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Grizzly bears, in particular interior populations without access to anadromous salmon, occur at low densities and require adult female annual survival rates >0.90 to persist. Due to low densities, high adult survival rates, small collared sample sizes, and often short field project durations, it is difficult to collect sufficient unbiased mortality data on marked individuals for comparisons at ecologically meaningful spatial and temporal scales. Previous work has identified sources and causes of mortality of grizzlies in 13 study areas of the Continent?s southern mountains, however, predictive models relating human activities and landscape conditions to grizzly bear mortality are rare. This project directly addresses a priority theme (Decision Tools) in the Sustainability program identified in the FIA Forest Science Program Strategic Plan by developing methodologies to simultaneously assess objectives for timber management with those for grizzly bears, a species that is a significant and sensitive non-timber resource. The project?s goal is to provide analytic and decision-making models to assess spatial-temporal habitat supply and mortality risk to grizzly bears from scenarios involving forest management plans. These tools will appeal to planners and managers that need to assess tradeoffs between objectives for grizzly bear management and timber production at tactical and operational levels. They will also be of interest to local and international organizations concerned with grizzly bear conservation. Because land-use planning is inherently a multi-scale, spatial-temporal process our aim is to also create models that will provide insights at strategic scales of planning, and over long time periods. The project seeks to complete 3 primary objectives over a multi-year time span: Objective 1: develop predictive models relating effects of forestry activities and landscape conditions to mortality of grizzly bears. Mortality and habitat use data collected on grizzly bears in two different study areas in the Flathead River drainage of southern BC, will be used to develop statistical models to predict the probability of grizzly bear mortality. Using logistic regression and an information-theoretic approach, models will compare locations that radio monitored bears used to those where they died against a candidate set of explanatory variables that include point (camps, settlements) and linear (trails, roads) sources of human activity in addition to geophysical and biophysical variables. We will refine and test our models by cross-validating them against independent data provided from a third study (Westslopes Grizzly Bear project) conducted in the Selkirk and Rocky mountains of the Revelstoke and Golden area. Objective 2: develop and integrate predictive models of habitat use by grizzly bears with mortality models. Seasonal models of grizzly bear habitat will be developed using logistic regression (Resource Selection Functions) or Bayesian Belief Networks and integrated with the mortality models. These models will be refined and cross-validated by testing the models' predictions to data collected in the Westslopes study of radio monitored grizzly bears. Objective 3: integrate the models produced from objectives 1 and 2 with existing timber management models to allow for assessing effects of timber objectives on grizzly bear habitat supply and mortality risk. The seasonal mortality and habitat supply models will be designed to link to forest harvesting/natural disturbance models such as ATLAS, TELES, or SELES so that trade-offs between timber supply, habitat supply, and mortality risks to bears can be evaluated under differing scenarios of timber management and land planning.
Hovey, Frederick W.. 2007. Development of analytic and decision models for assessing grizzly bear needs from forest management objectives. Forest Investment Account (FIA) - Forest Science Program. Forest Investment Account Report. FIA2007MR458
Topic: FLNRORD Research Program
Keywords: Forest, Investment, Account, (FIA), British, Columbia
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