Incorporating detection probability to estimate pheasant density

Lacey T. Williamson; W. David Walter; Scott R. Klinger; Duane R. Diefenbach

doi:10.1002/jwmg.21545

Home/Archive/USGS

USGS · 70228327

Incorporating detection probability to estimate pheasant density

Lacey T. Williamson·W. David Walter·Scott R. Klinger·Duane R. Diefenbach

View original source ↗Export metadata ↓

Abstract

ndices of abundance, such as point counts, commonly are used to monitor trends in bird populations. In some circumstances, however, an index of abundance provides insufficient information for making management decisions and accurate density estimates are necessary. Wild ring-necked pheasants ( Phasianus colchicus ) were translocated to 10 study areas in Pennsylvania from 2007 to 2014 with the goal of establishing female densities of 3.86 pheasants/km 2 . We developed a population density estimator that used 3-minute crowing counts adjusted for probability of detection to estimate male pheasant density and flushing surveys to estimate the female:male ratio. To account for detection probability, we estimated the probability a pheasant was available to be detected by monitoring crowing frequency of male pheasants fitted with radio-transmitters and the probability an observer was able to detect a crowing pheasant at distances from 0 to 0.93 km. We found the probability a pheasant crowed during 3 minutes decreased linearly over our survey period from 0.66 in mid-April to 0.46 by the end of May. At the farthest distance we were able to accurately detect a crowing pheasant. We estimated the probability of detecting a pheasant at 0.80 km to be 0.019 ± 0.005 (SE), which means that we could not assume any fixed distance beyond which crowing birds could not be detected. Therefore, we replaced the probability of detection in the standard distance sampling estimator with the effective area of detection. The estimation of the effective area of detection is robust to choice of radius of the point and did not require observers to estimate the distance to crowing pheasants. We estimated the female:male ratio to be 1.02:1, despite the ratio of released pheasants being 4.46:1. Only 1 study area achieved the female density goal ( = 4.16); the maximum density at all other study areas was <2 females/km 2 . The estimator we developed incorporated multiple detection probabilities to provide density estimates and simplified the crowing count protocol by eliminating the need for observers to estimate their distance from a detected bird, which makes the estimator useful for estimation of population abundance when explicit population density objectives must be evaluated.

Explore related subjects

Journal of Wildlife Management Article

Source-reported bounding extent: 39.9434364619742° to 41.27780646738183° latitude; -79.453125° to -75.5419921875° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Lacey T. Williamson, W. David Walter, Scott R. Klinger, Duane R. Diefenbach. 2018-08-06. Incorporating detection probability to estimate pheasant density. https://doi.org/10.1002/jwmg.21545

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Validating antler- and movement-based estimates of caribou reproduction using video camera collars

Wildlife agencies invest substantial resources in monitoring ungulate reproductive rates given ongoing concerns about population trends and their implications for management. For barren-ground caribou ( Rangifer tarandus ) in the North American Arctic, data on parturition and neonate survival have traditionally been collected using visual observations of antler retention and calf presence from small, fixed-wing aircraft. However, these surveys are weather-dependent, expensive, and dangerous, motivating the development of movement-based approaches that infer reproductive events from global positioning system (GPS) location data. We had the unique opportunity to use video camera collars to validate both antler- and movement-based methods for estimating reproduction in barren-ground caribou, using data from the Porcupine (2018–2023) and Western Arctic (2021, 2023) herds in Alaska, USA, and Yukon, Canada. For the movement-based approaches, we assessed individual-based and population-based methods, which both inferred parturition following a sharp decline in movement and inferred calf loss following a sharp increase in movement. We investigated these approaches using rarified 1-, 2-, 4-, and 8-hour fix intervals. Based on video collar observations, we found that antler retention at the onset of the calving period was highly accurate for predicting parturition (96% accuracy) but became unreliable as calving progressed, as approximately 80% of parturient females shed their antlers during the calving period. In contrast, both movement methods performed marginally for estimating caribou parturition (~70% accuracy), with estimates from the individual-based method exhibiting greater bias than those from the population-based method. The individual-based method also poorly predicted neonate survival (≤49% accuracy for detecting parturition and calf fate for the Porcupine Herd). Video data revealed that inaccuracies with the movement methods often occurred when caribou bedded during storms, rested after traversing mountainous terrain, lost a calf shortly after birth, or increased movement to evade insects. These results have important implications for management agencies using antler- and movement-based methods to estimate caribou reproduction, particularly when informing assessments of population decline or recovery. Our results demonstrate the utility of video collar data for validating reproductive monitoring approaches and provide insights into how these approaches can be improved.

