effort. In this paper, we employed a standardized sampling effort to study tree species richness along an elevational gradient on Mt. Bokor, a table-shaped mountain in southwestern Cambodia, and examined relationships between tree species richness and environmental factors. We used two methods to record tree species richness: first, we recorded trees taller than 4 m in 20 uniform plots (5 × 100 m) placed at 266–1048-m elevation; and second, we collected specimens along an elevational gradient from 200 to 1048 m. For both datasets, we applied rarefaction and a Chao1 estimator to standardize the sampling efforts. A generalized linear model (GLM) was used to test the relationship of species richness with elevation. We recorded 308 tree species from 20 plots and 389 tree species from the general collections. Species richness observed in 20 plots had a weak but non-significant correlation with elevation. Species richness estimated by rarefaction or Chao1 from both data sets also showed no significant correlations with elevation. Unlike many previous studies, tree species richness was nearly constant along the elevational gradient of Mt. Bokor where temperature and precipitation are expected to vary. We suggest that the table-shaped landscape of Mt. Bokor, where elevational interval areas do not significantly change between 200 and 900 m, may be a determinant of this constant species richness.     

Sensitivity of phylogeny estimation to taxonomic sampling

Recent studies have shown that addition or deletion of taxa from a data matrix can change the estimate of phylogeny. I used 29 data sets from the literature to examine the effect of taxon sampling on phylogeny estimation within data sets. I then used multiple regression to assess the effect of number of taxa, number of characters, homoplasy, strength of support, and tree symmetry on the sensitivity of data sets to taxonomic sampling. Sensitivity to sampling was measured by mapping characters from a matrix of culled taxa onto optimal trees for that reduced matrix and onto the pruned optimal tree for the entire matrix, then comparing the length of the reduced tree to the length of the pruned complete tree. Within-data-set patterns can be described by a second-order equation relating fraction of taxa sampled to sensitivity to sampling. Multiple regression analyses found number of taxa to be a significant predictor of sensitivity to sampling; retention index, number of informative characters, total support index, and tree symmetry were nonsignificant predictors. I derived a predictive regression equation relating fraction of taxa sampled and number of taxa potentially sampled to sensitivity to taxonomic sampling and calculated values for this equation within the bounds of the variables examined. The length difference between the complete tree and a subsampled tree was generally small (average difference of 0-2.9 steps), indicating that subsampling taxa is probably not an important problem for most phylogenetic analyses using up to 20 taxa.     

Randomvs non-random sampling: Effects on patterns of species abundance, species richness and vegetation-environment relationships

From a strictly statistical perspective, most of the commonly used statistical tests cannot be performed on vegetation data obtained using a non-random sampling design. Despite this, non-randomly sampled plots such as phytosociological relevés still make sense: because they may focus on objectives not appropriately addressed by random sampling, such as the study of rare plant communities or species; and because random sampling is often more time-demanding and expensive. Considering the huge body of phytosociological data available, an interesting question arises: if we compare randomly and non-randomly sampled data sets, to what extent do the results of our analyses differ with respect to various species and vegetation parameters? We present an attempt to tackle this question by comparing two data sets collected in a 25 km² area close to the city of Bremen, northwestern Germany: the first data set consisted of 30 subjectively (non-randomly) placed, homogeneous plots across different plant communities, each of which was laid out in a nested design including 9 sizes from 0.5 m² to 1,000 m². The second data set consisted of 30 (again nested) plots randomly selected and located with a GPS device; plots were rejected only if they for some reason were inaccessible. The data collection was the same for both data sets: presence-absence of all vascular plants was recorded for the different plot sizes, and soil samples were collected for the determination of the values of some important environmental variables. For the comparison of the two data sets, we used either the complete data sets or sub-sets of those plots located in woodlands. The main results included the following: (1) Species abundance patterns: Random sampling resulted in a larger number of common and a smaller number of rare species than non-random sampling. (2) Species richness at different spatial scales: For the small plot sizes, the number of species in the non-randomly placed plots was higher than in the randomly placed plots, while the differences were less pronounced at larger spatial scales. As a consequence, also the parameters of species-area curves differed between the data sets, especially in the sub-set including woodland plots. (3) Vegetation differentiation: In random sampling, there was considerable redundancy, i.e., there were several plots with high floristic similarity. (4) Vegetation-environment relationships: The ordination scores of the non-randomly placed plots showed a larger number of significant correlations to soil parameters than the scores of randomly placed plots. The results suggest that conclusions drawn from the analysis of non-randomly placed plots such as phytosociological relevés may be biased, especially regarding estimates of species abundance and species richness patterns.     

