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Combining expert knowledge of a threatened trout distribution with sparse occupancy data for climate-related projection

July 12, 2023

Objective

To evaluate the vulnerability of Bull Trout Salvelinus confluentus to potential climate changes across its range in Oregon, we compiled disparate expert knowledge of the distribution of spawning and rearing and combined these probabilistic statements as data along with documented records of breeding and rearing in a joint occupancy model.

Methods

The joint expert knowledge–occupancy model, which was based on discrete patches of cold water (≤13°C) suitable for spawning and rearing, permitted the association of true occupancy with climate and other explanatory variables while accounting for variation in detection probability. We then applied estimated relationships of patch occupancy with explanatory variables to projected coldwater patch configurations in the years 2040 and 2080.

Result

Projections of the kilometers of occupied coldwater patch in future decades suggest precipitous declines if current relationships of occupancy with environmental variables are maintained. Impacts of climate changes in future decades manifest directly through the outright loss of coldwater patches and increases in winter high flows but also indirectly by increased isolation.

Conclusion

Combining probabilistic statements of species distributions from knowledgeable experts with sparse occupancy data may be a robust and timely alternative when large numbers of repeated occupancy surveys are infeasible.

Publication Year 2023
Title Combining expert knowledge of a threatened trout distribution with sparse occupancy data for climate-related projection
DOI 10.1002/nafm.10905
Authors Nathan Chelgren, Jason B. Dunham, Stephanie L Gunckel, David P Hockman-Wert, Chris S Allen
Publication Type Article
Publication Subtype Journal Article
Series Title North American Journal of Fisheries Management
Index ID 70246687
Record Source USGS Publications Warehouse
USGS Organization Forest and Rangeland Ecosystem Science Center