Climate change effects on coastal wetlands - Linking microbial community composition and ecosystem responses

湿地是陆地和水生生态系统交界处的动态栖息地。它们的功能是净化受污染的水，改善洪水，补给地下水含水层，并支持各种动植物。遗憾的是，近年来由于人口膨胀、污染、沿海开发和其他人类活动，地球上一半的湿地已经消失。除了上面提到的生态系统服务，湿地是地球上生物地球化学最活跃的栖息地之一。它们已被确定为碳固存和温室气体排放调节的关键场所。这些环境对环境扰动非常敏感，全球气候变化的影响——尤其是海平面上升——已经很明显。海平面上升会将咸水带入历史上的淡水湿地，改变沉积物中的化学反应和土壤微生物群落的组成。本研究为淡水湿地对盐水入侵的响应提供了更好的理解，并特别关注了土壤微生物及其在碳固存和温室气体排放中的作用。除了其科学贡献外，该项目还促进了科学教育和公众对潮汐淡水湿地面临的威胁的认识，并包括旨在向社区（从小学到成人）进行环境科学基本方面教育的活动。微生物群落历来被视为“黑箱”，因为假设存在高水平的功能冗余，并且微生物种群动态（例如，对全球变化的响应）不重要。然而，最近的许多研究表明，微生物群落组成的变化可以直接影响生态系统过程速率，这促使了对微生物群落对干扰的响应的研究。本研究的总体目标是将基于基因组学的土壤微生物群落特征与重要生态系统碳转化的过程水平测量联系起来，并研究它们对环境变化的集体响应。该研究项目包括在切萨皮克湾主要支流弗吉尼亚州帕芒基/约克河系统的潮汐淡水和低盐沼泽中进行观测和操纵实验。该项目结合了沿现有河流盐度梯度的湿地评估，作为未来盐水入侵的时空替代，并进行了原位盐水添加实验，以表征微生物-植物-土壤耦合系统的变化。土壤微生物群落的分子遗传学分析（16S测序、qPCR和RT-qPCR）、过程速率测量（铁和硫酸盐还原、甲烷生成）以及生态系统二氧化碳和甲烷交换正在被用于开发微生物群落组成变化如何影响生物地球化学过程的详细机制理解。这一基础知识将为未来有效地将微生物群落纳入生态系统过程模型的研究铺平道路。

Wetlands are dynamic habitats that are found at the interface of terrestrial and aquatic ecosystems. They function to cleanse polluted water, ameliorate floods, recharge groundwater aquifers, and support diverse flora and fauna. Regretfully, half of Earth's wetlands have been lost in recent times due to population expansion, pollution, coastal development, and other human activities. In addition to the ecosystem services mentioned above, wetlands are among the most biogeochemically active habitats on Earth. They have been identified as key sites for carbon sequestration and regulation of greenhouse gas emissions. These environments are very sensitive to environmental perturbation, and the effects of global climate change - especially sea level rise - are already evident. Sea level rise can bring saltwater into historically freshwater wetlands, changing the chemical reactions that take place in the sediment and the composition of soil microbial communities. This research provides a better understanding of freshwater wetland response to saltwater intrusion and specifically focuses on soil microorganisms and their roles in carbon sequestration and greenhouse gas emissions. In addition to its scientific contributions, this project advances both science education and public awareness of the threats facing tidal freshwater wetlands, and includes activities intended to educate the community (grade school children through adults) on basic aspects of environmental science.Microbial communities have historically been treated as a "black box" due to assumptions that there is a high level of functional redundancy and that microbial population dynamics (e.g., in response to global change) are unimportant. However, numerous recent studies have demonstrated that changes in microbial community composition can directly influence ecosystem process rates, motivating this study of the responses of microbial consortia to disturbance. The overall goal of this research is to link genomics-based characterization of soil microbial communities with process-level measurements of important ecosystem carbon transformations, and to examine their collective responses to environmental change. This research project includes both observational and manipulative experiments in the tidal freshwater and oligohaline marshes of the Pamunkey/York River system in Virginia, a major tributary of Chesapeake Bay. The project combines assessment of wetlands along an existing riverine salinity gradient, as a space-for-time substitution for future saltwater intrusion, with an in situ saltwater addition experiment that characterizes changes in the coupled microbe-plant-soil system. Molecular genetic analyses (16S sequencing, qPCR, and RT-qPCR) of the soil microbial communities, process rate measurements (iron and sulfate reduction, methanogenesis), and ecosystem carbon dioxide and methane exchanges are being used to develop a detailed mechanistic understanding of how compositional changes in microbial communities affect biogeochemical processes. This fundamental knowledge will pave the way for future research that effectively incorporates microbial communities into ecosystem process models.