Estimating uncertainty in density surface models

Author:

Miller David L.1,Becker Elizabeth A.2,Forney Karin A.34,Roberts Jason J.5,Cañadas Ana5,Schick Robert S.5

Affiliation:

1. Centre for Research into Ecological & Environmental Modelling and School of Mathematics & Statistics, University of St Andrews, St Andrews, Fife, Scotland

2. Ocean Associates, Inc. under contract to Marine Mammal and Turtle Division, Southwest Fisheries Science Center National Marine Fisheries Service, National Oceanic and Atmospheric Administration, La Jolla, CA, United States of America

3. Marine Mammal and Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Moss Landing, CA, United States of America

4. Moss Landing Marine Laboratories, San Jose State University, Moss Landing, CA, United States of America

5. Marine Geospatial Ecology Laboratory, Nicholas School of the Environment, Duke University, Durham, NC, United States of America

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.

Funder

OPNAV N45 and the SURTASS LFA Settlement Agreement, and being managed by the U.S. Navy’s Living Marine Resources program

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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3. Inferring trackline detection probabilities, g(0), for cetaceans from apparent densities in different survey conditions;Barlow;Marine Mammal Science,2015

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