Near-term investments in forest management support long-term carbon sequestration capacity in forests of the United States.

The forest carbon sink of the United States offsets emissions in other sectors. Recently passed US laws include important climate legislation for wildfire reduction, forest restoration, and forest planting. In this study, we examine how wildfire reduction strategies and planting might alter the forest carbon sink. Our results suggest that wildfire reduction strategies reduce carbon sequestration potential in the near term but provide a longer term benefit. Planting initiatives increase carbon sequestration but at levels that do not offset lost sequestration from wildfire reduction strategies. We conclude that recent legislation may increase near-term carbon emissions due to fuel treatments and reduced wildfire frequency and intensity, and expand long-term US carbon sink strength.

Using a hybrid demand-allocation algorithm to enable distributional analysis of land use change patterns.

Future land use projections are needed to inform long-term planning and policy. However, most projections require downscaling into spatially explicit projection rasters for ecosystem service analyses. Empirical demand-allocation algorithms input coarse-level transition quotas and convert cells across the raster, based on a modeled probability surface. Such algorithms typically employ contagious and/or random allocation approaches. We present a hybrid seeding approach designed to generate a stochastic collection of spatial realizations for distributional analysis, by 1) randomly selecting a seed cell from a sample of n cells, then 2) converting patches of neighboring cells based on transition probability and distance to the seed. We generated a collection of realizations from 2001-2011 for the conterminous USA at 90m resolution based on varying the value of n, then computed forest area by fragmentation class and compared the results with observed 2011 forest area by fragmentation class. We found that realizations based on values of n ≤ 256 generally covered observed forest fragmentation at regional scales, for approximately 70% of assessed cases. We also demonstrate the potential of the seeding algorithm for distributional analysis by generating 20 trajectories of realizations from 2020-2070 from a single example scenario. Generating a library of such trajectories from across multiple scenarios will enable analysis of projected patterns and downstream ecosystem services, as well as their variation.

Assessment of hydrologic vulnerability to urbanization and climate change in a rapidly changing watershed in the Southeast U.S.

This study assessed the combined effects of increased urbanization and climate change on streamflow in the Yadkin-Pee Dee watershed (North Carolina, USA) and focused on the conversion from forest to urban land use, the primary land use transition occurring in the watershed. We used the Soil and Water Assessment Tool to simulate future (2050-2070) streamflow and baseflow for four combined climate and land use scenarios across the Yadkin-Pee Dee River watershed and three subwatersheds. The combined scenarios pair land use change and climate change scenarios together. Compared to the baseline, projected streamflow increased in three out of four combined scenarios and decreased in one combined scenario. Baseflow decreased in all combined scenarios, but decreases were largest in subwatersheds that lost the most forest. The effects of land use change and climate change were additive, amplifying the increases in runoff and decreases in baseflow. Streamflow was influenced more strongly by climate change than land use change. However, for baseflow the reverse was true; land use change tended to drive baseflow more than climate change. Land use change was also a stronger driver than climate in the most urban subwatershed. In the most extreme land use and climate projection the volume of the 1-day, 100 year flood nearly doubled at the watershed outlet. Our results underscore the importance of forests as hydrologic regulators buffering streamflow and baseflow from hydrologic extremes. Additionally, our results suggest that land managers and policy makers need to consider the implications of forest loss on streamflow and baseflow when planning for future urbanization and climate change adaptation options.

An empirical, hierarchical typology of tree species assemblages for assessing forest dynamics under global change scenarios.

The composition of tree species occurring in a forest is important and can be affected by global change drivers such as climate change. To inform assessment and projection of global change impacts at broad extents, we used hierarchical cluster analysis and over 120,000 recent forest inventory plots to empirically define forest tree assemblages across the U.S., and identified the indicator and dominant species associated with each. Cluster typologies in two levels of a hierarchy of forest assemblages, with 29 and 147 groups respectively, were supported by diagnostic criteria. Groups in these two levels of the hierarchy were labeled based on the top indicator species in each, and ranged widely in size. For example, in the 29-cluster typology, the sugar maple-red maple assemblage contained the largest number of plots (30,068), while the butternut-sweet birch and sourwood-scarlet oak assemblages were both smallest (6 plots each). We provide a case-study demonstration of the utility of the typology for informing forest climate change impact assessment. For five assemblages in the 29-cluster typology, we used existing projections of changes in importance value (IV) for the dominant species under one low and one high climate change scenario to assess impacts to the assemblages. Results ranged widely for each scenario by the end of the century, with each showing an average decrease in IV for dominant species in some assemblages, including the balsam fir-quaking aspen assemblage, and an average increase for others, like the green ash-American elm assemblage. Future work should assess adaptive capacity of these forest assemblages and investigate local population- and community-level dynamics in places where dominant species may be impacted. This typology will be ideal for monitoring, assessing, and projecting changes to forest communities within the emerging framework of macrosystems ecology, which emphasizes hierarchies and broad extents.

