Human-caused landscape change negatively affects the sustainability of many wildlife populations. In Alberta, Canada, grizzly bears ( Ursus arctos L., 1758) live in one of the most populated and heavily exploited landscapes in which the species survives. Long-term physiological stress in individual animals may be the predominant mechanism linking landscape change with impaired wildlife population health. Hair cortisol concentration has been validated as a biomarker of long-term stress in humans and domestic animals; however, limited work has examined factors that may affect its measurement or interpretation. We have measured cortisol in as few as five guard hairs of a grizzly bear and have identified factors influencing hair cortisol concentration in this species. Hair cortisol varies with hair type, body region, and capture method. It is not influenced by colour, age, sex, environmental exposure (18 days), or prolonged laboratory storage (>1 year) and does not vary along the length of the hair shaft. Recommendations for prudent use of hair cortisol analysis in grizzly bears are discussed with implications for the development of hair cortisol concentration as a tool to monitor long-term stress in other wildlife.

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Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).