Disturbances shape the structure and composition of forests over a variety of timescales. Ecosystems, and their component species, typically exhibit traits and resilience mechanisms suited to their characteristic disturbance regime. But many disturbance regimes are changing with the warming climate. Compound disturbances comprise multiple events at the same location within short timeframes, which can have larger impacts compared to the individual events in isolation. Compound disturbances appear to be more likely to overwhelm resilience mechanisms of an ecosystem and trigger ecological regime shifts. However, empirical data assessments have largely not been used to evaluate the persistence of regime shifts triggered by compound disturbances. Here, we utilize a well-known and well-studied compound disturbance event in a subalpine forest for repeat, long-term evaluation of the same sites over time to ask if regime shifts triggered by compound disturbance events are maintained over time using paired t-tests. Further, we explore the topographic and spatial contexts of contemporary conditions using regressions. The compound disturbance pushed the system towards a new regime that persists over 20 years post-disturbance. Despite being rare prior to the compound disturbance event, quaking aspen established at high densities across the landscape. Lodgepole pine has maintained a presence since the compound event; however, densities have declined and there is less new regeneration compared to quaking aspen. Subalpine fir and Engelmann spruce were less common prior to disturbance and maintained their observed low post-disturbance densities. The return to pre-disturbance conditions is unlikely to occur within decades to centuries pending future disturbances.

Several of the largest amplifying feedbacks in the climate system—warming-induced emissions (WIE) of greenhouse gases from natural sources—remain absent from most climate models. Their absence risks systematic underestimation of projected warming. To assess the potential magnitude of these feedbacks, we derived relationships between global temperature and WIE rates from process-based model estimates across three Shared Socioeconomic Pathways, SSP1-2.6, SSP2-4.5, and SSP4-6.0. The warming-induced methane emission rate from permafrost, wetlands, freshwaters, and wildfire combined increases with temperature at 97 ± 6 Tg CH4 yr-1 ℃-1 across all three scenarios, while the warming-induced carbon dioxide emission rate from permafrost and wildfire combined increases at 7 ± 1 Pg CO2 yr-1 ℃-1 in SSP2-4.5 and SSP4-6.0. Using the MAGICC climate model, we projected that WIE could add 0.2–0.4 ℃ of warming by 2100 across scenarios, split roughly equally between carbon dioxide and methane, amplifying anthropogenic warming by 20–30%. Combined emission sensitivity and climate response uncertainties are ±0.2 ℃ on the added warming and ±10–30% on the warming amplification. Until Earth system models comprehensively incorporate WIE, climate projections are likely to underestimate future warming and overestimate remaining carbon budgets.

Abstract Enhanced weathering in agriculture is a potential gigatonne-scale carbon dioxide removal (CDR) pathway, but its potential remains difficult to constrain. We used a formal expert elicitation process to estimate CDR potential and efficiency, uncertainties, and key data needs for six feedstocks. Expert opinion of global potential varied by feedstock, with estimates averaging 0.2-0.7 Gt CO2e/yr, but with a wide range (from a source to greater than 5 Gt CO2e/yr removal). When focusing on the American Midwest (pH 5.5-6), carbon dioxide removal efficiency, meaning the fraction of potential ultimately realized, ranged from 27-39%. Key uncertainties included feedstock availability, calcite saturation, and deep soil/freshwater emission pathways. There is a need for empirical data in key stages, with potential to leverage liming data where appropriate. Overall, there appears to be strong potential CDR at broad scales. However, continued research is necessary to build confidence when quantifying that potential and actual removals.

