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All wetland ecosystems are controlled by water table and soil saturation dynamics, so any local-scale deviation in soil elevation and thus water table position represents variability in this primary control. Wetland microtopography is the structured variability in soil elevation and is typically categorized into a binary classification of local high points (hummocks) and local low points (hollows). Although the influence of microtopography on vegetation composition and biogeochemical processes in wetlands has received attention around the globe, its role in forested wetlands is still less understood. We studied relationships among microtopography and understory vegetation communities, tree biomass, and soil chemistry in 10 black ash (Fraxinus nigra Marshall) wetlands in northern Minnesota, USA. To do so, we combined a 1 cm resolution surface elevation model generated from terrestrial laser scanning (TLS) with colocated water table, vegetation, and soil measurements. We observed that microtopography was an important structural element across sites, where hummocks were loci of greater species richness; greater midstory and canopy basal area; and higher soil concentrations of chloride, phosphorus, and base cations. In contrast, hollows were associated with higher soil nitrate and sulfate concentrations. We also found that the effect of microtopography on vegetation and soils was greater at wetter sites than at drier sites, suggesting that the distance-to-mean water table is a primary determinant of wetland biogeochemistry. These findings highlight clear controls of microtopography on vegetation and soil distributions while also supporting the notion that microtopography arises from feedbacks that concentrate biomass, soil nutrients, and productivity on microsite highs, especially in otherwise wet conditions. We therefore conclude that microtopography is a fundamental organizing structure in black ash wetlands. Minnesota Environmental and Natural Resources Trust Fund; USDA Forest Service Northern Research StationUnited States Department of Agriculture (USDA)United States Forest Service; Minnesota Forest Resources Council; Virginia Tech Department of Forest Resources and Environmental Conservation; Virginia Tech Institute for Critical Technology and Applied Science; Virginia Tech William J. Dann Fellowship This project was funded by the Minnesota Environmental and Natural Resources Trust Fund, the USDA Forest Service Northern Research Station, and the Minnesota Forest Resources Council. Additional funding was provided by the Virginia Tech Department of Forest Resources and Environmental Conservation, the Virginia Tech Institute for Critical Technology and Applied Science, and the Virginia Tech William J. Dann Fellowship. We gratefully acknowledge the fieldwork and data collection assistance provided by Mitch Slater, Alan Toczydlowksi, and Hannah Friesen. We also gratefully acknowledge Breanna Anderson for assistance with soil sample processing, David Mitchem for assistance in sample preparation and analysis, and Kelly Peeler for assistance in soil sample processing.

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.

Drought frequency and intensity are projected to increase throughout the southeastern USA, the natural range of loblolly pine (Pinus taeda L.), and are expected to have major ecological and economic implications. We analyzed the carbon and oxygen isotopic compositions in tree ring cellulose of loblolly pine in a factorial drought (similar to 30% throughfall reduction) and fertilization experiment, supplemented with trunk sap flow, allometry and microclimate data. We then simulated leaf temperature and applied a multi-dimensional sensitivity analysis to interpret the changes in the oxygen isotope data. This analysis found that the observed changes in tree ring cellulose could only be accounted for by inferring a change in the isotopic composition of the source water, indicating that the drought treatment increased the uptake of stored moisture from earlier precipitation events. The drought treatment also increased intrinsic water-use efficiency, but had no effect on growth, indicating that photosynthesis remained relatively unaffected despite 19% decrease in canopy conductance. In contrast, fertilization increased growth, but had no effect on the isotopic composition of tree ring cellulose, indicating that the fertilizer gains in biomass were attributable to greater leaf area and not to changes in leaf-level gas exchange. The multi-dimensional sensitivity analysis explored model behavior under different scenarios, highlighting the importance of explicit consideration of leaf temperature in the oxygen isotope discrimination (Delta O-18(c)) simulation and is expected to expand the inference space of the Delta O-18(c) models for plant ecophysiological studies. Pine Integrated Network: Education, Mitigation, and Adaptation project (PINEMAP); Coordinated Agricultural Project (USDA National Institute of Food and Agriculture award) [2011-68002-30185]; National Science Foundation (NSF)National Science Foundation (NSF) [EAR-1344703, IOS-1754893]; French Agence Nationale de la rechercheFrench National Research Agency (ANR) [ANR-17-ASIE-0007-02, ANR-18-PRIM-0006-09] This research was funded by The Pine Integrated Network: Education, Mitigation, and Adaptation project (PINEMAP), a Coordinated Agricultural Project (USDA National Institute of Food and Agriculture award 2011-68002-30185), the National Science Foundation (NSF-EAR-1344703 and NSF-IOS-1754893 to J.-C.D.) and the French Agence Nationale de la recherche (ANR-17-ASIE-0007-02 and ANR-18-PRIM-0006-09 to J.-C.D.). Public domain – authored by a U.S. government employee

Wetland microtopography is a visually striking feature, but also critically influences biogeochemical processes at both the scale of its observation (10(-2)-10(2)m(2)) and at aggregate scales (10(2)-10(4) m(2)). However, relatively little is known about how wetland microtopography develops or the factors influencing its structure and pattern. Growing research across different ecosystems suggests that reinforcing processes may be common between plants and their environment, resulting in self-organized patch features, like hummocks. Here, we used landscape ecology metrics and diagnostics to evaluate the plausibility of plant-environment feedback mechanisms in the maintenance of wetland microtopography. We used terrestrial laser scanning (TLS) to quantify the sizing and spatial distribution of hummocks in 10 black ash (Fraxinus nigra Marshall) wetlands in northern Minnesota, USA. We observed clear elevation bimodality in our wettest sites, indicating microsite divergence into two states: elevated hummocks and low elevation hollows. We coupled the TLS dataset to a 3-year water level record and soil-depth measurements, and showed that hummock height (mean = 0.31 +/- 0.06 m) variability is largely predicted by mean water level depth (R-2 = 0.8 at the site scale, R-2 = 0.12-0.56 at the hummock scale), with little influence of subsurface microtopography on surface microtopography. Hummocks at wetter sites exhibited regular spatial patterning (i.e., regular spacing of ca. 1.5 m, 25 %-30 % further apart than expected by chance) in contrast to the more random spatial arrangements of hummocks at drier sites Hummock size distributions (perimeters, areas, and volumes) were lognormal, with a characteristic patch area of approximately 1 m(2) across sites. Hummocks increase the effective soil surface area for redox gradients and exchange interfaces in black ash wetlands by up to 32 %, and influence surface water dynamics through modulation of specific yield by up to 30 %. Taken together, the data support the hypothesis that vegetation develops and maintains hummocks in response to anaerobic stresses from saturated soils, with a potential for a micro-topographic signature of life. Minnesota Environmental and Natural Resources Trust Fund; USDA Forest Service Northern Research StationUnited States Department of Agriculture (USDA)United States Forest Service; Minnesota Forest Resources Council; Virginia Tech Forest Resources and Environmental Conservation department; Virginia Tech Institute for Critical Technology and Applied Science; Virginia TechWilliam J. Dann Fellowship; POI FEDER Loire [2017-EX001784]; Water Agency of Loire Catchment AELB; University of Tours This project was funded by the Minnesota Environmental and Natural Resources Trust Fund, the USDA Forest Service Northern Research Station, and the Minnesota Forest Resources Council. Additional funding was provided by the Virginia Tech Forest Resources and Environmental Conservation department, the Virginia Tech Institute for Critical Technology and Applied Science, and the Virginia TechWilliam J. Dann Fellowship. Jacob S. Diamond is supported by POI FEDER Loire no. 2017-EX001784, the Water Agency of Loire Catchment AELB, and the University of Tours.

The rarity of rapid campaigns to characterize soils across scales limits opportunities to investigate variation in soil carbon stocks (SOC) storage simultaneously at large and small scales, with and without site-level replication. We used data from two complementary campaigns at 40 sites in the United States across the National Ecological Observatory Network (NEON), in which one campaign sampled profiles from closely co-located intensive plots and physically composited similar horizons, and the other sampled dozens of pedons across the landscape at each site. We demonstrate some consistencies between these distinct designs, while also revealing that within-site replication reveals patterns and predictors of SOC stocks not detectable with non-replicated designs. Both designs demonstrate that SOC stocks of whole soil profiles vary across continental-scale climate gradients. However, broad climate patterns may mask the importance of localized variation in soil physicochemical properties, as captured by within-site sampling, especially for SOC stocks of discrete genetic horizons. Within-site replication also reveals examples in which expectations based on readily explained continental-scale patterns do not hold. For example, even wide-ranging drainage class sequences within landscapes do not duplicate the clear differences in profile SOC stocks across drainage classes at the continental scale, and physicochemical factors associated with increasing B horizon SOC stocks at continental scales frequently do not follow the same patterns within landscapes. Because inferences from SOC studies are a product of their context (where, when, how), this study provides context-in terms of SOC stocks and the factors that influence them-for others assessing soils and the C cycle at NEON sites. National Science FoundationNational Science Foundation (NSF) [EF-1340681, EF-1340504, EF-1340516, EF-1340250]; Battelle [US001-0000757206]; USDA-Forest ServiceUnited States Department of Agriculture (USDA)United States Forest Service [16-CR-11242306-071, 17-CR-11242306-028]; National Institute of Food and AgricultureUnited States Department of Agriculture (USDA)National Institute of Food and Agriculture [2017-67003-26481]; University of Michigan Biological StationUniversity of Michigan System; National Science FoundationNational Science Foundation (NSF) The authors wish to acknowledge Kate Lajtha, Samantha Weintraub, and Will Wieder for their dedication to the special journal issue to which this paper was submitted, and to the anonymous reviewers whose comments improved it from its manuscript form. James Klapperich, Dave Mitchem, Paula Zermeno, and Rommel Zulueta made critical contributions to the acquisition of samples and data used in this analysis, and the USDA-NRCS NSSC, Kellogg Soil Survey Laboratory considerably facilitated data access. The National Ecological Observatory Network is a project sponsored by the National Science Foundation and managed under cooperative agreement by Battelle Memorial Institute, and this work was made possible by support from the National Science Foundation (Award Nos. EF-1340681, EF-1340504, EF-1340516, EF-1340250), Battelle (US001-0000757206), the USDA-Forest Service (Award Nos. 16-CR-11242306-071,17-CR-11242306-028) and National Institute of Food and Agriculture (2017-67003-26481), and the University of Michigan Biological Station. Public domain – authored by a U.S. government employee

Rapid DNA extraction is a critical barrier for routine and fieldable genetics tests for applications in conservation, such as illegal trafficking and fraudulent mislabelling. Here, we develop a non-thermal focused ultrasound extraction (FUSE) technique that creates a dense cloud of high-pressure acoustic cavitation bubbles to disintegrate targeted tissues into an acellular debris, resulting in the rapid release of entrapped DNA. In this work, we demonstrate the proof-of-concept of the FUSE technique by obtaining species identifiable sequences and shotgun sequencing reads from DNA extracted from Atlantic salmon Salmo salar tissues. Having mitigated the key risks for this technique, we hypothesize future developments with this technology can be applied to accelerate and simplify DNA extraction from exceedingly difficult samples with complex tissue matrices (i.e. fibrous tissue and timber samples) in both laboratory and field settings. Gordon and Betty Moore FoundationGordon and Betty Moore Foundation [8518]; Rhodes Trust; Schmidt Futures Foundation; Virginia Tech Department of Biomedical Engineering and Mechanics; Center for Engineering Health; Institute for Critical Technology and Applied Science; National Geographic SocietyNational Geographic Society National Geographic Society; Schmidt Science Fellows; Gordon and Betty Moore Foundation, Grant/Award Number: #8518; Rhodes Trust and Schmidt Futures Foundation; Virginia Tech Department of Biomedical Engineering and Mechanics; Institute for Critical Technology and Applied Science; Center for Engineering Health

