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1. Soil branched Glycerol dialkyl glycerol tetraether (brGDGT) distributions, soil temperatures, soil properties, and air temperatures of the Eastern Canadian Arctic and Iceland,2023-2024

   https://doi.org/10.18739/a27p8tf8w  

   Raberg, Jonathan; Crump, Sarah; De_Wet, Greg; Harning, David; Miller, Gifford; Geirsdóttir, Áslaug; Sepúlveda, Julio (January 2024, NSF Arctic Data Center)

   This dataset consists of lipid biomarker (branched glycerol dialkyl glycerol tetraether (brGDGT)) data, soil properties (pH, electrical conductivity, and soil water content), soil temperature data, and air temperature data for surface soils collected from the Eastern Canadian Arctic (ECA) and Iceland. These data were supplemented with brGDGT, soil property, soil temperature, and air temperature data from previously published studies from Iceland (De Jonge et al., 2019), China (Wang et al., 2020; Wang and Liu, 2021), Colombia (Pérez-Angel et al., 2020), and Scandinavia (Halffman et al., 2022). We collected soil samples at 0-10 centimeter (cm) depth from the Eastern Canadian Arctic (ECA; n = 44) and Iceland (n = 24) in the summers of 2015-2019. For 27 soil sites in the ECA and all soil sites in Iceland, we deployed in situ soil temperature loggers (Thermochron DS1925L or DS1922L iButtons, Maxim Integrated Products) at 10 cm depth for 1 to 2 years (362 – 727 days). All loggers had a 1- to 3-hourly sampling interval except for four deployed at sites CF3 and CF8 in the ECA, which had a 6-hour sampling interval. Raw soil temperature data is available at (Raberg, de Wet, et al., 2022; Raberg, Harning, Geirsdóttir, et al., 2021). We measured the pH of all ECA and Iceland soils using an Oaktan pH 150 meter with a WD‐35614‐30 probe. Soil pH was measured using milli‐Q water in a 1:2.5 (w:w) soil:water ratio. New containers were used for each soil and the pH meter was calibrated using pH 4.00, 7.00, and 10.00 buffer solutions every 5-10 samples. Electrical conductivity was measured with a SevenEasy conductivity meter (Mettler Toledo) at a 1:5 (w:w) soil:water ratio, with a calibration solution checked every 15-20 samples. SWC, calculated as the percent of the sample mass that was lost after freeze drying (SWC = (mass wet soil - mass dry soil) / mass dry soil × 100), was measured for all soils from Iceland and 15 soils from the ECA. For brGDGT analysis, we extracted 1-10 g of freeze-dried soil using a modified Bligh and Dyer method (Bligh and Dyer, 1959; Raberg, Flores, et al., 2022; Wörmer et al., 2013). We analyzed brGDGTs using a Thermo Scientific UltiMate 3,000 high-performance liquid chromatography instrument coupled to a Q Exactive Focus Orbitrap-Quadrupole high-resolution mass spectrometer (HPLC-MS) in full scan mode. We used a slightly modified version (Raberg, Harning, Crump, et al., 2021) of the chromatographic methods established by Hopmans et al. (2016), and identified brGDGTs based on their characteristic masses and elution patterns. We added a known quantity (1μg) of C46 GDGT internal standard (Huguet et al., 2006) to the extracts quantify brGDGT yields. BrGDGTs are reported as fractional abundances within the pool of the 15 most commonly measured brGDGTs. We also report fractional abundances of brGDGTs within an extended pool, which includes both the 15 commonly measured brGDGTs and less commonly reported isomers (IIIa’’ and 7-methyl isomers). Finally, we report the presence or absences of overly branched GDGT with a mass-to-charge ratio of 1064. To supplement the ECA and Iceland datasets, we also compiled results from published studies containing soil brGDGTs with associated in situ soil temperatures. These include 37 soils from altitudinal transects in Scandinavia (Halffman et al., 2022), 30 soils from geothermal transects in Iceland (De Jonge et al., 2019; Sigurdsson et al., 2016), 12 soils from an altitudinal transect in China (Mt. Laji; Wang and Liu, 2021), 30 soils from an altitudinal transect in the tropical Andes of Colombia (Pérez-Angel et al., 2020), and 149 soils from a regional study in China (Wang et al., 2020). Where data were available (n = 97), monthly mean soil temperatures were calculated from hourly data that was either previously published (Halamka et al., 2022; Halffman et al., 2022; Sigurdsson et al., 2016) or provided through personal communication with the authors (L. Pérez-Angel; C. de Jonge). Monthly, seasonal, or annual soil temperatures for the remaining samples were compiled as available from published studies and through personal communication with the authors (H. Wang and W. Liu). We calculated 10 soil temperature parameters (e.g., mean summer soil temperature), which are defined in the “readme” tab of the dataset. Finally, we generated monthly air temperatures for all ECA