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.

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers.

Carbon conundrums: Do United States' current carbon market baselines represent an undesirable ecological threshold?

Relative frequency distribution of observed annual mortality expressed in aboveground (AG) carbon (C) (Mg CO₂ e ha^-1 year^-1 ) summarized across supersections by forest type [Hardwood (HW) vs. Softwood (SW)] and site class (Low vs. High) based on approximately 130,000 remeasured USDA Forest Service Forest Inventory and Analysis plots across the US. Top panel summarizes conditions in plots that do and do not meet the California Air Resources Board standards based on total basal area, whereas bottom panel summarizes conditions in plots falling inside and outside of optimum relative density levels. The latter represents a biophysically-informed approach accounting for changes in tree (and carbon) packing over forest development.

Predicting downed woody material carbon stocks in forests of the conterminous United States

Downed woody material (DWM) is a unique part of the forest carbon cycle serving as a pool between living biomass and subsequent atmospheric emission or transference to other forest pools. Thus, DWM is an individually defined pool in national greenhouse gas inventories. The diversity of DWM carbon drivers (e.g., decay, tree mortality, or wildfire) and associated high spatial variability make this a difficult-to-predict component of forest ecosystems. Using the now fully established nationwide inventory of DWM across the United States (US), we developed models, which substantially improved predictions of stand-level DWM carbon density relative to the current national-reporting model ('previous' model, here). The previous model was developed from published DWM carbon densities prior to the NFI DWM inventory. Those predictions were tested using NFI DWM carbon densities resulting in a poor fit to the data (coefficient of determination, or R² = 0.03). We present new random forest (RF) and stochastic gradient boosted (SGB) regression models to prediction DWM carbon density on all NFI plots and spatially on all forest land pixels. We evaluated various biotic and abiotic regression predictors, and the most important were standing dead trees, long-term annual precipitation, and long-term maximum summer temperature. A RF model scored best for expanding predictions to NFI plots (R² = 0.31), while an SGB model was identified for DWM carbon predictions based on purely spatial data (i.e., NFI-plot-independent, with R² = 0.23). The new RF model predicts conterminous US DWM carbon stocks to be 15% lower than the previous model and 2% higher than NFI data expanded according to inventory design-based inference. The new NFI data-driven models not only improve the predictions of DWM carbon density on all plots, they also provide flexibility in extending these predictions beyond the NFI to make spatially explicit and spatially continuous estimates of DWM carbon on all forest land in the US.

Niche Shifts From Trees to Fecundity to Recruitment That Determine Species Response to Climate Change

Anticipating the next generation of forests requires understanding of recruitment responses to habitat change. Tree distribution and abundance depend not only on climate, but also on habitat variables, such as soils and drainage, and on competition beneath a shaded canopy. Recent analyses show that North American tree species are migrating in response to climate change, which is exposing each population to novel climate-habitat interactions (CHI). Because CHI have not been estimated for either adult trees or regeneration (recruits per year per adult basal area), we cannot evaluate migration potential into the future. Using the Masting Inference and Forecasting (MASTIF) network of tree fecundity and new continent-wide observations of tree recruitment, we quantify impacts for redistribution across life stages from adults to fecundity to recruitment. We jointly modeled response of adult abundance and recruitment rate to climate/habitat conditions, combined with fecundity sensitivity, to evaluate if shifting CHI explain community reorganization. To compare climate effects with tree fecundity, which is estimated from trees and thus is "conditional" on tree presence, we demonstrate how to quantify this conditional status for regeneration. We found that fecundity was regulated by temperature to a greater degree than other stages, yet exhibited limited responses to moisture deficit. Recruitment rate expressed strong sensitivities to CHI, more like adults than fecundity, but still with substantial differences. Communities reorganized from adults to fecundity, but there was a re-coalescence of groups as seedling recruitment partially reverted to community structure similar to that of adults. Results provide the first estimates of continent-wide community sensitivity and their implications for reorganization across three life-history stages under climate change.

