Freeze-thaw cycles (FTC) alter soil function through changes to physical organization of the soil matrix and biogeochemical processes. Understanding how dynamic climate and soil properties influence FTC may enable better prediction of ecosystem response to changing climate patterns. In this study, we quantified FTC occurrence and frequency across 40 National Ecological Observatory Network (NEON) sites. We used site mean annual precipitation (MAP) and mean annual temperature (MAT) to define warm and wet, warm and dry, and cold and dry climate groupings. Site and soil properties, including MAT, MAP, maximum-minimum temperature difference, aridity index, precipitation as snow (PAS), and organic mat thickness, were used to characterize climate groups and investigate relationships between site properties and FTC occurrence and frequency. Ecosystem-specific drivers of FTC provided insight into potential changes to FTC dynamics with climate warming. Warm and dry sites had the most FTC, driven by rapid diurnal FTC close to the soil surface in winter. Cold and dry sites were characterized by fewer, but longer-duration FTC, which mainly occurred in spring and increased in number with higher organic mat thickness (Spearman's  = 0.97,  < 0.01). The influence of PAS and MAT on the occurrence of FTC depended on climate group (binomial model interaction (χ) < 0.05), highlighting the role of a persistent snowpack in buffering soil temperature fluctuations. Integrating ecosystem type and season-specific FTC patterns identified here into predictive models may increase predictive accuracy for dynamic system response to climate change.

The oceans play a pivotal role in mitigating climate change by sequestering approximately 25% of annually emitted carbon dioxide (CO). High-latitude oceans, especially the Arctic continental shelves, emerge as crucial CO sinks due to their cold, low saline, and highly productive ecosystems. However, these heterogeneous regions remain inadequately understood, hindering accurate assessments of their carbon dynamics. This study investigates variation in CO levels during peak ice sheet melt, in the Greenland coastal ocean and estimates rates of air-sea exchange across 6° of latitude. The East and West coast of Greenland displayed distinct regions with unique controlling factors. Though, both coasts represent CO sinks in summer. Geographical variation in CO and air-sea exchange was linked intricately to freshwater export from the Greenland ice sheet and levels of primary production in these ecosystems. Air-sea exchange of CO ranged from 0.23 to -64 mmol m day. However, we found that flux estimation faces substantial uncertainties (up to 672%) due to wind product averaging and gas exchange formula selection. Upscaling only heightens this uncertainty leading to wide ranging estimates of Greenland coastal CO uptake between -16 and -26 Tg C year (This study, Dai et al., 2022, https://doi.org/10.1146/annurev-earth-032320-090746; Laruelle et al., 2014, https://doi.org/10.1002/2014gb004832). Obtaining a reliable assessment of air-sea CO exchange necessitates data collection across seasons, and, even more so, refinement of the gas transfer velocity estimations in the Arctic coastal zone.

Temperate lakes worldwide are losing ice cover but the implications for under-ice thermal dynamics are poorly constrained. Using a 92-year record of ice phenology from a temperate and historically dimictic lake, we examined trends, variability, and drivers of ice phenology and under-ice temperatures. The onset of ice formation decreased by 23 days century, which can be largely attributed to warming air temperatures. Ice-off date has become substantially more variable with spring air temperatures and cumulative February through April snowfall explaining over 80% of the variation in timing. As a result of changing ice phenology, total ice duration contracted by a month and more than doubled in interannual variability. Using weekly under-ice temperature profiles for the most recent 36 years, we found that shorter ice duration decreased winter inverse stratification and was associated with an extended spring mixing period. We illustrate the limitations of relying on discrete ice clearance dates in our assumptions around under-ice thermal dynamics by presenting high-frequency under-ice observations in two recent winters: one with intermittent ice cover and a year with slow spring ice clearance.

