Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 562602
Title Improving the assessment and reporting on rare and endangered species through species distribution models
Author(s) Sousa-Silva, Rita; Alves, Paulo; Honrado, João; Lomba, Angela
Source Global Ecology and Conservation 2 (2014). - ISSN 2351-9894 - p. 226 - 237.
Department(s) Biodiversity and Policy
Publication type Refereed Article in a scientific journal
Publication year 2014
Keyword(s) Conservation - Habitats directive - Monitoring - Predictive modeling - Range Tool - Suitable habitat

Species distribution models (SDMs) are increasingly used to understand rare and endangered species distributions, as well as the environmental pressures affecting them. Detailed knowledge of their distribution is critical for reporting its conservation status, and SDMs are potential tools to provide the relevant information to conservation practitioners. In this study, we modeled the distribution of Veronica micrantha, a vulnerable plant whose conservation status has to be periodically assessed under Article 17 of the Habitats Directive. The objective was to highlight the potential of SDMs for the assessment of threatened species within the periodical report on their conservation status. We used a spatially explicit modeling approach, which predicts species distributions by spatially combining two SDMs: one fitted with climate data alone and the other fitted solely with landscape variables. A comparison between the modeled distribution and the range obtained by classical methods (minimum convex polygon and Range Tool) is also presented. Our results show that while data-based approaches only consider the species known distribution, model-based methods allow a more complete evaluation of species distributions and their dynamics, as well as of the underlying pressures. This will ultimately improve the accuracy and usefulness of assessments in the context of EU reporting obligations.

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