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Effects of species traits and environmental predictors on performance and transferability of ecological niche models
- Source :
- Scientific Reports, Vol 9, Iss 1, Pp 1-14 (2019), Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela, instname, Scientific Reports, Digibug. Repositorio Institucional de la Universidad de Granada
- Publication Year :
- 2019
- Publisher :
- Nature Publishing Group, 2019.
-
Abstract
- Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-019-40766-5.<br />The ability of ecological niche models (ENMs) to produce robust predictions for different time frames (i.e. temporal transferability) may be hindered by a lack of ecologically relevant predictors. Model performance may also be affected by species traits, which may reflect different responses to processes controlling species distribution. In this study, we tested four primary hypotheses involving the role of species traits and environmental predictors in ENM performance and transferability. We compared the predictive accuracy of ENMs based upon (1) climate, (2) land-use/cover (LULC) and (3) ecosystem functional attributes (EFAs), and (4) the combination of these factors for 27 bird species within and beyond the time frame of model calibration. The combination of these factors significantly increased both model performance and transferability, highlighting the need to integrate climate, LULC and EFAs to improve biodiversity projections. However, the overall model transferability was low (being only acceptable for less than 25% of species), even under a hierarchical modelling approach, which calls for great caution in the use of ENMs to predict bird distributions under global change scenarios. Our findings also indicate that positive effects of species traits on predictive accuracy within model calibration are not necessarily translated into higher temporal transferability.<br />This research was developed as part of the project ECOPOTENTIAL, which received funding from the European Union’s Horizon 2020 Research and Innovation Programme under agreement No. 641762. We thank everyone who contributed to the fieldwork: Xosé Pardavila, Adrián Lamosa (Sorex, Ecoloxía e Medio Ambiente SL), Marta Arenas, Alberto Toupa and Fernando Martínez-Freiría. Field surveys were funded by the project INTERREG-POCTEC (‘NATURA Xurés-Gerês’). A.R. was financially supported by the Xunta de Galicia (post-doctoral fellowship ED481B2016/084-0). Miquel Ninyerola and Meritxell Batalla (UAB) generated climate variables from data provided by the Spanish Meteorological Agency and the Spanish Ministry of Marine and Rural Environment within the MONTES-Consolider project (CSD2008-00040).
- Subjects :
- 0301 basic medicine
Calibration (statistics)
Landsat-derived maps
Climate Change
Species distribution
Transferability
Biodiversity
Temporal transferability
lcsh:Medicine
Environmental change
Models, Biological
Article
Birds
03 medical and health sciences
0302 clinical medicine
Time frame
Animals
Ecosystem
Species distribution models
MODIS EVI
lcsh:Science
Ecological modelling
Ecological niche
Multidisciplinary
Ecology
lcsh:R
Global change
Climate-chenga ecology
15. Life on land
Remote sensing
030104 developmental biology
13. Climate action
Environmental science
lcsh:Q
Ecosystem functioning attributes
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 9
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....cfd38e74885274a402807d1e1e5e77bf