Publication Date
8-23-2022
Document Type
Article
Publication Title
PeerJ
Volume
10
DOI
10.7717/peerj.13950
Abstract
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.
Funding Number
N39430-17-C-1982
Funding Sponsor
Southwest Fisheries Science Center
Keywords
Density surface models, Distance sampling, Environmental uncertainty, Model uncertainty, Spatial modelling, Species distribution modelling, Uncertainty quantification
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Moss Landing Marine Laboratories
Recommended Citation
David L. Miller, Elizabeth A. Becker, Karin A. Forney, Jason J. Roberts, Ana Cañadas, and Robert S. Schick. "Estimating uncertainty in density surface models" PeerJ (2022). https://doi.org/10.7717/peerj.13950
