基于Biome-BGC模型的亚热带典型森林NPP动态模拟及气候响应

doi:10.13292/j.1000-4890.202504.019

生态学杂志 ›› 2025, Vol. 44 ›› Issue (4): 1284-1296.doi: 10.13292/j.1000-4890.202504.019

基于Biome-BGC模型的亚热带典型森林NPP动态模拟及气候响应

黄云^1,2,胡方清^1,2,3,郑博福^1,2,宋旭^1,2,徐黎亮^1,2,朱锦奇^1,2,万炜^1,2*

（¹南昌大学资源与环境学院，鄱阳湖环境与资源利用教育部重点实验室，南昌 330031； ²南昌大学江西生态文明研究院，南昌 330031； ³江西省生态环境科学研究与规划院，污染防治江西省重点实验室，南昌 330039）

出版日期:2025-04-10 发布日期:2025-04-14

Simulation of NPP dynamics and climate response of typical subtropical forest types based on Biome-BGC modeling.

HUANG Yun^1,2, HU Fangqing^1,2,3, ZHENG Bofu^1,2, SONG Xu^1,2, XU Liliang^1,2, ZHU Jinqi^1,2, WAN Wei^1,2*

(¹School of Resources and Environment, Key Laboratory of Poyang Lake Environment and Resource Utilization, Ministry of Education, Nanchang 330031, China; ²Nanchang University, Jiangxi Institute of Ecological Civilization, Nanchang 330031, China; ³Jiangxi Academy of Eco-Environmental Sciences & Planning, Jiangxi Key Laboratory of Environmental Pollution Control, Nanchang 330039, China).

Online:2025-04-10 Published:2025-04-14

摘要/Abstract

摘要： 净初级生产力（NPP）是评价森林生态系统碳收支状况的重要指标，精确评估森林NPP变化以应对气候变化有着重要意义。以江西省修河流域为研究区，基于参数本地化后的BiomeBGC模型模拟了1960—2021年6种亚热带典型森林NPP动态变化，并结合温度、降水及气候变化情景分析了森林NPP对温度、降水的响应。结果表明：（1）1960—2021年，修河流域不同森林类型的NPP由高到低依次为：竹林（655.20 g C·m^-2·a^-1）>常绿针叶林（629.42 g C·m^-2·a^-1）>常绿阔叶林（600.01 g C·m^-2·a^-1）>常绿针阔混交林（596.98 g C·m^-2·a^-1）>落叶阔叶林（325.20 g C·m^-2·a^-1）>灌木林（266.43 g C·m^-2·a^-1）。（2）6种典型森林NPP的月际变化表明，落叶阔叶林NPP呈单峰变化并在8月份达到最高值，其他森林NPP均在8月份降至峰谷并呈双峰趋势。除落叶阔叶林和灌木林以外，其他森林NPP在7—9月与温度大多呈极显著负相关性，而与降水呈正相关，表明夏季温度升高、降水减少极大影响了植被生长。（3）从气象因子的拟合强度来看，NPP对温度的响应强度大于降水，温度与竹林NPP及落叶阔叶林NPP的拟合较强（R²>0.46; P<0.01）；而降水与常绿针叶林、竹林、灌木林及阔叶落叶林NPP都是较弱的拟合关系（R²<0.21; P<0.01）。（4）未来气候情景中，适当升温有助于促进植被的生长，但升温超过阈值后NPP将受到抑制；在降水情景中，NPP与降水呈正相关性。NPP对温度的响应幅度远大于降水，且温度和降水的组合变化情景的拟合优度高于单一变化情景。

关键词: Biome-BGC模型, 气候变化, 森林类型, 净初级生产力, 修河流域

Abstract:

Net primary productivity (NPP) is an important index to evaluate the carbon budget of forest ecosystems. It is of great significance to accurately assess the changes of forest NPP to cope with climate change. Based on the Biome-BGC model with localized parameters, we simulated the dynamics of NPP in six typical subtropical forests in Xiuhe River Basin of Jiangxi Province during 1960-2021, and analyzed the responses of forest NPP to temperature and precipitation under different climate scenarios. The results showed that: (1) From 1960 to 2021, the NPP of different forest types was in order of bamboo forest (655.20 g C·m^-2·a^-1) > evergreen coniferous forest (629.42 g C·m^-2·a^-1) > evergreen broad-leaved forest (600.01 g C·m^-2·a^-1) > evergreen coniferous and broad-leaved mixed forest (596.98 g C·m^-2·a^-1) > deciduous broad-leaved forest (325.20 g C·m^-2·a^-1) > shrub (266.43 g C·m^-2·a^-1). (2) As for the inter-monthly variation of NPP, deciduous broad-leaved forest showed a unimodal trend and reached the highest value in August, while other forests decreased to a bimodal trend in August. Except for deciduous broad-leaved forest and shrub forest, the NPP of forests showed a significant negative correlation with temperature from July to September, but a positive correlation with precipitation, indicating that increased temperature and decreased precipitation in summer greatly affected vegetation growth. (3) According to the fitting strength of meteorological factors, the response strength of NPP to temperature was greater than that of precipitation, and the fitting strength of temperature to NPP of bamboo forest and deciduous broad-leaved forest was stronger (R²>0.46; P<0.01). The correlation between precipitation and NPP in evergreen coniferous forest, bamboo forest, shrub forest and broad-leaved deciduous forest was relatively weak (R²<0.21; P<0.01). (4) In the future climate scenario, appropriate temperature increase is helpful to promote vegetation growth, but NPP will be inhibited when temperature increase exceeds the threshold. In the precipitation scenario, NPP is positively correlated with precipitation. The response range of NPP to temperature is much greater than that of precipitation, and the effect of the combination of temperature and precipitation is stronger than that of the single change scenario.

Key words: Biome-BGC model, climate change, forest type, net primary productivity, Xiuhe River Basin

黄云, 胡方清, 郑博福, 宋旭, 徐黎亮, 朱锦奇, 万炜. 基于Biome-BGC模型的亚热带典型森林NPP动态模拟及气候响应[J]. 生态学杂志, 2025, 44(4): 1284-1296.

HUANG Yun, HU Fangqing, ZHENG Bofu, SONG Xu, XU Liliang, ZHU Jinqi, WAN Wei. Simulation of NPP dynamics and climate response of typical subtropical forest types based on Biome-BGC modeling.[J]. Chinese Journal of Ecology, 2025, 44(4): 1284-1296.

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基于Biome-BGC模型的亚热带典型森林NPP动态模拟及气候响应

Simulation of NPP dynamics and climate response of typical subtropical forest types based on Biome-BGC modeling.

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