Male greater sage‐grouse detectability on leks

Fremgen, Aleshia L.; Hansen, Christopher P.; Rumble, Mark A.; Gamo, R. Scott; Millspaugh, Joshua J.

doi:10.1002/jwmg.1001

Cited by 23 publications

(53 citation statements)

References 48 publications

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“…The second source of uncertainty was addressed by conducting multiple surveys and estimating detectability (i.e., the probability of detecting ≥1 male at an active lek; MacKenzie et al , Blomberg et al ). Although we did not estimate the detectability of individual males on leks, those values are generally high (Fremgen et al ) and, based on our data, similar between helicopter and ground counts. However, non‐detection of males on leks, and possibly disturbance from helicopters, may have led to a small negative bias in our estimates of lek detection probabilities.…”

Section: Discussionsupporting

confidence: 51%

“…McCaffery et al () used N‐mixture models to estimate per‐occasion detection probability of males over a 13‐year period in Montana, but these models have been discounted by some (Barker et al ) and our estimates of detection probability are for leks rather than males. Other studies have reported detectability of marked males on leks (Johnson and Rowland , Baumgardt , Blomberg et al , Fremgen et al ), mean annual lek attendance (Blomberg et al ), or daily lek attendance rates (Fremgen ) rather than detectability of leks. Additional dual‐frame lek survey studies, especially in larger populations with less fragmented habitat, are needed to determine whether detection probability of leks in the PPR is comparable with other populations.…”

Section: Discussionmentioning

confidence: 97%

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Dual‐frame lek surveys for estimating greater sage‐grouse populations

2018

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Effective monitoring programs are important for ensuring proper management of wildlife populations, but they require substantial resources, effort, and funding. For this reason, managers often use indices of animal abundance. However, indices typically rely on untested assumptions and may be unreliable for estimating population size, status, and trend. Therefore, it is important to test the assumptions underlying indices and to evaluate more rigorous methods of population estimation. Counts of males at leks are used as an index to monitor populations of greater sage‐grouse (Centrocercus urophasianus), a species of conservation concern, throughout its range in the western United States and Canada. However, not all leks are known, and wildlife managers typically have no rigorous, quantitative estimates of the number of leks and males in any given population. Therefore, it remains unclear what proportion of leks and males are included in, or excluded from, lek‐based population status assessments, trend analyses, and management decisions. We used dual‐frame surveys, in combination with occupancy analysis to adjust for imperfect detection, to estimate the number of active leks, the number of lekking males, and the proportion of active leks and lekking males counted on annual lek surveys over 3 consecutive breeding seasons in a small, low‐density greater sage‐grouse population in northwestern Colorado, USA. We estimated that annual lek surveys captured an average of 45–74% of active leks and 43–78% of lekking males each year. Our results suggest that many active leks remain unknown and annual counts fail to account for a substantial, but variable, proportion of the number of active leks and lekking males in the population in any given year. Managers need to recognize this potential source of bias in lek‐count data and, if possible, account for it in trend analyses and management efforts. Increased cost likely precludes annual use of dual‐frame lek surveys. However, we recommend using analytical methods that account for imperfect detection, mapping potential lek habitat to improve survey efficiency, and conducting dual‐frame surveys over multiple years to better understand temporal variation in the proportion of active greater sage‐grouse leks and lekking males being counted in specific populations of interest. © 2018 The Wildlife Society.

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Section: Discussionsupporting

confidence: 51%

Section: Discussionmentioning

confidence: 97%

Dual‐frame lek surveys for estimating greater sage‐grouse populations

2018

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“…The lack of support for either visual obstruction or Julian date in our sightability model suggests vegetation is not a significant source of visibility bias in our data. In a similar study in Wyoming, USA, Fremgen et al () concluded that sagebrush height was a significant covariate in their sightability model after removing time and effort covariates. Wyoming big sagebrush and mountain big sagebrush were listed as dominant species in lower and higher elevations, respectively, in their study.…”

