Differences in background environment and fertilization method mediate plant response to nitrogen fertilization in alpine grasslands on the Qinghai-Tibetan Plateau

Shun He; Jianqing Du; Yanfen Wang; Lizhen Cui; Wenjing Liu; Yifan Xiao; Qinwei Ran; Linfeng Li; Zuopei Zhang; Li Tang; Ronghai Hu; Yanbin Hao; Xiaoyong Cui; Kai Xue

doi:10.1016/j.scitotenv.2023.167272

Differences in background environment and fertilization method mediate plant response to nitrogen fertilization in alpine grasslands on the Qinghai-Tibetan Plateau

Sci Total Environ. 2024 Jan 1:906:167272. doi: 10.1016/j.scitotenv.2023.167272. Epub 2023 Sep 28.

Authors

Shun He¹, Jianqing Du², Yanfen Wang³, Lizhen Cui¹, Wenjing Liu⁴, Yifan Xiao¹, Qinwei Ran¹, Linfeng Li⁴, Zuopei Zhang⁴, Li Tang⁴, Ronghai Hu², Yanbin Hao⁵, Xiaoyong Cui⁵, Kai Xue⁶

Affiliations

¹ College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
² College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China.
³ College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China; State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Chinese Academy of Sciences, Beijing 100101, China. Electronic address: yfwang@ucas.ac.cn.
⁴ College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
⁵ College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China.
⁶ College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China; Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China; Binzhou Institute of Technology, Weiqiao-UCAS Science and Technology Park, Binzhou 256606, China.

PMID: 37774870
DOI: 10.1016/j.scitotenv.2023.167272

Abstract

Grassland degradation threatens ecosystem function and livestock production, partly induced by soil nutrient deficiency due to the lack of nutrient return to soils, which is largely ascribed to the intense grazing activities. Therefore, nitrogen (N) fertilization has been widely adopted to restore degraded Qinghai-Tibetan Plateau (QTP) grasslands. Despite numerous field manipulation studies investigating its effects on alpine grasslands, the patterns and thresholds of plant response to N fertilization remain unclear, thus hindering the prediction of its influences on the regional scale. Here, we established a random forest model to predict N fertilization effects on plant productivity based on a meta-analysis synthesizing 88 publications in QTP grasslands. Our results showed that N fertilization increased the aboveground biomass (AGB) by 46.51 %, varying wildly among plant functional groups. The positive fertilization effects intensified when the N fertilization rate increased to 272 kg ha^-1 yr^-1, and decreased after three years of continuous fertilization. These effects were more substantial when applying ammonium nitrate compared to urea. Further, a machine learning model was used to predict plant productivity response to N fertilization. The total explained variance and mean squared residuals ranged from 49.41 to 75.13 % and 0.011-0.058, respectively, both being the highest for grasses. The crucial predictors were identified as climatic and geographic factors, background AGB without N fertilization, and fertilization methods (i.e., rate, form, and duration). These predictors with easy access contributed 62.47 % of the prediction power of grasses' response, thus enhancing the generalizability and replicability of our model. Notably, if 30 % of yak dung is returned to soils on the QTP, the grassland productivity and plant carbon pool are predicted to increase by 5.90-6.51 % and 9.35-10.31 g C m^-2 yr ^-1, respectively. Overall, the predictions of this study based on literature synthesis enhance our understanding of plant responses to N fertilization in QTP grasslands, thereby providing helpful information for grassland management policies. Conflict of interest: The authors declare no conflict of interest.

Keywords: Biomass; Machine learning; Plant productivity; Restoration; Threshold.

Publication types

Meta-Analysis

MeSH terms

Ecosystem*
Fertilization
Grassland*
Nitrogen / analysis
Plants / metabolism
Poaceae / physiology
Soil
Tibet

Substances

Nitrogen
Soil