Combining citizen science and survey data in a log-Gaussian Cox process framework to estimate the monthly space-use of Southern Resident Killer Whales using R-INLA and inlabru

Mary Woodcock Kroble
Saturday 10 November 2018
Date: 1 May 2019
Time: 2:00 pm - 3:00 pm

Speaker: Joe Watson (University of British Columbia, Canada)


Species distribution models (SDMs) are useful tools to help ecologists quantify species-environment relationships, and they are being increasingly used to help determine the impacts of future climate and habitat changes on species. Estimating SDMs can be tricky from a statistical point of view since the effects of spatial and temporal autocorrelations, land cover and environmental covariates and detectability functions all need to be considered and inherently modeled. Furthemore, such models often assume that data have been collected from well-designed surveys and/or studies. In practice, data are often of the form of presence-only sightings collected from ‘citizen scientists’ and/or industry, and their ‘search effort’ can be difficult to quantify. Furthermore, search effort from such sources is often concentrated in areas in which the expected count of the species under study is high, and/or where population density is high. Ignoring the search effort can lead to severely biased estimates of the species distribution.

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