海河流域生态系统净初级生产力对气象干旱的响应与弹性

doi:10.17521/cjpe.2023.0076

摘要/Abstract

摘要： 干旱强度和频率上升严重威胁陆地生态系统结构和功能。为保证未来逆境下生态系统服务功能的正常发挥, 生态系统生产力对气象干旱响应与弹性的时空特征亟待探究。本研究以海河流域2001-2018年标准化降水蒸散指数(SPEI)度量气象干旱, 基于流域自然植被净初级生产力(NPP), 分析NPP与SPEI的数量关系, 评估自然植被的干旱风险及植被在干旱后呈现的弹性。结果显示: (1)海河流域自然植被NPP和归一化植被指数(NDVI)在研究期内均呈显著上升趋势; (2)植被NPP对干旱响应的滞后时间呈草原、稀树草原<落叶阔叶林、多树草原<落叶-常绿混交林、郁闭灌丛; (3)干旱致灾风险则呈现草原>郁闭灌丛>多树草原>落叶阔叶林>稀树草原>落叶-常绿混交林; (4)干旱后流域75%以上植被NPP明显偏低不超过1个月, 弹性较强; 森林类植被的弹性强于灌草类, 二者年内变化趋势相反, 年际均呈增长趋势; NPP响应和弹性特征随植被类型和干旱强度而变。基于植被干旱风险和弹性调整造林还草措施, 优化植被结构, 提升物种多样性, 可提高流域生态系统的稳定性。

关键词: 气象干旱, 干旱风险, 弹性, 净初级生产力, 标准化降水蒸散指数(SPEI)

Abstract:

Aims The increases in drought intensity and frequency severely threaten structure and functioning of terrestrial ecosystems. To ensure the normal functioning of ecosystems under such scenarios, it is critically needed to understand the spatial-temporal characteristics of ecosystem productivity response and resilience under meteorological droughts.

Methods The intensity and frequency of meteorological droughts were quantified by standardized precipitation evapotranspiration index (SPEI) of the Hai River Basin (HRB). Net primary productivity (NPP) of natural ecosystems was estimated based on Carnegie-Ames-Stanford Approach (CASA). We quantitatively analyzed the relationship between NPP and SPEI, evaluated the drought risk of natural vegetation and the resilience of vegetation after drought.

Important findings (1) Both NPP and normalized differential vegetation index (NDVI) in the HRB showed significantly increasing trend. (2) The lagging time of NPP response to droughts follow an order of grassland and savanna < deciduous broadleaf forest and woody savanna < deciduous-evergreen mixed forest and closed shrubland. (3) Drought risk followed an order of grassland > closed shrubland > woody savanna > deciduous broadleaf forest > savanna > deciduous-evergreen mixed forest. (4) More than 75% of the vegetation in the HRB showed no continuous distinctly low NPP status one month after the droughts, indicating relatively strong resilience. The resilience of forests was stronger than shrub or herbaceous vegetation, which showed opposite temporal pattern within each growing season but shared similar increasing trend interannually. Response and resilience characteristics of NPP varied with vegetation types and drought intensity. Ecosystem stability of the HRB could be improved by adjusting the afforestation and grass restoration measures based on vegetation drought risk and resilience, optimizing vegetation structure, and enhancing species diversity.

Key words: meteorological drought, drought risk, resilience, net primary productivity, standardized precipitation evapotranspiration index (SPEI)

黄砺成, 莫兴国. 海河流域生态系统净初级生产力对气象干旱的响应与弹性. 植物生态学报, 2024, 48(10): 1256-1273. DOI: 10.17521/cjpe.2023.0076

HUANG Li-Cheng, MO Xing-Guo. Response and resilience of net primary productivity of the Hai River Basin ecosystems under meteorological droughts. Chinese Journal of Plant Ecology, 2024, 48(10): 1256-1273. DOI: 10.17521/cjpe.2023.0076

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2023.0076

https://www.plant-ecology.com/CN/Y2024/V48/I10/1256

图/表 18

图1 海河流域自然植被分布图(国际地圈-生物圈计划(IGBP)土地覆被分类系统, 500 m空间分辨率)。

Fig. 1 Distribution of natural vegetation in the Hai River Basin (based on International Geosphere-Biosphere Programme (IGBP) land cover classification system with spatial resolution of 500 m). CS, closed shrubland; DBF, deciduous broadleaf forest; DEMF, deciduous-evergreen mixed forest; GL, grassland; HRB, the Hai River Basin; SVN, savanna; WSVN, woody savanna.

