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| Format: | Recurso digital |
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2026
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| Online Access: | https://doi.org/10.5281/zenodo.19253142 |
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| _version_ | 1866901228058836992 |
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| author | Demichele, Davide Camporeale, Carlo |
| author_facet | Demichele, Davide Camporeale, Carlo |
| contents | <p>Matlab scripts and datasets used to generate the results presented in the publication "A stochastic approach for Recovery Times of Coastal Dune Vegetation". The study introduces a novel analytical formulation to quantify coastal vegetation recovery time, defined as the time required to transition from a degraded to an optimal state. The approach is based on a minimal stochastic model that captures environmental variability while remaining computationally efficient. The framework links recovery dynamics to wind forcing, dune morphology, and species-specific traits.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19253142 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A stochastic approach for Recovery Times of Coastal Dune Vegetation Demichele, Davide Camporeale, Carlo <p>Matlab scripts and datasets used to generate the results presented in the publication "A stochastic approach for Recovery Times of Coastal Dune Vegetation". The study introduces a novel analytical formulation to quantify coastal vegetation recovery time, defined as the time required to transition from a degraded to an optimal state. The approach is based on a minimal stochastic model that captures environmental variability while remaining computationally efficient. The framework links recovery dynamics to wind forcing, dune morphology, and species-specific traits.</p> |
| title | A stochastic approach for Recovery Times of Coastal Dune Vegetation |
| url | https://doi.org/10.5281/zenodo.19253142 |