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As the Arctic and its rivers continue to warm, a better understanding of the possible future impacts on people would benefit from close partnership with Indigenous communities and scientists from diverse fields of study. We present efforts by the Arctic Rivers Project to conduct community‐engaged research to increase collective understanding of the historical and potential future impacts of climate change on rivers, fish, and Indigenous communities. Working in central to northern Alaska and the Yukon Territory in Canada, the project seeks to engage with Indigenous communities in ethical and equitable ways to produces science that is useful, useable, and used that may serve as an example for future research efforts. Toward this goal, we formed an Indigenous Advisory Council and together developed project‐specific knowledge co‐production protocols. This paper provides a novel model of design and implementation to co‐produce knowledge with communities across a large study domain. Plain Language Summary: The Arctic and rivers located in the Arctic and subarctic are warming due to climate change. To understand the impacts this warming will have on people, partnering with impacted Indigenous communities in the region is important. It is also important that these partnerships are ethical and equitable and produce science that is actionable. This paper discusses efforts undertaken by a specific project, the Arctic Rivers Project, to conduct ethical and equitable research with Indigenous communities and generate science that is useful to those communities. Through this research our goal is to better understand potential future impacts of climate change on rivers, fish, and Indigenous communities in central northern Alaska and the Yukon Territory in Canada. To achieve this goal, the project formed an Indigenous Advisory Council (IAC) and together developed guidelines for how we can work collaboratively with Indigenous communities. Our specific process of forming an IAC and guidelines is, to our knowledge, a new way to approach collaborative research when working across a large geographic area. We present our process here so that it may provide an example for other research efforts. Key Points: Arctic climate information can be made useful, useable, and used by equitably accounting for diverse community adaptation needs through knowledge co‐productionInstitutional and community capacity, including means and ability, is necessary for equitable knowledge co‐production to occurWe present an approach for co‐producing knowledge with Indigenous communities that can serve as an example for other scientific efforts [ABSTRACT FROM AUTHOR]

The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes. Plain Language Summary: The cloud feedback is the process by which cloud property changes in a warming climate can either further enhance warming or damp it. The Arctic is warming faster than the rest of the globe, and one of the largest sources of uncertainty in its climate projections is the cloud feedback. There are two popular methods to calculate the cloud feedback: the Adjusted Cloud Radiative Effect technique, and the Cloud Radiative Kernel technique. In this paper we compare the two methods in a suite of climate models by considering the extent to which changes in Arctic sea ice impact the cloud feedbacks. From this analysis we conclude that the Cloud Radiative Kernel method is less affected by sea ice loss. We then apply the Cloud Radiative Kernel technique to data from the two most recent generations of global climate models to investigate how polar day Arctic cloud feedbacks have changed between these generations. We find that the median value of these Arctic feedbacks is slightly positive in the newest generation of models, a change from slightly negative in the previous generation that is largely fueled by a weakening of the feedback associated with changes in cloud optical depth. Key Points: The Cloud Radiative Kernel method is less sensitive to surface albedo changes than the Adjusted Cloud Radiative Effect techniqueThe Cloud Radiative Kernel method provides poor radiative closure in a suite of global climate modelsThe median shortwave Arctic cloud feedback in recent climate models is slightly positive due to a weakened cloud optical depth feedback [ABSTRACT FROM AUTHOR]

Science, engineering, and society increasingly require integrative thinking about emerging problems in complex systems, a notion referred to as convergence science. Due to the concurrent pressures of two main stressors—rapid climate change and industrialization, Arctic research demands such a paradigm of scientific inquiry. This perspective represents a synthesis of a vision for its application in Arctic system studies, developed by a group of disciplinary experts consisting of social and earth system scientists, ecologists, and engineers. Our objective is to demonstrate how convergence research questions can be developed via a holistic view of system interactions that are then parsed into material links and concrete inquiries of disciplinary and interdisciplinary nature. We illustrate the application of the convergence science paradigm to several forms of Arctic stressors using the Yamal Peninsula of the Russian Arctic as a representative natural laboratory with a biogeographic gradient from the forest‐tundra ecotone to the high Arctic. Plain Language Summary: This paper represents a synthesis of conceptual analyses, case study analyses, and practical thoughts on the application of convergence science in Arctic change studies. During a virtual workshop in 2020, a diverse, multi‐national team of authors consisting of social scientists, engineers, earth system scientists, and ecologists came together to formulate broad, scientifically, and societally important questions on how the Arctic system in the Yamal Peninsula of Western Siberia responds to pressures of rapidly changing climate and increasing industrialization. The team "engineered" a novel approach for expert (representing a disciplinary domain) and non‐expert (representatives of other disciplines) communication and at the workshop conclusion developed several convergence science questions of high appeal. Three of such questions are presented in this manuscript to illustrate how the search and identification of appropriate mechanistic linkages are critical to the development of system‐level understanding of stressor impact propagation. The need to understand underlying disciplinary and cross‐disciplinary mechanisms connecting Arctic system elements is viewed to be an inherent part of the convergence science approach. Through pursuit of such understanding, the approach naturally leads to other novel emerging questions, thereby stimulating further application of the process of integrative thinking. Key Points: Arctic research demands convergence science as essential method to understand impacts from novel stressorsAn integrative approach is developed by a diverse team to formulate questions that cannot be fully addressed within disciplinary studiesA convergence science analysis is illustrated for three questions applicable to Yamal, Russian Arctic, a microcosm of the changing Arctic [ABSTRACT FROM AUTHOR]

Time‐lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high‐frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite‐derived phenology products.However, in remote regions including the high‐latitude Arctic, deploying time‐lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges.Here, we present a novel, low‐power, compact, lightweight time‐lapse camera system, called power‐interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low‐Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology.Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (< −30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground‐based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products. [ABSTRACT FROM AUTHOR]

Arctic Ocean freshwater storage increased since the mid‐1990s, but the cause was unknown. Jahn and Laiho (2020, https://doi.org/10.1029/2020GL088854) use ensemble runs of a coupled climate model to suggest that the observed increase is anthropogenic. The paper quantifies when the anthropogenic signals should emerge from the noise of natural variability. This result contextualizes research on the Arctic Ocean freshwater system and sketches an unprecedented opportunity. Future work should elucidate mechanisms, seek to observe the anthropogenic freshwater changes, and investigate the impacts on biogeochemistry and the North Atlantic Ocean circulation. Plain Language Summary: The Arctic is a region of clear man‐made climate change. Changes in the Arctic Ocean salinity and currents have been seen, but the cause was unknown. A new paper shows that the changes are probably due to man‐made climate change. The reason is they only occur in a climate model with man‐made climate forcing. This is an important result because it helps scientists focus their research into how the changes work. It also points to a valuable opportunity to watch the Arctic Ocean respond to man‐made climate change. There might be important future impacts on North Atlantic oceanography and North Atlantic climate that scientists can now look for. Key Points: A recent paper shows that observed increases in Arctic Ocean freshwater storage are anthropogenicThe paper anticipates future anthropogenic changes, which are testable predictions for observersThere are widespread impacts of anthropogenic freshwater change, both within the Arctic and the North Atlantic Oceans [ABSTRACT FROM AUTHOR]

Arctic tundra consists of diverse habitats that differ in dominant vegetation, soil moisture regimes, and relative importance of organic vs. inorganic nutrient cycling. The Arctic is also the most rapidly warming global area, with winter warming dominating. This warming is expected to have dramatic effects on tundra carbon and nutrient dynamics. We completed a meta‐analysis of 166 experimental warming study papers to evaluate the hypotheses that warming changes tundra biogeochemical cycles in a habitat‐ and seasonally specific manner and that the carbon (C), nitrogen (N), and phosphorus (P) cycles will be differentially accelerated, leading to decoupling of elemental cycles. We found that nutrient availability and plant leaf stoichiometry responses to experimental warming were variable and overall weak, but that both gross primary productivity and the plant C pool tended to increase with growing season warming. The effects of winter warming on C fluxes did not extend into the growing season. Overall, although warming led to more consistent increases in C fluxes compared to N or P fluxes, evidence for decoupling of biogeochemical cycles is weak and any effect appears limited to heath habitats. However, data on many habitats are too sparse to be able to generalize how warming might decouple biogeochemical cycles, and too few year‐round warming studies exist to ascertain whether the season under which warming occurs alters how ecosystems respond to warming. Coordinated field campaigns are necessary to more robustly document tundra habitat‐specific responses to realistic climate warming scenarios in order to better understand the mechanisms driving this heterogeneity and identify the tundra habitats, communities, and soil pools most susceptible to warming. [ABSTRACT FROM AUTHOR]

