Obtaining reliable estimates of population abundance is of utmost importance for wildlife research and management. To this aim, camera-traps are increasingly used, as this method has the advantage of being noninvasive and allows for continuous monitoring. Camera traps can be used to estimate abundance in combination with traditional capture-recapture techniques, as well as with estimators that do not require marked individuals. Here, we investigated the use of camera-based mark-recapture methods applied to an Alpine marmot (Marmota marmota) population in the Paneveggio-Pale di San Martino Natural Park (eastern Italian Alps). We compared abundance estimates derived from a traditional capture-mark-recapture (CMR) framework and camera trap mark-resight (CTMR) over three consecutive years. CMR models estimated a population size of n = 19 individuals (95% CI = 18-27), n = 15 (14-22) and n = 24 (22-32) in 2019, 2020 and 2021 respectively. CTMR returned an estimated population size of n = 24 (95% CI = 18-30), n = 20 (17-24) and n = 22 (21-24) for the same years. The difference between the estimate of these two methods was significant only in 2020, with CMR returning a lower estimate than CTMR (95% CI = –9.4-–0.6). This difference was not significant for 2019 (95% CI = –10.9-0.9) and 2021 (95% CI = –1.8-5.9). Based on our results, the use of CTMR techniques is promising in the estimation of absolute population size of marmots, and the estimator was slightly more precise than CMR. Further studies are needed to evaluate the effectiveness of CTMR with reduced capture effort.
We measured faecal cortisol metabolites of a free-ranging riparian population of red deer to investigate potential effects of season, ambient temperature, precipitations and water level on the annual secretion pattern. Individuals may cope with environmental challenges through the secretion of stress hormones (glucocorticoids) which allows the integration of environmental change and life history traits by means of an adaptive feedback mechanism. Adaptations regard cyclic day-to-day activities, short-term environmental stressors or long-term ecological pressures. We detected a clear seasonal pattern of glucocorticoid metabolites secretion, with higher levels in winter and lower levels in summer. The model relating glucocorticoids secretion to minimum ambient temperature was the best fit to our dataset, although the observed pattern might as well be due to declining nutritional intake and reduction of metabolic rate in the cold season. We observed an improvement of the fit when stochastic events (flash flood) were included in the model, and discussed their role as potential contingent environmental stressors.