خيارات البحث
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Do soil and water conservation practices influence crop productivity and household welfare? Evidence from rural Nigeria
2023
Ogunniyi, Adebayo Isaiah; Omotayo, Abiodun Olusola; Olagunju, Kehinde Oluseyi; Motunrayo, Olyeyemi; Awotide, Bola Amoke; Mavrotas, George; Oladapo, Adeyemi
PR | IFPRI3; ISI; CRP3.2; 4 Transforming Agricultural and Rural Economies | Development Strategies and Governance (DSG); Transformation Strategies | CGIAR Research Program on Maize (MAIZE)
اظهر المزيد [+] اقل [-]Impacts of extreme weather events on terrestrial carbon and nitrogen cycling : A global meta-analysis
2023
Qu, Qing | Xu, Hongwei | Ai, Zemin | Wang, Minggang | Wang, Guoliang | Liu, Guobin | Geissen, Violette | Ritsema, Coen J. | Xue, Sha
Some weather events like drought, increased precipitation, and warming exert substantial impact on the terrestrial C and N cycling. However, it remains largely unclear about the effect of extreme weather events (extreme drought, heavy rainfall, extreme heat, and extreme cold) on terrestrial C and N cycling. This study aims to analyze the responses of pools and fluxes of C and N in plants, soil, and microbes to extreme weather events by conducting a global meta-analysis of 656 pairwise observations. Results showed that extreme weather events (extreme drought, heavy rainfall, and extreme heat) decreased plant biomass and C flux, and extreme drought and heavy rainfall decreased the plant N pool and soil N flux. These results suggest that extreme weather events weaken the C and N cycling process in terrestrial ecosystems. However, this study did not determine the impact of extreme cold on ecosystem C and N cycling. Additional field experiments are needed to reveal the effects of extreme cold on global C and N cycling patterns.
اظهر المزيد [+] اقل [-]Variance-Based Fusion of VCI and TCI for Efficient Classification of Agriculture Drought Using Landsat Data in the High Atlas (Morocco, North Africa)
2023
Fathallah Fatima Ezzahra, Algouti Ahmed and Algouti Abdellah
Drought assessment using drought indices has been widely carried out for drought monitoring. Remote sensing-based indices use remotely sensed data to map drought conditions in a particular area or region. Therefore, the objective of the present study is to make a study on drought risk based on the calculation of an indicator from biophysical parameters extracted from NOAA/AVHRR satellite data, namely TCI and VCI, to obtain a better understanding of the differentiation between each index, and their application for drought monitoring in the High Atlas of Marrakech on the Chchaoua Morocco watershed during 1980-2020. Landsat oli7 and8 data were used to construct the indices. The result showed that each index proved to be a useful, fast, sufficient, and inexpensive tool for drought monitoring. However, each index has its differences. The TCI was found to be drought sensitive during the dry season or in months when high temperatures occurred. While VCI detected drought more sensitively in the rainy season as well (December-January-February to May) than TCI and VCI. Meanwhile, VCI, including the improved TCI, combined two indicators to better understand drought occurrence. These indices were calculated using GIS, QGis, ArcGis satellite imagery scenes, and Landsat. After a comparative study of these years, from 1984 to 2020, the evolution of the VCI and TCI was highlighted.
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