Biophysical characteristics influencing growth and abundance of western white pine (Pinus monticola) across spatial scales in the Coeur d'Alene River Basin, Idaho.

摘要

During the past 50 years the moist forests of northern Idaho changed from being dominated by western white pine (Pinus monticola), an early seral species, to ones dominated by late seral species, grand fit (Abies grandis) and western hemlock (Tsuga heterophylla ). Variable fire regimes, successional processes and endemic insects and pathogens worked in concert to produce the stable and resilient forests of the past. This conversion to late seral species would take 200 to 300 years depending on fire regime but because of the destabilizing impacts primarily from white pine blister rust (Cronartium ribicola), it took less than 50 years in many places. To reverse these trends and elevate forest stability and resiliency, there is considerable interest in increasing western white pine's abundance.; I conducted three studies in the 350,000 ha, Coeur d'Alene River Basin in northern Idaho. In the first study, I related historical (1930s) western white pine occurrence, abundance, and productivity (outcomes) to a spatial hierarchy defined by weathering, geological feature, and landtype. Using classification and regression trees, I identified the individual and combinations of landtypes and geological features that were related to the outcomes. In the second study, I related western white pine growth to canopy opening (visible sky). In 1999, 620 observations on western white pine seedlings and saplings growing in three watersheds were collected across elevation, aspect, and canopy opening gradients. Using log-linear and logistic regression, I detected positive (p ≤ .05) relationships between western white pine growth and visible sky. Occupancy (>25%), competitive advantage (>50%), and free to grow (>92%) visible sky thresholds were identified. In the third, study I combined elements from the first two studies to relate western white pine growth to four spatial scales (canopy opening, landtype, geological feature, and weathering). A log-linear regression model using these spatial scales explained 73% of the variation in western white pine growth. These three studies provided insight into ecosystem function, and the techniques and procedures are useful for future ecological studies. These studies can help inform decisions for increasing the abundance of western white pine in the Coeur d'Alene River Basin.