Under Pressure: Macroinvertebrate Community Responses to Agriculture in Temporary Streams
Bibliographic record
Abstract
ABSTRACT Temporary streams dominate global river networks and thus often occur in catchments dominated by agricultural land uses. Drying and agriculture can exert similar stressors on aquatic communities, for example, by decreasing dissolved oxygen concentrations and increasing fine sediment deposition. However, little is known about the effects of agriculture in driving taxonomic and trait variability in temporary stream communities. Therefore, we compared the effects of agricultural land use on variability in taxonomic and functional macroinvertebrate communities in temporary and perennial streams. We used 98 macroinvertebrate samples collected from sites with perennial (n = 49) and temporary (n = 49) flow in southern England. We quantified the spatial extent of agriculture surrounding each site, assigned samples to high (n = 62) and low (n = 36) agricultural land use categories, and tested whether variability in community composition differed between perennial and temporary reaches and between high and low agricultural categories. We also tested whether the occurrence of temporary stream specialist species was influenced by agriculture. Regardless of agricultural land use, temporary reach communities were more variable than those in perennial reaches, suggesting that drying is a bigger influence than agriculture on stream communities. Within temporary reaches, communities were comparably variable regardless of agriculture, whereas agriculture increased variability among perennial reach communities. The occurrence of temporary stream specialists was unaffected by agriculture. Our results suggest that tolerance of drying by temporary stream communities confers tolerance of agriculture. This co‐tolerance of drying and agriculture may occur because temporary stream communities typically comprise species that experience agriculture and drying as comparable pressures. These species include temporary stream specialists that tolerate a wide range of environmental conditions, including drying. Although temporary stream communities and their specialist species may be co‐tolerant of drying and agriculture, these and other human pressures are intensifying, with potentially detrimental impacts on their long‐term stability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".