Remotely-sensed slowing down in spatially patterned dryland ecosystems
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1111/ecog.06139 http://hdl.handle.net/11449/241556 |
Resumo: | Regular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longer-term in situ data. Here, we evaluate the theoretical prediction that regular vegetation patterns are associated with empirically derived temporal indicators (autocorrelation, variance, responsiveness) of critical slowing down in a dryland ecosystem in Sudan using different remote sensing products. We use recently developed methods using remote-sensing EVI time-series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test the predicted slowing down. We tested our empirical findings against theoretical predictions from a stochastic version of a spatial explicit model that has been used to describe vegetation dynamics in drylands under aridity stress. Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non-linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non-linear way. Our findings suggest that spatial self-organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non-linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions. |
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Remotely-sensed slowing down in spatially patterned dryland ecosystemsariditycritical slowing downregular vegetation patternsresilienceresponsivenessself-organizationSudantransient statesRegular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longer-term in situ data. Here, we evaluate the theoretical prediction that regular vegetation patterns are associated with empirically derived temporal indicators (autocorrelation, variance, responsiveness) of critical slowing down in a dryland ecosystem in Sudan using different remote sensing products. We use recently developed methods using remote-sensing EVI time-series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test the predicted slowing down. We tested our empirical findings against theoretical predictions from a stochastic version of a spatial explicit model that has been used to describe vegetation dynamics in drylands under aridity stress. Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non-linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non-linear way. Our findings suggest that spatial self-organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non-linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions.Inst. of Environmental Sciences (CML) Leiden Univ.Dept of Ecology and Evolutionary Biology Princeton Univ.Groningen Inst. for Evolutionary Life Sciences (GELIFES) Univ. of GroningenICTP South American Inst. for Fundamental Research&Inst. de Fisica Teorica Univ. Estadual Paulista – UNESP, SPInternational Inst. of Tropical AgricultureCenter for Tropical Research Inst. of the Environment and Sustainability Univ. of California Los AngelesInst. des Sciences de l'Evolution Montpellier Univ. of Montpellier/CNRS/EPHE/IRDICTP South American Inst. for Fundamental Research&Inst. de Fisica Teorica Univ. Estadual Paulista – UNESP, SPLeiden Univ.Princeton Univ.Univ. of GroningenUniversidade Estadual Paulista (UNESP)International Inst. of Tropical AgricultureLos AngelesUniv. of Montpellier/CNRS/EPHE/IRDVeldhuis, Michiel P.Martinez-Garcia, Ricardo [UNESP]Deblauwe, VincentDakos, Vasilis2023-03-01T21:09:52Z2023-03-01T21:09:52Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1111/ecog.06139Ecography.1600-05870906-7590http://hdl.handle.net/11449/24155610.1111/ecog.061392-s2.0-85136581520Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEcographyinfo:eu-repo/semantics/openAccess2023-03-01T21:09:52Zoai:repositorio.unesp.br:11449/241556Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:24:50.204062Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Remotely-sensed slowing down in spatially patterned dryland ecosystems |
title |
Remotely-sensed slowing down in spatially patterned dryland ecosystems |
spellingShingle |
Remotely-sensed slowing down in spatially patterned dryland ecosystems Veldhuis, Michiel P. aridity critical slowing down regular vegetation patterns resilience responsiveness self-organization Sudan transient states |
title_short |
Remotely-sensed slowing down in spatially patterned dryland ecosystems |
title_full |
Remotely-sensed slowing down in spatially patterned dryland ecosystems |
title_fullStr |
Remotely-sensed slowing down in spatially patterned dryland ecosystems |
title_full_unstemmed |
Remotely-sensed slowing down in spatially patterned dryland ecosystems |
title_sort |
Remotely-sensed slowing down in spatially patterned dryland ecosystems |
author |
Veldhuis, Michiel P. |
author_facet |
Veldhuis, Michiel P. Martinez-Garcia, Ricardo [UNESP] Deblauwe, Vincent Dakos, Vasilis |
author_role |
author |
author2 |
Martinez-Garcia, Ricardo [UNESP] Deblauwe, Vincent Dakos, Vasilis |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Leiden Univ. Princeton Univ. Univ. of Groningen Universidade Estadual Paulista (UNESP) International Inst. of Tropical Agriculture Los Angeles Univ. of Montpellier/CNRS/EPHE/IRD |
dc.contributor.author.fl_str_mv |
Veldhuis, Michiel P. Martinez-Garcia, Ricardo [UNESP] Deblauwe, Vincent Dakos, Vasilis |
dc.subject.por.fl_str_mv |
aridity critical slowing down regular vegetation patterns resilience responsiveness self-organization Sudan transient states |
topic |
aridity critical slowing down regular vegetation patterns resilience responsiveness self-organization Sudan transient states |
description |
Regular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longer-term in situ data. Here, we evaluate the theoretical prediction that regular vegetation patterns are associated with empirically derived temporal indicators (autocorrelation, variance, responsiveness) of critical slowing down in a dryland ecosystem in Sudan using different remote sensing products. We use recently developed methods using remote-sensing EVI time-series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test the predicted slowing down. We tested our empirical findings against theoretical predictions from a stochastic version of a spatial explicit model that has been used to describe vegetation dynamics in drylands under aridity stress. Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non-linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non-linear way. Our findings suggest that spatial self-organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non-linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 2023-03-01T21:09:52Z 2023-03-01T21:09:52Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1111/ecog.06139 Ecography. 1600-0587 0906-7590 http://hdl.handle.net/11449/241556 10.1111/ecog.06139 2-s2.0-85136581520 |
url |
http://dx.doi.org/10.1111/ecog.06139 http://hdl.handle.net/11449/241556 |
identifier_str_mv |
Ecography. 1600-0587 0906-7590 10.1111/ecog.06139 2-s2.0-85136581520 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ecography |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128357297029120 |