表1 海河流域植被与气候数据及其来源

Table 1 Vegetation and climate data and its sources of the Hai River Basin

数据产品 Data product	数据项 Data item	时间分辨率 Temporal resolution	空间分辨率 Spatial resolution	数据来源 Data source
中国区域地面气象要素驱动数据集 China Meteorological Forcing Dataset (CMFD)	月均气温 Monthly average air temperature	1自然月 1 sequential month	0.1°	国家青藏高原科学数据中心 National Tibetan Plateau Scientific Data Center (https://data.tpdc.ac.cn/zh-hans/data)
	月降水 Monthly precipitation
	太阳辐射量 Solar radiation
	近地面风速 Near-surface wind speed
	近地面气压 Near-surface air pressure
	近地面比湿 Near-surface specific humidity
实际蒸散量 Evapotranspiration (ET)		1自然月 1 sequential month	1 km	植被界面过程(VIP)模型 Vegetation Interface Process (VIP) model
MOD13A1.061	NDVI	16 d	500 m	Google Earth Engine (https://earthengine.google.com/)
MOD17A2.006	总初级生产力 Gross primary productivity (GPP)	8 d	500 m
MCD12Q1.006	土地覆被类型 Land cover type	1 a	500 m

表2 海河流域自然生态系统最大光能利用率(εmax)和最大归一化植被指数(NDVImax)

Table 2 Maximum light use efficiency (εmax) and maximum normalized differential vegetation index (NDVImax) of natural ecosystems in the Hai River Basin

土地覆被类型 Land cover type	ε_max(g·MJ^-1)	NDVI_max	样本量 Pixels of vegetations
落叶阔叶林 Deciduous broadleaf forest	0.692	0.862	8 912
落叶-常绿混交林 Deciduous-evergreen mixed forest	0.768	0.839	1 278
郁闭灌丛 Closed shrubland	0.429	0.831	2 314
多树草原 Woody savanna	0.542	0.811	1 754
稀树草原 Savanna	0.542	0.806	10 030
草原 Grassland	0.542	0.645	121 070

图2 植被界面过程(VIP)模型蒸散量(ET)模拟值-栾城站ET实测值相关系数(A)和t检验结果图(B) (平均值± 22.14/25.50)。

Fig. 2 Correlation coefficient (A) and t-test result (B) between Vegetation Interface Process (VIP) modelled evapotranspiration (ET) and ET measured in Luancheng station (mean ± 22.14/25.50).

图3 CASA净初级生产力(NPP)模拟值-MOD17A2总初级生产力(GPP)模拟值分布图。

Fig. 3 Distribution of CASA modelled net primary productivity (NPP) and MOD17A2 modelled gross primary productivity (GPP).

图4 海河流域自然植被净初级生产力(NPP)变化趋势(A)和线性趋势空间分布图(B)。CS, 郁闭灌丛; DBF, 落叶阔叶林; DEMF, 落叶-常绿混交林; GL, 草原; SVN, 稀树草原; WSVN, 多树草原。B中每个黑点代表0.1° × 0.1°范围内的样本存在通过Mann-Kendall检验的单调趋势, 且平均p < 0.05。

Fig. 4 Trends of natural vegetation net primary productivity (NPP) changes (A) and spatial distribution of linear trends of natural vegetation NPP changes (B) in the Hai River Basin. CS, closed shrubland; DBF, deciduous broadleaf forest; DEMF, deciduous-evergreen mixed forest; GL, grassland; HRB, the Hai River Basin; SVN, savanna; WSVN, woody savanna. Each black dot in B indicates samples within the 0.1° × 0.1° grid are with significant monotonic tendency confirmed through Mann-Kendall method, with average p < 0.05.