Similar tree species richness-productivity response but differing effects on carbon stocks and timber production in eastern US and continental Spain

Unimodal response of tree species richness to increases in aboveground productivity is evident in grasslands but to a lesser extent in forests, where confounding factors (e.g., abiotic factors and management regimes) may alter the response and compromise the delivery of ecosystem services. We hypothesize that unimodal response of biomass accumulation through increased species richness leads to greater tree above ground carbon (AGC) stocks and thus climate regulation but not necessarily higher timber volume production for human consumption across portions of North American and European forests. We first evaluated the biodiversity-productivity pattern and assessed if the addition of potential confounding variables altered the response. Afterwards, we integrated direct and indirect effects of species richness and confounding factors in the modelling of aboveground carbon stock and timber volume. We confirm an increase in carbon stocks concomitant with an increase in tree species richness up to an optimum biomass value in both regions. Tree species richness had a marginal effect on both aboveground carbon stocks and timber volume with a trade-off in the eastern US. Biomass accumulation is lower in tree plantations than in natural forests, although volume increased with species richness. Naturally-regenerated forests needed as much as double the number of tree species than plantations to reach the same carbon stocks. Distinct ecosystem services (AGC and timber volume) showed unique pathways of achieving their maximum provisioning. As increasing forest resilience to global change requires a fundamental understanding of how tree species combine with changing climatic conditions to drive the provisioning of various ecosystem services, further examination of this study's findings across additional biogeographical regions may lead the way to unraveling such dynamics and empowering adaptive management.

Release of coarse woody detritus-related carbon: a synthesis across forest biomes

BACKGROUND

Recent increases in forest tree mortality should increase the abundance coarse woody detritus (CWD) and ultimately lead to increased atmospheric carbon dioxide. However, the time course of carbon release from CWD is not well understood. We compiled CWD decomposition rate-constants (i.e., k) to examine how tree species, piece diameter, position (i.e., standing versus downed), canopy openness, and macroclimate influenced k. To illustrate their implications we modeled the effect of species and position on estimates of decomposition-related carbon flux. We examined a subset of currently used models to determine if their structure accounted for these factors.

RESULTS

Globally k of downed CWD varied at least 244-fold with interspecies variation at individual sites up to 76-fold. While k generally decreased with increasing piece diameter, under open canopies the opposite occurred. Standing CWD sometimes exhibited little decomposition, but sometimes had k values up to 3 times faster than downed CWD. There was a clear response of k to mean annual temperature of ≈ 2.6 times per 10 ℃; however, there was considerable variation for a given mean annual temperature related to species, diameter, and position. A key feature of carbon release from CWD after disturbance was the "evolution" of the ecosystem-level k value as positions and species mixtures of the remaining CWD changed. Variations in decomposition caused by disturbance (e.g., changes in species, positions, sizes, and microclimate) had the potential to cause net carbon fluxes to the atmosphere to be highly nonlinear. While several models currently being used for carbon accounting and assessing land-use/climate change would potentially capture some of these post disturbance changes in fluxes and carbon balances, many would not.

CONCLUSIONS

While much has been learned in the last 5 decades about CWD decomposition, to fully understand the time course of carbon release from increased mortality and other aspects of global change a new phase of global CWD research that is more systematic, experimental, and replicated needs to be initiated. If our findings are to be fully applied in modeling, an approach acknowledging how the rate of carbon release evolves over time should be implemented.

Estimating uncertainty in the volume and carbon storage of downed coarse woody debris

Downed coarse woody debris, also known as coarse woody detritus or downed dead wood, is challenging to estimate for many reasons, including irregular shapes, multiple stages of decay, and the difficulty of identifying species. In addition, some properties are commonly not measured, such as wood density and carbon concentration. As a result, there have been few previous evaluations of uncertainty in estimates of downed coarse woody debris, which are necessary for analysis and interpretation of the data. To address this shortcoming, we quantified uncertainties in estimates of downed coarse woody debris volume and carbon storage using data collected from permanent forest inventory plots in the northeastern United States by the Forest Inventory and Analysis program of the USDA Forest Service. Quality assurance data collected from blind remeasurement audits were used to quantify error in diameter measurements, hollowness of logs, species identification, and decay class determination. Uncertainty estimates for density, collapse ratio, and carbon concentration were taken from the literature. Estimates of individual sources of uncertainty were combined using Monte Carlo methods. Volume estimates were more reliable than carbon storage, with an average 95% confidence interval of 15.9 m³ /ha across the 79 plots evaluated, which was less than the mean of 31.2 m³ /ha. Estimates of carbon storage (and mass) were more uncertain, due to poorly constrained estimates of the density of wood. For carbon storage, the average 95% confidence interval was 11.1 Mg C/ha, which was larger than the mean of 4.6 Mg C/ha. Accounting for the collapse of dead wood as it decomposes would improve estimates of both volume and carbon storage. On the other hand, our analyses suggest that consideration of the hollowness of downed coarse woody debris pieces could be eliminated in this region, with little effect. This study demonstrates how uncertainty analysis can be used to quantify confidence in estimates and to help identify where best to allocate resources to improve monitoring designs.