and Icelandic sites in this study following the methods of Raberg et al. (2021). Briefly, for soils from six lakes in the ECA (Birch (BIR), Brother-of-Fog (BRO), Qaupat (QPT), Clyde Forelands 8 (CF8), Arnuiq (ARQ), and South America Lake (SAL)), we used a transfer function to convert 2 m air temperatures recorded by iButton temperature loggers to 30-year climate normals (1971-2000) using data from nearby meteorological stations (Department of Environment, Government of Canada). For all other samples, we used the WorldClim database (Fick and Hijmans, 2017) to generate 30-year (1970-2000) air temperature climate normals. For each soil temperature parameter above, we calculated an analogous air temperature parameter (e.g., mean annual air temperature (MAAT)), which are also defined in the “readme” tab of the dataset. Bligh, E. G., and Dyer, W. J. (1959). A rapid method of total lipid extraction and purification. Canadian Journal of Biochemistry and Physiology, 37(8), 911–917. https://doi.org/10.1139/o59-099 Halamka, T. A., Raberg, J. H., McFarlin, J. M., Younkin, A. D., Mulligan, C., Liu, X.-L., et al. (2022). Production of diverse brGDGTs by Acidobacterium Solibacter usitatus in response to temperature, pH, and O2 provides a culturing perspective on brGDGT proxies and biosynthesis. Geobiology, 00, 1–17. https://doi.org/10.1111/GBI.12525 Halffman, R., Lembrechts, J., Radujković, D., De Gruyter, J., Nijs, I., and De Jonge, C. (2022). Soil chemistry, temperature and bacterial community composition drive brGDGT distributions along a subarctic elevation gradient. Organic Geochemistry, 163, 104346. https://doi.org/10.1016/j.orggeochem.2021.104346 Hopmans, E. C., Schouten, S., and Sinninghe, J. S. (2016). The effect of improved chromatography on GDGT-based palaeoproxies. Organic Geochemistry, 93, 1–6. https://doi.org/10.1016/j.orggeochem.2015.12.006 Huguet, C., Hopmans, E. C., Febo-Ayala, W., Thompson, D. H., Sinninghe Damsté, J. S., and Schouten, S. (2006). An improved method to determine the absolute abundance of glycerol dibiphytanyl glycerol tetraether lipids. Organic Geochemistry, 37(9), 1036–1041. https://doi.org/10.1016/j.orggeochem.2006.05.008 De Jonge, C., Radujković, D., Sigurdsson, B. D., Weedon, J. T., Janssens, I., and Peterse, F. (2019). Lipid biomarker temperature proxy responds to abrupt shift in the bacterial community composition in geothermally heated soils. Organic Geochemistry, 137. https://doi.org/10.1016/j.orggeochem.2019.07.006 Pérez-Angel, L. C., Sepúlveda, J., Molnar, P., Montes, C., Rajagopalan, B., Snell, K., et al. (2020). Soil and Air Temperature Calibrations Using Branched GDGTs for the Tropical Andes of Colombia: Toward a Pan-Tropical Calibration. Geochemistry, Geophysics, Geosystems, 21(8), 1–18. https://doi.org/10.1029/2020GC008941 Raberg, J. H., Harning, D. J., Crump, S. E., De Wet, G., Blumm, A., Kopf, S., et al. (2021). Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments. Biogeosciences, 18, 3579–3603. https://doi.org/10.5194/bg-18-3579-2021 Raberg, J. H., Harning, D. J., Geirsdóttir, Á., Sepúlveda, J., and Miller, G. H. (2021). Soil and lake water temperatures of Iceland (2019-2021). Arctic Data Center. Raberg, J. H., de Wet, G., Crump, S. E., Raynolds, M. K., Sepúlveda, J., and Miller, G. H. (2022). Air, soil, and lake water temperatures of the Eastern Canadian Arctic (2017-2021). Arctic Data Center. Raberg, J. H., Flores, E., Crump, S. E., Wet, G. de, Dildar, N., Miller, G. H., et al. (2022). Intact Polar brGDGTs in Arctic Lake Catchments: Implications for Lipid Sources and Paleoclimate Applications. Journal of Geophysical Research: Biogeosciences, 127(10), e2022JG006969. https://doi.org/10.1029/2022JG006969 Sigurdsson, B. D., Leblans, N. I. W., Dauwe, S., Gudmundsdóttir, E., Gundersen, P., Gunnarsdóttir, G. E., et al. (2016). Geothermal ecosystems as natural climate change experiments: The ForHot research site in Iceland as a case study. Icelandic Agricultural Sciences, 29(1), 53–71. https://doi.org/10.16886/IAS.2016.05 Wang, H., and Liu, W. (2021). Soil temperature and brGDGTs along an elevation gradient on the northeastern Tibetan Plateau: A test of soil brGDGTs as a proxy for paleoelevation. Chemical Geology, 566, 120079. https://doi.org/10.1016/j.chemgeo.2021.120079 Wang, H., An, Z., Lu, H., Zhao, Z., and Liu, W. (2020). Calibrating bacterial tetraether distributions towards in situ soil temperature and application to a loess-paleosol sequence. Quaternary Science Reviews, 231, 106172. https://doi.org/10.1016/j.quascirev.2020.106172 Wörmer, L., Lipp, J. S., Schröder, J. M., and Hinrichs, K. U. (2013). Application of two new LC-ESI-MS methods for improved detection of intact polar lipids (IPLs) in environmental samples. Organic Geochemistry, 59, 10–21. https://doi.org/10.1016/j.orggeochem.2013.03.004 

