Species distribution model transferability and model grain size – finer may not always be better

Abstract Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of pr...

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Autores principales:	Syed Amir Manzoor, Geoffrey Griffiths, Martin Lukac
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2f01489ed5fb4cb584537f62e1c9ab3e
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spelling	oai:doaj.org-article:2f01489ed5fb4cb584537f62e1c9ab3e2021-12-02T16:08:01ZSpecies distribution model transferability and model grain size – finer may not always be better10.1038/s41598-018-25437-12045-2322https://doaj.org/article/2f01489ed5fb4cb584537f62e1c9ab3e2018-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-25437-1https://doaj.org/toc/2045-2322Abstract Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.Syed Amir ManzoorGeoffrey GriffithsMartin LukacNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-9 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Syed Amir Manzoor Geoffrey Griffiths Martin Lukac Species distribution model transferability and model grain size – finer may not always be better
description	Abstract Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.
format	article
author	Syed Amir Manzoor Geoffrey Griffiths Martin Lukac
author_facet	Syed Amir Manzoor Geoffrey Griffiths Martin Lukac
author_sort	Syed Amir Manzoor
title	Species distribution model transferability and model grain size – finer may not always be better
title_short	Species distribution model transferability and model grain size – finer may not always be better
title_full	Species distribution model transferability and model grain size – finer may not always be better
title_fullStr	Species distribution model transferability and model grain size – finer may not always be better
title_full_unstemmed	Species distribution model transferability and model grain size – finer may not always be better
title_sort	species distribution model transferability and model grain size – finer may not always be better
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/2f01489ed5fb4cb584537f62e1c9ab3e
work_keys_str_mv	AT syedamirmanzoor speciesdistributionmodeltransferabilityandmodelgrainsizefinermaynotalwaysbebetter AT geoffreygriffiths speciesdistributionmodeltransferabilityandmodelgrainsizefinermaynotalwaysbebetter AT martinlukac speciesdistributionmodeltransferabilityandmodelgrainsizefinermaynotalwaysbebetter
_version_	1718384644903141376

Species distribution model transferability and model grain size – finer may not always be better

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