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Alaska Native people and rural Alaskans rely on subsistence harvesting of wild resources for their well-being. This study integrates publicly-available data from >30 Interior Alaskan communities to examine the geospatial patterns of subsistence and develop model-based maps of subsistence land use for the region. Through analysis and identification of lands important for subsistence, this study provides a tool to inform sound decision-making on land use and facilitate communication among land users. We found that most contemporary subsistence land use (approx. 70%) occurred within areas that have been traditionally used for generations. The size of subsistence use areas varied widely among communities (approx. 50--25,000 km²) and was directly related to total population. Subsistence land use varied both by resource type and by season, which reflects differences in resource availability and harvesting strategies. The spatial patterns of subsistence land use were strongly influenced by accessibility, which differed between remote and road-connected communities. Our logistic regression models showed that subsistence land use was largely predictable by distance to communities, distance to main travel corridors (roads and/or rivers), distance to lakes (for remote communities), and population size. Probability maps of subsistence use were generated and classified into used and unused areas with accuracies from 83--86%. Results suggest a large spatial extent (353,771 km²) of subsistence land use in Interior Alaska, comprising >60% of the land area of this sparselypopulated region. The outcomes of this study provide a more comprehensive view of subsistence land use patterns and spatial products that may help reduce conflict and inform decisions affecting lands and resources important for sustaining the subsistence way of life. [ABSTRACT FROM AUTHOR]

Warmer climatic conditions have been associated with numerous hydrologic changes that may impact riverbank erosion in cold regions, but the net effect is not well understood. We used regression and correlation analyses to examine the relationships among subarctic riverbank erosion and seasonal hydrology, the impact of climate change and variability, and the societal implications. Geomorphic change (loss and gain of vegetated land) was mapped along several river reaches in the Yukon River Basin, Alaska, throughout 1984 and 2017 using Landsat satellite imagery. Annual erosion rates were estimated from these spatial data. At most study sites, erosion rates (km2/year) were either positively correlated (r = 0.68–0.84, p = 0.0085–0.061) with monthly mean discharge within the cold season or inversely correlated (r = − 0.74 – −0.62, p < 0.10) with river ice breakup date in the spring. These proximate controls on erosion, in turn, were influenced both by climate variability and long-term climatic change. We conclude that increased cold season discharge and earlier freshet that occurs under warmer conditions enhance riverbank erosion in most areas. Climate-related changes to fluvial dynamics may impact communities through effects on infrastructure, travel safety, channel navigability, fish and wildlife habitat, and access to subsistence resources. [ABSTRACT FROM AUTHOR]

Climate change coupled with an intensifying wildfire regime is becoming an important driver of permafrost loss and ecosystem change in the northern boreal forest. There is a growing need to understand the effects of fire on the spatial distribution of permafrost and its associated ecological consequences. We focus on the effects of fire a decade after disturbance in a rocky upland landscape in the interior Alaskan boreal forest. Our main objectives were to (1) map near-surface permafrost distribution and drainage classes and (2) analyze the controls over landscape-scale patterns of post-fire permafrost degradation. Relationships among remote sensing variables and field-based data on soil properties (temperature, moisture, organic layer thickness) and vegetation (plant community composition) were analyzed using correlation, regression, and ordination analyses. The remote sensing data we considered included spectral indices from optical datasets (Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI)), the principal components of a time series of radar backscatter (Advanced Land Observing Satellite-Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR)), and topographic variables from a Light Detection and Ranging (LiDAR)-derived digital elevation model (DEM). We found strong empirical relationships between the normalized difference infrared index (NDII) and post-fire vegetation, soil moisture, and soil temperature, enabling us to indirectly map permafrost status and drainage class using regression-based models. The thickness of the insulating surface organic layer after fire, a measure of burn severity, was an important control over the extent of permafrost degradation. According to our classifications, 90% of the area considered to have experienced high severity burn (using the difference normalized burn ratio (dNBR)) lacked permafrost after fire. Permafrost thaw, in turn, likely increased drainage and resulted in drier surface soils. Burn severity also influenced plant community composition, which was tightly linked to soil temperature and moisture. Overall, interactions between burn severity, topography, and vegetation appear to control the distribution of near-surface permafrost and associated drainage conditions after disturbance. [ABSTRACT FROM AUTHOR]

