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Forests are integral to the global land carbon sink, which has sequestered ~30% of anthropogenic carbon emissions over recent decades. The persistence of this sink depends on the balance of positive drivers that increase ecosystem carbon storage-e.g., CO2 fertilization-and negative drivers that decrease it-e.g., intensifying disturbances. The net response of forest productivity to these drivers is uncertain due to the challenge of separating their effects from background disturbance-regrowth dynamics. We fit non-linear models to US forest inventory data (113,806 plot remeasurements in non-plantation forests from ~1999 to 2020) to quantify productivity trends while accounting for stand age, tree mortality, and harvest. Productivity trends were generally positive in the eastern United States, where climate change has been mild, and negative in the western United States, where climate change has been more severe. Productivity declines in the western United States cannot be explained by increased mortality or harvest; these declines likely reflect adverse climate-change impacts on tree growth. In the eastern United States, where data were available to partition biomass change into age-dependent and age-independent components, forest maturation and increasing productivity (likely due, at least in part, to CO2 fertilization) contributed roughly equally to biomass carbon sinks. Thus, adverse effects of climate change appear to overwhelm any positive drivers in the water-limited forests of the western United States, whereas forest maturation and positive responses to age-independent drivers contribute to eastern US carbon sinks. The future land carbon balance of forests will likely depend on the geographic extent of drought and heat stress.
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Mudança Climática , Ecossistema , Estados Unidos , Dióxido de Carbono , Florestas , Árvores , Biomassa , CarbonoRESUMO
Several initiatives have been proposed to mitigate forest loss and climate change through tree planting as well as maintaining and restoring forest ecosystems. These initiatives have both inspired and been inspired by global assessments of tree and forest attributes and their contributions to offset carbon dioxide (CO2) emissions. Here we use data from more than 130,000 national forest inventory plots to describe the contribution of nearly 1.4 trillion trees on forestland in the conterminous United States to mitigate CO2 emissions and the potential to enhance carbon sequestration capacity on productive forestland. Forests and harvested wood products uptake the equivalent of more than 14% of economy-wide CO2 emissions in the United States annually, and there is potential to increase carbon sequestration capacity by â¼20% (-187.7 million metric tons [MMT] CO2 ±9.1 MMT CO2) per year by fully stocking all understocked productive forestland. However, there are challenges and opportunities to be considered with tree planting. We provide context and estimates from the United States to inform assessments of the potential contributions of forests in climate change mitigation associated with tree planting.
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Forest resource reporting techniques primarily use the two most recent measurements for understanding forest change. Multiple remeasurements now exist within the US national forest inventory (NFI), providing an opportunity to examine long-term forest demographics. We leverage two decades of remeasurements to quantify live-dead wood demographics which can better inform estimates of resource changes in forest ecosystems. Our overall objective is to identify opportunities and gaps in tracking 20 years of forest demographics within the US NFI using east Texas as a pilot study region given its diversity of tree species, prevalence of managed conditions, frequency of disturbances, and relatively rapid change driven by a warm, humid climate. We examine growth and mortality rates, identify transitions to downed dead wood/litter and removal via harvest, and describe implications of these processes focusing on key species groups (i.e., loblolly pine, post oak, and water oak) and size classes (i.e., saplings, small and large trees). Growth and mortality rates fluctuated differently over time by species and stem sizes in response to large-scale disturbances, namely the 2011 drought in Texas. Tree-fall rates were highest in saplings and snag-fall rates trended higher in smaller trees. For removal rates, different stem sizes generally followed similar patterns within each species group. Forest demographics from the field-based US NFI are informative for identifying diffuse lagged mortality, species- and size-specific effects, and management effects. Moreover, researchers continually seek to employ ancillary data and develop new statistical methods to enhance understanding of forest resource changes from field-based inventories.
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Ecossistema , Quercus , Projetos Piloto , Texas , Monitoramento Ambiental , Florestas , Árvores , DemografiaRESUMO
First principles predict that diversity at one trophic level often begets diversity at other levels, suggesting plant and mycorrhizal fungal diversity should be coupled. Local-scale studies have shown positive coupling between the two, but the association is less consistent when extended to larger spatial and temporal scales. These inconsistencies are likely due to divergent relationships of different mycorrhizal fungal guilds to plant diversity, scale dependency, and a lack of coordinated sampling efforts. Given that mycorrhizal fungi play a central role in plant productivity and nutrient cycling, as well as ecosystem responses to global change, an improved understanding of the coupling between plant and mycorrhizal fungal diversity across scales will reduce uncertainties in predicting the ecosystem consequences of species gains and losses.
