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Fire dynamics in Mato Grosso State, Brazil: the relative roles of gross primary productivity

机译：巴西Mato Grosso State的消防动力学：总初级生产力的相对角色

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摘要

The fires and biomass burning are responsible for affect ecosystem processes in a wide range of biomes at regional and global scales. In Brazil, the state of Mato Grosso is one of the most affected by the occurrence of forest fires. Thus, this study aims to quantify the long-term changes in the temporal and spatial patterns of fire occurrence and their effect on gross primary productivity (GPP) in the state of Mato Grosso, Brazil, considering the biomes that compose it. The images used in the study were acquired by satellite Terra and Aqua combined in the product MCD64A1.006, a monthly resolution of 500m by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, during the period from 01/10/2000 to 12/31/2018. The MOD17A2 product derived from the MODIS sensor provides the accumulated value of GPP. The points without the presence of burning presented higher values of GPP for all studied biomes. In some points with the presence of burning the GPP even decreased by 44.20%, 30.04% and 55.78% for Amazonia, Cerrado, and Pantanal, respectively. According to the results presented here, it is concluded that the burnings negatively impact gross primary production in the biomes of the state of Mato Grosso, Brazil and the dynamics of the burns do not keep up with the intensity of drought years. The use of cluster analysis techniques, such as principal component analysis (PCA), is an alternative to bigdata analysis when the objective is to evaluate the presence of forest burning in more than one biome.
机译：火灾和生物量燃烧负责影响区域和全球范围内各种生物群系的生态系统过程。在巴西，Mato Grosso的状态是受森林火灾发生的最大影响之一。因此，本研究旨在量化火灾发生的时间和空间模式的长期变化及其对巴西Mato Grosso状态的初级生产率（GPP）的影响，考虑到构成它的生物群体。该研究中使用的图像是由卫星Terra和Aqua组合在产品MCD64A1.006中，每月分辨率为500米的每月分辨率，在01/10/2000至12/31期间/ 2018。来自MODIS传感器的MOD17A2产品提供GPP的累计值。没有燃烧存在的点呈现出所有研究生物群的GPP的较高值。在某些方面，存在燃烧GPP的存在甚至减少了44.20％，分别为Amazonia，Cerrado和Pantanal的44.20％，30.04％和55.78％。根据此处提出的结果，得出结论是，燃烧对马托格罗索，巴西和烧伤的动态的生物群体产生负面的初级产量，不会跟上干旱年的强度。使用聚类分析技术，例如主成分分析（PCA），是当目标是在多于一个生物群系中燃烧的森林燃烧的存在时是BigData分析的替代方案。

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