Impacts of fine sediment addition to tussock, pasture, dairy and deer farming streams in New Zealand
Bibliographic record
Abstract
Summary 1. Increased fine sediment input caused by agricultural development is expected to act as a stressor for stream ecosystems. In a large‐scale field experiment, we added fine river sand to 50‐m reaches of three second‐order streams in each of four categories of catchment development (ungrazed tussock grasslands, grazed pasture, dairying and deer farming) and measured the responses of macroinvertebrates and aquatic moss. 2. Before addition, fine sediment cover differed between land uses, being lowest in tussock (7%), intermediate in pasture (30%) and dairy (47%) and highest in deer streams (88%). Sediment addition increased cover by one land‐use category (e.g. augmented sediment cover in tussock streams was similar to pre‐existing cover in pasture streams), and cover remained high in impact reaches (compared with controls) throughout the 5‐week experiment. Sediment addition did not change concentrations of phosphate, nitrate and ammonium, which were generally highest in dairy streams and lowest in tussock streams. 3. Aquatic mosses (most common in tussock, absent in dairy and deer), invertebrate density (highest in deer, lowest in tussock), taxon richness (highest in pasture, lowest in deer) and diversity (highest in pasture and tussock, lowest in dairy and deer) all differed between land uses. Sediment addition resulted in reductions of moss cover, invertebrate taxon richness and richness of Ephemeroptera, Plecoptera and Trichoptera in impact relative to control reaches. 4. The impact of sediment addition was strongest in pasture streams where pre‐existing sediment cover was moderate and richness and diversity of the invertebrate community highest. However, even in the already sediment‐rich and species‐poor deer streams, density of one common taxon was reduced significantly by sediment addition, and another two were affected in the same way in dairy streams, the second‐most intense land use. 5. Our experiment has disentangled the impact of sediment addition from other concomitant land‐use effects that could not be reliably distinguished in previous research, which has mainly consisted of correlative studies or unrealistically small‐scale experiments.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".