Per capita interactions and stress tolerance drive stress-induced changes in biodiversity effects on ecosystem functions

Environmental stress changes the relationship between biodiversity and ecosystem functions, but the underlying mechanisms are poorly understood. Because species interactions shape biodiversity-ecosystem functioning relationships, changes in per capita interactions under stress (as predicted by the stress gradient hypothesis) can be an important driver of stress-induced changes in these relationships. To test this hypothesis, we measure productivity in microalgae communities along a diversity and herbicide gradient. On the basis of additive partitioning and a mechanistic community model, we demonstrate that changes in per capita interactions do not explain effects of herbicide stress on the biodiversity-productivity relationship. Instead, assuming that the per capita interactions remain unaffected by stress, causing species densities to only change through differences in stress tolerance, suffices to predict the stress-induced changes in the biodiversity-productivity relationship and community composition. We discuss how our findings set the stage for developing theory on how environmental stress changes biodiversity effects on ecosystem functions

Construction of data-driven models to predict the occurrence of planktonic species in the North-Sea

Marine habitat suitability models typically predict the potential distribution of organisms based on basic abiotic variables such as salinity, oxygen concentrations, temperature fluctuations (Gogina & Zettler, 2010) or sediment class information (Degraer et al., 2008; Willems et al., 2008). Recently, Dachs & Méjanelle (2010) claimed that the modification of biota composition due to marine pollution is a factor to be taken into account in marine habitat suitability models. Although the anthropogenic pressure on the environment has been exponentially increasing during the last six decades (Dachs & Méjanelle, 2010), the global effect of human inputs on oceanic phytoplankton remains unknown (Echeveste et al., 2010). A limited number of studies have assessed the impact of anthropogenic stressors on phytoplankton in marine environments at a global level (Faust et al., 2003; Magnusson et al.,2008). In order to fill this knowledge gap, this research tries to determine to what extent pollution data can be used to predict the occurrence of the phytoplanktonic organisms compared to basic abiotic variables. Here we explored this issue by developing classification trees relating physical-chemical variables with the occurrence of the potential harmful toxic algae Odontella sinensis

The combined effects of biotic and abiotic stress on species richness and connectance

Food web structure and species richness are both subject to biotic (e.g. predation pressure and resource limitation) and abiotic stress (e.g. environmental change). We investigated the combined effects of both types of stress on richness and connectance, and on their relationship, in a predator-prey system. To this end, we developed a mathematical two trophic level food-web model to investigate the effects of biotic and abiotic stress on food web connectance and species richness. We found negative effects of top-down and bottom-up control on prey and predator richness, respectively. Effects of top-down and bottom-up control were stronger when initial connectance was high and low, respectively. Bottom-up control could either aggravate or buffer negative effects of top-down control. Abiotic stress affecting predator richness had positive indirect effects on prey richness, but only when initial connectance was low. However, no indirect effects on predator richness were observed following direct effects on prey richness. Top-down and bottom-up control selected for weakly connected prey and highly connected predators, thereby decreasing and increasing connectance, respectively. Our simulations suggest a broad range of negative and positive richness-connectance relationships, thereby revisiting the often found negative relationship between richness and connectance in food webs. Our results suggest that (1) initial foodweb connectance strongly influences the effects of biotic stress on richness and the occurrence of indirect effects on richness; and (2) the shape of the richness-connectance relationship depends on the type of biotic stress.</p

The topology and drivers of ant-symbiont networks across Europe

Intimate associations between different species drive community composition across ecosystems. Understanding the ecological and evolutionary drivers of these symbiotic associations is challenging because their structure eventually determines stability and resilience of the entire species network. Here, we compiled a detailed database on naturally occurring ant-symbiont networks in Europe to identify factors that affect symbiont network topology. These networks host an unrivalled diversity of macrosymbiotic associations, spanning the entire mutualism-antagonism continuum, including: (i) myrmecophiles - commensalistic and parasitic arthropods; (ii) trophobionts - mutualistic aphids, scale insects, planthoppers and caterpillars; (iii) social parasites - parasitic ant species; (iv) parasitic helminths; and (v) parasitic fungi. We dissected network topology to investigate what determines host specificity, symbiont species richness, and the capacity of different symbiont types to switch hosts. We found 722 macrosymbionts (multicellular symbionts) associated with European ants. Symbiont type explained host specificity and the average relatedness of the host species. Social parasites were associated with few hosts that were phylogenetically highly related, whereas the other symbiont types interacted with a larger number of hosts across a wider taxonomic distribution. The hosts of trophobionts were the least phylogenetically related across all symbiont types. Colony size, host range and habitat type predicted total symbiont richness: ant hosts with larger colony size, a larger distribution range or with a wider habitat range contained more symbiont species. However, we found that different sets of host factors affected diversity in the different types of symbionts. Ecological factors, such as colony size, host range and niche width predominantly determined myrmecophile species richness, whereas host phylogeny was the most important predictor of mutualistic trophobiont, social parasite and parasitic helminth species richness. Lastly, we found that hosts with a common biogeographic history support a more similar community of symbionts. Phylogenetically related hosts also shared more trophobionts, social parasites and helminths, but not myrmecophiles. Taken together, these results suggest that ecological and evolutionary processes structure host specificity and symbiont richness in large-scale ant-symbiont networks, but these drivers may shift in importance depending on the type of symbiosis. Our findings highlight the potential of well-characterized bipartite networks composed of different types of symbioses to identify candidate processes driving community composition