From sink to source: Regional variation in U.S. forest carbon futures.

The sequestration of atmospheric carbon (C) in forests has partially offset C emissions in the United States (US) and might reduce overall costs of achieving emission targets, especially while transportation and energy sectors are transitioning to lower-carbon technologies. Using detailed forest inventory data for the conterminous US, we estimate forests' current net sequestration of atmospheric C to be 173 Tg yr(-1), offsetting 9.7% of C emissions from transportation and energy sources. Accounting for multiple driving variables, we project a gradual decline in the forest C emission sink over the next 25 years (to 112 Tg yr(-1)) with regional differences. Sequestration in eastern regions declines gradually while sequestration in the Rocky Mountain region declines rapidly and could become a source of atmospheric C due to disturbances such as fire and insect epidemics. C sequestration in the Pacific Coast region stabilizes as forests harvested in previous decades regrow. Scenarios simulating climate-induced productivity enhancement and afforestation policies increase sequestration rates, but would not fully offset declines from aging and forest disturbances. Separating C transfers associated with land use changes from sequestration clarifies forests' role in reducing net emissions and demonstrates that retention of forest land is crucial for protecting or enhancing sink strength.

Complex forest dynamics indicate potential for slowing carbon accumulation in the southeastern United States.

Over the past century forest regrowth in Europe and North America expanded forest carbon (C) sinks and offset C emissions but future C accumulation is uncertain. Policy makers need insights into forest C dynamics as they anticipate emissions futures and goals. We used land use and forest inventory data to estimate how forest C dynamics have changed in the southeastern United States and attribute changes to land use, management, and disturbance causes. From 2007-2012, forests yielded a net sink of C because of net land use change (+6.48 Tg C yr(-1)) and net biomass accumulation (+75.4 Tg C yr(-1)). Forests disturbed by weather, insect/disease, and fire show dampened yet positive forest C changes (+1.56, +1.4, +5.48 Tg C yr(-1), respectively). Forest cutting caused net decreases in C (-76.7 Tg C yr(-1)) but was offset by forest growth (+143.77 Tg C yr(-1)). Forest growth rates depend on age or stage of development and projected C stock changes indicate a gradual slowing of carbon accumulation with anticipated forest aging (a reduction of 9.5% over the next five years). Additionally, small shifts in land use transitions consistent with economic futures resulted in a 40.6% decrease in C accumulation.

A primer for nonresponse in the US forest inventory and analysis program.

Nonresponse caused by denied access and hazardous conditions are a concern for the USDA Forest Service, Forest Inventory and Analysis (FIA) program, whose mission is to quantify status and trends in forest resources across the USA. Any appreciable amount of nonresponse can cause bias in FIA's estimates of population parameters. This paper will quantify the magnitude of nonresponse and describe the mechanisms that result in nonresponse, describe and qualitatively evaluate FIA's assumptions regarding nonresponse, provide a recommendation concerning plot replacement strategies, and identify appropriate strategies to pursue that minimize bias. The nonresponse rates ranged from 0% to 21% and differed by land owner group; with denied access to private land the leading cause of nonresponse. Current FIA estimators assume that nonresponse occurs at random. Although in most cases this assumption appears tenable, a qualitative assessment indicates a few situations where the assumption is not tenable. In the short-term, we recommend that FIA use stratification schemes that make the missing at random assumption tenable. We recommend the examination of alternative estimation techniques that use appropriate weighting and auxiliary information to mitigate the effects of nonresponse. We recommend the replacement of nonresponse sample locations not be used.

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.

Hot spots of perforated forest in the eastern United States.