When a tree falls: Controls on wood decay predict standing dead tree fall and new risks in changing forests

When standing dead trees (snags) fall, they have major impacts on forest ecosystems. Snag fall can redistribute wildlife habitat and impact public safety, while governing important carbon (C) cycle consequences of tree mortality because ground contact accelerates C emissions during deadwood decay. Managing the consequences of altered snag dynamics in changing forests requires predicting when snags fall as wood decay erodes mechanical resistance to breaking forces. Previous studies have pointed to common predictors, such as stem size, degree of decay and species identity, but few have assessed the relative strength of underlying mechanisms driving snag fall across biomes. Here, we analyze nearly 100,000 repeated snag observations from boreal to subtropical forests across the eastern United States to show that wood decay controls snag fall in ways that could generate previously unrecognized forest-climate feedback. Warmer locations where wood decays quickly had much faster rates of snag fall. The effect of temperature on snag fall was so strong that in a simple forest C model, anticipated warming by mid-century reduced snag C by 22%. Furthermore, species-level differences in wood decay resistance (durability) accurately predicted the timing of snag fall. Differences in half-life for standing dead trees were similar to expected differences in the service lifetimes of wooden structures built from their timber. Strong effects of temperature and wood durability imply future forests where dying trees fall and decay faster than at present, reducing terrestrial C storage and snag-dependent wildlife habitat. These results can improve the representation of forest C cycling and assist forest managers by helping predict when a dead tree may fall.

Toward inventory-based estimates of soil organic carbon in forests of the United States

Soil organic carbon (SOC) is the largest terrestrial carbon (C) sink on Earth; this pool plays a critical role in ecosystem processes and climate change. Given the cost and time required to measure SOC, and particularly changes in SOC, many signatory nations to the United Nations Framework Convention on Climate Change report estimates of SOC stocks and stock changes using default values from the Intergovernmental Panel on Climate Change or country-specific models. In the United States, SOC in forests is monitored by the national forest inventory (NFI) conducted by the Forest Inventory and Analysis (FIA) program within the U.S. Department of Agriculture, Forest Service. The FIA program has been consistently measuring soil attributes as part of the NFI since 2001 and has amassed an extensive inventory of SOC in forest land in the conterminous United States and southeast and southcentral coastal Alaska. That said, the FIA program has been using country-specific predictions of SOC based, in part, upon a model using SOC estimates from the State Soil Geographic (STATSGO) database compiled by the Natural Resources Conservation Service. Estimates obtained from the STATSGO database are averages over large map units and are not expected to provide accurate estimates for specific locations, e.g., NFI plots. To improve the accuracy of SOC estimates in U.S. forests, NFI SOC observations were used for the first time to predict SOC density to a depth of 100 cm for all forested NFI plots. Incorporating soil-forming factors along with observations of SOC into a new estimation framework resulted in a 75% (48 ± 0.78 Mg/ha) increase in SOC densities nationally. This substantially increases the contribution of the SOC pool, from approximately 44% (17 Pg) of the total forest ecosystem C stocks to 56% (28 Pg), in the forest C budget of the United States.

Attribution of net carbon change by disturbance type across forest lands of the conterminous United States

BACKGROUND

Locating terrestrial sources and sinks of carbon (C) will be critical to developing strategies that contribute to the climate change mitigation goals of the Paris Agreement. Here we present spatially resolved estimates of net C change across United States (US) forest lands between 2006 and 2010 and attribute them to natural and anthropogenic processes.

RESULTS

Forests in the conterminous US sequestered -460 ± 48 Tg C year^-1, while C losses from disturbance averaged 191 ± 10 Tg C year^-1. Combining estimates of net C losses and gains results in net carbon change of -269 ± 49 Tg C year^-1. New forests gained -8 ± 1 Tg C year^-1, while deforestation resulted in losses of 6 ± 1 Tg C year^-1. Forest land remaining forest land lost 185 ± 10 Tg C year^-1 to various disturbances; these losses were compensated by net carbon gains of -452 ± 48 Tg C year^-1. C loss in the southern US was highest (105 ± 6 Tg C year^-1) with the highest fractional contributions from harvest (92%) and wind (5%). C loss in the western US (44 ± 3 Tg C year^-1) was due predominantly to harvest (66%), fire (15%), and insect damage (13%). The northern US had the lowest C loss (41 ± 2 Tg C year^-1) with the most significant proportional contributions from harvest (86%), insect damage (9%), and conversion (3%). Taken together, these disturbances reduced the estimated potential C sink of US forests by 42%.

