Sources of bias in applying close‐kin mark–recapture to terrestrial game species with different life histories

Author:

Sévêque Anthony1ORCID,Lonsinger Robert C.2ORCID,Waits Lisette P.3,Brzeski Kristin E.4,Komoroske Lisa M.5,Ott‐Conn Caitlin N.6,Mayhew Sarah L.7,Norton D. Cody6,Petroelje Tyler R.6ORCID,Swenson John D.5ORCID,Morin Dana J.1ORCID

Affiliation:

1. Department of Wildlife, Fisheries and Aquaculture, Forest and Wildlife Research Center Mississippi State University Mississippi State Mississippi USA

2. U.S. Geological Survey, Oklahoma Cooperative Fish and Wildlife Research Unit Oklahoma State University Stillwater Oklahoma USA

3. Department of Fish and Wildlife Resources University of Idaho Moscow Idaho USA

4. College of Forest Resources and Environment Science Michigan Technological University Houghton Michigan USA

5. Department of Environmental Conservation University of Massachusetts Amherst Amherst Massachusetts USA

6. Wildlife Division, Michigan Department of Natural Resources Marquette Michigan USA

7. Wildlife Division, Michigan Department of Natural Resources Lansing Michigan USA

Abstract

AbstractClose‐kin mark–recapture (CKMR) is a method analogous to traditional mark–recapture but without requiring recapture of individuals. Instead, multilocus genotypes (genetic marks) are used to identify related individuals in one or more sampling occasions, which enables the opportunistic use of samples from harvested wildlife. To apply the method accurately, it is important to build appropriate CKMR models that do not violate assumptions linked to the species’ and population's biology and sampling methods. In this study, we evaluated the implications of fitting overly simplistic CKMR models to populations with complex reproductive success dynamics or selective sampling. We used forward‐in‐time, individual‐based simulations to evaluate the accuracy and precision of CKMR abundance and survival estimates in species with different longevities, mating systems, and sampling strategies. Simulated populations approximated a range of life histories among game species of North America with lethal sampling to evaluate the potential of using harvested samples to estimate population size. Our simulations show that CKMR can yield nontrivial biases in both survival and abundance estimates, unless influential life history traits and selective sampling are explicitly accounted for in the modeling framework. The number of kin pairs observed in the sample, in combination with the type of kinship used in the model (parent–offspring pairs and/or half‐sibling pairs), can affect the precision and/or accuracy of the estimates. CKMR is a promising method that will likely see an increasing number of applications in the field as costs of genetic analysis continue to decline. Our work highlights the importance of applying population‐specific CKMR models that consider relevant demographic parameters, individual covariates, and the protocol through which individuals were sampled.

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3