图5 海河流域自然植被净初级生产力(NPP)和归一化植被指数(NDVI) Mann-Kendall检验结果空间分布(A)和Mann-Kendall检验结果数量分布(B)。

Fig. 5 Spatial distribution of Mann-Kendall test results of natural vegetation net primary productivity (NPP) and normalized differential vegetation index (NDVI) changes in the Hai River Basin (A) and quantitative distribution of the Mann-Kendall test results (B).

表3 海河流域自然植被净初级生产力变幅(ΔNPP)分布表

Table 3 Distribution of natural vegetation net primary productivity changes (ΔNPP) in the Hai River Basin

分布参数 Distribution parameter	落叶阔叶林 Deciduous broadleaf forest	落叶-常绿混交林 Deciduous-evergreen mixed forest	郁闭灌丛 Closed shrubland	多树草原 Woody savanna	稀树草原 Savanna	草原 Grassland
标准差 Standard deviation (g·m^-2·month^-1)	42.18	46.67	27.15	37.51	35.66	38.12
选定样本数量比 Quantitative proportion of the chosen samples (%)	25.16	25.09	29.03	26.67	25.33	23.63
选定样本质量比 Qualitative proportion of the chosen samples (%)	60.54	59.70	61.97	59.82	58.54	56.67

图6 海河流域净初级生产力变幅(ΔNPP)-标准化降水蒸散指数(SPEI) Spearman秩相关系数(ρ)随SPEI时间尺度分布图。A, 落叶阔叶林。B, 落叶-常绿混交林。C, 郁闭灌丛。D, 多树草原。E, 稀树草原。F, 草原。

Fig. 6 Distribution of Spearman rank correlation coefficient (ρ) between net primary productivity changes (ΔNPP) and standardized precipitation evapotranspiration index (SPEI) in the Hai River Basin along SPEI time scales. A, Deciduous broadleaf forest. B, Deciduous-evergreen mixed forest. C, Closed shrubland. D, Woody savanna. E, Savanna. F, Grassland.

图7 海河流域净初级生产力变幅(ΔNPP)-标准化降水蒸散指数(SPEI) Spearman秩相关系数(ρ)与对应植被类型平均lag-1 SPEI-1线性拟合图。A, 落叶阔叶林。B, 落叶-常绿混交林。C, 郁闭灌丛。D, 多树草原。E, 稀树草原。F, 草原。RMSE, 均方根误差。

Fig. 7 Linear fit of net primary productivity changes (ΔNPP) to standardized precipitation evapotranspiration index (SPEI) Spearman rank correlation coefficient (ρ) and average lag-1 SPEI-1 of the corresponding vegetation types in the Hai River Basin. A, Deciduous broadleaf forest. B, Deciduous-evergreen mixed forest. C, Closed shrubland. D, Woody savanna. E, Savanna. F, Grassland. RMSE, root mean square error.

图8 海河流域各类型植被标准化干旱危害指数(DH)分布。CS, 郁闭灌丛; DBF, 落叶阔叶林; DEMF, 落叶-常绿混交林; GL, 草原; SVN, 稀树草原; WSVN, 多树草原。

Fig. 8 Distribution of standardized drought hazard (DH) in the Hai River Basin, listed by vegetation type. CS, closed shrubland; DBF, deciduous broadleaf forest; DEMF, deciduous-evergreen mixed forest; GL, grassland; SVN, savanna; WSVN, woody savanna

图9 海河流域各类型植被干旱适应性(DA)值分布。CS, 郁闭灌丛; DBF, 落叶阔叶林; DEMF, 落叶-常绿混交林; GL, 草原; SVN, 稀树草原; WSVN, 多树草原。

Fig. 9 Distribution of drought adaptability (DA) in the Hai River Basin, listed by vegetation type. CS, closed shrubland; DBF, deciduous broadleaf forest; DEMF, deciduous-evergreen mixed forest; GL, grassland; SVN, savanna; WSVN, woody savanna.

