Tracking 20 years of forest demographics in east Texas, USA, using national forest inventory data.

Forest resource reporting techniques primarily use the two most recent measurements for understanding forest change. Multiple remeasurements now exist within the US national forest inventory (NFI), providing an opportunity to examine long-term forest demographics. We leverage two decades of remeasurements to quantify live-dead wood demographics which can better inform estimates of resource changes in forest ecosystems. Our overall objective is to identify opportunities and gaps in tracking 20 years of forest demographics within the US NFI using east Texas as a pilot study region given its diversity of tree species, prevalence of managed conditions, frequency of disturbances, and relatively rapid change driven by a warm, humid climate. We examine growth and mortality rates, identify transitions to downed dead wood/litter and removal via harvest, and describe implications of these processes focusing on key species groups (i.e., loblolly pine, post oak, and water oak) and size classes (i.e., saplings, small and large trees). Growth and mortality rates fluctuated differently over time by species and stem sizes in response to large-scale disturbances, namely the 2011 drought in Texas. Tree-fall rates were highest in saplings and snag-fall rates trended higher in smaller trees. For removal rates, different stem sizes generally followed similar patterns within each species group. Forest demographics from the field-based US NFI are informative for identifying diffuse lagged mortality, species- and size-specific effects, and management effects. Moreover, researchers continually seek to employ ancillary data and develop new statistical methods to enhance understanding of forest resource changes from field-based inventories.

Predicting Kudzu (Pueraria montana) spread and its economic impacts in timber industry: A case study from Oklahoma.

Quantifying the economic impacts of invasive species is an essential step in developing and prioritizing invasive species management. In particular, kudzu, Pueraria montana (Lour.) Merr. is an aggressive and non-native vine that not only causes ecological damage and reduces biodiversity, but can have multiple economic consequences such as loss of timber value and volume. Using current infestation locations in Oklahoma, southcentral USA, a Monte Carlo simulation was run to estimate the natural as well as anthropogenic spread rate of kudzu in the next five years. Simulations were supplemented with an economic impact analysis within the Impact Analysis for PLANing (IMPLAN) platform. To account for economic loss in the forest product industry, a replacement cost approach with a sensitivity analysis was conducted. Occurrence data collections revealed that current kudzu populations are already established in Oklahoma forests. The results demonstrate that by year five, total industry output could be reduced by $167.9 million, which will influence 780 jobs in the most extreme case scenario. The predicted economic loss due to kudzu expansion could act as an incentive for appropriate management practices and plans to be implemented.

Tree mortality from an exceptional drought spanning mesic to semiarid ecoregions.

Significant areas of the southern USA periodically experience intense drought that can lead to episodic tree mortality events. Because drought tolerance varies among species and size of trees, such events can alter the structure and function of terrestrial ecosystem in ways that are difficult to detect with local data sets or solely with remote-sensing platforms. We investigated a widespread tree mortality event that resulted from the worst 1-year drought on record for the state of Texas, USA. The drought affected ecoregions spanning mesic to semiarid climate zones and provided a unique opportunity to test hypotheses related to how trees of varying genus and size were affected. The study was based on an extensive set of 599 distributed plots, each 0.16 ha, surveyed in the summer following the drought. In each plot, dead trees larger than 12.7 cm in diameter were counted, sized, and identified to the genus level. Estimates of total mortality were obtained for each of 10 regions using a combination of design-based estimators and calibrated remote sensing using MODIS 1-yr change in normalized difference vegetation index products developed by the U.S. Forest Service. As compared with most of the publicized extreme die-off events, this study documents relatively low rates of mortality occurring over a very large area. However, statewide, regional tree mortality was massive, with an estimated 6.2% of the live trees perishing, nearly nine times greater than normal annual mortality. Dead tree diameters averaged larger than the live trees for most ecoregions, and this trend was most pronounced in the wetter climate zones, suggesting a potential re-ordering of species dominance and downward trend in tree size that was specific to climatic regions. The net effect on carbon storage was estimated to be a redistribution of 24-30 Tg C from the live tree to dead tree carbon pool. The dead tree survey documented drought mortality in more than 29 genera across all regions, and surprisingly, drought resistant and sensitive species fared similarly in some regions. Both angiosperms and gymnosperms were affected. These results highlight that drought-driven mortality alters forest structure differently across climatic regions and genera.

A simulation study to assess the sensitivity of a forest health monitoring network to outbreaks of defoliating insects.

The sensitivity of the United States Forest Health Monitoring network to outbreaks of defoliating insects was examined by means of a simulation study. A model constructed specifically for the study was used to generate a wide variety of defoliation patterns in forested landscapes. Forest configuration was that of Minnesota, USA, as expressed by the GAP land cover classification. Combinations of model parameters were based on a Latin Hypercube sample. The relationship between the average number of plots defoliated and outbreak characteristics was then examined via multiple regression. Both theoretical and model results pointed to a strong, linear relationship between the average number of plots defoliated and outbreak size. Model results provided additional insight, suggesting a significant relationship between the average number of plots defoliated and other outbreak characteristics after outbreak size was taken into account.