In forest inventory, traditional ground-based resource assessments are often expensive and time-consuming forcing managers to reduce sample sizes to meet budgetary and logistical constraints. Small area estimation (SAE) is a class of statistical estimators that uses a combination of traditional survey data and linearly related auxiliary information to improve estimate precision. These techniques have been shown to improve the precision of stand-level inventory estimates in loblolly pine plantations using lidar height percentiles and thinning status as covariates. In this study, the effects of reduced lidar point-cloud densities and lower digital elevation model (DEM) spatial resolutions were investigated for total planted volume estimates using area-level SAE models. In the managed Piedmont pine plantation conditions evaluated, lower lidar point-cloud densities and DEM spatial resolutions were found to have minimal effects on estimates and precision. The results of this study are promising to those interested in incorporating SAE methods into forest inventory programs. Forest Modeling Research Cooperative; Department of Forest Resources and Environmental Conservation; Virginia Tech; USDA McIntire-Stennis program [VA-136630] This work was supported by the Forest Modeling Research Cooperative; the Department of Forest Resources and Environmental Conservation; Virginia Tech; and the USDA McIntire-Stennis program (Project No. VA-136630). Public domain – authored by a U.S. government employee

Accurate prediction of stem diameter is an important prerequisite of forest management. In this study, an appropriate stem taper function was developed for upper stem diameter estimation of white birch (Betula platyphylla Sukaczev) in ten sub-regions of the Daxing'an Mountains, northeast China. Three commonly used taper functions were assessed using a diameter and height dataset comprising 1344 trees. A first-order continuous-time error structure accounted for the inherent autocorrelation. The segmented model of Max and Burkhart (For Sci 22:283-289, 1976. 10.1093/forestscience/22.3.283) and the variable exponent taper function of Kozak (For Chron 80:507-515, 2004. 10.5558/tfc80507-4) described the data accurately. Owing to its lower multicollinearity, the Max and Burkhart (1976) model is recommended for diameter estimation at specific heights along the stem for the ten sub-regions. After comparison, the Max and Burkhart (1976) model was refitted using nonlinear mixed-effects techniques. Mixed-effects models would be used only when additional upper stem diameter measurements are available for calibration. Differences in region-specific taper functions were indicated by the method of the non-linear extra sum of squares. Therefore, the particular taper function should be adjusted accordingly for each sub-region in the Daxing'an Mountains. National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [31570624]; Applied Technology Research and Development Plan Project of Heilongjiang Province [GA19C006]; Fundamental Research Funds for Central UniversitiesFundamental Research Funds for the Central Universities [2572019CP15] This study was financially supported by the National Natural Science Foundation of China (31570624), Applied Technology Research and Development Plan Project of Heilongjiang Province (GA19C006), and Fundamental Research Funds for Central Universities (2572019CP15).

Loblolly pine (Pinus taeda L.) is one of the most widely planted tree species globally. As the reliability of estimating forest characteristics such as volume, biomass and carbon becomes more important, the necessary resources available for assessment are often insufficient to meet desired confidence levels. Small area estimation (SAE) methods were investigated for their potential to improve the precision of volume estimates in loblolly pine plantations aged 9-43. Area-level SAE models that included lidar height percentiles and stand thinning status as auxiliary information were developed to test whether precision gains could be achieved. Models that utilized both forms of auxiliary data provided larger gains in precision compared to using lidar alone. Unit-level SAE models were found to offer additional gains compared with area-level models in some cases; however, area-level models that incorporated both lidar and thinning status performed nearly as well or better. Despite their potential gains in precision, unit-level models are more difficult to apply in practice due to the need for highly accurate, spatially defined sample units and the inability to incorporate certain area-level covariates. The results of this study are of interest to those looking to reduce the uncertainty of stand parameter estimates. With improved estimate precision, managers, stakeholders and policy makers can have more confidence in resource assessments for informed decisions. Forest Modeling Research Cooperative; Department of Forest Resources and Environmental Conservation, Virginia Tech; United States Department of Agriculture McIntire-Stennis program [VA-136630] The Forest Modeling Research Cooperative, the Department of Forest Resources and Environmental Conservation, Virginia Tech and the United States Department of Agriculture McIntire-Stennis program (Project No. VA-136630) are all gratefully acknowledged for supporting this project. Public domain – authored by a U.S. government employee

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5. National Science Foundation (NSF)National Science Foundation (NSF); National Center for Atmospheric Research - NSF [1852977]; RUBISCO Scientific Focus Area (SFA) - Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science; Columbia University Presidential Fellowship; U.S. Department of Agriculture NIFA Award [2015-67003-23485]; NASA Interdisciplinary Science Program Award [NNX17AK19G]; U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science programUnited States Department of Energy (DOE) [DE-SC0008317, DESC0016188]; National Science FoundationNational Science Foundation (NSF) [DEB-1153401]; NASA's CARBON program; NASA's TE program; National Aeronautics and Space AdministrationNational Aeronautics & Space Administration (NASA) We would like to thank the reviewers for their insightful comments and helpful suggestions that improved the clarity and presentation of the manuscript. The CESM project is supported primarily by the National Science Foundation (NSF). This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement 1852977. Computing and data storage resources, including the Cheyenne supercomputer (doi: 10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. D. M. L. was supported in part by the RUBISCO Scientific Focus Area (SFA), which is sponsored by the Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science. D. K. and P. G. were supported by Columbia University Presidential Fellowship. G. B., D. L. L., W. R. W., and R. Q. T. were supported by the U.S. Department of Agriculture NIFA Award 2015-67003-23485. W. R. W. and G. K. A. were supported by the NASA Interdisciplinary Science Program Award NNX17AK19G. J. B. F. and M. S. carried out the research in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged. All rights reserved. J. B. F. and M. S. were supported in part by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science program under Awards DE-SC0008317 and DESC0016188; the National Science Foundation Ecosystem Science program (DEB-1153401); and NASA's CARBON and TE programs. All model data are archived and publicly available at the UCAR/NCAR Climate Data Gateway (https://doi.org/10.5065/d6154fwh).

Wild bees support global agroecosystems via pollination of agricultural crops and maintaining diverse plant communities. However, with an increased reliance on pesticides to enhance crop production, wild bee communities may inadvertently be affected through exposure to chemical residues. Laboratory and semi-field studies have demonstrated lethal and sublethal effects of neonicotinoids on limited genera (e.g., Apis, Bombus, Megachile), yet full field studies evaluating impacts to wild bee communities remain limited. Here, we conducted a two-year field study to assess whether neonicotinoid seed treatment and presence in environmental media (e.g., soil, flowers) influenced bee nest and diet guild abundance and richness. In 2017 and 2018, we planted 23 Missouri agricultural fields to soybeans (Glycine max) using one of three seed treatments: untreated (no insecticide), treated (imidadoprid), or previously-treated (untreated, but neonicotinoid use prior to 2017). During both years, wild bees were collected in study field margins monthly (May to September) in tandem with soil and flowers from fields and field margins that were analyzed for neonicotinoid residues. Insecticide presence in soils and flowers varied over the study with neonicotinoids infrequently detected in both years within margin flowers (0%), soybean flowers (

Active forest management operations, such as regeneration harvests, can reduce hazardous fuel loads and alter fuel structure, potentially minimizing extreme wildfire conditions while maintaining ecosystem services, such as wildlife habitat and water quality. Regeneration harvests of differing intensities (clearcut, high-retention shelterwood, and low-retention shelterwood) were first applied between 1995 and 1996 to three sites on the George Washington-Jefferson National Forest in the Ridge and Valley Province of Virginia, USA. Over two decades after the clearcut was conducted and 11–12 years after the overwood was removed in the shelterwood stands, woody debris, litter, and duff masses and depths were quantified. One-hour fuel loads were greater in clearcut units than in high-retention shelterwood, low-retention shelterwood, or control units. Ten-hour fuel loads were greater in clearcut and low-retention shelterwood units than in high-retention shelterwood and control units. No significant differences in 100-hour fuels were observed between treatments. Control units contained more rotten and total 1000-hour fuels than all other treatments. The total woody debris load was less in the clearcut and high-retention shelterwood than in the low-retention shelterwood and control. High-retention shelterwood woody fuel depth was greater than clearcut woody fuel depth. Litter and duff loads were less in treated units than in the control units. Total fuel load (woody fuel load + litter load + duff load) was greater in the control than the silvicultural treatments. Litter depth did not differ between treatments, while duff depth was greater in the control than in the treated units. Using the computer modeling software, BehavePlus 6.0.0, these alterations to fuel loads and depths led to increased values in the control units for six fire behavior parameters. Predicted surface flame length in the low-retention shelterwood was the only modeled value that was not less than control values. Overall, these results indicated that harvest intensity and timing may have long-term effects on down and dead woody fuels, forest floor depth, and potential fire behavior. Clearcutting reduced fire behavior most, followed by the high-retention shelterwood system. The potential differences in slash and debris generated by varying shelterwood systems may impact long-term fuel and fire dynamics. Published version

Effects of intensive forest management on soil phosphorus (P) are unclear and may impact long-term site productivity. We assessed changes in P availability over 10 years associated with harvest intensity (bole-only vs. whole-tree harvest) and vegetation control treatments (initial vegetation control (IVC) vs. five years of annual vegetation control (AVC)) using a P fractionation procedure. Fractions were characterized at 0-15, 15-30, and 30-60 cm soil depths in two coast Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. menziesii) plantations with strongly contrasting soil properties near Matlock, WA (young soils formed in glacial outwash) and Molalla, OR (relatively old soils formed in igneous residuum and exhibiting andic properties). Al and Fe concentrations associated with short-range order minerals were greater at Molalla than Matlock and generally decreased with depth at both sites. We observed decreases in most total-P and P-fraction concentrations across the three soil depths at the Molalla site. Effects were less pronounced and generally inconsistent at the Matlock site. Decreases in total P and P fraction concentrations were greatest in the AVC treatments at Matlock, but opposite trends were observed at Molalla where decreases were greatest with IVC. There was no difference between harvest treatments on the change in P fractions in most instances, with the exception of the 30-60 cm depth at Matlock where concentrations of some P fractions were maintained or increased with bole-only harvesting. Ten-year responses indicate harvest intensity has limited effects on long-term productivity associated with soil P because of the large size of the soil P pools and the relatively small changes in soil P that occurred with treatment. Decreases in P concentrations with AVC at Matlock and IVC at Molalla were larger than the other treatments and highlight the important role of vegetation in P dynamics following harvesting at these sites. USDA Forest Service Pacific Northwest Research StationUnited States Department of Agriculture (USDA)United States Forest Service; Virginia Tech; Green Diamond Resource Company; Port Blakely Tree Farms, LLC This is a product of the Sustainable Forestry component of Agenda 2020, a joint effort of the USDA Forest Service Research and Development and the American Forest and Paper Association. Funds were provided by the USDA Forest Service Pacific Northwest Research Station, Virginia Tech, Green Diamond Resource Company, and Port Blakely Tree Farms, LLC. The authors are grateful to Randall Greggs and Mike Warjone for providing critical financial and logistical support that made this study possible. Special thanks to J. Dollins for assisting with field work and sample preparation, and Stephanie Duston for her assistance in the laboratory. Public domain – authored by a U.S. government employee

We examined crown architecture and within crown leaf area distribution effects on Pinus taeda L. growth in North Carolina (NC), Virginia (VA), and Brazil (BR) to better understand why P. taeda can grow much better in Brazil than in the southeastern United States. The NC, VA, and BR sites were planted in 2009, 2009, and 2011, respectively. At all sites, we planted the same two genetic entries at 618, 1236, and 1854 trees ha(-1). In 2013, when trees were still open grown, the VA and NC sites had greater branch diameter (24%), branch number (14%), live crown length (44%), foliage mass (82%), and branch mass (91%), than the BR site. However, in 2017, after crown closure and when there was no significant difference in tree size, site did not significantly affect these crown variables. In 2013, site significantly affected absolute leaf area distribution, likely due to differences in live crown length and leaf area, such that there was more foliage at a given level in the crown at the VA and NC sites than at the BR site. In 2017, site was still a significant factor explaining leaf area distribution, although at this point, with crown closure and similar sized trees, there was more foliage at the BR site at a given level in the crown compared to the VA and NC sites. In 2013 and 2017, when including site, genetic entry, stand density, and leaf area distribution parameters as independent variables, site significantly affected individual tree growth efficiency, indicating that something other than leaf area distribution was influencing the site effect. Better BR P. taeda growth is likely due to a combination of factors, including leaf area distribution, crown architecture, and other factors that have been identified as influencing the site effect (heat sum), indicating that future work should include a modeling analysis to examine all known contributing factors. Public domain – authored by a U.S. government employee

