Modeling responses of the meadow steppe dominated by Leymus chinensis to climate change

This study compared the arbuscular mycorrhizal symbiosis of Leymus chinensis between meadow steppe and typical steppe in the West Ujimqin banner. Mycorrhizal colonization rate and number of rhizosphere spore of L. chinensis decreased from light to heavy grassland degradation in the both of steppes. The mycorrhizal colonization rate and rhizosphere spore number of L. chinensis decreased significantly at moderate-heavy degradation stages in meadow steppe, and the typical steppe occurred in light-moderate degradation stages. These results indicated that the mycorrhizal symbiotic patience of L. chinensis in typical steppe is lower than that of meadow steppe.

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Simulating the spatiotemporal variations in aboveground biomass in Inner Mongolian grasslands under environmental changes

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-3059-2021 ◽

2021 ◽

Vol 21 (4) ◽

pp. 3059-3071

Author(s):

Guocheng Wang ◽

Zhongkui Luo ◽

Yao Huang ◽

Wenjuan Sun ◽

Yurong Wei ◽

...

Keyword(s):

Climate Change ◽

Aboveground Biomass ◽

Large Scale ◽

Environmental Changes ◽

Regional Scale ◽

Future Climate Change ◽

Desert Steppe ◽

Meadow Steppe ◽

Grassland Type ◽

Spatiotemporal Changes

Abstract. Grassland aboveground biomass (AGB) is a critical component of the global carbon cycle and reflects ecosystem productivity. Although it is widely acknowledged that dynamics of grassland biomass is significantly regulated by climate change, in situ evidence at meaningfully large spatiotemporal scales is limited. Here, we combine biomass measurements from six long-term (> 30 years) experiments and data in existing literatures to explore the spatiotemporal changes in AGB in Inner Mongolian temperate grasslands. We show that, on average, annual AGB over the past 4 decades is 2561, 1496 and 835 kg ha−1, respectively, in meadow steppe, typical steppe and desert steppe in Inner Mongolia. The spatiotemporal changes of AGB are regulated by interactions of climatic attributes, edaphic properties, grassland type and livestock. Using a machine-learning-based approach, we map annual AGB (from 1981 to 2100) across the Inner Mongolian grasslands at the spatial resolution of 1 km. We find that on the regional scale, meadow steppe has the highest annual AGB, followed by typical and desert steppe. Future climate change characterized mainly by warming could lead to a general decrease in grassland AGB. Under climate change, on average, compared with the historical AGB (i.e. average of 1981–2019), the AGB at the end of this century (i.e. average of 2080–2100) would decrease by 14 % under Representative Concentration Pathway (RCP) 4.5 and 28 % under RCP8.5. If the carbon dioxide (CO2) enrichment effect on AGB is considered, however, the estimated decreases in future AGB can be reversed due to the growing atmospheric CO2 concentrations under both RCP4.5 and RCP8.5. The projected changes in AGB show large spatial and temporal disparities across different grassland types and RCP scenarios. Our study demonstrates the accuracy of predictions in AGB using a modelling approach driven by several readily obtainable environmental variables and provides new data at a large scale and fine resolution extrapolated from field measurements.

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Drought sensitivity of aboveground productivity in Leymus chinensis meadow steppe depends on drought timing

Oecologia ◽

10.1007/s00442-019-04506-w ◽

2019 ◽

Vol 191 (3) ◽

pp. 685-696 ◽

Cited By ~ 3

Author(s):

Bo Meng ◽

Baoku Shi ◽

Shangzhi Zhong ◽

Hua Chai ◽

Shuixiu Li ◽

...

Keyword(s):

Leymus Chinensis ◽

Meadow Steppe ◽

Drought Sensitivity ◽

Aboveground Productivity

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Response of nutrient resorption of Leymus chinensis to nitrogen and phosphorus addition in a meadow steppe of northeast China

Plant Biology ◽

10.1111/plb.13153 ◽

2020 ◽

Vol 22 (6) ◽

pp. 1123-1132

Author(s):

B. Shi ◽

X. Ling ◽

H. Cui ◽

W. Song ◽

Y. Gao ◽

...

Keyword(s):

Northeast China ◽

Nutrient Resorption ◽

Leymus Chinensis ◽

Meadow Steppe ◽

Nitrogen And Phosphorus ◽

Phosphorus Addition

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Ecology of meadow steppe in northeast China

The Rangeland Journal ◽

10.1071/rj08005 ◽

2008 ◽

Vol 30 (2) ◽

pp. 247 ◽

Cited By ~ 54

Author(s):

D. Wang ◽

L. Ba

Keyword(s):

Climate Change ◽

Past Research ◽

Grassland Management ◽

Future Research ◽

Meadow Steppe ◽

Ecological Processes ◽

Plant Adaptation ◽

North East ◽

Vegetation Production ◽

Plant Animal Interactions

Native grassland in China is mostly meadow, typical or desert steppe and comprises 400 million hectares, ~40% of the land area. We review past research on the meadow steppe of north-east China. Our foci are plant adaptation to climate, edaphic-related and defoliation stresses, vegetation production, grassland management, herbivore foraging behaviour, safe stocking rates, plant-animal interactions, ecosystem functioning, conservation of biodiversity and the influence of climate change on grassland function. Recent studies have provided some insights into ecological processes and functioning of meadow steppe, and have enabled better identification of research opportunities. Key areas identified for future research include plant adaptation, grassland function and value, monitoring of range health, ecological consequences of climate change on biodiversity and ecosystem function.

