基于陆地生态系统过程模型多尺度数据同化的青藏高原地区净生态系统生产力时空模拟

IF 5.6 1区 农林科学 Q1 AGRONOMY
Changhui Ma , Si-Bo Duan , Cong Xu , Wenhua Qin , Feng Wang , Lei He
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引用次数: 0

摘要

准确阐明青藏高原草原净生态系统生产力(NEP)的时空格局,对于理解草原碳循环对气候和放牧的反馈机制具有重要意义。陆地生态系统过程模型数据同化参数定位是准确模拟新生态环境的主要方法。然而,目前的研究以草地类型来标定生态系统过程模型,忽略了同一类型内模型参数的空间变异。因此,校准后的模型难以描述空间多样性的生态机制。因此,我们提出了CENTURY模式的多尺度参数化方案,描述如下。(1)利用涡动相关(EC)站的NEP观测资料,根据草地类型对模式参数进行校正。(2)将草地类型-尺度模型迁移到禁牧区内的离散像元,并在逐像元的基础上同化遥感NPP数据,对空间散度和灵敏度较强的模型参数进行微调;(3)利用集成学习算法构建环境因子驱动的离散参数空间插值模型。结果表明,与以往的参数化方案相比,标定后的CENTURY模型具有更高的空间泛化性能。具体而言,所有EC站NEP模拟的RMSE (R2)从10.18 g C m2 mo-1(0.58)降至7.58 g C m2 mo-1(0.72)。采用CENTURY模型在Selinco地区生成了1980 - 2020年不同放牧强度情景下的草地NEP时空数据集。从时空分析中得出以下结论:(1)在不同的放牧情景下,几乎所有草原都具有碳汇功能,净碳汇呈显著的年增长趋势。(2)年净汇随海拔高度显著降低。(3)由于高寒草甸固碳能力强,高寒草原分布广泛,高寒草甸和高寒草原是碳固碳的主要贡献者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatio-temporal simulation of net ecosystem productivity in the Tibetan Plateau region using multi-scale data assimilation for terrestrial ecosystem process model
Accurately elucidating the spatio-temporal pattern of net ecosystem productivity (NEP) in grasslands on the Tibetan Plateau (TP) is essential for understanding the feedback mechanisms of the carbon cycle to climate and grazing. Parameter localization through data assimilation for terrestrial ecosystem process model is the dominant approach to accurately simulate NEP. However, current studies calibrate ecosystem process model by grassland types, neglecting the spatial variation of model parameters within the same type. Consequently, the calibrated model struggles to characterize the spatially diverse ecological mechanisms. Therefore, we propose a multi-scale parameterization scheme for the CENTURY model, described as follows. (1) Calibrate model parameters in terms of grassland type by assimilating NEP observations from eddy covariance (EC) stations. (2) Migrate the grassland type-scale model to discrete pixels within prohibited pastures, then fine-tune the model parameters with strong spatial divergence and sensitivity by assimilating remotely sensed NPP data on a per-pixel basis; (3) Use ensemble learning algorithms to construct spatial interpolation models driven by environmental factors for discrete parameters. The results confirmed that the calibrated CENTURY model has higher spatial generalization performance compared to model calibrated using previous parameterization scheme. Specifically, the RMSE (R2) for NEP simulations at all EC stations was reduced from 10.18 g C m2 mo-1 (0.58) to 7.58 g C m2 mo-1 (0.72). The CENTURY model was employed in the Selinco region to generate spatio-temporal datasets of grassland NEP from 1980 to 2020, incorporating various grazing intensity scenarios. The following conclusions were drawn from the spatio-temporal analyses. (1) Regardless of grazing scenarios, almost all grasslands functioned as carbon sinks, exhibiting a significant annual increase of net sinks. (2) The annual net sink decreased significantly with altitude. (3) Alpine meadows and alpine steppe were the main contributors to carbon sequestration because alpine meadows have high sequestration capacity and alpine steppe are widely distributed.
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来源期刊
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.
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