Maternal effects of climate warming and nitrogen deposition vary with home and introduced ranges
Bibliographic record
Abstract
Abstract Maternal effects allow offspring to cope with rapidly changing environments. While the immediate effects of long‐term climate warming and nitrogen (N) deposition are well documented, their maternal effects have been little studied. We conducted a 6‐year maternal experiment withSolidago canadensis(Canadian goldenrod), native to North America (home range) and invasive in China (introduced range), and then performed two offspring experiments to address how maternal warming, maternal N‐addition and population source interacted to influence offspring performance. Maternal effects of warming and N‐addition on seed traits, leaf dry matter content and whole‐plant biomass were stronger inS. canadensisoffspring from China (introduced range) than in offspring from North America (home range). Matched maternal–offspring environments allowed offspring to perform better compared to mismatched environments; offspring grown under warming flowered and produced seeds within a growing season only when their maternal plants were previously exposed to warming. Offspring environments influenced its performance and also modulated maternal effects. We suggest that the maternal effects of simulated climate warming and N deposition could vary with home and introduced ranges. Our findings imply that maternal warming could advance the reproductive phenology of offspring. A free Plain Language Summary can be found within the Supporting Information of this article.
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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 | 0.001 |
| 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".