Environmental effects on genetic variance are likely to constrain adaptation in novel environments

Adaptive plasticity allows populations to cope with environmental variation but is expected to fail as conditions become unfamiliar. In novel conditions, populations may instead rely on rapid adaptation to increase fitness and avoid extinction. Adaptation should be fastest when both plasticity and selection occur in directions of the multivariate phenotype that contain abundant genetic variation. However, tests of this prediction from field experiments are rare. Here, we quantify how additive genetic variance in a multivariate phenotype changes across an elevational gradient, and test whether plasticity and selection align with genetic variation. We do so using two closely related, but ecologically distinct, sister species of Sicilian daisy (Senecio, Asteraceae) adapted to high and low elevations on Mount Etna. Using a paternal half-sibling breeding design, we generated and then reciprocally planted c.19,000 seeds of both species, across an elevational gradient spanning each species’ na..., All data was collected on seeds planted of two species at four elevations on Mt Etna, Sicily. Leaf pigment data was collected using a Dualex instrument (ForceA-France) and leaf morphology data was quantified from the software 'Lamina' that analyses scanned images of leaves., , # Environmental effects on genetic variance are likely to constrain adaptation in novel environments These data are from a field experiment that planted seeds of two species of *Senecio* at four elevations on the slopes of Mt Etna, Sicily. Seeds were produced using a quantitative genetic breeding design with c.80 individuals of each species so that additive genetic variance could be estimated for all traits measured. Survival was used as a proxy for fitness, and leaf trait measurements include leaf morphology, size and pigment content. ## Description of the data file: Walter\_etal\_2024\_EvolutionLetters.csv Below is a list of column identifiers in the .csv file. NA represent plants that died and could not be measured. Columns A-H are plant identifiers. * A: Species identifier. * B: TGSite is the transplant elevation (500m, 1000m, 1500m and 2000m). * C: PLANT is the individual ID for each plant. * D: Block is the experimental block at each elevation. * E: Family is the ...适应性可塑性（adaptive plasticity）可使种群应对环境波动，但当环境条件变得陌生时，该机制预计将失效。在全新环境中，种群或可转而依赖快速适应性进化提升适合度（fitness）、避免灭绝。当可塑性与自然选择均指向携带丰富遗传变异的多变量表型（multivariate phenotype）方向时，适应性进化速率应最快。然而，基于野外实验验证该预测的研究仍较为罕见。 本研究量化了多变量表型中的加性遗传方差（additive genetic variance）沿海拔梯度的变化规律，并检验可塑性与自然选择是否与遗传变异相匹配。我们以埃特纳火山上分别适应高、低海拔的两种亲缘关系密切但生态位分化的西西里雏菊近缘种——千里光属（*Senecio*，菊科Asteraceae）——为研究对象，采用父本半同胞育种设计（paternal half-sibling breeding design），培育并互作种植了约19000粒两个物种的种子，种植梯度覆盖了每个物种的原生…… 所有数据采集自西西里埃特纳火山四个海拔点位种植的两个物种的植株。叶片色素数据使用Dualex仪器（法国ForceA公司生产）采集，叶片形态数据通过分析叶片扫描图像的Lamina软件量化。 # 环境对遗传变异的影响或限制新环境中的适应性 本数据集源自一项野外实验：将两种千里光属植物的种子种植于西西里埃特纳火山山坡的四个海拔点位。实验采用数量遗传学育种设计，每个物种使用约80个个体繁育种子，以便对所有测定性状的加性遗传方差进行估算。本研究以存活率作为适合度的代理指标，叶片性状测定涵盖叶片形态、大小及色素含量。 ## 数据文件说明：Walter_etal_2024_EvolutionLetters.csv 以下为该.csv文件的列标识符列表。NA代表死亡且无法测定的植株。 A-H列为植株标识符： * A：物种标识符 * B：TGSite为移栽海拔（500m、1000m、1500m及2000m） * C：PLANT为单株个体ID * D：Block为各海拔点位的实验区组 * E：Family为……