Very high-resolution environmental predictors in species distribution models: moving beyond topography?
Details
Serval ID
serval:BIB_BEB351A749FF
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Very high-resolution environmental predictors in species distribution models: moving beyond topography?
Journal
Progress in Physical Geography
ISSN
0309-1333
Publication state
Published
Issued date
2014
Peer-reviewed
Oui
Volume
38
Number
1
Pages
79-96
Language
english
Abstract
Recent advances in remote sensing technologies have facilitated the generation of very high resolution (VHR) environmental data. Exploratory studies suggested that, if used in species distribution models (SDMs), these data should enable modelling species' micro-habitats and allow improving predictions for fine-scale biodiversity management. In the present study, we tested the influence, in SDMs, of predictors derived from a VHR digital elevation model (DEM) by comparing the predictive power of models for 239 plant species and their assemblages fitted at six different resolutions in the Swiss Alps. We also tested whether changes of the model quality for a species is related to its functional and ecological characteristics. Refining the resolution only contributed to slight improvement of the models for more than half of the examined species, with the best results obtained at 5 m, but no significant improvement was observed, on average, across all species. Contrary to our expectations, we could not consistently correlate the changes in model performance with species characteristics such as vegetation height. Temperature, the most important variable in the SDMs across the different resolutions, did not contribute any substantial improvement. Our results suggest that improving resolution of topographic data only is not sufficient to improve SDM predictions - and therefore local management - compared to previously used resolutions (here 25 and 100 m). More effort should be dedicated now to conduct finer-scale in-situ environmental measurements (e.g. for temperature, moisture, snow) to obtain improved environmental measurements for fine-scale species mapping and management.
Keywords
grain size, micro-topography, mountains, plants, predictive power, species distribution models (SDMs), VHR
Web of science
Create date
29/09/2013 17:00
Last modification date
01/06/2024 6:18