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in under-represented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback. National Natural Science Foundation of ChinaNational Natural Science Foundation of China [31430015, 31830012]; US NSFNational Science Foundation (NSF) [DEB-0955771]; ClimMani COST actionEuropean Cooperation in Science and Technology (COST) [ES1308] We thank J. Wang (Hebei University), S. Yang (Institute of Botany, Chinese Academy of Sciences), L. Zhou (East China Normal University), C. Qiao (Xinyang Normal University) and H. Li (Henan University) for their help in meta-analyses and interaction analyses, and H. Li, Y. Liu (Institute of Tibetan Plateau Research, Chinese Academy of Sciences) and Y. He (Peking University) for their help in plotting figures. This work was financially supported by the National Natural Science Foundation of China (grant nos. 31430015 and 31830012). This study emerged from the INTERFACE Workshop in Beijing, China (https://www.bio.purdue.edu/INTERFACE/) supported by the US NSF DEB-0955771. We also acknowledge support from the ClimMani COST action (ES1308). Public domain – authored by a U.S. government employee

Using a large dataset compiled from studies over the years covering 23 tree species, we developed methods to estimate total and components (stem, bark, branch, and foliage) of aboveground live tree biomass. Missing components in the dataset were imputed using species-specific or generalized (species combined into softwood and hardwood groups) Dirichlet imputation. Geometric means of the imputed stem wood proportions were 8% and 9% higher than the observed geometric mean of stem wood proportions in softwood and hardwood species, respectively. For other components, the differences were within 1%. On average, the component ratio method (CRM), used for the official United States forest carbon inventories, underestimated the aboveground biomass (AGB, kg) predictions by 3.7% with a very wide range (-70.3% to 31.6%). Compared with the CRM approach, equations developed in this study reduced RMSE of AGB by as much as 145.0%. On average, new equations reduced RMSE in predicting individual-tree AGB by 15.5% compared with the CRM approach and by 3.9% compared with a calibration of CRM AGB. Predicting AGB as a function of stem volume was not as accurate as using direct AGB equations. Generalized component ratio equations may be suitable for the stem wood component but were highly biased for other components. Public domain – authored by a U.S. government employee

Formal planning and development of what became the first Landsat satellite commenced over 50 years ago in 1967. Now, having collected earth observation data for well over four decades since the 1972 launch of Landsat-1, the Landsat program is increasingly complex and vibrant. Critical programmatic elements are ensuring the continuity of high quality measurements for scientific and operational investigations, including ground systems, acquisition planning, data archiving and management, and provision of analysis ready data products. Free and open access to archival and new imagery has resulted in a myriad of innovative applications and novel scientific insights. The planning of future compatible satellites in the Landsat series, which maintain continuity while incorporating technological advancements, has resulted in an increased operational use of Landsat data. Governments and international agencies, among others, can now build an expectation of Landsat data into a given operational data stream. International programs and conventions (e.g., deforestation monitoring, climate change mitigation) are empowered by access to systematically collected and calibrated data with expected future continuity further contributing to the existing multi-decadal record. The increased breadth and depth of Landsat science and applications have accelerated following the launch of Landsat-8, with significant improvements in data quality. Herein, we describe the programmatic developments and institutional context for the Landsat program and the unique ability of Landsat to meet the needs of national and international programs. We then present the key trends in Landsat science that underpin many of the recent scientific and application developments and follow-up with more detailed thematically organized summaries. The historical context offered by archival imagery combined with new imagery allows for the development of time series algorithms that can produce information on trends and dynamics. Landsat-8 has figured prominently in these recent developments, as has the improved understanding and calibration of historical data. Following the communication of the state of Landsat science, an outlook for future launches and envisioned programmatic developments are presented. Increased linkages between satellite programs are also made possible through an expectation of future mission continuity, such as developing a virtual constellation with Sentinel-2. Successful science and applications developments create a positive feedback loop—justifying and encouraging current and future programmatic support for Landsat. © 2019 The United States Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) are gratefully acknowledged for support and encouragement of the 2012–2017 Landsat Science Team ( https://landsat.usgs.gov/landsat-science-teams ). The Editor and Reviewers are thanked for the valuable insights and constructive suggestions made to improve this manuscript.

Drainage is a globally common disturbance in forested peatlands that impacts peat soils, forest communities, and associated ecosystem functions, calling for informed hydrologic restoration strategies. The Great Dismal Swamp (GDS), located in Virginia and North Carolina, U.S.A., has been altered since colonial times, particularly by extensive ditch networks installed to lower water levels and facilitate timber harvests. Consequently, peat decomposition rates have accelerated, and red maple has become the dominant tree species, reducing the historical mosaic of bald cypress, Atlantic white-cedar, and pocosin stands. Recent repair and installation of water control structures aim to control drainage and, in doing so, enhance forest community composition and preserve peat depths. To help inform these actions, we established five transects of 15 plots each (75 plots total) along a hydrologic gradient where we measured continuous water levels and ecosystem attributes, including peat depths, microtopography, and forest composition and structure. We found significant differences among transects, with wetter sites having thicker peat, lower red maple importance, greater tree density, and higher overall stand richness. Plot-level analyses comported with these trends, clearly grouping plots by transects (via nonmetric multidimensional scaling) and resulting in significant correlations between specific hydrologic metrics and ecosystem attributes. Our findings highlight hydrologic controls on soil carbon storage, forest structure, and maple dominance, with implications for large-scale hydrologic restoration at GDS and in other degraded forested peatlands more broadly. Virginia Tech Department of Forest Resources and Environmental Conservation; U.S. Fish and Wildlife Service Great Dismal Swamp National Wildlife Refuge; U.S. Geological SurveyUnited States Geological Survey This work was funded by the Virginia Tech Department of Forest Resources and Environmental Conservation, U.S. Fish and Wildlife Service Great Dismal Swamp National Wildlife Refuge, and U.S. Geological Survey. ("Any use of trade, product or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government") Special thanks to Ray Ludwig and Will Doran for data collection assistance and Tal Roberts for technical support. Public domain – authored by a U.S. government employee

Scotch broom [Cytisus scoparius (L.) Link] is a globally important nitrogen (N)-fixing invasive plant species that has potential to alter soil water dynamics, soil chemistry, and plant communities. We evaluated the effects of Scotch broom on soil moisture, soil chemistry, soil temperature, photosynthetically active radiation (PAR), and vegetation communities over 4years at a site recently harvested for timber. Treatments of Scotch broom (either present via planting or absent) and background vegetation (either present or absent via herbicide treatments) were applied to 4m(2) plots. Background vegetation was associated with the greatest decrease of soil water content (SWC) among treatments. During the driest year, Scotch broom showed some evidence of increased early-and late-season soil water usage, and, briefly, a high usage relative to background vegetation plots. On a percent cover basis, Scotch broom had a substantially greater negative influence on SWC than did background vegetation. Surprisingly, Scotch broom was not consistently associated with increases in total soil N, but there was evidence of increasing soil water N when Scotch broom was present. Scotch broom-only plots had greater concentrations of soil water magnesium (Mg2+) and calcium (Ca2+) than other treatments. On a percent cover basis, Scotch broom had a uniquely high demand for potassium (K+) relative to the background vegetation. Average soil temperature was slightly greater, and soil surface PAR lower, with Scotch broom present. Scotch broom-absent plots increased in species diversity and richness over time, while Scotch broom-present plots remained unchanged. Scotch broom presence was associated with an increase in cover of nonnative sweet vernalgrass (Anthoxanthum odoratum L.). Scotch broom generated positive feedbacks with resource conditions that favored its dominance and the establishment of nonnative grass. USDA National Institute for Food and Agriculture [GRANT 11325729] Financial support for this research was provided by the USDA National Institute for Food and Agriculture (Grants.gov number: GRANT 11325729). We wish to thank Green Diamond Resource Company for use of their land and logistical support. We would like to thank James Dollins for all of his efforts on this project. Public domain – authored by a U.S. government employee

Vegetation indices calculated from remotely sensed satellite imagery are commonly used within empirically derived models to estimate leaf area index in loblolly pine plantations in the southeastern United States. The data used to parameterize the models typically come with observation errors, resulting in biased parameters. The objective of this study was to quantify and reduce the effects of observation errors on a leaf area index (LAI) estimation model using imagery from Landsat 5 TM and 7 ETM+ and over 1500 multitemporal measurements from a Li-Cor 2000 Plant Canopy Analyzer. Study data comes from a 16 quarter 1 ha plot with 1667 trees per hectare (2 m × 3 m spacing) fertilization and irrigation research site with re-measurements taken between 1992 and 2004. Using error-in-variable methods, we evaluated multiple vegetation indices, calculated errors associated with their observations, and corrected for them in the modeling process. We found that the normalized difference moisture index provided the best correlation with below canopy LAI measurements (76.4%). A nonlinear model that accounts for the nutritional status of the stand was found to provide the best estimates of LAI, with a root mean square error of 0.418. The analysis in this research provides a more extensive evaluation of common vegetation indices used to estimate LAI in loblolly pine plantations and a modeling framework that extends beyond the typical linear model. The proposed model provides a simple to use form allowing forest practitioners to evaluate LAI development and its uncertainty in historic pine plantations in a spatial and temporal context. Published version

In this study, we explore the use of unsteady transit time distribution (TTD) theory to model solute transport in biofilters, a popular form of nature-based or "green" storm water infrastructure (GSI). TTD theory has the potential to address many unresolved challenges associated with predicting pollutant fate and transport through these systems, including unsteadiness in the water balance (time-varying inflows, outflows, and storage), unsteadiness in pollutant loading, time-dependent reactions, and scale-up to GSI networks and urban catchments. From a solution to the unsteady age conservation equation under uniform sampling, we derive an explicit expression for solute breakthrough during and after one or more storm events. The solution is calibrated and validated with breakthrough data from 17 simulated storms at a field-scale biofilter test facility in Southern California, using bromide as a conservative tracer. TTD theory closely reproduces bromide breakthrough concentrations, provided that lateral exchange with the surrounding soil is accounted for. At any given time, according to theory, more than half of the water in storage is from the most recent storm, while the rest is a mixture of penultimate and earlier storms. Thus, key management endpoints, such as the pollutant treatment credit attributable to GSI, are likely to depend on the evolving age distribution of water stored and released by these systems. U.S. National Science Foundation Growing Convergence Research Program (NSF Award)National Science Foundation (NSF) [2021015]; University of California Office of the President, Multicampus Research Programs and Initiatives awardUniversity of California System [MRP-17-455083]; Virginia Tech's Charles E. Via, Jr. Department of Civil and Environmental Engineering The authors declare no conflict of interest. Funding was provided by the U.S. National Science Foundation Growing Convergence Research Program award to SBG (NSF Award #2021015), the University of California Office of the President, Multicampus Research Programs and Initiatives award to PH and SBG (Grant ID MRP-17-455083), and Virginia Tech's Charles E. Via, Jr. Department of Civil and Environmental Engineering. EAP was supported by a Via Ph.D. Fellowship from Virginia Tech's Charles E. Via, Jr. Department of Civil and Environmental Engineering. The authors thank B. Hong, A. Mehring, and OCPW staff for their assistance with field sampling and lab analysis, and C. Harman, E. Fassman-Beck, the Associate Editor, and three anonymous reviewers for helpful edits and comments. E. A. Parker and S. B. Grant designed and implemented the experiments, derived the TTD framework, and drafted the manuscript. Y. Cao, J. Peng, and S. Shao coordinated field experiments. M. A. Rippy, P. Holden, M. Feraud, S. Avasarala, H. Liu, W. Hung, M. Rugh, J. Jay, D. Li contributed to field sampling and lab analysis. M. A. Rippy, S. Shao, and K. McGuire contributed analyses. All co-authors contributed edits.