Global-scale peatland restoration holds large potential for carbon sequestration; however, the peatland carbon balance is not often considered alongside co-benefits in restoration prioritization. Here, we present a spatial optimization framework for inland peatland restoration to minimize greenhouse gas (GHG) emissions and maximize peatland co-benefits, such as flood mitigation and water quality improvements. We find strategic restoration of 30% of the world's drained inland peatlands, targeting areas with the greatest potential for GHG emissions reductions, would sequester three times more GHGs (0.91 ± 0.17 Pg CO2eq. year-1) than the same magnitude of peatland restoration implemented randomly (0.27 ± 0.11 Pg CO2eq. year-1). Peatland restoration is often driven by local needs for the many ecosystem services that peatlands provide; therefore, we also quantify the GHG balance of restoration aimed at delivering either water quality improvements or flood mitigation. Meeting a 30% global inland peatland restoration target while prioritizing water quality improvements or flood mitigation can still achieve emissions reductions of 0.34 ± 0.14 and 0.50 ± 0.19 Pg CO2eq. year-1 (62% and 44% less emissions reductions than prioritizing emissions alone), respectively, demonstrating opportunities for overlap between global GHG budgets and local environmental objectives. Finally, we use future methane (CH4) emissions projections to evaluate the compatibility of peatland restoration prioritization schemes with future CH4 emissions. We find that priority regions for near-term GHG emissions reduction do not necessarily align with areas that would minimize future peatland CH4 emissions, due to increasing CH4 emissions by 2100. We account for uncertainty and variability in long-term emission trajectories of peatland restoration from diverse settings, site histories, and practices by testing our optimization framework with two alternate endpoint scenarios: "recently rewetted" and "restored to intact conditions." Our framework highlights numerous opportunities for inland peatland restoration to simultaneously achieve both near- and long-term emission reductions as well as multiple co-benefits. Broad-scale restoration strategies can be employed in concert with planning for regional needs and site-specific criteria to magnify the benefits of peatland restoration.

Bioclimatic feedbacks, driven by anthropogenic warming, produce indirectly human-caused emissions that contribute to a significant discrepancy between models, quantification frameworks, and atmospheric change. This discrepancy threatens climate ambitions, but policy is ill equipped to quantify the threat. Under two scenarios (SSP 1-1.9, roughly aligned with Paris Agreement goals and SSP 2-4.5, roughly current trajectory), thawing permafrost, increasing circumboreal fires, and warming tropical wetlands increase CO2 emissions by '15 to '300 Tg C year-1 and CH4 by '17 to '50 Tg C year-1 above 2020 levels by 2050, lessening time to the 1.5 degrees C and 2.0 degrees C Paris thresholds by '21%-25%. Policy frameworks and tools for quantifying/reporting indirect emissions from managed and unmanaged lands should be developed. The Earth system modeling community could inform this effort and would benefit from additional data. Ultimately, increased mitigation ambition to compensate for indirect emissions will likely proceed only if processes are measured and reported.

Methane measurements, particularly of natural sources, need to be expanded considerably.

Strategies to remove carbon dioxide from the atmosphere, known as carbon dioxide removal (CDR), are being pursued given the urgency of climate change. However, CDR measures may unintentionally increase emissions of other climate forcers. If emissions of potent short-lived climate forcers (like methane) are increased, the CDR mechanism could potentially worsen climate change in the near-term despite benefiting the climate in the long-term. This temporal trade-off can be easily overlooked when employing the standard climate metric used for assessments— carbon dioxide equivalent (CO _2 e) using a 100 year global warming potential (GWP)—because it solely conveys the long-term warming impacts of a pulse of emissions. A more sophisticated assessment method is needed to reveal potential temporal trade-offs in climate benefits—important information for effective decision making. In this study, we compare three climate impact assessment approaches of increasing complexity to evaluate temporal trade-offs in climate benefits from CDR strategies: (1) the standard CO _2 e using GWP approach with both 20 and 100 year time horizons (GWP20 and GWP100, respectively, or dual-valued CO _2 e); (2) a variation of GWP that considers the climate impact of continuous emissions over time (known as technology warming potential (TWP); and (3) reduced complexity climate models. We use wetland restoration as a case study because studies have shown that it may remove carbon dioxide from the atmosphere, while also increasing methane emissions. Analyzing eleven rewetting scenarios, we find that all approaches identify temporal tradeoffs. The TWP and reduced complexity climate model results are largely consistent and reveal drawbacks of the dual-valued CO _2 e that considers pulse rather than continuous emissions. Given the accessibility of the TWP approach relative to reduced complexity climate models, we recommend its use for most stakeholders. Overall, our findings emphasize the need to thoroughly assess potential climate trade-offs of CDR measures across all timescales.

