Shifts in the abiotic and biotic environment of cultivated sunflower under future climate change
Bibliographic record
Abstract
Sunflower is a unique model species for assessing crop responses and adaptation to climate change. We provide an initial assessment of how climate change may influence the abiotic and biotic environment of cultivated sunflower across the world. We find an 8% shift between current and future climate space in cultivated sunflower locations globally, and a 48% shift in Northern America, where the crop originates. Globally, the current niche occupied by sunflower crop wild relatives offer few opportunities to adapt to future climate for cultivated sunflower, but in Northern America 100% of the future climate space of cultivated sunflower is filled by the niche of primary wild relative germplasm alone (e.g. wild Helianthus annuus). Globally, we find little difference in the overlap between current and future climate space of cultivated sunflower with the niche of the important sunflower pathogen Sclerotinia sclerotiorum, but in Northern America, climate change will decrease the overlap between local populations of this pest and cultivated sunflower by 38%. Our analysis highlights the utility of multi-scale analysis for identifying candidate taxa for breeding efforts and for understanding how future climate will shift the abiotic and biotic environment of cultivated crops.
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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 | 0.000 |
| 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".