Mortality estimation from carcass searches using the R‐package carcass — a tutorial

Abstract

his article is a tutorial for the R-package carcass. It starts with a short overview of common methods used to estimate mortality based on carcass searches. hen, it guides step by step through a simple example. First, the proportion of animals that fall into the search area is estimated. Second, carcass persistence time is estimated based on experimental data. hird, searcher efficiency is estimated. Fourth, these three estimated parameters are combined to obtain the probability that an animal killed is found by an observer. Finally, this probability is used together with the observed number of carcasses found to obtain an estimate for the total number of killed animals together with a credible interval.

Carcass Persistence and Detectability: Reducing the Uncertainty Surrounding Wildlife-Vehicle Collision Surveys

“…before it is decomposed by traffic or removed by scavengers [20], and is influenced by several factors, including the size of the carcass, traffic volume, and weather conditions [18, 21–27]. Larger carcasses are expected to remain for longer periods, while roads with higher traffic volume are expected to reduce carcass persistence given the faster degradation of more vehicles passing by [18,23,26].…”

Methods to Monitor and Mitigate Wildlife Mortality in Railways

“…As stated, even in systematic surveys, the number of carcasses found largely underestimates mortality because (1) only a subset of animals killed stay within the area that is searched by the observer; (2) many carcasses are removed by scavengers, or decomposed until the survey occurs; and (3) some dead animals remain undetected because of the observers failure (Korner-Nievergelt et al 2015). Thus, to obtain unbiased estimates, the numbers obtained during surveys should be corrected by taking into account: (1) the proportion of animals killed in the area searched; (2) carcass persistence probability; and (3) searcher efficiency.…”

“…Thus, to obtain unbiased estimates, the numbers obtained during surveys should be corrected by taking into account: (1) the proportion of animals killed in the area searched; (2) carcass persistence probability; and (3) searcher efficiency. In order to take into account these sources of bias, several mortality estimators were developed in wind farm studies (Korner-Nievergelt et al 2015) and some have been applied to road casualties (Gerow et al 2010;Teixeira et al 2013), but rarely to railways, where these issues also apply.…”

“…However, the spatial distribution of the carcasses depends on the type of obstacle they collided with, the size of the animal, and the wind speed at the time of collision (Korner-Nievergelt et al 2015). Calculating the proportion of dead animals detected in the search area relative to the total area is rarely done because of the difficulties in estimating the variables involved (Teixeira et al 2013).…”

“…Intrinsic characteristics of the species, such as, the size, shape and color of a species, can compromise their identification (e.g., small carcasses with cryptic colors are more difficult to detect). These sources of error can be taken into account by mathematical estimators to recalculate a detectability function that is then used to correct the observed mortality estimates (Bernardino et al 2013;Korner-Nievergelt et al 2015), but this is not yet common practice in railway mortality studies.…”