Compositional Divergence and Convergence in Local Communities and Spatially Structured Landscapes

Community structure depends on both deterministic and stochastic processes. However, patterns of community dissimilarity (e.g. difference in species composition) are difficult to interpret in terms of the relative roles of these processes. Local communities can be more dissimilar (divergence) than, less dissimilar (convergence) than, or as dissimilar as a hypothetical control based on either null or neutral models. However, several mechanisms may result in the same pattern, or act concurrently to generate a pattern, and much research has recently been focusing on unravelling these mechanisms and their relative contributions. Using a simulation approach, we addressed the effect of a complex but realistic spatial structure in the distribution of the niche axis and we analysed patterns of species co-occurrence and beta diversity as measured by dissimilarity indices (e.g. Jaccard index) using either expectations under a null model or neutral dynamics (i.e., based on switching off the niche effect). The strength of niche processes, dispersal, and environmental noise strongly interacted so that niche-driven dynamics may result in local communities that either diverge or converge depending on the combination of these factors. Thus, a fundamental result is that, in real systems, interacting processes of community assembly can be disentangled only by measuring traits such as niche breadth and dispersal. The ability to detect the signal of the niche was also dependent on the spatial resolution of the sampling strategy, which must account for the multiple scale spatial patterns in the niche axis. Notably, some of the patterns we observed correspond to patterns of community dissimilarities previously observed in the field and suggest mechanistic explanations for them or the data required to solve them. Our framework offers a synthesis of the patterns of community dissimilarity produced by the interaction of deterministic and stochastic determinants of community assembly in a spatially explicit and complex context.

Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

The role of the seed bank in recovery of temperate heath and blanket bog following wildfires

Questions - Are the germinable seed banks of upland heath and blanket bog reduced following wildfires? Are some species at particular risk? Do the impacts of wildfires on seed banks differ between heathlands and blanket bog?

Location - Northern Ireland, United Kingdom.

Methods - Vegetation surveys and seed bank sampling were conducted in 2012 at burned and unburned areas within six upland sites where large wildfires had occurred during spring 2011. Differences in seedling abundance, species richness and Jaccard similarity indices between burned and unburned areas were compared using GLMMs. Differences in the community composition were examined using pRDA.

Results - In total, 24 of the 51 species in the vegetation were detected in the germinable seed bank. Species richness and the abundance of seedlings other than Calluna vulgaris were lower in areas where wildfires had occurred. Species composition of both germinable seed banks and vegetation differed between burned and unburned areas within sites; with negative associations between burned areas and some key indicator species including Drosera rotundifolia, Eriophorum vaginatum, Empetrum nigrum, Narthecium ossifragum and Trichophorum germanicum. We did not find any evidence of significant interactions between burning and habitat, suggesting that wildfires had similar impacts on each species regardless of the habitat in which they occurred.

Conclusions - This study differs from other UK studies in that it examines impacts of wildfires at sites that have not been previously intensively managed by burning. In particular, we highlight potential impacts on N. ossifragum and D. rotundifolia, which are key components of the upland flora and, to our knowledge, were not present in previous UK studies.