Rapid extensive magmatism may have a profound effect on global climate by liberating and releasing greenhouse gases to the atmosphere through contact metamorphism of lithologically heterogeneous host rocks and degassing of magma and associated lava flows. The high Arctic Archipelago of Svalbard offers accessible, superbly exposed outcrops revealing Early Cretaceous magmatism associated with the High Arctic Large Igneous Province (HALIP). In this contribution, we investigate the onshore‐offshore intrusive complex of central Spitsbergen formed due to HALIP activity, that is, the Diabasodden Suite. This is the most "data‐rich" part of Svalbard due to past petroleum exploration and research drilling. In this area, the predominantly dolerite intrusions are emplaced in a range of host rocks ranging from Permian carbonate‐dominated successions to organic‐rich shale‐dominated successions of Middle Triassic and Late Jurassic‐Early Cretaceous age. Two hundred sixty five individual igneous intrusions, covering 72 km2, are exposed onshore in the study area. This equates to approximately 0.14–2.5 km3 of emplaced magma. In addition, subsurface characterization using borehole, seismic and magnetic data indicates that an area of additional ca. 3,000 km2 is affected by magmatism (magma volume 3.2–195.2 km3). Wireline logs in boreholes characterize both intrusions and associated aureoles. Aureoles with very low resistivity indicate occurrence of organic‐rich shales suggesting past fluid circulation and de‐gassing. This study forms the foundation for quantifying HALIP‐related magmatism in the data‐poorer parts of Svalbard, and other circum‐Arctic basins. Plain Language Summary: Volcanic eruptions are known to influence global climate today. In the past, even greater volcanic eruptions have happened than we know today, and some of these likely caused major global climatic shifts and contributed to mass extinctions. Volcanic eruptions are fed by a complex of sub‐surface magma pathways. If magma in such "plumbing systems" does not reach the Earth's surface, it will solidify horizontally (as sills) or vertically (as dykes). Together dykes and sills form an igneous complex that heats up the surrounding rocks and may cause the release of gas during this process. If this happens relatively near to the surface, this gas may escape to the atmosphere and contribute to global climate change. The key variables that control the extent of climate effects include the emplacement depth, the spatial extent of the magmatism and the lithology of the host rocks. In this paper, we examine the igneous complex of dykes and sills in Spitsbergen in the high Arctic. We use borehole, seismic and field data to calculate how much magma was emplaced in this area and discuss whether it may have contributed to global climate change approximately 125 million years ago. Key Points: Igneous intrusions are well exposed in central Spitsbergen across a range of host rocksTwo‐hundred sixty five intrusions cover 72 km2 of the onshore part, and a further 3,000 km2 of intrusions are characterized by geophysical dataIgneous intrusions and associated aureoles are characterized by wireline data [ABSTRACT FROM AUTHOR]

The distribution and composition of Arctic vegetation are expected to shift with ongoing climate change. Global models generally predict northward shifts in high‐latitude ecotones, and analysis of remote sensing data shows widespread greening and changes in vegetation structure across the circumpolar Arctic. However, there are still uncertainties related to the timing of these shifts and variation among different plant functional types. In this paper, we investigate disequilibrium dynamics of green alder and white spruce in the Tuktoyaktuk Coastal Plain, NWT. We used high‐resolution air photographs captured in the 1970s and 2000s to quantify changes in the distribution and abundance of alder and spruce near their northern limits. We found increases in alder and spruce stem density over time, but no change in their range limits, indicating that both species are affected by leading‐edge disequilibrium. Low stand density and temperature limitation of reproduction along the northern margin likely contributed to observed disequilibrium in both species. We also observed the greatest change in species occupancy within a burned area, suggesting that the increased frequency of fire will play a significant role in the timing and magnitude of near‐term vegetation change. [ABSTRACT FROM AUTHOR]

Abstract: The rising costs of climate change merit serious evaluation of potential climate restoration solutions. The highest rate of change in climate is observed in the Arctic where the summer ice is diminishing at an accelerated rate. The loss of Arctic sea ice increases radiative forcing and contributes to global warming. Restoring reflectivity of Arctic ice could be a powerful lever to help in the effort to limit global warming to 1.5°C. Polar ice restoration should be considered in planning of 1.5°C pathways. In this paper, a novel localized surface albedo modification technique is presented that shows promise as a method to increase multiyear ice using reflective floating materials, chosen so as to have low subsidiary environmental impact. Detailed climate modeling studying the climate impact of such a method reveals more than 1.5°C cooler temperatures over a large part of the Arctic when simulating global sea ice albedo modification. In a region north of Barents and Kara Seas temperatures have been reduced by 3°C and in North Canada by almost 1°C. Additionally, there are notable increases in sea ice thickness (20–50 cm Arctic wide) and ice concentration (>15–20% across large parts of central Arctic). These results suggest that the geoengineering technology proposed in this study may be a viable instrument for restoring Arctic ice. [ABSTRACT FROM AUTHOR]

Surface, aircraft, and satellite measurements indicate pervasive early cold season (Augut–September) CO2 emissions across Arctic regions, consistent with increased ecosystem metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink‐to‐source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season. Plain Language Summary: The Arctic is warming rapidly, leading to an acceleration of carbon exchange across tundra and boreal ecosystems. These changing flows of carbon can be difficult to detect using traditional observing systems. We propose that measurement systems which observe Arctic ecosystems continuously from a quasi‐GEO orbit can more accurately detect these important changes, such that unexpected and dangerous feedbacks to climate warming can be monitored and accounted for. Key Points: The Arctic Fourier Transform Spectrometer Investigation (AURORA) mission concept addresses GHG sampling limitations in the ArcticAURORA uses a highly elliptical orbit (HEO) to increase repeat frequency, and a panchromatic iFTS for SWIR O2 and CO2 bands (0.7–2.5 μm)Simulation experiments show potential benefits of increased sampling frequency for grid scale detection of early cold season CO2 emissions [ABSTRACT FROM AUTHOR]

Aim: The rapidly changing Arctic is ideal for investigating uncertainties in climate projections. Despite the challenges of collecting data in this region, an unprecedented large‐scale survey of shorebirds has been conducted over the last 30 years. Our study aimed to (1) develop probabilistic estimates for the change in suitable habitat for 10 Arctic shorebird species in Canada by 2075 and (2) assess the contribution of modelling decisions to the uncertainty in these estimates. Location: Arctic Canada. Methods: To evaluate uncertainty, we considered six classes of modelling decisions, yielding 216 unique projections for each species. We tested three decisions that are less commonly explored − the pool of candidate variables, a method for selecting variables, and the maximum distance of tree line dispersal, as well as the modelling algorithm, carbon emissions scenario, and global circulation model. We used a bootstrapping approach, creating a probability distribution for the proportional change in suitable habitat for each species. Results: Our findings indicated a substantial risk for 8/10 species to lose over half of their suitable breeding habitat, but this projection is much less certain than has been described previously. While much uncertainty is unexplained, we were surprised that the largest source of uncertainty among our modelling decisions was from our choice of methods for variable selection, that the other modelling decisions were relatively small sources of uncertainty, overshadowing other modelling decisions. Main Conclusions: While most scenarios predict a northward shift and significant habitat loss for Arctic‐breeding shorebirds, the Arctic Archipelago of Canada will remain an important refuge because in many other Arctic regions, there is no land farther north for these species to shift into. A comprehensive understanding of uncertainty is important for deciding if future projections can or should be used when planning climate‐resilient protected area networks. [ABSTRACT FROM AUTHOR]

In a rapidly changing Arctic, multiple lines of evidence suggest that bowhead whale migration is changing. To explore these changes further, we used passive acoustic data to examine bowhead whale presence in the western Beaufort Sea (12 years) and Chukchi Plateau (11 years) spanning 2008 to 2022. Departure from the western Beaufort Sea shifted 45 days later over the 12‐year period. Summer presence increased at both sites, suggesting feeding areas within the Chukchi Sea are becoming more favorable. Likewise, findings from the Bering Strait suggest that some whales are remaining north of the Bering Strait for the winter instead of in the Bering Sea. These Pacific Arctic‐wide changes to migration have occurred over only one decade. Questions remain about prey availability in the Chukchi Sea, implications of migratory changes, such as a northward shift in the core overwintering area, and impact to communities south of the Bering Strait. Plain Language Summary: Bowhead whales are an important top predator in the Pacific Arctic. With increasing temperatures and decreasing sea ice, changes are occurring in the migration patterns of this "ecosystem sentinel" throughout the Pacific Arctic. We analyzed passive acoustic data from the western Beaufort Sea and Chukchi Plateau from 2008 to 2022. Whales are delaying their fall departure from the western Beaufort Sea and spending more time in the western Beaufort Sea and Chukchi Plateau, which, along with increased habitat use on the Chukchi Shelf, suggests that conditions there are becoming more favorable for feeding. Combined with previous data from the Bering Strait, which showed that some whales are spending winter in the southern Chukchi Sea rather than in the northern Bering Sea, these findings suggests that changes are occurring over a short period of time throughout the Pacific Arctic. A northward shift could put bowhead whales in the direct path of ships, especially along the western side of the Chukchi Sea, and impact whaling communities south of the Bering Strait. Key Points: Acoustic data reinforce known delay in bowhead fall departure from the western Beaufort Sea and overwintering in the southern Chukchi SeaIncreased presence in the western Beaufort Sea and Chukchi Plateau suggests these regions are becoming more favorable for bowhead feedingWhales are adapting to a rapidly changing Arctic, but changes and emerging threats may impact them and communities south of Bering Strait [ABSTRACT FROM AUTHOR]

Algal bioindicators, such as diatoms, often show subdued responses to eutrophication in Arctic lakes because climate‐related changes (e.g., ice cover) tend to be the overriding factors influencing assemblage composition. Here, we examined how sub‐Arctic ponds historically receiving high nutrient inputs from nesting seabirds have responded to recent climate change. We present diatom data obtained from 12 sediment cores in seaduck‐affected ponds located on islands through Hudson Strait, Canada. All study cores show consistently elevated values of sedimentary ẟ15N, an established proxy for tracking marine‐derived nutrients, indicating seabirds have been present on these islands for at least the duration of the sediment records (~100 to 400 years). We document diverse epiphytic diatom assemblages to the base of all sediment cores, which is in marked contrast to seabird‐free Arctic ponds—these oligotrophic sites typically record epilithic diatom flora prior to recent warming. Diatoms are likely responding indirectly to seabird nutrients via habitat as nutrients promote the growth of mosses supporting epiphytic diatom communities. This masks the typical diatom response to increased warming in the Arctic, which also results in habitat changes and the growth of mosses around the pond edges. Changes in sedimentary chlorophyll a were not consistently synchronous with large changes in ẟ15N values, suggesting that primary production in ponds is not responding linearly to changes in seabird‐derived nitrogen. Across all ponds, we recorded shifts in diatom epiphytic assemblages (e.g., increases in % relative abundance of many Nitzschia species) that often align with increases in chlorophyll a. The changes in diatoms and chlorophyll a, although variable, are most likely driven by climate change as they are generally consistent with longer ice‐free conditions and growing seasons. Together, our results show that to effectively use diatoms in animal population reconstructions across the sub‐Arctic and Arctic, a strong understanding of eutrophication and climate change, based on supplementary proxies, is also required. [ABSTRACT FROM AUTHOR]

