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Global biodiversity is decreasing rapidly. Parks and protected lands, while designed to conserve wildlife, often cannot provide the habitat protection needed for wide‐ranging animals such as the American black bear (Ursus americanus). Conversely, private lands are often working landscapes (e.g., farming) that have high human footprints relative to protected lands. In southwestern Alberta, road densities are highest on private lands and black bears can be hunted year‐round. On protected lands, road densities are lowest, and hunting is prohibited. On public lands under the jurisdiction of the provincial government (Crown lands), seasonal hunting is permitted. Population estimates are needed to calculate sustainable harvest levels and to monitor population trends. In our study area, there has never been a robust estimate of black bear density and spatial drivers of black bear density are poorly understood. We used non‐invasive genetic sampling and indices of habitat productivity and human disturbance to estimate density and abundance for male and female black bears in 2013 and 2014 using two methods: spatially explicit capture–recapture (SECR) and resource‐selection functions (RSF). Land tenure best explained spatial variation in black bear density. Black bear densities for females and males were highest on parkland and lowest on Crown lands. Sex ratios were female‐biased on private lands, likely a result of lower harvests and movement of females out of areas with high male density. Synthesis and application: Both SECR and RSF methods clearly indicate spatial structuring of black bear density, with a strong influence based on how lands are managed. Land tenure influences the distribution of available foods and risk from humans. We emphasize the need for improved harvest reporting, particularly for non‐licensed hunting on private land, to estimate the extent of black bear harvest mortality. American black bears are highly valued species but remain poorly monitored in North America. Using non‐invasive genetic sampling data, we used parallel methods to estimate black bear density and spatial drivers thereof. We found spatial structuring of black bear density and discussed modeling approaches and management implications. [ABSTRACT FROM AUTHOR]

Autocorrelation has been viewed as a problem in telemetry studies because sequential observations are not independent in time or space, therefore violating assumptions for statistical inference. Yet nearly all ecological and behavioural data are autocorrelated in both space and time. We argue that there is much to learn about the structure of ecological and behavioural data from patterns of autocorrelation. Such patterns include periodicity in movement and patchiness in spatial data, which can be characterized by an autocorrelogram, semivariogram or spectrum. We illustrate the utility of temporal autocorrelation functions (ACFs) for analysing step-length data from GPS telemetry of wolves (Canis lupus), cougars (Puma concolor), grizzly bears (Ursus arctos) and elk (Cervus elaphus) in western Alberta. ACFs often differ by season, reflecting differences in foraging behaviour. In wilderness landscapes, step-length ACFs for predators decay slowly to apparently random patterns, but sometimes display strong daily rhythms in areas of human disturbance. In contrast, step lengths of elk are consistently periodic, reflecting crepuscular activity.