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Aims To model regional vegetation cycles through data fusion methods for creating a 30‐m daily vegetation product from 2000 to 2018 and to analyze annual vegetation trends over this time period. Location The Yellowhead Bear Management Area, a 31,180‐km2 area in west central Alberta, Canada. Methods In this paper, we use Dynamic Time Warping (DTW) as a data fusion technique to combine Landsat 5, 7 and 8 satellite data and Moderate Resolution Image Spectroradiometer (MODIS) Aqua and Terra imagery, to quantify daily vegetation using Enhanced Vegetation Index at a 30‐m resolution, for the years 2000–2018. We validated this approach, entitled DRIVE (Daily Remote Inference of VEgetation), using imagery acquired from a network of ground cameras. Results When DRIVE was compared to start and end of season dates (SOS and EOS respectively) derived from ground cameras, correlations were r = 0.73 at SOS and r = 0.85 at EOS with a mean absolute error of 7.17 days at SOS and 10.76 days at EOS. Results showed that DRIVE accurately increased spatial and temporal resolution of remote‐sensing data. We demonstrated that SOS is advancing at a maximum rate of 0.78 days per year temporally over the 18‐year time period for varying elevation gradients and land cover classes over the region. Conclusions With DRIVE, we demonstrate the utility of DTW in quantifying vegetation cycles over a large heterogeneous region and determining how changing climate is affecting regional vegetation. DRIVE may prove to be an important method to determine how carbon sequestration is varying within fine‐scale individual plant communities in response to changing climate and likely will be beneficial to wildlife movement and habitat selection studies examining the varying response of wildlife species to changing vegetation cycles under shifting climatic conditions.

Both black and white populations from Birmingham, Alabama were analyzed for the frequencies of carbonic anhydrase II (CA II), glyoxalase I (GLO) and esterase D (EsD) isozymes. The results compared favorably with published frequencies of these genetic markers in other populations.

Changing environmental conditions are altering how animals interact with their habitats (Schmitz, Post, Burns, & Johnston, 2003). In many cases, directional changes in environmental conditions owing to changing climatic conditions are resulting in altered habitats in space and time which in turn affect animal behavior

Context To mitigate conservation conflicts, some jurisdictions translocate large carnivores into novel environments where they have no previous experience. Behavioural responses of these individuals are not typically monitored to evaluate the impacts of this management approach on the animals or populations. Aims We examined how grizzly bears (Ursus arctos) involved in conservation conflict responded to novel environments after translocation. Methods We used GPS location data to compare grizzly bears translocated to a novel environment (n = 12) with bears resident within the new area (n = 12). Our analyses investigated differences between these groups in relation to exploration behaviour, habitat use and response to human-caused mortality risk. Key results Translocated bears had higher movement rates, greater daily displacement and revisited areas less frequently than did resident bears. They spent more time in poor-quality habitat and the habitat used was of even lower quality in the second year after translocation. Translocated bears selected for agricultural lands and active oil and gas wellsites. They also spent more time in areas with higher potential mortality risk than resident bears. However, translocated bears avoided residential areas, which resident bears selected, and crossed roads at the same rate as did resident bears. Both groups avoided campgrounds and recreation sites. Only 25% of bears engaged in further conflict behaviour after translocation and 67% of translocated bears survived over the 2-year monitoring period. Conclusions This work found differences in exploration behaviour and habitat use between translocated and resident bears, and showed that translocated bears can survive without reoffending during the critical few years following translocation. Implications Managers and the public should recognise potential impacts for translocating grizzly bears. Translocated bears require time to explore and learn within their new environment, a process that can occur without repeating conflict. When conflict behaviour does re-occur, it should be viewed as a part of animal learning and not immediately as failure. On the basis of the amount of time translocated bears spent near humans and anthropogenic features, our findings suggest that translocated bears do not pose a greater threat to humans than do resident bears.