A roadmap for sampling and scaling biological nitrogen fixation in terrestrial ecosystems
A roadmap for sampling and scaling biological nitrogen fixation in terrestrial ecosystems
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DOI：
10.1111/2041-210x.13586
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发表时间：
2021-03
影响因子：
6.6
通讯作者：
F. Soper;B. Taylor;Joy B. Winbourne;M. Wong;Katherine A. Dynarski;C. R. Reis;M. Peoples;C. Cleveland;S. Reed;D. Menge;S. Perakis
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文献类型：
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作者：
F. Soper;B. Taylor;Joy B. Winbourne;M. Wong;Katherine A. Dynarski;C. R. Reis;M. Peoples;C. Cleveland;S. Reed;D. Menge;S. Perakis
准确定量陆地生态系统生物固氮（BNF）的速率和模式对于表征生态和地球化学相互作用、识别机制控制、提高BNF在概念和数值模拟中的代表性以及预测未来碳（C）循环的氮限制约束至关重要。虽然许多资料涉及衡量生物固氮的不同方法的技术优势和局限性，但对规划研究、解释数据和推断结果所涉及的更广泛的决策考虑较少。在这里，我们提出了一个概念和实际的路线图，研究设计，研究执行，数据分析和缩放，概述了每个步骤的关键考虑因素。我们解决的问题包括定义感兴趣的N固定生态位，确定时间和空间异质性的重要来源，设计抽样方案（包括方法选择，测量条件，复制，以及考虑热点和热点时刻），以及分析，缩放和报告BNF的方法。我们还回顾了文献中使用不同方法得出的估计值的可比性，并提供了用于模拟共生BNF数据帧和升级的样本R代码。在每个阶段改进和标准化研究设计将提高数据的准确性和可解释性，确定外推的限度，并促进下游应用中更广泛地使用生物固氮数据。我们强调的方面，如量化尺度的异质性，处理非正态性的统计方法，并考虑率与生态意义，是成熟的进一步发展。
Accurately quantifying rates and patterns of biological nitrogen fixation (BNF) in terrestrial ecosystems is essential to characterize ecological and biogeochemical interactions, identify mechanistic controls, improve BNF representation in conceptual and numerical modelling, and forecast nitrogen limitation constraints on future carbon (C) cycling. While many resources address the technical advantages and limitations of different methods for measuring BNF, less systematic consideration has been given to the broader decisions involved in planning studies, interpreting data, and extrapolating results. Here, we present a conceptual and practical road map to study design, study execution, data analysis and scaling, outlining key considerations at each step. We address issues including defining N‐fixing niches of interest, identifying important sources of temporal and spatial heterogeneity, designing a sampling scheme (including method selection, measurement conditions, replication, and consideration of hotspots and hot moments), and approaches to analysing, scaling and reporting BNF. We also review the comparability of estimates derived using different approaches in the literature, and provide sample R code for simulating symbiotic BNF data frames and upscaling. Improving and standardizing study design at each of these stages will improve the accuracy and interpretability of data, define limits of extrapolation, and facilitate broader use of BNF data for downstream applications. We highlight aspects—such as quantifying scales of heterogeneity, statistical approaches for dealing with non‐normality, and consideration of rates versus ecological significance—that are ripe for further development.