Wind is among one of the most frequent drivers of forest disturbance around the world. Wind disturbance (blowdown, windthrow) results from particular meteorological conditions, where wind gust speed is a key factor. Blowdown is conditioned also by wind direction together with local topography, and influence the soil disturbance due to tree uprooting.We mapped and analyzed the large-scale 2020 blowdown in the spruce-fir subalpine forest on the western slope of the Front Range, Rocky Mountains (Colorado, US). The area of interest (AOI) is a 9 x 29 km rectangle (39.80° N, 105.77° W and 40.06° N, 105.67° W) located south of the Rocky Mountain National Park and north of the Berthoud Pass. The mapping focused on developing and automating the workflow based on Sentinel 2 data and Change Vector Analysis (CVA) and comparing its output with the Global Forest Change (GFC) data. The CVA mapping is based on 1) the difference image computed using post- and pre-event images, and 2) the parameters calculated using two bands of the difference image: magnitude (mgt) representing the amount of change, and direction (drct) referring to the type of change. To create the CVA output, we used bands 11 and 12, together with 40° < drct < 47° and mgt > 0.1. Both CVA output and GFC data have a true positive rate (TPR) of 66-67%, with a false positive rate (FPR) of 0.9% and 3%, respectively. The CVA can be adjusted to achieve TPR up to 75.5%, of which FPR was 5.8%. Our approach is based on an unsupervised method, and open-source data, and is fully automated using R. Using CVA, the blowdown area was estimated to 1379.7 ha. The comparison between GFC data and CVA output revealed the higher efficiency of CVA for small patches with intensive damage. GFC data were better for indicating the location of patches with lower damage intensity.We also aimed to capture different environmental insights related to the meteorological conditions causing the blowdown, soil disturbance patterns, and the impact of topography. Large-scale blowdowns are infrequent in the Rockies and are usually associated with the occurrence of unusual meteorological conditions. The blowdown was caused by strong easterly winds (gusts of 30 m•s⁻¹) blowing on September 7th - 9th, 2020, associated with the passage of a cold front causing exceptionally early late-summer cooling. The blowdown patches distribution generally followed the run of the valleys and ridges (SE-NW), with large patches in southern and central parts, and smaller ones in the northern part. The blowdown caused soil disturbance, with root plate volumes of 0.1 – 0.8 m3. The bearings of uprooted tree stems followed the direction of the main wind currents reported in the climate time series. Our approach can be valuable for research on blowdown mapping and triggering factors, GFC data assessment, soil disturbance, and interplays with relief.The study has been supported by the Polish National Science Centre (project no. 2019/35/O/ST10/00032) and by the Polish National Agency for Academic Exchange (agreement no. PPN/STA/2021/1/00081/U/00001).

Earth-system feedback loops that exacerbate climate warming cause concern for both climate accounting and progress towards meeting international climate agreements. Methane emissions from wetlands are on the rise owing to climate change-a large and difficult-to-abate source of greenhouse gas that may be considered indirectly anthropogenic. Here we illustrate the power of emissions reduction from any sector for slowing the progress of earth-system feedbacks.

