期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 584, 期 -, 页码 282-290出版社
ELSEVIER
DOI: 10.1016/j.scitotenv.2016.12.038
关键词
Anticipation; Bayesian theorem sampling effort bias; Species distribution modeling; Uncertainty
资金
- EU BON (Building the European Biodiversity Observation Network) project - European Union under the Seventh Framework Programme [308454]
- ERANET BioDiversa FP7 project DIARS - European Union
- LIFE project Future For CoppiceS
Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories, and avoiding inappropriate decision-making. In particular, when dealing with species inventories, the bias resulting from sampling effort may lead to an over-or under-estimation of the local density of occurrences of a species. In this paper we propose an innovative method to i) map sampling effort bias using cartogram models and ii) explicitly consider such uncertainty in the modeling procedure under a Bayesian framework, which allows the integration of multilevel input data with prior information to improve the anticipation of species distributions. (C) 2017 Elsevier B.V. All rights reserved.
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