An examination of the absence of established moose (Alces alces) populations

ABSTRACT: An analysis was performed on habitat-related factors for the southeastern side of Cape Breton Island, Nova Scotia to investigate the continued absence of moose (Alces alces) from the region. Temperature and snow depth, at times, reach levels that could cause thermal stress or impede moveme...

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Bibliographic Details
Main Authors: Karen Beazley, Helen Kwan, Tony Nette
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.686.7460
http://alcesjournal.org/index.php/alces/article/download/39/38/
Description
Summary:ABSTRACT: An analysis was performed on habitat-related factors for the southeastern side of Cape Breton Island, Nova Scotia to investigate the continued absence of moose (Alces alces) from the region. Temperature and snow depth, at times, reach levels that could cause thermal stress or impede movement of moose; however, it is unlikely that these factors dictate the absence of moose. No clear relation-ships were established between environmental concentration levels of the heavy metals molybdenum, cadmium, copper, and lead and moose distribution; however, high concentration levels of molybdenum in the Cape Breton study area warrant further investigation. Road density assessments showed that the study area has a higher level of road density compared to 2 mainland control sites; however, higher road density occurs in other areas in which moose persist. Anthropogenic factors such as poaching were not considered influential enough to exclude moose. A forest habitat comparison analysis was performed to identify habitat features that were statistically correlated with moose presence, and then were applied in a probability model to predict moose presence in the study area. The logistic regression model used to predict the probability of moose presence was composed of positively associated forest inventory variables (softwood average maturity, hardwood average maturity, % mixed hardwood, % non-forested area, total wetland area) that best fit the data. The model identified 43 % of the Cape Breton study area