Accounting for residual heterogeneity in double‐observer sightability models decreases bias in burro abundance estimates

Hennig, Jacob D.; Schoenecker, Kathryn A.; Cain, James W.; Roemer, Gary W.; Laake, Jeffrey L.

doi:10.1002/jwmg.22239

Cited by 3 publications

(23 citation statements)

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“…Future studies should use exact distances or smaller distance bins (i.e., 50-m). Backseat observers in helicopters cannot see directly underneath them (i.e., on the transect line) and their vision is compromised at close distances (Hennig et al 2022). If possible, including bubble windows in the helicopter for backseat observers to see directly below the aircraft may alleviate this issue.…”

Section: Discussionmentioning

confidence: 99%

“…We also fit models including detections made via radiotelemetry to account for residual heterogeneity in detection probability (model structure M R ; Hennig et al 2022). We included a 3 rd encounter occasion, placed at the beginning of the capture history line, for these models to correspond to detections made by radiotelemetry.…”

Section: Analysis Of Dos Survey Datamentioning

confidence: 99%

“…The DOS survey design suffers from negatively biased estimates due to residual heterogeneity in detection probabilities (Hennig et al 2022). The BLM encourages the testing of alternative methods that may improve upon current procedures and the National Academy of Sciences has suggested aerial infrared (IR) surveys as a possible option (NRC 2013).…”

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confidence: 99%

“…steppe of northern Wyoming (Schoenecker et al 2018) and suggested that IR technology could be an effective tool for surveying horse populations in relatively flat and open terrain. The suitability of IR cameras for use in feral burro surveys has not been formally tested, but there is reason to believe IR cameras may be less effective due to the higher ambient temperatures in desert habitats, the smaller overall body size and small group sizes of burros, and the more topographically complex landscapes burros inhabit (Hennig et al 2022).…”

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confidence: 99%

“…The BLM uses simultaneous double‐observer sightability surveys (hereafter denoted as DOS) to estimate population sizes of feral horses and burros (Lubow and Ransom 2016, Griffin et al 2020, Hennig et al 2022). The DOS survey design suffers from negatively biased estimates due to residual heterogeneity in detection probabilities (Hennig et al 2022).…”

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confidence: 99%

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Comparing methods to estimate feral burro abundance

Hennig,

Schoenecker

2023

Wildlife Society Bulletin

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Obtaining precise and unbiased estimates of feral burro (Equus asinus) abundance in the western United States is challenging due to their cryptic pelage and the rugged terrain they inhabit. Management agencies employ helicopter‐based, simultaneous double‐observer sightability surveys (hereafter denoted as DOS) to estimate abundance of burros; but the DOS method routinely produces negatively biased estimates due to residual heterogeneity in detection probability. Consequently, testing alternative methods to improve upon current procedures is warranted. Residual heterogeneity in DOS surveys can be minimized by including radio‐collared individuals in the population. Alternatively, if distance measurements are recorded, residual heterogeneity can also be reduced via a mark‐recapture distance sampling (MRDS) approach. Aerial infrared (IR) surveys offer a safer alternative than helicopter‐based surveys because they can be flown at a higher altitude and require fewer observers in the aircraft. Further, IR surveys using a distance sampling approach have been shown to generate accurate and precise estimates of feral horse (E. caballus) populations. Accordingly, we compared results of surveys using aerial IR distance sampling, the standard DOS survey, a DOS survey incorporating detections of radio‐collared individuals, and an MRDS analysis of a feral burro population with a known minimum population size in central Utah, winter 2015–2016 and spring 2016. The minimum number of burros known alive during the winter and spring surveys were 236 and 136, respectively. The average detection probability of IR surveys was P = 0.88 (SE = 0.16) and distance models produced estimates of 127 burros (95% CIs = 99–175) for the winter survey, and 94 burros (CIs = 72–134) for the spring survey. Mean detection probability of the standard DOS surveys was P = 0.78 (SE = 0.09), and model‐generated abundance estimates were 155 burros (CIs = 133–227) in winter, and 92 burros (CIs = 79–139) in spring. Incorporating detections of radio‐collared individuals in the DOS survey resulted in a decreased detection probability (P = 0.46; SE = 0.06) and increased abundance estimates to 267 (CIs = 169–571) and 155 (CIs = 128–263) for winter and spring, respectively. Mark‐recapture distance sampling produced a mean detection probability of P = 0.48 (SE = 0.12) and resulted in estimates of 282 (CIs = 178–385) and 169 (CIs = 73–310) burros in winter and spring, respectively. Our study demonstrated that aerial IR surveys conducted using standard distance sampling can produce precise estimates of burro population sizes; however, estimates were negatively biased relative to the known population size. Small sample size limits generalization of our results, but the IR‐based distance approach did not improve upon DOS surveys. Accounting for residual heterogeneity through use of radio‐collars and mark‐recapture distance sampling eliminated the negative bias from the standard DOS survey but decreased survey precision. Managers will need to decide whether unbiased but less precise abundance estimates are preferable compared to a more precise, but biased, estimate.

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Section: Discussionmentioning

confidence: 99%

Section: Analysis Of Dos Survey Datamentioning

confidence: 99%

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confidence: 99%

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Comparing methods to estimate feral burro abundance

Hennig,

Schoenecker

2023

Wildlife Society Bulletin

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Understanding implications of detection heterogeneity in wildlife abundance estimation

Laake,

Collier

2023

J Wildl Manag

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Negative bias in mark‐recapture abundance estimators due to heterogeneity in detection (capture) probability is a well‐known problem, but we believe most biologists do not understand why heterogeneity causes bias and how bias can be reduced. We demonstrate how heterogeneity creates dependence and bias in mark‐recapture approaches to abundance estimation. In comparison, heterogeneity, and hence estimator bias, is not as problematic for distance sampling and mark‐resight methods because both techniques estimate detection probabilities based on a known quantity. We show how the introduction of a known number of individuals planted into a study population prior to a mark‐recapture survey can reduce bias from heterogeneity in detection probability. We provide examples with simulation and an analysis of motion‐sensitive camera data from a study population of introduced eastern wild turkeys (Meleagris gallopavo silvestris) of known size with a subset of telemetered birds. In choosing a method for abundance estimation, careful consideration should be given to assumptions and how heterogeneity in detection probability can be accommodated for each application.

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Feral Equids

Petersen,

Scasta,

Schoenecker

et al. 2023

Rangeland Wildlife Ecology and Conservation

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Feral horses (Equus ferus caballus) and burros (E. asinus) in North America, often referred to as free-roaming, free-ranging, or wild horses and burros, are introduced species that are currently increasing in arid and semi-arid rangelands. They differ from all other North American mammals by being the only feral species protected by federal law. These equids inhabit areas featuring rough topography, limited net primary productivity, and extreme weather conditions, and have potential to cause long-term ecosystem impacts. In this chapter, we review the historical and modern context of feral equids on North American rangelands including their evolutionary past and introduction to the continent, their relationships to the environment, and challenges associated with their management. The management of feral equids is perhaps more scrutinized than any other species because their legal status, body size, physiology, foraging patterns, and local abundance directly interacts and competes with rangeland resource quality, impacts native wildlife populations, and conflicts with the multiple-uses of the land that they inhabit.

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Accounting for residual heterogeneity in double‐observer sightability models decreases bias in burro abundance estimates

Cited by 3 publications

References 32 publications

Comparing methods to estimate feral burro abundance

Comparing methods to estimate feral burro abundance

Understanding implications of detection heterogeneity in wildlife abundance estimation

Feral Equids

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