Grant: Discovery Grants Program - Individual

Biodiversity is more than the distribution of individual species, it is also the collection of interactions among them driving ecosystem processes and supporting diversification of life. Research in my lab has recently shown that not only the distribution of species richness varies across environmental gradients, but also the architecture of biodiversity, i.-e. the structure of the network describing interactions between species. The long-term objective of my research program is to develop theory to understand and predict biodiversity distribution and ecosystem functioning at biogeographical scales. Perhaps one of the most important recent findings in biodiversity science is that, despite common believe, there is no net decrease in species richness at the local scale across the globe because extirpations are most often balanced by species introductions. Rather, shifts in community composition are more important and globally distributed. These observations suggest that we should abandon species richness as the most fundamental biodiversity currency to monitor and shift focus to other measures of biodiversity such as network structure. My general objective for the next cycle is therefore to develop and investigate the concept of ecological coherence. The coherence of a community describes the complex distribution of responses of an ecological network to an environmental change such as temperature. Coherence indicates that most species respond in a similar way and therefore maintains its integrity, while a lack of coherence would suggest alteration in its functioning, such as the loss of trophic regulation or secondary extinctions. The specific objectives of my research program are therefore to: 1) Quantify the dimensionality of ecological coherence across groups of organisms and over space ; 2) Test the hypothesis that interacting species have larger coherence than non-interacting species ; 3) Develop theory relating ecological coherence to disruption in ecosystem functioning in order to propose a new indicator to anticipate the consequences of biodiversity changes at the community level. These research activities will contribute to a successful training program in computational biodiversity science conducted in collaboration with leading scientists in biogeography, modelling, theoretical ecology, but also with collaborators from the government, industries and NGOs. The formalism I will develop will bring the field beyond the simplistic univariate assessment of biodiversity changes. I therefore expect practical, quantifiable, metrics to assess community to environmental changes. This is particularly relevant for the monitoring and projection of biodiversity changes following the new Global framework for biodiversity.