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Scripts & model output underlying the publication: Increasing spatial dispersion in ecosystem restoration mitigates risk in disturbance-driven environments

dataset

posted on 12.01.2022, 12:32 by G.S. (Gregory) FivashG.S. (Gregory) Fivash, Jim van Belzen, Karin Didderen, Wouter Lengkeek, Tjisse van der Heide, Tjeerd Bouma

This archived dataset contains the scripts used to run simulations of the model that appears in the publication: 'Increasing spatial dispersion in ecosystem restoration mitigates risk in disturbance-driven environments' (Journal of Applied Ecology, 2022).

It also includes: (1) the model output produced by our simluations, (2) the scripts used to produces the figures that appear in the manuscript, as well as (3) a set of functions that can be used to create randomized vegetation patterns (a key feature of the study).

See 'README.txt' for a full description.

Funding

This work was supported by Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)/Toegepaste en Technische Wetenschappen (TTW)-Open Technologieprogramma (OTP) grant 14424, in collaboration with private and public partners: Natuurmonumenten, STOWA, Rijkswaterstaat, Van Oord, Bureau Waardenburg, Enexio and Rodenburg Biopolymers.

History

Publisher

4TU.ResearchData

Format

(.r) R Scripts, (.rda) R binary data files readable with R, (.tiff) images, (.clip) layered images readable in the application Clup Studio.

Organizations

NIOZ Royal Netherlands Institute of Sea Research, Department of Estuarine and Delta Systems, and Utrecht University

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Read the peer-reviewed publication

Increasing spatial dispersion in ecosystem restoration mitigates risk in disturbance-driven environments

4TU.ResearchData

Categories

Keywords

restoration disturbances risk-mitigation spatial dispersion bet-hedging biogeomorphology edge-effects uncertainty

Licence

Exports