With continued global change as a result of land use changes, invasive species and changing climatic patterns, it is becoming increasingly important to understand the adaptability of Senegalia senegal provenances to maximize resilience in managed and natural populations of this species. The objective of this study is to investigate Senegalia senegal genotypic differences in water use efficiency (WUE) measured by stable C-13 isotope composition in foliage according to their ploidy levels. Secondary objectives are to discuss inherent adaptive variation related to soil pH, survival, growth indexes, gum arabic yield and WUE within provenance in the climate change context. A Senegalia senegal progeny trial, in Dahra, Senegal was used in this study: 443 adult trees consisting of 60 families nested within 4 provenances were assessed in this study. Results showed significant differences in gum yield among provenances (P = 0.0002) and families (P < 0.0001). Diamenar and Ngane provenances showed overall similar annual gum yield despite a lower tree survival rate of Ngane than Diamenar. Growth traits, especially stem volume index and crown area index were larger on Ngane provenance, which also displayed significantly higher foliar WUE and lower leaf area index (LAI) than the other provenances. WUE was positively correlated with gum yield (P = 0.0302), but the coefficient of determination was only 2%. Foliar delta C-13 varied significantly (P < 0.0001) between diploids (- 27.91 parts per thousand) and polyploids (- 27.12 parts per thousand). However, within each provenance no significant difference was found. Only 15% of isotope compositions could be explained by ploidy level variation. Differences found in growth and gum yield may be attributed to genotype-specific variation. However, a significant correlation between soil pH and tree survival rate was found (P = 0.0051; r = 0.60). This study confirmed a possible improvement of the gum arabic sector through genotype based selection. Ngane and Diamenar seem to be more profitable to grow in Dahra than the other tested provenances. Future research should investigate the effect of soil pH, other soil physical and chemical properties, and management activities to improve site quality on tree survival and gum yields among provenances. Further, more research is needed to clarify inherent traits underlying drought tolerance in the field and gum yield performance. United States Agency for International Development (USAID) as part of Feed the FutureUnited States Agency for International Development (USAID); U.S. Government's global hunger and food security initiative [AID-685-A-00-10-00194-00] We are grateful to Centre National de Recherche Forestiere for the logistical support provided during the fieldwork. We thank Mrs Momar Wade and Ibra Padane for their support in collecting data, Dr Marieme Fall Ba and Dr Mamadou Ousseynou Ly for their help to conduct soil analysis. A big thank to Mr Andy Laviner for his help on using the LAI 2200, and Mr David Mitchem to conduct isotope analysis of leaves. This article is made possible in part by the generous support of the American people through the United States Agency for International Development (USAID) as part of Feed the Future, the U.S. Government's global hunger and food security initiative, under the terms of Contract No. AID-685-A-00-10-00194-00 (USAID/Education and Research in Agriculture). The contents are the responsibility of the author(s) and do not necessarily reflect the views of USAID or the United States Government.

The Hubbard Brook Experimental Forest (HBEF) was established in 1955 by the U.S. Department of Agriculture, Forest Service out of concerns about the effects of logging increasing flooding and erosion. To address this issue, within the HBEF hydrological and micrometeorological monitoring was initiated in small watersheds designated for harvesting experiments. The Hubbard Brook Ecosystem Study (HBES) originated in 1963, with the idea of using the small watershed approach to study element fluxes and cycling and the response of forest ecosystems to disturbances, such as forest management practices and air pollution. Early evidence of acid rain was documented at the HBEF and research by scientists at the site helped shape acid rain mitigation policies. New lines of investigation at the HBEF have built on the long legacy of watershed research resulting in a shift from comparing inputs and outputs and quantifying pools and fluxes to a more mechanistic understanding of ecosystem processes within watersheds. For example, hydropedological studies have shed light on linkages between hydrologic flow paths and soil development that provide valuable perspective for managing forests and understanding stream water quality. New high frequency in situ stream chemistry sensors are providing insights about extreme events and diurnal patterns that were indiscernible with traditional weekly sampling. Additionally, tools are being developed for visual and auditory data exploration and discovery by a broad audience. Given the unprecedented environmental change that is occurring, data from the small watersheds at the HBEF are more relevant now than ever and will continue to serve as a basis for sound environmental decision-making. Public domain – authored by a U.S. government employee

Near-term, iterative ecological forecasts with quantified uncertainty have great potential for improving lake and reservoir management. For example, if managers received a forecast indicating a high likelihood of impending impairment, they could make decisions today to prevent or mitigate poor water quality in the future. Increasing the number of automated, real-time freshwater forecasts used for management requires integrating interdisciplinary expertise to develop a framework that seamlessly links data, models, and cyberinfrastructure, as well as collaborations with managers to ensure that forecasts are embedded into decision-making workflows. The goal of this study is to advance the implementation of near-term, iterative ecological forecasts for freshwater management. We first provide an overview of FLARE (Forecasting Lake And Reservoir Ecosystems), a forecasting framework we developed and applied to a drinking water reservoir to assist water quality management, as a potential open-source option for interested users. We used FLARE to develop scenario forecasts simulating different water quality interventions to inform manager decision-making. Second, we share lessons learned from our experience developing and running FLARE over 2 years to inform other forecasting projects. We specifically focus on how to develop, implement, and maintain a forecasting system used for active management. Our goal is to break down the barriers to forecasting for freshwater researchers, with the aim of improving lake and reservoir management globally. Western Virginia Water Authority; U.S. National Science FoundationNational Science Foundation (NSF) [CNS-1737424, DEB-1753639, DEB-1926050, DEB1926388, DBI-1933016, DBI-1933102] Published version This work was financially supported by the Western Virginia Water Authority and U.S. National Science Foundation grants CNS-1737424, DEB-1753639, DEB-1926050, and DEB1926388, DBI-1933016, DBI-1933102.

Ecosystems require access to key nutrients like nitrogen (N) and sulfur (S) to sustain growth and healthy function. However, excessive deposition can also damage ecosystems through nutrient imbalances, leading to changes in productivity and shifts in ecosystem structure. While wildland fires are a known source of atmospheric N and S, little has been done to examine the implications of wildland fire deposition for vulnerable ecosystems. We combine wildland fire emission estimates, atmospheric chemistry modeling, and forest inventory data to (a) quantify the contribution of wildland fire emissions to N and S deposition across the U S, and (b) assess the subsequent impacts on tree growth and survival rates in areas where impacts are likely meaningful based on the relative contribution of fire to total deposition. We estimate that wildland fires contributed 0.2 kg N ha−1 yr−1 and 0.04 kg S ha−1 yr−1 on average across the U S during 2008–2012, with maxima up to 1.4 kg N ha−1 yr−1 and 0.6 kg S ha−1 yr−1 in the Northwest representing over ∼30% of total deposition in some areas. Based on these fluxes, exceedances of S critical loads as a result of wildland fires are minimal, but exceedances for N may affect the survival and growth rates of 16 tree species across 4.2 million hectares, with the most concentrated impacts occurring in Oregon, northern California, and Idaho. Understanding the broader environmental impacts of wildland fires in the U S will inform future decision making related to both fire management and ecosystem services conservation.

Pesticide exposure is a growing global concern for pollinator conservation. While most current pesticide studies have specifically focused on the impacts of neonicotinoid insecticides toward honeybees and some native bee species, wild pollinators may be exposed to a broader range of agrochemicals. In 2016 and 2017 we collected a total of 637 wild bees and butterflies from the margins of cultivated agricultural fields situated on five Conservation Areas in mid-northern Missouri. Pollinators were composited by individual genera (90 samples) and whole tissues were then analyzed for the presence of 168 pesticides and degradation products. At least one pesticide was detected (% frequency) in the following wild bee genera: Bombus (96%), Eucera (75%), Melissodes (73%), Pnlothrix (50%), Xylocopa (50%), and Megachile ( 17%). Similarly, at least one pesticide was detected in the following lepidopteran genera: Hemaris (100%), Hylephila (75%), Danaus (60%), and Colitis (50%). Active ingredients detected in >2% of overall pollinator samples were as follows: metolachlor (24%), tebuconazole (22%), atrazine (18%), iinidadoprid desnitro (13%), bifenthrin (9%), flumetralin (9%), p, p'-DDD (6%), tebupirimfos (4%), Iludioxonil (4%), flutriafol (3%), cyproconazole (2%), and oxacliazon (2%). Concentrations of individual pesticides ranged from 2 to 174 ng/g. Results of this pilot field study indicate that wild pollinators arc exposed to and are potentially bioaccumulating a wide variety of pesticides in addition to neonicotinoids. Here, we provide evidence that wild bee and butterfly genera may face exposure to a wide range of insecticides, fungicides, and herbicides despite being collected from areas managed for conservation. Therefore, even with the presence of extensive habitat, minimal agricultural activity on Conservation Areas may expose pollinators to a range of pesticides. Published by Elsevier B.V. MDC; Missouri Cooperative Fish and Wildlife Research Unit; USDA-NIFAUnited States Department of Agriculture (USDA) [MO-HANR0007]; Multi-State Working Group W3045 [MOMSNR0002]; University of Missouri; U.S. Fish and Wildlife ServiceUS Fish & Wildlife Service; U.S. Geological SurveyUnited States Geological Survey; Wildlife Management Institute; USGS Toxic Substances Hydrology ProgramUnited States Geological Survey We thank the following individuals for assistance in field data collection and lab sample preparation: W. Boys, K. Kuechle, J. Murray, and J. Piercefield. Thank you to C. Sanders, M. McWayne and M. De Parsia who processed the pollinators for pesticide analysis. Special thanks to all of the Missouri Department of Conservation (MDC) Area Managers, biologists, and their staff for their willingness to support this research: B. Anderson, D. Bryant, J. Demand, B. Diekmann, C. Freeman, A. Pearson, C. Smith, and N. Walker. This work was funded through a cooperative agreement with the MDC in collaboration with L. Webb and K. Goyne. Partial support was also provided by the Missouri Cooperative Fish and Wildlife Research Unit and USDA-NIFA through Hatch funding (MO-HANR0007) and Multi-State Working Group W3045 (MOMSNR0002). The Missouri Cooperative Fish and Wildlife Research Unit is jointly sponsored by MDC, the University of Missouri, the U.S. Fish and Wildlife Service, the U.S. Geological Survey, and theWildlife Management Institute. Pesticide residue analysis was supported by the USGS Toxic Substances Hydrology Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Public domain – authored by a U.S. government employee

The response of mineral-stabilized soil organic carbon (SOC) to environmental change is a source of uncertainty in the understanding of SOC cycling. Fluctuating wet-dry cycles and associated redox changes in otherwise well-drained soils may drive mineral dissolution, organic carbon (OC) mobilization, and subsequent OC mineralization. However, the extent to which rapid fluctuations between water-saturated and unsaturated conditions (i.e., flashy conditions) result in long-term changes in mineral composition and organo-mineral interactions is not well understood. In this study, the effect of variable saturation frequency on soil mineral composition, mineral-associated OC, and OC mineralizability was tested using selective dissolution, bulk spectroscopy, microscale imaging, and aerobic-anaerobic incubation experiments. Previous water table fluctuation measurements and diagnostic profile characteristics at Hubbard Brook Experimental Forest (NH) were used to identify soils with high, medium, and low saturation frequency regimes (defined by historical water table cycling frequency; i.e., water table presence and recession in the upper B horizon). We found the amount of OC released during extractions targeting non-crystalline minerals was of similar magnitude as extracted iron (Fe) in lower saturation frequency soils. However, the magnitude of extracted OC was 2.5 times greater than Fe but more similar to extractable aluminum (Al) in higher saturation frequency soils. Bulk soil Fe was spatially more strongly correlated to soil organic matter (SOM) in lower saturation frequency soils (Spearman Rank r(s) = 0.62, p < 0.005), whereas strong correlations between Al and SOM were observed in higher saturation frequency soils (r(s) = 0.88, p < 0.005) using nanoscale secondary ion mass spectrometry (NanoSIMS) imaging. Characterization of bulk soil Fe with X-ray absorption spectroscopy showed 1.2-fold greater Fe(II) and 1-fold lower contribution of Fe-organic bonding in soils with high saturation frequency. Fe(III) interactions with carboxylic and aromatic C were identified with C-13 nuclear magnetic resonance (NMR) spectroscopy Fe(III) interference experiments. Additionally, carboxylic acid enrichment in high saturation frequency soils quantified by C K-edge X-ray absorption spectroscopy point towards the role of carboxylic functional groups in Al-organic in addition to Fe-organic interactions. In our incubation experiments, a doubling in short-term CO2 evolution (per unit total soil C) was detected for high relative to low saturation frequency soils. Further, an order of magnitude increase in CO2 evolution (per unit water-extractable OC) following anaerobic incubation was only detected in high saturation frequency soils. The observed shift towards Al-dominated SOC interactions and higher OC mineralizability highlights the need to describe C stabilization in soils with flashy wet-dry cycling separately from soils with low saturation frequency or persistent saturation. NSF IGERT in Cross-Scale Biogeochemistry and Climate at Cornell University (NSF)National Science Foundation (NSF) [1069193]; Institute for Advanced Study (IAS) from the Technical University of Munich (TUM); Andrew W. Mellon Foundation; Cornell College of Agriculture and Life Sciences Alumni Foundation, USA; National Science FoundationNational Science Foundation (NSF) [DMR-1332208]; Canada Foundation for InnovationCanada Foundation for InnovationCGIAR; Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of Canada (NSERC)CGIAR; University of Saskatchewan; Government of Saskatchewan; Western Economic Diversification Canada; National Research Council Canada; Canadian Institutes of Health Research, CanadaCanadian Institutes of Health Research (CIHR) Funding for this study was provided by the NSF IGERT in Cross-Scale Biogeochemistry and Climate at Cornell University (NSF Award #1069193) and the Institute for Advanced Study (IAS) from the Technical University of Munich (TUM) through the Hans-Fisher Senior Fellowship. Additional research funds were provided by the Andrew W. Mellon Foundation and the Cornell College of Agriculture and Life Sciences Alumni Foundation, USA. Hubbard Brook Experimental Forest is operated and maintained by the US Forest Service, Northern Research Station, Newtown Square, PA, USA. This work uses research conducted at the Cornell High Energy Synchrotron Source (CHESS) which is supported by the National Science Foundation under award DMR-1332208. Research was performed at the Canadian Light Source (CLS), which is supported by the Canada Foundation for Innovation, Natural Sciences and Engineering Research Council of Canada, the University of Saskatchewan, the Government of Saskatchewan, Western Economic Diversification Canada, the National Research Council Canada, and the Canadian Institutes of Health Research, Canada. The authors thank Dr. Rong Huang of CHESS, Dr. Tom Regier of CLS, Kelly Hanley and Akio Enders of Cornell University for technical assistance; Dr. Carmen Hoschen, Johann Lugmeier and Dr. Carsten Mueller of the Technical University of Munich for their support with the NanoSIMS measurements; Dr. Carmen Enid Martinez' research group for providing iron XAS standard materials; Dr. Linda Pardo, Stephanie Duston, Brittany LeBeau, and Johali Sotelo for soil sample collection and field characterization; and the referees for their invaluable insights. Public domain – authored by a U.S. government employee

