Spatiotemporal dynamics and driving mechanisms of grassland biomass in China from 2000 to 2022

IF 5.7 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology Pub Date : 2025-09-06 DOI:10.1016/j.agrformet.2025.110833

Shuai Wang , Xinshan Ma , Yan Yue , Tao Zhou , Zhihan Yang , Benjamin Laffitte , Songyu Fu , Xiaolu Tang

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引用次数: 0

Abstract

Grassland biomass is a key indicator for assessing the health and productivity of grassland ecosystems. Over the past two decades, China’s grasslands have undergone substantial changes. However, accurately estimating grassland biomass and its response to driving factors remains challenging. In this study, we predicted the spatiotemporal patterns of aboveground and belowground biomass (AGB and BGB) and examined their driving mechanisms at a 500 m resolution from 2000 to 2022, using a modified multi-layer perceptron (MLP) neural network combined with 2233 AGB and 1093 BGB observations, along with environmental variables across China. The MLP model demonstrated strong predictive performance for AGB (R² = 0.79, RMSE = 20.02 g C m⁻² yr⁻¹) and BGB (R² = 0.87, RMSE = 223.65 g C m⁻² yr⁻¹). Spatially, average AGB decreased from southeastern to northwest China, while BGB was highest along the eastern edge of the Qinghai-Tibet Plateau. Temporally, AGB increased by 1.27 Tg C yr⁻¹ over the past 23 years, covering 68.19 % of grassland areas, whereas BGB showed no significant trend. Projections indicate that AGB will increase in 48.6 % and BGB in 34.81 % of grassland areas in the future. Total AGB and BGB were estimated at 163.5 and 1044.5 Tg C, respectively. Temperature and precipitation were the primary drivers of both AGB (23.47 % and 20.21 % of grassland areas) and BGB (25.24 % and 21.05 %). For AGB, the remaining drivers, in descending order of influence, were vegetation, human activity intensity, soil physical properties, soil chemical properties, and terrain. For BGB, they were human activity intensity, followed by vegetation, soil physical properties, soil chemical properties, and terrain. This study offers critical insights for grassland biomass dynamics and their driving mechanisms, providing a scientific foundation for policy-making and adaptive management to ensure the long-term resilience of grassland ecosystems.

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2000 - 2022年中国草地生物量时空动态及驱动机制

草地生物量是评价草地生态系统健康和生产力的重要指标。在过去的二十年里，中国的草原发生了巨大的变化。然而，准确估算草地生物量及其对驱动因子的响应仍然具有挑战性。本文利用改进的多层感知器（MLP）神经网络，结合2233个AGB和1093个BGB观测数据，结合环境变量，在500 m分辨率下预测了2000 - 2022年中国地上和地下生物量（AGB和BGB）的时空格局，并探讨了其驱动机制。MLP模型对AGB （R2 = 0.79, RMSE = 20.02 g C m−2 yr−1）和BGB （R2 = 0.87, RMSE = 223.65 g C m−2 yr−1）具有较强的预测性能。从时间上看，23 a来AGB增加了1.27 Tg C yr - 1，覆盖了68.19%的草地面积，而BGB变化趋势不显著。预测表明，未来草地AGB将增加48.6%，BGB将增加34.81%。总AGB和BGB分别为163.5 Tg C和1044.5 Tg C。温度和降水分别是草地面积的23.47%和20.21%和25.24%和21.05%的主要驱动因素。其余影响因素依次为植被、人类活动强度、土壤物理性质、土壤化学性质和地形。BGB大小依次为人类活动强度、植被、土壤物理性质、土壤化学性质和地形。该研究为草地生物量动态及其驱动机制提供了重要见解，为制定政策和适应性管理提供了科学依据，以确保草地生态系统的长期恢复力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Agricultural and Forest Meteorology 农林科学-林学

CiteScore

10.30

自引率

9.70%

发文量

415

审稿时长

69 days

期刊介绍： Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published. Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.