Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous Abstract"Determination of the effects of different washing processes on aroma characteristics in silver carp mince by MMSE-GC-MS, e-nose and sensory evaluation"    Next Abstract"Impact of emissions controls on ambient carbonyls during the Asia-Pacific Economic Cooperation summit in Beijing, China" »

Sci Total Environ


Title:Distinguishing the vegetation dynamics induced by anthropogenic factors using vegetation optical depth and AVHRR NDVI: A cross-border study on the Mongolian Plateau
Author(s):Zhou X; Yamaguchi Y; Arjasakusuma S;
Address:"Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan. Electronic address: zhouxiang.gis@hotmail.com. Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan"
Journal Title:Sci Total Environ
Year:2018
Volume:20171031
Issue:
Page Number:730 - 743
DOI: 10.1016/j.scitotenv.2017.10.253
ISSN/ISBN:1879-1026 (Electronic) 0048-9697 (Linking)
Abstract:"Distinguishing the vegetation dynamics induced by anthropogenic factors and identifying the major drivers can provide crucial information for designing actionable and practical countermeasures to restore degraded grassland ecosystems. Based on the residual trend (RESTREND) method, this study distinguished the vegetation dynamics induced by anthropogenic factors from the effects of climate variability on the Mongolian Plateau during 1993-2012 using vegetation optical depth (VOD) and normalized difference vegetation index (NDVI), which measure vegetation water content in aboveground biomass and chlorophyll abundance in canopy cover respectively; afterwards, the major drivers within different agricultural zones and socio-institutional periods were identified by integrating agricultural statistics with statistical analysis techniques. The results showed that grasslands in Mongolia and the grazing zone of Inner Mongolia Autonomous Region (IMAR), China underwent a significant human-induced decrease in aboveground biomass during 1993-2012 and 1993-2000 respectively, which was attributable to the rapid growth of livestock densities stimulated by livestock privatization and market factors; by contrast, grasslands in these two regions did not experience a concurrent human-induced reduction in canopy greenness. Besides, the results indicated that grasslands in the grazing zone of IMAR underwent a significant human-induced increase in aboveground biomass since 2000, which was attributable to the reduced grazing pressure induced by China's ecological restoration programs; concurrently, grasslands in this region also experienced a remarkable increase in canopy greenness, however, this increase was found not directly caused by the decreased stocking densities. Furthermore, the results revealed that the farming and semi-grazing/farming zone of IMAR underwent a significant human-induced increase in both aboveground biomass and canopy greenness since 2000, which was attributable to the intensified grain production stimulated by market factors, open grazing regulation and confined feeding popularization. These findings suggest that China's grassland restoration practice has important implications for Mongolia to reverse the severe and continuous grassland degradation in the future"
Keywords:Animals Biomass China Environmental Monitoring/methods/*standards *Grassland Herbivory Livestock Ecological restoration programs Grain yields Livestock populations Restrend The Mongolian Plateau Vegetation dynamics;
Notes:"MedlineZhou, Xiang Yamaguchi, Yasushi Arjasakusuma, Sanjiwana eng Netherlands 2017/11/05 Sci Total Environ. 2018 Mar; 616-617:730-743. doi: 10.1016/j.scitotenv.2017.10.253. Epub 2017 Oct 31"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 27-12-2024