CONCLUSION

The framework presented here allows for the integration of ground and space observations to more fully inform US forest C policy and monitoring efforts.

The impacts of increasing drought on forest dynamics, structure, and biodiversity in the United States

We synthesize insights from current understanding of drought impacts at stand-to-biogeographic scales, including management options, and we identify challenges to be addressed with new research. Large stand-level shifts underway in western forests already are showing the importance of interactions involving drought, insects, and fire. Diebacks, changes in composition and structure, and shifting range limits are widely observed. In the eastern US, the effects of increasing drought are becoming better understood at the level of individual trees, but this knowledge cannot yet be confidently translated to predictions of changing structure and diversity of forest stands. While eastern forests have not experienced the types of changes seen in western forests in recent decades, they too are vulnerable to drought and could experience significant changes with increased severity, frequency, or duration in drought. Throughout the continental United States, the combination of projected large climate-induced shifts in suitable habitat from modeling studies and limited potential for the rapid migration of tree populations suggests that changing tree and forest biogeography could substantially lag habitat shifts already underway. Forest management practices can partially ameliorate drought impacts through reductions in stand density, selection of drought-tolerant species and genotypes, artificial regeneration, and the development of multistructured stands. However, silvicultural treatments also could exacerbate drought impacts unless implemented with careful attention to site and stand characteristics. Gaps in our understanding should motivate new research on the effects of interactions involving climate and other species at the stand scale and how interactions and multiple responses are represented in models. This assessment indicates that, without a stronger empirical basis for drought impacts at the stand scale, more complex models may provide limited guidance.

Estimating litter carbon stocks on forest land in the United States

Forest ecosystems are the largest terrestrial carbon sink on earth, with more than half of their net primary production moving to the soil via the decomposition of litter biomass. Therefore, changes in the litter carbon (C) pool have important implications for global carbon budgets and carbon emissions reduction targets and negotiations. Litter accounts for an estimated 5% of all forest ecosystem carbon stocks worldwide. Given the cost and time required to measure litter attributes, many of the signatory nations to the United Nations Framework Convention on Climate Change report estimates of litter carbon stocks and stock changes using default values from the Intergovernmental Panel on Climate Change or country-specific models. In the United States, the country-specific model used to predict litter C stocks is sensitive to attributes on each plot in the national forest inventory, but these predictions are not associated with the litter samples collected over the last decade in the national forest inventory. Here we present, for the first time, estimates of litter carbon obtained using more than 5000 field measurements from the national forest inventory of the United States. The field-based estimates mark a 44% reduction (2081±77Tg) in litter carbon stocks nationally when compared to country-specific model predictions reported in previous United Framework Convention on Climate Change submissions. Our work suggests that Intergovernmental Panel on Climate Change defaults and country-specific models used to estimate litter carbon in temperate forest ecosystems may grossly overestimate the contribution of this pool in national carbon budgets.

Prevalence and strength of density-dependent tree recruitment

Density dependence could maintain diversity in forests, but studies continue to disagree on its role. Part of the disagreement results from the fact that different studies have evaluated different responses (survival, recruitment, or growth) of different stages (seeds, seedlings, or adults) to different inputs (density of seedlings, density or distance to adults). Most studies are conducted on a single site and thus are difficult to generalize. Using USDA Forest Service's Forest Inventory and Analysis data, we analyzed over a million seedling-to-sapling recruitment observations of 50 species from the eastern United States, controlling for the effects of climate. We focused on the per-seedling recruitment rate, because it is most likely to promote diversity and to be identified in observational or experimental data. To understand the prevalence of density dependence, we quantified the number of species with significant positive or negative effects. To understand the strength of density dependence, we determined the magnitude of effects among con- and heterospecifics, and how it changes with overall species abundance. We found that density dependence is pervasive among the 50 species, as the majority of them have significant effects and mostly negative. Density-dependence effects are stronger from conspecific than heterospecfic adult neighbors, consistent with the predictions of the Janzen-Connell hypothesis. Contrary to recent reports, density-dependence effects are more negative for common than rare species, suggesting disproportionately stronger population regulation in common species. We conclude that density dependence is pervasive, and it is strongest from conspecific neighbors of common species. Our analysis provides direct evidence that density dependence reaulates opulation dynamics of tree species in eastern U.S. forests.

