Collaborative Research: Producing an Updated Synthesis of the Arctic's Marine Primary Production Regime and Its Controls

初级生产为北冰洋生态系统提供能源，就像在所有生态系统中一样。了解海洋初级生产力(PP)及其控制是评价北冰洋作为一个系统并允许对其现状进行诊断性模拟以及对未来变化进行预测模拟的关键一步。本建议的重点是综合现有关于海洋初级生产力及其变化的物理控制(如光、营养和层结)的研究和数据，并利用这种综合来更好地理解海洋初级生产力在时间和空间上的变化以及作为气候变化的函数。具体地说，这项工作将：-使用强调不同空间和时间尺度的互补方法来合成PP的估计，将强调不同空间和时间尺度的PAO数据集(ARCS-PP)整合为一个一致的泛AO数据集。这些方法是：(A)14C吸收(测量；瞬时总藻类初级生产量)，(B)营养物质、O2和无机碳的生产/消耗(衍生；季节性和区域尺度的群落净生产量)，(C)遥感(衍生；季节性、区域性和实时的泛澳净群落生产量)和(D)生物物理算法(衍生；净初级生产量作为物理、化学和生理因素的函数)。-使用ARCS-PP来测试关于PP控制的假设，并准备海洋PP数据集，以供AO建模师校准生物地球化学数值模型，这两个项目都是与现有的或拟议的ARCS资助的项目合作的。-定义具有类似时间和空间变异性的关于PP的操作类似于PP的功能区域。-使用历史数据记录中的类似物来研究PP的潜在未来变化。

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.