As human populations grow and come into more frequent contact with wildlife, it is important to understand how anthropogenic disturbance alters wildlife behaviour. Using fine‐scale spatial analyses, we examined how proximity to human settlements affects antipredator responses of ungulates. We studied seven common ungulate species (Kirk's dik‐dik, Thomson's gazelle, impala, common warthog, common wildebeest, common zebra and Masai giraffe) in the Tarangire–Manyara ecosystem in northern Tanzania. In zebra and giraffe, flight responses to humans were significantly more likely when closer to settlements; however, there was a weak relationship between flight responses and distance to settlement in all other species. While there was largely a weak relationship between proximity to human settlements, the distribution of settlements in the landscape appears to affect wildlife behaviour, suggesting that animals perceive and respond to spatial variation in risk exerted by humans.

Wildlife corridors are typically designed for single species, yet holistic conservation approaches require corridors suitable for multiple species. Modelling habitat linkages for wildlife is based on several modelling steps (each involving multiple choices), and in the case of multi-species corridors, an approach to optimize single species corridors to few or a single functional corridor for multiple species. To model robust corridors for multiple species and simultaneously evaluate the impact of methodological choices, we develop a multi-method approach to delineate corridors that effectively capture movement of multiple wildlife species, while limiting the area required. Using wildlife presence data collected along ground-based line transects between Lake Manyara and Tarangire National Parks, Tanzania, we assessed species-habitat association in both ensemble and stacked species distribution frameworks and used these to estimate linearly and non-linearly scaled landscape resistances for seven ungulate species. We evaluated habitat suitability and least-cost and circuit theory-based connectivity models for each species individually and generated a multi-species corridor. Our results revealed that species-habitat relationships and subsequent corridors differed across species, but the pattern of predicted landscape connectivity across the study area was similar for all seven species regardless of method (circuit theory or least-cost) and scaling of the habitat suitability-based cost surface (linear or non-linear). Stacked species distribution models were highly correlated with the seven species for all model outputs (r = 0.79 to 0.97), while having the greatest overlap with the individual species least-cost corridors (linear model: 61.6%; non-linear model: 60.2%). Zebra was the best single-species proxy for landscape connectivity. Overall, we show that multi-species corridors based on stacked species distribution models achieve relatively low cumulative costs for savanna ungulates as compared to their respective single-species corridors. Given the challenges and costs involved in acquiring data and parameterizing corridor models for multiple species, zebra may act as a suitable proxy species for ungulate corridor conservation in this system.

The jaguarundi (Puma yagouaroundi) is a small felid with a historical range from central Argentina through southern Texas. Information on the current distribution of this reclusive species is needed to inform recovery strategies in the United States where its last record was in 1986 in Texas. From 2003 to 2021, we conducted camera‐trap surveys across southern Texas and northern Tamaulipas, México to survey for medium‐sized wild cats (i.e., ocelots [Leopardus pardalis], bobcats [Lynx rufus], and jaguarundi). After 350,366 trap nights at 685 camera sites, we did not detect jaguarundis at 16 properties or along 2 highways (1050 km2) in Texas. However, we recorded 126 jaguarundi photographic detections in 15,784 trap nights on 2 properties (125.3 km2) in the northern Sierra of Tamaulipas, Tamaulipas, México. On these properties, latency to detection was 72 trap nights, with a 0.05 probability of detection per day and 0.73 photographic event rate every 100 trap nights. Due to a lack of confirmed class I sightings (e.g., specimen, photograph) in the 18 years of this study, and no other class I observations since 1986 in the United States, we conclude that the jaguarundi is likely extirpated from the United States. Based on survey effort and results from México, we would have expected to detect jaguarundis over the course of the study if still extant in Texas. We recommend that state and federal agencies consider jaguarundis as extirpated from the United States and initiate recovery actions as mandated in the federal jaguarundi recovery plan. These recovery actions include identification of suitable habitat in Texas, identification of robust populations in México, and re‐introduction of the jaguarundi to Texas.

Helicopters used for aerial wildlife surveys are expensive, dangerous and time consuming. Drones and thermal infrared cameras can detect wildlife, though the ability to detect individuals is dependent on weather conditions. While we have a good understanding of local weather conditions, we do not have a broad-scale assessment of ambient temperature to plan drone wildlife surveys. Climate change will affect our ability to conduct thermal surveys in the future. Our objective was to determine optimal annual and daily time periods to conduct surveys. We present a case study in Texas, (United States of America [USA]) where we acquired and compared average monthly temperature data from 1990 to 2019, hourly temperature data from 2010 to 2019 and projected monthly temperature data from 2021 to 2040 to identify areas where surveys would detect a commonly studied ungulate (white-tailed deer [Odocoileus virginianus]) during sunny or cloudy conditions. Mean temperatures increased when comparing the 1990–2019 to 2010–2019 periods. Mean temperatures above the maximum ambient temperature in which white-tailed deer can be detected increased in 72, 10, 10, and 24 of the 254 Texas counties in June, July, August, and September, respectively. Future climate projections indicate that temperatures above the maximum ambient temperature in which white-tailed deer can be detected will increase in 32, 12, 15, and 47 counties in June, July, August, and September, respectively when comparing 2010–2019 with 2021–2040. This analysis can assist planning, and scheduling thermal drone wildlife surveys across the year and combined with daily data can be efficient to plan drone flights.

Collisions with vehicles are a major threat to wildlife populations and often occur in identifiable patterns. To reduce wildlife road mortalities, mitigation structures including exclusionary fencing and wildlife crossings are constructed. Openings in fencing at road intersections may lead to concentration of road mortality hot spots at openings leading to a belief that these gaps concentrate road mortalities. However, it is also possible that hot spots existed at these locations before construction indicating that road mortality patterns have not changed with mitigation structure construction. Therefore, to assess mitigation structure effectiveness, it is important to examine both road mortality numbers and road mortality spatial distribution. Wildlife road mortality data was collected on a 15-km section of rural highway in Texas, USA before, during, and after the construction of wildlife mitigation structures. We expected that the number of road mortalities would decrease after construction compared to before construction and that road mortalities would become more concentrated around openings in the fence. We used ANOVA to compare numbers of road mortalities and emerging hot spot analysis and generalized linear modelling to assess changes in road mortality spatial distribution. Road mortalities were not significantly different in the before and after construction periods (p = 0.092). While there were no significant changes in road mortality patterns with construction, cluster intensity was greater when nearer to fence openings in all three time periods. Emerging hot spot analysis provides an effective and easy way to visualize road mortality patterns through time, however, due to low numbers of mortalities in many road mortality studies, including this one, the power of this analysis to detect significant changes in road mortality may be limited. This technique can provide both ecologists and transportation planners an effective tool for identifying patterns that may warrant further investigation using traditional statistical techniques.