Efficient effort allocation in line‐transect distance sampling of high‐density species: When to walk further, measure less‐often and gain precision

Abstract

Line‐transect distance sampling is widely used to estimate population densities using distances of observed targets from transect lines to model detectability. When the target taxa are high density, the frequent measuring of distances may make the method seem impractical. We present a method that improves the efficiency of distance sampling when the target species occurs at high density. Only a proportion of targets are measured to model the detection function, and the time saved on the survey is then used to cover a longer total length of transect and accrue a larger ‘count only’ sample. This approach can improve the precision of the population density estimate when the cost of measuring the distance to a detected target is more than half the cost of walking to the next target. We find the optimal proportion of distances to measure that minimises the variance of the density estimate for a fixed survey budget. We quantify how much this optimised strategy increases the precision of the density estimate compared with conventional line‐transect distance sampling. We then use simulated distance sampling data to test our expressions, and illustrate circumstances under which the optimised approach would be beneficial using distance sampling data on high‐density plants. The simulations indicate that the optimised method delivers benefits in precision, but the magnitude of the benefit is lower than predicted from our expressions, which are based on an asymptotic approximation of the variance. We apply an adjustment to the predicted benefit equation to account for this difference, and show that, in all three plant case studies, the optimised approach could improve the precision gained from a distance sampling survey between 20% and 50%. This new approach could broaden the ecological contexts in which distance sampling is applied, to include estimation of densities of abundant taxa where plots are conventionally used. The method may have interesting applications for other survey types, including multispecies surveys or those using cues or signs that occur at high density.

A comparison of survey method efficiency for estimating densities of Zebra Mussels (Dreissena polymorpha)

“…One caveat of this approach would be that the detection of many animals is known to be habitat-specific (e.g., Aars et al, 2009; Anderson et al, 2015; Ferguson et al, 2019); thus, the transects used to estimate detection should be representative of the available habitat. Work by Knights et al (2021) has shown that this could be addressed in distance surveys by measuring only a proportion of the targets, where the optimal proportion can be determined when the search time and the time taken to make a detection are known.…”

“…Work by Knights et al (2021) has shown that this could be addressed in distance surveys by measuring only a proportion of the targets, where the optimal proportion can be determined when the search time and the time taken to make a detection are known.…”

Optimally designing drone‐based surveys for wildlife abundance estimation with N‐mixture models

“…conscious sampling design; e.g. Conn et al, 2016; Knights et al, 2021). Simulation experiments are a powerful approach to address the performance of estimators in different contexts and assess optimal survey allocation to assist sampling design decisions (Kéry & Royle, 2016; Zurell et al, 2010).…”

Distance sampling from curving transects in dense tropical forests

“…Line transect distance sampling (Buckland et al, 2001) has been a popular method for estimating the density of tropical animals for decades (e.g., Plumptre, 2000; Silvius et al, 2004). The approach continues to be widely employed because it provides an unbiased estimate of density, does not require significant costs or equipment, and supports the engagement of local people in data collection (Fragoso et al, 2016; Knights et al, 2021). An implicit assumption of line transect sampling is that animals are detected from straight transects.…”

“…The random element can lead transects to cross landscape features such as rivers, swamps, dense vegetation, and more. Cutting and surveying these transects can be time‐consuming, expensive, and dangerous (Knights et al, 2021). As a result, observers may skirt around these features and deviate from the straight line.…”