NDLI: Robustness and uncertainty in estimates of butterfly abundance from transect counts

Content Provider	Springer Nature Link
Author	Gross, Kevin Kalendra, Eric J. Hudgens, Brian R. Haddad, Nick M.
Copyright Year	2007
Abstract	Many butterfly populations are monitored by counting the number of butterflies observed while walking transects during the butterfly’s flight season. Methods for estimating population abundance from these transect counts are appealing because they allow rare populations to be monitored without capture–recapture studies that could harm fragile individuals. An increasingly popular method for estimating abundance from transect counts relies on strong assumptions about the counting process and the processes that govern butterfly population dynamics. Here, we study the statistical performance of this method when underlying model assumptions are violated. We find that estimates of population size are robust to departures from underlying model assumptions, but that the uncertainty in these estimates (i.e., confidence intervals) is substantially underestimated. Alternative bootstrap and Bayesian methods provide better measures of the uncertainty in estimated population size, but are conditional upon knowledge of butterfly detectability. Because of these requirements, a mixed approach that combines data from small capture–recapture studies with transect counts strikes the best balance between accurate monitoring and minimal injury to individuals. Our study is motivated by monitoring studies for St. Francis satyr (Neonympha mitchelli francisci), a rare and relatively immobile butterfly occurring only in the sandhills region of south-central North Carolina, USA.
Starting Page	191
Ending Page	200
Page Count	10
File Format	PDF
ISSN	14383896
Journal	Population Ecology
Volume Number	49
Issue Number	3
e-ISSN	1438390X
Language	English
Publisher	Springer-Verlag
Publisher Date	2007-02-22
Publisher Place	Tokyo
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Abundance Bayesian statistics Estimation Parametric bootstrap Population monitoring Forestry Behavioural Sciences Evolutionary Biology Plant Sciences Zoology Ecology
Content Type	Text
Resource Type	Article
Subject	Ecology, Evolution, Behavior and Systematics

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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