The influence of lake attributes and predatory bass on the distribution of northern crayfish (<i>Orconectes</i> <i>virilis</i>) in central New Hampshire
Bibliographic record
Abstract
Introduced species influence the dynamics and structure of freshwater systems; understanding the variables that shape introduced species’ distributions can aid in anticipating their spread. We examined multiple factors that may influence the distribution of northern crayfish (Orconectes virilis (Hagen, 1870)), an introduced species, in New Hampshire, USA. Sampling occurred July to August 2010 in 20 lakes. We tested catch per unit effort (CPUE) and body size of crayfish against lake trophic status, size, depth, and shoreline development, as well as substrate type. We also compared CPUE and body size in the presence or absence of known predators, smallmouth bass (Micropterus dolomieu Lacepède, 1802) and largemouth bass (Micropterus salmoides (Lacepède, 1802)). Crayfish body size was not strongly associated with any tested variables, nor were there significant correlations between lake-level parameters and CPUE. CPUE increased with rocky substrates and decreased with macrophyte cover. We also found significantly lower CPUE in lakes with bass predators; this could be due to consumptive effects directly lowering crayfish abundance, nonconsumptive effects of bass on crayfish behavior, or both. Our work provides a baseline for future surveys examining northern crayfish or bass expansion in New Hampshire and highlights a variable that could be important as this crayfish colonizes additional locations outside its native range.
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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".