Common spatial patterns of trees in various tropical forests: Small trees are associated with increased diversity at small spatial scales

Tropical forests are notable for their high species diversity, even on small spatial scales, and right-skewed species and size abundance distributions. The role of individual species as drivers of the spatial organization of diversity in these forests has been explained by several hypotheses and processes, for example, stochastic dilution, negative density dependence, or gap dynamics. These processes leave a signature in spatial distribution of small trees, particularly in the vicinity of large trees, likely having stronger effects on their neighbors. We are exploring species diversity patterns within the framework of various diversity-generating hypotheses using individual species-area relationships. We used the data from three tropical forest plots (Wanang-Papua New Guinea, Barro Colorado Island-Panama, and Sinharaja-Sri Lanka) and included also the saplings (DBH ≥ 1 cm). Resulting cross-size patterns of species richness and evenness reflect the dynamics of saplings affected by the distribution of large trees. When all individuals with DBH ≥1 cm are included, ~50% of all tree species from the 25- or 50-ha plot can be found within 35 m radius of an individual tree. For all trees, 72%-78% of species were identified as species richness accumulators, having more species present in their surroundings than expected by null models. This pattern was driven by small trees as the analysis of DBH >10 cm trees showed much lower proportion of accumulators, 14%-65% of species identified as richness repellers and had low richness of surrounding small trees. Only 11%-26% of species had lower species evenness than was expected by null models. High proportions of species richness accumulators were probably due to gap dynamics and support Janzen-Connell hypothesis driven by competition or top-down control by pathogens and herbivores. Observed species diversity patterns show the importance of including small tree size classes in analyses of the spatial organization of diversity.

Plant functional types determine how close postfire seedlings are from their parents in a species-rich shrubland

BACKGROUND AND AIMS

Fine-scale spatial patterns of the seedlings of co-occurring species reveal the relative success of reproduction and dispersal and may help interpret coexistence patterns of adult plants. To understand whether postfire community dynamics are controlled by mathematical, biological or environmental factors, we documented seedling-adult (putative parent) distances for a range of co-occurring species. We hypothesized that nearest-seedling-to-adult distances should be a function of the distance between the closest conspecific seedlings, closest inter-adult distances and seedling-to-parent ratios, and also that these should scale up in a consistent way from all individuals, to within and between species and finally between functional types (FTs).

METHODS

We assessed seedling-adult, seedling-seedling and adult-adult distances for 19 co-occurring shrub species 10 months after fire in a species-rich shrubland in south-western Australia. Species were categorized into 2 × 2 FTs: those that are killed by fire [non-(re)sprouters] vs. those that survive (resprouters) in nine taxonomically matched pairs, and those that disperse their seeds prefire (geosporous) vs. those that disperse their seeds postfire (serotinous).

KEY RESULTS

For the total data set and means for all species, seedling-adult distance was essentially a mathematical phenomenon, and correlated positively with seedling-seedling distance and adult-adult distance, and inversely with seedlings per adult. Among the four FTs, seedling-adult distance was shortest for geosporous non-sprouters and widest for serotinous resprouters. Why adults that produce few seedlings (resprouters) should be further away from them defies a simple mathematical or biological explanation at present. Ecologically, however, it is adaptive: the closest seedling was usually under the (now incinerated) parent crown of non-sprouters whereas those of resprouters were on average four times further away.

CONCLUSIONS

Our study highlights the value of recognizing four reproductive syndromes within fire-prone vegetation, and shows how these are characterized by marked differences in their seedling-adult spatial relations that serve to enhance biodiversity of the community.

