Landscape-controlled chemistry variation affects communities and ecosystem function in headwater streams
Bibliographic record
Abstract
We show that benthic freshwater communities of naturally acidic streams in boreal catchments differ depending on properties of the surrounding landscape. Although low pH usually is associated with negative impacts on species diversity and ecosystem function, here decomposition by insects and microbes as well as the abundance of leaf-eating insects were generally high at low pH and at humic sites influenced by mire-dominated compared with forest-dominated surroundings. Moreover, in situ growth experiments showed that the survival of two of the most abundant insect species was higher when they originated from mire-influenced sites, underscoring their tolerance to low pH. However, species diversity generally increased with pH and was greater at forest-influenced than at mire-influenced sites. Although less diverse, acidic and humic streams proved to be functional and supported distinct macroinvertebrate assemblages. Diversity and function in naturally acidic streams are apparently greatly influenced by the prevailing kinds of landscape-driven influences on water chemistry. In conclusion, well-known negative impacts of anthropogenic acidity on diversity and function may not apply to naturally acidic systems that are chemically and biologically heterogeneous.
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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 | 0.001 | 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".