Data from: Sugar pine association genetics and performance in a post-fire restoration planting

Climate change is motivating a reassessment of how seeds are selected for reforestation, as rapid environmental change can lead to local maladaptation in trees. Genetic association studies and past seed source climate both have the potential to help identify appropriate planting stock, but these techniques have not been compared and tested as part of an operational planting program. In this study, we combined an analysis of SNPs associated with environmental gradients in sugar pine (P. lambertiana) with an analysis of post-fire seedling survival and growth in a restoration experiment. Our genotype-environment association (GEA) tests revealed 829 SNPs (single nucleotide polymorphisms) with significant association with climate gradients – especially April snowpack – 323 of which either had annotations that suggested potential functional importance or were identified by two different methods. We then built Bayesian models of survival and growth for all seedlings to test the effects of source elevation, a common proxy for climate. For the subset of seedlings alive and genotyped in 2020 (1–3 years after planting), we tested the relative predictive ability of source elevation versus the proportion of seedling alleles expected to be locally advantageous. We found that source elevation was generally better at predicting seedling performance than genotype indices, perhaps because of the limited scope of the association analysis. Seed sources from 500–1500 feet lower in elevation and one seed zone further south generally performed as well or better than local seed sources. This is likely because the temperatures in the planting area closely resemble that of those source regions in the mid-20th century, allowing seedlings to survive and exhibit the higher growth potential often seen in warmer-climate populations. By contrast, seedlings from cooler, wetter sources tended to perform poorly. This result, and those of similar previous studies, suggest that “climate matching” using past climate information for existing seed sourcing units is a reasonable starting point for finding seedlings suited to already-altered planting site climate conditions. However, further tests with more extensive genomic and performance data may improve the utility of genotype information for seed selection.

气候变化正推动人们重新评估造林用种的遴选方式，因为快速的环境变化会导致树木出现本地适应性不良的问题。遗传关联研究与基于历史种源气候的方法均有望助力筛选适宜的造林种植材料，但这两类技术尚未在商业化造林项目中开展对比与测试。本研究结合了糖松（P. lambertiana）与环境梯度相关的单核苷酸多态性（single nucleotide polymorphisms，SNPs）分析，以及某造林修复实验中火灾后幼苗存活与生长情况的分析。我们的基因型-环境关联（genotype-environment association，GEA）测试显示，共有829个单核苷酸多态性与气候梯度（尤其是四月积雪量）存在显著关联；其中323个要么具有提示潜在功能重要性的注释信息，要么通过两种不同方法得以鉴定。随后，我们为所有幼苗构建了存活与生长的贝叶斯模型，以测试种源海拔——一种常用的气候替代指标——的影响效应。针对2020年（造林后1~3年）仍存活且完成基因分型的幼苗子集，我们对比测试了种源海拔与预期携带本地适应性优势等位基因比例的相对预测能力。研究结果显示，种源海拔通常比基因型指标更能准确预测幼苗表现，这可能缘于关联分析的覆盖范围有限。海拔较种植地低500~1500英尺，以及再往南一个种源区的种源，其整体表现通常不亚于甚至优于本地种源。这一现象可能缘于：种植区域的气温与20世纪中期这些种源区的气温极为相似，使得幼苗能够存活，并展现出暖气候种群常见的更高生长潜力。与之相反，来自冷凉湿润种源的幼苗往往表现较差。本研究结果与此前同类研究均表明，基于现有种源单元的历史气候信息开展"气候匹配"，是筛选适配已发生气候变化的种植场地的幼苗的合理起点。不过，借助更全面的基因组与表现数据开展进一步测试，或可提升基因型信息在种苗遴选工作中的应用价值。