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Estimation and Climate Factor Contribution of Aboveground Biomass in Inner Mongolia’s Typical/Desert Steppes

Author

Listed:
  • Xiumei Wang

    (Ministry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau & Inner Mongolia Key Laboratory of Grassland Ecology, School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, China
    School of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010051, China
    These authors contributed equally to this work and should be considered co-first authors.)

  • Jianjun Dong

    (Ministry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau & Inner Mongolia Key Laboratory of Grassland Ecology, School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, China
    These authors contributed equally to this work and should be considered co-first authors.)

  • Taogetao Baoyin

    (Ministry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau & Inner Mongolia Key Laboratory of Grassland Ecology, School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, China)

  • Yuhai Bao

    (School of Geography Science, Inner Mongolia Normal University, Hohhot 010022, China)

Abstract

Grassland biomass is an essential part of the regional carbon cycle. Rapid and accurate estimation of grassland biomass is a hot topic in research on grassland ecosystems. This study was based on field-measured biomass data and satellite remote sensing data from the Moderate resolution imaging spectroradiometer (MODIS). A generalized linear model (GLM) was used to analyze the aboveground biomass (AGB), dynamic changes, and relevance of climatic factors of the typical/desert steppe in Inner Mongolia during the growing seasons from May 2009 to October 2015. The results showed that: (1) The logarithmic function model with the ratio vegetation index (RVI) as the independent variable worked best for the typical steppe area in Inner Mongolia, while the power function model with the normalized differential vegetation index (NDVI) as the independent variable worked best for the desert steppe area. The R 2 values at a spatial resolution of 250 m were higher than those at a spatial resolution 500 m. (2) From 2009 to 2015, the highest values of AGB in the typical steppe and desert steppe of Inner Mongolia both appeared in 2012, and were 41.9 Tg and 7.0 Tg, respectively. The lowest values were 30.7 Tg and 5.8 Tg, respectively, in 2009. (3) The overall spatial distribution of AGB decreased from northeast to southwest. It also changed considerably over time. From May to August, AGB at the same longitude increased from south to north with seasonal variations; from August to October, it increased from north to south. (4) A variation partitioning analysis showed that in both the typical steppe and desert steppe, the combined effect of precipitation and temperature contributed the most to the aboveground biomass. The individual effect of temperature contributed more than precipitation in the typical steppe, while the individual effect of precipitation contributed more in the desert steppe. Thus, the hydrothermal dynamic hypothesis was used to explain this pattern. This study provides support for grassland husbandry management and carbon storage assessment in Inner Mongolia.

Suggested Citation

  • Xiumei Wang & Jianjun Dong & Taogetao Baoyin & Yuhai Bao, 2019. "Estimation and Climate Factor Contribution of Aboveground Biomass in Inner Mongolia’s Typical/Desert Steppes," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:23:p:6559-:d:289132
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    References listed on IDEAS

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    1. Yongfei Bai & Xingguo Han & Jianguo Wu & Zuozhong Chen & Linghao Li, 2004. "Ecosystem stability and compensatory effects in the Inner Mongolia grassland," Nature, Nature, vol. 431(7005), pages 181-184, September.
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    3. Anna, Petrenko, . "Мaркування готової продукції як складова частина інформаційного забезпечення маркетингової діяльності підприємств овочепродуктового підкомплексу," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 2(01).
    4. Xie, Yichun & Sha, Zongyao & Yu, Mei & Bai, Yongfei & Zhang, Lei, 2009. "A comparison of two models with Landsat data for estimating above ground grassland biomass in Inner Mongolia, China," Ecological Modelling, Elsevier, vol. 220(15), pages 1810-1818.
    5. Camille Parmesan & Gary Yohe, 2003. "A globally coherent fingerprint of climate change impacts across natural systems," Nature, Nature, vol. 421(6918), pages 37-42, January.
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    1. Gongxin Wang & Changqing Jing & Ping Dong & Baoya Qin & Yang Cheng, 2022. "Spatiotemporal Dynamics of Aboveground Biomass and Its Influencing Factors in Xinjiang’s Desert Grasslands," Sustainability, MDPI, vol. 14(22), pages 1-20, November.

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