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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Wildlife ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Wildlife Management
Article . 2016 . Peer-reviewed
License: Wiley Online Library User Agreement
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Effects of lek count protocols on greater sage‐grouse population trend estimates

Authors: Adrian P. Monroe; David R. Edmunds; Cameron L. Aldridge;

Effects of lek count protocols on greater sage‐grouse population trend estimates

Abstract

ABSTRACTAnnual counts of males displaying at lek sites are an important tool for monitoring greater sage‐grouse populations (Centrocercus urophasianus), but seasonal and diurnal variation in lek attendance may increase variance and bias of trend analyses. Recommendations for protocols to reduce observation error have called for restricting lek counts to within 30 minutes of sunrise, but this may limit the number of lek counts available for analysis, particularly from years before monitoring was widely standardized. Reducing the temporal window for conducting lek counts also may constrain the ability of agencies to monitor leks efficiently. We used lek count data collected across Wyoming during 1995−2014 to investigate the effect of lek counts conducted between 30 minutes before and 30, 60, or 90 minutes after sunrise on population trend estimates. We also evaluated trends across scales relevant to management, including statewide, within Working Group Areas and Core Areas, and for individual leks. To further evaluate accuracy and precision of trend estimates from lek count protocols, we used simulations based on a lek attendance model and compared simulated and estimated values of annual rate of change in population size (λ) from scenarios of varying numbers of leks, lek count timing, and count frequency (counts/lek/year). We found that restricting analyses to counts conducted within 30 minutes of sunrise generally did not improve precision of population trend estimates, although differences among timings increased as the number of leks and count frequency decreased. Lek attendance declined >30 minutes after sunrise, but simulations indicated that including lek counts conducted up to 90 minutes after sunrise can increase the number of leks monitored compared to trend estimates based on counts conducted within 30 minutes of sunrise. This increase in leks monitored resulted in greater precision of estimates without reducing accuracy. Increasing count frequency also improved precision. These results suggest that the current distribution of count timings available in lek count databases such as that of Wyoming (conducted up to 90 minutes after sunrise) can be used to estimate sage‐grouse population trends without reducing precision or accuracy relative to trends from counts conducted within 30 minutes of sunrise. However, only 10% of all Wyoming counts in our sample (1995−2014) were conducted 61−90 minutes after sunrise, and further increasing this percentage may still bias trend estimates because of declining lek attendance. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

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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!
26
Top 10%
Top 10%
Top 10%
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