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SDM profiling: A tool for assessing the information-content of sampled and unsampled locations for species distribution models
- Species distribution models (SDMs) are key tools in biodiversity and conservation, but assessing their reliability in unsampled locations is difficult, especially where there are sampling biases. We present a spatially-explicit sensitivity analysis for SDMs – SDM profiling – which assesses the leverage that unsampled locations have on the overall model by exploring the interaction between the effect on the variable response curves and the prevalence of the affected environmental conditions. The method adds a ‘pseudo-presence’ and ‘pseudo-absence’ to unsampled locations, re-running the SDM for each, and measuring the difference between the probability surfaces of the original and new SDMs. When the standardised difference values are plotted against each other (a ‘profile plot’), each point's location can be summarized by four leverage measures, calculated as the distances to each corner. We explore several applications: visualization of model certainty; identification of optimal new sampling locations and redundant existing locations; and flagging potentially erroneous occurrence records.
Author: | Charles J. Marsh, Yoni Gavish, Mathias Kuemmerlen, Stefan Stoll, Peter Haase, William E. Kunin |
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URN: | urn:nbn:de:hbz:tr5-2453 |
DOI: | https://doi.org/10.1016/j.ecolmodel.2022.110170 |
Parent Title (English): | Ecological Modelling |
Publisher: | Elsevier |
Document Type: | Article (specialist journals) |
Language: | English |
Date of OPUS upload: | 2023/02/23 |
Year of first Publication: | 2023 |
Publishing University: | Hochschule Trier |
Release Date: | 2023/02/23 |
Tag: | active learning; conservation; ecological niche models; model evaluation; monitoring; uncertainty |
GND Keyword: | Biodiversität; Naturschutz; Biomonitoring; Art; Verteilung; Modell |
Volume: | 475 |
Article Number: | 110170 |
Page Number: | 11 |
First Page: | 1 |
Last Page: | 11 |
Departments: | FB Umweltplanung/-technik (UCB) |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |