Response and resilience of net primary productivity of the Hai River Basin ecosystems under meteorological droughts

doi:10.17521/cjpe.2023.0076

Abstract

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)

HUANG Li-Cheng, MO Xing-Guo. Response and resilience of net primary productivity of the Hai River Basin ecosystems under meteorological droughts[J]. Chin J Plant Ecol, 2024, 48(10): 1256-1273.

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Figures/Tables 18

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.

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

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

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).

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

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.

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).

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

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.

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.

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

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.

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.

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.

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

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.

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

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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