Keywords: Climate change impact, community ecology, functional traits, trophic niche, exploited marine ecosystem, Celtic sea

Scientific context and objectives of the PhD project
The (over)exploitation of marine ecosystems and services is widely acknowledged (IPBES 2019). Climate change impact on biodiversity is recognized worldwide at multiple biological and ecological levels that scale up to ecosystems (Poloczanska et al. 2016). Marine species shift their range edge under global warming at an average of 19km/year and 75% of marine range shifts occur in a poleward direction (Sorte et al. 2010). Indeed, the decrease of marine primary production expected in some ecoregions could be amplified through the trophic pathways and reduce the biomass of high trophic levels (Kwiatkowski et al. 2019). This threat would weaken coastal marine ecosystems already largely impacted by historical fishing pressure and habitat degradation. Additionally, species communities respond to sea temperature warming, both in terms of productivity and distribution, leading to local prey-predator spatial mismatch (Siddon et al. 2013), increasing species turnover, restructuration of marine communities and modification of food-web structure and stability (Burrows et al. 2019). Considering that fish consumption currently contributes to 20% of the animal protein and supplies more than 3.3 billion people (Jönsson et al. 2011), foreseeing the response of marine communities to climate change and exploitation is of crucial importance. If exploited stocks have been monitored for decades, reaching a complete ecosystem-based assessment integrating all aspects of marine resources is still challenging. To that aim, this PhD project aims to combine a trait-based approach and trophic niche modelling to hindcast and forecast the functional diversity and community composition in the Celtic sea under climate change scenarios. The quality of the estimations will be reinforced by the use of Bayesian modelling to characterize the dynamics of diversity patterns based on the 30-year time series. Additionally, analysis of forecast scenarios coming from ecosystems trophic modelling from a functional ecology point of view is original. From a more general point of view, this thesis project will lead to an integrative vision of the complexity of the different facets of the functional biodiversity of fisheries resources at the exploitation stage.

Structure of the PhD project and the methodology implemented
This thesis project is anchored in an integrative vision of the complexity of the different facets of the functional biodiversity of fisheries resources at the exploitation stage. Marine communities in the Celtic Sea have undergone spatio-temporal changes in the last decades (Hernvann & Gascuel 2020, Mérillet et al. 2020) but the consequences for ecosystem functioning remain unsolved. Therefore, the PhD student will first investigate temporal changes in regional (gamma) functional diversity and turnover (beta). The PhD student will identify species contributing the most to gamma; and beta diversities; and assess their vulnerability to climate change using traits. At the scale of the Celtic sea, south Lusitanian species should shift northward and compete with boreal species for niche. The second axis will test this hypothesis on trophic niche using isotopic and stomach content data for 5 Lusitanian (hake, sole, megrim and two species of anglerfish) and 5 Boreal (whiting, cod, plaice, haddock and blue whiting) species. Species niche will be described and their overlap between species will be investigated. The evolution of dietary niches will be investigated through time and space along a latitudinal gradient of 500km to determine whether novel interactions could lead to changes in trophic relationships and competition. Finally, the PhD student will integrate these outcomes in the modeling of future changes in functional and trophic diversities under two climatic scenarios (RCP 8.5 and RCP 4.5) for which we already have predictions on the trophic web from Hernvann et al. (2020). In particular, future biomasses of the species identified as important contributors will be modeled with species distribution modeling (Guisan & Thuiller 2005, Elith & Leathwick 2009) for the horizon 2050 and 2100 refined either with predicted trophic interactions or traits and community assembly rules (Laughlin et al. 2015).

Expected profiles of candidates
Applicants must hold a Master in biology- ecology, preferentially marine, or related field (fisheries science) with strong skills in quantitative ecology and modelling, especially habitat model and species distribution model. Background in biodiversity, functional ecology and trophic ecology would be appreciated Strong interest in fisheries sciences and ecosystem management


The candidate will be supervised by Maud Mouchet (UMR 7204 CESCO, MNHN, Paris) and Marianne Robert and Dorothée Kopp (LTBH, IFREMER, Lorient).

The completion of this thesis is conditional upon the success of the candidate in the Doctoral School 227 – NATURAL AND HUMAN SCIENCES: EVOLUTION AND ECOLOGY. You will find the detailed application procedure at:
Applications are expected before April 20th, 2022

For further information, please contact and .

Burrows et al. (2019) Ocean community warming responses explained by thermal affinities and temperature gradients. Nature Climate Change, 9: 959–963. DOI: 10.1038/s41558-019-0631-5
Elith & Leathwick (2009) Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annual Review of Ecology, Evolution, and Systematics, 40(1): 677-697. DOI: 10.1146/annurev.ecolsys.110308.120159
Guisan & Thuiller (2005) Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8: 993-1009. DOI: 10.1111/j.1461-0248.2005.00792.x
Hernvann & Gascuel (2020) Exploring the impacts of fishing and environment on the Celtic Sea ecosystem since 1950. Fisheries Research, 225: 105472. Doi: 10.1016/j.fishres.2019.105472.
Hernvann et al. (2020) The Celtic Sea Through Time and Space: Ecosystem Modeling to Unravel Fishing and Climate Change Impacts on Food-Web Structure and Dynamics. Frontiers in Marine Science, 7: 578717. DOI: 10.3389/fmars.2020.578717
IPBES (2019) Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Brondizio, Settele, Díaz & Ngo (editors). IPBES secretariat, Bonn, Germany.
Jönsson et al. (2011) Large variability in continental shelf production of phytoplankton carbon revealed by satellite. Biogeosciences, 8: 1213–1223. DOI: 10.5194/bg-8-1213-2011
Kwiatkowski et al. (2019) Consistent trophic amplification of marine biomass declines under climate change. Global Change Biology, 25: 218–229. DOI: 10.1111/gcb.14468
Laughlin et al. (2015) Quantifying multimodal trait distributions improves trait-based predictions of species abundances and functional diversity. Journal of Vegetation Science, 26: 46-57. DOI: 10.1111/jvs.12219
Mérillet et al. (2020) Environment outweighs the effects of fishing in regulating demersal community structure in an exploited marine ecosystem. Global Change Biology, 26: 2106–2119. DOI: 10.1111/gcb.14969
Poloczanska et al. (2016) Responses of Marine Organisms to Climate Change across Oceans. Frontiers in Marine Science, 3: 62. DOI: 10.3389/fmars.2016.00062
Siddon et al. (2013) Spatial Match-Mismatch between Juvenile Fish and Prey Provides a Mechanism for Recruitment Variability across Contrasting Climate Conditions in the Eastern Bering Sea. PLoS ONE 8(12): e84526. DOI: 10.1371/journal.pone.0084526
Sorte et al. (2010) Marine range shifts and species introductions: comparative spread rates and community impacts. Global Ecology and Biogeography, 19: 303-316. DOI: 10.1111/j.1466-8238.2009.00519.x

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