Miller DL, Becker EA, Forney KA, Roberts JJ, Cañadas A, Schick RS. Estimating uncertainty in density surface models.
PeerJ 2022;
10:e13950. [PMID:
36032955 PMCID:
PMC9415456 DOI:
10.7717/peerj.13950]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 08/05/2022] [Indexed: 01/19/2023] Open
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.
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