Editorial: The cold regions in transition: Impacts on soil and groundwater biogeochemistry
Bibliographic record
Abstract
The cold regions in transition: Impacts on soil and groundwater biogeochemistryGlobal climate warming disproportionately affects the ecosystems of the high-latitude cold regions, which can facilitate agricultural expansion, urban growth, and natural resource development, adding growing anthropogenic pressures to cold regions' landscapes, soil health, and biodiversity (Hansen et al., 2010; IPCC-Intergovernmental Panel on Climate Change, 2021;Pi et al., 2021).The terrestrial ecosystems in northern cold regions, including Arctic and subarctic regions, comprise components that are especially vulnerable to warming-snow cover and permafrost-as well as soil microbial communities adapted to cold temperatures.These changes are accompanied by changes in vegetation cover, the thermal regime of soils, fluxes, and timing of nutrient export to aquatic ecosystems, emissions of greenhouse gases (GHGs), and the mobilization of organic carbon and geogenic contaminants, among others (Edwards et al., 2007;Brooks et al., 2011;Hayashi, 2013;Kurylyk et al., 2014).Consequently, elucidating how these changes affect soil biogeochemical processes and fluxes is essential for predicting carbon and nutrient availability in subsurface and impacts on groundwater and surface water quality (Matzner et al., 2008;Cochand et al., 2019).For instance, the often-reported spring pulses of dissolved carbon and nutrients in cold regions' terrestrial ecosystems reflect the cumulated effects of hydro(bio)geochemical processes on the belowground pools of bioactive elements, the dynamic response of the soil microbial community to changes in hydrology and geochemistry that accompany spring snowmelt, and associated water quality and ecological impacts (Henry, 2007, Henry, 2008;Hayashi et al., 2013;Kurylyk et al., 2014;Lundberg et al., 2016).Thus, climate warming generates a set of interrelated changes in (hydro)geophysical properties, hydro(geo)logical flows, biogeochemical processes, and ecosystem functions in the world's cold regions.Research on how cold regions' microorganisms respond to shifts in environmental conditions is of particular importance for anticipating how a warming climate will affect the biogeochemical cycling of carbon, nutrients, metals, and pollutants in the Earth's cold regions.Quantifying the variability in cold region processes remains challenging but is, however, critical to unravel the linkages between climate warming and biogeochemical responses in cold climate ecosystems.The complex interconnections of hydro(bio)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.038 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".