Decision makers need to know the drivers of surface water phosphorus (P) concentrations, the environmental factors that mediate P loading in freshwater systems, and where pollution sources and mediating factors are co-located to inform water quality restoration efforts. To provide this information, publicly available spatial data sets of P pollution sources and relevant environmental variables, like temperature, precipitation, and agricultural soil erodibility, were matched with >7,000 stream and lake total P observations throughout the conterminous United States. Using three statistical approaches, consisting of (a) correlation, (b) regression, and (c) machine learning techniques, we identified likely drivers of P concentrations. Surface water concentrations in streams were more strongly correlated and effectively predicted by annual fertilizer and manure input rates and agricultural legacy sources compared to that of lakes. This observation suggests that streams may be more immediately responsive to improvements in agricultural nutrient management. In contrast, lake concentrations, though still positively associated with agricultural input and surplus variables, may be more influenced by historic erosional inputs, internal lake recycling, and other environmental factors. Thus, lake TP concentrations may not be as immediately responsive as streams to improvements in phosphorus management. Both stream and lake P concentrations will potentially increase because of warming temperatures and forest recovering from past acidification, putting even further pressure on existing water quality restoration efforts to meet nutrient loading reduction targets. The identified spatial data sets and relationships elucidated in this effort can inform the placement and development of watershed restoration strategies to reduce excess P in aquatic systems.

Measurements of ecosystem carbon (C) fluxes in temperate forests are concentrated in the Northern Hemisphere, leaving the functionally diverse temperate forests in the Southern Hemisphere underrepresented. Here, we report three years (February 2018-January 2021) of C fluxes, studied with eddy-covariance and closed chamber techniques, in an endangered temperate evergreen rainforest of the long-lived paleoendemic South American conifer . Using classification and regression trees we analyzed the most relevant drivers and thresholds of daily net ecosystem exchange (NEE) and soil respiration. The annual NEE showed that the forest was a moderate C sink during the period analyzed (-287±38 g C m year ). We found that the capacity to capture C of the rainforests in the Coastal Range of southern Chile is optimal under cool and rainy conditions in the early austral spring (October-November) and decreases rapidly towards the summer dry season (January-February) and autumn. Although the studied forest type has a narrow geographical coverage, the gross primary productivity measured at the tower was highly representative of and other rainforests in the region. Our results suggest that C fluxes in paleoendemic cool forests may be negatively affected by the warming and drying predicted by climate change models, reinforcing the importance of maintaining this and other long-term ecological research sites in the Southern Hemisphere.

Observations of planet Earth from space are a critical resource for science and society. Satellite measurements represent very large investments and United States (US) agencies organize their effort to maximize the return on that investment. The US National Research Council conducts a survey of Earth science and applications to prioritize observations for the coming decade. The most recent survey prioritized a visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager to meet a range of needs for studying Surface Biology and Geology (SBG). SBG will be the premier integrated observatory for observing the emerging impacts of climate change by characterizing the diversity of plant life and resolving chemical and physiological signatures. It will address wildfire risk, behavior, and recovery as well as responses to hazards such as oil spills, toxic minerals in minelands, harmful algal blooms, landslides, and other geological hazards. The SBG team analyzed needed instrument characteristics (spatial, temporal, and spectral resolutions, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. We present an overview of the Research and Applications trade-study analysis of algorithms, calibration and validation needs, and societal applications with specifics of substudies detailed in other articles in this special collection. We provide a value framework to converge from hundreds down to three candidate architectures recommended for development. The analysis identified valuable opportunities for international collaboration to increase the revisit frequency, adding value for all partners, leading to a clear measurement strategy for an observing system architecture.

