Standardized Data to Improve Understanding and Modeling of Soil Nitrogen at Continental Scale
Standardized Data to Improve Understanding and Modeling of Soil Nitrogen at Continental Scale
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DOI：
10.1029/2022ef003224
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发表时间：
2023-05
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通讯作者：
S. Weintraub‐Leff;S. Hall;M. Craig;D. Sihi;Zhuonan Wang;S. Hart
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作者：
S. Weintraub‐Leff;S. Hall;M. Craig;D. Sihi;Zhuonan Wang;S. Hart
氮（N）是陆地生态系统中的关键限制性营养素，但在我们预测和模拟控制土壤N循环的能力方面仍存在重大差距。这可能部分是由于缺乏广泛的时空尺度的标准化采样。在这里，我们介绍了一个大陆分布的，公开可用的数据集收集的国家生态观测网络（氖），可以帮助填补这些空白。首先，我们详细介绍了采样设计和方法，用于收集和分析土壤无机氮库和净通量率数据从47个陆地站点。我们解决方法上的挑战，即使是使用统一协议的网络生成一个标准化的数据集。然后，我们评估抽样设计内的变化来源，并比较测得的净氮矿化模拟通量从社区地球系统模型2（CESM 2）。我们观察到广泛的时空变化的无机氮库的大小和净转化率。研究中心解释了氖分层抽样设计中的最大变异，其次是研究中心内的地块。有机层有较大的池和净氮转化率比矿物层的样品重量的基础上。大多数网站表现出一定程度的季节性N动态，但总体上这些时间模式不匹配CESM2，导致观测数据和建模数据之间的对应关系较差。展望未来，这些数据可以揭示控制土壤氮循环的新见解，特别是在氖提供的其他环境数据集的背景下，应该利用这些数据来改善土壤氮循环的预测建模。
Nitrogen (N) is a key limiting nutrient in terrestrial ecosystems, but there remain critical gaps in our ability to predict and model controls on soil N cycling. This may be in part due to lack of standardized sampling across broad spatial–temporal scales. Here, we introduce a continentally distributed, publicly available data set collected by the National Ecological Observatory Network (NEON) that can help fill these gaps. First, we detail the sampling design and methods used to collect and analyze soil inorganic N pool and net flux rate data from 47 terrestrial sites. We address methodological challenges in generating a standardized data set, even for a network using uniform protocols. Then, we evaluate sources of variation within the sampling design and compare measured net N mineralization to simulated fluxes from the Community Earth System Model 2 (CESM2). We observed wide spatiotemporal variation in inorganic N pool sizes and net transformation rates. Site explained the most variation in NEON’s stratified sampling design, followed by plots within sites. Organic horizons had larger pools and net N transformation rates than mineral horizons on a sample weight basis. The majority of sites showed some degree of seasonality in N dynamics, but overall these temporal patterns were not matched by CESM2, leading to poor correspondence between observed and modeled data. Looking forward, these data can reveal new insights into controls on soil N cycling, especially in the context of other environmental data sets provided by NEON, and should be leveraged to improve predictive modeling of the soil N cycle.