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Plot-level photography is an attractive time-saving alternative to field measurements for vegetation monitoring. However, widespread adoption of this technique relies on efficient workflows for post-processing images and the accuracy of the resulting products. Here, we estimated relative vegetation cover using both traditional field sampling methods (point frame) and semi-automated classification of photographs (plot-level photography) across thirty 1 m2 plots near Utqiaġvik, Alaska, from 2012 to 2021. Geographic object-based image analysis (GEOBIA) was applied to generate objects based on the three spectral bands (red, green, and blue) of the images. Five machine learning algorithms were then applied to classify the objects into vegetation groups, and random forest performed best (60.5% overall accuracy). Objects were reliably classified into the following classes: bryophytes, forbs, graminoids, litter, shadows, and standing dead. Deciduous shrubs and lichens were not reliably classified. Multinomial regression models were used to gauge if the cover estimates from plot-level photography could accurately predict the cover estimates from the point frame across space or time. Plot-level photography yielded useful estimates of vegetation cover for graminoids. However, the predictive performance varied both by vegetation class and whether it was being used to predict cover in new locations or change over time in previously sampled plots. These results suggest that plot-level photography may maximize the efficient use of time, funding, and available technology to monitor vegetation cover in the Arctic, but the accuracy of current semi-automated image analysis is not sufficient to detect small changes in cover. 

The Arctic is experiencing rapid climate change. This research documents changes to tundra vegetation near Atqasuk and Utqiaġvik, Alaska. At each location, 30 plots were sampled annually from 2010 to 2019 using a point frame. For every encounter, we recorded the height and classified it into eight groupings (deciduous shrubs, evergreen shrubs, forbs, graminoids, bryophytes, lichens, litter, and standing dead vegetation); for vascular plants we also identified the species. We found an increase in plant stature and cover over time, consistent with regional warming. Graminoid cover and height increased at both sites, with a 5-fold increase in cover in Atqasuk. At Atqasuk, the cover and height of shrubs and forbs increased. Species diversity decreased at both the sites. Year was generally the strongest predictor of vegetation change, suggesting a cumulative change over time; however, soil moisture and soil temperature were also predictors of vegetation change. We anticipate that plants in the region will continue to grow taller as the region warms, resulting in greater plant cover, especially of graminoids and shrubs. The increase in plant cover and accumulation of litter may negatively impact non-vascular plants. Continued changes in community structure will impact energy balance and carbon cycling and may have regional and global consequences. 

In dryland soils, spatiotemporal variation in surface soils (0–10 cm) plays an important role in the function of the “critical zone” that extends from canopy to groundwater. Understanding connections between soil microbes and biogeochemical cycling in surface soils requires repeated multivariate measurements of nutrients, microbial abundance, and microbial function. We examined these processes in resource islands and interspaces over a two‐month period at a Chihuahuan Desert bajada shrubland site. We collected soil inProsopis glandulosa(honey mesquite),Larrea tridentata(creosote bush), and unvegetated (interspace) areas to measure soil nutrient concentrations, microbial biomass, and potential soil enzyme activity. We monitored the dynamics of these belowground processes as soil conditions dried and then rewetted due to rainfall. Most measured variables, including inorganic nutrients, microbial biomass, and soil enzyme activities, were greater under shrubs during both wet and dry periods, with the highest magnitudes under mesquite followed by creosote bush and then interspace. One exception was nitrate, which was highly variable and did not show resource island patterns. Temporally, rainfall pulses were associated with substantial changes in soil nutrient concentrations, though resource island patterns remained consistent during all phases of the soil moisture pulse. Microbial biomass was more consistent than nutrients, decreasing only when soils were driest. Potential enzyme activities were even more consistent and did not decline in dry periods, potentially helping to stimulate observed pulses in CO₂efflux following rain events observed at a co‐located eddy flux tower. These results indicate a critical zone with organic matter cycling patterns consistently elevated in shrub resource islands (which varied by shrub species), high decomposition potential that limits soil organic matter accumulation across the landscape, and nitrate fluxes that are decoupled from the organic matter pathways.

