Exploring the effects of truncated, pooled and sexed data in distance sampling estimation of breeding bird abundance

Distance sampling is being extensively used to estimate the abundance of animal populations. Nevertheless, the great variety of ways in which data can be analyzed may limit comparisons due to the lack of standardization of such protocols. In this study, the influence of analytical procedures for distance sampling data on density estimates and their precision was assessed. We have used data from 21 surveys of mountain ungulates in the Iberian Peninsula, France and the Italian Alps. Data from such surveys were analyzed with the program Distance 6.0. Our analyses show that estimated density can be higher for higher levels of data truncation. We also confirm that the estimates tend to be more precise when data are analyzed without binning and without truncating. We found no evidence of size biased sampling as group size and distances were uncorrelated in most of our surveys. Despite distance sampling being a fairly robust methodology, it can be sensitive to some data analysis strategies.

show abstract

“…This might seem counterintuitive and in disagreement with previous work (see for instance, Southwell & Weaver 1993;Stanbury & Gregory 2009). …”

Section: Discussioncontrasting

confidence: 54%

“…Nevertheless, the way in which data are analyzed in each survey is rarely described with this level of detail in the published literature. A few exceptions might be found for other taxonomic groups; see for instance Stanbury and Gregory (2009) on breeding bird abundance.…”

Section: Introductionmentioning

confidence: 99%

The effect of data analysis strategies in density estimation of mountain ungulates using distance sampling

Pérez

Sarasa

Moço

et al. 2014

Italian Journal of Zoology

View full text Add to dashboard Cite

show abstract

“…We estimated species ESWs and DPs using Program Distance (v. 7.2, Thomas et al 2010) for all species detected ≥30 times (Stanbury and Gregory 2009). We pooled detections for species across all sites, studies, and years to increase the number of detections (Pocewicz et al 2009).…”

Section: Methodsmentioning

confidence: 99%

Morphological traits determine detectability bias in North American grassland butterflies

et al. 2020

View full text Add to dashboard Cite

Ecological research often includes observing and counting individuals to obtain a population estimate or index that can inform conservation, management, and policy. However, the ability to accurately estimate wildlife populations has always been hindered by bias, and researchers aim to overcome bias by using correction factors that calculate the relationship between observer counts and true counts. Accurate estimates of butterfly populations, for example, are especially necessary to inform management and policy, with over 40 species listed or proposed for listing under the United States Endangered Species Act. Researchers can utilize methods like line‐transect distance sampling (LTDS) to help account for detection bias and calculate more accurate estimates, but species‐specific traits or behaviors may influence survey effectiveness. We used LTDS to detect nearly 35,000 individuals of 33 species across five studies to calculate butterfly species' effective strip widths (ESW)—a type of correction factor—across grasslands in the Great Plains, USA. To better understand how species' traits influence detectability, we modeled the influence of species' morphological, life history, and behavioral traits on ESW. The average ESW was 5.42 m, but varied from 1.84 to 12.6 m. We found that morphology (size and color) impacted the ability of observers to detect butterflies, with larger and brightly colored butterflies detected farther away from observers compared to smaller and dull‐colored butterflies. Additionally, observers were generally better at detecting individuals while they were flying and nectaring compared to resting. Surprisingly, species' life history and ecological traits did not help explain detectability differences. As conservation efforts continue to increase for butterflies, improved estimates of their population size will be necessary to evaluate management strategies and aid conservation decision‐making for future policy. Future surveys need to consider butterfly size and color, adjusting weather protocols when necessary, to minimize and account for bias associated with butterfly species, especially if accurate population estimates are a study goal.

show abstract

“…This is likely to happen when territories and nest have already been established and thus conspecific intruders may no longer be a threat. However, due to the limited information on the vocal differences between the sexes (Yee et al 2016), we are unable to determine if there was a sexual-related bias in density estimation (Stanbury & Gregory 2009). Moreover, we did not estimate the density of the owls based on different breeding stages over the survey period due to the lack of detailed information with respect to the breeding ecology of the focal species.…”

Section: Discussionmentioning

confidence: 99%

Sunda Scops-Owl Density Estimation via Distance Sampling and Call Playback

Pilla

Chong

Lim

et al. 2018

JSM

View full text Add to dashboard Cite

show abstract

Exploring the effects of truncated, pooled and sexed data in distance sampling estimation of breeding bird abundance

Cited by 10 publications

References 18 publications

The effect of data analysis strategies in density estimation of mountain ungulates using distance sampling

The effect of data analysis strategies in density estimation of mountain ungulates using distance sampling

Morphological traits determine detectability bias in North American grassland butterflies

Sunda Scops-Owl Density Estimation via Distance Sampling and Call Playback

Contact Info

Product

Resources

About