Quantifying the Vulnerability of Arctic Water Supply Lakes to Environmental Change Through Paleolimnological Assessment
Bibliographic record
Abstract
Anthropogenic stressors to freshwater environments have perpetuated water quality and quantity challenges for northern communities across Arctic Canada, making drinking water resources a primary concern for Arctic populations. To understand the ecological trajectory of freshwater supply sources, we conducted a paleolimnological assessment on two supplemental sources of freshwater in Igloolik, Nunavut, Canada. A stratigraphic examination of bioindicators (Insecta: Diptera: Chironomidae) allowed for paleotemperature reconstructions with decadal and centennial resolution over the past 2000 years. Between 200 and 1900 CE, the sub-fossil chironomid community was comprised of cold-water taxa, such as Abiskomyia, Micropsectra radialis-type, and Paracladius. Reconstructed temperatures were consistent with known climate anomalies during this period. A rapid shift in the composition of the chironomid community to warm-water adapted taxa (Chironomus anthracinus-type, Dicrotendipes, and Tanytarsus lugens-type) in the late 20th century was observed in both systems. Our results demonstrate that these lake ecosystems are undergoing marked transformations to warmer, more nutrient-rich environments, and suggest water sustainability pressures on freshwater and human systems will likely continue in tandem with ongoing climate change. To contextualize the influence of recent warming and elucidate the status of water resource vulnerability over the longer term, paleolimnological methods can be usefully applied as components of vulnerability assessments.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.000 | 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".