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Full-Text Articles in Life Sciences

Methane Emissions From Global Rice Fields: Magnitude, Spatiotemporal Patterns, And Environmental Controls, Bowen Zhang, Hanqin Tian, Wei Ren, Bo Tao, Chaoqun Lu, Jia Yang, Kamaljit Banger, Shufen Pan Sep 2016

Methane Emissions From Global Rice Fields: Magnitude, Spatiotemporal Patterns, And Environmental Controls, Bowen Zhang, Hanqin Tian, Wei Ren, Bo Tao, Chaoqun Lu, Jia Yang, Kamaljit Banger, Shufen Pan

Plant and Soil Sciences Faculty Publications

Given the importance of the potential positive feedback between methane (CH4) emissions and climate change, it is critical to accurately estimate the magnitude and spatiotemporal patterns of CH4 emissions from global rice fields and better understand the underlying determinants governing the emissions. Here we used a coupled biogeochemical model in combination with satellite-derived contemporary inundation area to quantify the magnitude and spatiotemporal variation of CH4 emissions from global rice fields and attribute the environmental controls of CH4 emissions during 1901–2010. Our study estimated that CH4 emissions from global rice fields varied from 18.3 ± …


Mapping Temperate Vegetation Climate Adaptation Variability Using Normalized Land Surface Phenology, Liang Liang, Mark D. Schwartz, Xiaoyang Zhang Apr 2016

Mapping Temperate Vegetation Climate Adaptation Variability Using Normalized Land Surface Phenology, Liang Liang, Mark D. Schwartz, Xiaoyang Zhang

Geography Faculty Publications

Climate influences geographic differences of vegetation phenology through both contemporary and historical variability. The latter effect is embodied in vegetation heterogeneity underlain by spatially varied genotype and species compositions tied to climatic adaptation. Such long-term climatic effects are difficult to map and therefore often neglected in evaluating spatially explicit phenological responses to climate change. In this study we demonstrate a way to indirectly infer the portion of land surface phenology variation that is potentially contributed by underlying genotypic differences across space. The method undertaken normalized remotely sensed vegetation start-of-season (or greenup onset) with a cloned plants-based phenological model. As the …