Representing mixing state of black carbon (BC) is challenging for global climate models (GCMs). The Community Atmosphere Model version 6 (CAM6) with the four‐mode version of the Modal Aerosol Module (MAM4) represents aerosols as fully internal mixtures with uniform composition within each aerosol mode, resulting in high degree of internal mixing of BC with non‐BC species and large mass ratio of coating to BC (RBC, the mass ratio of non‐BC species to BC in BC‐containing particles). To improve BC mixing state representation, we coupled a machine learning (ML) model of BC mixing state index trained on particle‐resolved simulations to the CAM6 with MAM4 (MAM4‐ML). In MAM4‐ML, we use RBC to partition accumulation mode particles into two new modes, BC‐free particles and BC‐containing particles. We adjust RBC to make the modeled BC mixing state index (χmode) match the one predicted by the ML model (χML). On a global average, the mass fraction of BC‐containing particles in accumulation mode decreases from 100% (MAM4‐default) to 48% (MAM4‐ML). The globally averaged χmode decreases from 78% (MAM4‐default) to 63% (MAM4‐ML, 19% reduction) and agrees well with χML (66%). The RBC decreases by 52% for accumulation mode and better agrees with observations. The hygroscopicity drops by 9% for BC‐containing particles in accumulation mode, leading to a 20% reduction in the BC activation fraction. The surface BC concentration increases most (6.9%) in the Arctic, and the BC burden increases by 4%, globally. Our study highlights the application of the ML model for improving key aerosol processes in GCMs. Plain Language Summary: Black carbon (BC) mixing state is an important property for assessing impacts of BC on human health and climate. It describes how BC is distributed among the particle population and within individual particles. Due to computational costs, global climate models (GCMs) consider aerosols as either external mixtures (e.g., bulk models) or fully internal mixtures with uniform composition within a certain size range (e.g., an aerosol bin in sectional models or an aerosol mode in modal models). To improve BC mixing state representation, we coupled a machine learning (ML) model learned from particle‐resolved simulations to the online simulations of the Community Atmosphere Model version 6 (CAM6) with the four‐mode version of the Modal Aerosol Module (MAM4‐ML). We used the mass ratio of coating to BC (RBC) to determine the mass fraction of BC‐free particles and BC‐containing particles, and we adjusted RBC to make the modeled BC mixing state match ML model. The MAM4‐ML model reduces the degree of internal mixture of BC substantially. In addition, MAM4‐ML RBC is reduced by 52%, leading to a 20% reduction in BC activation fraction and a 4% increase in BC burden. This study proposes a method for the application of the ML to improve GCMs. Key Points: Machine learning model trained on particle‐resolved simulations has been coupled to CAM6 MAM4 to improve BC mixing state representationThe BC mixing state index is reduced by 19%, and the mass ratio of coating to BC is reduced by 52%, in better agreement with observationsDue to the drop in hygroscopicity of BC‐containing aerosol (9%), BC activation fraction decreased by 20%, and BC burden increased by 4% [ABSTRACT FROM AUTHOR]

The Arctic has experienced rapid change associated with warming since the 1970s. The rapid retreat of the terrestrial cryosphere can release a large amount greenhouse gas from the permafrost regions into the air, and the sea ice decline will affect the CO2 and CH4 balance in the ocean. Changes in the Arctic provide feedback mechanisms that can also impinge on the global ocean's thermohaline circulation. During the past years, the overall natural processes in the Arctic have been studied although the magnitude and timing of carbon release from the cryosphere changes require further investigation. However, few studies have been conducted to link the natural and social systems in the Arctic. Scientists and policymakers must consider the coupled Arctic land, ocean, and social systems in their decisions for coping with climate change. Plain Language Summary: The Arctic is warming more than twice the global average. The Arctic is connected to the rest of the world through the climate system, it appears to be the first domino to fall, with the other dominoes pointing south. The Arctic science community and the people who live in the Arctic have known the rapid Arctic changes for a long time. It has been recognized that the cryosphere components are declining, and the carbon cycle in both the land and ocean will be affected by the cryosphere shrinkage. Despite some scientific breakthroughs, there are still major knowledge gaps in the Arctic carbon cycle. The policymakers at this stage are not only asking for more data about the Arctic changes, they also need scientific suggestions to cope with Arctic changes. The science community should work together to draw a full picture of the Arctic changes that include both natural and social systems. Key Points: The changing Arctic carbon cycle can affect global climateMore field observation should be carried out in the Arctic land and oceanThe Arctic land, ocean, and social domain should be considered as a system [ABSTRACT FROM AUTHOR]

Climate change is already occurring in the Arctic and the Arctic Climate Impact Assessment recently concluded that future climate change could be devastating for Inuit. This paper characterises vulnerability to climate change in two Inuit communities in the Canadian territory of Nunavut, focusing on the resource harvesting sector. In both communities, Inuit have demonstrated significant adaptability in the face of current changes in climatic conditions. This adaptability is facilitated by traditional Inuit knowledge, strong social networks, flexibility in resource use, and institutional support. Changing Inuit livelihoods, however, have undermined certain aspects of adaptive capacity and have resulted in emerging vulnerabilities. Global and regional climate projections indicate that climatic conditions which currently pose risks are expected to be negatively affected by future climate change. These projections are not without precedent and analysis of current vulnerability and identification of adaptation constraints by Inuit in the two communities indicate the continued importance of traditional coping mechanisms. The ability to draw on these coping mechanisms in light of future climate change, however, will be unequal and the research indicates that young Inuit and those without access to economic resources, in particular, are vulnerable. [ABSTRACT FROM AUTHOR]

Despite multiple advances in the understanding of the water cycle intensification in a warmer climate, climate models still diverge in their hydrological projections. Here we constrain annual runoff projections over individual and aggregated Arctic river basins. For this purpose, we use two ensembles of global climate models and two statistical methods: a regression scheme assuming similar runoff sensitivities at interannual versus climate change timescales, and a Bayesian method where models are used to derive a posterior runoff response conditioned on historical observations. While both techniques are shown to narrow model uncertainties, more or less substantially depending on rivers, the Bayesian method is less sensitive to the choice of the model ensemble and is more skillful when tested with synthetic observations. It has also been applied over the whole Arctic watershed, showing so far a limited narrowing of the inter‐model spread, but its skill will further improve with increasing climate change. Plain Language Summary: Despite considerable progress in understanding the intensification of the water cycle in response to global warming, projections of changes in the various components of the continental water balance remain highly model‐dependent. This is particularly the case for the evolution of runoff, which remains very sensitive to the way atmospheric and continental processes are represented. Here we evaluate and compare two statistical methods to constrain climate projections of annual runoff at high latitudes via available or synthetic observations. Our Bayesian method, based on historical observations, is found to be more robust than a previous method based on observed interannual climate variability. It underlines the importance of having reliable flow reconstructions to constrain runoff projections and of using empirical observational constraints with caution, as they are likely to lead to over‐confident projections. Key Points: Runoff sensitivity to temperature depends on the considered timescaleObservational constraints based on interannual variability can thus lead to overconfident projectionsObservational constraints based on historical trends can be effective if such trends are driven by human emissions of greenhouse gasses [ABSTRACT FROM AUTHOR]

Root‐associated fungi play a critical role in plant ecophysiology, growth and subsequent responses to disturbances, so they are thought to be particularly instrumental in shaping vegetation dynamics after fire in the boreal forest. Despite increasing data on the distribution of fungal taxonomic diversity through space and time in boreal ecosystems, there are knowledge gaps with respect to linking these patterns to ecosystem function and process.Here we explore what is currently known about postfire root‐associated fungi in the boreal forest. We focus on wildfire impacts on mycorrhizal fungi and the relationships between plant–fungal interactions and forest recovery in an effort to explore whether postfire mycorrhizal dynamics underlie plant–soil feedbacks that may influence fire‐facilitated vegetation shifts.We characterize the mechanisms by which wildfire influences root‐associated fungal community assembly. We identify scenarios of postfire plant–fungal interactions that represent putative positive and negative plant–soil feedbacks that may impact successional trajectories. We highlight the need for empirical field observations and experiments to inform our ability to translate patterns of postfire root‐associated fungal diversity to ecological function and application in models.We suggest that understanding postfire interactions between root‐associated fungi and plants is critical to predict fire effects on vegetation patterns, ecosystem function, future landscape flammability and feedbacks to climate. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Warming‐driven growth of tall woody vegetation in the Arctic has the potential to accelerate climate change through multiple positive feedbacks. Local‐scale evidence suggests that large herbivores limit this vegetation shift, but there is uncertainty at larger, regional scales whether current herbivory pressure is a major top‐down control on ecosystem structure and functioning. Across a 67,000 km2 region of the Yamal Peninsula in West Siberia, we integrated satellite remote sensing with a novel data set mapping the migrations of herds comprising 151,000 domesticated reindeer. Where reindeer numbers varied over space, higher reindeer herbivory pressure was consistently linked with lower coverage of tall woody vegetation. Within areas dominated by this vegetation type, productivity and climate were increasingly decoupled where reindeer density was higher. Our spaceborne fingerprint detection suggests that large herbivores, at current population densities, counteract Arctic vegetation responses to climate change over large spatial scales. Plain Language Summary: Large herbivores influence tundra vegetation via their grazing, trampling, and nutrient inputs from feces and urine. However, the extent of these impacts remains unclear as we seek to understand and predict the responses of Arctic ecosystems to climate change. Using maps that we developed that record the annual summertime movements of herds comprising 151,000 domesticated reindeer managed by indigenous Nenets herders, we assessed whether reindeer had an effect on vegetation productivity and composition across a 67,000 km2 region of the Yamal Peninsula in West Siberia, an area about the size of the Republic of Ireland. Analyses of satellite data comparing areas with varying reindeer density consistently showed that higher reindeer herbivory pressure was limiting the coverage of tall woody vegetation and its expansion in response to warming. This effect had not been observed previously at such a large spatial scale and was significant enough to be detected from space. Our findings demonstrate that reindeer have a substantial impact on ecosystem structure and functioning, which likely has implications for the carbon cycle and energy balance within the Arctic and beyond. Key Points: Integrating maps of migrations of indigenous‐managed reindeer herds with remote sensing enabled analysis of large‐scale herbivory impactsAreas on the Yamal Peninsula with higher reindeer herbivory pressure consistently had lower coverage of tall woody vegetationThe productivity of tall woody vegetation was less sensitive to climate variability where reindeer density was higher [ABSTRACT FROM AUTHOR]

