Large-diameter trees provide vital ecological functions in forested ecosystems. Old, large-diameter trees may also be vulnerable to climate-driven mortality events, but past work on large tree populations has been geographically limited. Here, we characterize the population of large-diameter trees from two size categories, 50 to 100 cm diameter at breast height (DBH) (medium) and >100 cm DBH (big), within the United States using Forest Inventory and Analysis data. Although populations of big trees are concentrated along the west coast, populations of medium trees are more evenly distributed across the nation. In the western United States, trees >50 cm DBH comprise ~75% of the total carbon stored in live trees, while in the eastern United States they comprise ~20%. Plot remeasurement data indicate that populations of big trees are increasing at an annual rate of 0.49% in the west and 2.9% in the east, and populations of medium trees are increasing at an annual rate of 0.5% in the west and 2.4% in the east. One exception is the Sierra Nevada region, where big trees are declining. Additionally, we observed declines for several individual species. While the overall population trend for large-diameter trees is positive, declines in these species could have localized impacts for the environments in which they occur.

Although many species display relationships - both positive and negative - with various forest successional stages, researchers often rely on datasets that describe forest presence rather than forest age (i.e., National Landcover Database). In 2023, the USDA Forest Service introduced standardized region-specific mature and oldgrowth (MOG) forest definitions for the United States, but these definitions have not been readily integrated to address questions in ecology and conservation. Here, we introduce 'mapMOG'-an open access R function that applies the recently adopted federal MOG definitions to Forest Inventory and Analysis (FIA) plots across the contiguous United States (US). Additionally, our novel function interpolates MOG status across US forested lands between FIA plots. To demonstrate the utility of these data for forest landscape ecological modeling, we compare the predictive power of the MOG covariate against binary forest/non-forest and percent canopy cover covariates to examine forest habitat associations across three taxa, geographies, and modelling frameworks: avian richness in Mid-Atlantic national parks; Seminole bat (Lasiurus seminolus) occupancy in the Southeastern Coastal Plain; and Cascade torrent salamander (Rhyacotriton cascadae) distribution associated with US National Forests in the Pacific Northwest. In all three cases, our MOG covariate produced by our function explained variation in the wildlife occurrence data better than the alternative forest metrics. Finally, we compared imputed results across multiple spatial scales and found notable but statistically insignificant differences in interpolated MOG scores.

Changing climate conditions, wildfires, and tree harvests could affect the area of mature and old-growth forests in the United States. We used a stochastic modeling system to project future areal extents of mature and old-growth forests on National Forest System (NFS) and Bureau of Land Management (BLM) land across the conterminous United States, and to assess threats to these forests under a variety of socioeconomic and climate futures, to 2070. The area of old-growth forest is expected to increase 19%-27% on NFS and BLM lands while mature forest trends (0.8% decrease to 2.5% increase) depend on the socioeconomic and climate future. Trends vary regionally, with old-growth area increasing everywhere but the South, where it is projected to remain approximately the same, while the area of mature forest remains relatively flat everywhere but the Pacific Northwest, where an increase is expected. Old growth is projected to increase for most major forest types while mature forest increases for some and decreases for others. The volume of trees killed by fire annually is projected to increase by as much as 48% for old-growth and 22%-100% for mature forests, while harvested volume could increase by 367%-441% in old-growth and 125%-150% in mature forests under some scenarios. Fire and cutting would cause only a small proportional decrease in overall tree volume, however. By identifying the ecosystems susceptible to loss of older forest, these results can inform management and conservation efforts to retain such forests and help them adapt to future change.

Validation studies of the Forest Vegetation Simulator (FVS), a stand projection model widely used to predict carbon outcomes of alternative forest management strategies, have found departures from observed forest growth for several FVS variants in the western USA. We evaluated the accuracy of stand-level biomass accumulation predicted by FVS across an environmental gradient represented by three > 2 million ha landscapes that overlap seven FVS variants in Oregon, USA and the extent to which commonly deployed calibrations could correct for any departures. Calibrations included: growth multipliers, maximum stand density parameters, and limits to large tree growth. FVS "out-of-the-box" (uncalibrated) simulations overpredicted net stand growth by 12-35 percent when evaluated against 10-yr stand remeasurements in Forest Inventory and Analysis (FIA) data. Applying all calibrations reduced departures to the-5 to + 9 % range for these landscapes, but variation in their efficacy among landscapes, stand ages, and forest types warrant thoughtful choices of calibrations that are specific to area of interest. Even with all calibrations applied, longer term (80-yr) FVS projections remained departed from a reference dataset constructed from yield curves fit to FIA data by substituting space for time, with percent error on net stand growth ranging from + 21 to + 49 percent (reduced from +109 to +161 % with uncalibrated projections). Bias reduction via calibration is an important, tractable, and short-term solution for obtaining meaningful short-term predictions to support policy. Accurate long-term predictions likely require additional calibrations to account for increased mortality and stress due to changes in climate and disturbance regimes.

