基于生态系统服务的中国陆地生态风险评价

doi:10.11821/dlxb201903003

Abstract

Abstract:

The ecological risk assessment was previously explored according to ecological entity characteristics, such as point source threat and regional landscape pattern change, and ignored the factors related to the human well-being. The academic contribution of the essay is to integrate ecosystem services into assessment system of ecological risk in a new perspective. In this paper, the spatial mapping of ecosystem services on China's land is reconstructed with the aid of GIS and RS. Moreover, the ecological risk analysis model is established in order to quantitatively expound the spatial pattern of the ecological risk based on ecosystem services, and identify ecological risk control priority regions at different confidence levels. The results showed that: (1) From 2000 to 2010, the average annual value of total terrestrial ecosystem services index in China was between 0-2.17, and slightly fluctuated between 0.30-0.57 over the years. Some 24.7% of the regions with significantly increasing value included Taiwan, Yunnan-Guizhou Plateau, inland Xinjiang of northwest China, 37.1% of the regions with significantly decreasing value, including northeast China, Qinghai-Tibet Plateau, central and eastern regions of China; (2) The risk losses of ecosystem services were exposed to different situations under different confidence levels. When the confidence level was 90%, the potential loss ratio of the total ecosystem services index was 24.19%, and the ecological risk index was 0.253. Furthermore, by analyzing the relationship between confidence level and ecological risk index, when the confidence level was high, the probability of risk was reduced correspondingly, but the losses correspondingly increased when risk occurred; (3) We investigated the scenario as an example under the 90% confidence level. The different eco-regions with the risk characteristics are as follows: the top six eco-regions with average ecosystem services risk index are Inner Mongolia Plateau, North China Plain, Loess Plateau, Northeast China Plain, Hengduan Mountain Region, and Qinghai-Tibet Plateau. The proportions of the eco-regions with extreme risk are 55.89%, 26.63%, 24.35%, 20.62%, 18.70% and 25.12%, respectively.

Key words: ecological risk, ecosystem services, risk index, ecological risk control priority regions, GIS and RS, China

Feng CHEN, Hongbo LI, Anlu ZHANG. Ecological risk assessment based on terrestrial ecosystem services in China[J].Acta Geographica Sinica, 2019, 74(3): 432-445.

Figures/Tables 6

Tab. 1

Fig. 1

Tab. 2

Tab. 3

Fig. 2

Tab. 4

References 53

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生态地理区划	多年平均总生态系统服务指数均值	总生态系统服务指数变化趋势均值
东北平原生态区(A)	0.522	-0.026
内蒙古高原生态区(B)	0.224	-0.010
华北平原生态区(C)	0.492	-0.020
长江中下游平原生态区(D)	0.633	-0.031
四川盆地生态区(E)	0.658	-0.030
黄土高原生态区(F)	0.423	-0.014
西北内陆生态区(G)	0.048	-0.001
青藏高原生态区(H)	0.091	-0.004
横断山生态区(I)	0.482	-0.016
云贵高原生态区(J)	0.947	-0.029
江南山地丘陵生态区(K)	0.922	-0.043
东南沿海丘陵生态区(L)	1.132	-0.032

年份	平均生态系统服务指数	平均生态系统服务指数变化率(%)	平均生态系统服务指数变化率期望(%)	平均生态系统服务指数变化率标准差(%)
2000	0.423		-1.147	18.87
2001	0.372	-12.06
2002	0.415	11.56
2003	0.574	38.31
2004	0.343	-40.24
2005	0.332	-3.21
2006	0.315	-5.12
2007	0.335	6.35
2008	0.332	-0.90
2009	0.297	-10.54
2010	0.310	4.38

置信水平(%）	1-α对应分位数	生态系统服务最大损失值(%)	生态风险指数
99	-2.326	42.19	0.433
95	-1.645	31.04	0.322
90	-1.282	24.19	0.253
85	-1.036	19.55	0.207
80	-0.842	15.89	0.170

生态地理区划	平均生态系统服务风险指数	各等级风险所占面积百分比(%)
生态地理区划	平均生态系统服务风险指数	极轻度	轻度	中度	重度	极重度
东北平原生态区(A)	0.374	0.51	19.55	28.52	30.80	20.62
内蒙古高原生态区(B)	0.447	11.99	2.75	7.75	21.62	55.89
华北平原生态区(C)	0.390	0.31	21.10	29.54	22.42	26.63
长江中下游平原生态区(D)	0.295	1.07	60.32	31.41	3.99	3.21
四川盆地生态区(E)	0.333	0.18	37.49	34.11	21.82	6.4
黄土高原生态区(F)	0.384	0.30	20.89	28.02	26.44	24.35
西北内陆生态区(G)	0.233	51.16	22.74	6.54	10.39	9.17
青藏高原生态区(H)	0.347	21.56	11.43	13.35	28.54	25.12
横断山生态区(I)	0.357	1.51	32.16	25.17	22.46	18.70
云贵高原生态区(J)	0.308	0.94	47.80	35.02	14.18	2.06
江南山地丘陵生态区(K)	0.290	1.41	57.14	31.64	8.68	1.13
东南沿海丘陵生态区(L)	0.323	1.20	41.18	36.90	16.17	4.55

Ecological risk assessment based on terrestrial ecosystem services in China

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