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Micorrizas , Biodiversidade , Ecossistema , Fungos , Micorrizas/fisiologia , Nutrientes , Plantas/microbiologia , Solo , Microbiologia do SoloRESUMO
Carbon (C)-informed forest management requires understanding how disturbance and management influence soil organic carbon (SOC) stocks at scales relevant to landowners and forest policy and management professionals. The continued growth of data sets and publications allows powerful synthesis approaches to be applied to such questions at increasingly fine scales. Here, we report results from a synthesis that used meta-analysis of published studies and two large observational databases to quantify disturbance and management impacts on SOC stocks. We conducted this, the third in a series of ecoregional SOC assessments, for the Pacific Northwest, which comprises ~8% of the land area but ~12% of the U.S. forest sector C sink. At the ecoregional level, our analysis indicated that fundamental patterns of vegetation, climate, and topography are far more important controls on SOC stocks than land use history, disturbance, or management. However, the same patterns suggested that increased warming, drying, wildland fire, and forest regeneration failure pose significant risks to SOC stocks across the region. Detailed meta-analysis results indicated that wildfires diminished SOC stocks throughout the soil profile, while prescribed fire only influenced surface organic materials and harvesting had no significant overall impact on SOC. Independent observational data corroborated the negative influence of fire on SOC derived from meta-analysis, suggested that harvest impacts may vary subregionally with climate or vegetation, and revealed that forests with agricultural uses (e.g., grazing) or legacies (e.g., cultivation) had smaller SOC stocks. We also quantified effects of a range of common forest management practices having either positive (organic amendments, nitrogen [N]-fixing vegetation establishment, inorganic N fertilization) or no overall effects on SOC (other inorganic fertilizers, urea fertilization, competition suppression through herbicides). In order to maximize the management applications of our results, we qualified them with ratings of confidence based on degree of support across approaches. Last, similar to earlier published assessments from other ecoregions, we supplemented our quantitative synthesis results with a literature review to arrive at a concise set of tactics for adapting management operations to site-specific criteria.
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Carbono , Solo , Agricultura , Carbono/análise , Florestas , Nitrogênio/análiseRESUMO
Forest disturbances play a critical role in ecosystem dynamics. However, the methods for quantifying these disturbances at broad scales may underestimate disturbances that affect individual trees. Utilizing individual tree variables may provide early disturbance detection that directly affects tree demographics and forest dynamics. The goals of this study were to (1) describe different methods for quantifying disturbances at individual tree and condition-level scales, (2) compare the differences between disturbance variables, and (3) provide a methodology for selecting an appropriate disturbance variable from national forest inventories for diverse applications depending on user needs. To achieve these goals, we used all the remeasurements available from the USDA Forest Inventory and Analysis (FIA) database since the start of the annual inventory for the lower 48 US states. Variables used included disturbance code, treatment code, agent of mortality, and damage code. Chi-square tests of independence were used to verify how the choice of the variable that represents disturbance affects its magnitude. Disturbed plots, as classified by each disturbance variable, were mapped to observe their spatial distribution. We found that the Chi-square tests were significant when using all the states and comparing each state individually, indicating that different results exist depending on which variable is used to represent disturbance. Our results will be a useful tool to help researchers measure the magnitude and scale of disturbance since the manner in which disturbances are categorized will impact forest management plans, national and international reports of forest carbon stocks, and sequestration potential under future global change scenarios.
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Ecossistema , Monitoramento Ambiental , Carbono , Florestas , Árvores , Estados UnidosRESUMO
Soils are Earth's largest terrestrial carbon (C) pool, and their responsiveness to land use and management make them appealing targets for strategies to enhance C sequestration. Numerous studies have identified practices that increase soil C, but their inferences are often based on limited data extrapolated over large areas. Here, we combine 15,000 observations from two national-level databases with remote sensing information to address the impacts of reforestation on the sequestration of C in topsoils (uppermost mineral soil horizons). We quantify C stocks in cultivated, reforesting, and natural forest topsoils; rates of C accumulation in reforesting topsoils; and their contribution to the US forest C sink. Our results indicate that reforestation increases topsoil C storage, and that reforesting lands, currently occupying >500,000 km2 in the United States, will sequester a cumulative 1.3-2.1 Pg C within a century (13-21 Tg C·y-1). Annually, these C gains constitute 10% of the US forest sector C sink and offset 1% of all US greenhouse gas emissions.