Globally, prescribed fire, harvesting, and understory mastication, alone and in combination, are common forest management practices. Timber commodities, wildlife habitat, wildfire fuel reduction, soil conservation, and water quality are frequently targeted and assessed as these practices are utilized. In the 1960s, a study of paired, first-order watersheds was established in coastal South Carolina, USA, to evaluate the long-term impacts of forest management (i.e. prescribed fire, thinning, mastication of understory vegetation) on water quantity and quality. Following Hurricane Hugo in 1989, this included salvage logging on one watershed, but not the other. In 2015, these watersheds were comprehensively evaluated to determine differences in forest species composition, fuels, and soil chemistry. Softwood basal area was greater in the managed watershed than in the unmanaged watershed and hardwood basal area was greater in the unmanaged watershed than in the managed watershed. Total fuel mass did not differ between the two watersheds, but 1-hr and 1000-hr rotten fuel mass were greater on the unmanaged watershed. Ten-hr fuel mass was greater on the managed watershed. Calcium, nitrogen, magnesium, phosphorus, potassium, and pH differed between the litter (Oi horizon) and duff (Oe + Oa horizons) of both watersheds, but carbon only differed in the duff. Mineral soil (Ultisols, 0-10 and 10-20 cm depths) calcium and phosphorus differed between the watersheds, but pH and the other chemicals did not. Collectively, these results indicated that: (1) forest management and natural disturbance on these watersheds altered long-term forest structure; (2) different species compositions and the inclusion or exclusion of salvage logging after Hurricane Hugo produced different fuel compositions that may potentially impact potential wildfire hazard and fire behavior; (3) organisms as a primary soil-forming factor were impacted by long-term management, therefore, some soil chemical properties were affected. Collectively, these analyses highlighted the broad, long-term impacts to ecosystem properties and processes that might directly and indirectly result from active forest management and natural disturbance and the scale of site-specific assessment that might be considered when landowner objectives are targeted in forest management plans and practices. Public domain – authored by a U.S. government employee

Thousands of trees are lost in urbanizing areas of Virginia each year to land development, storms, and pests. As a result, large amounts of tree debris, much of which could be suitable for high-value wood products, are flowing from Virginia&rsquo, s urban forests annually. Finding cost-effective, sustainable strategies for recycling this debris, particularly into durable wood products that keep carbon stored, could benefit the local economy and the local environment throughout the state. To inform outreach and technical assistance efforts of multiple groups across the state, a survey study was conducted in the City of Harrisonburg to determine household perceptions and practices of tree debris recycling. A random sample of owner-occupied, single-family dwellings was contacted using a mixed-mode survey approach to determine why and how trees were removed from the properties in the past and how the debris was disposed of or recycled. Survey responses were received from 189 households, with survey responses pointing toward a strong community sentiment for trees and their care. Nearly all respondents agreed that wood from street trees, park trees, and other neighborhood trees should be recycled into products rather than disposed of in a landfill, however, the majority of households do not currently recycle woody debris from trees removed on these properties. The three most important factors that would facilitate future participation in tree recycling include timely removal of the wood, free curbside pick-up of the wood, and knowledge of who to contact to handle the wood. Overall, these results point to household interest and willingness to participate in wood recycling programs given appropriate information to guide their decisions and local services to facilitate transfer of wood to the municipality or commercial woodworkers. This suggests a need for greater availability of neighborhood or municipal wood recycling programs, ideally coupled with greater education and outreach about the economic and environmental benefits of recovering and utilizing wood from felled trees.

The concentration of oxygen is fundamental to lake water quality and ecosystem functioning through its control over habitat availability for organisms, redox reactions, and recycling of organic material. In many eutrophic lakes, oxygen depletion in the bottom layer (hypolimnion) occurs annually during summer stratification. The temporal and spatial extent of summer hypolimnetic anoxia is determined by interactions between the lake and its external drivers (e.g., catchment characteristics, nutrient loads, meteorology) as well as internal feedback mechanisms (e.g., organic matter recycling, phytoplankton blooms). How these drivers interact to control the evolution of lake anoxia over decadal timescales will determine, in part, the future lake water quality. In this study, we used a vertical one-dimensional hydrodynamic-ecological model (GLM-AED2) coupled with a calibrated hydrological catchment model (PIHM-Lake) to simulate the thermal and water quality dynamics of the eutrophic Lake Mendota (USA) over a 37 year period. The calibration and validation of the lake model consisted of a global sensitivity evaluation as well as the application of an optimization algorithm to improve the fit between observed and simulated data. We calculated stability indices (Schmidt stability, Birgean work, stored internal heat), identified spring mixing and summer stratification periods, and quantified the energy required for stratification and mixing. To qualify which external and internal factors were most important in driving the interannual variation in summer anoxia, we applied a random-forest classifier and multiple linear regressions to modeled ecosystem variables (e.g., stratification onset and offset, ice duration, gross primary production). Lake Mendota exhibited prolonged hypolimnetic anoxia each summer, lasting between 50-60 d. The summer heat budget, the timing of thermal stratification, and the gross primary production in the epilimnion prior to summer stratification were the most important predictors of the spatial and temporal extent of summer anoxia periods in Lake Mendota. Interannual variability in anoxia was largely driven by physical factors: earlier onset of thermal stratification in combination with a higher vertical stability strongly affected the duration and spatial extent of summer anoxia. A measured step change upward in summer anoxia in 2010 was unexplained by the GLM-AED2 model. Although the cause remains unknown, possible factors include invasion by the predacious zooplankton Bythotrephes longimanus. As the heat budget depended primarily on external meteorological conditions, the spatial and temporal extent of summer anoxia in Lake Mendota is likely to increase in the near future as a result of projected climate change in the region. NSF ABI development grant [DBI 1759865]; NSF CNH grant [1517823]; NSFNational Science Foundation (NSF) [DEB 1753639, DEB 1753657] The project was funded through an NSF ABI development grant (#DBI 1759865), an NSF CNH grant (#1517823), as well as NSF grants DEB 1753639 and DEB 1753657.

Forest tree species are increasingly subject to severe mortalities from exotic pests, pathogens, and invasive organisms, accelerated by climate change. Such forest health issues are threatening multiple species and ecosystem sustainability globally. One of the most extreme examples of forest ecosystem disruption is the extirpation of the American chestnut (Castanea dentata) caused by the introduction of chestnut blight and root rot pathogens from Asia. Asian species of chestnut are being employed as donors of disease resistance genes to restore native chestnut species in North America and Europe. To aid in the restoration of threatened chestnut species, we present the assembly of a reference genome for Chinese chestnut (C. mollissima) "Vanuxem," one of the donors of disease resistance for American chestnut restoration. From the de novo assembly of the complete genome (725.2 Mb in 14,110 contigs), over half of the sequences have been anchored to the 12 genetic linkage groups. The anchoring is validated by genetic maps and in situ hybridization to chromosomes. We demonstrate the value of the genome as a platform for research and species restoration, including signatures of selection differentiating American chestnut from Chinese chestnut to identify important candidate genes for disease resistance, comparisons of genome organization with other woody species, and a genome-wide examination of progress in backcross breeding for blight resistance. This reference assembly should prove of great value in the understanding, improvement, and restoration of chestnut species. Forest Health Initiative [137RFP, 2008-011]; United States Department of Agriculture (USDA) National Institute of Food and AgricultureUnited States Department of Agriculture (USDA) [2016-67013-24581]; USDA National Institute of Food and Agriculture Federal Appropriations [PEN04532, 1000326, NE-1833]; Foundation for the Carolinas; National Science Foundation (NSF)National Science Foundation (NSF) [1444573]; NSF Postdoctoral Research Fellowships in Biology Grant [1711950]; Institutional Development Award (IDeA) from the National Institute of GeneralMedical Sciences of the National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [P20GM109094]; American Chestnut Foundation This project was funded by the Forest Health Initiative (https://foresthealthinitiative.org/) through grant #137RFP#2008-011 to JEC. Support was also provided by the United States Department of Agriculture (USDA) National Institute of Food and Agriculture grant 2016-67013-24581 to The American Chestnut Foundation. Additional support was provided through several grants-inaid to JEC fromThe American Chestnut Foundation and to JEC andMES through the USDA National Institute of Food and Agriculture Federal Appropriations under Project PEN04532 (Accession number 1000326) and NE-1833, respectively. Construction of saturated genetic maps and root RNAseq dataset was partially supported by the Foundation for the Carolinas. Bioinformatics was supported by National Science Foundation (NSF) Award #1444573, "Standards and Cyberinfrastructure that Enable 'Big-Data' Driven Discovery for Tree Crop Research" (MES; PI Main). Emily Bellis was supported by NSF Postdoctoral Research Fellowships in Biology Grant No. 1711950. Rooksana Noorai was supported by an Institutional Development Award (IDeA) from the National Institute of GeneralMedical Sciences of the National Institutes of Health under grant number P20GM109094. Public domain – authored by a U.S. government employee

From 2001&ndash, 2018, a series of fuel reduction and ecosystem restoration treatments were implemented in the southern Appalachian Mountains near Asheville, North Carolina, USA. Treatments consisted of prescribed fire (four burns), mechanical cutting of understory shrubs and mid-story trees (two cuttings), and a combination of both cutting and prescribed fire (two cuts + four burns). Soils were sampled in 2018 to determine potential treatment impacts for O horizon and mineral soil (0&ndash, 10 cm depth) carbon (C) and nitrogen (N) and mineral soil calcium (Ca), magnesium (Mg), phosphorus (P), potassium (K), and pH. Results suggested that mean changes in O horizon C and N and mineral soil C, N, C:N, Ca, and P from 2001&ndash, 2018 differed between the treatments, but only mineral soil C, N, C:N and Ca displayed differences between at least one fuel reduction treatment and the untreated control. One soils-related restoration objective was mineral soil N reduction and the cut + burn treatment best achieved this result. Increased organic matter recalcitrance was another priority, but this was not obtained with any treatment. When paired with previously reported fuels and vegetation results from this site, it appeared that continued use of the cut + burn treatment may best achieve long-term management objectives for this site and other locations being managed for similar long-term restoration and fuels management objectives.

