Animal movement and resource use are tightly linked. Investigating these links to understand how animals use space and select habitats is especially relevant in areas affected by habitat fragmentation and agricultural conversion. We set out to explore the space use and habitat selection of Burmese pythons (Python bivittatus) in a heterogenous, agricultural landscape within the Sakaerat Biosphere Reserve, northeast Thailand. We used VHF telemetry to record the daily locations of seven Burmese pythons and created dynamic Brownian Bridge Movement Models to produce occurrence distributions and model movement extent and temporal patterns. To explore relationships between movement and habitat selection we used integrated step selection functions at both the individual and population level. Burmese pythons had a mean 99% occurrence distribution contour of 98.97 ha (range 9.05–285.56 ha). Furthermore, our results indicated that Burmese pythons had low mean individual motion variance, indicating infrequent moves and long periods at a single location. In general, Burmese pythons restricted movement and selected aquatic habitats but did not avoid potentially dangerous land use types like human settlements. Although our sample is small, we suggest that Burmese pythons are capitalizing on human disturbed landscapes.

Global road networks continue to expand, and the wildlife responses to these landscape‐level changes need to be understood to advise long‐term management decisions. Roads have high mortality risk to snakes because snakes typically move slowly and can be intentionally targeted by drivers. We investigated how radio‐tracked King Cobras (Ophiophagus hannah) traverse a major highway in northeast Thailand, and if reproductive cycles were associated with road hazards. We surveyed a 15.3 km stretch of Highway 304 to determine if there were any locations where snakes could safely move across the road (e.g., culverts and bridges). We used recurse analyses to detect possible road‐crossing events, and used dynamic Brownian Bridge Movement Models (dBBMMs) to show movement pathways association with possible unintentional crossing structures. We further used Integrated Step Selection Functions (ISSF) to assess seasonal differences in avoidance of major roads for adult King Cobras in relation to reproductive state. We discovered 32 unintentional wildlife crossing locations capable of facilitating King Cobra movement across the highway. While our dBBMMs broadly revealed underpasses as possible crossing points, they failed to identify specific underpasses used by telemetered individuals; however, the tracking locations pre‐ and post‐crossing and photographs provided strong evidence of underpass use. Our ISSF suggested a lower avoidance of roads during the breeding season, although the results were inconclusive. With the high volume of traffic, large size of King Cobras, and a 98.8% success rate of crossing the road in our study (nine individuals: 84 crossing attempts with one fatality), we strongly suspect that individuals are using the unintentional crossing structures to safely traverse the road. Further research is needed to determine the extent of wildlife underpass use at our study site. We propose that more consistent integration of drainage culverts and bridges could help mitigate the impacts of roads on some terrestrial wildlife.

Global road networks continue to expand, and the wildlife responses to these landscape-level changes need to be understood to advise long-term management decisions. Roads have high mortality risk to snakes because snakes typically move slowly and can be intentionally targeted by drivers. We investigated how radio-tracked King Cobras (Ophiophagus hannah) traverse a major highway in northeast Thailand, and if reproductive cycles were associated with road hazards. We surveyed a 15.3km stretch of Highway 304 to determine if there were any locations where snakes, and other wildlife, could safely move across the road (e.g., culverts, bridges). We used recurse analysis to detect possible road-crossing events, and used subsets of King Cobra movement data to create dynamic Brownian Bridge Movement Models (dBBMM) in an attempt to show movement pathways association with possible unintentional crossing structures. We further used Integrated Step Selection Functions (ISSF) to assess seasonal differences in avoidance of major roads for adult King Cobras in relation to reproductive state. We discovered 32 unintentional wildlife crossing locations capable of facilitating King Cobra movement across the highway. Our dBBMMs failed to show if underpasses were being used by telemetered individuals; however, the tracking locations pre- and post-crossing provided strong evidence of underpass use. Our ISSF suggested a lower avoidance of roads during the breeding season, though the results were inconclusive. With the high volume of traffic, large size of King Cobras and a 98.8% success rate of crossing the road in our study, we strongly suspect that individuals are using the unintentional crossing structures to safely traverse the road. Further research is needed to determine the extent of wildlife underpass use at our study site and globally, alongside using previously proven fencing to facilitate their use. We propose that more consistent integration of drainage culverts and bridges could help mitigate the impacts of roads on some terrestrial wildlife, particularly in areas where roads fragment forests and wildlife corridors.

Animal movement and resource use are tightly linked. Investigating these links to understand how animals utilize space and select habitats is especially relevant in areas that have been affected by habitat fragmentation and agricultural conversion. We set out to explore the space use and habitat selection of Burmese pythons (Python bivittatus) in a patchy land use matrix dominated by agricultural crops and human settlements. We used radio telemetry to record daily locations of seven Burmese pythons over the course of our study period of approximately 22 months. We created dynamic Brownian Bridge Movement Models (dBBMMs) for all individuals, using occurrence distributions to estimate extent of movements and motion variance to reveal temporal patterns. Then we used integrated step selection functions to determine whether individual movements were associated with particular landscape features (aquatic agriculture, forest, roads, settlements, terrestrial agriculture, water), and whether there were consistent associations at the population level. Our dBBMM estimates suggested that Burmese pythons made use of small areas (98.97 ± 35.42 ha), with low mean individual motion variance characterized by infrequent moves and long periods at a single location. At both the individual and population level, Burmese pythons in the agricultural matrix were associated with aquatic environments. Only one individual showed a strong avoidance for human settlements which is troublesome from a human-wildlife conflict angle, especially as Burmese pythons have been observed entering human settlements and consuming livestock in our study site. Our study is one of the first to contribute to the knowledge of Burmese python ecology in their native range as the majority of studies have focused on invasive populations.

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