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首页> 外文期刊>Ecosystems >Determination of Aboveground Net Primary Productivity and Plant Traits in Grasslands with Near-Infrared Reflectance Spectroscopy
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Determination of Aboveground Net Primary Productivity and Plant Traits in Grasslands with Near-Infrared Reflectance Spectroscopy

机译：用近红外反射光谱法测定草原地上净初级生产力和植物性状

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摘要

Proposed links between biodiversity and ecosystem processes have generated intense interest in the linkage between aboveground net primary productivity (ANPP) and soil C storage. Quantity and quality of ANPP largely depend on plant functional groups and management practices. In a context of environmental change (that is, land-use and climate) long-term studies of ANPP and functional groups are gaining interest. However, rapid determination of ANPP and functional groups are often limited in time and money, resulting in less than ideal sampling schemes and replications. Near-infrared reflectance spectroscopy (NIRS) can relieve constraints of labor intensive hand-sorting by providing quick, non-destructive, and quantitative analyses of a range of organic constituents (for example, plant tissues). Here, we investigated the potential of a NIRS method to rapidly predict harvested green aboveground biomass, the proportion of dead material, and simple functional plant traits, necessary to determine ANPP and related ecosystem properties. The issue was investigated for two independent grassland experiments of contrasted long-term field management (high vs. low grazing and N fertilization). Our results show that NIRS analyses are well suited to determine ANPP (12 and 19% error of prediction) and simple plant traits (error 9%) of contrasted treatment of two independent multi-species grasslands. Moreover, we show that calibration may be simplified when compared to commonly used protocols, which offers ecologists enormous analytical power.
机译：提议的生物多样性与生态系统过程之间的联系引起了人们对地上净初级生产力（ANPP）与土壤碳储存之间联系的强烈兴趣。 ANPP的数量和质量在很大程度上取决于工厂的职能部门和管理实践。在环境变化（即土地利用和气候）的背景下，对ANPP和功能组的长期研究越来越引起人们的兴趣。但是，快速确定ANPP和官能团通常受时间和金钱的限制，从而导致采样方案和复制方法不理想。近红外反射光谱（NIRS）通过对一系列有机成分（例如植物组织）进行快速，无损和定量分析，可以减轻劳动密集型人工分拣的限制。在这里，我们研究了NIRS方法快速预测收获的绿色地上生物量，枯死物质的比例以及简单的植物功能性状（确定ANPP和相关生态系统特性所必需）的潜力。在两个独立的对比长期田间管理（高放牧与低放牧和氮肥）的草原实验中研究了该问题。我们的结果表明，NIRS分析非常适合确定两个独立的多物种草地的对比处理的ANPP（预测误差为12％和19％）和简单植物性状（误差为9％）。此外，我们显示，与常用协议相比，校准可能会简化，这为生态学家提供了巨大的分析能力。

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