Comparative functional responses of crayfishes: variation across species and populations
Bibliographic record
Abstract
Managers require effective methods for forecasting the impacts of introduced species, so that invasion threats can be prioritized. An emerging tool for invasive species risk assessment is the systematic comparison of the functional response (the relationship between predation rate and prey density) of native and invasive species. This approach is based on the assumption that species that have higher resource consumption rates will be more disruptive to food webs. Here, I use functional response analysis to examine the influence of biotic interactions on per capita effects of two congeneric North American crayfishes (Orconectes limosus and O. virilis) that have extensive invasion histories throughout this continent and in Europe. By experimental testing geographically disparate populations, I found intraspecific variation in the functional response curves and maximum feeding rates. A second set of experiments compared O. limosus and O. virilis from their respective native and invaded ranges, and from populations that are sympatric and allopatric with one another; these experiments further revealed interspecific and intraspecific variation in functional responses. Finally, I tested the effects of perceived competitors on the functional responses of both crayfishes. The presence of conspecific and heterospecific crayfish suppressed the maximum feeding rate of O. limosus, but they had no effect on the feeding rate of O. virilis. I conclude that source population and interspecific interactions mediate per capita effects, and possibly the overall impact, of introduced crayfishes. My results caution against the use of single populations in conducting invasive species risk assessments.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".