MétaCan
Menu
← Back to cohort
Record W4212945586 · doi:10.5194/bg-2021-317-ac1

Reply on RC1

2022· peer-review· en· W4212945586 on OpenAlexfundaboutno aff
Niek Jesse Speetjens

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersEuropean CommissionAurora Research Institute
KeywordsDissolved organic carbonEnvironmental sciencePermafrostHumusOrganic matterSoil waterHydrology (agriculture)Drainage basinNutrientTotal organic carbonArcticSoil organic matterBiogeochemical cycleEnvironmental chemistryOceanographySoil scienceEcologyGeologyChemistry

Abstract

fetched live from OpenAlex

Ongoing climate warming in the western Canadian Arctic is leading to thawing of permafrost soils and subsequent mobilization of its organic matter pool. Part of this mobilized terrestrial organic matter enters the aquatic system as dissolved organic matter (DOM) and is laterally transported from land to sea. Mobilized organic matter is an important source of nutrients for ecosystems as it is available for microbial breakdown, and thus a source of greenhouse gases. We are beginning to understand spatial controls on the release of DOM as well as the quantities and fate of this material in large arctic rivers. Yet, these processes remain systematically understudied in small, high-arctic watersheds, despite the fact that these watersheds experience the strongest warming rates in comparison. Here, we sampled soil (active layer and permafrost) and water (porewater and stream water) from a small catchment along the Yukon coast, Canada, during the summer of 2018. We assessed the organic carbon (OC) quantity (using dissolved (DOC) and particulate OC (POC) concentrations and soil OC content), quality (δ13C-DOC, optical properties, source-apportionment), and bioavailability (incubations, optical indices such as slope ratio (Sr) and humification index (HIX)) along with stream water properties (T, pH, EC, water isotopes). We classify and compare different landscape units and their soil horizons that differ in microtopography and hydrological connectivity, giving rise to differences in drainage capacity. Our results show that porewater DOC concentrations and yield reflect drainage patterns and waterlogged conditions in the watershed. DOC yield (in mg DOC g soil OC−1) generally increases with depth but shows a large variability near the transition zone (around the permafrost table). Active layer porewater DOC generally is more labile than permafrost DOC, due to various reasons (heterogeneity, presence of a paleo-active layer, and sampling strategies). Despite these differences, the very long transport times of porewater DOC indicate that substantial processing occurs in soils prior to release into streams. Within the stream, DOC strongly dominates over POC, illustrated by DOC/POC ratios around 50, yet storm events decrease that ratio to around 5. Source-apportionment of stream DOC suggests a contribution of around 50 % from permafrost/deep-active layer OC, which contrasts to patterns observed in large arctic rivers (12 ± 8 % Wild et al., 2019). Our 10-day monitoring period demonstrated temporal DOC patterns on multiple scales (i.e. diurnal patterns, storm-events, and longer-term trend) underlining the need for high-resolution long-term monitoring. First estimates of Black Creek annual DOC (8.2 ± 6.4 t DOC yr−1) and POC (0.21 ± 0.20 t yr−1) export allowed us to make a rough upscaling towards the entire Yukon Coastal Plain (447 ± 313 t DOC yr−1 and 8.95 ± 9.7 t POC yr−1). With raising arctic temperatures, increases in runoff, soil OM leaching, permafrost thawing and primary production are likely to increase the net lateral OC flux. Consequently, altered lateral fluxes may have strong impacts on the arctic aquatic ecosystems and arctic carbon cycling.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.501

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0050.005
Open science0.0040.003
Research integrity0.0240.025
Insufficient payload (model declined to judge)0.1500.118

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.

Opus teacher head0.091
GPT teacher head0.297
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

Same topicClimate change and permafrost→French-language works237,207→