Abstract:
For species at risk, it is important that demographic models be consistent with our most recent knowledge because alternate model versions can have differing predictions for wildlife and natural resource management. To establish and maintain this consistency, we can compare predicted model values to current or past observations and demographic knowledge. When novel predictor information becomes available, testing for consistency between modeled and observed values ensures the best models are used for robust, evidence‐based, wildlife management. We combine novel information on the extent of historical disturbance regimes (industrial and fire) to an existing demographic model and predict historical and projected demographics of woodland caribou (Rangifer tarandus caribou). Exploring 6 simulation experiments across 5 populations in Alberta, Canada, we identify the relative importance of industrial disturbance, fire, and population density to observed population size and growth rate. We confirm the onset of significant declines across all 5 populations began approximately 30 years ago, demonstrate these declines have been consistent, and conclude they are more likely due to industrial disturbance from the oil and gas sector within contemporary population ranges than historical fire regimes. These findings reinforce recent research on the cause of woodland caribou declines. Testing for consistency between observations and models prescribed for species recovery is paramount for assessing the cause of declines, projecting population trends, and refining recovery strategies for effective wildlife management. We provide a novel simulation method for conducting these tests.