Variance and spatial scales in a tropical rain forest: changing the size of sampling units

The size of a sampling unit has a critical effect on our perception of ecological phenomena; it influences the variance and correlation structure estimates of the data. Classical statistical theory works well to predict the changes in variance when there is no autocorrelation structure, but it is not applicable when the data are spatially autocorrelated. Geostatistical theory, on the other hand, uses analytical relationships to predict the variance and autocorrelation structure that would be observed if a survey was conducted using sampling units of a different size. To test the geostatistical predictions, we used information about individual tree locations in the tropical rain forest of the Pasoh Reserve, Malaysia. This allowed us to simulate and compare various sampling designs. The original data were reorganised into three artificial data sets, computing tree densities (number of trees per square meter in each quadrat) corresponding to three quadrat sizes (5×5, 10×10 and 20×20 m⁽²⁾). Based upon the 5×5 m⁽²⁾ data set, the spatial structure was modelled using a random component (nugget effect) plus an exponential model for the spatially structured component. Using the within-quadrat variances inferred from the variogram model, the change of support relationships predicted the spatial autocorrelation structure and new variances corresponding to 10×10 m⁽²⁾ and 20×20 m⁽²⁾ quadrats. The theoretical and empirical results agreed closely, while the classical approach would have largely underestimated the variance. As quadrat size increases, the range of the autocorrelation model increases, while the variance and proportion of noise in the data decrease. Large quadrats filter out the spatial variation occurring at scales smaller than the size of their sampling units, thus increasing the proportion of spatially structured component with range larger than the size of the sampling units.     

Modeling the spatial distribution and fruiting pattern of a key tree species in a neotropical forest: methodology and potential applications

Background

The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama.

Methodology and Principal Findings

Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI.

Conclusions and Significance

We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.     

Variation in modes and rates of evolution in nuclear and mitochondrial ribosomal DNA in the mushroom genus Amanita (Agaricales, Basidiomycota): phylogenetic implications

Modes and rates of molecular evolution, and congruence and combinability for phylogenetic reconstruction, of portions of the nuclear large ribosomal subunit (nLSU-rDNA) and mitochondrial small subunit (mtSSU-rDNA) genes were investigated in the mushroom genus Amanita. The AT content was higher in the mtSSU-rDNA than in the nLSU-rDNA. A transition bias in which AT substitutions were as frequent as transitions was present in the mtSSU-rDNA but not in the nLSU-rDNA. Among-sites rate variation in nucleotide substitutions at variable sites was present in the nLSU-rDNA but not in the mtSSU-rDNA. Likelihood ratio tests indicated very different models of evolution for the two molecules. A molecular clock could be rejected for both data sets. Rates of molecular evolution in the two molecules were uncoupled: faster evolutionary rates in the mtSSU-rDNA and nLSU-rDNA were not observed for the same taxa. In separate phylogenetic analyses, the nLSU-rDNA data set had higher phylogenetic resolution. The partition homogeneity test and statistical bootstrap support for branches indicated absence of conflict in the phylogenetic signal in the two data sets; however, tree topologies produced from the separate data sets were not congruent. Heterogeneity in modes and rates of evolution in the two molecules pose difficulties for a combined analysis of the two data sets: the use of equally weighted parsimony is not fully satisfactory when rate heterogeneity is present, and it is impractical to determine a model for maximum-likelihood analysis that fits simultaneously two heterogeneous data sets. Overall topologies produced from either the separated or the combined analyses using various tree reconstruction methods were identical for nearly all statistically significant branches.     

Similar non-random processes maintain diversity in two tropical rainforests.

Quadrat-based analysis of two rainforest plots of area 50 ha, one in Panama (Barro Colorado Island, BCI) and the other in Malaysia (Pasoh), shows that in both plots recruitment is in general negatively correlated with both numbers and biomass of adult trees of the same species in the same quadrat. At BCI, this effect is not significantly influenced by treefall gaps. In both plots, recruitment of individual species is negatively correlated with the numbers of trees of all species in the quadrats, but not with overall biomass. These observations suggest, but do not prove, widespread frequency-dependent effects produced by pathogens and seed-predators that act most effectively in quadrats crowded with trees. Within-species correlations of mortality with numbers or biomass are not found in either plot, indicating that most frequency-dependent mortality takes place before the trees reach 1 cm in diameter. Stochastic effects caused by BCI's more rapid tree turnover may contribute to a larger variance in diversity from quadrat to quadrat at BCI, although they are not sufficient to explain why BCI has fewer than half as many tree species as Pasoh. Finally, in both plots quadrats with low diversity show a significant increase in diversity over time, and this increase is stronger at BCI. This process, like the frequency-dependence, will tend to maintain diversity over time. In general, these non-random forces that should lead to the maintenance of diversity are slightly stronger at BCI, even though the BCI plot is less diverse than the Pasoh plot.