Factors associated with the success of native and nonnative species in an unfragmented arid-land riverscape
Bibliographic record
Abstract
Native fish persistence is threatened by the establishment and spread of nonnatives. Identifying environmental and biotic factors associated with the success of co-occurring native fishes and nonnative taxa is central to identifying mechanisms responsible for native declines and nonnative expansion. We related physicochemical variables, food resources, and community composition to the success (secondary production) of native and nonnative fishes, tadpoles, and crayfish across six sites in three reaches (tributary, canyon, and valley) during 2008–2011 in the Gila River, New Mexico. Native fish success was greater than nonnative success across a range of physicochemical conditions, basal resource supply rates, and nonnative communities, although nonnative fish, tadpole, and crayfish success could approach or exceed that of native fishes in canyon habitats, a warm-water tributary, or in downstream valley sites, respectively. Native fish success was lowest in canyon reaches, when flathead catfish (Pylodictis olivaris) and common carp (Cyprinus carpio) were highly productive. These results demonstrate the potential for native fish persistence in the presence of nonnatives in physically unmodified streams, highlighting the importance of habitat preservation for native conservation.
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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 | 0.001 | 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) | 0.001 | 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".