This study investigated the anti-predator strategies adopted by 19 radio-collared female roe deer during the fawning season by monitoring their spatial behaviour and habitat selection by means of radio-tracking. The study was carried out in a forest area of the Apennine Mountains (central Italy), where wolves are natural predators of roe deer and in summer fawns are more frequently predated than adult roe deer. The presence of fawns was monitored by means of direct observations. Roe deer fawns are known to adopt the hiding strategy during the lactation period, when they lie concealed for long periods waiting for their mothers' milk. As a consequence of this, the home-range sizes of mothers were significantly smaller than those of non-mothers during the summer lactation only. In contrast, no significant difference was found in spring, when fawns were absent, or autumn, when they were already weaned. In order to increase the success of the hiding strategy adopted by their fawns against wolf predation, mothers selected denser habitats (deciduous coppice forests) that provided denser undergrowth vegetation and limited visibility. In doing so, mothers traded open areas for forests throughout the fawning season. Indeed, mothers made significant habitat selection throughout the monitored period, and this was marked after the birth of fawns. In contrast, non-mothers generally used habitat types according to their availability. During lactation, the correlation between habitat use by mothers and habitat visibility (assessed using the form of a standard-sized roe deer) was inversely significant. These results taken together highlight the importance of anti-predator strategies adopted by roe deer mothers during the critical phase for fawn survival.

The aim of the study was to assess which kill site characteristics were selected by a lone wolf living in a protected Mediterranean coastal area near the city of Pisa, Italy, where both wild and domestic ungulates were available as potential prey. Between 2017 and 2019, we monitored the wolf’s predatory behaviour through a combination of camera trapping and active search for kill sites and prey carcasses. The main prey found was the fallow deer (n = 82); only two wild boars and no domestic ungulates were found preyed upon. The features and habitat of kill sites were modelled to test for selection by the wolf. The habitat type of kill site was composed of meadows and pastures (89.3%), woods (7.3%), degraded coastal areas (1.9%), roads and rivers (1.1%), and marshes (0.5%). We calculated their distance from landscape features and ran a binomial generalised linear model to test the influence of such landscape variables. The distance of kill sites from landscape elements was significantly different from random control sites, and a positive selection for fences was found. In fact, the wolf pushed fallow deer towards a fence to constrain them and prevent them from escaping. We also analysed the body condition of predated fallow deer as a percentage of fat content in the bone marrow of the hind legs. Our results revealed the selection of the lone wolf for deer in good body condition. This is a possible outcome of the habitat selection shown by fallow deer in the study area, where fenced open pastures are the richest in trophic resources; therefore, our findings suggest a high efficacy for the lone wolf hunting strategy, but also the adoption of a high risk feeding strategy by deer. This study suggests that a lone predator can take advantage of human infrastructures to maximise its predatory effectiveness.

We propose a design‐based strategy to exploit pellet group counts performed within plots of a prefixed size using the clearance count technique with the purposes of analyzing habitat selection, mapping the pellet group presence throughout the study area, and estimating the abundance of deer populations. As is customary in design‐based inference, the strategy is free of model assumptions, and the precision and statistical consistency of the proposed estimators are determined by the probabilistic sampling scheme adopted to locate plots. The unique necessary assumptions are the absence of migratory movements during the survey period, the accurate recording of the number of pellet groups deposited within sample plots between the 2 visits, and a precise approximation of the daily defecation rate of the population. In addition to these assumptions, which can be attained by a suitable design of the survey, the statistical soundness of the strategy rests on the use of tessellation stratified sampling, a stratified sampling scheme that ensures an even distribution of plots throughout the study area. The scheme also allows for the estimation of the standard errors and the construction of confidence intervals without involving any other assumptions. We applied this strategy in summer 2019 in a protected area of a Mediterranean coastal region to estimate the density of a fallow deer (Dama dama) population. We estimated the corresponding standard error considering the uncertainty entailed by the estimation of the daily defecation rate, with the purpose of performing reliable monitoring. The proposed strategy provided precise estimates of deer abundance and is readily implementable in the field, standardized, and easily repeatable over time, thus allowing reliable monitoring and comparisons across time and space, which are fundamental attributes for management of deer populations.