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An open-source framework to model present and future marine species distributions at local scale
- Source :
- Ecological Informatics, Ecological Informatics, 2020, 59, pp.101130. ⟨10.1016/j.ecoinf.2020.101130⟩, Ecological Informatics (1574-9541) (Elsevier BV), 2020-09, Vol. 59, P. 101130 (9p.), Ecological Informatics, Elsevier, 2020, 59, ⟨10.1016/j.ecoinf.2020.101130⟩, Ecological Informatics, Elsevier, 2020, 59, pp.101130. ⟨10.1016/j.ecoinf.2020.101130⟩
- Publication Year :
- 2020
-
Abstract
- (IF 3.14; Q2); International audience; Species Distribution Models (SDMs) are useful tools to project potential future species distributions under climate change scenarios. Despite the ability to run SDMs in recent and reliable tools, there are some misuses and proxies that are widely practiced and rarely addressed together, particularly when dealing with marine species.In this paper, we propose an open-source framework that includes (i) a procedure for homogenizing occurrence data to reduce the influence of sampling bias, (ii) a procedure for generating pseudo-absences, (iii) a hierarchical-filter approach, (iv) full incorporation of the third dimension by considering climatic variables at multiple depths and (v) building of maps that predict current and potential future ranges of marine species. This framework is available for non-modeller ecologists interested in investigating future species ranges with a user-friendly script. We investigated the robustness of the framework by applying it to marine species of the Eastern English Channel. Projections were built for the middle and the end of this century under RCP2.6 and RCP8.5 scenarios.
- Subjects :
- 0106 biological sciences
[SDV]Life Sciences [q-bio]
Species distribution
Climate change
010603 evolutionary biology
01 natural sciences
Marine species
Pseudo-absences
Bioclimatic envelope models
14. Life underwater
Dimension (data warehouse)
Habitat models
Robustness (economics)
Ecology, Evolution, Behavior and Systematics
Sampling bias
Future projections
Ecology
business.industry
010604 marine biology & hydrobiology
Applied Mathematics
Ecological Modeling
Acl
Environmental resource management
Vertical gradient
Computer Science Applications
Open source
Computational Theory and Mathematics
13. Climate action
Modeling and Simulation
[SDE]Environmental Sciences
Automated modelling framework
Environmental science
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
business
Communication channel
Subjects
Details
- Language :
- English
- ISSN :
- 15749541
- Database :
- OpenAIRE
- Journal :
- Ecological Informatics, Ecological Informatics, 2020, 59, pp.101130. ⟨10.1016/j.ecoinf.2020.101130⟩, Ecological Informatics (1574-9541) (Elsevier BV), 2020-09, Vol. 59, P. 101130 (9p.), Ecological Informatics, Elsevier, 2020, 59, ⟨10.1016/j.ecoinf.2020.101130⟩, Ecological Informatics, Elsevier, 2020, 59, pp.101130. ⟨10.1016/j.ecoinf.2020.101130⟩
- Accession number :
- edsair.doi.dedup.....07a248fbc6902fb43bbfc998279b8e07