Forested landscapes have the potential to help offset global carbon emissions. However, current global models do not, nor are they intended to, capture the fine‐scale variability of the distributions of carbon in aboveground or belowground stocks or their simultaneous variability. Regional investigations are necessary to resolve patterns in carbon that can guide policy and planning, but regional maps that quantify multiple carbon pools are scarce. We quantified the spatial relationships of aboveground and belowground carbon stocks to understand their simultaneous variability across the forested area of the perhumid ecoregion of the Pacific Coastal Temperate Rainforest. Further, we identified topo‐climatic contexts associated with unique patterns in both aboveground and belowground carbon stocks by conducting an overlay analysis across the entire ecoregion. We utilized previously published estimates of carbon stocks based on extensive governmental data and machine learning techniques to model simultaneous spatial relationships of aboveground and belowground carbon stocks and generate a map for a high carbon region. We employed Pearson's correlations as well as ANOVA and Tukey honestly significant difference (HSD) tests for comparisons of topography and climate. Approximately 25% (2.6 million ha) of the area across the perhumid ecoregion had similar trends in aboveground and belowground stocks (convergence). Likewise, 20% of the ecoregion had opposite trends of aboveground and belowground stocks (divergence), and 56% of the ecoregion experienced no relationship (moderate conditions) between aboveground and belowground stocks. Convergence areas consist of carbon hotspots associated with 1.3 million ha and 794 Mg C ha −1 on average, or carbon cold spots associated with 1.2 million ha and 224 Mg C ha −1 . Areas with convergence, divergence, and moderate carbon stocks all had unique associations with slope, elevation, aspect, mean annual precipitation, and annual mean temperature. High levels of aboveground carbon were associated with steeper slopes, while high levels of belowground carbon were associated with high levels of precipitation. The interactions between slope, precipitation, and temperature correspond with carbon convergence and divergence, likely due to water accumulation which impacts the decomposition of organic matter in soil. These data are critical to regional planning and carbon policy and inform expectations for future carbon storage as the climate changes.

As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned-unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost-wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone.

Fine-root traits are important for understanding the strategies plant species use to coexist in communities and persist in resource-limited environments. The extent to which aboveground and belowground strategies are coordinated is a continued subject of debate, and the role of fine-root traits in determining species responses to disturbance is largely unknown. We measured fine-root traits representing the conservation and collaboration axes of the root economics space and leaf traits associated with the leaf economics spectrum of 56 understory species across 75 plots that experienced a canopy opening disturbance 10 years prior in Wyoming, USA. We used principal component analysis to assess the coordination of aboveground and belowground strategies, and linear models to assess the relative importance of aboveground and belowground traits at explaining the change in understory species cover. Traits related to the leaf economics spectrum (leaf dry matter content, leaf nitrogen) and the root conservation axis (root nitrogen, root tissue density) aligned with each other, but were orthogonal to the root collaboration axis (root diameter, specific root length) and aboveground plant height. Fine-root traits did not explain any additional variation in the response of understory species cover to disturbance beyond the variation explained by vegetative height and pre-disturbance species frequency. We provide further evidence for the coordination of aboveground and belowground economics strategies. Our results suggest that competition for light is more important than competition for resources belowground following the widespread disturbance that opened the canopy but did not physically perturb the soil or understory.

Wind disturbance (blowdown, windthrow) results from particular meteorological conditions, where wind gust speed is a key factor. We map and analyze the 2020 blowdown in the Colorado Front Range (CFR), US. We (1) develop and test a tunable blowdown mapping workflow based on Sentinel 2 data and change vector analysis (CVA) and compare its output with the Global Forest Change (GFC) data, (2) explore soil disturbance patterns, and (3) analyze the impact of topography on blowdown occurrence. The CVA mapping is based on (1) the difference image computed using post- and pre-event images and (2) the parameters calculated using two bands of the difference image: magnitude representing the amount of change and direction referring to the type of change. The methodology is tunable for desired error characteristics, for example, true positive vs. false positive rates. For our test analysis, we balanced the CVA output and GFC data at a true positive rate (TPR) of 66%-67%, with a false positive rate (FPR) of 0.9% and 3%, respectively. The CVA can be adjusted to achieve a TPR up to 88.7%, which increases the FPR to 17.8%. In our test landscape, the blowdown led to soil disturbances, with root plate volumes of 0.1-0.8 m3.

