Combining individual and close‐kin mark–recapture to design an effective wildlife population survey

Abstract Close‐kin mark–recapture (CKMR) is a promising approach for assessing population size of species that have been difficult to survey using more traditional methods. Here, we combine individual and close‐kin mark–recapture in a single modeling framework (ICKMR) and provide an example of study design using this approach for Pacific walrus ( Odobenus rosmarus divergens ). We develop the ICKMR model and test it using simulated datasets, then use properties of the pseudo‐likelihood to investigate the expected precision in estimates of abundance with different proposed survey designs. Our motivating example, the Pacific walrus, is an ice‐associated marine mammal found in the Bering and Chukchi seas, where it is an important resource for Indigenous peoples. Pacific walrus abundance declined in the late 20th century, and it is currently a species of conservation concern due to potential impacts of climate change, particularly the loss of sea ice. To reduce uncertainty in population size estimates, researchers undertook a genetic mark–recapture sampling campaign from 2013 to 2017 and collected tissue samples from over 8000 individuals. Another campaign of a similar scale is ongoing (2023–2028). While sample collection was designed for individual mark–recapture, advances in CKMR methods and associated molecular techniques mean that these samples could also be suitable for CKMR. The advantages of CKMR over mark–recapture include an increased effective sample size (because each individual tags itself and its parents, siblings, and offspring) and additional insights into demographic quantities of interest. To make best use of genetic samples, we combine individual mark–recapture (IMR) with CKMR (ICKMR) and investigate whether different sampling strategies can increase precision in estimates of abundance. Our modeling approach includes special considerations for walrus life history, including a multi‐year inter‐birth interval. We found that expected coefficients of variation (CVs) of the ICKMR estimates of abundance, adult female survival, juvenile female survival, and proportion of breeding females are lower than those expected from IMR alone, and with ICKMR, fewer years of sampling can be conducted to obtain sufficient precision in estimates of abundance. This work demonstrates the utility of ICKMR and could be applicable across a variety of taxa.