Fire exclusion and past management have altered the composition, structure, and function of frequent-fire forests throughout western North America. In mixed-conifer forests of the California Sierra Nevada, fire exclusion has exacerbated the effects of drought and endemic bark beetles, resulting in extensive mortality of fire-adapted pine species. Thinning and prescribed fire are widely used in these forests to reduce fuels, moderate fire behavior, and restore ecosystems. Tree regeneration influences future forest composition and structure, and therefore future resilience to disturbances, but long-term effects of thinning and prescribed burning on tree regeneration after prolonged fire exclusion are poorly understood. We measured tree regeneration one year prior to, and periodically for 16 years following thinning and prescribed burning in a mixed-conifer forest in the Sierra Nevada, California, USA. We asked three questions. How did the composition and density of tree regeneration change after thinning and prescribed burning? Did pretreatment vegetation types influence conifer regeneration density after treatments? Did planting after overstory thinning increase regeneration density of native pine species? Sixteen years after treatments, combined natural regeneration of shade-tolerant white fir (Abies concolor) and incense-cedar (Calocedrus decurrens) averaged 2,032 trees per hectare (tph) after understory thinning, and 7,745 tph after understory thinning combined with prescribed burning, increases of 37 % and 146 % from pretreatment densities. In contrast, combined natural regeneration of white fir and incense-cedar averaged 497 tph after overstory thinning, 780 tph after overstory thinning with prescribed burning, 113 tph after prescribed burning alone, and 807 tph in untreated controls, all of which were declines from pretreatment densities. Natural regeneration of white fir and incense-cedar was consistently an order of magnitude greater than Jeffrey pine (Pinus jeffreyi) and sugar pine (Pinus lambertiana), whose combined densities 16 years after treatments averaged 37 tph across treatments and did not significantly respond to thinning and/or prescribed burning. Natural conifer regeneration after treatments varied by pre-treatment vegetation type (closed canopy, Ceanothus cordulatus shrub dominated, and open sparse), with large increases of natural regeneration after understory thinning in closed canopy and Ceanothus shrub vegetation types. Planting increased sugar pine regeneration density after overstory thinning, marginally increased Jeffrey pine regeneration after overstory thinning combined with prescribed burning, and increased white fir regeneration after overstory thinning with and without burning. No treatments reduced white fir and incense-cedar natural regeneration while simultaneously increasing natural pine regeneration, suggesting new thinning, burning, and planting approaches may be required to meet regeneration restoration objectives.

The Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture, Forest Service conducts the national forest inventory of the United States.Although FIA assembles a myriad of forest resource information, many analyses rely on the fundamental attributes of tree volume, biomass, and carbon content.Due to the chronological development of the FIA Program, numerous models and methods are currently used across the country, contingent upon the tree species and geographic location.Thus, an effort to develop nationally consistent methods for prediction of tree volume, biomass, and carbon content was undertaken.A key component of this study was amassing existing data in conjunction with collection of new data to fill information gaps related to tree size and species frequency and spatial distributions.These data were used in a modeling framework that provides compatible predictions of tree volume, biomass, and carbon content across the entire United States.National-scale comparisons to currently used methods show that only a small increase in volume occurs, but substantial increases in biomass and carbon are realized due to relatively large increases in predicted tree top/limbs biomass and carbon.Changes in tree carbon were also affected by use of newly developed species carbon fractions instead of the current constant conversion factor of 0.5.Examples of the calculations required to predict tree volume, biomass, and carbon content for commonly encountered tree conditions provide step-by-step implementation details.

