KaDonna C. Randolph

Status and future of the forest health indicators program of the USA

For two decades, the US Department of Agriculture, Forest Service, has been charged with implementing a nationwide field-based forest health monitoring effort. Given its extensive nature, the monitoring program has been gradually implemented across forest health indicators and inventoried states. Currently, the Forest Service’s Forest Inventory and Analysis program has initiated forest health inventories in all states, and most forest health indicators are being documented in terms of sampling protocols, data management structures, and estimation procedures. Field data from most sample years and indicators are available on-line with numerous analytical examples published both internally and externally. This investment in national forest health monitoring has begun to yield dividends by allowing evaluation of state/regional forest health issues (e.g., pollution and invasive pests) and contributing substantially to national/international reporting efforts (e.g., National Report on Sustainability and US EPA Annual Greenhouse Gas Estimates). With the emerging threat of climate change, full national implementation and remeasurement of a forest health inventory should allow for more robust assessment of forest communities that are undergoing unprecedented changes, aiding future land management and policy decisions.

Mortality rates associated with crown health for eastern forest tree species

The condition of tree crowns is an important indicator of tree and forest health. Crown conditions have been evaluated during inventories of the US Forest Service Forest Inventory and Analysis (FIA) program since 1999. In this study, remeasured data from 55,013 trees on 2616 FIA plots in the eastern USA were used to assess the probability of survival among various tree species using the suite of FIA crown condition variables. Logistic regression procedures were employed to develop models for predicting tree survival. Results of the regression analyses indicated that crown dieback was the most important crown condition variable for predicting tree survival for all species combined and for many of the 15 individual species in the study. The logistic models were generally successful in representing recent tree mortality responses to multiyear infestations of beech bark disease and hemlock woolly adelgid. Although our models are only applicable to trees growing in a forest setting, the utility of models that predict impending tree mortality goes beyond forest inventory or traditional forestry growth and yield models and includes any application where managers need to assess tree health or predict tree mortality including urban forest, recreation, wildlife, and pest management.

Modeling Caribbean tree heights and crown widths

Abstract. Regression models to predict total tree height and maximum crown radius as a function of diameter at breast height were developed for Caribbean trees using data collected by the U.S. Forest Service in the Commonwealth of Puerto Rico and Territory of the U.S. Virgin Islands. Nonlinear models predicting height fit the data well with an overall pseudo-R2 = 0.9220, as did models of height to diameter by Holdridge life zone and by the most frequently encountered species. The linear model predicting maximum crown radius for all trees combined fit the data poorly (R2 = 0.3478). Crown model fits showed only moderate improvements when the data were modeled by species, crown class, and inventory measurement protocol, highlighting the variability of Caribbean forest tree crowns within and between species. Height models presented here will be useful for applications such as growth and yield simulation, forest health monitoring, and wildlife habitat modeling, but the crown radius prediction models only should be applied with an understanding of their limitations.