Enhanced shrub growth in the Arctic increases habitat connectivity for browsing herbivores

Extralimital terrestrials: A reassessment of range limits in Alaska's land mammals

Understanding and mitigating the effects of anthropogenic climate change on species distributions requires the ability to track range shifts over time. This is particularly true for species occupying high-latitude regions, which are experiencing more extreme climate change than the rest of the world. In North America, the geographic ranges of many mammals reach their northernmost extent in Alaska, positioning this region at the leading edge of climate-induced distribution change. Over a decade has elapsed since the publication of the last spatial assessments of terrestrial mammals in the state. We compared public occurrence records against commonly referenced range maps to evaluate potential extralimital records and develop repeatable baseline range maps. We compared occurrence records from the Global Biodiversity Information Facility for 61 terrestrial mammal species native to mainland Alaska against a variety of range estimates (International Union for Conservation of Nature, Alaska Gap Analysis Project, and the published literature). We mapped extralimital records and calculated proportions of occurrences encompassed by range extents, measured mean direction and distance to prior range margins, evaluated predictive accuracy of published species models, and highlighted observations on federal lands in Alaska. Range comparisons identified 6,848 extralimital records for 39 of 61 (63.9%) terrestrial mainland Alaskan species. On average, 95.5% of Alaska Gap Analysis Project occurrence records and ranges were deemed accurate (i.e., > 90.0% correct) for 31 of 37 species, but overestimated extents for 13 species. The International Union for Conservation of Nature range maps encompassed 68.1% of occurrence records and were > 90% accurate for 17 of 39 species. Extralimital records represent either improved sampling and digitization or actual geographic range expansions. Here we provide new data-driven range maps, update standards for the archiving of museum-quality locational records and offer recommendations for mapping range changes for monitoring and conservation.

The Arctic Plant Aboveground Biomass Synthesis Dataset

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 present The 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.

Wolverines (Gulo gulo) in the Arctic: Revisiting distribution and identifying research and conservation priorities amid rapid environmental change

Wolverines (Gulo gulo) occupy most of the globe’s Arctic tundra. Given the rapidly warming climate and expanding human activity in this biome, understanding wolverine ecology, and therefore the species’ vulnerability to such changes, is increasingly important for developing research priorities and effective management strategies. Here, we review and synthesize knowledge of wolverines in the Arctic using both Western science sources and available Indigenous Knowledge (IK) to improve our understanding of wolverine ecology in the Arctic and better predict the species’ susceptibility to change. To accomplish this, we update the pan-Arctic distribution map of wolverines to account for recent observations and then discuss resulting inference and uncertainties. We use these patterns to contextualize and discuss potential underlying drivers of distribution and population dynamics, drawing upon knowledge of food habits, habitat associations, and harvest, as well as studies of wolverine ecology elsewhere. We then identify four broad areas to prioritize conservation and research efforts: (1) Monitoring trends in population abundance, demographics, and distribution and the drivers thereof, (2) Evaluating and predicting wolverines’ responses to ongoing climate change, particularly the consequences of reduced snow and sea ice, and shifts in prey availability, (3) Understanding wolverines’ response to human development, including the possible impact of wintertime over-snow travel and seismic testing to reproductive denning, as well as vulnerability to hunting and trapping associated with increased human access, and (4) Ensuring that current and future harvest are sustainable.

Late Pleistocene shrub expansion preceded megafauna turnover and extinctions in eastern Beringia

The collapse of the steppe-tundra biome (mammoth steppe) at the end of the Pleistocene is used as an important example of top-down ecosystem cascades, where human hunting of keystone species led to profound changes in vegetation across high latitudes in the Northern Hemisphere. Alternatively, it is argued that this biome transformation occurred through a bottom-up process, where climate-driven expansion of shrub tundra (Betula, Salix spp.) replaced the steppe-tundra vegetation that grazing megafauna taxa relied on. In eastern Beringia, these differing hypotheses remain largely untested, in part because the precise timing and spatial pattern of Late Pleistocene shrub expansion remains poorly resolved. This uncertainty is caused by chronological ambiguity in many lake sediment records, which typically rely on radiocarbon (¹⁴C) dates from bulk sediment or aquatic macrofossils-materials that are known to overestimate the age of sediment layers. Here, we reexamine Late Pleistocene pollen records for which ¹⁴C dating of terrestrial macrofossils is available and augment these data with ¹⁴C dates from arctic ground-squirrel middens and plant macrofossils. Comparing these paleovegetation data with a database of published ¹⁴C dates from megafauna remains, we find the postglacial expansion of shrub tundra preceded the regional extinctions of horse (Equus spp.) and mammoth (Mammuthus primigenius) and began during a period when the frequency of ¹⁴C dates indicates large grazers were abundant. These results are not consistent with a model of top-down ecosystem cascades and support the hypothesis that climate-driven habitat loss preceded and contributed to turnover in mammal communities.