This special issue of GeoHealth, entitled Rhythms of the Earth: Ecological Calendars and Anticipating the Anthropogenic Climate Crisis, is a transdisciplinary articulation of a methodology of hope to confront the multiple injustices of the Anthropocene. One of the greatest challenges of the climate crisis is the lack of predictability at the scale of communities where impacts are most immediate. Indigenous and rural societies face an ever shifting "new normal" through increasing inconsistency in the seasonality of temperature and precipitation, as well as greater frequency of extreme weather events. With global food systems dependent on local and small producers, climatic variability disrupts access to affordable, nutritious, and culturally relevant food. Ecological calendars are context‐specific knowledge systems grounded in a particular cultural milieu and ecological space, that build anticipatory capacity for seasonal change. They measure and give meaning to time. Based on close observation of one's habitat, human societies have used such calendars for hundreds of years and potentially millennia. By engaging with the interactions among physical phenomena (such as the first snowfall or last frost) and biological events (such as blossoming of specific trees, arrival of migratory birds or mammals, appearance of plants or insects), human societies have been able to identify optimal time windows for their livelihood activities. The 11 research articles in Rhythms of the Earth cover a considerable geographical breadth from Africa to the Arctic; and, from North and South America to Central Asia. They provide evidence that spans millennia from the Roman Empire to the contemporary Anthropocene. Key Points: Rhythms of the Earth is a transdisciplinary collaboration between Indigenous Knowledge and ScienceIn Rhythms of the Earth , an innovative culturally and ecologically grounded way to anticipate seasonal change is proposedSignificant diversity of thought from around the world is engaged in Rhythms of the Earth because the research articles are co‐authored by artists, Indigenous community members, and scholars in the biological, physical, and social sciences as well as the humanities [ABSTRACT FROM AUTHOR]

In the high Arctic, plant community species composition generally responds slowly to climate warming, whereas less is known about the community functional trait responses and consequences for ecosystem functioning. The slow species turnover and large distribution ranges of many Arctic plant species suggest a significant role of intraspecific trait variability in functional responses to climate change. Here we compare taxonomic and functional community compositional responses to a long‐term (17‐year) warming experiment in Svalbard, Norway, replicated across three major high Arctic habitats shaped by topography and contrasting snow regimes. We observed taxonomic compositional changes in all plant communities over time. Still, responses to experimental warming were minor and most pronounced in the drier habitats with relatively early snowmelt timing and long growing seasons (Cassiope and Dryas heaths). The habitats were clearly separated in functional trait space, defined by 12 size‐ and leaf economics‐related traits, primarily due to interspecific trait variation. Functional traits also responded to experimental warming, most prominently in the Dryas heath and mostly due to intraspecific trait variation. Leaf area and mass increased and leaf δ15N decreased in response to the warming treatment. Intraspecific trait variability ranged between 30% and 71% of the total trait variation, reflecting the functional resilience of those communities, dominated by long‐lived plants, due to either phenotypic plasticity or genotypic variation, which most likely underlies the observed resistance of high Arctic vegetation to climate warming. We further explored the consequences of trait variability for ecosystem functioning by measuring peak season CO2 fluxes. Together, environmental, taxonomic, and functional trait variables explained a large proportion of the variation in net ecosystem exchange (NEE), which increased when intraspecific trait variation was accounted for. In contrast, even though ecosystem respiration and gross ecosystem production both increased in response to warming across habitats, they were mainly driven by the direct kinetic impacts of temperature on plant physiology and biochemical processes. Our study shows that long‐term experimental warming has a modest but significant effect on plant community functional trait composition and suggests that intraspecific trait variability is a key feature underlying high Arctic ecosystem resistance to climate warming. [ABSTRACT FROM AUTHOR]

Employing a model democracy in which each model is equally weighted may lead to a poor estimation of the true uncertainty in climate projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). The improvement and increase in number of CMIP6 models compared with previous phases of CMIP indicate that both model skill and independence need to be considered to provide convincing projections. In this study, we use a weighting scheme, which weights both the skill and independence of multi‐model simulations, to efficiently constrain the large uncertainty in the projection of the timing of an ice‐free Arctic. The uncertainty‐constrained projections of CMIP6 show that the multi‐model spread of the projected first year of an ice‐free Arctic can be reduced by about 29 years under the Shared Socioeconomic Pathway (SSP)3–7.0 scenario (a regional rivalry scenario), indicating a faster tendency to an ice‐free Arctic summer than projections based solely on model democracy. A fossil‐fuel‐based development scenario (i.e., SSP5‐8.5) leads to an ice‐free Arctic before the 2070s (ranging from 2038 to 2071), while an ice‐free Arctic occurs slightly later (by ∼10 years) under the SSP2‐4.5 scenario (i.e., intermediate scenario) and the SSP3‐7.0 scenario, but is inevitable this century. The sustainable development scenario (i.e., SSP1‐2.6) is likely to prevent the occurrence of an ice‐free Arctic. Internal variability strongly affects the projection estimated by the equally weighted ensemble; however, it has a negligible impact on the results obtained by the weighting scheme, thereby indicating that the results of this study are robust and convincing. Plain Language Summary: Climate models are a key tool used by scientists to estimate climate changes in the future. However, the outputs of such models carry inherent uncertainties that can affect the confidence in projections. These uncertainties may not be appropriately estimated by simple and traditional methods that do not adequately consider the model skill or independence (i.e., similarity to other models). In this study, we found that the uncertainties in Arctic sea‐ice projections can be largely reduced if the outputs of climate models are weighted according to their performance and independence. By doing so, we can increase the level of confidence in estimating the year when the Arctic is likely to see its first ice‐free summer (sea‐ice extent below 1 × 106 km2). It is indicated that a sustainable development scenario may avoid an ice‐free Arctic. In contrast, a fossil‐fuel‐based development scenario will lead to an ice‐free Arctic before the 2070s (ranging from 2038 to 2071); and an ice‐free Arctic will occur slightly later (by ∼10 years) under an intermediate or regional rivalry scenario, but is still inevitable this century. Key Points: The performance and interdependence of climate models may lead to a poor estimation of the true uncertainty in climate projectionsA weighting scheme considering both model skill and independence can reduce the spread in the first year of an ice‐free Arctic by ∼29 yearsThe weighted spread indicates that the first year of an ice‐free Arctic is likely to occur during 2040–2072 under the SSP3‐7.0 scenario [ABSTRACT FROM AUTHOR]

As arctic permafrost continues to thaw, previously inaccessible nitrogen (N) becomes available to N‐limited arctic plants. Increased N availability could enhance plant growth and thereby potentially offset climate‐induced carbon release. Arctic plants can take up newly available permafrost‐N locally upon release. However, in a topographically diverse arctic landscape, permafrost‐N may be transported along hillslopes, away from the point‐of‐release. The extent to which topographical N transport can impact arctic vegetation change depends on whether N is retained locally, captured by downslope recipient plant communities, or transported away.We used stable isotope labelling (15N) to simulate upslope release of ammonium (NH4+) and nitrate (NO3−) from thawing permafrost on an arctic hillslope, western Greenland. We tracked the plant species‐specific uptake of simulated permafrost‐released N from the upslope point‐of‐release to the bottom of the slope through 4 years.We found that arctic tundra plants successfully acquired locally released permafrost‐N, even in sloping terrain, and that N was strongly retained in the plant–soil system through multiple years. At the same time, we also importantly demonstrate that permafrost‐N can be transported and taken up by plants up to 30 m downslope from the point‐of‐release. Especially NO3− was more easily redistributed vertically within the soil column compared to NH4+ and therefore potentially more accessible to plants. Specifically, plant species with fast N uptake capacity and deep‐soil foraging strategies may have competitive advantages for capitalising on deep‐soil released and topographically transported permafrost‐N (here exemplified by Equisetum arvense and Salix glauca). Nevertheless, even mosses gained access to permafrost‐N via vertical and lateral redistribution on the slope. Ultimately, the intricate balance between strong local N retention, downslope transport and plant species‐specific uptake strategies may contribute to shaping arctic vegetation change.Synthesis. Across spatially complex arctic ecosystems, arctic plants can take up permafrost‐released N both at the local point‐of‐release and at a considerable distance downslope. The potential for arctic plants to take advantage of topographically transported permafrost‐N could lead to long‐term and landscape‐scale changes in species composition, plant productivity, and ultimately carbon and climate feedbacks across the Arctic. [ABSTRACT FROM AUTHOR]

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the "best" CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step‐like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time. Plain Language Summary: The rate of Arctic warming varied in time, while the rate of global warming was nearly constant over the period 1960–2020. This led to a variable Arctic Amplification (AA) defined as a ratio of the Arctic warming trend to mean global warming trend. In addition, the Arctic experienced sudden changes in the rate of warming with step‐like changes in annual mean Arctic Amplification around the years 1986 and 1999. Climate models do not capture the second observed sharp increase of the AA. We suggest that the first AA increase around 1986 is primarily due to external forcing (increasing concentration of carbon dioxide) while the second sharp increase around 1999 is dominated by internal climate variability which current models cannot capture accurately within the time scale of the physical phenomena. Key Points: Annual mean Arctic Amplification (AA) within the period 1970–2020 changed in steep steps around 1986 and 1999. It reached values over 4.0Even those CMIP6 models best at reproducing the AA did not reproduce the second sudden increase near 1999We conjecture that the first AA sharp increase is due to external forcing, while the second is due to internal climate variability [ABSTRACT FROM AUTHOR]