Monitoring Network Confirms Land Use Change is a Substantial Component of the Forest Carbon Sink in the eastern United States

Quantifying forest carbon (C) stocks and stock change within a matrix of land use (LU) and LU change is a central component of large-scale forest C monitoring and reporting practices prescribed by the Intergovernmental Panel on Climate Change (IPCC). Using a region-wide, repeated forest inventory, forest C stocks and stock change by pool were examined by LU categories. In eastern US forests, LU change is a substantial component of C sink strength (~37% of forest sink strength) only secondary to that of C accumulation in forests remaining forest where their comingling with other LUs does not substantially reduce sink strength. The strongest sinks of forest C were study areas not completely dominated by forests, even when there was some loss of forest to agriculture/settlement/other LUs. Long-term LU planning exercises and policy development that seeks to maintain and/or enhance regional C sinks should explicitly recognize the importance of maximizing non-forest to forest LU changes and not overlook management and conservation of forests located in landscapes not currently dominated by forests.

Comparisons of allometric and climate-derived estimates of tree coarse root carbon stocks in forests of the United States

BACKGROUND

Refined estimation of carbon (C) stocks within forest ecosystems is a critical component of efforts to reduce greenhouse gas emissions and mitigate the effects of projected climate change through forest C management. Specifically, belowground C stocks are currently estimated in the United States' national greenhouse gas inventory (US NGHGI) using nationally consistent species- and diameter-specific equations applied to individual trees. Recent scientific evidence has pointed to the importance of climate as a driver of belowground C stocks. This study estimates belowground C using current methods applied in the US NGHGI and describes a new approach for merging both allometric models with climate-derived predictions of belowground C stocks.

RESULTS

Climate-adjusted predictions were variable depending on the region and forest type of interest, but represented an increase of 368.87 Tg of belowground C across the US, or a 6.4 % increase when compared to currently-implemented NGHGI estimates. Random forests regressions indicated that aboveground biomass, stand age, and stand origin (i.e., planted versus artificial regeneration) were useful predictors of belowground C stocks. Decreases in belowground C stocks were modeled after projecting mean annual temperatures at various locations throughout the US up to year 2090.

CONCLUSIONS

By combining allometric equations with trends in temperature, we conclude that climate variables can be used to adjust the US NGHGI estimates of belowground C stocks. Such strategies can be used to determine the effects of future global change scenarios within a C accounting framework.

Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

We propose a novel multivariate method to analyse biodiversity data based on the Latent Dirichlet Allocation (LDA) model. LDA, a probabilistic model, reduces assemblages to sets of distinct component communities. It produces easily interpretable results, can represent abrupt and gradual changes in composition, accommodates missing data and allows for coherent estimates of uncertainty. We illustrate our method using tree data for the eastern United States and from a tropical successional chronosequence. The model is able to detect pervasive declines in the oak community in Minnesota and Indiana, potentially due to fire suppression, increased growing season precipitation and herbivory. The chronosequence analysis is able to delineate clear successional trends in species composition, while also revealing that site-specific factors significantly impact these successional trajectories. The proposed method provides a means to decompose and track the dynamics of species assemblages along temporal and spatial gradients, including effects of global change and forest disturbances.

More than the sum of the parts: forest climate response from joint species distribution models

The perceived threat of climate change is often evaluated from species distribution models that are fitted to many species independently and then added together. This approach ignores the fact that species are jointly distributed and limit one another. Species respond to the same underlying climatic variables, and the abundance of any one species can be constrained by competition; a large increase in one is inevitably linked to declines of others. Omitting this basic relationship explains why responses modeled independently do not agree with the species richness or basal areas of actual forests. We introduce a joint species distribution modeling approach (JSDM), which is unique in three ways, and apply it to forests of eastern North America. First, it accommodates the joint distribution of species. Second, this joint distribution includes both abundance and presence-absence data. We solve the common issue of large numbers of zeros in abundance data by accommodating zeros in both stem counts and basal area data, i.e., a new approach to zero inflation. Finally, inverse prediction can be applied to the joint distribution of predictions to integrate the role of climate risks across all species and identify geographic areas where communities will change most (in terms of changes in abundance) with climate change. Application to forests in the eastern United States shows that climate can have greatest impact in the Northeast, due to temperature, and in the Upper Midwest, due to temperature and precipitation. Thus, these are the regions experiencing the fastest warming and are also identified as most responsive at this scale.

