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

Abstract

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.

Population estimates, density–dependence and the risk of disease outbreaks in the Alpine ibex Capra ibex

“…Our results show that the mean bias of Alpine ibex counts leads to underestimations. However, the mean bias of Iberian ibex estimates -as for other mountain ungulates-is an issue that is still unresolved because the use of data truncation in distance sampling analysis can overestimate densities of mountain ungulates, and consequently, their abundance (Pérez et al, 2015). Thus, Alpine ibex may well be the most abundant ibex in Western Europe.…”

The value of transhumance for biodiversity conservation: Vulture foraging in relation to livestock movements

“…1). Transects were carried out at dawn or dusk when ungulates are more active (Pe ´rez et al 2014). For each transect, we recorded the observed species and number of individuals.…”

El alzacola rojizo en España. Población reproductora en 2020 y método de censo

“…(Buckland et al, 2015). Sin embargo, la decisión de la distancia a partir de la cual truncar los contactos puede afectar a la estima de la densidad, de manera que cuanto más se reduce esa distancia se tiende a obtener una mayor densidad y el análisis se ve expuesto al efecto de una decisión arbitraria (Pérez et al, 2015). Para minimizar este problema se ha analizado cómo afecta a la estima de densidad truncar los datos a diferentes distancias.…”