Spatially explicit global estimates of forest carbon storage are typically coarsely scaled. While useful, these estimates do not account for the variability and distribution of carbon at management scales. We asked how climate, topography, and disturbance regimes interact across and within geopolitical boundaries to influence tree biomass carbon, using the perhumid region of the Pacific Coastal Temperate Rainforest, an infrequently disturbed carbon dense landscape, as a test case. We leveraged permanent sample plots in southeast Alaska and coastal British Columbia and used multiple quantile regression forests and generalized linear models to estimate tree biomass carbon stocks and the effects of topography, climate, and disturbance regimes. We estimate tree biomass carbon stocks are either 211 (SD = 163) Mg C ha-1 or 218 (SD = 169) Mg C ha-1. Natural disturbance regimes had no correlation with tree biomass but logging decreased tree biomass carbon and the effect diminished with increasing time since logging. Despite accounting for 0.3% of global forest area, this forest stores between 0.63% and 1.07% of global aboveground forest carbon as aboveground live tree biomass. The disparate impact of logging and natural disturbance regimes on tree biomass carbon suggests a mismatch between current forest management and disturbance history.

Understanding what regulates ecosystem functional responses to disturbance is essential in this era of global change. However, many pioneering and still influential disturbance-related theorie proposed by ecosystem ecologists were developed prior to rapid global change, and before tools and metrics were available to test them. In light of new knowledge and conceptual advances across biological disciplines, we present four disturbance ecology concepts that are particularly relevant to ecosystem ecologists new to the field: (a) the directionality of ecosystem functional response to disturbance; (b) functional thresholds; (c) disturbance-succession interactions; and (d) diversity-functional stability relationships. We discuss how knowledge, theory, and terminology developed by several biological disciplines, when integrated, can enhance how ecosystem ecologists analyze and interpret functional responses to disturbance. For example, when interpreting thresholds and disturbance-succession interactions, ecosystem ecologists should consider concurrent biotic regime change, non-linearity, and multiple response pathways, typically the theoretical and analytical domain of population and community ecologists. Similarly, the interpretation of ecosystem functional responses to disturbance requires analytical approaches that recognize disturbance can promote, inhibit, or fundamentally change ecosystem functions. We suggest that truly integrative approaches and knowledge are essential to advancing ecosystem functional responses to disturbance.

AbstractNitrous oxide (N2O) is a significant greenhouse gas and the most important currently emitted ozone depleting substance, primarily via agricultural fertilization. Current N2O emission estimation methods at the national scale are predominantly via emission factors. Models estimating national‐scale emissions are focused on growing season emissions. However, a substantial fraction of N2O can be emitted during non‐growing season periods. Using newly published off‐season N2O emission ratio maps and high‐resolution nitrogen application data, this study explores the potential magnitude of underestimated N2O emissions if using only the default growing‐season focused methodology. Although there is large variation at county scales (12%–35%), non‐growing season national emissions are estimated at 31% of the total, a potential 12,000 Gg CO2e year−1. Further work should better refine emission estimates spatially as well as fully integrate estimates across growing and non‐growing seasons.

Fire frequency in boreal forests has increased via longer burning seasons, drier conditions, and higher temperatures. However, fires have historically self-regulated via fuel limitations, mediating the effects of changes in climate and fire weather. Early post-fire boreal forests (10-15 years postfire) are often dominated by mixed conifer-broadleaf or broadleaf regeneration, considered less flammable due to the higher foliar moisture of broadleaf trees and shrubs compared to their more intact conifer counterparts. However, the strength of selfregulation in the context of changing fire weather and climate combined with the emergence of novel broadleaf forest communities and structures remains unclear. We quantified fuel composition, abundance, and structure in burned and reburned forests in Interior Alaska and used a physics-based fire behavior model (the Wildland-Urban Interface Fire Dynamics Simulator) to simulate how these unique patterns of fuel influence potential rates and sustainability of fire spread. In once-burned forests dominated by mixed conifer-broadleaf regeneration, extreme fire weather conditions allowed for sustained fire spread, suggesting that intense fire conditions can enable reburning, even 10 to 15 years following a previous high-severity fire. However, fire spread was not sustained in thrice-burned regenerating broadleaf forests, where regeneration was often dense but more clumped, and thus less connected, separated by patches of bare soil. Crown fire traveled an average of 50 meters into thrice-burned forests before dying out, even under extreme fire weather conditions. This work suggests that fire spread may be possible in once-burned regenerating forests under extreme fire weather conditions but may be more limited in less connected and less fuel abundant thrice-burned regenerating forests, at least within the 10-15-year window post-fire.