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How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

机译:如何使用土壤监测网络改善对农业土壤中有机碳库动态和CO 2 通量的预测?

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As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach).
机译:随着陆地生态系统区域性和大陆性碳平衡的获得,显然土壤是最大的不确定性来源。在许多国家/地区正在实施土壤监测网络(SMN)中组织的土壤有机碳(SOC)重复清单。本文回顾了十个国家中SMN的概念和设计,并讨论了此类网络对减少土壤碳平衡不确定性的贡献。一些SMN旨在估算特定国家/地区的土地使用或管理对SOC存量的影响,而另一些SMN则收集土壤碳和辅助数据,以在全国范围内评估主要土地利用/土壤类型组合中的土壤碳状况。前者使用成对站点的单个采样活动,而后者使用系统的(通常是基于网格的)和分层的重复采样活动(间隔5-10年),每10–1,040km²使用一个站点的密度。对于成对的站点,为了允许进行统计分析,在每个站点取多个样本,而对于单个站点,则取复合样本。在这两种情况下,建议使用固定的深度增量以及体积密度和石材含量的样品。样品应存档,以便使用更新的技术进行重新测量。应系统记录每个地点的土地管理信息,并在可能的情况下记录土地使用历史。提出了一个巴西农业边疆的案例研究,其中计算了土地利用影响因子,以量化国家土地利用/管理转换矩阵中的CO 2 通量。只要有详细的土地管理记录,就可以为SMN的各个点运行基于过程的SOC模型。这些研究仍然很少,因为大多数SMN已在近期实施或正在进行中。以美国和比利时为例,SOC预测值的不确定性范围为1.6–6.5 Mg C ha -1 ,用于预测单个站点的SOC储量变化,不确定度为11.72 Mg C ha -1 或土壤/土地利用/气候单位的SOC平均变化的34%。对于国家SOC监测而言,分层采样站点似乎是将SOC值最直接地归因于具有相似土壤/土地使用/气候条件的单位(即空间隐式放大方法)。

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