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Carbono/análise , Solo/química , Carbono/metabolismo , Monitoramento Ambiental , Florestas , Efeito Estufa , Árvores/crescimento & desenvolvimento , Árvores/metabolismo , Estados UnidosRESUMO
Downed coarse woody debris, also known as coarse woody detritus or downed dead wood, is challenging to estimate for many reasons, including irregular shapes, multiple stages of decay, and the difficulty of identifying species. In addition, some properties are commonly not measured, such as wood density and carbon concentration. As a result, there have been few previous evaluations of uncertainty in estimates of downed coarse woody debris, which are necessary for analysis and interpretation of the data. To address this shortcoming, we quantified uncertainties in estimates of downed coarse woody debris volume and carbon storage using data collected from permanent forest inventory plots in the northeastern United States by the Forest Inventory and Analysis program of the USDA Forest Service. Quality assurance data collected from blind remeasurement audits were used to quantify error in diameter measurements, hollowness of logs, species identification, and decay class determination. Uncertainty estimates for density, collapse ratio, and carbon concentration were taken from the literature. Estimates of individual sources of uncertainty were combined using Monte Carlo methods. Volume estimates were more reliable than carbon storage, with an average 95% confidence interval of 15.9 m3 /ha across the 79 plots evaluated, which was less than the mean of 31.2 m3 /ha. Estimates of carbon storage (and mass) were more uncertain, due to poorly constrained estimates of the density of wood. For carbon storage, the average 95% confidence interval was 11.1 Mg C/ha, which was larger than the mean of 4.6 Mg C/ha. Accounting for the collapse of dead wood as it decomposes would improve estimates of both volume and carbon storage. On the other hand, our analyses suggest that consideration of the hollowness of downed coarse woody debris pieces could be eliminated in this region, with little effect. This study demonstrates how uncertainty analysis can be used to quantify confidence in estimates and to help identify where best to allocate resources to improve monitoring designs.
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Carbono , Madeira , New England , Árvores , IncertezaRESUMO
Disturbances play a critical role in forest ecosystem dynamics. Disturbances cause changes in forest structure which in turn influence the species composition of the site and alter landscape patterns over time. The impacts of disturbance are seen over a broad spectrum of spatial scales and varying intensities, ranging from biotic agents such as insect and leaf disease outbreaks to abiotic agents such as a windstorm (a stand-replacing disturbance). This study utilized Forest Inventory and Analysis (FIA) data collected between 1999 and 2014 in the US Lake States (Michigan, Minnesota, and Wisconsin) to examine the impacts that disturbances have on the growth of residual trees using species-specific diameter increment equations. Results showed that animal and weather damage were the most common disturbance agents and fires were the least common in the region. Results also indicated that while the diameter increment equations performed well on average (overprediction of 0.08 ± 1.98 cm/10 years in non-disturbed stands), when the data were analyzed by species and disturbance agent, the model equation was rarely validated using equivalence tests (underprediction of 0.30 ± 2.24 cm/10 years in non-disturbed stands). This study highlights the importance of monitoring forest disturbances for their impacts on forest growth and yield.
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Monitoramento Ambiental/métodos , Árvores/crescimento & desenvolvimento , Animais , Incêndios , Florestas , Lagos , Michigan , Minnesota , Tempo (Meteorologia) , WisconsinRESUMO
Forest mycorrhizal type mediates nutrient dynamics, which in turn can influence forest community structure and processes. Using forest inventory data, we explored how dominant forest tree mycorrhizal type affects understory plant invasions with consideration of forest structure and soil properties. We found that arbuscular mycorrhizal (AM) dominant forests, which are characterised by thin forest floors and low soil C : N ratio, were invaded to a greater extent by non-native invasive species than ectomycorrhizal (ECM) dominant forests. Understory native species cover and richness had no strong associations with AM tree dominance. We also found no difference in the mycorrhizal type composition of understory invaders between AM and ECM dominant forests. Our results indicate that dominant forest tree mycorrhizal type is closely linked with understory invasions. The increased invader abundance in AM dominant forests can further facilitate nutrient cycling, leading to the alteration of ecosystem structure and functions.
