极端气候对陕西植被生产力时空变化的影响

doi:10.11755/j.issn.1006-7639-2026-03-0470

摘要/Abstract

摘要：

分析极端气候条件对植被生产力的影响机理，对区域适应和减缓气候变化影响具有重要意义。基于植被总初级生产力（Gross Primary Productivity，GPP）数据与同期极端气候指数，使用二维Copula联合分析、一元线性回归法和Pearson相关系数法等，分析极端气候指数对陕西不同区域、不同植被类型GPP的影响差异。结果表明：1）1981—2018年，全省97.9%的区域植被GPP呈增加趋势，固碳能力稳步提升，其中陕北地区植被GPP增长率最高；2）不同区域植被GPP对极端气候的空间响应存在明显差异，极端低温与极端干旱对陕北和关中地区植被GPP存在显著抑制作用，极端高温和极端降水对陕南地区植被GPP的促进效应突出；3）月尺度是极端气候影响植被生产力的关键时间窗口，其影响强度远高于年和生长季尺度；4）不同极端气候条件对森林、草地、农田GPP的影响呈现明显的植被特异性与季节动态性。

关键词: 极端气候指数, GPP, 植被类型, 响应特征

Abstract:

Analyzing the mechanism of the impact of extreme climatic conditions on vegetation productivity is of great significance for regional adaptation and the mitigation of the effects of climate change. Based on the Gross Primary Productivity (GPP) data of vegetation and the extreme climate indices of the same period, two-dimensional Copula joint analysis, the univariate linear regression method and Pearson correlation coefficient method, etc. were used to analyze the differences in the influence of four extreme climate indices on the GPP of different regions and different vegetation types in Shaanxi Province. The results show that: 1) From 1981 to 2018, 97.9% of the province’s vegetation GPP showed an increasing trend, indicating a steady improvement in carbon sequestration capacity, with the highest GPP growth rate observed in northern Shaanxi. 2) The spatial response of vegetation GPP to extreme climates showed remarkable spatial heterogeneity. Extremely low temperature and extreme drought strongly suppressed GPP in northern Shaanxi and Guanzhong regions, whereas extremely high temperature and extreme precipitation significantly had a prominent promoting effect on vegetation GPP in southern Shaanxi. 3) The monthly scale was the critical time window for the impact of extreme climate on vegetation productivity, and its influence intensity was much greater than that at the annual and growing season scales. 4) The effects of different extreme climate events on GPP of forest, grassland, and cropland exhibited clear vegetation specificity and seasonal dynamics.

Key words: extreme climate indices, GPP, vegetation type, response characteristics

中图分类号:

P46
Q148

王娟敏, 孙娴, 植石群, 程路, 刘爱君. 极端气候对陕西植被生产力时空变化的影响[J]. 干旱气象, 2026, 44(3): 470-478.

WANG Juanmin, SUN Xian, ZHI Shiqun, CHENG Lu, LIU Aijun. Impact of extreme climate on the spatiotemporal changes of vegetation productivity in Shaanxi Province[J]. Journal of Arid Meteorology, 2026, 44(3): 470-478.

图/表 8

参考文献 28

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指数名称	类别	定义
极端高温指数	最高高温	日最高气温的年（月）最大值
极端低温指数	最低低温	日最低气温的年（月）最小值
极端降水指数	年（月）降水总量	年（月）全部日降水量的总和
极端干旱指数	最大干旱持续时长	日降水量<1 mm的最大连续天数

指数名称	类别	定义
极端高温指数	最高高温	日最高气温的年（月）最大值
极端低温指数	最低低温	日最低气温的年（月）最小值
极端降水指数	年（月）降水总量	年（月）全部日降水量的总和
极端干旱指数	最大干旱持续时长	日降水量<1 mm的最大连续天数

变化趋势区间/（gC·m^-2·a^-1）	变化等级	面积占比/%
[-0.5，0]	略有变差	2.1
（0，0.1]	轻微好转	30.4
（0.1，0.6]	明显好转	67.5

变化趋势区间/（gC·m^-2·a^-1）	变化等级	面积占比/%
[-0.5，0]	略有变差	2.1
（0，0.1]	轻微好转	30.4
（0.1，0.6]	明显好转	67.5

极端气候指数	陕北			关中			陕南			全省
极端气候指数	正相关	负相关	p<0.05	正相关	负相关	p<0.05	正相关	负相关	p<0.05	正相关	负相关	p<0.05
极端高温指数	71.4	28.6	27.8	51.5	48.5	36.2	75.6	24.4	33.5	63.9	37.1	38.7
极端低温指数	31.7	68.3	49.9	26.5	73.5	52.3	51.3	49.7	56.7	35.5	64.5	62.3
极端降水指数	42.7	57.3	54.7	78.5	21.5	59.5	87.3	12.7	52.4	76.9	33.1	58.6
极端干旱指数	11.4	88.6	63.2	26.9	73.1	68.2	43.9	56.1	65.3	33.9	67.1	61.2