Community assembly of prairie farm ponds: build it and they will come, stock it and they won't
Bibliographic record
Abstract
Dam construction affects freshwater ecosystems worldwide. While there is much focus on large impoundments, farm ponds are overlooked despite their near-ubiquity across human-altered landscapes. Within the Great Plains of North America, there are millions of farm ponds, yet little is known about the fish communities and factors structuring them. We propose a conceptual model where fish, amphibian, and crayfish abundances differ along a pond size and water permanency gradient and are further influenced by interactions among species. In the summer of 2021, we sampled 100 farm ponds across central Kansas, primarily on private land. Pond size and permanency explained community structure with smaller and less permanent ponds being dominated by amphibians and crayfish while larger ponds were dominated by stocked sportfish. Distribution modeling revealed a negative correlation between stocked fish and other community components indicating potential interactions. If we are to conserve headwater stream species, especially those that are threatened or endangered, strategies that integrate farm ponds seem necessary given their prevalence on the landscape.
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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 | 0.001 |
| 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 | 0.000 |
| 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".