 

The intensification of coastal storms, combined with declining sea ice cover, sea level rise, and changes to permafrost conditions, will likely increase the incidence and impact of storm surge flooding in Arctic coastal environments. In coastal communities accurate information on the exposure of infrastructure can make an important contribution to adaptation planning. In this study, we use high resolution elevation data from airborne LiDAR to generate storm flooding scenarios for three coastal communities (Utqiag_ vik, Wainwright, and Kaktovik) in northern Alaska. To estimate the potential for damage to infrastructure caused by flooding for each community, we generated data on replacement costs and used it to estimate the financial impact of 24 storm flooding scenarios of varying intensities. This analysis shows that all three communities are exposed to storm surges, but highlights the fact that infrastructure in Utqiag_ vik (the administrative center of the North Slope Borough) is significantly more exposed than buildings in Wainwright and Kaktovik. Our findings show that flooding scenarios can complement information gained from past events and help to inform local-decision making. 

High‐latitude climate change has impacted vegetation productivity, composition, and distribution across tundra ecosystems. Over the past few decades in northern Alaska, emergent macrophytes have increased in cover and density, coincident with increased air and water temperature, active layer depth, and nutrient availability. Unraveling the covarying climate and environmental controls influencing long‐term change trajectories is paramount for advancing our predictive understanding of the causes and consequences of warming in permafrost ecosystems. Within a climate‐controlled carbon flux monitoring system, we evaluate the impact of elevated nutrient availability associated with degraded permafrost (high‐treatment) and maximum field observations (low‐treatment), on aquatic macrophyte growth and methane (CH₄) emissions. Nine aquaticArctophila fulva‐dominated tundra monoliths were extracted from tundra ponds near Utqiaġvik, Alaska, and placed in growth chambers that controlled ambient conditions (i.e., light, temperature, and water table), while measuring plant growth (periodically) and CH₄fluxes (continuously) for 12 weeks. Results indicate that high nutrient treatments similar to that released from permafrost thaw can increase macrophyte biomass and total CH₄emission by 54 and 64%, respectively. However, low treatments did not respond to fertilization. We estimate that permafrost thaw in tundra wetlands near Utqiaġvik have the potential to enhance regional CH₄efflux by 30%. This study demonstrates the sensitivity of arctic tundra wetland biogeochemistry to nutrient release from permafrost thaw and suggests the decadal‐scale expansion ofA. fulva‐dominant aquatic plant communities, and increased CH₄emissions in the region were likely in response to thawing permafrost, potentially representing a novel case study of the permafrost carbon feedback to warming.

 

Plant‐mediatedCH₄flux is an important pathway for land–atmosphereCH₄emissions, but the magnitude, timing, and environmental controls, spanning scales of space and time, remain poorly understood in arctic tundra wetlands, particularly under the long‐term effects of climate change.CH₄fluxes were measuredin situduring peak growing season for the dominant aquatic emergent plants in the Alaskan arctic coastal plain,Carex aquatilisandArctophila fulva, to assess the magnitude and species‐specific controls onCH₄flux. Plant biomass was a strong predictor ofA. fulvaCH₄flux while water depth and thaw depth were copredictors forC. aquatilisCH₄flux. We used plant and environmental data from 1971 to 1972 from the historic International Biological Program (IBP) research site near Barrow, Alaska, which we resampled in 2010–2013, to quantify changes in plant biomass and thaw depth, and used these to estimate species‐specific decadal‐scale changes inCH₄fluxes. A ~60% increase inCH₄flux was estimated from the observed plant biomass and thaw depth increases in tundra ponds over the past 40 years. Despite covering only ~5% of the landscape, we estimate that aquaticC. aquatilisandA. fulvaaccount for two‐thirds of the total regionalCH₄flux of the Barrow Peninsula. The regionally observed increases in plant biomass and active layer thickening over the past 40 years not only have major implications for energy and water balance, but also have significantly altered land–atmosphereCH₄emissions for this region, potentially acting as a positive feedback to climate warming.