Reconstructing Glacial Nitrogen and Carbon Cycling Using Isotopes

深海沉积物中氮和碳同位素的测量记录了上一个冰河时代和现代海洋之间的巨大变化。然而，氮和碳同位素都受到不同物理和生物地球化学过程的影响，这使得它们的解释不明确。在本研究中，将使用一个基于过程的气候、海洋环流和生物地球化学耦合模型，包括碳和氮同位素，并结合沉积物数据，以重建冰川氮和碳循环。该模型将用明确的铁循环进行修正，并将编制末次冰期极大期和现代海洋沉积物的氮和碳同位素的全球数据库。这种方法可以检验有关海洋总氮储量变化、铁施肥引起的极地养分消耗及其对大气二氧化碳浓度影响的假设。该项目继续由俄勒冈州立大学的一位气候建模师和一位古海洋学家进行合作，并与麦吉尔大学的一位加拿大研究人员进行国际合作。资金支持一名研究生，来自俄勒冈州各地的30名K-12教师的夏季研讨会，以及俄勒冈州立大学一名本科生的夏季研究经历。此外，研究人员将积极参与古气候模拟比对项目（PMIP）和新成立的古碳模拟比对项目（PCMIP），努力评估古气候条件下气候模型的技能，提高对过去气候变化的认识。

Measurements of nitrogen and carbon isotopes from deep-sea sediments document dramatic changes between the last ice age and the modern ocean. However, both nitrogen and carbon isotopes are influenced by different physical and biogeochemical processes, which makes their interpretation ambiguous. In this research, a process-based coupled model of climate, ocean circulation and biogeochemistry that includes carbon and nitrogen isotopes will be used in conjunction with sediment data in order to reconstruct glacial nitrogen and carbon cycles. The model will be amended with explicit iron cycling and global databases of nitrogen and carbon isotopes from Last Glacial Maximum and modern ocean sediments will be compiled. This approach allows testing of hypotheses concerning changes in the total ocean nitrogen inventory, polar nutrient consumption due to iron fertilization and their effects on atmospheric CO2 concentrations. The project continues collaboration between a climate modeler and a paleoceanographer from Oregon State University and international collaboration with a Canadian investigator from McGill University. Funding supports a graduate student, a summer workshop for 30 K-12 teachers from all parts of Oregon and a summer research experience for an undergraduate student at Oregon State University. In addition, the researchers will actively participate in both the Paleoclimate Modeling Intercomparison Project (PMIP) and in the new Paleo Carbon Modeling Intercomparison Project (PCMIP), efforts that evaluate the skill of climate models under paleoclimate conditions and improve understanding of past climate changes.