Project Code: ANC-01-047
Program: FRIP
Sponsor:ANC Timber Ltd.
Project Status:Completed

Object & Deliverables

Provide support to the ongoing fRI Research Grizzly Bear Program lead by Gord Stenhouse. Continuation of ANC-01-033.

Alberta faces ongoing and expanding challenges in land and resource management as we try to balance and reconcile our societal needs for natural resources with the desire and commitment to protect other resource values on a shared landscape. Grizzly Bears represent one such value and are a high profile species at risk in Alberta. In order to successfully recover and sustain grizzly bear populations it is felt that additional scientific data and methodologies are required to support land management decisions in provincial grizzly bear habitat to allow the measurement of progress on these objectives.

This research project focused on three separate but inter-related information needs, which were identified as research themes by the team. The first area of study was directed towards a greater and more detailed understanding of key grizzly bear food resources. Managers needs to know what these foods are, where are they found, and what their values are to bears from a nutritional standpoint. Through a combination of field data collection, laboratory and modelling work they developed nutritional estimates for common grizzly bear foods in Alberta. This data showed that bears were more likely to be limited by foods high in non-protein energy that protein. Bears were potentially able to optimize their intake of macronutrients by consuming fruit and complementary foods, such as high-protein ungulates. The team then developed bio-energetic models that aided in our understanding of the daily energy expenditures of bears, their body size as well as the reproductive energy costs for female grizzly bears, This work showed that grizzly bears in the study area have greater reproductive constraints (based on energy) than other bear populations in North America and therefore population recovery for some populations of grizzly bears in Alberta will be slower. Building upon this combination of findings the team developed new models that showed the abundance and distribution of key bears foods within our study areas. These “nutritional landscape maps” were compared with existing data sets on the distribution and abundance of bears on the landscape from DNA inventory work and a strong linkage was shown with local patterns of bear abundance. They utilized these findings and novel data sets to establish theoretical carry capacity estimates for the study area based on the nutritional requirements of bears and the nutritional characteristics for the landscape to establish that for one population unit (BMA 3) the landscape could potentially support twice the density of grizzly bears that was observed there in 2004. This component of our work suggests that ‘bottom-up’ factors relating to the differences in the spatial and temporal abundance and distribution of food resources explain local and regional patterns in distribution, abundance, body size and habitat selection of bears. This component of the project can be used by land and resource managers to guide the establishment of population recovery targets for grizzly bears populations and to assist in determining long term sustainable habitat supply targets for bears to meet their nutritional needs.
The second component of the work was focused on the identified need to improve our ability to map, measure and quantity landscape disturbance in grizzly bear habitat, as these habitat “changes” are known to influence the foods that bears depend on. A number of important technical advances were made with the fusion of fine spatial resolution Landsat imager (30m) with high temporal resolution (albeit lower spatial resolution) MODIS imagery (biweekly). This allowed detailed tracking of anthropogenic landscape change. The team utilized new satellite imagery (LiDAR) and climate data to show how the inclusion of this new high-resolution data set was valuable in improving our understanding and mapping of grizzly bear foods on the landscape. This work showed that including fine-scale terrain conditions generally affected the distribution of the studied food species more than forest canopy or climate conditions. In addition, the team also was able to integrate data sets from Landsat imagery with those from LiDAR to improve our data base of habitat classification for mapping grizzly bear habitats. The results from this integration will allow managers to understand and monitor grizzly bear habitat use on changing landscapes.
In order to improve our understanding and ability to measure reproductive performance in grizzly bears our team developed new laboratory techniques to accurately and reliably measure three reproductive hormones – estradiol, progesterone, and testosterone – in the hair of grizzly bears. We then verified that reproductive hormone dynamics in the hair of captive grizzly bears coincide with changes in reproductive status and annual activity pattern of captive adult grizzly bears. This new technique shows promise but our level of understanding possible factors that may influence these results should receive further attention.

Final Report

The complete findings of this project, methodology, observations and results are contained in the Project Final Report.