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Anticipating species distributions: Handling sampling effort bias under a Bayesian framework.
- Source :
-
Science of the Total Environment . Apr2017, Vol. 584, p282-290. 9p. - Publication Year :
- 2017
-
Abstract
- 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, 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 species distributions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00489697
- Volume :
- 584
- Database :
- Academic Search Index
- Journal :
- Science of the Total Environment
- Publication Type :
- Academic Journal
- Accession number :
- 121672639
- Full Text :
- https://doi.org/10.1016/j.scitotenv.2016.12.038