Summary: Bacterial communities form the basis of biogeochemical processes and determine plant growth and health. Mosses harbour diverse bacterial communities that are involved in nitrogen fixation and carbon cycling. Global climate change is causing changes in aboveground plant biomass and shifting species composition in the Arctic, but little is known about the response of moss microbiomes in these environments.Here, we studied the total and potentially active bacterial communities associated with Racomitrium lanuginosum in response to a 20‐yr in situ warming in an Icelandic heathland. We evaluated the effect of warming and warming‐induced shrub expansion on the moss bacterial community composition and diversity, and nifH gene abundance.Warming changed both the total and the potentially active bacterial community structure, while litter abundance only affected the total bacterial community structure. The abundance of nifH genes was negatively affected by litter abundance. We also found shifts in the potentially nitrogen‐fixing community, with Nostoc decreasing and noncyanobacterial diazotrophs increasing in relative abundance.Our data suggest that the moss microbial community and potentially nitrogen fixing taxa will be sensitive to future warming, partly via changes in litter and shrub abundance. [ABSTRACT FROM AUTHOR]

Arctic sea ice has substantially changed over the past four decades, with a large decrease in sea‐ice area and volume. The exact causes of these changes are not entirely known. In our study, we make use of the Swedish Meteorological and Hydrological Institute Large Ensemble. This ensemble consists of 50 members realized with the EC‐Earth3 global climate model and covers the period 1970‐2100. We apply for the first time the Liang‐Kleeman information flow method to analyze the cause‐effect relationships between Arctic sea ice and its potential drivers. We show that recent and future changes in Arctic sea ice are mainly driven by air and sea‐surface temperatures and ocean heat transport. Conversely, changes in Arctic sea ice also considerably impact temperature and ocean heat transport. Finally, we find a progressive decrease in the influence of sea‐ice area and volume on air temperature and ocean heat transport through the twenty‐first century. Plain Language Summary: The Arctic has been warming at a larger rate than the rest of the world, resulting in a substantial loss of sea ice since the late 1970s. This has had and will continue to have an impact on our climate and societies. The exact causes of the ongoing sea‐ice loss are not entirely known, and understanding them is important in order to better prepare our societies for future climate changes. In our study, we apply a relatively novel approach that quantifies the cause‐effect relationships between Arctic sea ice and its potential drivers. We make use of a large range of model simulations performed with the EC‐Earth3 global climate model covering the period 1970‐2100. We find that air temperature, sea‐surface temperature, and the transport of heat by the ocean are important drivers of the ongoing and future retreat of Arctic sea ice. Conversely, changes in Arctic sea ice also affect the three former quantities. Our study demonstrates the performance of causal inference methods in the quest for a better understanding of relationships between climate variables. The geophysical and climate communities could greatly benefit from using these methods more intensively. Key Points: The Liang‐Kleeman rate of information transfer allows quantification of the directional dependence between Arctic sea ice and its driversRecent and future changes in Arctic sea ice are mainly driven by air and sea‐surface temperatures and ocean heat transportThe influence of Arctic sea ice on air temperature and ocean heat transport progressively decreases through the twenty‐first century [ABSTRACT FROM AUTHOR]

Aim: Tree life spans, as an important determinant of carbon turnover in forest ecosystems, are strongly linked to climate change. Enhanced drought has led to extensive tree mortality, but whether climate dryness will widely shorten tree life spans remains unclear. Here we aimed to establish the relationship between climate dryness and tree life span, and identify the regulatory effects of functional traits on tree life span. Location: Global. Time period: Until 2015. Major taxa studied: Woody plants. Methods: We used tree ring records sampled at 2,348 sites ranging from the tropics to Arctic regions to estimate tree life span. First, we investigated which of nine functional traits related to trees' adaptability best explained the variation in tree life span. Second, we established a structural equation model between climate dryness, functional traits and tree life span to illustrate the regulatory effects of climate dryness and trees' adaptability on tree life span. Results: Our results suggested that tree life span significantly increased with climate dryness across biomes. Hydraulic traits indicating the adaptability of trees to climate dryness regulated the relationship between climate dryness and tree life span. Trees with high‐density wood or with high resistance to drought‐induced embolisms extend their life span with increasing climate dryness, but climate dryness reduces the life spans of low‐drought‐tolerance trees. Main conclusions: Tree life span is not fixed within species but regulated by climate dryness and trees' hydraulic adaptability to drought. Our large‐scale links between climate change and tree life span allow for incorporation of these factors into future Earth system models for a better representation of climate‐driven forest dynamics. [ABSTRACT FROM AUTHOR]

Recent satellite observations confirm that the Arctic is absorbing more solar radiation now than at the start of this century in response to declining Arctic sea ice and snow covers. Trends in the solar radiation input to Arctic ocean and land surfaces now each exceed interannual variability at the 95% confidence level, although all‐sky trends have taken 20%–40% longer to emerge compared to clear‐sky conditions. Clouds reduce mean solar absorption and secular trends over both land and ocean, but the effect of clouds on natural variability depends on the underlying surface. While clouds increase the time needed to unambiguously identify trends in nearly all Arctic regions, their masking effects are strongest over oceans. Clouds have extended the time to emergence of already observed clear‐sky trends beyond the existing 21 years Clouds and Earth's Radiant Energy System record in half of eight Arctic seas, supporting the need for continued satellite‐based radiative flux observations over the Arctic. Plain Language Summary: The Arctic has been rapidly changing in response to rising greenhouse gases, including dramatic sea ice loss. Sea ice is bright and reflects most sunlight that hits it, so when it melts more sunlight is absorbed at the surface, leading to more surface melting or warming. However, when viewed from satellites in space, it can be difficult to distinguish between bright clouds and the bright surface. Because clouds also reflect a large amount of incoming sunlight, they reduce the amount of sunlight that reaches the surface. Without clouds, far more sunlight would have been absorbed into the Arctic over the last two decades. The presence of clouds has also made it more difficult to observe how the amount of sunlight being absorbed is changing. Nevertheless, the Arctic has been evolving so quickly that even with the masking effect of clouds we can measure trends in absorbed sunlight using 20 years of satellite observations, a relatively short amount of time compared to most other climate changes. Key Points: Significantly more solar radiation is being absorbed into the Arctic now than at the turn of the centuryClouds increase the time needed to detect trends in solar absorptionClouds exert the largest masking effect over oceans and areas with the greatest sea ice loss [ABSTRACT FROM AUTHOR]

Aim: Plant growth and phenology respond plastically to changing climatic conditions in both space and time. Species‐specific levels of growth plasticity determine biogeographical patterns and the adaptive capacity of species to climate change. However, a direct assessment of spatial and temporal variability in radial growth dynamics is complicated, because long records of cambial phenology do not exist. Location: Sixteen sites across European distribution margins of Juniperus communis L. (the Mediterranean, the Arctic, the Alps and the Urals). Time period: 1940–2016. Major taxa studied: Juniperus communis. Methods: We applied the Vaganov–Shashkin process‐based model of wood formation to estimate trends in growing season duration and growth kinetics since 1940. We assumed that J. communis would exhibit spatially and temporally variable growth patterns reflecting local climatic conditions. Results: Our simulations indicate regional differences in growth dynamics and plastic responses to climate warming. The mean growing season duration is the longest at Mediterranean sites and, recently, there has been a significant trend towards its extension of up to 0.44 days/year. However, this stimulating effect of a longer growing season is counteracted by declining summer growth rates caused by amplified drought stress. Consequently, overall trends in simulated ring widths are marginal in the Mediterranean. In contrast, durations of growing seasons in the Arctic show lower and mostly non‐significant trends. However, spring and summer growth rates follow increasing temperatures, leading to a growth increase of up to 0.32 %/year. Main conclusions: This study highlights the plasticity in growth phenology of widely distributed shrubs to climate warming: an earlier onset of cambial activity that offsets the negative effects of summer droughts in the Mediterranean and, conversely, an intensification of growth rates during the short growing seasons in the Arctic. Such plastic growth responsiveness allows woody plants to adapt to the local pace of climate change. [ABSTRACT FROM AUTHOR]

Climate models are crucial for assessing climate variability and change. A reliable model for future climate should reasonably simulate the historical climate. Here, we assess the performance of CMIP6 models in reproducing statistical properties of observed annual maxima of daily precipitation. We go beyond the commonly used methods and assess CMIP6 simulations on three scales by performing: (a) univariate comparison based on L‐moments and relative difference measures; (b) bivariate comparison using Kernel densities of mean and L‐variation, and of L‐skewness and L‐kurtosis, and (c) comparison of the entire distribution function using the Generalized Extreme Value (GEV) distribution coupled with a novel application of the Anderson‐Darling Goodness‐of‐fit test. The results reveal that the statistical shape properties (related to the frequency and magnitude of extremes) of CMIP6 simulations match well with the observational datasets. The simulated mean and variation differ among the models with 70% of simulations having a difference within ±10% from the observations. Biases are observed in the bivariate investigation of mean and variation. Several models perform well with the HadGEM3‐GC31‐MM model performing well in all three scales when compared to the ground‐based Global Precipitation Climatology Centre data. Finally, the study highlights biases of CMIP6 models in simulating extreme precipitation in the Arctic, Tropics, arid and semi‐arid regions. Plain Language Summary: Annual maxima of daily precipitation are widely used to design critical infrastructures such as dams and stormwater networks. Climate change is expected to increase the frequency and intensity of extreme events. Climate model projections offer a glimpse into the future and can help assess potential changes and impacts. It is reasonable to assume that climate models simulating accurately the historical climate may also simulate well the future. Here, we assessed the latest generation of climate models, that is the CMIP6 models, to reproduce the historical annual maximum daily precipitation. We compared simulations and observations of extreme precipitation using advanced summary statistics, novel probability similarity measures, and robust statistical tests. The results indicate that models, in general, reproduce well the behavior of annual maximum precipitation, but biases exist especially in the simultaneous behavior of mean and variance. Shortcomings of CMIP6 models are highlighted in the Arctic, Tropics, arid, and semi‐arid regions. Key Points: Assessment of CMIP6 biases in precipitation extremes using L‐moments, novel probability similarity measures and statistical testsCMIP6 models reproduce fairly well observed annual maximum precipitation but biases exist in the joint behavior of mean and variabilityShortcomings of CMIP6 models are highlighted in the Arctic, Tropics, arid, and semi‐arid regions [ABSTRACT FROM AUTHOR]

