The effects of drought on biodiversity in <scp>UK</scp> river ecosystems: Drying rivers in a wet country
Bibliographic record
Abstract
Abstract Climate change is interacting with water resource pressures to alter the frequency, severity and spatial extent of drought, which can thus no longer be considered a purely natural hazard. Although particularly severe ecological impacts of drought have occurred in drylands, its effects on temperate ecosystems, including rivers, are also considerable. Extensive research spanning a diverse range of UK rivers offers an opportunity to place the effects of past drought in the context of intensifying climate change and to examine the likely effects of future drought in a typically cool, wet country. Here, drought manifests instream as deficits in surface water, modified flow velocities, and—increasingly—partial or complete drying of previously perennial and naturally non‐perennial reaches. As a result, drought causes declines in the taxonomic and functional biodiversity of freshwater communities including microorganisms, algae, plants, invertebrates and fish, altering ecological processes and associated benefits to people. Although freshwater communities have typically recovered quickly after previous UK droughts, an increase in drought extremity may compromise recovery following future events. The risk of droughts that push ecosystems beyond thresholds to persistent, species‐poor, functionally simplified states is increasing. Research and monitoring are needed to enable timely identification of rivers approaching such thresholds and thus to inform interventions that pull these ecosystems back from the brink. Management actions that support natural flow regimes and promote natural processes that diversify instream habitats, including drought refuges, are also crucial to support biodiversity within functional river ecosystems as they adapt to a changing world. This article is categorized under: Water and Life > Nature of Freshwater Ecosystems Water and Life > Stresses and Pressures on Ecosystems Water and Life > Conservation, Management, and Awareness
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".