Dual impacts of climate change: forest migration and turnover through life history

Tree species are predicted to track future climate by shifting their geographic distributions, but climate-mediated migrations are not apparent in a recent continental-scale analysis. To better understand the mechanisms of a possible migration lag, we analyzed relative recruitment patterns by comparing juvenile and adult tree abundances in climate space. One would expect relative recruitment to be higher in cold and dry climates as a result of tree migration with juveniles located further poleward than adults. Alternatively, relative recruitment could be higher in warm and wet climates as a result of higher tree population turnover with increased temperature and precipitation. Using the USDA Forest Service's Forest Inventory and Analysis data at regional scales, we jointly modeled juvenile and adult abundance distributions for 65 tree species in climate space of the eastern United States. We directly compared the optimal climate conditions for juveniles and adults, identified the climates where each species has high relative recruitment, and synthesized relative recruitment patterns across species. Results suggest that for 77% and 83% of the tree species, juveniles have higher optimal temperature and optimal precipitation, respectively, than adults. Across species, the relative recruitment pattern is dominated by relatively more abundant juveniles than adults in warm and wet climates. These different abundance-climate responses through life history are consistent with faster population turnover and inconsistent with the geographic trend of large-scale tree migration. Taken together, this juvenile-adult analysis suggests that tree species might respond to climate change by having faster turnover as dynamics accelerate with longer growing seasons and higher temperatures, before there is evidence of poleward migration at biogeographic scales.

A framework for assessing global change risks to forest carbon stocks in the United States

Among terrestrial environments, forests are not only the largest long-term sink of atmospheric carbon (C), but are also susceptible to global change themselves, with potential consequences including alterations of C cycles and potential C emission. To inform global change risk assessment of forest C across large spatial/temporal scales, this study constructed and evaluated a basic risk framework which combined the magnitude of C stocks and their associated probability of stock change in the context of global change across the US. For the purposes of this analysis, forest C was divided into five pools, two live (aboveground and belowground biomass) and three dead (dead wood, soil organic matter, and forest floor) with a risk framework parameterized using the US's national greenhouse gas inventory and associated forest inventory data across current and projected future Köppen-Geiger climate zones (A1F1 scenario). Results suggest that an initial forest C risk matrix may be constructed to focus attention on short- and long-term risks to forest C stocks (as opposed to implementation in decision making) using inventory-based estimates of total stocks and associated estimates of variability (i.e., coefficient of variation) among climate zones. The empirical parameterization of such a risk matrix highlighted numerous knowledge gaps: 1) robust measures of the likelihood of forest C stock change under climate change scenarios, 2) projections of forest C stocks given unforeseen socioeconomic conditions (i.e., land-use change), and 3) appropriate social responses to global change events for which there is no contemporary climate/disturbance analog (e.g., severe droughts in the Lake States). Coupling these current technical/social limits of developing a risk matrix to the biological processes of forest ecosystems (i.e., disturbance events and interaction among diverse forest C pools, potential positive feedbacks, and forest resiliency/recovery) suggests an operational forest C risk matrix remains elusive.

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.'s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon) and spatial scales (e.g., sub-county to biome). Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood) is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations). In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area), with weaker agreement for detrital pools (e.g., standing dead trees). Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC) and regional scales (e.g., Reducing Emissions from Deforestation and Forest Degradation projects) while allowing timely incorporation of empirical data (e.g., annual forest inventory).

Trends over time in tree and seedling phylogenetic diversity indicate regional differences in forest biodiversity change

Changing climate conditions may impact the short-term ability of forest tree species to regenerate in many locations. In the longer term, tree species may be unable to persist in some locations while they become established in new places. Over both time frames, forest tree biodiversity may change in unexpected ways. Using repeated inventory measurements five years apart from more than 7000 forested plots in the eastern United States, we tested three hypotheses: phylogenetic diversity is substantially different from species richness as a measure of biodiversity; forest communities have undergone recent changes in phylogenetic diversity that differ by size class, region, and seed dispersal strategy; and these patterns are consistent with expected early effects of climate change. Specifically, the magnitude of diversity change across broad regions should be greater among seedlings than in trees, should be associated with latitude and elevation, and should be greater among species with high dispersal capacity. Our analyses demonstrated that phylogenetic diversity and species richness are decoupled at small and medium scales and are imperfectly associated at large scales. This suggests that it is appropriate to apply indicators of biodiversity change based on phylogenetic diversity, which account for evolutionary relationships among species and may better represent community functional diversity. Our results also detected broadscale patterns of forest biodiversity change that are consistent with expected early effects of climate change. First, the statistically significant increase over time in seedling diversity in the South suggests that conditions there have become more favorable for the reproduction and dispersal of a wider variety of species, whereas the significant decrease in northern seedling diversity indicates that northern conditions have become less favorable. Second, we found weak correlations between seedling diversity change and latitude in both zones, with stronger relationships apparent in some ecoregions. Finally, we detected broadscale seedling diversity increases among species with longer-distance dispersal capacity, even in the northern zone, where overall seedling diversity declined. The statistical power and geographic extent of such analyses will increase as data become available over larger areas and as plot measurements are repeated at regular intervals over a longer period of time.