Section: Discussionmentioning

confidence: 98%

Visibility bias for sage‐grouse lek counts

et al. 2017

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Declining populations of greater sage‐grouse (Centrocercus urophasianus; hereafter, sage‐grouse) necessitate accurate estimates of population trends. The most widespread approach to monitoring sage‐grouse populations involves counting males attending leks and tracking changes across years. Visibility of male sage‐grouse on leks is likely <100% for numerous reasons, but this potential bias has generally been overlooked. Our objectives were to estimate the visibility bias (failure to enumerate all males on a lek during a count) of sage‐grouse and identify variables that influence visibility of males attending leks by developing a sightability model. We conducted simultaneous counts of male sage‐grouse from a truck using standard lek‐counting procedures and ground blinds during 2007–2009 in south‐central Idaho, USA. We built candidate sightability models using logistic regression with proportion counted from the blind that were also counted from the truck as the response variable. Naïve visibility in our study averaged 79%. Our sightability model suggests visibility bias decreased when sun was shining on the lek and when female birds were present, but increased with time of day. Additionally, cloud cover appeared to negatively affect visibility before sunrise, but improved visibility later in the mornings. Per our model, average visibility of male sage‐grouse on leks decreased 16% from 33 min before sunrise to 90 min past sunrise when both female birds and direct sun were recorded, and decreased 28% over the same time without direct sun or females. Additionally, our model predicted visibility decreased 9% as cloud cover increased from 0% to 100% at 30 min before sunrise, but increased 44% as cloud cover increased from 0% to 100% at 90 min past sunrise. Our study does not suggest the visibility bias we observed necessarily relates to a bias in the lek route index. However, by accounting for visibility bias, detecting population changes should require fewer counts or be evident with fewer years of data. © 2017 The Wildlife Society.

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“…For availability and detection probabilities, we assumed their product was the mean estimate previously reported from sightability models (

p_{normala} p_{d_{t}}

= 0.87; Fremgen et al. ). We similarly simulated counts of yearlings

()(, c_{{yearling}_{italicijt}})

, and the observed count used in analyses was:

c_{ijt} = c_{{adult}_{italicijt}} + c_{{yearling}_{italicijt}}

.…”

Section: Methodsmentioning

confidence: 99%

“…Additionally, detectability of grouse may be influenced by visual obstruction from vegetation, snow, and topography (Fremgen et al. ) as well as visibility changes due to weather and time of day (Baumgardt et al. ).…”

Section: Introductionmentioning

confidence: 99%

The importance of simulation assumptions when evaluating detectability in population models

et al. 2019

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Population monitoring is important for investigating a variety of ecological questions, and N‐mixture models are increasingly used to model population size (N) and trends (λ) while estimating detectability (p) from repeated counts within primary periods (when populations are closed to changes). Extending these models to dynamic processes with serial dependence across primary periods may relax the closure assumption, but simulations to evaluate models and inform effort (e.g., number of repeated counts) typically assume p is constant or random across sites and years. Thus, it is unknown how these models perform under scenarios where trends in p confound inferences on N and λ, and conclusions regarding effort may be overoptimistic. Here, we used global positioning system data from greater sage‐grouse (Centrocercus urophasianus) to inform simulations of the detection process for lek counts of this species, and we created scenarios with and without linear annual trends in p. We then compared estimates of N and λ from hierarchical population models either fit with single maximum counts or with detectability estimated from repeated counts (dynamic N‐mixture models). We also explored using auxiliary data to correct counts for variation in detectability. Uncorrected count models consistently underestimated N by >50%, whereas N‐mixture models without auxiliary data underestimated N to a lesser degree due to unmodeled heterogeneity in p such as age. Nevertheless, estimates of λ from both types of models were unbiased and similar for scenarios without trends in p. When p declined systematically across years, uncorrected count models underestimated λ, whereas N‐mixture models estimated λ with little bias when all sites were counted repeatedly. Auxiliary data also reduced bias in parameter estimates. Evaluating population models using scenarios with systematic variation in p may better reveal potential biases and inform effort than simulations that assume p is constant or random. Dynamic N‐mixture models can distinguish between trends in p and N, but also require repeated counts within primary periods for accurate estimates. Auxiliary data may be useful when researchers lack repeated counts, wish to monitor more sites less intensively, or require unbiased estimates of N.

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Male greater sage‐grouse detectability on leks

Cited by 23 publications

References 48 publications

Dual‐frame lek surveys for estimating greater sage‐grouse populations

Dual‐frame lek surveys for estimating greater sage‐grouse populations

Visibility bias for sage‐grouse lek counts

The importance of simulation assumptions when evaluating detectability in population models

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