This study introduces a new automated system that blends multi-satellite information and citizen science data for reliable and timely observations of lake and river ice in under-observed northern regions. The system leverages the Google Earth Engine resources to facilitate the analysis and visualization of ice conditions. The adopted approach utilizes a combination of moderate and high-resolution optical data, along with radar observations. The results demonstrate the system's capability to accurately detect and monitor river ice, particularly during key periods, such as the freeze-up and the breakup. The integration citizen science data showed added values in the validation of remote sensing products, as well as filling gaps whenever satellite observations cannot be collected due to cloud obstruction. Moreover, it was shown that citizen science data can be converted to valuable quantitative information, such as the case of ice thickness, which is very useful when combined with ice extent derived from remote sensing. In this study, citizen science data were employed for the quantitative assessment of the remote sensing product. Obtained results showed a good agreement between the product and observed river status, with a Critical Success Index of 0.82. Notably, the system has shown effectiveness in capturing the spatial and temporal evolution of snow and ice conditions, as evidenced by its application in analyzing specific ice jam events in 2023. The study concludes that the developed system marks a significant advancement in river ice monitoring, combining technological innovation with community engagement. [ABSTRACT FROM AUTHOR]

The formation, growth, and decay of freshwater ice on lakes and rivers are fundamental processes of northern regions with wide-ranging implications for socio-ecological systems. Ice thickness at the end of winter is perhaps the best integration of cold-season weather and climate, while the duration of thick and growing ice cover is a useful indicator for the winter travel and recreation season. Both maximum ice thickness (MIT) and ice travel duration (ITD) can be estimated from temperature-driven ice growth curves fit to ice thickness observations. We simulated and analyzed ice growth curves based on ice thickness data collected from a range of observation programs throughout Alaska spanning the past 20–60 years to understand patterns and trends in lake and river ice. Results suggest reductions in MIT (thinning) in several northern, interior, and coastal regions of Alaska and overall greater interannual variability in rivers compared to lakes. Interior regions generally showed less variability in MIT and even slightly increasing trends in at least one river site. Average ITD ranged from 214 d in the northernmost lakes to 114 d across southernmost lakes, with significant decreases in duration for half of sites. River ITD showed low regional variability but high interannual variability, underscoring the challenges with predicting seasonally consistent river travel. Standardization and analysis of these ice observation data provide a comprehensive summary for understanding changes in winter climate and its impact on freshwater ice services. [ABSTRACT FROM AUTHOR]

Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1(relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets. [ABSTRACT FROM AUTHOR]

Amplified climate warming at high northern latitudes is challenging societies that depend on local provisional and cultural ecosystem services, e.g., subsistence resources, for their livelihoods. Previous qualitative research suggests that climate-induced changes in environmental conditions are affecting rural residents' ability to travel across the land and access local resources, but detailed information on the nature and effect of specific conditions is lacking. Our objectives were to identify climate-related environmental conditions affecting subsistence travel and access, and then estimate rural resident travel and access vulnerability to those environmental conditions. We collaborated with nine Interior Alaskan communities within the Yukon River basin and provided residents with cameraequipped GPS units to document environmental conditions directly affecting subsistence access for 12 consecutive months. We also conducted comprehensive interviews with research participants to incorporate the effects of environmental conditions not documented with GPS units. Environmental conditions reported by rural residents were categorized into seven condition types. We assessed vulnerability to each condition by accounting for both likelihood (number of times a condition was documented) and sensitivity (magnitude of the effect from the condition) information derived from GPS observations and interviews. We also tested for differences in mean vulnerability values among environmental conditions and between community types (road-connected vs. remote) using a oneway analysis of variance. Rural community travel and access were most vulnerable to changes in ice conditions, erosion, vegetative community composition, and water levels. Environmental conditions that impeded natural travel corridors, e.g., waterways, more strongly influenced remote communities than those connected by roads. Increased vulnerability to environmental change puts remote communities at increased risk for food-security issues. Our study used a novel community-based approach to integrate local knowledge with scientific analysis to document and estimate the relative effects that specific environmental conditions are having on access to subsistence resources across Interior Alaska. [ABSTRACT FROM AUTHOR]

Characterization of permafrost, particularly warm and near-surface permafrost which can contain significant liquid water, is critical to understanding complex interrelationships with climate change, ecosystems, and disturbances such as wildfires. Understanding the vulnerability and resilience of permafrost requires an interdisciplinary approach, relying on (for example) geophysical investigations, ecological characterization, direct observations, remote sensing, and more. As part of a multiyear investigation into the impacts of wildfires on permafrost, we have collected in situ measurements of the nuclear magnetic resonance (NMR) response of the active layer and permafrost in a variety of soil conditions, types, and saturations. In this paper, we summarize the NMR data and present quantitative relationships between active layer and permafrost liquid water content and pore sizes and show the efficacy of borehole NMR (bNMR) to permafrost studies. Through statistical analyses and synthetic freezing simulations, we also demonstrate that borehole NMR is sensitive to the nucleation of ice within soil pore spaces. [ABSTRACT FROM AUTHOR]

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type. [ABSTRACT FROM AUTHOR]