The Arctic Ocean is surrounded by land that feeds highly seasonal rivers with water enriched in high concentrations of dissolved and particulate organic carbon (DOC and POC). Explicit estimates of the flux of organic carbon across the land-ocean interface are difficult to quantify and many interdependent processes makes source attribution difficult. A high-resolution 3-D biogeochemical model was built for the lower Yukon River and coastal ocean to estimate biogeochemical cycling across the land-ocean continuum. The model solves for complex reactions related to organic carbon transformation, including mechanistic photodegradation and multi-reactivity microbial processing, DOC-POC flocculation, and phytoplankton dynamics. The baseline DOC and POC flux out of the delta from April to September 2019, was 977 and 536 Gg C (∼80% of the annual total), but only 50% of the DOC and 25% of the POC exited the plume across the 10 m isobath. Microbial breakdown of DOC accounted for a net loss of 168 Gg C (17% of delta export) within the plume and photodegradation accounted for a net loss of 46.6 Gg C DOC (5% of delta export) in 2019. Flocculation decreased the total organic carbon flux by only 6.4 Gg C (∼1%), while POC sinking accounted for 63.3 Gg C (10%) settling in the plume. The loss of chromophoric dissolved organic matter due to photodegradation increased the light available for phytoplankton growth throughout the coastal ocean, demonstrating the secondary effects that organic carbon reactions can have on biological processes and the net coastal carbon flux.

Stable carbon isotopes in plants can help evaluate and improve the representation of carbon and water cycles in land-surface models, increasing confidence in projections of vegetation response to climate change. Here, we evaluated the predictive skills of the Joint UK Land Environmental Simulator (JULES) to capture spatio-temporal variations in carbon isotope discrimination (ΔC) reconstructed by tree rings at 12 sites in the United Kingdom over the period 1979-2016. Modeled and measured ΔC time series were compared at each site and their relationships with local climate investigated. Modeled ΔC time series were significantly correlated ( < 0.05) with tree-ring ΔC at eight sites, but JULES underestimated mean ΔC values at all sites, by up to 2.6‰. Differences in mean ΔC may result from post-photosynthetic isotopic fractionations that were not considered in JULES. Inter-annual variability in ΔC was also underestimated by JULES at all sites. While modeled ΔC typically increased over time across the UK, tree-ring ΔC values increased only at five sites located in the northern regions but decreased at the southern-most sites. Considering all sites together, JULES captured the overall influence of environmental drivers on ΔC but failed to capture the direction of change in ΔC caused by air temperature, atmospheric CO and vapor pressure deficit at some sites. Results indicate that the representation of carbon-water coupling in JULES could be improved to reproduce both the trend and magnitude of interannual variability in isotopic records, the influence of local climate on ΔC, and to reduce uncertainties in predicting vegetation-environment interactions.

The forests of south-central Chile are facing a drying climate and a megadrought that started in 2010. This study addressed the physiological responses of five stands across the Mediterranean-Temperate gradient (35.9 ° -40.3° S) using carbon isotope discrimination (Δ C) and intrinsic water use efficiency (iWUE) in tree rings during 1967-2017. Moreover, δO was evaluated in the northernmost site to better understand the effects of the megadrought in this drier location. These forests have become more efficient in their use of water. However, trees from the densest stand are discriminating more against C, probably due to reduced photosynthetic rates associated with increasing competition. The strongest associations between climate and ΔC were found in the northernmost stand, suggesting that warmer and drier conditions could have reduced C discrimination. Tree growth in this site has not decreased, and δO was negatively related to annual rainfall. However, a shift in this relationship was found since 2007, when both precipitation and δO decreased, while correlations between δO and growth increased. This implies that tree growth and δO are coupled in recent years, but precipitation is not the cause, suggesting that trees probably changed their water source to deeper and more depleted pools. Our research demonstrates that forests are not reducing their growth in central Chile, mainly due to a shift towards the use of deeper water sources. Despite a common climate trend across the gradient, there is a non-uniform response of forests to climate drying, being their response site specific. Keywords: Tree rings, stable isotopes, tree physiology, climate gradient, megadrought, climate change.

