Estimating the abundance of mouse populations of known size: Promises and pitfalls of new methods. Conn, P., Arthur, A., Bailey, L., & Singleton, G. Ecological Applications, 16(2):829–837, USGS Cooperative Fish and Wildlife Research Unit, North Carolina State University, Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, MD 20708-4017, United States, 2006. abstract bibtex Knowledge of animal abundance is fundamental to many ecological studies. Frequently, researchers cannot determine true abundance, and so must estimate it using a method such as mark-recapture or distance sampling. Recent advances in abundance estimation allow one to model heterogeneity with individual covariates or mixture distributions and to derive multimodel abundance estimators that explicitly address uncertainty about which model parameterization best represents truth. Further, it is possible to borrow information on detection probability across several populations when data are sparse. While promising, these methods have not been evaluated using mark-recapture data from populations of known abundance, and thus far have largely been overlooked by ecologists. In this paper, we explored the utility of newly developed mark-recapture methods for estimating the abundance of 12 captive populations of wild house mice (Mus musculus). We found that mark-recapture methods employing individual covariates yielded satisfactory abundance estimates for most populations. In contrast, model sets with heterogeneity formulations consisting solely of mixture distributions did not perform well for several of the populations. We show through simulation that a higher number of trapping occasions would have been necessary to achieve good estimator performance in this case. Finally, we show that simultaneous analysis of data from low abundance populations can yield viable abundance estimates. © 2006 by the Ecological Society of America.
@ARTICLE{Conn2006,
author = {Conn, P.B. and Arthur, A.D. and Bailey, L.L. and Singleton, G.R.},
title = {Estimating the abundance of mouse populations of known size: Promises
and pitfalls of new methods},
journal = {Ecological Applications},
year = {2006},
volume = {16},
pages = {829--837},
number = {2},
abstract = {Knowledge of animal abundance is fundamental to many ecological studies.
Frequently, researchers cannot determine true abundance, and so must
estimate it using a method such as mark-recapture or distance sampling.
Recent advances in abundance estimation allow one to model heterogeneity
with individual covariates or mixture distributions and to derive
multimodel abundance estimators that explicitly address uncertainty
about which model parameterization best represents truth. Further,
it is possible to borrow information on detection probability across
several populations when data are sparse. While promising, these
methods have not been evaluated using mark-recapture data from populations
of known abundance, and thus far have largely been overlooked by
ecologists. In this paper, we explored the utility of newly developed
mark-recapture methods for estimating the abundance of 12 captive
populations of wild house mice (Mus musculus). We found that mark-recapture
methods employing individual covariates yielded satisfactory abundance
estimates for most populations. In contrast, model sets with heterogeneity
formulations consisting solely of mixture distributions did not perform
well for several of the populations. We show through simulation that
a higher number of trapping occasions would have been necessary to
achieve good estimator performance in this case. Finally, we show
that simultaneous analysis of data from low abundance populations
can yield viable abundance estimates. © 2006 by the Ecological Society
of America.},
address = {USGS Cooperative Fish and Wildlife Research Unit, North Carolina
State University, Patuxent Wildlife Research Center, 12100 Beech
Forest Road, Laurel, MD 20708-4017, United States},
file = {:Connetal2006.pdf:PDF},
keywords = {Abundance estimation, Huggins-Alho model, MARK, Mark-recapture, Model
averaging, Mus musculus, Pledger model},
owner = {eric},
subdatabase = {distance},
timestamp = {2006.11.05}
}
Downloads: 0
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