Characterization of a Highly Biodiverse Floodplain Meadow Using Hyperspectral Remote Sensing within a Plant Functional Trait Framework
Characterization of a Highly Biodiverse Floodplain Meadow Using Hyperspectral Remote Sensing within a Plant Functional Trait Framework
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DOI：
10.3390/rs8020112
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发表时间：
2016-02
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影响因子：
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通讯作者：
S. Punalekar;A. Verhoef;I. Tatarenko;C. Tol;D. Macdonald;B. Marchant;F. Gerard;K. White;D. Gowing
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文献类型：
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作者：
S. Punalekar;A. Verhoef;I. Tatarenko;C. Tol;D. Macdonald;B. Marchant;F. Gerard;K. White;D. Gowing
我们评估了利用光学功能类型作为有效标记来监测与当地环境变化相关的洪泛平原草甸植被变化的潜力。洪泛区草甸具有高度的生物多样性，对生态系统的监测和保护具有挑战性。我们的目的是了解和解释洪泛平原草甸主要成员之间的光谱差异，并表征其功能特征的差异。本研究在英国一个典型的洪泛平原草甸上进行（根据英国国家植被分类，mg4型，中营养草地4型）。我们比较了两种利用场光谱表征洪泛区群落的方法。第一种方法是基于亚群落的，我们收集了表明两种不同生态水文条件（干土壤和湿土壤指示物种）的物种分组的光谱特征。另一种方法是“物种特异性”，我们专注于在草地上发现的三个关键物种的光谱反射率。其中一种草本植物是MG4河漫滩草甸群落的典型成员，而另外两种植物莎草和灯尾草则代表湿地植被。我们还监测了植被的生物物理和功能特性，以及土壤养分和地下水位。我们发现，代表草甸亚群落的植被类别无法相互区分，而单个草本物种与莎草和灯心草物种具有明显不同的光谱特征。这三种植物的光谱差异可以通过观测到的植物生物物理参数的差异来解释，这一点通过辐射转移模型模拟得到了证实。叶面积指数、叶干物质含量、叶含水量和比叶面积等参数，以及最大羧基化能力和叶片氮含量等功能参数，也有助于解释不同物种在功能动态上的差异。地下水水位和土壤氮有效性是控制植物营养状况的重要因素，在草本植物/湿地物种的位置上也存在显著差异。该研究的结论是，光谱可区分的物种，在高度生物多样性的地点（如洪泛平原草甸）中是典型的，可能被用作监测变化环境条件下植被动态的目标物种。
We assessed the potential for using optical functional types as effective markers to monitor changes in vegetation in floodplain meadows associated with changes in their local environment. Floodplain meadows are challenging ecosystems for monitoring and conservation because of their highly biodiverse nature. Our aim was to understand and explain spectral differences among key members of floodplain meadows and also characterize differences with respect to functional traits. The study was conducted on a typical floodplain meadow in UK (MG4-type, mesotrophic grassland type 4, according to British National Vegetation Classification). We compared two approaches to characterize floodplain communities using field spectroscopy. The first approach was sub-community based, in which we collected spectral signatures for species groupings indicating two distinct eco-hydrological conditions (dry and wet soil indicator species). The other approach was “species-specific”, in which we focused on the spectral reflectance of three key species found on the meadow. One herb species is a typical member of the MG4 floodplain meadow community, while the other two species, sedge and rush, represent wetland vegetation. We also monitored vegetation biophysical and functional properties as well as soil nutrients and ground water levels. We found that the vegetation classes representing meadow sub-communities could not be spectrally distinguished from each other, whereas the individual herb species was found to have a distinctly different spectral signature from the sedge and rush species. The spectral differences between these three species could be explained by their observed differences in plant biophysical parameters, as corroborated through radiative transfer model simulations. These parameters, such as leaf area index, leaf dry matter content, leaf water content, and specific leaf area, along with other functional parameters, such as maximum carboxylation capacity and leaf nitrogen content, also helped explain the species’ differences in functional dynamics. Groundwater level and soil nitrogen availability, which are important factors governing plant nutrient status, were also found to be significantly different for the herb/wetland species’ locations. The study concludes that spectrally distinguishable species, typical for a highly biodiverse site such as a floodplain meadow, could potentially be used as target species to monitor vegetation dynamics under changing environmental conditions.