Research

• Forecasting changes in biodiversity

We increasingly need tools to evaluate how the different components of biodiversity are likely to evolove in the future under the influence of global changes. Such forecast are particularly important if we are to anticipate and mitigate the effect of anthropogenic activities on biodiversity and preserve ecosystem functioning and the services the provide to human societies. Although a lot of studies have been published on this subject across the past 20 years, there is still no consensus about which method/model has the best forecast accuracy. I’m currently testing different approaches to try to fill this gap. In particular, I’m comparing the forecasting accuracy of univariate approches where a given statistical model is fitted to each time series separately to multivariate approaches combining all time series for inference and where spatial variation is explicitely accounted for.

• Better characterizing changes in ecological systems following environmental impacts

Before-After Control-Impact (BACI) design are widely used to assess the effect of environmental impacts on ecological systems when experimental approaches are not feasible. This approch rely on a significant interaction between periods and treatments (BACI contrast) to determine whether a given perturbation has had an impact. However, BACI contrast do not make it possible to account for the full range of effects related to perturbations. My aim is to develop new models to help better characterize changes associated to perturbations and provide managers a nice and easy to use framework to assess the effect of restoration programs or conservation measures on ecological systems.

• Evaluating the exposition of biodiversity to future climate change

Climate change metrics have been used to quantify the exposure of geographic areas to different facets of change and relate these facets to different threats and opportunities for biodiversity at a global scale. In parallel, a suite of indicators have been developed to detect approaching transitions between alternative stable states in ecological systems at a local scale. I’m using the theory of Early Warning Signals to evaluate the probability of a future critical transition in the temperature regime at the worldwide scale. For this purpose, I rely on raster maps of temperature time series collected  for terrestrial and marine systems.

• Understanding how climate change influence population dynamics

There is increasing evidence that climate change influence species distribution and population dynamics with potential consequences on species extinction risk and ecosystem functioning. We nonetheless lack a comprehensive understanding of the mechanisms underlying the influence of climate on species. I am using Bayesian inference and state space modeling to understand how climate change influence stream fish species. I specifically try to highlight through which population dynamics parameters (i.e. the intrinisc growth rate, the strength of density dependence) climate change mostly influence population dynamics and how it contribute to spatial variation in population dynamics. I am also using population viability analyses to estimate future species extinction risk under different scenarios of climate change with the aim to refine the conservation status of species.

• Highlighting the underlying determinants of interspecific differences in population dynamics

Across the past few decades, large interspecific differences have been revealed regarding species range shift, population trends, spatial population synchrony or population dynamics. Although some species characteristics related to life-history strategies, thermal tolerance or dietary requirements have been shown to influence among species differences, the determinants of interspecific differences in the influence of climate change on freshwater fish population dynamics remain unclear. Furthermore, few studies have explored the extent to which species characteristics can interact to reinforce the differences abserved between species. By using statistical approaches controlling for phylogenetic non-independence, I try to unravel the determinants of interspecific differences in spatial population synchrony as well as the intrinisc and extrinsic determinants of population dynamics.

• Understanding spatio-temporal variations in taxonomic and functional diversity

The Tonle Sap Lake (Cambodia) is one of the largest indiscriminate fisheries in the world and perhaps also the most productive freshwater fishery. Current subsistence and commercial fisheries within the lake harvest ≈2.5 Mt of fish yr-1, accounting for nearly two-thirds of the protein consumed by more than 14 million people of the region. The Tonle Sap is a “flood pulse” lake, which undergoes a remarkable transformation each year as it fills with floodwaters from the Mekong River, increasing the surface area of the lake by 500%-600%. Using this system, I try to unravel the determinants of spatio-temporal variations in species community assemblages and to predict how fisheries production is expected to evolve in the future with emphasis on climate change and construction of upstream dams. I also investigate questions related to trophic interactions. The ultimate goal of this research is to provide stakeholders a comprehensive decision support tool to manage the Tonle Sap lake.