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2. Multibeam bathymetry data (from 2021-2022) and bathymetry difference data (from 2021 and 2022 compared to the 1950s) from Harrison Bay, Alaska

   https://doi.org/10.18739/A2M90251D  

   Eidam, Emily; Duncan, Dan; Brilli, Nick; Nienhuis, Jaap; Heath, Adrian; Langhoff, Cory; Stark, Nina (January 2025, NSF Arctic Data Center)

   This dataset contains ascii text files of latitude, longitude, and water depth data which were collected using a pole-mounted multibeam echosounder system from the R/V Ukpik in July-August, 2021. Dr. Emily Eidam was the team lead and Dan Duncan was the multibeam operator. The data were collected along discrete tracklines across Harrison Bay. The general study was seaward of the Colville Delta between Cape Halkett to the west and Oliktok Point to the east, with a maximum seaward extent to water depths of approximately 30 meters (m) (about half to three-quarters of the way across the shelf from the shoreline). The dataset also contains a netcdf file of bathymetric change which was computed as the difference between the combined 2021 and 2022 data contained in this archive and a 1950s dataset which was recently corrected and is publicly available through Zimmerman et al., 2022 (doi.org/10.1016/j.csr.2022.104745). The multibeam data provide information about a rich diversity of seabed features including large and small ice-keel scours, sand waves, strudel scour pits, and unusual scoured substrates. A detailed description of these datasets is provided in an in-preparation manuscript (Eidam et al., Seafloor sediments and morphologic features of Harrison Bay in the Alaskan Beaufort Sea). The bathymetric change data illustrates erosion of the inner and inner-middle shelf over the past ~70 years, including erosion of up to ~3 m near Cape Halkett and on the Colville Delta front. These changes are addressed in detail in Heath, 2024 (Oregon State University Master of Science Thesis, "Sedimentation and Erosion on an Arctic Continental Shelf: Harrison Bay and Colville River Delta, Alaska"). 

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3. The Circumpolar Arctic Vegetation Science Initiative (CAVSI): A framework to help guide the next decade of Arctic vegetation research

   https://doi.org/10.18739/A2T43J49W  

   CAVSI_Organizing_Team (June 2025, National Science Foundation Arctic Data Center)

   Walker, D A; Peirce, J L (Ed.)

