TESTING THE SENSITIVITY OF MOOSE HARVEST DATA TO CHANGES IN AERIAL POPULATION ESTIMATES IN ONTARIO

Authors

  • H. R. Timmermann
  • H. A. Whitlaw
  • A. R. Rodgers

Abstract

A model for predicting moose winter density in northcentral Ontario was computed using a stepwise linear regression relating 29 aerial census estimates to 4 harvest variables: percent hunter success, percent calves in the fall harvest, days hunted per kill and moose seen per hunter. The final model was: Moose density (/km2) = -0.065 + 1.073 (arcsine percent hunter success) + 0.554 (arcsine percent calves) (F=14.25, df=27, R2=0.528, p<0.05). It was validated by comparing predicted and observed density estimates for 33 aerial censuses carried out in the same region between 1975 and 1991. Approximately half (15/33) of the predicted density values using the harvest equation fell within the 95 percent  confidence interval of the aerial census estimate. Insufficient sample sizes in mail survey harvest data are believed to have contributed to variations between actual and predicted values in 8 of the 33 data sets. In future, we believe quality harvest data, especially hunter success and percent calves in the harvest, can help identify changes in population densities.

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Published

1993-01-01

How to Cite

Timmermann, H. R., Whitlaw, H. A., & Rodgers, A. R. (1993). TESTING THE SENSITIVITY OF MOOSE HARVEST DATA TO CHANGES IN AERIAL POPULATION ESTIMATES IN ONTARIO. Alces, 29, 47–53. Retrieved from https://alcesjournal.org/index.php/alces/article/view/979

Issue

Vol. 29 (1993): Alces Vol. 29 (1993)

Section

Articles

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