I am a quantitative ecologist, with interests ranging from population dynamics or coexistence theory to the statistical analysis of time series. Much of my research deals with ecological interactions in a dynamic setting (and sometimes a spatially explicit one).

I am a CNRS researcher, based at the Institute of Mathematics of Bordeaux. These are tenured, full-time research positions and researchers belong to disciplinary sections. I am affiliated to the main ecology and evolution section, as well as to the interdisciplinary section on mathematical, computational and physical modelling for the life sciences.

Contact: frederic dot barraquand <sign_here> u-bordeaux dot fr. Find me on Mastodon.

Current projects include, on the statistical/modelling side:

• multivariate time series methods to infer causal relationships
• data fusion techniques for mechanistic ecological models – and increasingly, biodiversity monitoring
• identifiability properties of such models
• individual-based modelling using point processes

Some fundamental ecological questions that interest me:

• What are the causes of cyclic population dynamics in rodents & insects?
• What are the main drivers of coexistence (or exclusion) of primary producers?
• How does environmental variability (food resources, climate) affect population dynamics?

A few other, more applied interests: biodiversity indicators, biodiversity monitoring, agricultural and urban ecology.

Selected publications by theme

Data integration for community dynamics

Barraquand F., Gimenez O. Fitting stochastic predator-prey models using both population density and kill rate data. Theoretical Population Biology, 2021, 138, 1-27.

Quéroué M., Barbraud C., Barraquand F., Turek D., Delord K., Pacoureau N., Gimenez O. Multispecies integrated population model reveals bottom-up dynamics in a seabird predator-prey system. Ecological Monographs, 2021, 91(3), e01459.

Barraquand F., Gimenez O. Integrating multiple data sources to fit matrix population models for interacting species Ecological Modelling, 2019, 411.

Time series analysis and interaction network inference

Barraquand F., Picoche C., Detto M., Hartig F. Inferring species interactions using Granger causality and convergent cross mapping. Theoretical Ecology, 2021, 14, 87-105.

Picoche C., Barraquand F. Strong self-regulation and widespread facilitative interactions between genera of phytoplankton. Journal of Ecology, 2020, 108(6), 2232-2242.

Population cycles

Barraquand F., Louca S., Abbott K.C., Cobbold C., Cordoleani F., DeAngelis D., Elderd B.D., Fox J.W., Greenwood P., Hilker F.M., Lutscher F., Murray D., Stieha C.R., Taylor R.A., Vitense K., Wolkowicz G. & Tyson R.C. Moving forward in circles: challenges and opportunities in modelling population cycles. Ecology Letters, 2017, 20(8) ,1074–1092.

Barraquand F., Pinot A. , Yoccoz N.G. & Bretagnolle V. 2014. Overcompensation and phase effects in a cyclic common vole population: between first and second order cycles. Journal of Animal Ecology, 2014, 83, 1367–1378.

Effects of environmental variability on population and community dynamics

Barraquand F., New. L.F., Redpath S. & Matthiopoulos J. 2015. Indirect effects of primary prey population dynamics on alternative prey. Theoretical Population Biology, 2015, 103,44-49.

Barraquand F., Høye T.T., Henden J.-A., Yoccoz N.G., Gilg O., Schmidt N.M., Sittler B. & Ims R.A. Demographic responses of a site-faithful and territorial predator to its fluctuating prey: Long-tailed skuas and arctic lemmings Journal of Animal Ecology, 2014, 83: 375–387.

Barraquand F. & Yoccoz N.G. When can environmental variability benefit population growth ? Counterintuitive effects of nonlinearities in vital rates. Theoretical Population Biology. 2013, 89, 1-11.

Individual-based modelling of spatial population and community dynamics

Picoche C., Young W.R., Barraquand F. [Re] Reproductive pair correlations and the clustering of organisms ReScience 2022 DOI: 10.5281/zenodo.6546488

Barraquand F. & Murrell D.J. Scaling up predator-prey dynamics with spatial moment equations. Methods in ecology and evolution 2013, 4, 276–289.

Barraquand, F., & Murrell, D. J. Intense or spatially heterogeneous predation can select against prey dispersal. PloS One, 2012, 7(1), e28924.

Barraquand, F., & Murrell, D.J. Evolutionarily stable consumer home range size in relation to resource demography and consumer spatial organization. Theoretical ecology, 2012, 5(4), 567-589.