Invasive acacias differ from native dune species in the hyperspectral/biochemical trait space
Invasive acacias differ from native dune species in the hyperspectral/biochemical trait space
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DOI：
10.1111/jvs.12608
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发表时间：
2018-03-01
影响因子：
2.8
通讯作者：
Werner, Christiane
中科院分区：
文献类型：
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作者：
Grosse-Stoltenberg, Andre;Hellmann, Christine;Werner, Christiane
目的：入侵物种的影响可能取决于其功能性状相对于本地社区的差异。因此，在多维空间中比较物种性状有助于更好地了解入侵者的影响，但需要新的方法来有效地测量不同植物群落的多种性状。主要目的是以全群落方法基于田间光谱评估生化叶片参数。我们的具体目标是评估（1）植物群落内的生化分化，（2）生化参数光谱预测模型的准确性，（3）利用野外光谱描述多变量分化的能力。地点：地中海沙丘生态系统，大西洋海岸，葡萄牙西南部。我们分析了18个物种（包括两种入侵的阿卡西亚斯）的叶子生物量，包括C、delta C-13、N、delta N-15、木质素、纤维和单宁。此外，我们收集了叶和冠层场光谱的每一个采样植物。我们使用偏最小二乘（PLS）回归预测生化参数从现场光谱。此外，我们评估的生化分化的物种使用PCA湿化学测定的基础上，以及spectroscopically预测values.Results：我们发现物种之间的高生化变化，特别是入侵相思属之间的显着性状相异。和本地物种，主要是相对于N含量。基于场光谱成功地预测了生化参数。预测精度特别高，与C，δ C-13，N和单宁。生化参数的主成分分析表明，入侵相思属。与同一生活型的本地种不同，但与本地矮灌木聚在一起。这种模式是准确再现的PCA使用光谱预测值。与类似生长形式的本地物种相比，具有不同的叶特征。它们的特性差异可能加剧了它们对生态系统的影响。这种性状的差异，叶生化可以准确地预测高光谱全群落模型。因此，现场光谱可以大大提高测量的空间和时间分辨率，从而促进生态系统功能和入侵者的影响在生态系统尺度上的评估。
Aim: The impact of invasive species may depend on dissimilarity of their functional traits relative to the native community. Therefore, comparing species traits in a multidimensional space can help to better understand invader impacts, but novel methods are needed to effectively measure multiple traits across diverse plant communities. The main aim was to assess biochemical leaf parameters based on field spectra in a whole-community approach. Our specific objectives were to assess (1) biochemical differentiation within the plant community, (2) accuracy of spectroscopic prediction models of biochemical parameters, and (3) ability to depict the multivariate differentiation using field spectroscopy.Location: Mediterranean dune ecosystems, Atlantic coast, southwest Portugal.Methods: We analysed leaf biomass of 18 species, including two invasive acacias, for C, delta C-13, N, delta N-15, lignin, fibre and tannin. Additionally, we collected leaf and canopy field spectra of each sampled plant. We used partial least squares (PLS) regression to predict biochemical parameters from field spectra. Further, we assessed the biochemical differentiation of the species using PCA based on wet chemically determined as well as spectroscopically predicted values.Results: We found high biochemical variation among species and, in particular, marked trait dissimilarity between invasive Acacia spp. and native species, primarily with respect to N content. Biochemical parameters were predicted successfully based on field spectra. Prediction accuracies were particularly high with C, delta C-13, N and tannin. A PCA of biochemical parameters showed that invasive Acacia spp. were distinct from native species of the same life form, but grouped with native dwarf shrubs. This pattern was accurately reproduced by a PCA using spectroscopically predicted values.Conclusions: Invasive Acacia spp. have different leaf traits compared to native species of similar growth form. Their trait dissimilarity likely exacerbates their impacts on the ecosystem. This trait dissimilarity in leaf biochemistry can be accurately predicted with hyperspectral whole-community models. Thus, field spectroscopy can substantially increase the spatial and temporal resolution of measurements and hence facilitate assessments of ecosystem functioning and invader impacts at ecosystem scale.