Long-running eddy covariance flux towers provide insights into how the terrestrial carbon cycle operates over multiple timescales. Here, we evaluated variation in net ecosystem exchange (NEE) of carbon dioxide (CO) across the Chequamegon Ecosystem-Atmosphere Study AmeriFlux core site cluster in the upper Great Lakes region of the USA from 1997 to 2020. The tower network included two mature hardwood forests with differing management regimes (US-WCr and US-Syv), two fen wetlands with varying levels of canopy sheltering and vegetation (US-Los and US-ALQ), and a very tall (400 m) landscape-level tower (US-PFa). Together, they provided over 70 site-years of observations. The 19-tower Chequamegon Heterogenous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 campaign centered around US-PFa provided additional information on the spatial variation of NEE. Decadal variability was present in all long-term sites, but cross-site coherence in interannual NEE in the earlier part of the record became weaker with time as non-climatic factors such as local disturbances likely dominated flux time series. Average decadal NEE at the tall tower transitioned from carbon source to sink to near neutral over 24 years. Respiration had a greater effect than photosynthesis on driving variations in NEE at all sites. Declining snowfall offset potential increases in assimilation from warmer springs, as less-insulated soils delayed start of spring green-up. Higher CO increased maximum net assimilation parameters but not total gross primary productivity. Stand-scale sites were larger net sinks than the landscape tower. Clustered, long-term carbon flux observations provide value for understanding the diverse links between carbon and climate and the challenges of upscaling these responses across space.

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species-specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing.

In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH) flux. In the first part of the study, we used a CH release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint-Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m s whereas background flux from the open water were on average 15.2 ± 7.5 nmol m s. This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy-covariance towers and creates important insights for the interpretation of hot spots of CH flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH flux.

High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.

Lakes have been highlighted as one of the largest natural sources of the greenhouse gas methane (CH) to the atmosphere. However, global estimates of lake CH fluxes over the last 20 years exhibit widely different results ranging from 6 to 185 Tg CH yr, which is to a large extent driven by differences in lake areas and thaw season lengths used. This has generated uncertainty regarding both lake fluxes and the global CH budget. This study constrains global lake water CH emissions by using new information on lake area and distribution and CH fluxes distinguished by major emission pathways; ecoclimatic lake type; satellite-derived ice-free emission period length; and diel- and temperature-related seasonal flux corrections. We produced gridded data sets at 0.25° latitude × 0.25° longitude spatial resolution, representing daily emission estimates over a full annual climatological cycle, appropriate for use in global CH budget estimates, climate and Earth System Models, bottom-up biogeochemical models, and top-down inverse model simulations. Global lake CH fluxes are 41.6 ± 18.3 Tg CH yr with approximately 50% of the flux contributed by tropical/subtropical lakes. Strong temperature-dependent flux seasonality and satellite-derived freeze/thaw dynamics limit emissions at high latitudes. The primary emission pathway for global annual lake fluxes is ebullition (23.4 Tg) followed by diffusion (14.1 Tg), ice-out and spring water-column turnover (3.1 Tg), and fall water-column turnover (1.0 Tg). These results represent a major contribution to reconciling differences between bottom-up and top-town estimates of inland aquatic system emissions in the global CH budget.

The Gulf of Maine North Atlantic Time Series (GNATS) has been run since 1998, across the Gulf of Maine (GoM), between Maine and Nova Scotia. GNATS goals are to provide ocean color satellite validation and to examine change in this coastal ecosystem. We have sampled hydrographical, biological, chemical, biogeochemical, and bio-optical variables. After 2008, warm water intrusions (likely North Atlantic Slope Water [NASW]) were observed in the eastern GoM at 50-180 m depths. Shallow waters (<50 m) significantly warmed in winter, summer, and fall but during spring. Surface salinity and density of the GoM also significantly increased over the 20 years. Phytoplankton standing stock and primary production showed highly-significant decreases during the period. Concentrations of phosphate increased, silicate decreased, residual nitrate [N*; nitrate-silicate] increased, and the ratio of dissolved inorganic nitrogen:phosphate decreased, suggesting increasing nitrogen limitation. Dissolved organic carbon (DOC) and its optical indices generally increased over two decades, suggesting changes to the DOC cycle. Surface seawater carbonate chemistry showed winter periods where the aragonite saturation (Ω) dropped below 1.6 gulf-wide due to upward winter mixing of cool, corrosive water. However, associated with increased average GoM temperatures, Ω has significantly increased. These results reinforce the hypothesis that the observed decrease in surface GoM primary production resulted from a switch from Labrador Sea Water to NASW entering the GoM. A multifactor analysis shows that decreasing GoM primary production is most significantly correlated to decreases in chlorophyll and particulate organic carbon plus increases in N* and temperature.

