ORCID Profile
0000-0002-2624-3508
Current Organisation
Université Laval
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Publisher: American Association for the Advancement of Science (AAAS)
Date: 06-11-2020
Abstract: Human activities are rapidly altering the natural world. Nowhere is this more evident, perhaps, than in the Arctic, yet this region remains one of the most remote and difficult to study. Researchers have increasingly relied on animal tracking data in these regions to understand in idual species' responses, but if we want to understand larger-scale change, we need to integrate our understanding across species. Davidson et al. introduce an open-source data archive that currently hosts more than 15 million location data points across 96 species and use it to show distinct climate change responses across species. Such ecological “big data” can lead to a wider understanding of change. Science , this issue p. 712
Publisher: Elsevier BV
Date: 11-2021
Publisher: Wiley
Date: 26-01-2020
DOI: 10.1111/JZO.12756
Publisher: Elsevier BV
Date: 10-2015
DOI: 10.1016/J.TREE.2015.07.006
Abstract: The recent trend for journals to require open access to primary data included in publications has been embraced by many biologists, but has caused apprehension amongst researchers engaged in long-term ecological and evolutionary studies. A worldwide survey of 73 principal investigators (Pls) with long-term studies revealed positive attitudes towards sharing data with the agreement or involvement of the PI, and 93% of PIs have historically shared data. Only 8% were in favor of uncontrolled, open access to primary data while 63% expressed serious concern. We present here their viewpoint on an issue that can have non-trivial scientific consequences. We discuss potential costs of public data archiving and provide possible solutions to meet the needs of journals and researchers.
Publisher: Wiley
Date: 19-05-2016
DOI: 10.1111/GEB.12470
Publisher: Springer Science and Business Media LLC
Date: 03-09-2019
Publisher: Cold Spring Harbor Laboratory
Date: 04-11-2020
DOI: 10.1101/2020.11.04.368670
Abstract: The functional response is central to our understanding of any predator–prey system as it establishes the link between trophic levels. Most functional responses are evaluated using phenomenological models linking predator acquisition rate and prey density. However, our ability to measure functional responses using such an approach is often limited in natural systems and the use of inaccurate functions can profoundly affect the outcomes of population and community models. Here, we develop a mechanistic model based on extensive data to assess the functional response of a generalist predator, the arctic fox ( Vulpes lagopus ), to various tundra prey species (lemmings and the nests of geese, passerines and sandpipers). We found that predator acquisition rates derived from the mechanistic model were consistent with field observations. Although sigmoidal functional responses were previously used to model fox-prey population dynamics, none of our simulations resulted in a saturating response in all prey species. Our results highlight the importance of predator searching components in predator-prey interactions, especially predator speed, while predator acquisition rates were not limited by handling processes. By combining theory with field observations, our study provides evidences that predator acquisition rate is not systematically limited at the highest prey densities observed in a natural system. We reinforce the idea that functional response categories, typically types I, II, and III, should be considered as particular cases along a continuum. Specific functions derived with a mechanistic approach for a range of densities observed in natural communities should improve our ability to model and understand predator-prey systems.
No related grants have been discovered for Gilles Gauthier.