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

ABSTRACT: Spatial 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.

SUBMITTER: Bastiaansen R

PROVIDER: S-EPMC6217401 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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

Bastiaansen Robbin R Jaïbi Olfa O Deblauwe Vincent V Eppinga Maarten B MB Siteur Koen K Siero Eric E Mermoz Stéphane S Bouvet Alexandre A Doelman Arjen A Rietkerk Max M

Proceedings of the National Academy of Sciences of the United States of America 20181015 44

Spatial 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, ...[more]

PMID: 30322906

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Project description:Ample research in visual working memory (VWM) has demonstrated that the memorized items are maintained in integrated spatial configurations, even when the spatial context is task irrelevant. These insights were obtained in studies in which participants were provided with the information they memorized. However, the encoding of provided information is only one aspect of memory. In everyday life, individuals often construct their own memory representations, an aspect of memory we have previously termed self-initiated (SI) working memory. In this study, we employed a SI VWM task in which participants selected the visual targets they memorized. The spatial locations of the targets were task irrelevant. Nevertheless, we were interested to see whether participants would construct spatially structured memory representations, which would suggest that they intended to maintain the visual targets as integrated spatial configurations. The results of two experiments demonstrated that participants constructed spatially structured configurations relative to random displays. Specifically, participants selected visual targets in close spatial proximity and constructed spatial sequences with short distances and fewer path crossings. When asked to construct configurations for a hypothetical competitor in a memory contest, participants disrupted the spatial structure by selecting visual targets that were further apart and by increasing the distances between them, which suggests that these characteristics were under their control. At the end of each experiment, participants provided verbal descriptions of the strategies they used to construct the memory displays. While the spatial structure of the SI memory representations was robust, it was absent from the participants' explicit descriptions, which focused on non-spatial strategies. Participants reported selecting items based, most frequently, on semantic categories and visual features. Taken together, these results demonstrated that participants had access to the metacognitive knowledge on the spatial structure of VWM representations, knowledge they manipulated to construct memory representations that enhanced or disrupted memory performance. While having a profound impact on behavior, this metacognitive knowledge on spatial structure remained implicit, as it was absent from the participants' verbal reports. Viewed from a larger perspective, this study explores how individuals interact with the world by actively structuring their surroundings to maximize cognitive performance.

Dataset Information

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

Publications

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

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