TY  - JOUR
A1  - Marsh, Charles J.
A1  - Gavish, Yoni
A1  - Kuemmerlen, Mathias
A1  - Stoll, Stefan
A1  - Haase, Peter
A1  - Kunin, William E.
T1  - SDM profiling: A tool for assessing the information-content of sampled and unsampled locations for species distribution models
T2  - Ecological Modelling
N2  - 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.
KW  - active learning
KW  - conservation
KW  - ecological niche models
KW  - model evaluation
KW  - monitoring
KW  - uncertainty
KW  - Biodiversität
KW  - Naturschutz
KW  - Biomonitoring
KW  - Art
KW  - Verteilung
KW  - Modell
Y1  - 2023
UR  - https://hst.opus.hbz-nrw.de/frontdoor/index/index/docId/245
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:tr5-2453
VL  - 475
SP  - 1
EP  - 11
PB  - Elsevier
ER  -