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Investigating the morphological dynamics of vegetation patterns in semiarid areas: a theoretical and empirical study of ecosystem bistability
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Chen, Zhuoxue. Investigating the morphological dynamics of vegetation patterns in semiarid areas: a theoretical and empirical study of ecosystem bistability. Retrieved from https://doi.org/doi:10.7282/t3-73sd-ev39

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TitleInvestigating the morphological dynamics of vegetation patterns in semiarid areas: a theoretical and empirical study of ecosystem bistability
NameChen, Zhuoxue (author); Bonachela, Juan (chair); Morin, Peter (member); Richard, Lathrop (member); Rutgers University; School of Graduate Studies
Date Created2023
Other Date2023-05 (degree)
SubjectEcology, Arid regions plants -- Morphology
Extent75 pages : illustrations
DescriptionDryland ecosystems are vulnerable to desertification, which is a pressing issue in the face of global climate change. In these ecosystems, vegetation often grows in spatially periodic patterns that differ as aridity increases (clumps, labyrinths and gaps), which has been widely studied theoretically to better understand how close the system is to reach the point of desertification. Most theoretical models, however, also predict bistability close to the ecological transition. Bistability adds to the challenges posed by desertification, since environmental fluctuations can make the system switch between two states (here, desert and vegetated states) that are stable for a given environmental condition. Although studies have investigated how to identify whether the system is approaching desertification, none of the existing methods can indicate the presence of bistability. In our study, we combined empirical and theoretical methods to investigate whether there exist early-warning indicators of bistability. Specifically, we found that the morphology of the vegetation pattern, and how it changes with aridity, provide two reliable indicators of bistability and an impending desertification transition. Our approach is simple and accessible with existing data, and therefore can potentially be applied to a diversity of systems to inform future management strategies.
NoteM.S.
NoteIncludes bibliographical references
Genretheses
Persistent URLhttps://doi.org/doi:10.7282/t3-73sd-ev39
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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