State‐of‐the‐art climate models simulate a large spread in the projected decline of Arctic sea‐ice area (SIA) over the 21st century. Here we diagnose causes of this intermodel spread using a simple model that approximates future SIA based on present SIA and the sensitivity of SIA to Arctic temperatures. This model accounts for 70%–95% of the intermodel variance, with the majority of the spread arising from present‐day biases. The remaining spread arises from intermodel differences in Arctic warming, with some contribution from differences in the local sea‐ice sensitivity. Using observations to constrain the projections moves the probability of an ice‐free Arctic forward by 10–35 years when compared to unconstrained projections. Under a high‐emissions scenario, an ice‐free Arctic will likely (>66% probability) occur between 2036 and 2056 in September and between 2050 and 2068 from July to October. Under a medium‐emissions scenario, the "likely" date occurs between 2040 and 2062 in September and much later in the 21st century from July to October. Plain Language Summary: Arctic sea ice coverage has declined substantially over the past few decades and is projected to continue to decline over the next century. These projections, however, are marred by large uncertainties which arise primarily due to differences between climate models. In this study, we use a simple model that emulates the future evolution of Arctic sea ice as simulated by climate models to explain where this uncertainty comes from. We show that biases in simulating present‐day Arctic sea ice contribute most of the uncertainty, with differences in the simulated amount of Arctic warming from climate models contributing much of the rest. We use observations to constrain our simple model and show that under a high emissions scenario it is likely the Arctic will be free of sea ice in September sometime between 2036 and 2056 and from July to October sometime between 2050 and 2068. We also show that the emissions pathway impacts the length of ice free summers in the Arctic, indicating a low‐emissions pathway will reduce the likelihood of seeing ice‐free Arctic summers. Key Points: A model relating future sea‐ice area (SIA) to present SIA and local sea‐ice sensitivity is used to explain the intermodel spread in Arctic SIA projectionsBiases in simulating present‐day SIA contribute most to the spread, with model differences in Arctic warming contributing the restUnder a high‐emissions scenario, the Arctic will likely be ice‐free in September between 2036 and 2056 and from July to October between 2050 and 2068 [ABSTRACT FROM AUTHOR]

Aim: The Arctic is one of the planet's most rapidly warming regions, with trends expected to intensify in the future. Projections of shifts in species distributional ranges under future climate change are thus far lacking for most vertebrate species using the Arctic tundra. Our aim was to assess possible climate‐induced changes in distributional ranges and inter‐specific overlap of an Arctic species assemblage within the world's largest land‐based protected area. Location: During 1979–2013 location data of eight Arctic birds and mammals, Arctic fox (Vulpes lagopus), Arctic hare (Lepus arcticus), Arctic wolf (Canis lupus arctos), muskox (Ovibos moschatus), polar bear (Ursus maritimus), rock ptarmigan (Lagopus muta), snow bunting (Plectrophenax nivalis) and snowy owl (Bubo scandiacus) were collected in the Northeast Greenland National Park. Methods: The maximum entropy (MaxEnt) algorithm and Schoener's D niche overlap index were used to assess shifts and changes in overlap of species‐specific distributions under recent (1979–2013) and future (2061–2080; representative concentration pathways [RCPs] 2.6, 4.5 and 8.5) bioclimatic conditions. Results: Species distributions were projected to shift northward and upwards across all scenarios, and at higher rates than previously reported. Future distributions were also forecasted to become spatially less clustered and to expand in size for all species. Species‐specific shifts in distribution ranges altered inter‐specific overlap, most notably by an increase in overlap under scenario RCP 8.5. Main conclusions: The rapid shifts in distribution ranges detected here underline that climate change impacts are most pronounced in areas with higher levels of warming, leading to accelerated shifts in species' ranges towards the poles. However, the concomitant range expansions we found may suggest that future climatic conditions in north‐east Greenland may not have such a detrimental impact on the distribution of cold‐adapted species as generally expected, at least in the near future. [ABSTRACT FROM AUTHOR]

Climate change is projected to cause the Arctic soundscape to become noisier due to sea ice loss and increased anthropogenic activity. Many studies on underwater sound levels have been conducted in the western North American Arctic and Fram Strait, but the rest of the Arctic is full of geographic gaps. Han et al. (2021, https://doi.org/10.1029/2021gl093097) published a study in Geophysical Research Letters on underwater sound levels in the East Siberian Sea, providing the first estimates of seasonal trends and the natural and anthropogenic drivers of underwater sound levels in this region. This is an excellent first step in filling geographic gaps in the Russian Arctic, and I call on other researchers to continue to fill these geographic gaps throughout the Arctic so that we can set a baseline and study changes to underwater sound levels being caused directly and indirectly by climate change. Plain Language Summary: The Arctic marine environment can be one of the quietest on Earth, particularly under solid sea ice. Climate change is causing sea ice to melt at an alarming rate and is also allowing increased human shipping activity. Both sea ice loss and increased shipping activity will likely lead to a noisier environment underwater in the Arctic. Many studies have examined how loud the underwater environment is in the Arctic of western North America and between East Greenland and Svalbard, but there are many areas throughout the Arctic with no studies. Han et al. (2021, https://doi.org/10.1029/2021gl093097) just published the first study on the loudness of the underwater environment in the East Siberian Sea. This study fills an important gap in our knowledge, and I call on other researchers to continue expanding studies into areas of the Arctic where we have no data on underwater sound levels. More studies will help us track the changes in underwater sound levels being caused by climate change. Key Points: Han et al. (2021) published a study in Geophysical Research Letters on underwater sound levels in the East Siberian SeaI place this study in the context of broader effort to establish baselines of underwater sound levels in the ArcticI call on researchers to continue filling geographic gaps in studies of underwater sound levels, particularly in the Russian Arctic [ABSTRACT FROM AUTHOR]

Changes in summer temperatures in Arctic Alaska have led to longer and warmer growing seasons over the last three decades. Corresponding with these changes in climate, the abundance and distributions of geese have increased and expanded over the same period. We used an experimental approach to assess the response of goose forage plants to simulated environmental change. We subjected Carex subspathacea, a preferred goose forage growing on the Arctic Coastal Plain (ACP) of Alaska, to manipulations of temperature and timing of spring thaw to measure potential effects in terms of plant nitrogen concentration, aboveground biomass, and total nitrogen availability. Carex subspathacea responded to warming in a dynamic fashion. Increases in temperature led to decreases in leaf nitrogen concentration but increases in aboveground biomass. The increase in biomass was stronger than the decline in nitrogen concentration such that total nitrogen availability was increased with temperature for the first 35–40 d of the season. Grazing removal accounted for only minimal offtake of biomass, and we found no indication that grazing maintained elevated levels of nitrogen concentration longer in the season as reported in other studies. Based on demonstrated relationships in the literature between forage nitrogen concentrations and gosling growth rates, we conclude that there is currently abundant high‐quality forage available across the ACP. This finding fits with recent evidence of high gosling growth rates and increasing trends in goose abundance on the ACP. Our results suggest that with climate warming of a few degrees, nitrogen concentration of forage may decrease, but forage biomass and total nitrogen availability will increase. Our data suggest that nitrogen concentration will not fall below the minimum threshold required by geese in the near future. As such, we suggest that there is currently no bottom‐up limitation to goose numbers on the ACP. [ABSTRACT FROM AUTHOR]

Species interactions are known to structure ecological communities. Still, the influence of climate change on biodiversity has primarily been evaluated by correlating individual species distributions with local climatic descriptors, then extrapolating into future climate scenarios. We ask whether predictions on arctic arthropod response to climate change can be improved by accounting for species interactions. For this, we use a 14‐year‐long, weekly time series from Greenland, resolved to the species level by mitogenome mapping. During the study period, temperature increased by 2°C and arthropod species richness halved. We show that with abiotic variables alone, we are essentially unable to predict species responses, but with species interactions included, the predictive power of the models improves considerably. Cascading trophic effects thereby emerge as important in structuring biodiversity response to climate change. Given the need to scale up from species‐level to community‐level projections of biodiversity change, these results represent a major step forward for predictive ecology. [ABSTRACT FROM AUTHOR]

Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid‐latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter‐model spread of PHT into the Arctic reflects the tug‐of‐war between sea‐ice and surface‐warming effects. Plain Language Summary: A major conundrum in current climate science is to understand what Arctic changes imply for the climate and environment in mid‐latitude regions. The Polar Amplification Model Intercomparison Project (PAMIP) designed a set of climate model experiments to specifically answer this question in a carefully designed, idealized framework. PAMIP's approach is to separate historic and projected climate change into parts associated with Arctic sea ice loss and ocean surface warming and investigate how these two contributions can influence the atmosphere. To isolate these effects, only models can be used, because, in reality, sea ice loss and ocean surface warming are strongly linked together. This letter focuses on what the PAMIP experiments imply for the transport and redistribution of heat and moisture in the atmosphere. In PAMIP, we learn that Arctic sea ice loss causes the atmosphere to reduce the transport of dry and cold air away from the Arctic while ocean warming causes more transport of moist warm air toward the Arctic. These two effects are in a tug‐of‐war, suggesting that climate change can cause a mix of competing impacts on the global energy transport from the tropics to the Arctic. Key Points: Sea ice loss exports static energy from the Arctic by warming the equatorward branch of the global mass circulationSea surface warming imports static energy into the Arctic by increasing the mid‐latitude mass transport, overwhelming the sea ice effectThere is more spread amongst models for the effect of sea‐surface warming than for sea ice loss [ABSTRACT FROM AUTHOR]

Aim: Growth rates of organisms are routinely used to summarize physiological performance, but the consequences of local evolutionary history and ecology are largely missed by analyses on wide biogeographical scales. This broad approach has been commonly applied to other physiological parameters across terrestrial and aquatic environments. Here, we examine growth rates of marine bivalves across all biogeographical realms, latitude, and temperature, with analyses to determine regional effects on growth on global scales. Location: Global: marine ecosystems. Time period: 1930–2018. Major taxa: Bivalves. Methods: We use a comprehensive data set of bivalve growth parameters (n = 966, 243 species) representing all biogeographical realms to calculate overall growth performances. We use these data with environmental temperature to analyse global patterns in growth, accounting for regional primary productivity and phylogeny using general additive mixed and linear models. The Arrhenius relationship and corresponding activation energies are used to quantify the sensitivity to temperature in each biogeographical realm and province. Results: Our analyses show that bivalve growth demonstrates latitudinal asymmetry and exhibits nonlinear relationships with latitude. We find that overall growth performance is affected by temperature and particulate organic carbon, but the form of these relationships differs with phylogeny. Growth is slower and more sensitive to increasing temperature in the Antarctic than it is in the Arctic, and decreases with increasing temperature in some tropical realms, a previously unidentified and fundamental difference in growth and physiological sensitivity. Main conclusions: Our findings provide compelling evidence that the widely used curvilinear relationship between temperature and growth rates in marine ectotherms is an inappropriate descriptor of thermal sensitivity, because it normalizes regional variations in physiological performance. Without a more detailed assessment of global physiological patterns, the responses of species to local variations associated with climate change will be under‐appreciated in global assessments of climate risk, minimizing the effectiveness of management and conservation. [ABSTRACT FROM AUTHOR]

Climate change is driving worldwide shifts in the distribution of biodiversity, and fundamental changes to global avian migrations. Some arctic‐nesting species may shorten their migration distance as warmer temperatures allow them to winter closer to their high‐latitude breeding grounds. However, such decisions are not without risks, since this intensifies pressure on resources when they are used for greater periods of time. In this study, we used an individual‐based model to predict how future changes in food abundance, winter ice coverage, and human disturbance could impact an Arctic/sub‐Arctic breeding goose species, black brant (Branta bernicla nigricans, Lawrence 1846), and their primary food source, common eelgrass (Zostera marina L.), at the Izembek Lagoon complex in southwest Alaska. Brant use the site during fall and spring migrations, and increasingly, for the duration of winter. The model was validated by comparing predictions to empirical observations of proportion of geese surviving, proportion of geese emigrating, mean duration of stay, mean rate of mass gain/loss, percentage of time spent feeding, number of bird days, peak population numbers, and distribution across the complex. The model predicted that reductions >50% of the current decadal (2007–2015) mean of eelgrass biomass, which have been observed in some years, or increases in the number of brant, could lead to a reduction in the proportion of birds that successfully migrate to their breeding grounds from the site. The model also predicted that access to eelgrass in lagoons other than Izembek was critical for overwinter survival and spring migration of brant, if overall eelgrass biomass was 50% of the decadal mean biomass. Geese were typically predicted to be more vulnerable to environmental change during winter and spring, when eelgrass biomass is lower, and thermoregulatory costs for the geese are higher than in fall. We discuss the consequences of these predictions for goose population trends in the face of natural and human drivers of change. [ABSTRACT FROM AUTHOR]

Climate simulations for the North Atlantic and Europe for recent and future conditions simulated with the regionally coupled ROM model are analyzed and compared to the results from the MPI‐ESM. The ROM simulations also include a biogeochemistry and ocean tides. For recent climate conditions, ROM generally improves the simulations compared to the driving model MPI‐ESM. Reduced oceanic biases in the Northern Atlantic are found, as well as a better simulation of the atmospheric circulation, notably storm tracks and blocking. Regarding future climate projections for the 21st century following the RCP 4.5 and 8.5 scenarios, MPI‐ESM and ROM largely agree qualitatively on the climate change signal over Europe. However, many important differences are identified. For example, ROM shows an SST cooling in the Subpolar Gyre, which is not present in MPI‐ESM. Under the RCP8.5 scenario, ROM Arctic sea ice cover is thinner and reaches the seasonally ice‐free state by 2055, well before MPI‐ESM. This shows the decisive importance of higher ocean resolution and regional coupling for determining the regional responses to global warming trends. Regarding biogeochemistry, both ROM and MPI‐ESM simulate a widespread decline in winter nutrient concentration in the North Atlantic of up to ~35%. On the other hand, the phytoplankton spring bloom in the Arctic and in the North‐Western Atlantic starts earlier, and the yearly primary production is enhanced in the Arctic in the late 21st century. These results clearly demonstrate the added value of ROM to determine more detailed and more reliable climate projections at the regional scale. Plain Language Summary: We downscale present climate and future climate change projections for the North Atlantic and Europe using a regionally coupled Earth System Model including atmosphere, ocean, river runoff, and ocean biogeochemistry components. This approach allows us to attain higher spatial resolution and to a more accurate representation of key physical processes, yielding a better simulation of present climate at regional and local scales when compared to the driving global climate model. Future climate change projections show more detail at regional and local scale, mostly related to the improvement in the representation of orography and bathymetry. These improvements along with a better representation of the interactive ocean‐atmosphere coupling lead to other remarkable differences with the driving global climate model: (1) colder Sea Surface Temperature in the Subpolar Gyre region, indicating a local convection collapse and a Atlantic Meridional Overturning Circulation slowdown; (2) a seasonal free‐ice Arctic is reached by 2055 under RCP8.5 scenario, well before projected by the driving global climate model; and (3) stronger reduction in nutrients in the North Atlantic by the end of the 21st century. These results clearly demonstrate the added value of the regionally coupled model system to determine more reliable climate projections at the regional scale. Key Points: The regionally coupled model shows reduced oceanic biases in the North Atlantic and a better simulation of the atmospheric circulationThe Arctic reaches a seasonally ice‐free state by 2055 with the regionally coupled model under RCP8.5 scenarioChanges in biogeochemistry are generally stronger and show enhanced details in the regionally coupled model [ABSTRACT FROM AUTHOR]

Arctic summer temperatures mostly cooled over the last ~7 kyr, owing to decreasing summer insolation. However, knowledge of the winter season is limited in the Arctic paleoclimate literature. Here we develop a composite record of δ18O from ice wedges—a winter precipitation archive—to reconstruct changes in winter climate in the northwestern Canadian Arctic since ~7.4 kyr b2k. Our record shows a long‐term δ18O enrichment (+(0.14 ± 0.10)‰ kyr−1), suggesting winter temperatures increased since the mid‐Holocene, a finding that is corroborated by reconstructions from the Siberian Arctic. Winter warming over the last ~7 kyr is consistent with increasing winter insolation and greenhouse gas forcing. This study provides some of the first insights on the sensitivity of winter temperatures in the Canadian Arctic to past, and potentially future, climate forcings, and contributes to a more seasonally holistic understanding of the Arctic system. Plain Language Summary: The history of climate change during the last 11,700 years, a period known as the Holocene Epoch, has been traditionally studied using natural climate proxies such as tree rings or pollen in the sedimentary record. Such records allow us to better understand past climate variability in response to changing greenhouse gas concentrations, solar radiation, and other boundary conditions. However, most traditional climate proxies are biological and sensitive mainly to growing‐season conditions, whereas changes in cold‐season conditions are not well described in the literature. This is especially true in the Arctic where recent climate warming has been most pronounced in the winter season, but few cold‐season‐specific proxy records are available. In this study, we develop a ~7,400‐year record of the δ18O isotope composition of relict ice wedges in the northwestern Canadian Arctic, a proxy type that is specifically sensitive to cold‐season conditions. We observe a long‐term increase in ice‐wedge δ18O over the past ~7,400 years, indicating warming winter temperatures since the mid‐Holocene. This warming corresponds to increasing winter solar radiation and greenhouse gas concentrations and is in agreement with recent reports from ice wedges in the Siberian Arctic. Key Points: Ice‐wedge δ18O reveals an enrichment trend over the last ~7.4 kyrThe enrichment reflects a long‐term winter warming trend, coinciding with increasing winter insolation and greenhouse gas forcingThis record provides key insights on winter Holocene climate not previously described by other records in this region [ABSTRACT FROM AUTHOR]

