Department of Forest Resources, University of Minnesota, St. Paul, MN 55108, USA.
Department of Forest Resources, University of Minnesota, St. Paul, MN 55108, USA; USDA Forest Service, Northern Research Station, St. Paul, MN 55108, USA.
Sci Total Environ. 2019 Mar 1;654:94-106. doi: 10.1016/j.scitotenv.2018.10.359. Epub 2018 Oct 29.
Forest ecosystems contribute substantially to carbon (C) storage. The dynamics of litter decomposition, translocation and stabilization into soil layers are essential processes in the functioning of forest ecosystems, as these processes control the cycling of soil organic matter and the accumulation and release of C to the atmosphere. Therefore, the spatial distribution of litter and soil C stocks are important in greenhouse gas estimation and reporting and inform land management decisions, policy, and climate change mitigation strategies. Here we explored the effects of spatial aggregation of climatic, biotic, topographic and soil variables on national estimates of litter and soil C stocks and characterized the spatial distribution of litter and soil C stocks in the conterminous United States (CONUS). Litter and soil variables were measured on permanent sample plots (n = 3303) from the National Forest Inventory (NFI) within the United States from 2000 to 2011. These data were used with vegetation phenology data estimated from LANDSAT imagery (30 m) and raster data describing environmental variables for the entire CONUS to predict litter and soil C stocks. The total estimated litter C stock was 2.07 ± 0.97 Pg with an average density of 10.45 ± 2.38 Mg ha, and the soil C stock at 0-20 cm depth was 14.68 ± 3.50 Pg with an average density of 62.68 ± 8.98 Mg ha. This study extends NFI data from points to pixels providing spatially explicit and continuous predictions of litter and soil C stocks on forest land in the CONUS. The approaches described illustrate the utility of harmonizing field measurements with remotely sensed data to facilitate modeling and prediction across spatial scales in support of inventory, monitoring, and reporting activities, particularly in countries with ready access to remotely sensed data but with limited observations of litter and soil variables.
森林生态系统对碳（C）储存有重要贡献。凋落物分解、迁移和稳定到土壤层的动态是森林生态系统功能的重要过程，因为这些过程控制着土壤有机质的循环以及 C 向大气的积累和释放。因此，凋落物和土壤 C 储量的空间分布对于温室气体估算和报告以及土地管理决策、政策和气候变化缓解策略非常重要。在这里，我们探讨了气候、生物、地形和土壤变量的空间聚集对全国凋落物和土壤 C 储量估计的影响，并描述了美国大陆（CONUS）的凋落物和土壤 C 储量的空间分布。从 2000 年到 2011 年，在美国国家森林清查（NFI）的永久性样地（n=3303）上测量了凋落物和土壤变量。这些数据与从 LANDSAT 图像（30m）估计的植被物候数据和描述整个 CONUS 环境变量的栅格数据一起使用，以预测凋落物和土壤 C 储量。估计的总凋落物 C 储量为 2.07±0.97Pg，平均密度为 10.45±2.38Mg ha，0-20cm 深度的土壤 C 储量为 14.68±3.50Pg，平均密度为 62.68±8.98Mg ha。本研究将 NFI 数据从点扩展到像素，为 CONUS 森林土地上的凋落物和土壤 C 储量提供了空间明确和连续的预测。所描述的方法说明了协调实地测量和遥感数据以促进模型和预测跨空间尺度的效用，以支持清查、监测和报告活动，特别是在有现成的遥感数据但凋落物和土壤变量观测有限的国家。
