Population reconstruction as an informative tool for monitoring chamois populations

Abstract

Knowledge of population trends is of key importance for sustainable management of wildlife and finding reliable and cost–effective monitoring methods is therefore of great interest. In two populations of Alpine chamois Rupicapra rupicapra, we collected data on mortality from 12 424 individuals hunted or found dead and population size data based on ground counts over a period of 28 years. Our study had three aims: 1) we investigated if changes in population size obtained with a simple deterministic population reconstruction (DPR) approach using hunting and natural mortality covary with population size estimates obtained from ground count data. 2) We investigated if the performance of DPR is affected by the removal of natural mortality data. 3) We assessed how many years of mortality data are needed to obtain consistent population trends using DPR. Our results suggested that 1) population abundance from mortality data using DPR significantly and positively correlated with population abundance obtained with ground counts. 2) DPR without natural mortality data performed similarly as compared to DPR using full data (hunting and natural mortality). 3) Consistent estimates of population trends can be obtained with ≥10 years of mortality data, however, this time span was influenced by the mean age at death, which in turn was affected by the local hunting regime. Our results suggest that DPR and ground counts perform similarly for the estimation of temporal trends in Alpine chamois abundance. The consistence of ground counts and DPR supports the use of these methods as reliable tools for tracking abundance of chamois populations over time. However, the reliability of abundance estimates using DPR may vary between populations and the influence of different hunting regimes must be considered for the correct interpretation of results.

Forests buffer the climate‐induced decline of body mass in a mountain herbivore

“…Because population size data were not available for all populations, we used the yearly number of harvested chamois of all age classes in relation to suitable habitat (in km²; see below for definition) within each mountain range as a density index. This density index is positively and significantly correlated with the population abundance estimates available for two populations included in this study (Reiner et al, 2020) (Fig. S1).…”

“…The grouping according to mountain ranges coincides with chamois (sub)populations ( n = 28) with only limited dispersal among (sub)populations (cf. Reiner, 2015 ; Reiner et al, 2020 ).…”

“…Within each hunting area, quotas are set for specific sex and age classes, and the duration of the hunting season is from July 16 to December 15 in Salzburg, and from August 1 to December 31 in Styria and Carinthia. Yearlings are hunted solely on the basis of numerical quotas, that is, not in relation to physical or sex characteristics, and biometric measurements were collected for all hunted individuals according to provincial hunting regulations (Reiner et al, 2020 ). For each harvested individual, body mass (eviscerated, without head, with skin) was recorded with a precision of 0.5 kg.…”

“…To investigate the potential effect of forest cover on the effect of increasing ambient temperatures on chamois body mass, we estimated the relative area covered by forest within each mountain range (hereafter ‘forest cover’). The overall suitable chamois habitat was defined as the sum of all open Alpine areas (i.e., Alpine meadows, sparsely vegetated areas and bare rocks) and all forested areas (i.e., broad leaved, coniferous, and mixed forests; Krofel et al, 2013 ; Reiner et al, 2020 ; Zeiler, 2012 ) for hunting areas with chamois harvest during the study period (Figure 1 ). Forest cover was calculated using the Corine Landcover data (Copernicus Land Monitoring Service, 2018 ) in ArcGIS Pro 2.6 (ESRI Inc., 2020 ).…”

Tracking red deer population size using deterministic cohort analysis

“…The age at death can then be used to reconstruct population size, as the number of individuals of a specific age will correspond to the sum of the number of individuals from that age and of the individuals in subsequent years (Ueno et al 2009). The reconstruction of population size through cohort analysis was originally developed in fishery (Fry 1949), but it has been extended to other taxa, including ungulates such as red deer Cervus elaphus (Lowe 1969;Mysterud et al 2007), white-tailed deer Odocoilenus virginianus (Fryxell et al 1991) and chamois Rupicapra rupicapra (Reiner et al 2020). In its simplest form, this deterministic method assumes that the population is closed, all mortality events are recorded and that, for each dead animal, exact age is known.…”