Context-dependent differences in the functional responses of conspecific native and non-native crayfishes
Bibliographic record
Abstract
Invasive species are proliferating globally and cause a range of impacts, necessitating risk assessment and prioritization prior to management action. Experimentally derived estimates of per capita effects (e.g. functional responses) have been advocated as predictors of field impacts of potential invaders. However, risk assessments based on estimates from single populations can be misleading if per capita effects vary greatly across space and time. Here, we present a large-scale, multi-population comparison of per capita effects of the American spinycheek crayfish, Faxonius (formerly Orconectes) limosus—a species with an extensive invasion history in eastern North America and Europe. Functional responses were measured on individuals from six geographically disparate populations of F. limosus in its native and invaded ranges on two continents. These revealed inter-population differences in both the maximum feeding rate and functional response type that could not be explained by the biogeographic origin of the population nor by time since the invasion. We propose that other differences in source communities (including the presence of competitors) impose selective pressures for phenotypic traits that result in dissimilar per capita effects. We also compared functional responses of the congeners F. limosus and F. virilis in the presence and absence of potential competitors to examine indirect competitive effects on feeding behaviour. The maximum feeding rate of F. limosus, but not F. virilis, was suppressed in the presence of heterospecific and conspecific competitors, demonstrating how the per capita effects of these species can differ across biotic contexts. In the competitor-presence experiments, individuals from the invasive population of F. limosus consistently had a higher maximum feeding rate than those of the native F. virilis, regardless of treatment. Our results caution against invasion risk assessments that use information from only one (or a few) populations or that do not consider the biotic context of target habitats. We conclude that comparative functional responses offer a rapid assessment tool for invader ecological impacts under context dependencies when multiple populations are analyzed.
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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 | 0.000 |
| 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 | 0.000 | 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".