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Multistability of model and real dryland ecosystems through spatial self-organization

dc.contributor.authorBastiaansen, R.
dc.contributor.authorJaibi, O.
dc.contributor.authorDeblauwe, V.
dc.contributor.authorEppinga, M.B.
dc.contributor.authorSiteur, K.
dc.contributor.authorSiero, E.
dc.contributor.authorMermoz, S.
dc.contributor.authorBouvet, A.
dc.contributor.authorDoelman, A.
dc.contributor.authorRietkerk, M.
dc.date.accessioned2019-12-04T11:26:33Z
dc.date.available2019-12-04T11:26:33Z
dc.date.issued2018
dc.identifier.citationBastiaansen, R., Jaïbi, O., Deblauwe, V., Eppinga, M.B., Siteur, K., Siero, E., ... & Rietkerk, M. (2018). Multistability of model and real dryland ecosystems through spatial self-organization. Proceedings of the National Academy of Sciences, 1-6.
dc.identifier.issn0027-8424
dc.identifier.urihttps://hdl.handle.net/20.500.12478/4647
dc.descriptionPublished online: 15 Oct 2018
dc.description.abstractpatial self-organization of dryland vegetation constitutes one of the most promising indicators for an ecosystem’s proximity to desertification. This insight is based on studies of reaction–diffusion models that reproduce visual characteristics of vegetation patterns observed on aerial photographs. However, until now, the development of reliable early warning systems has been hampered by the lack of more in-depth comparisons between model predictions and real ecosystem patterns. In this paper, we combined topographical data, (remotely sensed) optical data, and in situ biomass measurements from two sites in Somalia to generate a multilevel description of dryland vegetation patterns. We performed an in-depth comparison between these observed vegetation pattern characteristics and predictions made by the extended-Klausmeier model for dryland vegetation patterning. Consistent with model predictions, we found that for a given topography, there is multistability of ecosystem states with different pattern wavenumbers. Furthermore, observations corroborated model predictions regarding the relationships between pattern wavenumber, total biomass, and maximum biomass. In contrast, model predictions regarding the role of slope angles were not corroborated by the empirical data, suggesting that inclusion of small-scale topographical heterogeneity is a promising avenue for future model development. Our findings suggest that patterned dryland ecosystems may be more resilient to environmental change than previously anticipated, but this enhanced resilience crucially depends on the adaptive capacity of vegetation patterns.
dc.description.sponsorshipNational Key Research and Development Program, China
dc.description.sponsorshipNational Natural Science Foundation of China
dc.description.sponsorshipEuropean Union
dc.format.extent1-6
dc.language.isoen
dc.rightsOther
dc.subjectVegetation
dc.subjectArid Zones
dc.subjectEcosystems
dc.subjectResilience
dc.titleMultistability of model and real dryland ecosystems through spatial self-organization
dc.typeJournal Article
dc.description.versionPeer Review
cg.contributor.affiliationLeiden University
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationUniversity of California
cg.contributor.affiliationUtrecht University
cg.contributor.affiliationRoyal Netherlands Institute for Sea Research
cg.contributor.affiliationEast China Normal University
cg.contributor.affiliationCarl von Ossietzky University Oldenburg
cg.contributor.affiliationInstitut de Recherche pour le Développement
cg.creator.identifierVincent Deblauwe: 0000-0001-9881-1052
cg.researchthemeNATURAL RESOURCE MANAGEMENT
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectNatural Resource Management
cg.journalProceedings of the National Academy of Sciences of the United States of America
cg.howpublishedFormally Published
cg.accessibilitystatusLimited Access
local.dspaceid101392
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1073/pnas.1804771115


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