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Micorrizas , Plantas , Árvores , Ecossistema , Florestas , Espécies IntroduzidasRESUMO
BACKGROUND: Wood carbon fractions (CFs)-the proportion of dry woody biomass comprised of elemental carbon (C)-are a key component of forest C estimation protocols and studies. Traditionally, a wood CF of 50% has been assumed in forest C estimation protocols, but recent studies have specifically quantified differences in wood CFs across several different forest biomes and taxonomic divisions, negating the need for generic wood CF assumptions. The Intergovernmental Panel on Climate Change (IPCC), in its 2006 "Guidelines for National Greenhouse Gas Inventories", published its own multitiered system of protocols for estimating forest C stocks, which included wood CFs that (1) were based on the best available literature (at the time) and (2) represented a significant improvement over the generic 50% wood CF assumption. However, a considerable number of new studies on wood CFs have been published since 2006, providing more accurate, robust, and spatially- and taxonomically- specific wood CFs for use in forest C estimation. MAIN TEXT: We argue that the IPCC's recommended wood CFs and those in many other forest C estimation models and protocols (1) differ substantially from, and are less robust than, wood CFs derived from recently published data-rich studies; and (2) may lead to nontrivial errors in forest C estimates, particularly for countries that rely heavily on Tier 1 forest C methods and protocols (e.g., countries of the Global South with large expanses of tropical forests). Based on previous studies on this topic, we propose an alternative set of refined wood CFs for use in multiscale forest C estimation, and propose a novel decision-making framework for integrating species- and location-specific wood CFs into forest C estimation models. CONCLUSION: The refined wood CFs that we present in this commentary may be used by the IPCC to update its recommended wood CFs for use in forest C estimation. Additionally, we propose a novel decision-making framework for integrating data-driven wood CFs into a wider suite of multitiered forest C estimation protocols, models, and studies.
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BACKGROUND: Forests are significant terrestrial biomes for carbon storage, and annual carbon accumulation of forest biomass contributes offsets affecting net greenhouse gases in the atmosphere. The immediate loss of stored carbon through fire on forest lands reduces the annual offsets provided by forests. As such, the United States reporting includes annual estimates of direct fire emissions in conjunction with the overall forest stock and change estimates as a part of national greenhouse gas inventories within the United Nations Framework Convention on Climate Change. Forest fire emissions reported for the United States, such as the 129 Tg CO2 reported for 2022, are based on the Wildland Fire Emissions Inventory System (WFEIS). Current WFEIS estimates are included in the Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2022 published in 2024 by the United States Environmental Protection Agency. Here, we describe WFEIS the fire emissions inventory system we used to address current information needs, and an analysis to confirm compatibility of carbon mass between estimated forest fire emissions and carbon in forest stocks. RESULTS: The summaries of emissions from forests are consistent with previous reports that show rates and interannual variability in emissions and forest land area burned are generally greater in recent years relative to the 1990s. Both emissions and interannual variability are greater in the western United States. The years with the highest CO2 emissions from forest fires on the 48 conterminous states plus Alaska were 2004, 2005, and 2015. In some years, Alaska emissions exceed those of the 48 conterminous states, such as in 2022, for example. Comparison of forest fire emission to forest carbon stocks indicate there is unlikely any serious disconnect between inventory and fire emissions estimates. CONCLUSIONS: The WFEIS system is a user-driven approach made available via a web browser. Model results are compatible with the scope and reporting needs of the annual national greenhouse gas inventories.
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BACKGROUND: In most regions and ecosystems, soils are the largest terrestrial carbon pool. Their potential vulnerability to climate and land use change, management, and other drivers, along with soils' ability to mitigate climate change through carbon sequestration, makes them important to carbon balance and management. To date, most studies of soil carbon management have been based at either large or site-specific scales, resulting in either broad generalizations or narrow conclusions, respectively. Advancing the science and practice of soil carbon management requires scientific progress at intermediate scales. Here, we conducted the fifth in a series of ecoregional assessments of the effects of land use change and forest management on soil carbon stocks, this time addressing the Northeast U.S. We used synthesis approaches including (1) meta-analysis of published literature, (2) soil survey and (3) national forest inventory databases to examine overall effects and underlying drivers of deforestation, reforestation, and forest harvesting on soil carbon stocks. The three complementary data sources allowed us to quantify direction, magnitude, and uncertainty in trends. RESULTS: Our meta-analysis findings revealed regionally consistent declines in soil carbon stocks due to deforestation, whether for agriculture or urban development. Conversely, reforestation led to significant increases in soil C stocks, with variation based on specific geographic factors. Forest harvesting showed no significant effect on soil carbon stocks, regardless of place-based or practice-specific factors. Observational soil survey and national forest inventory data generally supported meta-analytic harvest trends, and provided broader context by revealing the factors that act as baseline controls on soil carbon stocks in this ecoregion of carbon-dense soils. These factors include a range of soil physical, parent material, and topographic controls, with land use and climate factors also playing a role. CONCLUSIONS: Forest harvesting has limited potential to alter forest soil C stocks in either direction, in contrast to the significant changes driven by land use shifts. These findings underscore the importance of understanding soil C changes at intermediate scales, and the need for an all-lands approach to managing soil carbon for climate change mitigation in the Northeast U.S.
