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ABSTRACT Climate change is inducing wide-scale permafrost thaw in the Arctic and subarctic, triggering concerns that long-dormant pathogens could reemerge from the thawing ground and initiate epidemics or pandemics. Viruses, as opposed to bacterial pathogens, garner particular interest because outbreaks cannot be controlled with antibiotics, though the effects can be mitigated by vaccines and newer antiviral drugs. To evaluate the potential hazards posed by viral pathogens emerging from thawing permafrost, we review information from a diverse range of disciplines. This includes efforts to recover infectious virus from human remains, studies on disease occurrence in polar animal populations, investigations into viral persistence and infectivity in permafrost, and assessments of human exposure to the enormous viral diversity present in the environment. Based on currently available knowledge, we conclude that the risk posed by viruses from thawing permafrost is no greater than viruses in other environments such as temperate soils and aquatic systems. 

Abstract Co-production, or integrating a range of perspectives from researchers and non-researchers into the knowledge development process, is considered valuable for increasing the potential that scientific results will be applied by practitioners. While the literature around co-production often touts the benefits of such work, there is less focus on the potential costs of co-production, and discussions often lack nuance about the specific meaning of co-production in a particular context. In this perspective essay, we use an example co-production process focused on the development of a science agenda for a federal research program to consider the ideal of co-production. Specifically, we reflect on the appropriate level of non-researcher involvement throughout the full cycle of research, and position our process within the diverse range of existing co-production approaches. We suggest that the ideal of co-production is not necessarily one that integrates the maximum amount of non-research involvement throughout the full cycle of research at all costs, but one that focuses on mitigating the research-management gap while limiting the risks to those involved. 

ABSTRACT Permafrost microbial research has flourished in the past decades, due in part to improvements in sampling and molecular techniques, but also the increased focus on the permafrost greenhouse gas feedback to climate change and other ecological processes in high latitude and alpine permafrost soils. Permafrost microorganisms are adapted to these extreme environments and remain active at low temperatures and when resources are limited. They are also an important component of global elemental cycles as they regulate organic matter turnover and greenhouse gas production, particularly as permafrost thaws. Here we review the permafrost microbiology literature coupled with an exploration of its historical aspects, with a particular focus on a new understanding advanced by molecular biology techniques. We further identify knowledge gaps and ways forward to improve our understanding of microbial contributions to ecosystem biogeochemistry of permafrost‐affected systems. 

Abstract ContextClimate change is altering suitable habitat distributions of many species at high latitudes. Fleshy fruit-producing plants (hereafter, “berry plants”) are important in arctic food webs and as subsistence resources for human communities, but their response to a warming and increasingly variable climate at a landscape scale has not yet been examined. ObjectivesWe aimed to identify environmental determinants of berry plant distribution and predict how climate change might shift these distributions. MethodsWe used species distribution models to identify characteristics and predict the distribution of suitable habitat under current (2006–2013) and future climate conditions (2081–2100; representative concentration pathways 4.5, 6.0, & 8.5) for five berry plant species:Vaccinium uliginosumL.,Empetrum nigrumL.,Rubus chamaemorusL.,Vaccinium vitis-idaeaL., andViburnum edule(Michx.) Raf.. ResultsElevation, soil characteristics, and January and July temperatures were important drivers of habitat distributions. Future suitable habitat predictions showed net declines in suitable habitat area for all species modeled under almost all future climate scenarios tested. ConclusionsOur work contributes to understanding potential geographic shifts in suitable berry plant habitat with climate change at a landscape scale. Shifting and retracting distributions may alter where communities can harvest, suggesting that access to these resources may become restricted in the future. Our prediction maps may help inform climate adaptation planning as communities anticipate shifting access to harvesting locations. 

Abstract The Arctic–Boreal Zone is rapidly warming, impacting its large soil carbon stocks. Here we use a new compilation of terrestrial ecosystem CO₂fluxes, geospatial datasets and random forest models to show that although the Arctic–Boreal Zone was overall an increasing terrestrial CO₂sink from 2001 to 2020 (mean ± standard deviation in net ecosystem exchange, −548 ± 140 Tg C yr⁻¹; trend, −14 Tg C yr⁻¹;P < 0.001), more than 30% of the region was a net CO₂source. Tundra regions may have already started to function on average as CO₂sources, demonstrating a shift in carbon dynamics. When fire emissions are factored in, the increasing Arctic–Boreal Zone sink is no longer statistically significant (budget, −319 ± 140 Tg C yr⁻¹; trend, −9 Tg C yr⁻¹), and the permafrost region becomes CO₂neutral (budget, −24 ± 123 Tg C yr⁻¹; trend, −3 Tg C yr⁻¹), underscoring the importance of fire in this region. 

