Journal article
Using artificial neural networks to predict future dryland responses to human and climate disturbances
- Abstract:
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Land degradation and sediment remobilisation in dryland environments is considered to be a significant global environmental problem. Given the potential for currently stabilised dune systems to reactivate under climate change and increased anthropogenic pressures, identifying the role of external disturbances in driving geomorphic response is vitally important. We developed a novel approach, using artificial neural networks (ANNs) applied to time series of historical reactivation-deposition e...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Version of record, pdf, 2.1MB)
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- Publisher copy:
- 10.1038/s41598-019-40429-5
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Bibliographic Details
- Publisher:
- Nature Research Publisher's website
- Journal:
- Scientific Reports Journal website
- Volume:
- 9
- Article number:
- 3855
- Publication date:
- 2019-03-07
- Acceptance date:
- 2019-02-11
- DOI:
- ISSN:
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2045-2322
- Source identifiers:
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969966
Item Description
- Pubs id:
-
pubs:969966
- UUID:
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uuid:2987622a-b462-4eb3-8c72-90ea09306b4a
- Local pid:
- pubs:969966
- Deposit date:
- 2019-02-11
Terms of use
- Copyright holder:
- Buckland et al
- Copyright date:
- 2019
- Notes:
- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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