A map of theoretical bridges and empirical landmarks for many-species community ecology

Le 07 Janvier 2022
11h30 - Webinar online only

Matthieu Barbier

Plant Health Institute Montpellier, CIRAD, France

 

Link to seminar: https://umontpellier-fr.zoom.us/webinar/register/WN_T8go-kEQRJmlcmBUjmRqsw

Summary

From microbiomes to forests, empirical research on species-rich communities seems to suggest that processes vary considerably across contexts, while some outcomes of species distribution and dynamics present striking regularities. Theoretical research has also shown that we can construct many models, with widely different assump-tions and mechanisms, that succeed equally at predicting the same pattern. Yet we need to know enough about processes to correctly extrapolate these patterns to different or future settings.
I will propose that a broad range of theoretical efforts can be grouped into a few different regions on a common map of ecological behaviors. The challenge is to find which set of predictions and indicators can be used to discrim-inate precisely between these behaviors in empirical data.
Starting from probabilistic (e.g. random network, neutral or maximum entropy) theories, I will ask which of these questions can be addressed using field data, or require controlled environments, or an extensive number of ex-perimental manipulations. I will draw examples from competition in grasslands, fluctuations in microbial systems, and species distribution modeling, to suggest that simple theories of complex communities may indeed find sup-port, but only if they are connected and confronted to a broad spectrum of empirical evidence.
 
Recent publications:
1 Barbier, Matthieu, et al. "Generic assembly patterns in complex ecological communities." PNAS 115.9 (2018)
2 Barbier, Matthieu, et al. "Fingerprints of high-dimensional coexistence in complex ecosystems." Physical Review X 11.1 (2021):
3 Hu, Jiliang, et al. "Emergent phases of ecological diversity and dynamics mapped in microcosms." bioRxiv (2021).
 
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Contact: 

Contact: yannis.michalakis@ird.fr
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