   Arctic vegetation is the visible surface expression of Arctic terrestrial systems. It is the key to monitoring and modeling changes to most components of the system, such as shrub distribution; greening patterns, plant and animal habitats and biodiversity, hydrological networks, and snow distribution, as well as the less visible aspects, such as permafrost, soil carbon stocks, and greenhouse-gas emissions. Currently, there are no standardized approaches to sample, describe, map, and analyze circumpolar patterns of Arctic vegetation across a hierarchy of spatial scales and international boundaries. There is a need for a well-distributed Arctic vegetation observatory network and a set of internationally accepted protocols for sampling, data information systems, classifying, and mapping vegetation to aid in addressing priority research topics for the Fourth International Conference on Arctic Research Planning (ICARP IV) and the The Fifth International Polar Year (IPY5). The Circumpolar Arctic Vegetation Science Initiative (CAVSI) is a response to these needs and those expressed by ICARP IV Research Priority Team 1 (RPT 1) (Zhang and Rasouli 2025) and Research Priority Team 2 (RPT2) (Bret-Harte 2025), which focus on the role of the Arctic in the global system and observing, reconstructing, and predicting future Arctic climate dynamics and ecosystem responses. CAVSI is also a response to the recommendation by the Arctic Council for long-term biodiversity monitoring to address key gaps in Arctic-system knowledge (Conservation of Arctic Flora and Fauna (CAFF) 2013, Christiansen et al. 2020, Barry 2023). It aligns with several national and international Arctic research plans and policies that involve observation, monitoring, modeling, and prediction, including those of the United States (Office of Science & Technology Policy (OSTP) 2022, United States Army Reserve Command (USARC) 2023) and the international Sustaining Arctic Research Network (Sustaining Arctic Observing Networks (SAON), Starkweather et al. 2021). This white paper provides a framework for vegetation description and monitoring. It includes: (1) a network of sites across the full range of Arctic climates, phytogeographic regions, local habitats, and disturbance regimes; (2) standardized methods to describe and monitor local floras, vegetation composition, and key environmental factors; (3) a pan-Arctic vegetation plot archive to store legacy and recent plot data; (4) a consistent hierarchical classification and checklist of Arctic vegetation; (5) an archive of Arctic vegetation and landcover maps; (6) applications and ideas for CAVSI IPY5 initiatives; (7) an 11-year timeline for CAVSI activities leading up to and including synthesis from IPY5 activities; and (8) recommendations for priority activities and research related to ICARP IV RPTs 1 and 2. 

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4. Climate data from the former Arctic LTER Toolik Inlet Wet Sedge Flux site, Toolik Field Station, Alaska 2017 to 2025.

   https://doi.org/10.6073/pasta/962202d7b980c50f36880c473805c7bf  

   Kling, George; Laundre, Jim; Eugster, Werner (January 2026, Environmental Data Initiative)

   One-minute averages of air temperature and relative humidity, soil temperature and moisture, and solar radiation from 2017 to 2025 for the former Arctic LTER Toolik wet sedge eddy covariance flux site. This site was originally set up for seasonal eddy covariance flux measurements during the summers of 2010–2015 and partially during winters starting in 2014, until 15 June 2016. Flux data are reported in Eugster et al.(2020)(doi:10.5194/amt-2019-402). IMPORTANT NOTE: The data has only been checked for obvious outliers. Use with caution since most of the data has not been carefully checked. It was decided to release this version instead of waiting until there were resources for a complete check. 

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5. Parallel Reachability and Shortest Paths on Non-Sparse Digraphs: Near-Linear Work and Sub-Square-Root Depth

   https://doi.org/10.4230/lipics.icalp.2026.15  

   Ashvinkumar, Vikrant; Bernstein, Aaron; Gutenberg, Maximilian Probst; Saranurak, Thatchaphol (January 2026, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Bhattacharya, Sayan; Nanongkai, Danupon; Benedikt, Michael; Puppis, Gabriele (Ed.)

   Abstract: We present parallel algorithms for computing single-source reachability and shortest paths on directed n-vertex m-edge graphs using near-linear Õ(m) work and o(√n) depth whenever m ≥ n^{1+o(1)}. At the extreme of m = Ω(n²), our reachability and shortest path algorithms have depth only n^0.136 and n^{0.25+o(1)}, respectively. The state-of-the-art parallel algorithms with near-linear work for both problems [Jambulapati et al., 2019; Cao et al., 2020; Rozhoň et al., 2023; Cao and Fineman, 2023; Brand et al., 2025] require Ω(√n) depth in all density regimes. 

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