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The Contribution of Vegetation and Landscape Configuration for Predicting Environmental Change Impacts on Iberian Birds

Trivino, Maria; Thuiller, Wilfried; Cabeza, Mar; Hickler, Thomas LU and Araujo, Miguel B. (2011) In PLoS ONE 6(12).
Abstract
Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT).... (More)
Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT). For each species, several models were created, differing in the predictor variables used (climate, vegetation, and landscape configuration). Discrimination ability of each model in the present-day was then tested with four commonly used evaluation methods (AUC, TSS, specificity and sensitivity). The different sets of predictor variables yielded similar spatial patterns for well-modelled species, but the future projections diverged for poorly-modelled species. Models using all predictor variables were not significantly better than models fitted with climate variables alone for ca. 50% of the cases. Moreover, models fitted with climate data were always better than models fitted with landscape configuration variables, and vegetation variables were found to correlate with bird species distributions in 26-40% of the cases with BRT, and in 1-18% of the cases with RF. We conclude that improvements from including vegetation and its landscape configuration variables in comparison with climate only variables might not always be as great as expected for future projections of Iberian bird species. (Less)
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published
subject
in
PLoS ONE
volume
6
issue
12
publisher
Public Library of Science
external identifiers
  • wos:000299684700051
  • scopus:84055182551
ISSN
1932-6203
DOI
10.1371/journal.pone.0029373
language
English
LU publication?
yes
id
7f7f4225-93e9-4ace-96bd-b2e10b42e637 (old id 2378537)
date added to LUP
2012-03-27 14:06:43
date last changed
2017-10-29 03:51:05
@article{7f7f4225-93e9-4ace-96bd-b2e10b42e637,
  abstract     = {Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT). For each species, several models were created, differing in the predictor variables used (climate, vegetation, and landscape configuration). Discrimination ability of each model in the present-day was then tested with four commonly used evaluation methods (AUC, TSS, specificity and sensitivity). The different sets of predictor variables yielded similar spatial patterns for well-modelled species, but the future projections diverged for poorly-modelled species. Models using all predictor variables were not significantly better than models fitted with climate variables alone for ca. 50% of the cases. Moreover, models fitted with climate data were always better than models fitted with landscape configuration variables, and vegetation variables were found to correlate with bird species distributions in 26-40% of the cases with BRT, and in 1-18% of the cases with RF. We conclude that improvements from including vegetation and its landscape configuration variables in comparison with climate only variables might not always be as great as expected for future projections of Iberian bird species.},
  author       = {Trivino, Maria and Thuiller, Wilfried and Cabeza, Mar and Hickler, Thomas and Araujo, Miguel B.},
  issn         = {1932-6203},
  language     = {eng},
  number       = {12},
  publisher    = {Public Library of Science},
  series       = {PLoS ONE},
  title        = {The Contribution of Vegetation and Landscape Configuration for Predicting Environmental Change Impacts on Iberian Birds},
  url          = {http://dx.doi.org/10.1371/journal.pone.0029373},
  volume       = {6},
  year         = {2011},
}