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This dataset consists of pulse-amplitude modulation (PAM) fluorometry data collected using six Micro-PAM (Walz GmbH, Effeltrich, Germany) measurement heads installed on two black spruce trees at the Caribou-Poker Creeks Research Watershed National Ecological Observatory Network (NEON) site (site abbreviation: BONA) near Fairbanks, Alaska. These measurements provide information on the physiological status of photosystem II and photosynthesis more broadly for the needles and trees observed. Three PAM measurement heads were installed on each tree at low, intermediate, and high heights qualitatively within the canopy. Five measurement heads (second intermediate position measurement excluded) were installed in March 2022, with the sixth measurement head being installed in July 2022. Data was collected semi-continuously, including the harsh winter season, until July 2024. PAM fluorescence measurements were collected in a ramped scheme centered around noon to maximize measurement frequency while still allowing for adequate dark acclimation for the nighttime measurement. Saturation pulses were performed by each measuring head every fifteen minutes from 9:00AM – 5:00PM, every thirty minutes from 7:00AM-9:00AM and 5:00PM-7:00PM, and every hour from 2:00AM-7:00AM and 7:00PM-9:00PM. 

This dataset consists of tower-based remote sensing measurements collected using a pair of Fluospec2 (FS2; Yang et al., 2018) instruments, each consisting of two QEPro spectrometers (Ocean Optics, Orlando, USA), installed at the Caribou-Poker Creeks Research Watershed National Ecological Observatory Network (NEON) site (site abbreviation: BONA) near Fairbanks, Alaska. Remote sensing observations include solar-induced fluorescence, derived via a spectral fitting method, near-infrared reflectance of vegetation, and several vegetation indices that can collectively be used to evaluate canopy productivity, photosynthetic phenology, and physiology. Data was collected from two subsites, one FS2 (frequency-synthesizer) instrument installed at each site, located roughly one kilometer apart along a topographic gradient. The evergreen site consists of a black spruce canopy and a lichen and moss understory, with a few larch trees interspersed. The FS2 instrument here was installed on an observation tower (latitude/longitude: 65.15401/-147.50258) installed by NEON that also hosts NEON's meteorological and flux instruments, with the FS2 instrument observing a cluster of black spruce (Picea mariana) trees. At the deciduous site (latitude and longitude: 65.15686833, -147.50367667), a mast was installed within a deciduous canopy consisting of alaskan paper birch (Betula neoalaskana), black spruce, and quaking aspen (Populus tremuloides) trees located roughly one kilometer (km) uphill from the evergreen site. The FS2 instrument installed here observed a paper birch tree located near-nadir from the instrument. Literature Citation: Yang, X., Shi, H., Stovall, A., Guan, K., Miao, G., Zhang, Y., Zhang, Y., Xiao, X., Ryu, Y., & Lee, J. E. (2018). FluoSpec 2—an automated field spectroscopy system to monitor canopy solar-induced fluorescence. Sensors (Switzerland), 18(7). https://doi.org/10.3390/s18072063 

DVM-DOS-TEM model version used for simulations at Caribou-Poker-Creek Watershed. 

This project aims to gain an improved understanding of the boreal forest carbon balance, including the seasonal contributions of carbon flux (μmol m^-2 s^-1 [micromoles per square meter per second]) and the influence of key environmental conditions (e.g., soil moisture, soil temperature, and vegetation community characteristics) that regulate carbon loss. The dataset includes carbon flux data from chamber-based measurements and the Bonanza Creek National Ecological Observatory Network (BONA NEON) eddy covariance tower, which we gap-filled using a random forest machine learning model. It also includes associated measurements of vegetation (aboveground woody biomass, understory biomass, tree age), radiation (photosynthetically active radiation, leaf area index, air temperature), and soil (moisture, temperature, thaw depth, organic layer depth, bulk density %C [percent carbon], %N [percent nitrogen], C:N [carbon-to-nitrogen ratio], 13C [carbon-13], 14C [carbon-14]), including a soil incubation experiment which measured microbial respiration (mg C / kg soil d [milligrams of carbon per kilogram of soil per day]) under different soil conditions. Chamber-based carbon flux data and their associated measurements (soil moisture, soil temperature, PAR [Photosynthetically Active Radiation], thaw depth) are available May - September 2021 and 2022. In situ sensor data (soil temperature, soil moisture, air temperature, PAR) is available June 2021 - August 2022. Vegetation data and soil samples were collected in July 2022. The gap-filled tower flux data is available from 2019 - 2024. A land cover analysis of the tower footprint is available 2021 - 2022. The study area spans the footprint of the eddy covariance tower, and a 300 m (meters) slopeside lowland-to-upland forest within the Caribou-Poker Creek Research Watershed northeast of Fairbanks, Alaska, described below. 

