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dc.contributor.authorVeldhuis, M.P.
dc.contributor.authorMartinez-Garcia, R.
dc.contributor.authorDeblauwe, V.
dc.contributor.authorDakos, V.
dc.date.accessioned2023-01-13T09:46:34Z
dc.date.available2023-01-13T09:46:34Z
dc.date.issued2022-10
dc.identifier.citationVeldhuis, M.P., Martinez‐Garcia, R., Deblauwe, V. & Dakos, V. (2022). Remotely‐sensed slowing down in spatially patterned dryland ecosystems. Ecography, 2022(10): e06139, 1-10.
dc.identifier.issn0906-7590
dc.identifier.urihttps://hdl.handle.net/20.500.12478/8000
dc.description.abstractRegular 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.
dc.description.sponsorshipEuropean Union’s Horizon 2020 Research and Innovation Program
dc.format.extent1-10
dc.language.isoen
dc.subjectVegetation
dc.subjectResilience
dc.subjectSudan
dc.subjectEcosystems
dc.titleRemotely-sensed slowing down in spatially patterned dryland ecosystems
dc.typeJournal Article
cg.contributor.affiliationLeiden University
cg.contributor.affiliationPrinceton University
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationUniversite de Montpellier
cg.coverage.regionAfrica
cg.coverage.regionNorth Africa
cg.coverage.countrySudan
cg.coverage.hubCentral Africa Hub
cg.researchthemePlant Production and Health
cg.identifier.bibtexciteidVELDHUIS:2022
cg.isijournalISI Journal
cg.authorship.typesCGIAR and advanced research institute
cg.iitasubjectClimate Change
cg.iitasubjectFood Security
cg.iitasubjectMeteorology and Climatology
cg.journalEcography
cg.notesOpen Access Journal; Published online: 23 Aug 2022
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1111/ecog.06139
cg.iitaauthor.identifierVincent Deblauwe: 0000-0001-9881-1052
cg.futureupdate.requiredNo
cg.identifier.issue10: e06139
cg.identifier.volume2022


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