Accounting for density reduction and structural loss in standing dead trees: Implications for forest biomass and carbon stock estimates in the United States

BACKGROUND

Standing dead trees are one component of forest ecosystem dead wood carbon (C) pools, whose national stock is estimated by the U.S. as required by the United Nations Framework Convention on Climate Change. Historically, standing dead tree C has been estimated as a function of live tree growing stock volume in the U.S.'s National Greenhouse Gas Inventory. Initiated in 1998, the USDA Forest Service's Forest Inventory and Analysis program (responsible for compiling the Nation's forest C estimates) began consistent nationwide sampling of standing dead trees, which may now supplant previous purely model-based approaches to standing dead biomass and C stock estimation. A substantial hurdle to estimating standing dead tree biomass and C attributes is that traditional estimation procedures are based on merchantability paradigms that may not reflect density reductions or structural loss due to decomposition common in standing dead trees. The goal of this study was to incorporate standing dead tree adjustments into the current estimation procedures and assess how biomass and C stocks change at multiple spatial scales.

RESULTS

Accounting for decay and structural loss in standing dead trees significantly decreased tree- and plot-level C stock estimates (and subsequent C stocks) by decay class and tree component. At a regional scale, incorporating adjustment factors decreased standing dead quaking aspen biomass estimates by almost 50 percent in the Lake States and Douglas-fir estimates by more than 36 percent in the Pacific Northwest.

CONCLUSIONS

Substantial overestimates of standing dead tree biomass and C stocks occur when one does not account for density reductions or structural loss. Forest inventory estimation procedures that are descended from merchantability standards may need to be revised toward a more holistic approach to determining standing dead tree biomass and C attributes (i.e., attributes of tree biomass outside of sawlog portions). Incorporating density reductions and structural loss adjustments reduces uncertainty associated with standing dead tree biomass and C while improving consistency with field methods and documentation.

High-dimensional coexistence of temperate tree species: functional traits, demographic rates, life-history stages, and their physical context

Theoretical models indicate that trade-offs between growth and survival strategies of tree species can lead to coexistence across life history stages (ontogeny) and physical conditions experienced by individuals. There exist predicted physiological mechanisms regulating these trade-offs, such as an investment in leaf characters that may increase survival in stressful environments at the expense of investment in bole or root growth. Confirming these mechanisms, however, requires that potential environmental, ontogenetic, and trait influences are analyzed together. Here, we infer growth and mortality of tree species given size, site, and light characteristics from forest inventory data from Wisconsin to test hypotheses about growth-survival trade-offs given species functional trait values under different ontogenetic and environmental states. A series of regression analyses including traits and rates their interactions with environmental and ontogenetic stages supported the relationships between traits and vital rates expected from the expectations from tree physiology. A combined model including interactions between all variables indicated that relationships between demographic rates and functional traits supports growth-survival trade-offs and their differences across species in high-dimensional niche space. The combined model explained 65% of the variation in tree growth and supports a concept of community coexistence similar to Hutchinson's n-dimensional hypervolume and not a low-dimensional niche model or neutral model.