Methane measurements, particularly of natural sources, need to be expanded considerably 

Northern forest soils are vital for climate change mitigation since upland sandy soils favor the net consumption/oxidation of atmospheric methane (CH4). We are studying biogeochemical CH4 cycle processes in a Northern Forest (Howland Research Forest, Maine), where upland soils are interspersed with wetland (Sphagnum bog), and upland-wetland transition soils along with hummock-hollow microtopography. This complex mosaic of microsites with sources and sinks of CH4 is subjected to change under future wet climates projected for this region, with a potential for these forests to shift from a net CH4 sink to a net CH4 source. Net CH4 emissions in a wet climate can increase either by inhibiting methanotrophs or favoring methanogens, or both. Thus, quantifying underlying processes of gross CH4 production and consumption can reduce the uncertainty of CH4 sink/source estimation in this critical ecosystem. We have collected baseline soil data across the forest's landscape including Total Carbon and Total Nitrogen with the Elemental Analyzer, Gravimetric Soil Moisture, and pH. Furthermore, stable isotope dilution method will serve as a proxy for methanogenic and methanotrophic activities to quantify gross rates of CH4 production and consumption from a flooding (wet-up) experiment in Howland Forest. We will differentiate between CH4 consumption and production by measuring both the change in the amount of CH4 and the ratio between labeled and unlabeled CH4 in a closed system. We will analyze the stable C isotope in 13CH4 to determine gross rates of CH4 production and oxidation in situ and within laboratory incubations. The in situ stable isotope dilution technique will be compared with the gas push-pull method, to test the suitability of a simple, low cost method to quantify gross CH4 oxidation rates. Novel data obtained in this study will constrain CH4 cycle processes in a biogeochemical model to quantify CH4 source-sink potential in Northern Forests under current and future climatic conditions. 

Abstract Arctic permafrost is undergoing rapid changes due to climate warming in high latitudes. Retrogressive thaw slumps (RTS) are one of the most abrupt and impactful thermal-denudation events that change Arctic landscapes and accelerate carbon feedbacks. Their spatial distribution remains poorly characterised due to time-intensive conventional mapping methods. While numerous RTS studies have published standalone digitisation datasets, the lack of a centralised, unified database has limited their utilisation, affecting the scale of RTS studies and the generalisation ability of deep learning models. To address this, we established the Arctic Retrogressive Thaw Slumps (ARTS) dataset containing 23,529 RTS-present and 20,434 RTS-absent digitisations from 20 standalone datasets. We also proposed a Data Curation Framework as a working standard for RTS digitisations. This dataset is designed to be comprehensive, accessible, contributable, and adaptable for various RTS-related studies. This dataset and its accompanying curation framework establish a foundation for enhanced collaboration in RTS research, facilitating standardised data sharing and comprehensive analyses across the Arctic permafrost research community. 

Abstract. Rapid warming across the Arctic is the primary driver of widespread permafrost thaw, with far-reaching consequences for local ecosystem resilience, the regional carbon budget, and the global climate system. Because permafrost characteristics and vulnerability are tightly linked to land cover, particularly vegetation type and surface properties, understanding these dynamics requires accurate and detailed land cover information. Spatial variation in vegetation cover influences energy balance, snow insulation, and soil moisture, factors that directly affect permafrost stability. Consequently, high-resolution land cover products are essential for assessing the ecological impacts of permafrost thaw and for improving the representation of permafrost-related processes in predictive models. However, many global land cover datasets fail to capture the spatial heterogeneity and fine-scale ecological features that influence permafrost dynamics, while more detailed regional products often lack coverage across broader, continental extents. This gap presents a challenge for large-scale assessments of permafrost vulnerability under accelerating climate change. To create a spatially cohesive land cover map that accurately represents the distribution of ecosystems across the Arctic-Boreal region, we integrated existing global and regional land cover datasets using a workflow including machine learning techniques. This approach seamlessly combines diverse data sources, enhancing representation and accuracy. The resulting map represents high-latitude land cover types at a 1-km spatial resolution, better capturing the spatial heterogeneity of the landscape compared to coarser resolution land surface products, with a total of 35 land cover classes, including 20 forest types (e.g., Larch, Birch, Mixed forests), 6 shrubland classes, and wetlands subdivided into bog, fen, and marsh. To achieve this, we used a global land cover map, the European Space Agency Climate Change Initiative Land Cover data (ESA CCI-LC), as the base map and integrated regional maps across the circumpolar region with finer-resolution land cover information to capture the diversity of land cover types. This approach ensured consistent classification across geopolitical boundaries while incorporating representative vegetation communities at a region-specific level. We show that regional land cover products can be successfully fused to yield a higher-resolution thematic content at the circumpolar scale in comparison to existing global products. The hybrid land cover product can be freely access via https://doi.org/10.5281/zenodo.15231293 (Briones et al 2025). 

Abstract Drylands cover 41% of Earth’s land surface, support 36% of the global population and contribute 60% of global food production. Despite these ecosystems’ importance and high vulnerability to droughts and heatwaves, drylands remain some of the most understudied systems on Earth. Monitoring drylands is challenging due to their complex ecosystem structure of visible soil mixed with diverse plant species that respond rapidly to weather and climate. In 2023 and 2024, a NASA scoping study was conducted for a proposed dryland terrestrial ecology field campaign called Adaptation and Response in Drylands (ARID). Thereafter, the NASA ARID scoping team submitted their campaign proposal to NASA Headquarters, providing a study design for how field, aircraft and satellite measurements, as well as modeling, could address the most critical fundamental and applied science questions in drylands. The extensive strategic vision was created by and for the drylands research community, including remote sensors, modelers, experimentalists and ecologists from across the world, and the overall approach can be further utilized and altered for different uses and data information needs. Here, we summarize the final ARID research agenda, including its main objectives, field campaign strategy, data end-user support strategy, and U.S. and global community engagement.