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The forest carbon sink of the United States offsets emissions in other sectors. Recently passed US laws include important climate legislation for wildfire reduction, forest restoration, and forest planting. In this study, we examine how wildfire reduction strategies and planting might alter the forest carbon sink. Our results suggest that wildfire reduction strategies reduce carbon sequestration potential in the near term but provide a longer term benefit. Planting initiatives increase carbon sequestration but at levels that do not offset lost sequestration from wildfire reduction strategies. We conclude that recent legislation may increase near-term carbon emissions due to fuel treatments and reduced wildfire frequency and intensity, and expand long-term US carbon sink strength.
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Downed woody material (DWM) is a unique part of the forest carbon cycle serving as a pool between living biomass and subsequent atmospheric emission or transference to other forest pools. Thus, DWM is an individually defined pool in national greenhouse gas inventories. The diversity of DWM carbon drivers (e.g., decay, tree mortality, or wildfire) and associated high spatial variability make this a difficult-to-predict component of forest ecosystems. Using the now fully established nationwide inventory of DWM across the United States (US), we developed models, which substantially improved predictions of stand-level DWM carbon density relative to the current national-reporting model ('previous' model, here). The previous model was developed from published DWM carbon densities prior to the NFI DWM inventory. Those predictions were tested using NFI DWM carbon densities resulting in a poor fit to the data (coefficient of determination, or R2 = 0.03). We present new random forest (RF) and stochastic gradient boosted (SGB) regression models to prediction DWM carbon density on all NFI plots and spatially on all forest land pixels. We evaluated various biotic and abiotic regression predictors, and the most important were standing dead trees, long-term annual precipitation, and long-term maximum summer temperature. A RF model scored best for expanding predictions to NFI plots (R2 = 0.31), while an SGB model was identified for DWM carbon predictions based on purely spatial data (i.e., NFI-plot-independent, with R2 = 0.23). The new RF model predicts conterminous US DWM carbon stocks to be 15% lower than the previous model and 2% higher than NFI data expanded according to inventory design-based inference. The new NFI data-driven models not only improve the predictions of DWM carbon density on all plots, they also provide flexibility in extending these predictions beyond the NFI to make spatially explicit and spatially continuous estimates of DWM carbon on all forest land in the US.
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Carbono , Ecossistema , Biomassa , Carbono/análise , Ciclo do Carbono , Estados Unidos , Madeira/químicaRESUMO
Most existing functional diversity indices focus on a single facet of functional diversity. Although these indices are useful for quantifying specific aspects of functional diversity, they often present some conceptual or practical limitations in estimating functional diversity. Here, we present a new functional extension and evenness (FEE) index that encompasses two important aspects of functional diversity. This new index is based on the straightforward notion that a community has high diversity when its species are distant from each other in trait space. The index quantifies functional diversity by evaluating the overall extension of species traits and the interspecific differences of a species assemblage in trait space. The concept of minimum spanning tree (MST) of points was adopted to obtain the essential distribution properties for a species assembly in trait space. We combined the total length of MST branches (extension) and the variation of branch lengths (evenness) into a raw FEE0 metric and then translated FEE0 to a species richness-independent FEE index using a null model approach. We assessed the properties of FEE and used multiple approaches to evaluate its performance. The results show that the FEE index performs well in quantifying functional diversity and presents the following desired properties: (a) It allows a fair comparison of functional diversity across different species richness levels; (b) it preserves the essence of single-facet indices while overcoming some of their limitations; (c) it standardizes comparisons among communities by taking into consideration the trait space of the shared species pool; and (d) it has the potential to distinguish among different community assembly processes. With these attributes, we suggest that the FEE index is a promising metric to inform biodiversity conservation policy and management, especially in applications at large spatial and/or temporal scales.
