Estimating uncertainty in density surface models

• Published in: PeerJ
• Main Authors: Miller, David L., Becker, Elizabeth A., Forney, Karin A., Roberts, Jason J., Cañadas, Ana, Schick, Robert S.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2022
• Subjects: Density surface models; Distance sampling; Uncertainty quantification; Spatial modelling; Species distribution modelling; Model uncertainty; Environmental uncertainty; Balaenoptera physalus
• Online Access: https://risweb.st-andrews.ac.uk/portal/en/researchoutput/estimating-uncertainty-in-density-surface-models(aa605baa-db86-45ea-83c2-57136a782905).html; https://doi.org/10.7717/peerj.13950; https://research-repository.st-andrews.ac.uk/bitstream/10023/25879/1/Miller_2022_PeerJ_Estimating_CC.pdf

Providing uncertainty estimates for predictions derived from species distribution models is essential for management but there is little guidance on potential sources of uncertainty in predictions and how best to combine these. Here we show where uncertainty can arise in density surface models (a multi-stage spatial modelling approach for distance sampling data), focussing on cetacean density modelling. We propose an extensible, modular, hybrid analytical-simulation approach to encapsulate these sources. We provide example analyses of fin whales Balaenoptera physalus in the California Current Ecosystem.