Temporal validation of an estimator for successful breeding pairs of wolves Canis lupus in the U.S. northern Rocky Mountains.

Model-based predictors derived from historical data are rarely evaluated before they are used to draw inferences. We performed a temporal validation, (i.e. assessed the performance of a predictive model using data collected from the same population after the model was developed) of a statistical predictor for the number of successful breeding pairs of wolves Canis lupus in the northern Rocky Mountains (NRM). We predicted the number of successful breeding pairs, β, in Idaho, Montana and Wyoming based on the distribution of pack sizes observed through monitoring in 2006 and 2007 (ˆβ), and compared these estimates to the minimum number of successful breeding pairs, β_MIN, observed through intensive monitoring. β_MIN was consistently included within the 95% confidence intervals of ˆβ for all states in both years (except for Idaho in 2007), generally following the pattern ˆβ_L (lower 95% prediction interval for ˆβ) , ˆβ_MIN , ˆ β. This evaluation of ˆβ estimates for 2006 and 2007 suggest it will be a robust model-based method for predicting successful breeding pairs of NRM wolves in the future, provided influences other than those modeled in ˆβ (e.g. disease outbreak, severe winter) do not have a strong effect on wolf populations. Managers can use ˆβ models with added confidence as part of their post-delisting monitoring of wolves in NRM. [ABSTRACT FROM AUTHOR]