White spruce (Picea glauca [Moench] Voss) is a valuable commercial species found in interior and southcentral Alaska. Numerous regional and local volume tables or equations exist; however, no statewide model exists or has been tested for accuracy. There is a demand for an accurate model to determine the cubic-foot volume of white spruce trees in Alaska. Multiple models were developed for white spruce to estimate total and merchantable cubic-foot volume to a 2-, 4-, and 6-in. top. These multiple-entry (diameter and height) models were developed for both inside and outside bark volume from a 6-in. stump. The models were tested on a regional basis at various geographic locations and were shown to be highly accurate. The Alaska models chosen have R-2 at or near 0.99 and mean square error from 0 to 0.16 for all models. These models are shown to be superior to other white spruce models in Alaska.

Global climate change may be affecting forests around the world. However, the impact of climate change on forest population dynamics, especially at the landscape or regional level, has hardly been addressed before. A new methodology was proposed to enable matrix transition models to account for climate impact on forest population dynamics. The first climate-sensitive matrix (CSMatrix) model was developed for the Alaska boreal forest based on observations from over 15 years of forest inventory. The spatially explicit model was used to map climate-induced forest population dynamics across the region. The model predicted that the basal area increment in the region under natural succession would be hindered by global warming, more so for dry upland areas than for moist wetlands. It was suggested that temperature-induced drought stress could more than offset a predicted increase of future precipitation in the region to lower overall forest productivity. At the same time, stand diversity would increase across the region through transient species redistribution. Accounting for climate conditions made the CSMatrix model more accurate than conventional matrix models. (C) 2011 Elsevier B.V. All rights reserved.

Here we developed a simple linear model to estimate white spruce bark thickness in the northern forests of Alaska. Data were collected from six areas throughout interior and southcentral Alaska. Geographic variation of bark thickness was tested between the Alaska statewide model and for each geographic area. The results show that the Alaska statewide model is accurate, simple, and robust, and has no practical geographic variation over the six areas. The model provides accurate estimates of the bark thickness for white spruce trees in Alaska for a wide array of future studies, and it is in demand by landowners and forest managers to support their management decisions.

Fire has been the dominant disturbance in boreal America since the Pleistocene, resulting in a spatial mosaic in which the most fire occurs in the continental northwest. Spatial variation in snowshoe hare (Lepus americanus) density reflects the fire mosaic. Because fire initiates secondary forest succession, a fire mosaic creates variation in the abundance of early successional plants that snowshoe hares eat in winter, leading to geographic variation in hare density. We hypothesize that fire is the template for a geographic mosaic of natural selection: where fire is greatest and hares are most abundant, hare browsing has most strongly selected juvenile‐phase woody plants for defense. We tested the hypothesis at multiple spatial scales using Alaska birch (Betula neoalaskana) and white birch (Betula papyrifera). We also examined five alternative hypotheses for geographic variation in antibrowsing defense. The fire‐hare‐defense hypothesis was supported at transcontinental, regional, and local scales; alternative hypotheses were rejected. Our results link transcontinental variation in species interactions to an abiotic environmental driver, fire. Intakes of defense toxins by Alaskan hares exceed those by Wisconsin hares, suggesting that the proposed selection mosaic may coincide with a geographic mosaic of coevolution.