Process-Based Modeling to Assess the Effects of Recent Climatic Variation on Site Productivity and Forest Function across Western North America

A Spatial Forestry Productivity Potential Model for Pinus arizonica Engelm, a Key Timber Species from Northwest Mexico

Pinus arizonica is a widely distributed tree species growing in temperate forests of Northwest Mexico where it is utilized through different regeneration harvest methods. Yet, management models based on estimations of its productive potential are sorely lacking. In this study, a procedure to create a productive map using site index (SI) equations and Geographic Information Systems (GIS) was developed. A SI model for P. arizonica was created for the study area and used to classify a group of randomly sampled plots on three productivity categories (High, Medium, and Low) for management purposes. Climatic, topographic and edaphic variables were determined on the sampled plots. Then, a statistically-based analysis was performed to identify the climatic, topographic and edaphic variables significantly influencing the productivity levels. Based on the values of these significant variables, a map of productive potential was elaborated for the whole study area. Sites with the highest productivity were those with slopes ≤12°, soil depths ≥0.46 m, minimum and maximum mean annual temperatures of 5 °C and 18 °C respectively, and precipitation ≥900 mm. This methodology could be considered for similar species/conditions where productivity models do not exist or to update old models rendered obsolete by climate change.

Projecting the Spatial Distribution of Possible Planted Forest Expansion in the United States

As the demand for forest products and carbon storage in standing timbers increases, intensive planting of forest resources is expected to increase. With the increased use of plantation practices, it is important to understand the influence that forest plot characteristics have on the likelihood of where these practices are occurring. Depending on the goals of a policy or program, increasing forest planting could be a desirable outcome or something to avoid. This study estimates a spatially explicit logistical regression function to assess the likelihood that forest plots will be planted based on physical, climate, and economic factors. The empirical results are used to project the potential spatial distribution of forest planting, at the intensive and extensive land-use margins, across illustrative future scenarios. Results from this analysis offer insight into the factors that have driven forest planting in the United States historically and the potential distribution of new forest planting in the coming decades under policy or market scenarios that incentivize improved forest productivity or certain ecosystem services provided by intensively managed systems (e.g., carbon sequestration).

An ecoregion assessment of projected tree species vulnerabilities in western North America through the 21st century

Forest ecosystems across western North America will likely see shifts in both tree species dominance and composition over the rest of this century in response to climate change. Our objective in this study was to identify which ecological regions might expect the greatest changes to occur. We used the process-based growth model 3-PG, to provide estimates of tree species responses to changes in environmental conditions and to evaluate the extent that species are resilient to shifts in climate over the rest of this century. We assessed the vulnerability of 20 tree species in western North America using the Canadian global circulation model under three different emission scenarios. We provided detailed projections of species shifts by including soil maps that account for the spatial variation in soil water availability and soil fertility as well as by utilizing annual climate projections of monthly changes in air temperature, precipitation, solar radiation, vapor pressure deficit and frost at a spatial resolution of one km. Projected suitable areas for tree species were compared to their current ranges based on observations at >40 000 field survey plots. Tree species were classified as vulnerable if environmental conditions projected in the future appear outside that of their current distribution ≥70% of the time. We added a migration constraint that limits species dispersal to <200 m yr^-1 to provide more realistic projections on species distributions. Based on these combinations of constraints, we predicted the greatest changes in the distribution of dominant tree species to occur within the Northwest Forested Mountains and the highest number of tree species stressed will likely be in the North American Deserts. Projected climatic changes appear especially unfavorable for species in the subalpine zone, where major shifts in composition may lead to the emergence of new forest types.