An integrative assessment of aquatic ecosystem services based on guideline thresholds
Bibliographic record
Abstract
Abstract Ecologists typically associate water quality with trophic status where oligotrophic ecosystems have excellent water quality and presumably provide more aquatic ecosystem services. However water quality is perceived differently among worldviews. Aquatic ecosystem service provisioning to the public health and agriculture sectors is determined using specific guidelines. But are these guidelines related to trophic status? Here, we developed an integrative ecosystem service framework using guideline thresholds for drinking, swimming, irrigation, suitability for livestock and aquatic wildlife in canadian rivers of varying trophic status. Drinkability was the most sensitive ecosystem service, met in 37% of cases, whereas livestock was the least, provided in 99%. Trophic status is a fair proxy for ecosystem services limited by fecal contamination as nutrients are related to human and animal populations, but not to those limited by metals. Using quantitative thresholds to assess the safe provisioning of multiple ecosystem services provides clear guidance for supporting resource management. In a nutshell Water quality is a commonly used term in management, but the metrics that determine whether a river can safely provide various aquatic ecosystem services differ among worldviews. We propose an integrative approach based on guideline thresholds to evaluate the frequency with which rivers are drinkable, swimmable, suitable for irrigation, livestock, and aquatic wildlife and compared this suitability with trophic status. Trophic status is a fair proxy for ecosystem services limited by fecal contamination, but not for those limited by metals. Using and developing more guideline thresholds provides a concrete way to assess ecosystem service provisioning that could help serve management.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".