Microplastic (MP) transport in the atmosphere, one of the least studied environmental compartments because of the relatively small size of air-borne MPs and the challenges in identifying them, may be inferred from their occurrence in snowfall. In this study, 11 sites across western coastal North America were sampled and analyzed for MP presence in fresh snowfall, months-old summer surface snow, and stratified deposits in snow pits. MPs were detected and characterized using a method integrating linear array µ-Fourier Transform Spectroscopy (µFTIR) and batch spectral analysis with open-source platform Open Specy. Recovery rate analysis from sample filtration to data analysis was conducted, and analysis of field or laboratory blanks suggested negligible contamination (≤ 1 polyamide fragment per blank). Concentrations of MPs in the fresh snowfall of remote sites and those proximal to sources were 5.1-150.8 p/L and 104.5-325 p/L of snowmelt water, respectively. Summer surface snow that was several months old had MP concentrations ranging from 57.5-539 p/L of meltwater, and snow sampled at different depths within a snowpack had concentrations ranging from 35-914 p/L. Our results demonstrate a streamlined method that may be used for measuring MPs in remote or pristine environments, contributing to a better understanding of long-range MP transport.

Forest ecosystems store large amounts of carbon and can be important sources, or sinks, of the atmospheric carbon dioxide that is contributing to global warming. Understanding the carbon storage potential of different forests and their response to management and disturbance events are fundamental to developing policies and scenarios to partially offset greenhouse gas emissions. Projections of live tree carbon accumulation are handled differently in different models, with inconsistent results. We developed growth-and-yield style models to predict stand-level live tree carbon density as a function of stand age in all vegetation types of the coastal Pacific region, US (California, Oregon, and Washington), from 7,523 national forest inventory plots. We incorporated site productivity and stockability within the Chapman-Richards equation and tested whether intensively managed private forests behaved differently from less managed public forests. We found that the best models incorporated stockability in the equation term controlling stand carrying capacity, and site productivity in the equation terms controlling the growth rate and shape of the curve. RMSEs ranged from 10 to 137 Mg C/ha for different vegetation types. There was not a significant effect of ownership over the standard industrial rotation length (~50 yrs) for the productive Douglas-fir/western hemlock zone, indicating that differences in stockability and productivity captured much of the variation attributed to management intensity. Our models suggest that doubling the rotation length on these intensively managed lands from 35 to 70 years would result in 2.35 times more live tree carbon stored on the landscape. These findings are at odds with some studies that have projected higher carbon densities with stand age for the same vegetation types, and have not found an increase in yields (on an annual basis) with longer rotations. We suspect that differences are primarily due to the application of yield curves developed from fully-stocked, undisturbed, single-species, “normal” stands without accounting for the substantial proportion of forests that don’t meet those assumptions. The carbon accumulation curves developed here can be applied directly in growth-and-yield style projection models, and used to validate the predictions of ecophysiological, cohort, or single-tree style models being used to project carbon futures for forests in the region. Our approach may prove useful for developing robust models in other forest types.

<p>Globally, fluxes of microplastics to marine environments are thought to be dominated by stormflow from urban environments, which may be moderated by storage in estuaries. Fluvial transport of microplastics is primarily a supply-limited phenomenon, but flow field and particle characteristics can result in a wide range of transport modes, from surface load to bedload, with potential ramifications for estuarine transport and fate. Here we report preliminary findings from microplastic monitoring campaigns conducted in a number of streams draining urban watersheds in Southern California, and estuarine wetland and benthic sediment deposits. These studies will serve as the basis for microplastic flux, accretion, and composition evaluation, and inform the optimization of microplastic monitoring in urban systems.</p>

In response to US Congressional acts (e.g., Infrastructure Investment and Jobs Act, 2022), Presidential orders (EO#14072, April 22, 2022) and increasing public interest in older forests and associated spiritual and ecosystem services they often render (e.g., carbon storage), this study developed an approach to consistently estimate extent of old-growth forest on USDA Forest Service National Forest System (NFS) lands, using nationally-consistent population estimates (totals and sampling errors) derived from the USDA Forest Service, Forest Inventory and Analysis (FIA) Program plot network. We worked with NFS scientists to obtain regionally-approved criteria for establishing ‘old forest’ status based on NFS old-growth forest definitions, assessments, and related documents. We use the term ‘old forest’ instead of old-growth forest when referring to the exact criteria used here since this is an initial inventory and because in some cases unaltered FIA data could not provide desired forest structure metrics (such as pieces of down wood or forest patch size). Determining regional ‘old forest’ criteria was relatively straightforward for some regions where old-growth forest definitions were specific, and in some cases already used for quantifying old-growth forest. In other NFS regions, such as where definitions have never been applied in an operational manner, or where there were merely assessments of old-growth forest conditions, determining exact inventory criteria was more difficult for NFS scientists. The NFS regional ‘old forest’ criteria most commonly included minimum abundance of large live trees (in eight of nine regions), tree or stand age (in eight of nine regions), and dead large tree density (in three of nine regions). We estimate that there are approximately 10 million ha of ‘old forest’ across NFS forests, with the preponderance in the western US states. This study produces the first, initial ‘old forest’ inventory based on agency definitions of old growth. Revisions are expected to account for concerns about reliability in hard to measure criteria, changes in ecological understanding since definitions were made, and changing conditions on the ground (such as due to climate change or invasive species). We also expect adjustments to improve compatibility with old-growth assessments at different spatial scales and in relation to management strategies.

