Dynamics of net primary productivity on the Mongolian Plateau: Joint regulations of phenology and drought

Bao, Gang; Chen, Jiquan; Chopping, Mark; Bao, Yuhai; Bayarsaikhan, Sainbuyan; Dorjsuren, Altanchimeg; Tuya, Alateng; Jirigala, Buren; Qin, Zhihao

doi:10.1016/j.jag.2019.05.009

Cited by 56 publications

(51 citation statements)

References 55 publications

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“…The trends in both the SOS and EOS of the whole region appeared to weakly advance during 1982-2015. These results are consistent with previous studies on the changes of phenology in the Mongolian region [52,53]. Through piecewise linear regression on the different regions of change for SOS and EOS, we found that a dramatic trend for grassland phenology emerged around 1997, while there was no obvious trend previously observed.…”

Section: Phenology Spatial Pattern and Changessupporting

confidence: 92%

“…Therefore, we further examined the relationship between meteorological factors and SOS. Considering that summer NPP accounts for more than 70% of the annual NPP, while the spring and autumn NPPs account for the remaining proportions [52,60], we checked the relationship between the climate factor and SOS in June, July, August, and September. Notably, the pixels where the SOS significantly positively correlated with precipitation and negatively correlated with temperature in the summer months (June, July, and August) were generally consistent with the pixels where the SOS correlated with NPP ( Figure 8).…”

Section: Npp Response To Phenologymentioning

confidence: 99%

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Monitoring Phenology in the Temperate Grasslands of China from 1982 to 2015 and Its Relation to Net Primary Productivity

Zhang

Wang

et al. 2019

Sustainability

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Both vegetation phenology and net primary productivity (NPP) are crucial topics under the background of global change, but the relationships between them are far from clear. In this study, we quantified the spatial-temporal vegetation start (SOS), end (EOS), and length (LOS) of the growing season and NPP for the temperate grasslands of China based on a 34-year time-series (1982–2015) normalized difference vegetation index (NDVI) derived from global inventory modeling and mapping studies (GIMMS) and meteorological data. Then, we demonstrated the relationships between NPP and phenology dynamics. The results showed that more than half of the grasslands experienced significant changes in their phenology and NPP. The rates of their changes exhibited spatial heterogeneity, but their phenological changes could be roughly divided into three different clustered trend regions, while NPP presented a polarized pattern that increased in the south and decreased in the north. Different trend zones’ analyses revealed that phenology trends accelerated after 1997, which was a turning point. Prolonged LOS did not necessarily increase the current year’s NPP. SOS correlated with the NPP most closely during the same year compared to EOS and LOS. Delayed SOS contributed to increasing the summer NPP, and vice versa. Thus, SOS could be a predictor for current year grass growth. In view of this result, we suggest that future studies should further explore the mechanisms of SOS and plant growth.

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Section: Phenology Spatial Pattern and Changessupporting

confidence: 92%

Section: Npp Response To Phenologymentioning

confidence: 99%

Monitoring Phenology in the Temperate Grasslands of China from 1982 to 2015 and Its Relation to Net Primary Productivity

Zhang

Wang

et al. 2019

Sustainability

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“…Our results confirm that previous studies reported a significant and positive correlation between inter-annual variation of precipitation and NPP at site level studies [57,58]. In this study area, grass grows rapidly in summer when it is hot and rains at the same time, so that NPP in summer was approximately 60% proportionate in the current year, meanwhile that showed a strong relationship with the current season precipitation [59] (Figure 2). This means that precipitation from June to August is essential for grass growth.…”

Section: Response Of Grassland Npp To Climate Changesupporting

confidence: 91%

“…Field harvest measurement was widely used to model validation [27,59,65]. In general, the field biomass measurements that represented NPP depends on the number of samples and the homogeneity of field vegetation.…”

Section: Uncertaintymentioning

confidence: 99%

Grassland Productivity Response to Climate Change in the Hulunbuir Steppes of China

