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Anthropogenic infrastructures and land-use changes are major threats to animal movements across heterogeneous landscapes. Yet, the behavioural consequences of such constraints remain poorly understood. We investigated the relationship between the behaviour of the Common genet (Genetta genetta) and road proximity, within a dominant mixed forest-agricultural landscape in southern Portugal, fragmented by roads. Specifically, we aimed to: (i) identify and characterise the behavioural states displayed by genets and related movement patterns; and (ii) understand how behavioural states are influenced by proximity to main paved roads and landscape features. We used a multivariate Hidden Markov Model (HMM) to characterise the fine-scale movements (10-min fixes GPS) of seven genets tracked during 187 nights (mean 27 days per individual) during the period 2016–2019, using distance to major paved roads and landscape features as predictors. Our findings indicated that genet’s movement patterns were composed of three basic behavioural states, classified as “resting” (short step-lengths [mean = 10.6 m] and highly tortuous), “foraging” (intermediate step-lengths [mean = 46.1 m] and with a wide range in turning angle) and “travelling” (longer step-lengths [mean = 113.7 m] and mainly linear movements). Within the genet’s main activity-period (17.00 h-08.00 h), the movement model predicts that genets spend 36.7% of their time travelling, 35.4% foraging and 28.0% resting. The probability of genets displaying the travelling state was highest in areas far away from roads (> 500 m), whereas foraging and resting states were more likely in areas relatively close to roads (up to 500 m). Landscape features also had a pronounced effect on behaviour state occurrence. More specifically, travelling was most likely to occur in areas with lower forest edge density and close to riparian habitats, while foraging was more likely to occur in areas with higher forest edge density and far away from riparian habitats. The results suggest that, although roads represent a behavioural barrier to the movement of genets, they also take advantage of road proximity as foraging areas. Our study demonstrates that the HMM approach is useful for disentangling movement behaviour and understanding how animals respond to roadsides and fragmented habitats. We emphasise that road-engaged stakeholders need to consider movement behaviour of genets when targeting management practices to maximise road permeability for wildlife.

Context Road impacts on biodiversity are increasing worldwide. Few attempts have been made to integrate multiple taxonomic groups into roadkill mitigation plans, while using remotely sensed habitat suitability and functional connectivity. Objectives We pinpoint high-risk road locations (road planning units) for 19 woodland species from different taxonomic groups (non-flying mammals, birds, and bats) to enhance prioritisation and versatility of roadkill mitigation plans.Methods In Southern Portugal, we collected species occurrence data, roadkill, and high-resolution satellite imageries, along 15 years. We identified remotely sensed habitat metrics, in turn weighted together with functional connectivity models and road metrics to estimate roadkill vulnerability, using random forests. The roadkill cumulative risk across species is then estimated, as well the likelihood variation within and between taxonomic groups to verify prediction consistency. Results Remote sensing information thoroughly explained habitat suitability, identifying similar metrics within each group, and non-uniform environmental tolerance across species. Functional connectivity and habitat suitability significantly explained

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation‐related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications.

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