Biogenic volatile organic compound (BVOC) flux dynamics during the subarctic autumn are largely unexplored and have been considered insignificant due to the relatively low biological activity expected during autumn. Here, we exposed subarctic heath ecosystems to predicted future autumn climate scenarios (ambient, warming, and colder, dark conditions), changes in light availability, and flooding, to mimic the more extreme rainfall or snowmelt events expected in the future. We used climate chambers to measure the net ecosystem fluxes and bidirectional exchange of BVOCs from intact heath mesocosms using a dynamic enclosure technique coupled to a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS). We focused on six BVOCs (methanol, acetic acid, acetaldehyde, acetone, isoprene, and monoterpenes) that were among the most dominant and that were previously identified in arctic tundra ecosystems. Warming increased ecosystem respiration and resulted in either net BVOC release or increased uptake compared to the ambient scenario. None of the targeted BVOCs showed net release in the cold and dark scenario. Acetic acid exhibited significantly lower net uptake in the cold and dark scenario than in the ambient scenario, which suggests reduced microbial activity. Flooding was characterized by net uptake of the targeted BVOCs and overruled any temperature effects conferred by the climate scenarios. Monoterpenes were mainly taken up by the mesocosms and their fluxes were not affected by the climate scenarios or flooding. This study shows that although autumn BVOC fluxes on a subarctic heath are generally low, changes in future climate may strongly modify them.

Primary productivity in the ocean plays a major role in the global carbon cycle. To estimate its changes through geological time, different sedimentary proxies are used. However, the relative weights of the various processes driving the sedimentary accumulation of organic matter are not fully constrained or represent the flux of specific algal classes. Here, we compare sea-surface chlorophyll- (SSchla) abundance estimated from remote sensing data over the last 20 years with the sedimentary concentration of its derivatives (i.e., chlorin) on a suite of 140 core-top sediments from different biogeochemical regions. We estimate with field data that only 0.33% of SSchla in tropical and subtropical regions is transferred to surface sediments in the form of chlorin. Despite the small fraction of chlorin that arrive to the sea-floor, the sedimentary spatial distribution of chlorin is driven primarily by SSchla concentration in high and moderate productivity locations (SSchla > 0.20 mg·m). Our calibration paves the way for the use of chlorin as quantitative proxies of primary productivity in paleoreconstructions and cautions on their use in low primary productivity settings.

Quantifying air-water gas exchange is critical for estimating greenhouse gas fluxes and metabolism in aquatic ecosystems. In high-energy streams, the gas exchange rate is poorly constrained, due to an incomplete understanding of turbulence and bubble contributions to . We performed a flume experiment with air bubble additions to evaluate the combined effects of turbulence and bubbles on for helium, argon, xenon, and methane. We created contrasting hydraulic conditions by varying channel slope, bed roughness, water discharge, and bubble flux. We found that increased from 1-4 to 17-66 m d with increases in turbulence and bubble flux metrics. Mechanistic models that explicitly account for these metrics, as well as gas diffusivity and solubility, agreed well with the data and indicated that bubble-mediated gas exchange accounted for 64-93% of . Bubble contributions increased with bubble flux but were independent of gas type, as bubbles did not equilibrate with the water. This was evident through modeled bubble life and equilibration times inferred from bubble size distributions obtained from underwater sound spectra. Sound spectral properties correlated well with turbulence and bubble flux metrics. Our results demonstrate that (a) mechanistic models can be applied to separate free surface- and bubble-mediated gas exchange in running waters, (b) bubble life and equilibration times are critical for accurate scaling of between different gases, and (c) ambient sound spectra can be used to approximate contributions of turbulence and bubbles.

