Collaborative Research: Producing an Updated Synthesis of the Arcrtic's Primary Production Regime and its Controls

初级生产为北冰洋生态系统和所有生态系统提供能源。了解海洋初级生产（PP）及其控制是了解北冰洋作为一个系统，并允许对其现状进行诊断建模以及对未来变化进行预测建模的关键一步。本提案的重点是综合有关AO PP及其变化的物理控制因素（如光、营养和分层）的现有研究和数据，并利用这种综合来更好地了解PP在时间和空间上的变化以及作为气候变化的函数。具体来说，这项工作将：-综合估算PP，使用互补的方法，强调不同的空间和时间尺度到一个一致的泛ao数据集（ARCSS-PP）。这些方法是：(a) 14C吸收（测量；瞬时藻类净初级产量），(b)养分、O2和无机碳生产/消耗（推导；季节性和区域规模净群落产量），(c)遥感（推导；季节性、区域和实时泛ao净群落产量）和(d)生物物理算法（推导；净初级产量作为物理、化学和生理因素的函数）。-利用ARCSS-PP测试关于PP控制的假设，并为AO建模者准备海洋PP数据集，以校准生物地球化学数值模型，与现有或拟议的arcss资助项目合作。-定义AO的功能区域，这些区域与PP相似，具有相似的时空变异性。-利用历史数据记录中的类似物调查未来PP的潜在变化。

Primary production provides the energy that fuels the Arctic Ocean (AO) ecosystem, as in all ecosystems. Understanding marine primary production (PP) and its controls is a critical step towards appreciating the Arctic Ocean as a system and allowing diagnostic modeling of its current status as well as prognostic modeling of future change.The focus of this proposal is to synthesize existing studies and data relating to AO PP and its changing physical controls such as light, nutrients, and stratification, and to use this synthesis to better understand how PP varies in time and space and as a function of climate change.Specifically, this work will:-Synthesize estimates of PP, using complementary methods that emphasize different spatial and temporal scales into a consistent pan-AO data set (ARCSS-PP). These methods are: (a) 14C uptake (measured; instantaneous gross to net algal primary production), (b) nutrient, O2 and inorganic carbon production/consumption (derived; seasonal and regional scale net community production), (c) remote sensing (derived; seasonal, regional, and real-time pan-AO net community production) and (d) bio-physical algorithms (derived; net primary production as a function of physical, chemical and physiological factors).-Employ ARCSS-PP to test hypotheses regarding the controls of PP and to prepare a marine PP dataset for AO modelers to calibrate biogeochemical numerical models, both in collaboration with existing or proposed ARCSS-funded projects.-Define functional regions of the AO that operate similarly with respect to PP with similar temporal and spatial variability.-Investigate potential future changes in PP using analogues from the historical data record.