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The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This data set includes weekly thaw depth measurements collected from winter warming, summer warming, and control treatment plots at CiPEHR. Additional measurements from on-plot gas flux wells, water table monitoring wells, and off-plot locations are also reported. Note that the experimental warming portion of this experiment concluded in 2022. These data are a continuation of measurements taken at previously warmed plots but plots were not actively manipulated after 2022. 

In this larger study, we are asking the question: Is old carbon that comprises the bulk of the soil organic matter pool released in response to thawing of permafrost? We are answering this question by using a combination of field and laboratory experiments to measure radiocarbon isotope ratios in soil organic matter, soil respiration, and dissolved organic carbon, in tundra ecosystems. The objective of these proposed measurements is to develop a mechanistic understanding of the SOM sources contributing to C losses following permafrost thawing. We are making these measurements at an established tundra field site near Healy, Alaska in the foothills of the Alaska Range. Field measurements center on a natural experiment where permafrost has been observed to warm and thaw over the past several decades. This area represents a gradient of sites each with a different degree of change due to permafrost thawing. As such, this area is unique for addressing questions at the time and spatial scales relevant for change in arctic ecosystems. 

Abstract. Our understanding of how rapid Arctic warming and permafrost thaw affect global climate dynamics is restricted by limited spatio-temporal data coverage due to logistical challenges and the complex landscape of Arctic regions. It is therefore crucial to make best use of the available observations, including the integrated data analysis across disciplines and observational platforms. To alleviate the data compilation process for syntheses, cross-scale analyses, earth system models, and remote sensing applications, we introduce ARGO, a new meta-dataset comprised of greenhouse gas observations from various observational platforms across the Arctic and boreal biomes within the polar region of the northern hemisphere. ARGO provides a centralised repository for metadata on carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) measurements linked with an interactive online tool (https://www.bgc-jena.mpg.de/argo/). This tool offers prompt metadata visualisation for the research community. Here, we present the structure and features of ARGO, underscoring its role as a valuable resource for advancing Arctic climate research and guiding synthesis efforts in the face of rapid environmental change in northern regions. The ARGO meta-dataset is openly available for download at Zenodo (https://doi.org/10.5281/zenodo.13870390) (Vogt et al., 2024). 

The permafrost region has accumulated organic carbon in cold and waterlogged soils over thousands of years and now contains three times as much carbon as the atmosphere. Global warming is degrading permafrost with the potential to accelerate climate change as increased microbial decomposition releases soil carbon as greenhouse gases. A 19-year time series of soil and ecosystem respiration radiocarbon from Alaska provides long-term insight into changing permafrost soil carbon dynamics in a warmer world. Nine per cent of ecosystem respiration and 23% of soil respiration observations had radiocarbon values more than 50‰ lower than the atmospheric value. Furthermore, the overall trend of ecosystem and soil respiration radiocarbon values through time decreased more than atmospheric radiocarbon values did, indicating that old carbon degradation was enhanced. Boosted regression tree analyses showed that temperature and moisture environmental variables had the largest relative influence on lower radiocarbon values. This suggested that old carbon degradation was controlled by warming/permafrost thaw and soil drying together, as waterlogged soil conditions could protect soil carbon from microbial decomposition even when thawed. Overall, changing conditions increasingly favoured the release of old carbon, which is a definitive fingerprint of an accelerating feedback to climate change as a consequence of warming and permafrost destabilization. This article is part of the Theo Murphy meeting issue ‘Radiocarbon in the Anthropocene’. 

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. 

Drone-based multispectral sensing is a valuable tool for dryland spatial ecology, yet there has been limited investigation of the reproducibility of measurements from drone-mounted multispectral camera array systems or the intercomparison between drone-derived measurements, field spectroscopy, and satellite data. Using radiometrically calibrated data from two multispectral drone sensors (MicaSense RedEdge (MRE) and Parrot Sequoia (PS)) co-located with a transect of hyperspectral measurements (tramway) in the Chihuahuan desert (New Mexico, USA), we found a high degree of correspondence within individual drone data sets, but that reflectance measurements and vegetation indices varied between field, drone, and satellite sensors. In comparison to field spectra, MRE had a negative bias, while PS had a positive bias. In comparison to Sentinel-2, PS showed the best agreement, while MRE had a negative bias for all bands. A variogram analysis of NDVI showed that ecological pattern information was lost at grains coarser than 1.8 m, indicating that drone-based multispectral sensors provide information at an appropriate spatial grain to capture the heterogeneity and spectral variability of this dryland ecosystem in a dry season state. Investigators using similar workflows should understand the need to account for biases between sensors. Modelling spatial and spectral upscaling between drone and satellite data remains an important research priority. 

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. 

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under- sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.