The Arctic is undergoing a rapid transition toward a seasonal ice regime, with widespread implications for the polar ecosystem, human activities, as well as the global climate. Here we focus on how the changing ice cover impacts transborder exchange of sea ice between the exclusive economic zones of the Arctic states. We use the Sea Ice Tracking Utility, which follows ice floes from formation to melt, in conjunction with output diagnostics from two ensembles of the Community Earth System Model that follow different future emissions scenarios. The Community Earth System Model projects that by midcentury, transnational ice exchange will more than triple, with the largest increase in the amount of transnational ice originating from Russia and the Central Arctic. However, long‐distance ice transport pathways are predicted to diminish in favor of ice exchanged between neighboring countries. By the end of the 21st century, we see a large difference between the two future emissions scenarios considered: Consistent nearly ice‐free summers under the high emissions scenario act to reduce the total fraction of transnational ice exchange compared to midcentury, whereas the low emissions scenario continues to see an increase in the proportion of transnational ice. Under both scenarios, transit times are predicted to decrease to less than 2 yr by 2100, compared to a maximum of 6 yr under present‐day conditions and 2.5 yr by midcentury. These significant changes in ice exchange and transit time raise important concerns regarding risks associated with ice‐rafted contaminants. Plain Language Summary: The Arctic is undergoing a rapid transition toward a thinner, less extensive, more mobile sea ice cover. This affects the amount of sea ice exchanged between the exclusive economic zones of Arctic states. Here we use an Earth System Model, the Community Earth System Model, to track sea ice from where it forms to where it ultimately melts. By midcentury, the area of sea ice exchanged between the different regions of the Arctic is predicted to more than triple compared to the end of the twentieth century, with the Central Arctic joining Russia as a major ice "exporter." At the same time, the exchange of sea ice over long distances is predicted to diminish in favor of ice exchanged between neighboring Arctic states. By midcentury, the average time required for ice to travel from one region to another is more than halved; by 2100, nearly all transports take less than a year, with little multiyear ice left in the Arctic. Sea ice provides a transport mechanism for a variety of material, including algae, dust, and a range of pollutants. The acceleration, and then disappearance, of sea ice has important implications for managing contamination in Arctic waters. Key Points: The CESM projects a large increase in transnational ice exchanged in the Arctic by midcentury with transit times reduced to under 2 yrBy midcentury the amount of transnational ice originating from Russia doubles and the Central Arctic emerges as the second dominant sourceLong‐distance ice transport pathways diminish by 2100 in favor of regions directly downstream, especially under the high emissions scenario [ABSTRACT FROM AUTHOR]

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Abstract: One of the most dramatic indicators of climate change is the reduction in the extent and thickness of Arctic sea ice that has resulted in an increase in wind‐driven sea ice mobility. During April and May 2017, satellite observations indicated that the ice arch that forms between Nares Strait and the Lincoln Sea collapsed. Typically, this collapse occurs in July or August allowing multiyear ice to exit the Arctic through Nares Strait. Here we show that the period of the collapse was associated with the presence of a polynya in northern Nares Strait, thin ice in the Lincoln Sea, and an unusual wind regime characterized by strong northerly flow. We propose that these anomalous conditions resulted in the arch's early collapse. If the ice in the region continues to thin, early collapses may occur more frequently with implications for the regional as well as the downstream climate and ecosystems. [ABSTRACT FROM AUTHOR]

A full understanding of population dynamics depends not only on estimation of mechanistic contributions of recruitment and survival, but also knowledge about the ecological processes that drive each of these vital rates. The process of recruitment in particular may be protracted over several years, and can depend on numerous ecological complexities until sexually mature adulthood is attained. We addressed long-term declines (23 breeding seasons, 1992-2014) in the per capita production of young by both Ross's Geese ( Chen rossii) and Lesser Snow Geese ( Chen caerulescens caerulescens) nesting at Karrak Lake in Canada's central Arctic. During this period, there was a contemporaneous increase from 0.4 to 1.1 million adults nesting at this colony. We evaluated whether (1) density-dependent nutritional deficiencies of pre-breeding females or (2) phenological mismatch between peak gosling hatch and peak forage quality, inferred from NDVI on the brood-rearing areas, may have been behind decadal declines in the per capita production of goslings. We found that, in years when pre-breeding females arrived to the nesting grounds with diminished nutrient reserves, the proportional composition of young during brood-rearing was reduced for both species. Furthermore, increased mismatch between peak gosling hatch and peak forage quality contributed additively to further declines in gosling production, in addition to declines caused by delayed nesting with associated subsequent negative effects on clutch size and nest success. The degree of mismatch increased over the course of our study because of advanced vegetation phenology without a corresponding advance in Goose nesting phenology. Vegetation phenology was significantly earlier in years with warm surface air temperatures measured in spring (i.e., 25 May-30 June). We suggest that both increased phenological mismatch and reduced nutritional condition of arriving females were behind declines in population-level recruitment, leading to the recent attenuation in population growth of Snow Geese. [ABSTRACT FROM AUTHOR]

To investigate the underlying mechanisms that control long-term recovery of tundra carbon (C) and nutrients after fire, we employed the Multiple Element Limitation ( MEL) model to simulate 200-yr post-fire changes in the biogeochemistry of three sites along a burn severity gradient in response to increases in air temperature, CO2 concentration, nitrogen (N) deposition, and phosphorus (P) weathering rates. The simulations were conducted for severely burned, moderately burned, and unburned arctic tundra. Our simulations indicated that recovery of C balance after fire was mainly determined by the internal redistribution of nutrients among ecosystem components (controlled by air temperature), rather than the supply of nutrients from external sources (e.g., nitrogen deposition and fixation, phosphorus weathering). Increases in air temperature and atmospheric CO2 concentration resulted in (1) a net transfer of nutrient from soil organic matter to vegetation and (2) higher C : nutrient ratios in vegetation and soil organic matter. These changes led to gains in vegetation biomass C but net losses in soil organic C stocks. Under a warming climate, nutrients lost in wildfire were difficult to recover because the warming-induced acceleration in nutrient cycles caused further net nutrient loss from the system through leaching. In both burned and unburned tundra, the warming-caused acceleration in nutrient cycles and increases in ecosystem C stocks were eventually constrained by increases in soil C : nutrient ratios, which increased microbial retention of plant-available nutrients in the soil. Accelerated nutrient turnover, loss of C, and increasing soil temperatures will likely result in vegetation changes, which further regulate the long-term biogeochemical succession. Our analysis should help in the assessment of tundra C budgets and of the recovery of biogeochemical function following fire, which is in turn necessary for the maintenance of wildlife habitat and tundra vegetation. [ABSTRACT FROM AUTHOR]

The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flows to detect, observe, and understand changes and provide adaptation information. There has, however, been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska, and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle. [ABSTRACT FROM AUTHOR]

Recent trends and climate models suggest that the Arctic summer sea ice cover is likely to be lost before climate interventions can stabilize it. There are environmental, socioeconomic, and sociocultural arguments for, but also against, restoring and sustaining current conditions. Even if global warming can be reversed, some people will experience ice-free summers before perennial sea ice begins to return. We ask: How will future generations feel about bringing sea ice back where they have not experienced it before? How will conflicted interests in ice-covered vs. ice-free conditions be resolved? What role will science play in these debates? [ABSTRACT FROM AUTHOR]

1. The polar desert biome of the Canadian high Arctic Archipelago is currently experiencing some of the greatest mean annual air temperature increases on the planet, threatening the stability of ecosystems residing above temperature-sensitive permafrost. 2. Ice wedges are the most widespread form of ground ice, occurring in up to 25% of the world's terrestrial near-surface, and their melting (thermokarst) may catalyse a suite of biotic and ecological changes, facilitating major ecosystem shifts. 3. These unknown ecosystem shifts raise serious questions as to how permafrost stability, vegetation diversity and edaphic conditions will change with a warming high Arctic. Ecosystem and thermokarst processes tend to be examined independently, limiting our understanding of a coupled system whereby the effect of climate change on one will affect the outcome of the other. 4. Using in-depth, comprehensive field observations and a space-for-time approach, we investigate the highly structured landscape that has emerged due to the thermokarst-induced partitioning of microhabitats. We examine differences in vegetation diversity, community composition and soil conditions on the Fosheim Peninsula, Ellesmere Island, Nunavut. We hypothesize that (i) greater ice wedge subsidence results in increased vegetation cover due to elevated soil moisture, thereby decreasing the seasonal depth of thaw and restricting groundwater outflow; (ii) thermokarst processes result in altered vegetation richness, turnover and dispersion, with greater microhabitat diversity at the landscape scale; and (iii) shifts in hydrology and plant community structure alter soil chemistry. 5. We found that the disturbance caused by melting ice wedges catalysed a suite of environmental and biotic effects: topographical changes, a new hydrological balance, significant species richness and turnover changes, and distinct soil chemistries. Thermokarst areas favour a subset of species unique from the polar desert and are characterized by greater species turnover (b-diversity) across the landscape. 6. Synthesis. Our findings suggest that projected increases of thermokarst in the polar desert will lead to the increased partitioning of microhabitats, creating a more heterogeneous high arctic landscape through diverging vegetation communities and edaphic conditions, resulting in a wetland-like biome in the high Arctic that could replace much of the ice-rich polar desert. [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The physical and biological responses to rapid arctic warming are proving acute, and as such, there is a need to monitor, understand, and predict ecological responses over large spatial and temporal scales. The use of the normalized difference vegetation index (NDVI) acquired from airborne and satellite sensors addresses this need, as it is widely used as a tool for detecting and quantifying spatial and temporal dynamics of tundra vegetation cover, productivity, and phenology. Such extensive use of the NDVI to quantify vegetation characteristics suggests that it may be similarly applied to characterizing primary and secondary consumer communities. Here, we develop empirical models to predict canopy arthropod biomass with canopy-level measurements of the NDVI both across and within distinct tundra vegetation communities over four growing seasons in the Arctic Foothills region of the Brooks Range, Alaska, USA. When canopy arthropod biomass is predicted with the NDVI across all four growing seasons, our overall model that includes all four vegetation communities explains 63% of the variance in canopy arthropod biomass, whereas our models specific to each of the four vegetation communities explain 74% (moist tussock tundra), 82% (erect shrub tundra), 84% (riparian shrub tundra), and 87% (dwarf shrub tundra) of the observed variation in canopy arthropod biomass. our field-based study suggests that measurements of the NDVI made from air- and spaceborne sensors may be able to quantify spatial and temporal variation in canopy arthropod biomass at landscape to regional scales. [ABSTRACT FROM AUTHOR]