Alaska, Yukon↗

USGS2026

Ringtail (Bassariscus astutus) survival in southwestern Oregon

The effective conservation and management of small carnivore populations requires understanding species’ life-history traits and identifying important vital rates that drive population trajectories. However, many of these species are rare or elusive and of state or federal conservation concern, and demographic information is often lacking and difficult to obtain. At the northern limit of their range in Oregon, USA, ringtail ( Bassariscus astutus ) occupy mid-elevation forests and are a species of conservation concern because of their limited distribution and suspected low density. We initiated a radio-telemetry study in 2020 to estimate monthly and annual survival of ringtail in southwest Oregon. We monitored 26 ringtail from November 2020 to October 2022 and estimated survival rates using a known-fate framework and Program MARK. Model-averaged monthly survival estimates ranged from lows of 0.963 (SE = 0.022, 95% CI = 0.887–0.988) in spring (Feb–May) of 2021 to highs of 0.980 (SE = 0.018, 95% CI = 0.889–0.997) in summer (Jun–Oct) of 2022. Model-averaged estimates of annual survival were 0.695 (SE = 0.176, 95% CI = 0.310–0.920) during 2020–2021 and 0.728 (SE = 0.168, 95% CI = 0.336–0.934) during 2021–2022. Predation was the leading cause of mortality, but notably, no mortalities could be attributed to avian predation. Survival rates were much higher within forested landscapes in Oregon than for populations in the southwestern United States, which may have implications for regional conservation and management strategies.

Oregon↗

USGS2026

Linking distribution and return-on-investment models to optimize woody management for prairie grouse in Nebraska

Grasslands in Nebraska, USA, face threats from agricultural conversion, urban development, and woody encroachment, all of which negatively affect prairie grouse ( Tympanuchus spp.) populations. To optimize conservation planning, Nebraska wildlife agencies developed probabilistic area-based surveys for greater prairie-chicken ( T. cupido ) and sharp-tailed grouse ( T. phasianellus ) to sample landscapes across a range of environmental conditions. This design improves historical surveys and enables the development of distribution models that quantitatively define habitat associations and support scenario-based conservation planning. Using survey data collected during 2020–2022, we modeled prairie grouse occurrence and abundance as functions of land cover, topography, and climate using Bayesian logistic and zero-inflated negative binomial models with regularized horseshoe priors. We then conducted a maximum potential return-on-investment analysis of woody cover treatments, assuming sustained treatment success, relative to projected impacts of woody encroachment on prairie grouse populations by 2050. Among modeled associations were a positive association with grasslands having low woody cover and a negative association with grasslands having high woody cover. Across the 3-year period, median estimated annual populations were 142,380 for greater prairie-chicken (range of 95% CIs across years = 68,821–277,615) and 64,154 for sharp-tailed grouse (range of 95% CIs across years = 27,550–146,559). Under projected woody encroachment, mean predicted population declines were 10% for greater prairie-chicken (range of 95% CIs = 7–14%) and 6% for sharp-tailed grouse (range of 95% CIs = 5–7%). Areas with high prairie grouse density and low treatment costs in 2021, and high projected woody encroachment and population loss by 2050, offered the greatest return on investment for woody management. Return on investment was greatest in the northwestern Shortgrass Prairie ecoregion (northwestern Nebraska) for sharp-tailed grouse and the eastern Sandhills ecoregion (central Nebraska) for both species. These models underscore the value of evidence-based, quantitative approaches for prioritizing conservation actions on working lands. Scenario-based modeling could be extended to guide other treatments, such as optimizing restoration (e.g., Conservation Reserve Program) or incentivizing grassland persistence in areas with predicted climate resilience.

Nebraska↗