图10 海河流域植被干旱风险(DR)数量分布(A)和空间分布(B)。CS, 郁闭灌丛; DBF, 落叶阔叶林; DEMF, 落叶-常绿混交林; GL, 草原; SVN, 稀树草原; WSVN, 多树草原。

Fig. 10 Quantitative (A) and spatial (B) distribution of vegetation drought risk (DR) in the Hai River Basin. CS, closed shrubland; DBF, deciduous broadleaf forest; DEMF, deciduous-evergreen mixed forest; GL, grassland; SVN, savanna; WSVN, woody savanna.

图11 落叶阔叶林全生长季净初级生产力变幅(∆NPP)箱线图和1个月尺度的标准化降水蒸散指数(SPEI-1)提琴图。提琴图对应SPEI的概率密度分布, 箱线图箱体代表25%-75%范围, 中间线代表中位数, 空心圆代表均值, 须线代表1.5倍四分位距, 菱形点代表异常值。A-E依次为5-9月NPP明显下降。

Fig. 11 Net primary productivity changes (∆NPP) boxplot and 1-month standardized precipitation evapotranspiration index (SPEI-1) violin plot of the whole growing season. The violin plot indicates probability density distribution of SPEI, in the boxplot, the box indicates 25%-75% distribution range, the middle line indicates the median value, the hollow circle indicates mean value, the whiskers indicate 1.5 interquartile range, the rhombuses indicate outliers. A-E correspond the situation in which NPP declined distinctly in May, June, …, September.

图12 森林类(A)和灌草类(B)植被净初级生产力(NPP)弹性幅度(ar)对比图。

Fig. 12 Net primary productivity (NPP) resilience amplitude (ar) of forest (A) and shrub/grass (B) vegetation.

图13 海河流域植被净初级生产力变幅(∆NPP)对1个月尺度的标准化降水蒸散指数(SPEI-1)的典型响应过程。A-E分别为森林类5-9月NPP发生明显下降时, 全生长季SPEI-1和∆NPP变化模式。F-J分别为灌草类5-9月NPP发生明显下降时, 全生长季SPEI-1和∆NPP变化模式。

Fig. 13 Typical response pattern of vegetation net primary productivity changes (∆NPP) to 1-month standardized precipitation evapotranspiration index (SPEI-1) in the Hai River Basin. A-E present typical SPEI-1 and ∆NPP pattern of forest vegetation when NPP distinctly decrease in May to September, while F-J present typical SPEI-1 and ∆NPP pattern of shrub/grass vegetation when NPP distinctly decrease in May to September.

图14 2001-2018年海河流域森林类(A)和灌草类(B)植被弹性幅度(ar)分布图。

Fig. 14 Distribution of forest (A) and shrub/grass (B) vegetation resilience amplitude (ar) in the Hai River Basin, 2001-2018.

图15 海河流域净初级生产力变幅(ΔNPP)-标准化降水蒸散指数(SPEI)呈显著正相关关系的样本分布。CS, 郁闭灌丛; DBF, 落叶阔叶林; DEMF, 落叶-常绿混交林; GL, 草原; SVN, 稀树草原; WSVN, 多树草原。x轴1, 3, 6, 9, 12, lag-1为SPEI时间尺度, 其上方数字为对应时间尺度SPEI与ΔNPP呈显著正相关关系的月份数。

Fig. 15 Distribution of samples presenting significant positive correlation between net primary productivity changes (∆NPP) and standardized precipitation evapotranspiration index (SPEI) in the Hai River Basin. CS, closed shrubland; DBF, deciduous broadleaf forest; DEMF, deciduous-evergreen mixed forest; GL, grassland; SVN, savanna; WSVN, woody savanna. 1, 3, 6, 9, 12 and lag-1 under x axis are SPEI time scales, and the numbers above are the number of months in which the corresponding time scale SPEI is significantly positively correlated with ∆NPP.

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