Analyzing vegetation dynamic trend on the Mongolian Plateau based on the Hurst exponent and influencing factors from 1982–2013

Tong, Siqin; Zhang, Jiquan; Bao, Yuhai; Lai, Quan; Xiao, Lian; Li, Na; Bao, Yu

doi:10.1007/s11442-018-1493-x

Cited by 93 publications

(73 citation statements)

References 32 publications

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“…The NDVI is also very sensitive to the physical characteristics of vegetation: sensor observation angles, solar radiation, and different soil backgrounds [13,14]. Several vegetation properties, such as the length of the growing season, onset date of greenness, and date of maximum photosynthetic activity, can be derived from the NDVI time series to monitor vegetation changes [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Impacts of Climate on Spatiotemporal Variations in Vegetation NDVI from 1982–2015 in Inner Mongolia, China

et al. 2019

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By using the Global Inventory Modeling and Mapping Studies (GIMMS) third-generation normalized difference vegetation index (NDVI3g) data, this paper explores the spatiotemporal variations in vegetation and their relationship with temperature and precipitation between 1982 and 2015 in the Inner Mongolia region of China. Based on yearly scale data, the vegetation changes in Inner Mongolia have experienced three stages from 1982 to 2015: the vegetation activity kept a continuous improvement from 1982–1999, then downward between 1999–2009, and upward from 2009 to 2015. On the whole, the general trend is increasing. Several areas even witnessed significant vegetation increases: in the east and south of Tongliao and Chifeng, north of Xing’anmeng, north and west of Hulunbir, and in the west of Inner Mongolia. Based on monthly scale data, one-year and half-year cycles exist in normalized difference vegetation index (NDVI) and temperature but only a one-year cycle in precipitation. Finally, based on the one-year cycle, the relationship between NDVI and climatic were studied; NDVI has a significant positive correlation with temperature and precipitation, and temperature has a greater effect in promoting vegetation growth than precipitation. Moreover, based on a half-year changing period, NDVI is only affected by temperature in the study region. Those findings can serve as a critical reference for grassland managers or policy makers to make informed decisions on grassland management.

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Section: Introductionmentioning

confidence: 99%

Impacts of Climate on Spatiotemporal Variations in Vegetation NDVI from 1982–2015 in Inner Mongolia, China

et al. 2019

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“…As mentioned above, the state of vegetation in this region is not only related to local ecosystem services and human welfare, but also has an important impact on the environment in northern China. Previous studies have used line regression methods to investigate vegetation variations and related effects of climate and anthropogenic activity [8,36]. However, limitations in the vegetation change trend detection method have hindered our ability to investigate the drivers of vegetation variations [37,38].…”

Section: Introductionmentioning

confidence: 99%

Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method

Xue

Zhang

et al. 2019

Remote Sensing

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Vegetation is the major component of the terrestrial ecosystem. Understanding both climate change and anthropogenically induced vegetation variation is essential for ecosystem management. In this study, we used an ensemble empirical mode decomposition (EEMD) method and a linear regression model to investigate spatiotemporal variations in the normalized difference vegetation index (NDVI) over the agropastoral ecotone of northern China (APENC) during the 1982–2015 period. A quantitative approach was proposed based on the residual trend (RESTREND) method to distinguish the effects of climatic (i.e., temperature (TEM), precipitation (PRE), total downward solar radiation (RAD), and near surface wind speed (SWS)) and anthropogenic effects on vegetation variations. The results showed that the NDVI exhibited a significant greening trend of 0.002 year−1 over the entire study period of 1982–2015 and that areas with monotonous greening dominated the entire APENC, occupying 40.97% of the region. A browning trend was also found in the central and northern parts of the APENC. PRE presented the highest spatial correlation with the NDVI and climate factors, suggesting that PRE was the most important factor affecting NDVI changes in the study area. In addition, the RESTREND results indicated that anthropogenic contributions dominated the vegetation variations in the APENC. Therefore, reusing farmland for grass and tree planting made a positive contribution to vegetation restoration, while deforestation, overgrazing, and the reclamation of grasslands were the opposite. In addition, with the continuous implementation of national ecological engineering programs such as the Grain to Green Program, positive human activity contributions to vegetation greening significantly increased. These results will support decision- and policy-making in the assessment and rehabilitation of ecosystems in the study region.

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“…However, the proposed R/S analysis, with the Hurst exponent, was unable to determine how long the anticipated trend would continue into the future. Thus, it is important for future research to focus on extending the time span for which future forest pest dynamics can be forecasted [66].…”

Section: Future Trends Consistency On Drought and Pine Caterpillar Omentioning

confidence: 99%

Effect of Drought on Outbreaks of Major Forest Pests, Pine Caterpillars (Dendrolimus spp.), in Shandong Province, China

Bao

Zhang

Tong

et al. 2019

Forests

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As the main defoliators of coniferous forests in Shandong Province, China, pine caterpillars (including Dendrolimus suffuscus suffuscus Lajonquiere, D. spectabilis Butler, and D. tabulaeformis Tsai et Liu) have caused substantial forest damage, adverse economic impacts, and losses of ecosystem resources. Therefore, elucidating the effects of drought on the outbreak of these pests is important for promoting forestry production and ecological reconstruction. Accordingly, the aim of the present study was to analyse the spatiotemporal variation of drought in Shandong Province, using the Standard Precipitation Index, and to investigate the impact of drought on the outbreak of pine caterpillar infestations. Future trends in drought and pine caterpillar populations were then estimated using the Hurst exponent. The results showed that: (1) Drought decreased gradually and showed a wetting trend from 1981 to 2012, with frequency decreasing on a decadal scale as follows: 1980s > 1990s > 2000s > 2010s; (2) The total area of pine caterpillar occurrence decreased strongly from 1992 to 2012; (3) Long-term or prolonged drought had a greater positive impact on pine caterpillar outbreak than short-term drought; (4) In the future, a greater portion of the province’s area will experience increased wetting conditions (57%) than increased drought (43%), and the area of pine caterpillar outbreak is estimated to decrease overall. These findings help elucidate the relationship between drought and pine caterpillar outbreak in Shandong Province and, hence, provide a basis for developing preventive measures and plans.

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Analyzing vegetation dynamic trend on the Mongolian Plateau based on the Hurst exponent and influencing factors from 1982–2013

Cited by 93 publications

References 32 publications

Impacts of Climate on Spatiotemporal Variations in Vegetation NDVI from 1982–2015 in Inner Mongolia, China

Impacts of Climate on Spatiotemporal Variations in Vegetation NDVI from 1982–2015 in Inner Mongolia, China

Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method

Effect of Drought on Outbreaks of Major Forest Pests, Pine Caterpillars (Dendrolimus spp.), in Shandong Province, China

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