Estimating dead wood during national forest inventories: a review of inventory methodologies and suggestions for harmonization

Efforts to assess forest ecosystem carbon stocks, biodiversity, and fire hazards have spurred the need for comprehensive assessments of forest ecosystem dead wood (DW) components around the world. Currently, information regarding the prevalence, status, and methods of DW inventories occurring in the world's forested landscapes is scattered. The goal of this study is to describe the status, DW components measured, sample methods employed, and DW component thresholds used by national forest inventories that currently inventory DW around the world. Study results indicate that most countries do not inventory forest DW. Globally, we estimate that about 13% of countries inventory DW using a diversity of sample methods and DW component definitions. A common feature among DW inventories was that most countries had only just begun DW inventories and employ very low sample intensities. There are major hurdles to harmonizing national forest inventories of DW: differences in population definitions, lack of clarity on sample protocols/estimation procedures, and sparse availability of inventory data/reports. Increasing database/estimation flexibility, developing common dimensional thresholds of DW components, publishing inventory procedures/protocols, releasing inventory data/reports to international peer review, and increasing communication (e.g., workshops) among countries inventorying DW are suggestions forwarded by this study to increase DW inventory harmonization.

Assessment of forest fuel loadings in Puerto Rico and the US Virgin Islands

Quantification of the downed woody materials that comprise forest fuels has gained importance in Caribbean forest ecosystems due to the increasing incidence and severity of wildfires on island ecosystems. Because large-scale assessments of forest fuels have rarely been conducted for these ecosystems, forest fuels were assessed at 121 US Department of Agriculture forest service inventory plots on Puerto Rico, Vieques, and the US Virgin Islands. Results indicated that fuel loadings averaged 24.05 Mg ha(-1) in 2004-2006. Forest litter decreased from wetter to drier forest life zones. These island forests showed a paucity of coarse woody fuels (CWD) (2.91 Mg ha(-1)) and relatively greater quantities of smaller-sized fine woody fuels (FWD) (10.18 Mg ha(-1) for FWD and 10.82 Mg ha(-1) for duff/litter) when compared to continental tropical forests. Between 2001 and 2006, CWD fuel loads decreased, while fine fuels and litter increased, such that total fuel loads remained constant on a subset of plots on Puerto Rico. This trend indicates that continued decomposition of CWD deposited by the last severe hurricane is balanced by increasing inputs of FWD from recovering and maturing secondary forests. Forest disturbance cycles and successional development must be taken into account by agencies charged with fire protection and risk assessment.

Climatic regions as an indicator of forest coarse and fine woody debris carbon stocks in the United States

BACKGROUND

Coarse and fine woody debris are substantial forest ecosystem carbon stocks; however, there is a lack of understanding how these detrital carbon stocks vary across forested landscapes. Because forest woody detritus production and decay rates may partially depend on climatic conditions, the accumulation of coarse and fine woody debris carbon stocks in forests may be correlated with climate. This study used a nationwide inventory of coarse and fine woody debris in the United States to examine how these carbon stocks vary by climatic regions and variables.

RESULTS

Mean coarse and fine woody debris forest carbon stocks vary by Köppen's climatic regions across the United States. The highest carbon stocks were found in regions with cool summers while the lowest carbon stocks were found in arid desert/steppes or temperate humid regions. Coarse and fine woody debris carbon stocks were found to be positively correlated with available moisture and negatively correlated with maximum temperature.

CONCLUSION

It was concluded with only medium confidence that coarse and fine woody debris carbon stocks may be at risk of becoming net emitter of carbon under a global climate warming scenario as increases in coarse or fine woody debris production (sinks) may be more than offset by increases in forest woody detritus decay rates (emission). Given the preliminary results of this study and the rather tenuous status of coarse and fine woody debris carbon stocks as either a source or sink of CO2, further research is suggested in the areas of forest detritus decay and production.

Survival analysis for a large-scale forest health issue: Missouri oak decline

Survival analysis methodologies provide novel approaches for forest mortality analysis that may aid in detecting, monitoring, and mitigating of large-scale forest health issues. This study examined survivor analysis for evaluating a regional forest health issue - Missouri oak decline. With a statewide Missouri forest inventory, log-rank tests of the effects of covariates on the survivor function and equality of the survivor function among classes were conducted for selected oak species. Additionally, hazard functions were determined for diameter classes for damaged and undamaged oaks. Results indicate that mortality appears to vary significantly among some inventory classes such as oak species, but not among other classes such as ownership class. Indicators of individual tree vigor (i.e., crown class and ratio) were more significant predictors of oak tree mortality than site/stand attributes (i.e., density and aspect). Finally, results indicate that even fast-growing oak trees are at high risk of mortality if damaged by disease. Survival analyses, such as those applied in this study, may enable testing of forest health hypotheses using large-scale inventories. In the context of Missouri's oak forest decline, study results suggest management efforts should focus on limiting the spread of disease damage, increasing the vigor of residual trees, and emphasizing small trees when developing stand prescriptions.