Mechanical mastication is a fuels treatment that shreds midstorey trees and shrubs into a compacted woody fuel layer to abate fire hazards in fire-prone ecosystems. Increased surface fuel loading from mastication may, however, lead to undesirable fire intensity, long-duration flaming or smouldering, and undesirable residual tree mortality. Two major questions facing fuels managers are: how long do masticated fuels persist, and how does the composition of masticated fuelbeds change over time? To evaluate these changes, we measured 25 masticated sites with a range of vegetation, species masticated and time since treatment (1-16 years) in the western US. Seven of the 25 sites were sampled nearly a decade earlier, providing a unique opportunity to document fuelbed changes. Woody fuel loading ranged from 12.1 to 91.9 Mg ha(-1) across sites and was negatively related to time since treatment. At remeasured sites, woody fuel loads declined by 20%, with the greatest losses in 1- and 10-h woody fuels (69 and 33% reductions in mass respectively). Reductions were due to declines in number of particles and reduced specific gravity. Mastication treatments that generate greater proportions of smaller-diameter fuels may result in faster decomposition and potentially be more effective at mitigating fire hazard. USDAUnited States Department of Agriculture (USDA) [12-1-03-31]; USDI [12-1-03-31] An earlier draft of the manuscript benefitted from feedback provided by C. Copenheaver. We are grateful for the helpful comments from the three anonymous reviewers that helped improve this manuscript. This research was supported in part by funds provided by the USDA and the USDI Joint Fire Science Program (Project 12-1-03-31). Assistance with field data collection was provided by G. Hamby, C. Keller and J. Tobia. We appreciate the cooperation of the Sierra, Stanislaus, Tahoe, Lake Tahoe Basin Management Unit, Shasta-Trinity and Klamath National Forests as well as the Medford Bureau of Land Management office for assistance with selecting study sites and providing information about how treatments were implemented. J. Kane provided logistical support and numerous conversations through project development from which this study benefited. Public domain – authored by a U.S. government employee

Neonicotinoid pesticides can persist in soils for extended time periods; however, they also have a high potential to contaminate ground and surface waters. Studies have reported negative effects associated with neonicotinoids and nontarget taxa, including aquatic invertebrates, pollinating insect species, and insectivorous birds. This study evaluated factors associated with clothianidin (CTN) degradation and sorption in Missouri wetland soils to assess the potential for wetland soils to mitigate potential environmental risks associated with neonicotinoids. Solid-to-solution partition coefficients (K-d) for CTN sorption to eight wetland soils were determined via single-point sorption experiments, and sorption isotherm experiments were conducted using the two most contrasting soils. Clothianidin degradation was determined under oxic and anoxic conditions over 60 d. Degradation data were fit to zero- and first-order kinetic decay models to determine CTN half-life (t(0.5)). Sorption results indicated CTN sorption to wetland soil was relatively weak (average K-d, 3.58 L kg(-1)); thus, CTN has the potential to be mobile and bioavailable within wetland soils. However, incubation results showed anoxic conditions significantly increased CTN degradation rates in wetland soils (anoxic average t(0.5), 27.2 d; oxic average t(0.5), 149.1 d). A significant negative correlation was observed between anoxic half-life values and soil organic C content (r(2) = .782; p = .046). Greater CTN degradation rates in wetland soils under anoxic conditions suggest that managing wetlands to facilitate anoxic conditions could mitigate CTN presence in the environment and reduce exposure to nontarget organisms. Missouri Department of Conservation; USDA-NIFAUnited States Department of Agriculture (USDA) [MO-HANR0007]; Multi-State Working Group [W3045 (MO-MSNR0002)]; MDC; University of Missouri; U.S. Fish and Wildlife ServiceUS Fish & Wildlife Service; USGSUnited States Geological Survey; Wildlife Management Institute Funding for this research was provided through a cooperative agreement with the Missouri Department of Conservation. Partial support was also provided by USDA-NIFA through Hatch funding (MO-HANR0007) and Multi-State Working Group W3045 (MO-MSNR0002). The authors thank the following individuals for their contributions: Craig Scroggins of MDC; Elizabeth Spiegel, Edward Winchester, and Kathleen Hatch from the USDA-ARS; and Elizabeth Tustison, Laura Satkowski, Rachel Owen, and Anson Main of the University of Missouri. The Missouri Cooperative Fish and Wildlife Research Unit is jointly sponsored by MDC, the University of Missouri, the U.S. Fish and Wildlife Service, the USGS and the Wildlife Management Institute. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Public domain – authored by a U.S. government employee

Leaf area index (LAI) is an important biophysical indicator of forest health that is linearly related to productivity, serving as a key criterion for potential nutrient management. A single equation was produced to model surface reflectance values captured from the Sentinel-2 Multispectral Instrument (MSI) with a robust dataset of field observations of loblolly pine (Pinus taeda L.) LAI collected with a LAI-2200C plant canopy analyzer. Support vector machine (SVM)-supervised classification was used to improve the model fit by removing plots saturated with aberrant radiometric signatures that would not be captured in the association between Sentinel-2 and LAI-2200C. The resulting equation, LAI = 0.310SR − 0.098 (where SR = the simple ratio between near-infrared (NIR) and red bands), displayed good performance ( R 2 = 0.81, RMSE = 0.36) at estimating the LAI for loblolly pine within the analyzed region at a 10 m spatial resolution. Our model incorporated a high number of validation plots (n = 292) spanning from southern Virginia to northern Florida across a range of soil textures (sandy to clayey), drainage classes (well drained to very poorly drained), and site characteristics common to pine forest plantations in the southeastern United States. The training dataset included plot-level treatment metrics—silviculture intensity, genetics, and density—on which sensitivity analysis was performed to inform model fit behavior. Plot density, particularly when there were ≤618 trees per hectare, was shown to impact model performance, causing LAI estimates to be overpredicted (to a maximum of X i + 0.16). Silviculture intensity (competition control and fertilization rates) and genetics did not markedly impact the relationship between SR and LAI. Results indicate that Sentinel-2’s improved spatial resolution and temporal revisit interval provide new opportunities for managers to detect within-stand variance and improve accuracy for LAI estimation over current industry standard models. Published version

Interception is the storage and subsequent evaporation of rainfall by above-ground structures, including canopy and groundcover vegetation and surface litter. Accurately quantifying interception is critical for understanding how ecosystems partition incoming precipitation, but it is difficult and costly to measure, leading most studies to rely on modeled interception estimates. Moreover, forest interception estimates typically focus only on canopy storage, despite the potential for substantial interception by groundcover vegetation and surface litter. In this study, we developed an approach to quantify “total” interception (i.e., including forest canopy, understory, and surface litter layers) using measurements of shallow soil moisture dynamics during rainfall events. Across 34 pine and mixed forest stands in Florida (USA), we used soil moisture and precipitation (P) data to estimate interception storage capacity (βs), a parameter required to estimate total annual interception (Ia) relative to P. Estimated values for βs(mean βs=0.30 cm; 0.01≤βs≤0.62 cm) and Ia∕P (mean Ia/P=0.14; 0.06≤Ia/P≤0.21) were broadly consistent with reported literature values for these ecosystems and were significantly predicted by forest structural attributes (leaf area index and percent ground cover) as well as other site variables (e.g., water table depth). The best-fit model was dominated by LAI and explained nearly 80 % of observed βs variation. These results suggest that whole-forest interception can be estimated using near-surface soil moisture time series, though additional direct comparisons would further support this assertion. Additionally, variability in interception across a single forest type underscores the need for expanded empirical measurement. Potential cost savings and logistical advantages of this proposed method relative to conventional, labor-intensive interception measurements may improve empirical estimation of this critical water budget element.

Eastern deciduous forests in the United States have supplied marketable non-timber forest products (NTFP) since the 18th century. However, trade is still largely informal, and the market scope and structure are not well understood. One exception is American ginseng (Panax quinquefolius L.). Ginseng’s legal status as a threatened species requires that buyers apply for a license and keep sales records that are submitted to a state authority. Other marketable medicinal plants collected from the same forests, known colloquially as ‘off-roots’, are not similarly tracked. To study the characteristics of off-root trade in the eastern deciduous forests of the United States, registered ginseng buyers in 15 eastern states were surveyed in 2015 and 2016 about business attributes, purchase volume, and harvest distribution for 15 off-root species selected for their economic and conservation value. Buyers voluntarily reported harvesting 47 additional NTFP species. The most frequently purchased off-root species were the roots and rhizomes of two perennial understory plants: black cohosh (Actaea racemosa L.) and goldenseal (Hydrastis canadensis L.). Survey data were used to develop a buyer typology and describe the off-root market structure and material sourcing. The buyer typology included four distinct categories: side or specialty (small), seasonal venture (medium), large integrated or dedicated business (large), and dedicated bulk enterprise (regional aggregator). Market activity was mapped across the study area, demonstrating that most off-root trade is concentrated in central Appalachia, an area with extensive forests and a struggling economy. Study methods and data improve non-timber forest product market insights, are useful for forest management, and can support efforts to advance sustainable NTFP supply chains.

Forest ecosystem services such as clean water, wildlife habitat, and timber supplies are increasingly threatened by drought and disturbances (e.g., harvesting, fires and conversion to other uses), which can have great impacts on stand development and water balance. Improved understanding of the hydrologic response of forested systems to drought and disturbance at spatiotemporal resolutions commensurate with these impacts is important for effective forest management. Evapotranspiration (ET) is a key hydrologic variable in assessing forest functioning and health, but it remains a challenge to accurately quantify ET at landscape scales with the spatial and temporal detail required for effective decision-making. In this study, we apply a multi-sensor satellite data fusion approach to study the response of forest ET to drought and disturbance over a 7-year period. This approach combines Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) ET product time series retrieved using a surface energy balance model to generate a multi-year ET datacube at 30-m resolution and daily timesteps. The study area (similar to 900 km(2)) contains natural and managed forest as well as croplands in the humid lower coastal plains in North Carolina, USA, and the simulation period from 2006 to 2012 includes both normal and severe drought conditions. The model results were evaluated at two AmeriFlux sites (US-NC2 and US-NC1) dominated by a mature and a recently clearcut pine plantation, respectively, and showed good agreement with observed fluxes, with 813% relative errors at monthly timesteps. Changes in water use patterns in response to drought and disturbance as well as forest stand aging were assessed using the remotely sensed time series describing total evapotranspiration, the transpiration (T) component of ET, and a moisture stress metric given by the actual-to-reference ET ratio (f(RET)). Analyses demonstrate differential response to drought by land cover type and stand age, with larger impacts on total ET observed in young pine stands than in mature stands which have substantially deeper rooting systems. Transpiration flux shows a clear ascending trend with the growth of young pine plantations, while stand thinning within the plantation leads to decreases in both remotely sensed leaf area index and T, as expected. Time series maps of f(RET) anomalies at 30-m resolution capture signals of drought, disturbance and the subsequent recovery after clearcut at the stand scale and may be an effective indicator for water use change detection and monitoring in forested landscapes. National Aeronautics and Space AdministrationNational Aeronautics & Space Administration (NASA) [NNH14AX36I] This work was funded in part by a grant from National Aeronautics and Space Administration (NNH14AX36I). We thank the Weyerhaeuser Company for providing stand age data. The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on the basis of race, color, national origin, age, disability, and where applicable, sex, marital status, familial status, parental status, religion, sexual orientation, genetic information, political beliefs, reprisal, or because all or part of an individual's income is derived from any public assistance program. (Not all prohibited bases apply to all programs.) Persons with disabilities who require alternative means for communication of program information (Braille, large print, audiotape, etc.) should contact USDA's TARGET Center at (202) 720-2600 (voice and TDD). To file a complaint of discrimination, write to USDA, Director, Office of Civil Rights, 1400 Independence Avenue, S.W., Washington, D.C. 20250-9410, or call (800) 795-3272 (voice) or (202) 720-6382 (TDD). USDA is an equal opportunity provider and employer.

