Rapid evolution of a coastal marsh ecosystem engineer in response to global change
Rapid evolution of a coastal marsh ecosystem engineer in response to global change
复制标题
沿海沼泽生态系统工程师响应全球变化的快速演变
DOI：
10.1016/j.scitotenv.2022.157846
复制
发表时间：
2022
影响因子：
9.8
通讯作者：
Megonigal, J. Patrick
中科院分区：
文献类型：
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作者：
Mozdzer, Thomas J.;McCormick, Melissa K.;Slette, Ingrid J.;Blum, Michael J.;Megonigal, J. Patrick
有越来越多的证据表明，全球变化可以改变生态系统，引发能够塑造重要属性和过程的基础植物的快速进化。在这里，我们描述了一个现场规模的曝光实验和多位点分析的结果，说明升高的CO2（eCO2）和氮（N）富集可以导致在遗传和基因型变异的快速转变，芦苇，生态优势植物，作为一个生态系统工程师在全球沿海沼泽。与对照处理相比，基因型多样性下降超过三年的曝光，特别是氮富集。在氮富集的条件下，损失的幅度也随着时间的推移而增加。基因型频率的比较显示，比例丰度与暴露于eCO2和N的方式与预期的选择反应一致。比较还显示了权衡的证据，限制暴露反应，其中任何特定的基因型有利的一个因素，而不是不同的因素或因素的组合。这些研究结果挑战了普遍的观点，即植物介导的生态系统的全球变化的结果主要是由物种对环境压力变化的反应差异决定的，并强调了在预测模型中考虑生物进化的价值，以改善生态系统对全球变化的反应预测。
There is increasing evidence that global change can alter ecosystems by eliciting rapid evolution of foundational plants capable of shaping vital attributes and processes. Here we describe results of a field-scale exposure experiment and multilocus assays illustrating that elevated CO2(eCO2) and nitrogen (N) enrichment can result in rapid shifts in genetic and genotypic variation inPhragmites australis, an ecologically dominant plant that acts as an ecosystem engineer in coastal marshes worldwide. Compared to control treatments, genotypic diversity declined over three years of exposure, especially to N enrichment. The magnitude of loss also increased over time under conditions of N enrichment. Comparisons of genotype frequencies revealed that proportional abundances shifted with exposure to eCO2and N in a manner consistent with expected responses to selection. Comparisons also revealed evidence of tradeoffs that constrained exposure responses, where any particular genotype responded favorably to one factor rather than to different factors or to combinations of factors. These findings challenge the prevailing view that plant-mediated ecosystem outcomes of global change are governed primarily by differences in species responses to shifting environmental pressures and highlight the value of accounting for organismal evolution in predictive models to improve forecasts of ecosystem responses to global change.