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Moderately prolonged dry intervals between precipitation events promote production in Leymus chinensis in a semi-arid grassland of Northeast China

BMC Plant Biology ◽

10.1186/s12870-021-02920-y ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jinwei Zhang ◽

Xiangjin Shen ◽

Bifan Mu ◽

Yujie Shi ◽

Yuheng Yang ◽

...

Keyword(s):

Climate Change ◽

Soil Moisture ◽

Biomass Production ◽

Soil Nitrogen ◽

Precipitation Amount ◽

Leymus Chinensis ◽

N Content ◽

Grassland Productivity ◽

Semi Arid ◽

Precipitation Events

Abstract Background Climate change is predicted to lead to changes in the amount and distribution of precipitation during the growing seasonal. This “repackaging” of rainfall could be particularly important for grassland productivity. Here, we designed a two-factor full factorial experiment (three levels of precipitation amount and six levels of dry intervals) to investigate the effect of precipitation patterns on biomass production in Leymus chinensis (Trin.) Tzvel. (a dominant species in the Eastern Eurasian Steppe). Results Our results showed that increased amounts of rainfall with prolonged dry intervals promoted biomass production in L. chinensis by increasing soil moisture, except for the longest dry interval (21 days). However, prolonged dry intervals with increased amount of precipitation per event decreased the available soil nitrogen content, especially the soil NO3−-N content. For small with more frequent rainfall events pattern, L. chinensis biomass decreased due to smaller plant size (plant height) and fewer ramets. Under large quantities of rain falling during a few events, the reduction in biomass was not only affected by decreasing plant individual size and lower ramet number but also by withering of aboveground parts, which resulted from both lower soil water content and lower NO3−-N content. Conclusion Our study suggests that prolonged dry intervals between rainfall combined with large precipitation events will dramatically change grassland productivity in the future. For certain combinations of prolonged dry intervals and increased amounts of intervening rainfall, semi-arid grassland productivity may improve. However, this rainfall pattern may accelerate the loss of available soil nitrogen. Under extremely prolonged dry intervals, the periods between precipitation events exceeded the soil moisture recharge interval, the available soil moisture became fully depleted, and plant growth ceased. This implies that changes in the seasonal distribution of rainfall due to climate change could have a major impact on grassland productivity.

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Phenology Response to Climatic Dynamic across China’s Grasslands from 1985 to 2010

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi7080290 ◽

2018 ◽

Vol 7 (8) ◽

pp. 290 ◽

Cited By ~ 3

Author(s):

Jun Wang ◽

Tiancai Zhou ◽

Peihao Peng

Keyword(s):

Climate Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Climatic Factors ◽

Growing Season ◽

Northern China ◽

Plant Phenology ◽

Meadow Steppe ◽

Typical Steppe ◽

Alpine Steppe

Because the dynamics of phenology in response to climate change may be diverse in different grasslands, quantifying how climate change influences plant growth in different grasslands across northern China should be particularly informative. In this study, we explored the spatiotemporal variation of the phenology (start of the growing season [SOS], peak of the growing season [POS], end of the growing season [EOS], and length of the growing season [LOS]) across China’s grasslands using a dataset of the GIMMS3g normalized difference vegetation index (NDVI, 1985–2010), and determined the effects of the annual mean temperature (AMT) and annual mean precipitation (AMP) on the significantly changed phenology. We found that the SOS, POS, and EOS advanced at the rates of 0.54 days/year, 0.64 days/year, and 0.65 days/year, respectively; the LOS was shortened at a rate of 0.62 days/year across China’s grasslands. Additionally, the AMT combined with the AMP explained the different rates (ER) for the significantly dynamic SOS in the meadow steppe (R2 = 0.26, p = 0.007, ER = 12.65%) and typical steppe (R2 = 0.28, p = 0.005, ER = 32.52%); the EOS in the alpine steppe (R2 = 0.16, p < 0.05, ER = 6.22%); and the LOS in the alpine (R2 = 0.20, p < 0.05, ER = 6.06%), meadow (R2 = 0.18, p < 0.05, ER = 16.69%) and typical (R2 = 0.18, p < 0.05, ER = 19.58%) steppes. Our findings demonstrated that the plant phenology in different grasslands presented discrepant dynamic patterns, highlighting the fact that climate change has played an important role in the variation of the plant phenology across China’s grasslands, and suggested that the variation and relationships between the climatic factors and phenology in different grasslands should be explored further in the future.

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VARIATIONS OF VEGETATION NET PRIMARY PRODUCTIVITY AND ITS RESPONSES TO CLIMATE CHANGE FROM 1982 TO 2015 IN MONGOLIA

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-v-3-2020-347-2020 ◽

2020 ◽

Vol V-3-2020 ◽

pp. 347-353

Author(s):

S. Bayarsaikhan ◽

U. Mandakh ◽

A. Dorjsuren ◽

B. Batsaikhan ◽

Y. Bao ◽

...

Keyword(s):

Climate Change ◽

Net Primary Productivity ◽

Regional Scale ◽

Measurement Data ◽

Arid Ecosystems ◽

Forest Steppe ◽

Meadow Steppe ◽

The North ◽

Green Vegetation ◽

Semi Arid

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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