Assessment of congruence between co-occurrence and functional networks: A new framework for revealing community assembly rules

Describing how communities change over space and time is crucial to better understand and predict the functioning of ecosystems. We propose a new methodological framework, based on network theory and modularity concept, to determine which type of mechanisms (i.e. deterministic versus stochastic processes) has the strongest influence on structuring communities. This framework is based on the computation and comparison of two networks: the co-occurrence (based on species abundances) and the functional networks (based on the species traits values). In this way we can assess whether the species belonging to a given functional group also belong to the same co-occurrence group. We adapted the Dg index of Gauzens et al. (2015) to analyze congruence between both networks. This offers the opportunity to identify which assembly rule(s) play(s) the major role in structuring the community. We illustrate our framework with two datasets corresponding to different faunal groups and ecosystems, and characterized by different scales (spatial and temporal scales). By considering both species abundance and multiple functional traits, our framework improves significantly the ability to discriminate the main assembly rules structuring the communities. This point is critical not only to understand community structuring but also its response to global changes and other disturbances.

Trait-based community assembly of epiphytic diatoms in saline astatic ponds: a test of the stress-dominance hypothesis

The stress dominance hypothesis (SDH) postulates that strong environmental gradients drive trait convergence in communities over limiting similarity. Previous studies, conducted mostly with terrestrial plant communities, found controversial evidence for this prediction. We provide here the first test for SDH for epiphytic diatoms. We studied community assembly in diatom communities of astatic ponds. These water bodies serve as a good model system for testing SDH because they exhibit stress gradients of various environmental factors. Functional diversity of diatom communities was assessed based on four traits: (1) combined trait reflecting the trade-off between stress tolerance and competitive dominance, (2) cell size, (3) oxygen requirement and (4) N-uptake strategy. According to our results, salinity, pH and the width of the macrophyte belt appeared as significant predictors of the trait convergence/divergence patterns presumably acting through influencing the availability of carbon dioxide and turbidity. Lower trait diversity was found in turbid, more saline and more alkaline ponds and functional diversity was higher in transparent, less saline and less alkaline ponds. Overall, our results supported the stress dominance hypothesis. In habitats representing increased environmental stress, environmental filtering was the most important community assembly rule, while limiting similarity became dominant under more favourable conditions.

Quantifying the Scientific Cost of Ambiguous Terminology in Community Ecology

Fundamental terms in the field of ecology are ambiguous, with multiple meanings associated with them. While this could lead to confusion, discord, or even tests that violate core assumptions of a given theory or model, this ambiguity could also be a feature that allows for new knowledge creation through the interconnected nature of concepts. We approached this debate from a quantitative perspective, and investigated the cost of ambiguity related to definitions of ecological units in ecology related to the general term “community.” We did a meta-analysis of tests associated with two bodies of literature, Hubbell’s unified neutral theory of biodiversity and biogeography and Diamond’s assembly rules, that rely on a specific ecological unit that assumes that species are existing within a local area and that they have overlapping resource needs. We predicted that if ambiguous terminology is widespread, then researchers will have tested them with many different ecological units, that in addition some of these ecological units will violate the core assumptions of the theory, and finally that the overall level of support for a theory will be stronger if appropriate ecological units were used. We found that indeed multiple different ecological units were used in the literature to test both theories, with 65 percent appropriate ecological units for neutral theory tests, and only 6 percent for assembly rule tests. Finally, there was some evidence that the support for a theory depended on whether appropriate ecological units were used for neutral tests, but there was not enough data for the assembly rule tests. These results thus show that ambiguous terminology in ecology is having measurable effects on research and is not of solely philosophical concern. We advocate that authors be explicit in their writing and outline core assumptions of theories, that researchers apply these consistently in their tests, and that readers be attentive to what is written and cognizant of their potential biases.

Community structure follows simple assembly rules in microbial microcosms

IntroductionMicrobes typically form diverse communities of interacting species, whose activities have tremendous impact on the plants, animals, and humans they associate with1–3, as well as on the biogeochemistry of the entire planet4. The ability to predict the structure of these complex communities is crucial to understanding, managing, and utilizing them5. Here, we propose a simple, qualitative assembly rule that predicts community structure from the outcomes of competitions between small sets of species, and experimentally assess its predictive power using synthetic microbial communities. The rule's accuracy was evaluated by competing combinations of up to eight soil bacterial species, and comparing the experimentally observed outcomes to the predicted ones. Nearly all competitions resulted in a unique, stable community, whose composition was independent of the initial species fractions. Survival in three-species competitions was predicted by the pairwise outcomes with an accuracy of ~90%. Obtaining a similar level of accuracy in competitions between sets of seven or all eight species required incorporating additional information regarding the outcomes of the three-species competitions. Our results demonstrate experimentally the ability of a simple bottom-up approach to predict community structure. Such an approach is key for anticipating the response of communities to changing environments, designing interventions to steer existing communities to more desirable states, and, ultimately, rationally designing communities de novo6,7.