高光谱叶片反射检测遗传和环境对树木表型的交互影响,实现气候变化下的大规模监测和恢复规划。

IF 6 1区 生物学 Q1 PLANT SCIENCES Plant, Cell & Environment Pub Date : 2024-11-04 DOI:10.1111/pce.15263
Jaclyn P M Corbin, Rebecca J Best, Iris J Garthwaite, Hillary F Cooper, Christopher E Doughty, Catherine A Gehring, Kevin R Hultine, Gerard J Allan, Thomas G Whitham
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引用次数: 0

摘要

植物对快速环境变化的反应取决于其遗传特性和表型可塑性,从而影响其生存和相关生态系统。然而,遗传和环境对表型的影响很难在大的空间尺度和时间范围内量化。叶片高光谱反射率为绘制从局部到景观层面的这些影响提供了一种潜在的可靠方法。利用手持式野外光谱仪,我们分析了野生种群和三个跨越陡峭气候梯度的有 6 年树龄的普通实验园中基础树种杨树的叶片高光谱反射率。首先,我们利用多变量和单变量方法表明,通过叶光谱可以检测到种群间和克隆基因型间的遗传变异。光谱预测野生树木之间种群身份的准确率为 100%,预测普通花园内种群身份的准确率为 87%-98%,预测不同环境下种群身份的准确率为 86%。植物健康的多个光谱指数具有显著的遗传性,基因型占种群内光谱变异的 10%-23%,占所有种群间变异的 14%-48%。其次,我们发现基因与环境之间的相互作用导致了光谱表型在常见花园环境中的种群特异性变化。光谱指数表明,基因不同的种群在应对相同的环境压力时会对叶绿素和含水量做出独特的调整,因此检测基因特性对于预测树木对变化的反应至关重要。第三,当种群转移到年平均最高温度比原产地条件更高的生长环境时,绿色度和光合效率的光谱指标会下降。这一结果表明,植物的生理策略发生了改变,进一步偏离了其本地适应的条件。转移到温度较低的环境中产生的负面影响较小,这表明植物光谱在植物性能调整方面具有方向性。因此,叶片反射率数据既能检测植物生理的局部适应性,也能检测植物生理的可塑性变化,从而通过高分辨率跟踪基因和表型变化以应对气候变化,为战略性恢复和保护决策提供信息。
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Hyperspectral Leaf Reflectance Detects Interactive Genetic and Environmental Effects on Tree Phenotypes, Enabling Large-Scale Monitoring and Restoration Planning Under Climate Change.

Plants respond to rapid environmental change in ways that depend on both their genetic identity and their phenotypic plasticity, impacting their survival as well as associated ecosystems. However, genetic and environmental effects on phenotype are difficult to quantify across large spatial scales and through time. Leaf hyperspectral reflectance offers a potentially robust approach to map these effects from local to landscape levels. Using a handheld field spectrometer, we analyzed leaf-level hyperspectral reflectance of the foundation tree species Populus fremontii in wild populations and in three 6-year-old experimental common gardens spanning a steep climatic gradient. First, we show that genetic variation among populations and among clonal genotypes is detectable with leaf spectra, using both multivariate and univariate approaches. Spectra predicted population identity with 100% accuracy among trees in the wild, 87%-98% accuracy within a common garden, and 86% accuracy across different environments. Multiple spectral indices of plant health had significant heritability, with genotype accounting for 10%-23% of spectral variation within populations and 14%-48% of the variation across all populations. Second, we found gene by environment interactions leading to population-specific shifts in the spectral phenotype across common garden environments. Spectral indices indicate that genetically divergent populations made unique adjustments to their chlorophyll and water content in response to the same environmental stresses, so that detecting genetic identity is critical to predicting tree response to change. Third, spectral indicators of greenness and photosynthetic efficiency decreased when populations were transferred to growing environments with higher mean annual maximum temperatures relative to home conditions. This result suggests altered physiological strategies further from the conditions to which plants are locally adapted. Transfers to cooler environments had fewer negative effects, demonstrating that plant spectra show directionality in plant performance adjustments. Thus, leaf reflectance data can detect both local adaptation and plastic shifts in plant physiology, informing strategic restoration and conservation decisions by enabling high resolution tracking of genetic and phenotypic changes in response to climate change.

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来源期刊
Plant, Cell & Environment
Plant, Cell & Environment 生物-植物科学
CiteScore
13.30
自引率
4.10%
发文量
253
审稿时长
1.8 months
期刊介绍: Plant, Cell & Environment is a premier plant science journal, offering valuable insights into plant responses to their environment. Committed to publishing high-quality theoretical and experimental research, the journal covers a broad spectrum of factors, spanning from molecular to community levels. Researchers exploring various aspects of plant biology, physiology, and ecology contribute to the journal's comprehensive understanding of plant-environment interactions.
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