Mature and old-growth forests are valued for biodiversity, carbon sequestration, habitat, hydrologic function, aesthetics, and spirituality, as well as Tribal and Indigenous histories, cultures, and practices. Over the last 500 years, land use change and industrialization have resulted in global declines in the area of older forests (however defined). The goal of this study was to identify concepts and indicators to define mature and old-growth forests across the vegetation types of the United States in order to quantify their abundance and distribution. Defining old growth has been described as a "wicked problem" that involves values, science, and management; requires multiple disciplines; and can be expressed from many contradictory approaches.The most common approach to defining mature and old-growth forests is to place them in a successional continuum of increases in tree size, biodiversity, habitat niches, and structural diversity with forest age. Time since severe disturbance, including human impact, is often a consideration, although humans have influenced the development of many forests for millennia. The successional framework is less useful in low-productivity or frequently-disturbed forests, or where current structural diversity under fire suppression may not reflect historic or desired future conditions. In order to classify forests into "old" and "not old", existing structure-based ap-proaches apply minima of one or more structural or compositional criteria. Site productivity and/or plant as-sociation is an element of many definitions.Once defined, estimating the area of mature and old-growth forest presents challenges. The only compre-hensive, consistent field data of US forests is the Forest Inventory and Analysis (FIA) network of >140,000 forested plots. While the 0.067 ha sample area of FIA plots limits the number of structural metrics that might be useful and the plot density cannot capture fine-scale spatial heterogeneity, measurements enable a granular application of multiple structural and compositional criteria by vegetation type at broad spatial extents, and the ability to track change consistently over time. Spatial models integrate field and remotely-sensed data to predict the distribution of structural classes at finer spatial grain, but with substantial error in high-resolution estimates. There does not seem to be a readily-available method to map mature and old-growth stands across a landscape with a high degree of accuracy. Identifying mature and old growth forests in a stand management context will likely require additional measurements, adjustments to criteria at local scales, and incorporation of social and traditional knowledge within a consistent definition framework.

Subalpine forests in western North America are threatened by rapid climate change, increased activity by endemic and exotic insects and diseases, and changing wildfire regimes. The interactive effects of these stressors have resulted in pronounced population declines in many subalpine tree species; however, a systematic assessment of the status and trends of subalpine forests is lacking. Subalpine fir (Abies lasiocarpa) is a widespread species across the western United States, with documented population declines in many parts of its distribution. Here we use subalpine fir as an initial leverage point to build a more complete understanding of subalpine forest baseline conditions and responses to environmental change. Specifically, we leverage the USDA Forest Service Forest Inventory and Analysis (FIA) database to (1) ask how subalpine fir populations are changing across the species' distribution in the western US, (2) assess the drivers of recent subalpine fir population trends, and (3) explore whether those changes imply generalized species-wide and/or system-wide decline. We found that subalpine fir abundance and basal area are declining concurrently across - 62% of the species' distribution, and increasing across - 19%. Range-wide, we estimated 25.02 & PLUSMN; 2.74 % subalpine fir mortality between 2000 and 2009 and 2010-2019 FIA inventory periods, with higher mortality concentrated in the eastern Oregon Cascades, central Idaho, and parts of southern Colorado. High regeneration density did not predict positive population trajectories, which were instead associated with higher rates of adult recruitment. While the importance of different mortality agents varied substantially between ecoregions, 83.4% of total range-wide mortality was related to fire or biological disturbance. Declining subalpine fir basal area coincided with declines in the basal area of other co-occurring tree species in 39% of subalpine forest area, and with increases in conspecific basal area in 22% of forest area. Fire disturbance was the single largest cause of subalpine fir mortality; however, even where subalpine fir fire mortality was high, mortality among other species was primarily caused by insects. Our results suggest that subalpine fir declines across large portions of the western United States are driven by forest disturbance, and that declines in subalpine fir populations may be indicative of negative change in subalpine forest systems broadly.

