A synthesis of local adaptation to climate through reciprocal common gardens
Bibliographic record
Abstract
Abstract Contrasts of differences within plant species and ecotypes are often best examined in ecology, evolution and genetics through provenance and biogeographical comparisons. Climate adaptation studies in plants are no exception and benefit from experiments that use these sets of factors. Reciprocal common gardens are a tool used to test for local adaptation in species to different contexts including climate. A synthesis of common gardens and intraspecific tests for climate adaptation was used to compile over 200 studies that explored the relative efficacy of this tool and the ecology of change. Exclusion criteria were applied to review this literature and to compile specific tests that explicitly examined climate, plants and reciprocity in gardens for a total of 70 independent instances. A meta‐analysis was used to test for consistency and significance of detecting ecotypes for the different categories of traits tested and by the transplanting of seeds or seedlings. This meta‐analysis provides clear evidence for plant adaptation to climate change because all significant effect size estimates were positive, relatively large, and both seed and seedling transplants demonstrated consistent evidence for local adaptation. Emergence and germination responses from seed transplant experiments and relative growth and biomass differences from seedling transplants provided particularly strong support. Synthesis . Reciprocal common gardens were a highly effective experimental design to test for ecotypic differentiation and for climate adaptation. Nonetheless, we propose that future studies clearly define whether ecotypes are being explicitly tested in common garden experiments to enable evidence syntheses and discovery, and we highlight the need for reciprocal climatic gardens to clearly test for continued capacity for local adaptation in response to divergent climate selection processes in many plant species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.028 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".