Water and land resource management planning benefits greatly from accurate prediction and understanding of the spatial distribution of wetness. The topographic wetness index (TWI) was conceived to predict relative surface wetness, and thus hydrologic responsiveness, across a watershed based on the assumption that shallow slope-parallel flow is a major driver of the movement and distribution of soil water. The index has been extensively used in modeling of landscape characteristics responsive to wetness, and some studies have shown the TWI performs well in landscapes where interflow is a dominant process. However, groundwater flow dominates the hydrology of low-slope landscapes with high subsurface conductivities, and the TWI assumptions are not likely to perform well in such environments. For groundwater dominated systems, we propose a hybrid wetness index (Wetness Index based on Landscape position and Topography, WILT) that inversely weights the upslope contributing area by the distance to the nearest surface water feature and the depth to groundwater. When explicit depth to groundwater data are not available, height above and separation from surface water features can act as surrogates for proximity to groundwater. The resulting WILT map provides a more realistic spatial distribution of relative wetness across a low-slope Coastal Plain landscape as demonstrated by improved prediction of hydric soils, depth to groundwater, nitrogen and carbon concentrations in the A horizon of the soil profile, and sensitivity to DEM scale. Department of Energy-Bioenergy Technologies Office and Savannah River Operations Office through the U.S. Forest Service Savannah River under Interagency Agreement [DE-AI09-00SR22188] This research was implemented as part of large-scale collaborative investigation of dominant hydrologic processes within small watersheds of the Sandhills of South Carolina within the Savannah River Site (SRS). SRS is a National Environmental Research Park. Support was provided by the Department of Energy-Bioenergy Technologies Office and Savannah River Operations Office through the U.S. Forest Service Savannah River under Interagency Agreement DE-AI09-00SR22188. Public domain – authored by a U.S. government employee

Freshwater ecosystems are experiencing greater variability due to human activities, necessitating new tools to anticipate future water quality. In response, we developed and deployed a real-time iterative water temperature forecasting system (FLARE-Forecasting Lake And Reservoir Ecosystems). FLARE is composed of water temperature and meteorology sensors that wirelessly stream data, a data assimilation algorithm that uses sensor observations to update predictions from a hydrodynamic model and calibrate model parameters, and an ensemble-based forecasting algorithm to generate forecasts that include uncertainty. Importantly, FLARE quantifies the contribution of different sources of uncertainty (driver data, initial conditions, model process, and parameters) to each daily forecast of water temperature at multiple depths. We applied FLARE to Falling Creek Reservoir (Vinton, Virginia, USA), a drinking water supply, during a 475-day period encompassing stratified and mixed thermal conditions. Aggregated across this period, root mean square error (RMSE) of daily forecasted water temperatures was 1.13 degrees C at the reservoir's near-surface (1.0 m) for 7-day ahead forecasts and 1.62 degrees C for 16-day ahead forecasts. The RMSE of forecasted water temperatures at the near-sediments (8.0 m) was 0.87 degrees C for 7-day forecasts and 1.20 degrees C for 16-day forecasts. FLARE successfully predicted the onset of fall turnover 4-14 days in advance in two sequential years. Uncertainty partitioning identified meteorology driver data as the dominant source of uncertainty in forecasts for most depths and thermal conditions, except for the near-sediments in summer, when model process uncertainty dominated. Overall, FLARE provides an open-source system for lake and reservoir water quality forecasting to improve real-time management. U.S. National Science FoundationNational Science Foundation (NSF) [CNS-1737424, DEB-1753639, DBI-1933016, DEB-1926050, DEB-1926388]; Virginia Tech Global Change Center; Fralin Life Sciences Institute This work was supported by the U.S. National Science Foundation (CNS-1737424, DEB-1753639, DBI-1933016, DEB-1926050, and DEB-1926388); the Virginia Tech Global Change Center; and Fralin Life Sciences Institute. We thank our Ecological Forecasting seminar students, the Smart Reservoir team, and Ecological Forecasting Initiative (EFI) colleagues for helpful feedback on the project; the Western Virginia Water Authority for their long-term support and access to field sites; and Mary Lofton, Ryan McClure, and Whitney Woelmer for their critical help in the field.

The volume, value and distribution of the nontimber forest product (NTFP) trade in the United States are largely unknown. This is due to the lack of systematic, periodic and comprehensive market tracking programs. Trade measurement and mapping would allow market actors and stakeholders to improve market conditions, manage NTFP resources, and increase the sustainable production of raw material. This is especially true in the heavily forested and mountainous regions of the eastern United States. This study hypothesized that the tendency to purchase medicinal NTFPs in this region can be predicted using socioeconomic and environmental variables associated with habitat and trade, and those same variables can be used to build more robust estimates of trade volume. American ginseng (Panax quinquefolius L.) dealers were surveyed (n = 700), because by law they must acquire a license to legally trade in this species, and therefore report a business address. They also record purchase data. Similar data are not reported for other medicinal species sold to the same buyers, known colloquially as &lsquo, off-roots&rsquo, Ginseng buyers were queried about trade activity in eleven commonly-harvested and previously untracked medicinal NTFP species in 15 states. Multinomial logistic regression comprised of socioeconomic and environmental predictors tied to business location was used to determine the probability that a respondent purchased off-roots. Significant predictors included location in a particular subregion, population and percentage of employment in related industries. These variables were used in a two-step cluster analysis to group respondents and nonrespondents. Modeled probabilities for off-root purchasing among respondents in each cluster were used to impute average off-root volumes for a proportion of nonrespondents in the same cluster. Respondent observations and nonrespondent estimations were summed and used to map off-root trade volume and value. Model functionality and estimates of the total volume, value and spatial distribution are discussed. The total value of the species surveyed to harvesters was 4.3 million USD. We also find that 77 percent of the trade value and 73 percent of the trade volume were represented by two species: black cohosh (Actaea racemosa L.) and goldenseal (Hydrastis canqdensis L.)

Forest ecosystems provide important ecological services and resources, from habitat for biodiversity to the production of environmentally friendly products, and play a key role in the global carbon cycle. Humanity is counting on forests to sequester and store a substantial portion of the anthropogenic carbon dioxide produced globally. However, the unprecedented rate of climate change, deforestation, and accidental importation of invasive insects and diseases are threatening the health and productivity of forests, and their capacity to provide these services. Knowledge of genetic diversity, local adaptation, and genetic control of key traits is required to predict the adaptive capacity of tree populations, inform forest management and conservation decisions, and improve breeding for productive trees that will withstand the challenges of the 21st century. Genomic approaches have well accelerated the generation of knowledge of the genetic and evolutionary underpinnings of nonmodel tree species, and advanced their applications to address these challenges. This special issue of Evolutionary Applications features 14 papers that demonstrate the value of a wide range of genomic approaches that can be used to better understand the biology of forest trees, including species that are widespread and managed for timber production, and others that are threatened or endangered, or serve important ecological roles. We highlight some of the major advances, ranging from understanding the evolution of genomes since the period when gymnosperms separated from angiosperms 300 million years ago to using genomic selection to accelerate breeding for tree health and productivity. We also discuss some of the challenges and future directions for applying genomic tools to address long‐standing questions about forest trees.

Aerodynamic canopy height (h(a)) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate h(a) from data are limited. This synthesis evaluates the applicability and robustness of the calculation of h(a) from eddy covariance momentum-flux data. At 69 forest sites, annual h(a) robustly predicted site-to-site and year-to-year differences in canopy heights (R-2=0.88, 111site-years). At 23 cropland/grassland sites, weekly h(a) successfully captured the dynamics of vegetation canopies over growing seasons (R-2>0.70 in 74site-years). Our results demonstrate the potential of flux-derived h(a) determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying h(a) derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. Plain Language Summary Vegetation canopy height is a key descriptor of the Earth surface and is in use by many modeling and conservation applications. However, large-scale and time-varying data of canopy heights are often unavailable. This synthesis evaluates the applicability and robustness of the calculation of canopy heights from the momentum flux data measured at eddy covariance flux tower sites (i.e., meteorological observation towers with high frequency measurements of wind speed and surface fluxes). We show that the aerodynamic estimation of annual canopy heights robustly predicts the site-to-site and year-to-year differences in canopy heights across a wide variety of forests. The weekly aerodynamic canopy heights successfully capture the dynamics of vegetation canopies over growing seasons at cropland and grassland sites. Our results demonstrate the potential of aerodynamic canopy heights for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. Given the amount of data collected and the diversity of vegetation covered by the global networks of eddy covariance flux tower sites, the flux-derived canopy height has great potential for providing a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. U.S. Department of Energy's Office of ScienceUnited States Department of Energy (DOE) [DE-SC0012456, DE-AC02-05CH11231] This study is supported by FLUXNET and AmeriFlux projects, sponsored by U.S. Department of Energy's Office of Science (DE-SC0012456 and DE-AC02-05CH11231). We thank the supports from AmeriFlux Data Team: Gilberto Pastorello, Deb Agarwal, Danielle Christianson, You-Wei Cheah, Norman Beekwilder, Tom Boden, Bai Yang, and Dario Papale, and Berkeley Biomet Lab: Siyan Ma, Joseph Verfaillie, Elke Eichelmann, and Sara Knox. This work uses eddy covariance and BADM data acquired and shared by the investigators involved in the AmeriFlux and Fluxnet-Canada Research Network. The site list and corresponding references are provided in the supporting information. We thank Claudia Wagner-Riddle, Andy Suyker, David Cook, Asko Noormets, Paul Stoy, and Brian Amiro for providing additional data. All actual canopy height data can be downloaded from AmeriFlux BADM. The R codes and aerodynamic canopy height data can be accessed at http://github.com/chuhousen/aerodynamic_canopy_height. Public domain – authored by a U.S. government employee

Agricultural land use is typically associated with high stream nutrient concentrations and increased nutrient loading to lakes. For lakes, evidence for these associations mostly comes from studies on individual lakes or watersheds that relate concentrations of nitrogen (N) or phosphorus (P) to aggregate measures of agricultural land use, such as the proportion of land used for agriculture in a lake's watershed. However, at macroscales (i.e., in hundreds to thousands of lakes across large spatial extents), there is high variability around such relationships and it is unclear whether considering more granular (or detailed) agricultural data, such as fertilizer application, planting of specific crops, or the extent of near-stream cropping, would improve prediction and inform understanding of lake nutrient drivers. Furthermore, it is unclear whether lake N and P would have different relationships to such measures and whether these relationships would vary by region, since regional variation has been observed in prior studies using aggregate measures of agriculture. To address these knowledge gaps, we examined relationships between granular measures of agricultural activity and lake total phosphorus (TP) and total nitrogen (TN) concentrations in 928 lakes and their watersheds in the Northeastern and Midwest U.S. using a Bayesian hierarchical modeling approach. We found that both lake TN and TP concentrations were related to these measures of agriculture, especially near-stream agriculture. The relationships between measures of agriculture and lake TN concentrations were more regionally variable than those for TP. Conversely, TP concentrations were more strongly related to lake-specific measures like depth and watershed hydrology relative to TN. Our finding that lake TN and TP concentrations have different relationships with granular measures of agricultural activity has implications for the design of effective and efficient policy approaches to maintain and improve water quality. U.S. National Science Foundation's Dynamics of Coupled Natural and Human Systems (CNH) Program [1517823]; U.S. National Science Foundation's Macrosystems Biology Program [EF-1638679, EF-1638554, EF-1638539, EF-1638550]; USDA National Institute of Food and Agriculture, Hatch project [1013544]; Hatch Appropriations [PEN04571, 1003346] This work was supported by the U.S. National Science Foundation's Dynamics of Coupled Natural and Human Systems (CNH) Program (award 1517823) and Macrosystems Biology Program (awards EF-1638679, EF-1638554, EF-1638539, and EF-1638550). PAS was also supported by the USDA National Institute of Food and Agriculture, Hatch project 1013544. ARK supported by Hatch Appropriations under Project #PEN04571 and Accession #1003346. We thank Sarah Collins for early input on the design and motivation for this study. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Author contributions: J. Stachelek conceived of the study, built models, analyzed data, and wrote the paper. C. C. Carey, A. R. Kemanian, and P. A. Soranno contributed to the conception of the manuscript and edited the paper. W. Weng, K. M. Cobourn, T. Wagner, K. C. Weathers, and P. A. Soranno provided interpretation of results and edited the paper. Public domain – authored by a U.S. government employee

In-stream watershed level evaluations confirm that application of recommended forestry best management practices (BMPs) can minimize sedimentation following management, while on-site erosion research shows that BMPs reduce erosion from individual forest operations, thus implying watershed-level sediment reductions. Assessments of forest operations and sediment have developed very few sediment delivery ratios (SDR). Linking BMP levels (low, standard recommendation, high) within specific forest operations to sedimentation could enable managers to evaluate BMP effects. Reported data regarding forest operations, erosion rates and SDR by forest operation, and BMP implementation levels were sufficient within the Piedmont region to allow approximations of sediment delivery and BMP efficiency. Existing United States Department of Agriculture (USDA) Forest Service reports and published erosion and sediment research were used to comprise the following method. For regional annual harvests, estimated sediment deliveries (Mg year&minus, 1) = annual harvest area (ha year&minus, 1) &times, weighted average erosion rate from all forest operations (Mg ha&minus, 1 year&minus, SDR (unitless ratio). Weighted average erosion rates for all forest operations were determined by applying areas in each operational activity (%) &times, estimated erosion per operation (Mg ha&minus, 1). In comparing published data, standard BMPs reduced estimated sedimentation by 75% compared to low BMP implementation levels. This supports forestry BMP efficiency findings reported for sediment removals in watershed studies. Higher levels of BMP implementation were estimated to potentially remove nearly all forest operation-produced sediment. Values of this pilot study should be viewed cautiously, as estimates were based on limited data, estimated operations, and limited SDRs, are based on BMP categories that vary between states, and address only one year following harvests. However, the approach provided approximations that facilitate BMP evaluations and can be improved with additional data. This methodology highlights the importance of accurate estimates of erosion rates, SDRs, sediment masses, and area for operations. This supports the importance of state programs, which have increased BMP implementation rates and compliance options with BMP program maturation.

