Integrating climate and local factors for geomorphological distribution models
ABSTRACT Earth surface processes (ESPs) drive landscape development and ecosystem processes in high‐latitude regions by creating spatially heterogeneous abiotic and biotic conditions. Ongoing global change may potentially alter the activity of ESPs through feedback on ground conditions, vegetation a...
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crwiley:10.1002/esp.3554 2024-09-15T18:29:07+00:00 Integrating climate and local factors for geomorphological distribution models Aalto, Juha Luoto, Miska 2014 http://dx.doi.org/10.1002/esp.3554 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fesp.3554 https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.3554 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Earth Surface Processes and Landforms volume 39, issue 13, page 1729-1740 ISSN 0197-9337 1096-9837 journal-article 2014 crwiley https://doi.org/10.1002/esp.3554 2024-08-27T04:27:01Z ABSTRACT Earth surface processes (ESPs) drive landscape development and ecosystem processes in high‐latitude regions by creating spatially heterogeneous abiotic and biotic conditions. Ongoing global change may potentially alter the activity of ESPs through feedback on ground conditions, vegetation and the carbon cycle. Consequently, accurate modeling of ESPs is important for improving understanding of the current and future distributions of these processes. The aims of this study were to: (1) integrate climate and multiple local predictors to develop realistic ensemble models for the four key ESPs occurring at high latitudes (slope processes, cryoturbation, nivation and palsa mires) based on the outputs of 10 modern statistical techniques; (2) test whether models of ESPs are improved by incorporating topography, soil and vegetation predictors to climate‐only models; (3) examine the relative importance of these variables in a multivariate setting. Overall, the models showed high transferability with the mean area under curve of a receiver operating characteristics (AUC) ranging from 0.83 to 0.96 and true skill statistics (TSS) from 0.52 to 0.87 for the most complex models. Even though the analyses highlighted the importance of the climate variables as the most influential predictors, three out of four models benefitted from the inclusion of local predictors. We conclude that disregarding local topography and soil conditions in spatial models of ESPs may cause a significant source of error in geomorphological distribution models. Copyright © 2014 John Wiley & Sons, Ltd. Article in Journal/Newspaper palsa Wiley Online Library Earth Surface Processes and Landforms 39 13 1729 1740 |
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English |
description |
ABSTRACT Earth surface processes (ESPs) drive landscape development and ecosystem processes in high‐latitude regions by creating spatially heterogeneous abiotic and biotic conditions. Ongoing global change may potentially alter the activity of ESPs through feedback on ground conditions, vegetation and the carbon cycle. Consequently, accurate modeling of ESPs is important for improving understanding of the current and future distributions of these processes. The aims of this study were to: (1) integrate climate and multiple local predictors to develop realistic ensemble models for the four key ESPs occurring at high latitudes (slope processes, cryoturbation, nivation and palsa mires) based on the outputs of 10 modern statistical techniques; (2) test whether models of ESPs are improved by incorporating topography, soil and vegetation predictors to climate‐only models; (3) examine the relative importance of these variables in a multivariate setting. Overall, the models showed high transferability with the mean area under curve of a receiver operating characteristics (AUC) ranging from 0.83 to 0.96 and true skill statistics (TSS) from 0.52 to 0.87 for the most complex models. Even though the analyses highlighted the importance of the climate variables as the most influential predictors, three out of four models benefitted from the inclusion of local predictors. We conclude that disregarding local topography and soil conditions in spatial models of ESPs may cause a significant source of error in geomorphological distribution models. Copyright © 2014 John Wiley & Sons, Ltd. |
format |
Article in Journal/Newspaper |
author |
Aalto, Juha Luoto, Miska |
spellingShingle |
Aalto, Juha Luoto, Miska Integrating climate and local factors for geomorphological distribution models |
author_facet |
Aalto, Juha Luoto, Miska |
author_sort |
Aalto, Juha |
title |
Integrating climate and local factors for geomorphological distribution models |
title_short |
Integrating climate and local factors for geomorphological distribution models |
title_full |
Integrating climate and local factors for geomorphological distribution models |
title_fullStr |
Integrating climate and local factors for geomorphological distribution models |
title_full_unstemmed |
Integrating climate and local factors for geomorphological distribution models |
title_sort |
integrating climate and local factors for geomorphological distribution models |
publisher |
Wiley |
publishDate |
2014 |
url |
http://dx.doi.org/10.1002/esp.3554 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fesp.3554 https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.3554 |
genre |
palsa |
genre_facet |
palsa |
op_source |
Earth Surface Processes and Landforms volume 39, issue 13, page 1729-1740 ISSN 0197-9337 1096-9837 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/esp.3554 |
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Earth Surface Processes and Landforms |
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39 |
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13 |
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1729 |
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1740 |
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1810470529438580736 |