Aim To test whether congeneric species are significantly associated with one another in space, either positively or negatively. Also, to provide a framework for a causal investigation of co-occurrence patterns by a parallel comparison of interactions in geographical and ecological data matrices.Location For the analysis of congeneric species' co-occurrences we used 30 matrices covering a wide range of taxa and geographical areas, while for the causal investigation we used the distribution of 50 terrestrial isopod species on 20 islands and 264 sampling stations in the central Aegean archipelago, as well as a number of ecological variables for each sampling station. MethodsWe developed a software program (  ) that incorporates the speciesby-species approach to co-occurrence analysis using EcoSim's output of prior null model analysis of co-occurrence. We describe this program in detail, and use it to investigate one of the most common assembly rules, namely, the decreased levels of co-occurrence among congeneric species pairs. For the causal analysis, we proceed likewise, cross-checking the results from the geographical and the ecological matrices. There is only one possible combination of results that can support claims for direct competition among species. ResultsWe do not get any strong evidence for widespread competition among congeneric species, while most communities investigated do not show significant patterns of species associations. The causal analysis suggests that the principal factors behind terrestrial isopod species associations are of historical nature. Some exceptional cases are also discussed.Main conclusions Presence/absence data for a variety of taxa do not support the assembly rule that congeneric species are under more intense competition compared to less related species. Also, these same data do not suggest strong interactions among species pairs, regardless of taxonomic status. When significant species associations can be seen in such matrices, they mainly reflect the effects of history or of habitat requirements.

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Complex natural systems, spanning from individuals and populations to ecosystems and social-ecological systems, often exhibit abrupt reorganizations in response to changing stressors, known as regime shifts or critical transitions. Theory suggests that such systems feature folded stability landscapes with fluctuating resilience, fold-bifurcations, and alternate basins of attraction. However, the implementation of such features to elucidate response mechanisms in an empirical context is scarce, due to the lack of generic approaches to quantify resilience dynamics in individual natural systems. Here, we introduce an Integrated Resilience Assessment (IRA) framework: a three-step analytical process to assess resilience and construct stability landscapes of empirical systems. The proposed framework involves a multivariate analysis to estimate holistic system indicator variables, non-additive modelling to estimate alternate attractors, and a quantitative resilience assessment to scale stability landscapes. We implement this framework to investigate the temporal development of the Mediterranean marine communities in response to sea warming during 1985–2013, using fisheries landings data. Our analysis revealed a nonlinear tropicalisation of the Mediterranean Sea, expressed as abrupt shifts to regimes dominated by thermophilic species. The approach exemplified here for the Mediterranean Sea, revealing previously unknown resilience dynamics driven by climate forcing, can elucidate resilience and shifts in other complex systems.

Aim To investigate the formation of nestedness and species co-occurrence patterns at the local (sampling station), the intermediate (island group), and the archipelago scale.Location The study used data on the distribution of terrestrial isopods on 20 islands of the central Aegean (Greece). These islands are assigned to two distinct subgroups (Kyklades and Eastern islands). MethodsThe Nestedness Temperature Calculator was used to obtain nestedness values and maximally nested matrices, the EcoSim7 software and a modified version of Sanderson (2000) method were used for the analysis of species cooccurrences. Idiosyncratic temperatures of species and the order of species placement in the maximally nested matrices were used for further comparisons among spatial scales. The relationships of nestedness values with beta-diversity, habitat diversity and a number of ecological factors recorded for each sampling station were also investigated. ResultsSignificant nestedness was found at all spatial scales. Levels of nestedness were not related to beta-diversity or habitat diversity. Nestedness values were similar among spatial scales, but they were affected by matrix size. The species that contributed most to the nested patterns within single islands were not the same as those that produce nestedness at the archipelago scale. There was significant variation in the frequency of species occurrence among islands and among spatial scales. There was no direct effect of ecological factors on the shaping of patterns of nestedness within individual islands, but habitat heterogeneity was crucial for the existence of such patterns. Positive associations among species prevailed at all scales when species per station were considered, while negative associations prevailed in the species per island matrices. All associations resulted from the habitat structure of sampling stations and from particularities of geographical distributions. ConclusionsThere was no clear-cut distinction between nestedness patterns among spatial scales, even though different species, and partially different factors, contributed to the formation of these patterns in each case. There was a core of species that contributed to the formation of nested patterns at all spatial scales, while the patterns of species associations suggested that biotic interactions are not an important causal factor. The results of this study suggest that locally rare species cannot be widespread at a higher spatial scale, while locally common species can have a restricted distribution.