The strength and direction of local (mal)adaptation depends on neighbour density and the environment
Bibliographic record
Abstract
Abstract Populations are embedded in communities, but despite their potential to affect individual fitness, it is unknown whether and how species interactions evolve in communities. Evolutionary outcomes are likely more complex in natural communities because (a) the evolution of interactions may not be evenly distributed among all community members and (b) coevolution is conditional on the environmental conditions within which interactions are playing out. To test the evolution of interaction strengths in natural communities, we performed two common garden experiments in grassland communities in Northern California. In each garden, we transplanted individuals of four populations (one local, three foreign) of an annual invasive grass Bromus hordeaceus into natural communities, characterized the interaction neighbourhood around each focal individual, and quantified individual fitness. This method allowed us to fit multispecies competition models to fitness data, estimating interaction strengths between focal B. hordeaceus populations and each of seven species that were common in the interaction neighbourhoods, in each garden. We found that interaction strengths significantly differed among local and foreign source populations, but the direction and magnitude of evolution differed among common gardens and among neighbour species—in neither garden were interactions experienced more strongly by foreign populations compared to local populations. The fitness of local populations (relative to foreign populations) decreased when neighbours were removed, strongly enough in one garden to cause strong local maladaptation, and the local population did not perform the best in either garden. Synthesis . Together, our results demonstrate how species interactions evolve to determine fitness in ecological communities, providing a richer view of adaptation in natural systems. In our study, this richness included the unique challenges populations face in nature: uneven abundances and a diffuseness of species interactions, nonlinear density effects on fitness, and evidence of (mal)adaptation that is conditional on local conditions. We conclude by hypothesizing the causes and consequences of challenges to adaptation and how they help identify priority areas for the field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".