Silhouette width using generalized mean-A flexible method for assessing clustering efficiency

Cluster analysis plays vital role in pattern recognition in several fields of science. Silhouette width is a widely used index for assessing the fit of individual objects in the classification, as well as the quality of clusters and the entire classification. Silhouette combines two clustering criteria, compactness and separation, which imply that spherical cluster shapes are preferred over others-a property that can be seen as a disadvantage in the presence of complex, nonspherical clusters, which is common in real situations. We suggest a generalization of the silhouette width using the generalized mean. By changing the p parameter of the generalized mean between -∞ and +∞, several specific summary statistics, including the minimum, maximum, the arithmetic, harmonic, and geometric means, can be reproduced. Implementing the generalized mean in the calculation of silhouette width allows for changing the sensitivity of the index to compactness versus connectedness. With higher sensitivity to connectedness, the preference of silhouette width toward spherical clusters should reduce. We test the performance of the generalized silhouette width on artificial data sets and on the Iris data set. We examine how classifications with different numbers of clusters prepared by different algorithms are evaluated, if p is set to different values. When p was negative, well-separated clusters achieved high silhouette widths despite their elongated or circular shapes. Positive values of p increased the importance of compactness; hence, the preference toward spherical clusters became even more detectable. With low p, single linkage clustering was deemed the most efficient clustering method, while with higher parameter values the performance of group average, complete linkage, and beta flexible with beta = -0.25 seemed better. The generalized silhouette allows for adjusting the contribution of compactness and connectedness criteria, thus avoiding underestimation of clustering efficiency in the presence of clusters with high internal heterogeneity.

When do we have the power to detect biological interactions in spatial point patterns?

Uncovering the roles of biotic interactions in assembling and maintaining species-rich communities remains a major challenge in ecology. In plant communities, interactions between individuals of different species are expected to generate positive or negative spatial interspecific associations over short distances. Recent studies using individual-based point pattern datasets have concluded that (a) detectable interspecific interactions are generally rare, but (b) are most common in communities with fewer species; and (c) the most abundant species tend to have the highest frequency of interactions. However, it is unclear how the detection of spatial interactions may change with the abundances of each species, or the scale and intensity of interactions. We ask if statistical power is sufficient to explain all three key results.We use a simple two-species model, assuming no habitat associations, and where the abundances, scale and intensity of interactions are controlled to simulate point pattern data. In combination with an approximation to the variance of the spatial summary statistics that we sample, we investigate the power of current spatial point pattern methods to correctly reject the null model of pairwise species independence.We show the power to detect interactions is positively related to both the abundances of the species tested, and the intensity and scale of interactions, but negatively related to imbalance in abundances. Differences in detection power in combination with the abundance distributions found in natural communities are sufficient to explain all the three key empirical results, even if all pairwise interactions are identical. Critically, many hundreds of individuals of both species may be required to detect even intense interactions, implying current abundance thresholds for including species in the analyses are too low. Sy n thesis. The widespread failure to reject the null model of spatial interspecific independence could be due to low power of the tests rather than any key biological process. Since we do not model habitat associations, our results represent a first step in quantifying sample sizes required to make strong statements about the role of biotic interactions in diverse plant communities. However, power should be factored into analyses and considered when designing empirical studies.

Spatially Explicit Metrics of Species Diversity, Functional Diversity, and Phylogenetic Diversity: Insights into Plant Community Assembly Processes

Spatial processes underlie major species coexistence mechanisms. A range of spatial analysis techniques are increasingly applied to data of fully mapped communities to quantify spatial structures in species and phylogenetic and functional diversity at some given spatial scale with the goal of gaining insights into processes of community assembly and dynamics. We review these techniques, including spatial point pattern analysis, quadrat-based analyses, and individual-based neighborhood models, and provide a practical roadmap for ecologists in the analysis of local spatial structures in species and phylogenetic and functional diversity. We show how scale-dependent metrics of spatial diversity can be used in concert with ecological null models, statistical models, and dynamic community simulation models to detect spatial patterns, reveal the influence of the biotic neighborhood on plant performance, and quantify the relative contribution of species interactions, habitat heterogeneity, and stochastic processes to community assembly across scale. Future works should integrate these approaches into a dynamic spatiotemporal framework.