Zhang

2019

Sustainability

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As global climate change deeply affects terrestrial ecosystem carbon cycle, it is necessary to understand how grasslands respond to climate change. In this study, we examined the role of climate change on net primary productivity (NPP) from 1961 to 2010 in the Hulunbuir grasslands of China, using a calibrated process-based biogeochemistry model. The results indicated that: Temperature experienced a rise trend from 1961; summer and autumn precipitation showed a rise trend before the 1990s and decline trend after the 1990s. Winter and spring precipitation showed an ascending trend. Simulated NPP had a high inter-annual variability during the study period, ranging from 139 g Cm−2 to 348 g Cm−2. The annual mean NPP was significant and positive in correlation with the annual variation of precipitation, and the trend was first raised then fell with the turn point at the 1990s. Temperature had a 20–30 d lag in summer, but none in spring and autumn; precipitation had a 10–20 d lag in summer. The climate lag effect analysis confirmed that temperature had a positive effect on NPP in spring and a negative effect in summer.

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“…Here, previously calculated εmax value (Bao et al 2016b), values calculated for three major zones in Inner Mongolia (meadow steppe, steppe and desert-steppe), values for other categories and values identified by researchers, including Zhu and others (Zhu et al 2006) (Table 1). Mongolia has four seasons, when the plant growth period lasts in April-October; this has been taken into account for selection of growth period (Bao et al 2019).…”

Section: The Casa Modelmentioning

confidence: 99%

Variations of Vegetation Net Primary Productivity and Its Responses to Climate Change From 1982 to 2015 in Mongolia

Bayarsaikhan

Mandakh

Dorjsuren

et al. 2020

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Climate warming in Mongolia is relatively high, with extreme dry climate, and low precipitation, the input of green vegetation on the ecosystem functioning is relatively high. The impacts of climate change are critically affected to desertification, biodiversity loses, decreases of water sources, land degradation of rangeland in Mongolia. In order to better adapt to such changing climate, it is important to understand the long terms vegetation dynamics and its relation with precipitation. In this study, the third-generation GIMMS NDVI data of NOAA satellites and CASA model with metrological data have been used to estimate NPP between 1982 and 2015 throughout Mongolia. Results show that during 34 years mean NPP seems to have decreased greatly from semi-arid in the North to desert in the South across natural zone in Mongolia. The average NPP value was averaged at 166.1 g C/m2 and ranged between 19 and 724.85 g C/m2 for the terrain land. 60% of total NPP was relating to annual precipitation about R2 = 0.78 (p = 0.000). Total amount of NPP between 1982 and 2015 was estimated to be 0.32 Pg C/year and 0.29 Pg C/year in 1982 and 2015, respectively, with an average amount of NPP was 0.32 Pg (1 Pg = 1015 g) for 34 years. These results indicate that during most of vegetation growing season, NPP decreased by 0.03 Pg С/year. Field measurement data of 2007, 2009, 2014 and 2015 were used for correlation with the NPP estimation. As a result, R2 = 0.742 (p < 0.001) in 2007 for forest steppe, R2 = 0.74 (p < 0.001) in 2009 for meadow steppe and grassy steppe, R2 = 0.73 (p < 0.001) in 2014 for meadow steppe, R2 = 0.715 (p < 0.001) in 2015 for a desert steppe, respectively. The results obtained in this study contributes to understanding productivity of pasturelands of semi-arid ecosystems of Mongolia and Central Asia. By providing insights on the relationship between pasture productivity and climate variables such as precipitation and temperature, this study could be useful for national and regional scale climate change adaptation strategies.

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Dynamics of net primary productivity on the Mongolian Plateau: Joint regulations of phenology and drought

Cited by 56 publications

References 55 publications

Monitoring Phenology in the Temperate Grasslands of China from 1982 to 2015 and Its Relation to Net Primary Productivity

Monitoring Phenology in the Temperate Grasslands of China from 1982 to 2015 and Its Relation to Net Primary Productivity

Grassland Productivity Response to Climate Change in the Hulunbuir Steppes of China

Variations of Vegetation Net Primary Productivity and Its Responses to Climate Change From 1982 to 2015 in Mongolia

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