Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Wildlife Society Bul...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Wildlife Society Bulletin
Article . 2020 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
versions View all 1 versions
addClaim

Costs and Precision of Fecal DNA Mark–Recapture versus Traditional Mark–Resight

Authors: Stephen S. Pfeiler; Mary M. Conner; Jane S. Mckeever; Thomas R. Stephenson; David W. German; Rachel S. Crowhurst; Paige R. Prentice; +1 Authors

Costs and Precision of Fecal DNA Mark–Recapture versus Traditional Mark–Resight

Abstract

ABSTRACT Wildlife managers often need to estimate population abundance to make well‐informed decisions. However, obtaining such estimates can be difficult and costly, particularly for species with small populations, wide distributions, and spatial clustering of individuals. For this reason, DNA surveys and capture–recapture modeling has become increasingly common where direct observation is consistently difficult or counts are small or variable. We compared the precision, as indicated by the coefficient of variation (CV), and cost‐effectiveness of 2 methods to estimate abundance of desert bighorn sheep ( Ovis canadensis nelsoni ) populations: traditional ground‐based mark–resight and fecal DNA capture–recapture. In the Marble Mountains in the Mojave Desert of southeastern California, USA, we conducted annual ground‐based mark–resight surveys and collected fecal samples at water sources concurrently during the dry seasons (Jun–Jul) of 2016 and 2017. Fecal DNA samples were genotyped to identify unique individuals. The Lincoln–Peterson bias‐corrected estimator and Huggins closed‐capture recapture models were used to estimate abundance for the ground‐based mark resight and fecal DNA capture–recapture, respectively. We compared costs between the 2 methods for our study and used simulations to estimate costs for a variety of possible sampling scenarios for our study system based on field‐based estimates. Population abundance estimates from fecal DNA capture–recapture achieved much greater precision (CV = 5–7%) than estimates derived from ground‐based mark–resight (CV = 21–56%). Our simulations indicated that for a population of 100, 2 sampling occasions, and resight probability of 0.20, the lowest CV obtained by mark–resight was approximately 12%. We predict the cost of abundance estimates for this level of precision (CV = 12%) from fecal DNA capture–recapture would be 28% of the cost of ground‐based mark–resight (i.e., a 72% cost reduction). We conclude that fecal DNA capture–recapture is a highly cost‐effective alternative for estimating abundance of relatively small populations (≤300) of desert bighorn sheep. More broadly, integrating simulated study designs with cost analyses provides a tool to identify the most effective method for estimating abundance over a wide variety of sampling scenarios. © 2020 The Wildlife Society.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
gold