National assessments of forest fragmentation satisfy international biodiversity conventions, but they do not identify specific places where ecological impacts are likely. In this article, we identify geographic concentrations (hot spots) of forest located near holes in otherwise intact forest canopies (perforated forest) in the eastern United States, and we describe the proximate causes in terms of the non-forest land-cover types contained in those hot spots. Perforated forest, defined as a 0.09-ha unit of forest that is located at the center of a 7.29-ha neighborhood containing 60-99% forest with relatively low connectivity, was mapped over the eastern United States by using land-cover maps with roads superimposed. Statistically significant (P < 0.001) hot spots of high perforation rate (perforated area per unit area of forest) were then located by using a spatial scan statistic. Hot spots were widely distributed and covered 20.4% of the total area of the 10 ecological provinces examined, but 50.1% of the total hot-spot area was concentrated in only two provinces. In the central part of the study area, more than 90% of the forest edge in hot spots was attributed to anthropogenic land-cover types, whereas in the northern and southern parts it was more often associated with semi-natural land cover such as herbaceous wetlands.

A preliminary assessment of the Montreal process indicators of air pollution for the United States.

Air pollutants pose a risk to forest health and vitality in the United States. Here we present the major findings from a national scale air pollution assessment that is part of the United States' 2003 Report on Sustainable Forests. We examine trends and the percent forest subjected to specific levels of ozone and wet deposition of sulfate, nitrate, and ammonium. Results are reported by Resource Planning Act (RPA) reporting region and integrated by forest type using multivariate clustering. Estimates of sulfate deposition for forested areas had decreasing trends (1994-2000) across RPA regions that were statistically significant for North and South RPA regions. Nitrate deposition rates were relatively constant for the 1994 to 2000 period, but the South RPA region had a statistically decreasing trend. The North and South RPA regions experienced the highest ammonium deposition rates and showed slightly decreasing trends. Ozone concentrations were highest in portions of the Pacific Coast RPA region and relatively high across much of the South RPA region. Both the South and Rocky Mountain RPA regions had an increasing trend in ozone exposure. Ozone-induced foliar injury to sensitive species was recorded in all regions except for the Rocky Mountain region. The multivariate analysis showed that the oak-hickory and loblolly-shortleaf pine forest types were generally exposed to more air pollution than other forest types, and the redwood, western white pine, and larch forest types were generally exposed to less. These findings offer a new approach to national air pollution assessments and are intended to help focus research and planning initiatives related to air pollution and forest health.

A preliminary assessment of Montréal process indicators of forest fragmentation for the United States.

As part of the U.S. 2003 National Report on Sustainable Forests, four metrics of forest fragmentation--patch size, edge amount, inter-patch distance, and patch contrast--were measured within 137744 non-overlapping 5625 ha analysis units on land-cover maps derived from satellite imagery for the 48 conterminous States. The perimeter of a typical forest patch is about 100 m from the perimeter of its nearest neighbor, except when there is not much forest, in which case that distance is 200 to 300 m. A typical analysis unit has from 10 to 40% as much forest edge as it could possibly have, given the amount of forest present. Most analysis units contain a large number of patches that are less than one hectare in size, and about 10% contain one or more 2000 to 5000 ha patches. Forest often defines the background landscape, and patch contrast is generally either very high or very low in eastern regions and intermediate in western regions. Many research needs were identified by this experimental analysis of available data and metrics.

Geographic analysis of forest health indicators using spatial scan statistics.

Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.

Regional assessment of ozone sensitive tree species using bioindicator plants.

Tropospheric ozone occurs at phytotoxic levels in the northeastern and mid-Atlantic regions of the United States. Quantifying possible regional-scale impacts of ambient ozone on forest tree species is difficult and is confounded by other factors, such as moisture and light, which influence the uptake of ozone by plants. Biomonitoring provides an approach to document direct foliar injury irrespective of direct measure of ozone uptake. We used bioindicator and field plot data from the USDA Forest Service to identify tree species likely to exhibit regional-scale ozone impacts. Approximately 24% of sampled sweetgum (Liquidambar styraciflua), 15% of sampled loblolly pine (Pinus taeda), and 12% of sampled black cherry (Prunus serotina) trees were in the highest risk category. Sweetgum and loblolly pine trees were at risk on the coastal plain of Maryland, Virginia and Delaware. Black cherry trees were at risk on the Allegheny Plateau (Pennsylvania), in the Allegheny Mountains (Pennsylvania, West Virginia, and Maryland) as well as coastal plain areas of Maryland and Virginia. Our findings indicate a need for more in-depth study of actual impacts on growth and reproduction of these three species.