fThe control of multihost pathogens, such as Coxiella burnetii, should rely on accurate information about the roles played by the main hosts. We aimed to determine the involvement of the red deer (Cervus elaphus) in the ecology of C. burnetii. We predicted that red deer populations from broad geographic areas within a European context would be exposed to C. burnetii, and therefore, we hypothesized that a series of factors would modulate the exposure of red deer to C. burnetii. To test this hypothesis, we designed a retrospective survey of 47 Iberian red deer populations from which 1,751 serum samples and 489 spleen samples were collected. Sera were analyzed by enzyme-linked immunosorbent assays (ELISA) in order to estimate exposure to C. burnetii, and spleen samples were analyzed by PCR in order to estimate the prevalence of systemic infections. Thereafter, we gathered 23 variables-within environmental, host, and management factors-potentially modulating the risk of exposure of deer to C. burnetii, and we performed multivariate statistical analyses to identify the main risk factors. Twenty-three populations were seropositive (48.9%), and C. burnetii DNA in the spleen was detected in 50% of the populations analyzed. The statistical analyses reflect the complexity of C. burnetii ecology and suggest that although red deer may maintain the circulation of C. burnetii without third species, the most frequent scenario probably includes other wild and domestic host species. These findings, taken together with previous evidence of C. burnetii shedding by naturally infected red deer, point at this wild ungulate as a true reservoir for C. burnetii and an important node in the life cycle of C. burnetii, at least in the Iberian Peninsula.C oxiella burnetii is a Gram-negative intracellular bacterium that causes Q fever, a disease that affects both humans and animals. Whereas the epidemiological status of C. burnetii in European domestic ruminants is well known (1), information for wildlife is mostly local and scattered (2, 3). Although the majority of human Q fever outbreaks are linked to the transmission of C. burnetii from domestic ruminants (4, 5), the ability of C. burnetii to infect wild hosts (3, 6) and its high environmental resistance (1) make wildlife species potential reservoirs of C. burnetii. Based on this hypothesis, wildlife could maintain C. burnetii and transmit it to wildlife (7), domestic animals (8), or humans (9). It is therefore of paramount relevance (i) to identify those potential wild reservoir species that could, through direct and indirect interactions, transmit C. burnetii to target species (domestic animals and humans) and (ii) to determine which environmental factors are the main drivers of C. burnetii within the most relevant wild reservoirs. Efficient prevention of C. burnetii transmission at the wildlifedomestic-animal-human interface can be approached only once the main reservoirs have been identified and the driving risk factors are known (10).Several wild ruminant species are present and wel...

Over the last decades roe deer (Capreolus capreolus) populations have increased in number and distribution throughout Europe. Such increases have profound impacts on ecosystems, both positive and negative. Therefore monitoring roe deer populations is essential for the appropriate management of this species, in order to achieve a balance between conservation and mitigation of the negative impacts. Despite being required for an effective management plan, the study of roe deer ecology in Portugal is at an early stage, and hence there is still a complete lack of knowledge of roe deer density within its known range. Distance sampling of pellet groups coupled with production and decay rates for pellet groups provided density estimates for roe deer in northeastern Portugal (Lombada National Hunting Area - LNHA, Serra de Montesinho – SM and Serra da Nogueira – SN; LNHA and SM located in Montesinho Natural Park). The estimated roe deer density using a stratified detection function was 1.23/100 ha for LNHA, 4.87/100 ha for SM and 4.25/100 ha in SN, with 95% confidence intervals (CI) of 0.68 to 2.21, 3.08 to 7.71 and 2.25 to 8.03, respectively. For the entire area, the estimated density was about 3.51/100 ha (95% CI - 2.26–5.45). This method can provide estimates of roe deer density, which will ultimately support management decisions. However, effective monitoring should be based on long-term studies that are able to detect population fluctuations. This study represents the initial phase of roe deer monitoring at the edge of its European range and intends to fill the gap in this species ecology, as the gathering of similar data over a number of years will provide the basis for stronger inferences. Monitoring should be continued, although the study area should be increased to evaluate the accuracy of estimates and assess the impact of management actions.

a b s t r a c tThe European roe deer population in Portugal is on the southwestern edge of its distribution. Understanding limiting factors that act on these populations enlightens both local aspects concerning their conservation and wider scale aspects of the species bioclimatic envelope, which is crucial for being better able to predict the impacts of environmental change. Accordingly, a survey was conducted to explore roe deer distribution in a 75,000 ha area located in Trás-os-Montes region, a Mediterranean landscape in the northeast of Portugal. Pellet-group counts were used to examine how roe deer distribution was related to habitat structure and composition, landscape structure, and human disturbance. The analysis considered two spatial scales: habitat patch and the wider landscape. At the patch scale, roe deer distribution was positively associated with high density of shrubs and with increasing distance from roads. At the landscape scale, roe deer distribution was negatively associated with spatial heterogeneity, namely mean shape index. Our findings suggest that landscape structure, vegetation composition and distance to roads are all important factors influencing roe deer distribution, highlighting the importance of multi-scale approaches.