Identifying the influence of terrestrial–aquatic connectivity on palaeoecological inferences of past climate in Arctic lakes
Bibliographic record
Abstract
Increased hydrological connectivity due to permafrost degradation is likely to have substantial implications for shallow aquatic systems common to sub‐arctic landscapes due to changes to overland and subsurface flow of water and transport of sediments and dissolved nutrients. Here, we explore the influence of increased connectivity on aquatic productivity based on multi‐parameter palaeolimnological analysis of two lakes located near Inuvik (Northwest Territories, Canada). We contrast a lake with little evidence of permafrost degradation in the surrounding area (Lake PG03) to one that has multiple connections to the terrestrial landscape through a network of thaw polygons in the lake catchment (Lake PG09). Comparisons of biological indicators (chironomids) and organic carbon and nitrogen elemental and isotope composition reveal recent divergent lake histories. The chironomid assemblage of Lake PG03 followed an expected temperature gradient, with a warming signal evident since ˜1970 CE, whereas the chironomid assemblage of Lake PG09 was found to primarily respond to nutrient availability and changes in habitat, likely as a result of increasing hydrological connectivity to the landscape. Rapid assemblage and habitat change along with a prominent increase in chironomid abundance were observed at Lake PG09 after ˜1960 CE, following a shift to greater inputs from the terrestrial environment as indicated by high C:N ratios (>15) and low δ13Corg (−30‰). Increased aquatic productivity following high allochthonous additions (˜1960–2014 CE) is supported by decreased C:N and rapidly increasing organic matter (Corg, N). These results demonstrate that increased connectivity along the terrestrial–aquatic interface for lakes is likely to foster elevated productivity in the future. Likewise, increased production poses a challenge to chironomid‐inferred July air temperature reconstructions in lakes that are less resilient to secondary gradients, where analogue mismatches can occur due to shifts in dominance of indicators that are orthogonal to the temperature gradient.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".