Bidirectional reflectance distribution function (BRDF) effects are a persistent issue for the analysis of vegetation in airborne imaging spectroscopy data, especially when mosaicking results from adjacent flightlines. With the advent of large airborne imaging efforts from NASA and the U.S. National Ecological Observatory Network (NEON), there is increasing need for methods that are flexible and automatable across images with diverse land cover. Flexible bidirectional reflectance distribution function (FlexBRDF) is built upon the widely used kernel method, with additional features including stratified random sampling across flightline groups, dynamic land cover stratification by normalized difference vegetation index (NDVI), interpolation of correction coefficients across NDVI bins, and the use of a reference solar zenith angle. We demonstrate FlexBRDF using nine long (150-400 km) airborne visible/infrared imaging spectrometer (AVIRIS)-Classic flightlines collected on 22 May 2013 over Southern California, where diverse land cover and a wide range of solar illumination yield significant BRDF effects. We further test the approach on additional AVIRIS-Classic data from California, AVIRIS-Next Generation data from the Arctic and India, and NEON imagery from Wisconsin. Comparison of overlapping areas of flightlines show that models built from multiple flightlines performed better than those built for single images (root mean square error improved up to 2.3% and mean absolute deviation 2.5%). Standardization to a common solar zenith angle among a flightline group improved performance, and interpolation across bins minimized between-bin boundaries. While BRDF corrections for individual sites suffice for local studies, FlexBRDF is an open source option that is compatible with bulk processing of large airborne data sets covering diverse land cover needed for calibration/validation of forthcoming spaceborne imaging spectroscopy missions.

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond to (resistance) and recover from (resilience) rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the Ecosystem Demography-2.2 (ED-2.2) model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900 (approximating the clear-cut conditions at the time), and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes such as gross primary production (GPP), and interacted with one another. We then calculated resistance and resilience, two dimensions of ecosystem stability. Modeled GPP exhibited a two-fold decrease in mean resistance across disturbance severities of 45%, 65%, and 85% mortality; conversely, resilience increased by a factor of two with increasing disturbance severity. This pattern held for net primary production and net ecosystem production, indicating a trade-off in which greater initial declines were followed by faster recovery. Notably, however, heterotrophic respiration responded more slowly to disturbance, and it's highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

The mobilization and land-to-ocean transfer of dissolved organic carbon (DOC) in Arctic watersheds is intricately linked with the region's climate and water cycle, and furthermore at risk of changes from climate warming and associated impacts. This study quantifies model-simulated estimates of runoff, surface and active layer leachate DOC concentrations and loadings to western Arctic rivers, specifically for basins that drain into coastal waters between and including the Yukon and Mackenzie Rivers. Model validation leverages data from other field measurements, synthesis studies, and modeling efforts. The simulations effectively quantify DOC leaching in surface and subsurface runoff and broadly capture the seasonal cycle in DOC concentration and mass loadings reported from other studies that use river-based measurements. A marked east-west gradient in simulated spring and summer DOC concentrations of 24 drainage basins on the North Slope of Alaska is captured by the modeling, consistent with independent data derived from river sampling. Simulated loadings for the Mackenzie and Yukon show reasonable agreement with estimates of DOC export for annual totals and four of the six seasonal comparisons. Nearly equivalent loading occurs to rivers which drain north to the Beaufort Sea and west to the Bering and Chukchi Seas. The modeling framework provides a basis for understanding carbon export to coastal waters and for assessing impacts of hydrological cycle intensification and permafrost thaw with ongoing warming in the Arctic.