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首页> 外文期刊>Ecosystems >A Benchmark Test for Ecohydrological Models of Interannual Variability of NDVI in Semi-arid Tropical Grasslands
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A Benchmark Test for Ecohydrological Models of Interannual Variability of NDVI in Semi-arid Tropical Grasslands

机译：半干旱热带草原NDVI年际变化的生态水文模型基准测试

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Pulses of aboveground net primary productivity (ANPP) in response to discrete precipitation events are an integral feature of ecosystem functioning in arid and semi-arid lands. Yet, the usefulness of nonlinear, ecohydrological pulse response functions to predict regional-scale patterns of annual ANPP at decadal scales remains unclear. Here, we assessed how different pulse response (PR) models compete with simple linear statistical models to capture variability in yearly integrated values of Normalized Difference Vegetation Index (NDVIint), a remotely sensed proxy of annual ANPP. We examined 24-year-long time series of NDVIint calculated from Advanced Very High Resolution Radiometer (AVHRR) NDVI for 350,000 km2 of tropical grasslands in northern Australia. Based on goodness-of-fit statistics, PR models clearly outperformed statistical models when parameters were optimized for each site but all models showed the same error magnitude when all sites were combined in ensemble simulations or when the models were evaluated outside the calibration period. PR models were less biased and their performance did not deteriorate in the driest areas compared to linear models. Increasing the complexity of PR models to provide a better representation of soil water balance and its feedback with plant growth did not improve model performance in ensemble simulations. When error magnitude, bias, and sensitivity to parameter uncertainty were all considered, we concluded that a low-dimensional PR model was the most robust to capture NDVIint variability. This study shows the potential of long time series of AVHRR NDVI to benchmark process-oriented models of interannual variability of NDVIint in water-controlled ecosystems. This opens new avenues to examine at the global scale and over several decades the causal relationships between climate and leaf dynamics in the grassland biome.
机译：响应离散降水事件的地上净初级生产力的脉冲是干旱和半干旱地区生态系统功能的一个整体特征。然而，非线性，生态水文脉冲响应函数在十年尺度上预测年度ANPP的区域尺度格局的有用性仍不清楚。在这里，我们评估了不同的脉冲响应（PR）模型如何与简单的线性统计模型竞争，以捕获归一化植被指数（NDVI int ）（年度ANPP的遥感代理）的年度累计值中的变异性。我们检查了根据先进超高分辨率辐射计（AVHRR）NDVI计算的24年的NDVI int 时间序列，该序列用于澳大利亚北部热带草原的350,000 km 2 。基于拟合优度统计，当针对每个站点优化参数时，PR模型明显胜过统计模型，但是当将所有站点组合在一起进行集成仿真或在校准周期之外评估模型时，所有模型都显示出相同的误差幅度。与线性模型相比，PR模型的偏见较少，在最干燥的地区其性能也不会降低。增加PR模型的复杂性以更好地表示土壤水分平衡及其对植物生长的反馈并不能改善集成模拟中的模型性能。当综合考虑误差幅度，偏差和对参数不确定性的敏感性时，我们得出结论，低维PR模型是捕获NDVI int 变异性最强的模型。这项研究表明，AVHRR NDVI的长期序列有潜力成为水调控生态系统中NDVI int 年际变化的面向过程的基准模型。这开辟了新的途径，可以在全球范围内以及几十年间研究草原生物群落中气候与叶片动态之间的因果关系。

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