Adaptive geographical clines in the growth and defense of a native plant
Bibliographic record
Abstract
Broad‐scale geographical gradients in the abiotic environment and interspecific interactions should select for clinal adaptation. How trait clines evolve has recently received increased attention because of anticipated climate change and the importance of rapid evolution in invasive species. This issue is particularly relevant for clines in growth and defense of plants, because both sets of traits are closely tied to fitness and because such sessile organisms experience strong local selection. Yet despite widespread recognition that growth and defense traits are intertwined, the general issue of their joint clinal evolution is not well resolved. To address heritable clinal variation and adaptation of growth and defense traits of common milkweed ( Asclepias syriaca ), we planted seed from 22 populations encompassing the species' latitudinal range in common gardens near the range center (New York) and toward the range edges (New Brunswick and North Carolina). Populations were differentiated in 13 traits, and six traits showed genetically based latitudinal clines. Higher‐latitude populations had earlier phenology, lower shoot biomass, more root buds and clonal growth, higher root‐to‐shoot ratio, and greater latex production. The cline in shoot biomass was consistent in all three locations. Selection on phenology was reversed in New Brunswick and North Carolina, with early genotypes favored in the north but not the south. We found no clines in foliar trichomes or toxic cardenolides. Annual precipitation of source populations explained variation in phenology, clonal growth, root‐to‐shoot ratio, and latex. Across four traits measured in New Brunswick and North Carolina, we found garden‐by‐latitude (and garden‐by‐precipitation) interactions, indicating plasticity in genetically based trait clines. In the two gardens with substantial herbivory (New York and North Carolina), northern populations showed higher resistance to insects. Resistance to aphids was driven by trichomes and water content, while resistance to monarch caterpillars was driven by latex. However, surveys of natural populations indicated that leaf damage and insect diversity on milkweed are low at the geographical extremes (New Brunswick and North Carolina) and higher toward the range center. We speculate that milkweed plants evolved clines in growth traits in response to climate, and that this set the template for tolerance to herbivory, which subsequently shaped the evolution of defensive traits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".