Characterizing Wetland Inundation and Vegetation Dynamics in the Arctic Coastal Plain Using Recent Satellite Data and Field Photos

Arctic wetlands play a critical role in the global carbon cycle and are experiencing disproportionate impacts from climate change. Even though Alaska hosts 65% of U.S. wetlands, less than half of the wetlands in Alaska have been mapped by the U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) or other high-resolution wetlands protocols. The availability of time series satellite data and the development of machine learning algorithms have enabled the characterization of Arctic wetland inundation dynamics and vegetation types with limited ground data input. In this study, we built a semi-automatic process to generate sub-pixel water fraction (SWF) maps across the Coastal Plain of the Arctic National Wildlife Refuge (ANWR) in Alaska using random forest regression and 139 Sentinel-2 images taken in ice-free seasons from 2016 to 2019. With this, we characterized the seasonal dynamics of wetland inundation and explored their potential usage in determining NWI water regimes. The highest levels of surface water expression were detected in June, resulting from seasonal active layer thaw and snowmelt. Inundation was most variable in riverbeds, lake and pond margins, and depressional wetlands, where water levels fluctuate substantially between dry and wet seasons. NWI water regimes that indicate frequent inundation, such as permanently flooded wetlands, had high SWF values (SWF ≥ 90%), while those with infrequent inundation, such as temporarily flooded wetlands, had low SWF values (SWF < 10%). Vegetation types were also classified through the synergistic use of a vegetation index, water regimes, synthetic-aperture radar (SAR) data, topographic data, and a random forest classifier. The random forest classification algorithms demonstrated good performance in classifying Arctic wetland vegetation types, with an overall accuracy of 0.87. Compared with NWI data produced in the 1980s, scrub-shrub wetlands appear to have increased from 91 to 258 km2 over the last three decades, which is the largest percentage change (182%) among all vegetation types. However, additional field data are needed to confirm this shift in vegetation type. This study demonstrates the potential of using time series satellite data and machine learning algorithms in characterizing inundation dynamics and vegetation types of Arctic wetlands. This approach could aid in the creation and maintenance of wetland inventories, including the NWI, in Arctic regions and enable an improved understanding of long-term wetland dynamics.

Homeostatic Response to Three Years of Experimental Warming Suggests High Intrinsic Natural Resistance in the Páramos to Warming in the Short Term

Páramos, tropical alpine ecosystems, host one of the world’s most diverse alpine floras, account for the largest water reservoirs in the Andes, and some of the largest soil carbon pools worldwide. It is of global importance to understand the future of this extremely carbon-rich ecosystem in a warmer world and its role on global climate feedbacks. This study presents the result of the first in situ warming experiment in two Colombian páramos using Open-Top Chambers. We evaluated the response to warming of several ecosystem carbon balance-related processes, including decomposition, soil respiration, photosynthesis, plant productivity, and vegetation structure after 3 years of warming. We found that OTCs are an efficient warming method in the páramo, increasing mean air temperature by 1.7°C and mean daytime temperature by 3.4°C. The maximum air temperature differences between OTC and control was 23.1°C. Soil temperature increased only by 0.1°C. After 3 years of warming using 20 OTC (10 per páramo) in a randomized block design, we found no evidence that warming increased CO2 emissions from soil respiration, nor did it increase decomposition rate, photosynthesis or productivity in the two páramos studied. However, total C and N in the soil and vegetation structure are slowly changing as result of warming and changes are site dependent. In Sumapaz, shrubs, and graminoids cover increased in response to warming while in Matarredonda we observed an increase in lichen cover. Whether this change in vegetation might influence the carbon sequestration potential of the páramo needs to be further evaluated. Our results suggest that páramos ecosystems can resist an increase in temperature with no significant alteration of ecosystem carbon balance related processes in the short term. However, the long-term effect of warming could depend on the vegetation changes and how these changes alter the microbial soil composition and soil processes. The differential response among páramos suggest that the response to warming could be highly dependent on the initial conditions and therefore we urgently need more warming experiments in páramos to understand how specific site characteristics will affect their response to warming and their role in global climate feedbacks.