Theoretical Ecology and Evolution

Our research lies at the crossing of coexistence theory, ecosystem-functioning, and eco-evolutionary dynamics. We aim at developing a coherent and extensive theory explaining how coevolutionary trajectories shape communities and their functioning, and in turn, how ecological dynamics feedback into coevolution. Our aim is to unravel and understand the key factor shaping the sustainability of ecosystems and their functioning. Our research questions include among others:

• How coexistence conditions are modulated by abiotic and biotic factors?
• How these conditions impact ecosystems functioning?
• What are the consequences of eco-evolutionary dynamics on coexistence, ecosystem functioning, and ecological network architecture.
• How the architecture of interspecific interactions network effects coexistence conditions and ecosystem functioning?

Our research combines field data, theoretical models, and numerical simulations.

Ongoing projects:

• SNSF Sinergia grant n° 202290: "Why do toxic cyanobacteria bloom? A gene to ecosystem approach"
  [link] [project homepage]
  
• SNSF Projet grant n° 182386: "Consequences of Eco-Evolutionary Dynamics on Biodiversity Maintenance, Ecosystem Functioning, and Network Architecture"
  [link]

• Structural approach to coexistence theory

  In Saavedra, Rohr et al. (2017), we formalise a multidimensional approach to coexistence theory: the structural approach. The aim of coexistence theory is to provide metrics for coexistence and then to study how abiotic and biotic factors impact those metrics. The structural approach extends the modern coexistence theory by going beyond pairwise interactions and by fully incorporating the indirect effects that emerge from multispecies interactions. We apply the structural approach to several systems such as mutualistic networks (2014, 2016), food-webs (2016, 2017), economy (2014). Recently, we provided a guideline to the structural approach for multi-trophic and changing ecological communities (2018).

  

  Graphical representation of the structural approach to coexistence theory. The angles Omega and theta define the structural niche and fitness difference (from 2017).

   

• Ecosystem-functioning and biodiversity

  We aim at providing a mechanistic understanding of relationship between biodiversity and ecosystem-functioning (the BEF relationship). Using community dynamic models, we infer how species persistence, biodiversity, biomass production, and biomass distribution (evenness) are related (2016, 2018).

  

  Graphical representation of the relationships between species persistence, biomass distribution (evenness), and biomass production (from 2016).

   

  Recently (2018), we derived a mechanistic model to the BEF relationship. Its main advantage is the interpretation of the slope in terms of interspecific competition; the slope is inversely related to the average level of competition.

  

  The BEF relationship in natural microbial microcosms and its temperature dependence. Our mechanistic model predicts that a temperature increase results in higher levels of competition, which in turn, flatten the BEF relationship (from 2018).

   

• Eco-evolutionary dynamics

  Eco-evolutionary dynamics study the feedback loop between ecological and evolutionary dynamics. It has the main advantage of considering frequency and density depend selection process. We use adaptive-dynamic framework to study the consequences of eco-evolutionary dynamic on species coexistence and ecosystem functioning.

  

  Diagram depicting the feedback loop between the ecological and the evolutionary dynamics, within the adaptive dynamics framework.

   

• Ecological networks

  Ecological networks depict the set of interspecific interactions among species in an ecosystem. We developed statistical models aiming at inferring, reconstructing, and predicting the architecture of networks (2010, 2016). Our latest model: the matching -centrality models aims at quantifying matching and centrality traits for each species. Those traits can be correlated to species traits and, then, used to reconstruct and forecast network structure (2016, 2017).

  

  The matching-centrality model (from 2016).

Our main collaboratros are Prof. Lous-Félix Bersier (Fribourg), Prof. Serguei Saavedra (MIT), Prof. Nicolas Loeuille (Sorbonne University), Dr. Francesco Pomati (Eawag), Dr. Elisabeth Janssen (Eawag), Dr. David Johnson (Eawag), and their group.