Abstract

White spruce ( Picea glauca (Moench) Voss) cone crops were measured from 1986 to 2011 in the Kluane region of southwestern Yukon to test the hypothesis that the size of cone crops could be predicted from spring and summer temperature and rainfall of years t, t – 1, and t – 2. We counted cones in the top 3 m of an average of 700 white spruce trees each year spread over 3–14 sites along 210 km of the Alaska Highway and the Haines Highway. We tested the conventional explanation for white spruce cone crops that implicates summer temperatures and rainfall in years t and t – 1 and rejected it, since it explained very little of the variation in our 26 years of data. We used exploratory data analysis with robust multiple regressions coupled with Akaike’s information criterion corrected (AICc) analysis to determine the best statistical model to predict the size of cone crops. We could statistically explain 54% of the variation in cone crops from July and August temperatures of years t – 1 and t – 2 and May precipitation of year t – 2. There was no indication of a periodicity in cone crops, and years of large cone crops were synchronous over the Kluane region with few exceptions. This is the first quantitative model developed for the prediction of white spruce cone crops in the Canadian boreal forest and has the surprising result that weather conditions 2 years prior to the cone crop are the most significant predictors.

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