Emerging evidence shows that interactions between soils and subsurface flow paths contribute to spatial variations in stream water chemistry in headwater catchments. However, few have yet attempted to quantify chemical variations in soils at catchment and hillslope scales. Watershed 3 (WS3) at Hubbard Brook Experimental Forest, New Hampshire, USA, was studied in order to better understand pedogenesis and its relationship to subsurface water dynamics. In WS3, 99 soil profiles were described, sampled by horizon, and assigned to a hydropedologic unit (HPU), a functional classification previously developed using landscape and morphological metrics which corresponded with distinct water table regimes. Soil samples were extracted with 1) citrate-dithionite (d) and analyzed for Fe-d and Mn-d; and 2) acid ammonium oxalate (o) and analyzed for Al-o, Fe-o and the rare earth elements La-o, Ce-o, and Pr-o. Total organic C was also measured. These elements were redistributed via vertical and lateral podzolization. Typical (horizontally layered) podzols developed in the majority of the catchment due to predominantly vertical, unsaturated flow. However, lateral flow produced four other podzol types with distinct chemistry; thicker spodic horizons of laterally accumulating soils generally reflected larger pools of trace metals and subsoil organic C. The spatial distribution of positive cerium-anomalies (Ce/Ce*) in soil profiles proved to be a consistent hydropedologic indicator of lateral flow and seasonally high water table in three hillslopes. Despite occasional high water table in some of the HPUs, they were not hydric soils and were distinct from wetter podzols of coastal plains due to their high Fe content. This study suggests that vertical and lateral spatial variation in soil chemical composition, including the complexity of Ce distribution, as it relates to subsurface water dynamics should be considered when studying or predicting catchment scale functions such as stream solute export and biogeochemical processes. NSF Hydrologic SciencesNational Science Foundation (NSF)NSF - Directorate for Geosciences (GEO) [EAR 1014507]; LTER [DEB 1114804] The authors wish to thank the following people for assistance in the field and laboratory: Noah Ahles, Andrea Brendalen, Margaret Burns, Silene DeCiucies, Cody Gillin, Ethan Morehouse, Emily Fiche, Geoff Schwaner, and Margaret Zimmer. Thanks also to dissertation committee members Greg Druschel, Josef Gorres, and Jeff Hughes for ideas and insight. Funding was provided by NSF Hydrologic Sciences (EAR 1014507) and LTER (DEB 1114804) programs. Hubbard Brook Experimental Forest is operated and maintained by the US Forest Service, Northern Research Station, Newtown Square, PA. Public domain – authored by a U.S. government employee

Harvesting traffic may alter soil properties and reduce forest productivity if soil disturbances are not mitigated. Logging operations were conducted during high soil moisture conditions on the South Carolina, USA coast to salvage timber and reduce wildfire potential following Hurricane Hugo in 1989. Long term study sites were established on wet pine flats to evaluate effects of primary skid trails and site preparation on soil properties and loblolly pine productivity. The experiment was analyzed as a split-plot within an unbalanced randomized complete block design having 12 blocks, two levels of traffic (primary skid trail (On), no obvious traffic (Off)) and four levels of site preparation (bedding (Bed), disking with bedding (D/B), disking (Disk), no site preparation (None)). Remeasurement of the study was conducted in 2015 at 25 years after salvage logging (stand age 23 years). Bed and D/B treatments had greater saturated hydraulic conductivity (p = 0.0567) and macro porosity (p = 0.0071) and lower bulk density (p = 0.0226) values than Disk and None treatments. Macroporosity benefits were evident two years after site preparation installation, but bulk density and saturated hydraulic conductivity were not, suggesting these two measurements were affected over time by differences in rooting activity influenced by initial aeration benefits. Depth to iron depletion (p = 0.0055) was significantly greater and soil carbon (p < 0.0001) was significantly lower in Bed and D/B treatments due to bed elevation above the water table and improved drainage. This implies greater aeration for roots, but trade-offs in aboveground biomass and soil carbon storage. However, above and below ground carbon differences balanced one another between treatments so that combined carbon storage in soil and above ground loblolly pine biomass was not significantly different by site preparation treatment (p = 0.1127). Bed and D/B resulted in approximately double the stand biomass (p < 0.0001) and stand density (p < 0.0001) than Disk and None. Bed and D/B generally created more favorable soil properties and enhanced long term loblolly pine stand productivity. Differences in soil properties and stand productivity between traffic levels, with and without site preparation, were negligible suggesting natural soil recovery mechanisms were mitigated effects of wet site harvesting over 25 years. McIntire-Stennis Program of the National Institute of Food and Agriculture, USDA; National Council for Air and Stream Improvement Inc. (NCASI); USDA Forest Service Southern Research Station Santee Experimental Forest; Virginia Tech Forest Operations and Business Research Cooperative; Virginia Tech Department of Forest Resources and Environmental Conservation This research received financial and/or logistical support from the McIntire-Stennis Program of the National Institute of Food and Agriculture, USDA; the National Council for Air and Stream Improvement Inc. (NCASI); The USDA Forest Service Southern Research Station Santee Experimental Forest personnel; the Virginia Tech Forest Operations and Business Research Cooperative; and the Virginia Tech Department of Forest Resources and Environmental Conservation. Public domain – authored by a U.S. government employee

Ground based timber harvesting on wet sites has been linked to alteration of soil properties that may result in reduced long term site productivity. Following Hurricane Hugo in the fall of 1989, numerous salvage logging operations were conducted under high soil moisture conditions to reduce wildfire risk and salvage timber within the Francis Marion National Forest in the lower coastal plain of South Carolina. Study sites were established on wet pine flats to examine the long term effects of primary skid trails and site preparation on planted loblolly pine (Pinus taeda L.) growth. Treatment effects were analyzed as a split-plot within a randomized complete block design with 12 blocks, four levels of site preparation (none, disking, bedding, disking with bedding), and two levels of machine traffic (primary skid trail, no obvious traffic). After 23 years, bedding and disking with bedding enhanced stand density (p < 0.0001) and above ground stand biomass (p < 0.0001) relative to the disking and non-site prepared treatments. None of the site preparation treatments were effective at increasing biomass of individual trees. Mean height (p < 0.0001), DBH (p < 0.0001), and biomass of individual trees (p < 0.0001) were lower on primary skid trails than in non-trafficked areas. Traffic did not have a significant effect on stand density (p < 0.4662) or stand biomass (p = 0.1564). Selected soil physical properties and productivity measurements were similar for the non-site prepared treatment on and off primary skid trails, suggesting that 23 years is sufficient time for soils in wet flats to naturally recover from wet weather harvest disturbance. This study indicates that bedding may be the most efficient management practice to enhance long term stand productivity for loblolly pine on aeration-limited sites by increasing seedling survival. Minimizing the spatial extent of skid trails may increase growth of individual trees. (C) 2017 Elsevier B.V. All rights reserved. McIntire-Stennis Program of the National Institute of Food and Agriculture, USDA; National Council for Air and Stream Improvement Inc. (NCASI); USDA Forest Service Southern Research Station Santee Experimental Forest personnel; Virginia Tech Forest Operations and Business Research Cooperative; Virginia Tech Department of Forest Resources and Environmental Conservation This research received financial and/or logistical support from the McIntire-Stennis Program of the National Institute of Food and Agriculture, USDA; the National Council for Air and Stream Improvement Inc. (NCASI); The USDA Forest Service Southern Research Station Santee Experimental Forest personnel; the Virginia Tech Forest Operations and Business Research Cooperative; and the Virginia Tech Department of Forest Resources and Environmental Conservation. Public domain – authored by a U.S. government employee

As southern pine forests (both planted and naturally regenerated) are more heavily used to provide biomass for the developing energy sectors and carbon sequestration, a better understanding of models used to characterize regional biomass estimates is needed. We harvested loblolly pines (Pinus taeda L.) between 0.5 and 15 cm dbh from several plantations and naturally regenerated stands in southeastern Arkansas to evaluate allometric relationships based on stand origin. In this process, each pine was separated into stemwood, branches + foliage, and taproot biomass components. Although the differences changed with dbh, loblolly pines from planted stands generally had greater percentages of biomass allocated to foliage + branches and taproots, whereas those from natural-origin stands had greater amounts in stemwood, aboveground, and total biomass. National Biomass Estimator (NBE) high-specific gravity pine equations predicted natural-origin aboveground biomass reasonably well. However, the same NBE model underpredicted aboveground biomass for small (similar to 5 cm) diameter planted pine and overpredicted planted pines between 7 and 15 cm dbh. When scaled to stand-level estimates, the NBE models resulted in estimates for average stand diameters of 5, 10, and 15 cm that ranged from -18.6 to 2.1% for natural stands and from -21.9 to 62.8% for planted stands. Agriculture and Food Research Initiative Competitive Grant from the USDA National Institute of Food and Agriculture [2009-35103-05356]; Southern Research Station of the USDA Forest Service; Arkansas Forest Resources Center We thank the following individuals for their contributions: Kirby Sneed and Rick Stagg (USDA Forest Service); Jonathan Hartley (University of Arkansas-Monticello); and Conner Fristoe (Weyerhaeuser Company). This research was supported by Agriculture and Food Research Initiative Competitive Grant 2009-35103-05356 from the USDA National Institute of Food and Agriculture, the Southern Research Station of the USDA Forest Service, and the Arkansas Forest Resources Center. Public domain – authored by a U.S. government employee

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95 +/- 0.45 Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17 +/- 0.06 Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87 +/- 0.49 Gt) overestimated the national ground-based estimate by 7.5%. The comparable log -linear model result (63.29 +/- 1.36 Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log -linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119,414 ground plots. At the US state level, the average absolute value of the deviation of LNI GLAS estimates from the comparable ground estimate of total biomass was 18.8% (range: Oregon, -40.8% to North Dakota, 128.6%). Log-linear models produced gross overestimates in the continental US, i.e., >2.6x, and the use of this model to predict regional biomass using GLAS data in temperate, western hemisphere forests is not appropriate. The best model form, LNI, is used to produce biomass estimates in Mexico. The average biomass density in Mexican forests is 53.10 +/- 0.88 t/ha, and the total biomass for the country, given a total forest area of 688,096 km(2), is 3.65 +/- 0.06 Gt. In Mexico, our GLAS biomass total underestimated a 2005 FAO estimate (4.152 Gt) by 12% and overestimated a 2007/8 radar study's figure (3.06 Gt) by 19%. (C) Published by Elsevier Inc. NASA's Carbon Cycle Science Program within the Science Mission Directorate Earth Science Division [NNH10ZDA001N-CARBON(2010)] This research was funded by NASA's Carbon Cycle Science Program within the Science Mission Directorate Earth Science Division-NNH10ZDA001N-CARBON(2010).