Plant responses to climatic extremes: within‐species variation equals among‐species variation
Bibliographic record
Abstract
Within-species and among-species differences in growth responses to a changing climate have been well documented, yet the relative magnitude of within-species vs. among-species variation has remained largely unexplored. This missing comparison impedes our ability to make general predictions of biodiversity change and to project future species distributions using models. We present a direct comparison of among- versus within-species variation in response to three of the main stresses anticipated with climate change: drought, warming, and frost. Two earlier experiments had experimentally induced (i) summer drought and (ii) spring frost for four common European grass species and their ecotypes from across Europe. To supplement existing data, a third experiment was carried out, to compare variation among species from different functional groups to within-species variation. Here, we simulated (iii) winter warming plus frost for four grasses, two nonleguminous, and two leguminous forbs, in addition to eleven European ecotypes of the widespread grass Arrhenatherum elatius. For each experiment, we measured: (i) C/N ratio and biomass, (ii) chlorophyll content and biomass, and (iii) plant greenness, root (15) N uptake, and live and dead tissue mass. Using coefficients of variation (CVs) for each experiment and response parameter, a total of 156 within- vs. among-species comparisons were conducted, comparing within-species variation in each of four species with among-species variation for each seed origin (five countries). Of the six significant differences, within-species CVs were higher than among-species CVs in four cases. Partitioning of variance within each treatment in two of the three experiments showed that within-species variability (ecotypes) could explain an additional 9% of response variation after accounting for the among-species variation. Our observation that within-species variation was generally as high as among-species variation emphasizes the importance of including both within- and among-species variability in ecological theory (e.g., the insurance hypothesis) and for practical applications (e.g., biodiversity conservation).
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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 | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".