Adaptive genetic variation mediates bottom-up and top-down control in an aquatic ecosystem
Bibliographic record
Abstract
Research in eco-evolutionary dynamics and community genetics has demonstrated that variation within a species can have strong impacts on associated communities and ecosystem processes. Yet, these studies have centred around individual focal species and at single trophic levels, ignoring the role of phenotypic variation in multiple taxa within an ecosystem. Given the ubiquitous nature of local adaptation, and thus intraspecific variation, we sought to understand how combinations of intraspecific variation in multiple species within an ecosystem impacts its ecology. Using two species that co-occur and demonstrate adaptation to their natal environments, black cottonwood (Populus trichocarpa) and three-spined stickleback (Gasterosteus aculeatus), we investigated the effects of intraspecific phenotypic variation on both top-down and bottom-up forces using a large-scale aquatic mesocosm experiment. Black cottonwood genotypes exhibit genetic variation in their productivity and consequently their leaf litter subsidies to the aquatic system, which mediates the strength of top-down effects from stickleback on prey abundances. Abundances of four common invertebrate prey species and available phosphorous, the most critically limiting nutrient in freshwater systems, are dictated by the interaction between genetic variation in cottonwood productivity and stickleback morphology. These interactive effects fit with ecological theory on the relationship between productivity and top-down control and are comparable in strength to the effects of predator addition. Our results illustrate that intraspecific variation, which can evolve rapidly, is an under-appreciated driver of community structure and ecosystem function, demonstrating that a multi-trophic perspective is essential to understanding the role of evolution in structuring ecological patterns.
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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 | 0.001 |
| 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".