Comparison of Long-term Carbon Dynamics of Two Conifer Ecosystems

小行星9416821 森林在全球碳循环中发挥着重要作用，但其目前的作用尚未得到充分了解。 在某种程度上，这种不确定性源于对区域尺度分析缺乏重视。 森林地区之间和内部的异质性可显著影响碳循环过程以及对气候和土地利用变化的反应。 该项目将在三个空间层次上比较地球仪的两个重要森林区域-太平洋西北部和俄罗斯西北部-的碳动态：林分、景观和区域。 主要目的是确定控制这两个主要的针叶林生态系统的碳储量和通量的空间和时间格局的主要因素。 这一分析将以这两个地区的长期林分和天气记录、森林清查数据、航空摄影和遥感图像的综合为基础。 过去NSF-LTER/NASA对太平洋西北部森林的研究为拟议的俄罗斯项目和比较提供了模板。 该项目还以与彼得堡森林学院正在进行的合作研究为基础。 对于这两个地区，将使用相同的复杂建模工具来分析三个空间层面的碳动态以及森林项目中采伐和碳储存的影响。 对于俄罗斯西北部，将利用现有数据对模型进行校准和测试，这些数据包括对永久地块的长期观测、当地生长表和生物量方程、森林清查数据（包括森林类型和土壤）、天气数据、遥感图像以及木材采伐和加工参数。 该项目将鼓励在长期生态研究方面建立进一步的国际伙伴关系，并为美国科学界提供宝贵的俄罗斯新数据资源。

9416821 Harmon Forests play a major role in the global carbon cycle, but their current role is not fully understood. To some degree this uncertainty stems from the lack of attention to regional scale analysis. Heterogeneity between and within forested regions can significantly affect carbon cycling processes and the response to climate and landuse change. This project will compare the carbon dynamics of two significant forest regions of the globe, the Pacific Northwest and northwestern Russia at three spatial levels: stand, landscape and region. The main objective is to determine the major factors controlling the spatial and temporal patterns of carbon stores and fluxes within these two major coniferous ecosystems. This analysis will be abased on the synthesis of long-term stand and weather records, forest inventory data, aerial photography, and remote sensing imagery for both regions. Past NSF-LTER/NASA studies of the Pacific Northwest forests provide the template for the proposed Russian project and comparison. The project also builds upon an ongoing collaborative study with the St. Petersburg Forest Academy. For both regions the same complex of modeling tools will be used to analyze carbon dynamics at three spatial levels as well as the impact of harvesting and carbon stored in forest projects. For northwestern Russia the models will be calibrated and tested with existing data including long-term observations on permanent plots, local growth tables and biomass equations, forest inventory data including forest types and soils, weather data, remotely sensed images and timber harvest and processing parameters. This project will encourage further international partnerships in long-term ecological studies as well as make valuable new Russian data resources available to the US scientific community.