Abstract How forests respond to accelerated climate change will affect the terrestrial carbon cycle. To better understand these responses, more examples are needed to assess how tree growth rates react to abrupt changes in growing‐season temperatures. Here we use a natural experiment in which a glacier's fluctuations exposed a temperate rainforest to changes in summer temperatures of similar magnitude to those predicted to occur by 2050. We hypothesized that the onset of glacier‐accentuated temperature trends would act to increase the variance in stand‐level tree growth rates, a proxy for forest net primary productivity. Instead, dendrochronological records reveal that the growth rates of five, co‐occurring conifer species became less synchronous, and this diversification of species responses acted to reduce the variance and to increase the stability of community‐wide growth rates. These results warrant further inquiry into how climate‐induced changes in tree‐growth diversity may help stabilize future ecosystem services like forest carbon storage. 

Abstract Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we presentThe Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m⁻²) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic. 

Abstract Snow conditions are changing rapidly across our planet, which has important implications for wildlife managers. In Alaska, USA, the later arrival of snow is challenging wildlife managers' ability to conduct aerial fall (autumn) moose (Alces alces) surveys. Complete snow cover is required to reliably detect and count moose using visual observation from an aircraft. With inadequate snow to help generate high‐quality moose survey data, it is difficult for managers to determine if they are effectively meeting population goals and optimizing hunting opportunities. We quantified past relationships and projected future trends between snow conditions and moose survey success across 7 different moose management areas in Alaska using 32 years (1987–2019) of moose survey data and modeled snow data. We found that modeled mean snow depth was 15 cm (SD = 11) when moose surveys were initiated, and snow depths were greater in years when surveys were completed compared to years when surveys were canceled. Further, we found that mean snow depth toward the beginning of the survey season (1 November) was the best predictor of whether a survey was completed in any given year. Based on modeled conditions, the trend in mean snow depth on 1 November declined from 1980 to 2020 in 5 out of 7 survey areas. These findings, coupled with future projections, indicated that by 2055, the delayed onset of adequate snow accumulation in the fall will prevent the completion of moose surveys over roughly 60% of Alaska's managed moose areas at this time of the year. Our findings can be used by wildlife managers to guide decisions related to the future reliability of aerial fall moose surveys and help to identify timelines for development of alternate measurement and monitoring methods. 

Abstract Boreal forests of Alaska and Western Canada are experiencing rapid climate change characterized by higher temperatures, more extreme droughts, and changing disturbance regimes, resulting in forest mortality and composition changes. Mechanistic models are increasingly important for predicting future forest trends as the region experiences novel environmental change. Previously, many process-based models have generated starting conditions by ‘spinning up’ to equilibrium. However, setting appropriate initial conditions remains a persistent challenge in using mechanistic forest models, where stochastic events and latent parameters governing tree establishment have long-lasting impacts on simulation outcomes. Recent advances in remote sensing analysis provide information that can help address this issue. We updated an individual-based gap model, the University of Virginia Forest Model Enhanced (UVAFME), to include initial conditions derived from aerial and satellite imagery at two locations. Following these updates, material legacies (e.g. trees, seed banks, soil organic layer) allowed new forest types to persist in UVAFME simulations, landscape-level forest heterogeneity increased, and forest-wide biomass estimates increased. At both study sites, initialization from remotely sensed data had a strong impact on forest cover and volume. Climate change impacts were simulated decades earlier than when the model was ‘spun up’. In Alaska’s Tanana Valley State Forest, warmer climate scenarios drove deciduous expansion, increased drought stress, and resulted in a 28% decrease in overall biomass by 2100 between historical and high emissions climate scenarios. At a lowland site in Northern British Columbia, lodgepole pine(Pinus contorta)remained dominant and became more productive with exogenous climate forcing as temperature, nutrient, and flooding limitations decreased. These case studies demonstrate a new framework for forest modeling and emphasize the advantages of integrating remotely sensed data with mechanistic models, thereby laying groundwork for future research that explores near-term impacts of non-stationary ecological change. 

Summary Plant phenology, the timing of recurrent biological events, shows key and complex response to climate warming, with consequences for ecosystem functions and services. A key challenge for predicting plant phenology under future climates is to determine whether the phenological changes will persist with more intensive and long‐term warming.Here, we conducted a meta‐analysis of 103 experimental warming studies around the globe to investigate the responses of four phenophases – leaf‐out, first flowering, last flowering, and leaf coloring.We showed that warming advanced leaf‐out and flowering but delayed leaf coloring across herbaceous and woody plants. As the magnitude of warming increased, the response of most plant phenophases gradually leveled off for herbaceous plants, while phenology responded in proportion to warming in woody plants. We also found that the experimental effects of warming on plant phenology diminished over time across all phenophases. Specifically, the rate of changes in first flowering for herbaceous species, as well as leaf‐out and leaf coloring for woody species, decreased as the experimental duration extended.Together, these results suggest that the real‐world impact of global warming on plant phenology will diminish over time as temperatures continue to increase.