Ecological and Evolutionary Effects of Stickleback on Community Structure
Bibliographic record
Abstract
Species' ecology and evolution can have strong effects on communities. Both may change concurrently when species colonize a new ecosystem. We know little, however, about the combined effects of ecological and evolutionary change on community structure. We simultaneously examined the effects of top-predator ecology and evolution on freshwater community parameters using recently evolved generalist and specialist ecotypes of three-spine stickleback (Gasterosteus aculeatus). We used a mesocosm experiment to directly examine the effects of ecological (fish presence and density) and evolutionary (phenotypic diversity and specialization) factors on community structure at lower trophic levels. We evaluated zooplankton biomass and composition, periphyton and phytoplankton chlorophyll-a concentration, and net primary production among treatments containing different densities and diversities of stickleback. Our results showed that both ecological and evolutionary differences in the top-predator affect different aspects of community structure and composition. Community structure, specifically the abundance of organisms at each trophic level, was affected by stickleback presence and density, whereas composition of zooplankton was influenced by stickleback diversity and specialization. Primary productivity, in terms of chlorophyll-a concentration and net primary production was affected by ecological but not evolutionary factors. Our results stress the importance of concurrently evaluating both changes in density and phenotypic diversity on the structure and composition of communities.
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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 | 0.000 | 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".