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The distribution of plant species along environmental gradients is expected to be predictable based on organismal function. Plant functional trait research has shown that trait values generally vary predictably along broad-scale climatic and soil gradients. This work has also demonstrated that at any one point along these gradients there is a large amount of interspecific trait variation. The present research proposes that this variation may be explained by the local-scale sorting of traits along soil fertility and acidity axes. Specifically, we predicted that trait values associated with high resource acquisition and growth rates would be found on soils that are more fertile and less acidic. We tested the expected relationships at the species-level and quadrat-level (20x20 m) using two large forest plots in Panama and China that contain over 450 species combined. Predicted relationships between leaf area and wood density and soil fertility were supported in some instances, but the majority of the predicted relationships were rejected. Alternative resource axes, such as light gradients, therefore likely play a larger role in determining the interspecific variability in plant functional traits in the two forests studied. [ABSTRACT FROM AUTHOR]

Ecology Letters (2010) 13: 695–704 How extraordinary numbers of species can coexist in hyper-diverse communities remains unresolved. While numerous hypotheses have been proposed based on observational and theoretical investigations, little is known about which mechanisms are truly active in forest communities and less is known about their relative contributions to community assembly. In this study, generalized linear mixed models with crossed random effects were used to assess the relative contributions of density dependence and habitat association to community-level diversity maintenance. Species habitat associations were classified based on soil nutrients, topography and species composition. Local neighbourhood effects were also addressed with spatially explicit models of seedling survival. The results shown here reveal that local- and community-level seedling dynamics were consistent with density-dependent predictions, although habitat association played a more important role in shaping short-term seedling survival. We conclude that density dependence could promote species coexistence on the premise of habitat partitioning. [ABSTRACT FROM AUTHOR]

Although negative conspecific density dependence among neighbours is widely studied, the general prevalence of the effects is still poorly understood due to a lack of studies from zonal forests other than the tropics. In addition, the detection of density dependence may be confounded by the influence of habitat heterogeneity. Here we examined the spatial distributions of 47 common tree species (diameter at breast height≥1 cm) using the pair-correlation function g(r) in a fully mapped 24-ha subtropical forest in China. We first investigated whether habitat heterogeneity influenced tree distributions, and then examined the conspecific tree patterns and density dependence after removing the effects of habitat heterogeneity. We found that the forest plot exhibited strong large-scale heterogeneity in the distribution of both large adult trees of different growth forms and individual species. After the habitat heterogeneity was accounted for, 39 of the 47 species (83.0%) were found to exhibit density dependence predominantly at close distances among neighbors. Our findings highlight density dependence as a prevalent mechanism for regulating the population spatial structure of most tree species in the species-rich subtropical forest studied here. Furthermore, the occurrence of density dependence is closely associated with species abundance and the strength of conspecific aggregation at local scales. Abundant species with high strength of conspecific aggregation tend to show density dependence. [ABSTRACT FROM AUTHOR]

Species-area relationships (SARs) characterize the spatial distribution of species diversity in community ecology, but the biological mechanisms underlying the SARs have not been fully explored. Here, we examined the roles of dispersal limitation and habitat heterogeneity in shaping SARs in two large-scale forest plots. One is a 24-ha subtropical forest in Gutianshan National Nature Reserve, China. The other is a 50-ha tropical rain forest in Barro Colorado Island, Panama. Spatial point pattern models were applied to investigate the contributions of dispersal and habitat heterogeneity and their interactions to the formation of the SARs in the two sites. The results showed that, although dispersal and habitat heterogeneity each could significantly contribute to the SARs, each alone was insufficient to explain the SARs. Their joint effects sufficiently explained the real SARs, suggesting that heterogeneous habitat and dispersal limitation are two predominant mechanisms for maintaining the spatial distributions of the species in these two forests. These results add to our understanding of the ecological processes underlying the spatial variation of SARs in natural forest communities. [ABSTRACT FROM AUTHOR]

The classical environmental control model assumes that species distribution is determined by the spatial variation of underlying habitat conditions. This niche-based model has recently been challenged by the neutral theory of biodiversity which assumes that ecological drift is a key process regulating species coexistence. Understanding the mechanisms that maintain biodiversity in communities critically depends on our ability to decompose the variation of diversity into the contributions of different processes affecting it. Here we investigated the effects of pure habitat, pure spatial, and spatially structured habitat processes on the distributions of species richness and species composition in a recently established 24-ha stem-mapping plot in the subtropical evergreen broad-leaved forest of Gutianshan National Nature Reserve, in East China. We used the new spatial analysis method of principal coordinates of neighbor matrices (PCNM) to disentangle the contributions of these processes. The results showed that (1) habitat and space jointly explained ∼53% of the variation in richness and ∼65% of the variation in species composition, depending on the scale (sampling unit size); (2) tree diversity (richness and composition) in the Gutianshan forest was dominantly controlled by spatially structured habitat (24%) and habitat-independent spatial component (29%); the spatially independent, habitat contributed a negligible effect (6%); (3) distributions of richness and species composition were strongly affected by altitude and terrain convexity, while the effects of slope and aspect were weak; (4) the spatial distribution of diversity in the forest was dominated by broad-scaled spatial variation; (5) environmental control on the one hand and unexplained spatial variation on the other (unmeasured environmental variables and neutral processes) corresponded to spatial structures with different scales in the Gutianshan forest plot; and (6) five habitat types were recognized; a few species were statistically significant indicators of three of these habitats, whereas two habitats had no significant indicator species. The results suggest that the diversity of the forest is equally governed by environmental control (30%) and neutral processes (29%). In the fine-scale analysis (10 x 10 m cells), neutral processes dominated (43%) over environmental control (20%). [ABSTRACT FROM AUTHOR]

In this paper, we compare the relationship between scale and period in ecological pattern analysis and wavelet analysis. We also adapt a commonly used wavelet, the Morlet, to ecological pattern analysis. Using Monte Carlo assessments, we apply methods of statistical significance test to wavelet analysis for pattern analysis. In order to understand the inherent strength and weakness of the Morlet and the Mexican Hat wavelets, we also investigate and compare the properties of two frequently used wavelets by testing with field data and four artificial transects of different typical patterns which is often encountered in ecological research. It is shown that the Mexican Hat provides better detection and localization of patch and gap events over the Morlet, whereas the Morlet offers improved detection and localization of scale over the Mexican Hat. There is always a trade-off between the detection and localization of scale versus patch and gap events. Therefore, the best composite analysis is the combination of their advantages. The properties of wavelet in dealing with ecological data may be affected by characteristics intrinsic to wavelet itself. The peaks of different scales in isograms of wavelet power spectrum from the Mexican Hat may overlap with each other. Alternatively, these peaks of different scales in isograms of wavelet power spectrum may combine with each other unless the size of the analyzed scales is significantly different. These overlapping or combining lead to combining of peaks for different scales, or the masking of trough between peaks of different scales in the scalogram. Ecologists should combine all the information in scalogram and isograms of wavelet coefficient and wavelet power spectrum from different wavelets, which can provide us a broader view and precise pattern information. [ABSTRACT FROM AUTHOR]