Paleolimnology as a Tool to Achieve Environmental Sustainability in the Anthropocene: An Overview
Bibliographic record
Abstract
Lacustrine sediment accumulation provides meaningful and diverse long-term records of environmental change. This overview highlights the usefulness of the paleolimnological approach in evaluating the magnitude and direction of human-induced environmental change in lakes and their catchments. Because of the services they provide, freshwater ecosystems have always been significantly affected by human activities. However, the rate and extent of human-induced change in continental freshwaters and their catchments has considerably increased since the beginning of industrialization (mid-18th century), and are even more pronounced since the advent of the “Great Acceleration” (since the mid-20th century). Global change, including climate and landscape changes, loss of biodiversity, species introductions and the spread of pollutants, leave traces in lake sediment archives that provide valuable long-term information with which to evaluate and quantify past environmental changes. This paper outlines how the knowledge gleaned from an interdisciplinary paleolimnological approach can benefit the development of mitigation and adaptation measures to current global change at various latitudes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".