| 青藏高原草地地上生物量和理论载畜量 |
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| 引用本文： | 张宪洲,李猛,武建双,何永涛,牛犇.青藏高原草地地上生物量和理论载畜量[J].资源与生态学报（英文版）,2022,13(1):129-141. |
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| 作者姓名： | 张宪洲 李猛 武建双 何永涛 牛犇 |
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| 作者单位： | 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室拉萨高原生态试验站;中国科学院大学资源与环境学院;南通大学地理科学学院;中国农业科学院农业环境与可持续发展研究所 |
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| 基金项目： | The Second Tibetan Plateau Scientific Expedition and Research Program (STEP)(2019QZKK1002);The National Natural Sciences Foundation of China (41807331);The West Light Foundation of the Chinese Academy of Sciences (2018)。 |
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| 摘 要： | 准确模拟和预测草地地上生物量(Aboveground biomass,AGB)和理论载畜量对于维持草地生态系统平衡、优化放牧管理至关重要。当前很多研究以围栏外草地AGB为基础,估算了青藏高原草地AGB的现存量。但是,牛羊啃食后的草地AGB现存量无法准确评估草地理论载畜量。围栏内草地不受家畜采食影响,其年际变率由环境因子驱动,可视为草地潜在AGB (potential AGB,AGBp),更适用于草地理论载畜量的评估。本研究以青藏高原345个围栏内AGB观测数据为基础,结合气候、土壤和地形数据,利用随机森林算法构建草地潜在地上生物量估算模型,并对当前气候条件(2000-2018年)和未来20年(2021-2040年)4种气候变化情景(SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5)下的草地AGBp和高寒草地理论载畜量进行模拟与预测。结果表明:(1)随机森林算法可准确模拟当前气候条件下的青藏高寒草地AGBp(R2=0.76,P<0.001);2000-2018年青藏高寒草地AGBp平均值为102.4 g m-2,时间上增加趋势不明显(P>0.05);AGBp年际波动和生长季降水显著正相关(R2=0.57,P<0.001),和生长季温度日较差显著负相关(R2=0.51,P<0.001)。(2)当前气候条件下,青藏高寒草地平均理论载畜量为0.94 SSU ha-1(standardized sheep unit ha-1);在过去20年约有54.1%草地理论载畜量呈提升状态。(3)和当前相比,未来20年青藏高原中部和北部草地AGBp和理论载畜量呈下降态势。因此,建议未来在厘清气候变化影响下草畜关系的基础上进行有针对性的草牧业规划和管理,以缓解区域气候变化引起的草畜矛盾。
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| 关 键 词： | 高寒草地 承载力 地上生物量 气候变化 随机森林 青藏高原 |
| 收稿时间： | 2021-09-13 |
Alpine Grassland Aboveground Biomass and Theoretical Livestock Carrying Capacity on the Tibetan Plateau |
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| ZHANG Xianzhou,LI Meng,WU Jianshuang,HE Yongtao,NIU.Alpine Grassland Aboveground Biomass and Theoretical Livestock Carrying Capacity on the Tibetan Plateau[J].Journal of Resources and Ecology,2022,13(1):129-141. |
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| Authors: | ZHANG Xianzhou LI Meng WU Jianshuang HE Yongtao NIU |
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| Institution: | (Lhasa Plateau Ecosystem Research Station,Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences andNatural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100190,China;School of Geographic Sciences,Nantong University,Nantong,Jiangsu 226007,China;Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agricultural Sciences,Beijing 100081,China) |
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| Abstract: | The accurate simulation and prediction of grassland aboveground biomass (AGB) and theoretical livestock carrying capacity are key steps for maintaining ecosystem balance and sustainable grassland management. The AGB in fenced grassland is not affected by grazing and its variability is only driven by climate change, which can be regarded as the grassland potential AGB (AGBp). In this study, we compiled the data for 345 AGB field observations in fenced grasslands and their corresponding climate data, soil data, and topographical data on the Qinghai-Tibetan Plateau (TP). We further simulated and predicted grassland AGBp and theoretical livestock carrying capacity under the climate conditions of the past (2000-2018) and future two decades (2021-2040) based on a random forest (RF) algorithm. The results showed that simulated AGBp matched well with observed values in the field (R2 = 0.76, P < 0.001) in the past two decades. The average grassland AGBp on the Tibetan Plateau was 102.4 g m-2, and the inter-annual changes in AGBp during this period showed a non-significant increasing trend. AGBp fluctuation was positively correlated with growing season precipitation (R2 = 0.57, P < 0.001), and negatively correlated with the growing season diurnal temperature range (R2 = 0.51, P < 0.001). The average theoretical livestock carrying capacity was 0.94 standardized sheep units (SSU) ha-1 on the TP, in which about 54.1% of the areas showed an increasing trend during the past two decades. Compared with the past two decades, the theoretical livestock carrying capacity showed a decreasing trend in the future, which was mainly distributed in the central and northern TP. This study suggested that targeted planning and management should be carried out to alleviate the forage-livestock contradiction in grazing systems on the Tibetan Plateau. |
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| Keywords: | alpine grassland aboveground biomass carrying capacity climate change random forest Tibetan Plateau |
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