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A key uncertainty in quantifying dead wood carbon (C) stocks-which comprise ~8% of total forest C pools globally-is a lack of accurate dead wood C fractions (CFs) that are employed to convert dead woody biomass into C. Most C estimation protocols utilize a default dead wood CF of 50%, but live tree studies suggest this value is an over-estimate. Here, we compile and analyze a global database of dead wood CFs in trees, showing that dead wood CFs average 48.5% across forests, deviating significantly from 50%, and varying systematically among biomes, taxonomic divisions, tissue types, and decay classes. Utilizing data-driven dead wood CFs in tropical forests alone may correct systematic overestimates in dead wood C stocks of ~3.0 Pg C: an estimate approaching nearly the entire dead wood C pool in the temperate forest biome. We provide for the first time, robust empirical dead wood CFs to inform global forest C estimation.
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Carbono/análise , Madeira/química , Biodegradação Ambiental , Carbono/metabolismo , Ciclo do Carbono , Clima , Florestas , Estruturas Vegetais/química , Estruturas Vegetais/classificação , Árvores/química , Árvores/classificação , Madeira/metabolismoRESUMO
BACKGROUND: Forests provide the largest terrestrial sink of carbon (C). However, these C stocks are threatened by forest land conversion. Land use change has global impacts and is a critical component when studying C fluxes, but it is not always fully considered in C accounting despite being a major contributor to emissions. An urgent need exists among decision-makers to identify the likelihood of forest conversion to other land uses and factors affecting C loss. To help address this issue, we conducted our research in California, Colorado, Georgia, New York, Texas, and Wisconsin. The objectives were to (1) model the probability of forest conversion and C stocks dynamics using USDA Forest Service Forest Inventory and Analysis (FIA) data and (2) create wall-to-wall maps showing estimates of the risk of areas to convert from forest to non-forest. We used two modeling approaches: a machine learning algorithm (random forest) and generalized mixed-effects models. Explanatory variables for the models included ecological attributes, topography, census data, forest disturbances, and forest conditions. Model predictions and Landsat spectral information were used to produce wall-to-wall probability maps of forest change using Google Earth Engine. RESULTS: During the study period (2000-2017), 3.4% of the analyzed FIA plots transitioned from forest to mixed or non-forested conditions. Results indicate that the change in land use from forests is more likely with increasing human population and housing growth rates. Furthermore, non-public forests showed a higher probability of forest change compared to public forests. Areas closer to cities and coastal areas showed a higher risk of transition to non-forests. Out of the six states analyzed, Colorado had the highest risk of conversion and the largest amount of aboveground C lost. Natural forest disturbances were not a major predictor of land use change. CONCLUSIONS: Land use change is accelerating globally, causing a large increase in C emissions. Our results will help policy-makers prioritize forest management activities and land use planning by providing a quantitative framework that can enhance forest health and productivity. This work will also inform climate change mitigation strategies by understanding the role that land use change plays in C emissions.
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Changing forest disturbance regimes and climate are driving accelerated tree mortality across temperate forests. However, it remains unknown if elevated mortality has induced decline of tree populations and the ecological, economic, and social benefits they provide. Here, we develop a standardized forest demographic index and use it to quantify trends in tree population dynamics over the last two decades in the western United States. The rate and pattern of change we observe across species and tree size-distributions is alarming and often undesirable. We observe significant population decline in a majority of species examined, show decline was particularly severe, albeit size-dependent, among subalpine tree species, and provide evidence of widespread shifts in the size-structure of montane forests. Our findings offer a stark warning of changing forest composition and structure across the western US, and suggest that sustained anthropogenic and natural stress will likely result in broad-scale transformation of temperate forests globally.
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Monitorização de Parâmetros Ecológicos/tendências , Florestas , Dispersão Vegetal , Árvores , Mudança Climática , Conservação dos Recursos Naturais , Monitorização de Parâmetros Ecológicos/estatística & dados numéricos , Modelos Estatísticos , Análise Espacial , Estados UnidosRESUMO
Plant-fungal symbioses play critical roles in vegetation dynamics and nutrient cycling, modulating the impacts of global changes on ecosystem functioning. Here, we used forest inventory data consisting of more than 3 million trees to develop a spatially resolved "mycorrhizal tree map" of the contiguous United States. We show that abundances of the two dominant mycorrhizal tree groups-arbuscular mycorrhizal (AM) and ectomycorrhizal trees-are associated primarily with climate. Further, we show that anthropogenic influences, primarily nitrogen (N) deposition and fire suppression, in concert with climate change, have increased AM tree dominance during the past three decades in the eastern United States. Given that most AM-dominated forests in this region are underlain by soils with high N availability, our results suggest that the increasing abundance of AM trees has the potential to induce nutrient acceleration, with critical consequences for forest productivity, ecosystem carbon and nutrient retention, and feedbacks to climate change.