Following life-cycle assessment (LCA) methodology, this study presents a state-level estimation of embodied carbon of wood products harvested in 2019 from California and subsequently processed, manufactured, transported, used, and disposed at the end-of-life (EoL). In a conventional static approach to LCA, all GHG emissions were aggregated and considered to occur at year 0 of the given time horizon (500 years in this study) and used a static characterization factor (CF). In dynamic LCA, GHG emissions occurring in different years were considered, and their global warming impact (GWI) was determined using a time-dependent CF over the selected time horizon of 500 years. Four scenarios were developed to examine the impact of EoL choices on GWI. It was found that dynamic GWI for all scenarios ranged from 0.27 to 0.93 million tonne CO₂e, which were 45-73 % lower than those estimated with static LCA approach, indicating that the static LCA approach could lead to an underestimation of the benefits of substituting wood for non-wood products, compared to those based on dynamic LCA approach. This analysis also demonstrated that the choice of EoL treatment option is a key factor affecting the estimated GWI as it directly determines the annual emission of GHGs released into atmosphere and subsequently their warming effect depending on the time harvested wood products (HWPs) spend in the horizon of assessment. Overall, the dynamic LCA performed in this study enabled more robust interpretations of embodied carbon by including temporal boundaries associated with the HWPs life cycle.

Quality assurance and quality control (QA/QC) techniques are critical to analytical chemistry, and thus the analysis of microplastics. Procedural blanks are a key component of QA/QC for quantifying and characterizing background contamination. Although procedural blanks are becoming increasingly common in microplastics research, how researchers acquire a blank and report and/or use blank contamination data varies. Here, we use the results of laboratory procedural blanks from a method evaluation study to inform QA/QC procedures for microplastics quantification and characterization. Suspected microplastic contamination in the procedural blanks, collected by 12 participating laboratories, had between 7 and 511 particles, with a mean of 80 particles per sample (±SD 134). The most common color and morphology reported were black fibers, and the most common size fraction reported was 20-212 μm. The lack of even smaller particles is likely due to limits of detection versus lack of contamination, as very few labs reported particles <20 μm. Participating labs used a range of QA/QC techniques, including air filtration, filtered water, and working in contained/'enclosed' environments. Our analyses showed that these procedures did not significantly affect blank contamination. To inform blank subtraction, several subtraction methods were tested. No clear pattern based on total recovery was observed. Despite our results, we recommend commonly accepted procedures such as thorough training and cleaning procedures, air filtration, filtered water (e.g., MilliQ, deionized or reverse osmosis), non-synthetic clothing policies and 'enclosed' air flow systems (e.g., clean cabinet). We also recommend blank subtracting by a combination of particle characteristics (color, morphology and size fraction), as it likely provides final microplastic particle characteristics that are most representative of the sample. Further work should be done to assess other QA/QC parameters, such as the use of other types of blanks (e.g., field blanks, matrix blanks) and limits of detection and quantification.

COPYRIGHT © 2023 Morin, Healey, Prisley, Randolph, Westfall and Gray. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Monitoring and responding to global change to promote resilient and productive forests through innovative forest inventory

President Biden's executive order, 'Strengthening the Nation's Forests, Communities, and Local Economies,' (EO#14072, April 22, 2022) acknowledges the interest in mature and old-growth (MOG) forests by directing U.S. Federal agencies to define and inventory these resources on United States Forest Service (USFS) and Bureau of Land Management (BLM) lands. We propose using an effective and enduring mature forest classification system that could be adaptable to social paradigms, monitoring data streams, scientific information, and global change factors. We accommodate these design aspects by defining mature forests as a growth stage prior to the onset of old-growth attributes within a proposed Forest Inventory Growth Stage System (FIGSS). FIGSS uses the longestablished USFS old-growth assessments often conducted in concert with public dialogues to identify key structural indicators of older forests. The system informs inverse modeling of the prior "mature" stage's structural thresholds enabling initial population estimates of mature forest extent using the USFS' nationally consistent Forest Inventory and Analysis (FIA) program data. With this approach, we estimate that approximately 45 percent of all USFS/BLM forest is mature. The FIGSS system is based on a variety of components that could be used to account for cultural values ascribed to forest conditions which could be refined across future versions such as assumptions about the relative length of growth stages, incorporating data from emerging monitoring technologies along with old-growth/mature field sampling campaigns, accommodating spectrums of site-limited and/or disturbance-driven stand development, refined variable selection processes such as machine-learning, and consideration of traditional ecological knowledge.