Timothée Poisot

A conceptual framework for the evolution of ecological specialisation

Ecology Letters (2011) 14: 841-851 ABSTRACT: Ecological specialisation concerns all species and underlies many major ecological and evolutionary patterns. Yet its status as a unifying concept is not always appreciated because of its similarity to concepts of the niche, the many levels of biological phenomena to which it applies, and the complexity of the mechanisms influencing it. The evolution of specialisation requires the coupling of constraints on adaptive evolution with covariation of genotype and environmental performance. This covariation itself depends upon organismal properties such as dispersal behaviour and life history and complexity in the environment stemming from factors such as species interactions and spatio-temporal heterogeneity in resources. Here, we develop a view on specialisation that integrates across the range of biological phenomena with the goal of developing a more predictive conceptual framework that specifically accounts for the importance of biotic complexity and coevolutionary events.

Phage-bacteria infection networks.

Phage and their bacterial hosts are the most abundant and genetically diverse group of organisms on the planet. Given their dominance, it is no wonder that many recent studies have found that phage-bacteria interactions strongly influence global biogeochemical cycles, incidence of human diseases, productivity of industrial microbial commodities, and patterns of microbial genome diversity. Unfortunately, given the extreme diversity and complexity of microbial communities, traditional analyses fail to characterize interaction patterns and underlying processes. Here, we review emerging systems approaches that combine empirical data with rigorous theoretical analysis to study phage-bacterial interactions as networks rather than as coupled interactions in isolation.

The dissimilarity of species interaction networks

In a context of global changes, and amidst the perpetual modification of community structure undergone by most natural ecosystems, it is more important than ever to understand how species interactions vary through space and time. The integration of biogeography and network theory will yield important results and further our understanding of species interactions. It has, however, been hampered so far by the difficulty to quantify variation among interaction networks. Here, we propose a general framework to study the dissimilarity of species interaction networks over time, space or environments, allowing both the use of quantitative and qualitative data. We decompose network dissimilarity into interactions and species turnover components, so that it is immediately comparable to common measures of β-diversity. We emphasise that scaling up β-diversity of community composition to the β-diversity of interactions requires only a small methodological step, which we foresee will help empiricists adopt this method. We illustrate the framework with a large dataset of hosts and parasites interactions and highlight other possible usages. We discuss a research agenda towards a biogeographical theory of species interactions.

Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees.

Network-based diffusion analysis demonstrates that a novel tool-use behavior, “moss-sponging”, spread via social learning in a wild East-African chimpanzee community.

Inferring food web structure from predator–prey body size relationships

1. Current global changes make it important to be able to predict which interactions will occur in the emerging ecosystems. Most of the current methods to infer the existence of interactions between two species require a good knowledge of their behaviour or a direct observation of interactions. In this paper, we overcome these limitations by developing a method, inspired from the niche model of food web structure, using the statistical relationship between predator and prey body size to infer the matrix of potential interactions among a pool of species. 2. The novelty of our approach is to infer, for any species of a given species pool, the three species-specific parameters of the niche model. The method applies to both local and metaweb scales. It allows one to evaluate the feeding interactions of a new species entering the community. 3. We find that this method gives robust predictions of the structure of food webs and that its efficiency is increased when the strength of the body-size relationship between predators and preys increases. 4. We finally illustrate the potential of the method to infer the metaweb structure of pelagic fishes of the Mediterranean sea under different global change scenarios.

Trophic complementarity drives the biodiversity-ecosystem functioning relationship in food webs

The biodiversity-ecosystem functioning (BEF) relationship is central in community ecology. Its drivers in competitive systems (sampling effect and functional complementarity) are intuitive and elegant, but we lack an integrative understanding of these drivers in complex ecosystems. Because networks encompass two key components of the BEF relationship (species richness and biomass flow), they provide a key to identify these drivers, assuming that we have a meaningful measure of functional complementarity. In a network, diversity can be defined by species richness, the number of trophic levels, but perhaps more importantly, the diversity of interactions. In this paper, we define the concept of trophic complementarity (TC), which emerges through exploitative and apparent competition processes, and study its contribution to ecosystem functioning. Using a model of trophic community dynamics, we show that TC predicts various measures of ecosystem functioning, and generate a range of testable predictions. We find that, in addition to the number of species, the structure of their interactions needs to be accounted for to predict ecosystem productivity.

Connecting people and ideas from around the world: global innovation platforms for next-generation ecology and beyond

We present a case for using Global Community Innovation Platforms (GCIPs), an approach to improve innovation and knowledge exchange in international scientific communities through a common and open online infrastructure. We highlight the value of GCIPs by focusing on recent efforts targeting the ecological sciences, where GCIPs are of high relevance given the urgent need for interdisciplinary, geographical, and cross-sector collaboration to cope with growing challenges to the environment as well as the scientific community itself. Amidst the emergence of new international institutions, organizations, and meetings, GCIPs provide a stable international infrastructure for rapid and long-term coordination that can be accessed by any individual. This accessibility can be especially important for researchers early in their careers. Recent examples of early-career GCIPs complement an array of existing options for early-career scientists to improve skill sets, increase academic and social impact, and broaden career opportunities. We provide a number of examples of existing early-career initiatives that incorporate elements from the GCIPs approach, and highlight an in-depth case study from the ecological sciences: the International Network of Next-Generation Ecologists (INNGE), initiated in 2010 with support from the International Association for Ecology and 20 member institutions from six continents.

Resource availability affects the structure of a natural bacteria- bacteriophage community

Antagonistic networks are known to be structured in the wild, but knowledge on how this structure may change as a response to environmental perturbations is scarce. We describe a natural bipartite network between bacteria and lytic bacteriophages, and investigate how it is affected by environmental productivity in the form of different resource levels for the bacteria. We report that low amounts of resource decrease phage generality and lead to less robust and less stable communities. We discuss how resource levels in nature may alter the structure of complex communities.

The Case for Open Preprints in Biology

Biologists should submit their preprints to open servers, a practice common in mathematics and physics, to open and accelerate the scientific process.

Trophic network structure emerges through antagonistic coevolution in temporally varying environments

Understanding the mechanisms underlying ecological specialization is central to our understanding of community ecology and evolution. Although theoretical work has investigated how variable environments may affect specialization in single species, little is known about how such variation impacts bipartite network structure in antagonistically coevolving systems. Here, we develop and analyse a general model of victim–enemy coevolution that explicitly includes resource and population dynamics. We investigate how temporal environmental heterogeneity affects the evolution of specialization and associated community structure. Environmental productivity influences victim investment in resistance, which will shape patterns of specialization through its regulating effect on enemy investment in infectivity. We also investigate the epidemiological consequences of environmental variability and show that enemy population density is maximized for intermediate lengths of productive seasons, which corresponds to situations where enemies can evolve higher infectivity than victims can evolve defence. We discuss our results in the light of empirical studies, and further highlight ways in which our model applies to a range of natural systems.