In coniferous western forests, recent widespread tree mortality provided opportunities to test the long-held theory that forest cover loss increases water yield. We reviewed 78 studies of hydrologic response to standing-replacing (severe wildfire, harvest) or nonstand-replacing (drought, insects, low-severity wildfire) disturbances, and reassessed the question: Does water yield or snowpack increase after forest disturbance? Collective results indicate that postdisturbance streamflow and snowpack may increase, not change, or even decrease, and illuminate factors that may help improve predictability of hydrologic response to disturbance. Contrary to the expectation that tree mortality reduces evapotranspiration, making more water available as runoff, postdisturbance evapotranspiration sometimes increased—particularly following nonstand-replacing disturbance—because of (a) increased evaporation resulting from higher subcanopy radiation, and (b) increased transpiration resulting from rapid postdisturbance growth. Postdisturbance hydrologic response depends on vegetation structure, climate, and topography, and new hypotheses continue to be formulated and tested in this rapidly evolving discipline.

We used data collected from >1400 plots by a national forest inventory to quantify population-level indicators for a tree species of concern. Whitebark pine (Pinus albicaulis) has recently experienced high mortality throughout its US range, where we assessed the area of land with whitebark pine present, size-class distribution of individual whitebark pine, growth rates, and mortality rates, all with respect to dominant forest type. As of 2016, 51% of all standing whitebark pine trees in the US were dead. Dead whitebark pines outnumbered live ones—and whitebark pine mortality outpaced growth—in all size classes ≥22.8 cm diameter at breast height (DBH), across all forest types. Although whitebark pine occurred across 4.1 million ha in the US, the vast majority of this area (85%) and of the total number of whitebark pine seedlings (72%) fell within forest types other than the whitebark pine type. Standardized growth of whitebark pines was most strongly correlated with the relative basal area of whitebark pine trees (rho = 0.67; p < 0.01), while both standardized growth and mortality were moderately correlated with relative whitebark pine stem density (rho = 0.39 and 0.40; p = 0.031 and p < 0.01, respectively). Neither growth nor mortality were well correlated with total stand basal area, total stem density, or stand mean diameter. The abundance, extent, and relative growth vs. mortality rates of whitebark pine in multiple forest types presents opportunities for management to encourage whitebark pine recruitment in mixed-species stands. The lodgepole pine forest type contained more whitebark pine seedlings (35%) than any other forest type, suggesting that this forest type represents a potential management target for silvicultural treatments that seek to facilitate the recruitment of whitebark pine seedlings into larger size classes. National forest inventories in other countries may use a similar approach to assess species of concern.

In 2012, the US Forest Service promulgated new regulations for land-management planning that emphasize the importance of scientifically credible assessment and monitoring strategies for adaptive forest planning and the maintenance or restoration of ecological integrity. However, in an era of declining budgets, the implementation of robust assessment and monitoring strategies represents a significant challenge for fulfilling the intent of the new planning rule. In this article, we explore opportunities for using data and products produced by the USDA Forest Service’s Forest Inventory and Analysis (FIA) Program to support the implementation of the 2012 Planning Rule. FIA maintains a nationally consistent statistical sample of field plots that covers most national forests with hundreds of plots. We suggest that leveraging FIA data and products can generate efficiencies for assessment, planning, and monitoring requirements detailed in the 2012 Planning Rule, and help fulfill the adaptive intent of the new planning rule. However, strong national leadership and investment in regional-level analytical capacity, FIA liaisons, and decision-support tools are essential for systematically realizing the benefits of FIA data for forest planning across the National Forest System.