近20 a塔里木河流域人类活动及景观生态风险时空变化

doi:10.13866/j.azr.2024.06.10

摘要/Abstract

摘要：

人类活动是区域生态风险加剧的重要因素，亟需探讨人类活动强度对景观生态风险影响。本文以塔里木河流域为研究对象，基于近20 a的5期土地利用、人口空间分布和夜间灯光数据，引入土地利用程度综合指数以改进人类活动强度（HAI）评价体系，定量评价强人类活动下的流域景观生态风险（LER）时空变化，并结合Copula函数以及双变量局部空间自相关模型，揭示LER与HAI的时空关联性。结果表明：（1）近20 a塔里木河流域HAI显著提高，强人类活动主要分布于水资源较丰富的绿洲区；流域人类活动强度呈增加趋势，低强度区面积占比减少17.88%、中高强度区面积占比增加3.57%。（2）塔里木河流域LER整体呈四周高、中部低的特征，高风险区主要分布于人类活动较为频繁的绿洲区；流域LER在2015年前呈加剧趋势，但2010年后加剧趋势减缓，2015年后改善趋势逐步显现。（3）近20 a HAI与LER呈正相关关系，人类活动对LER的正向效应不断增加；2010年后二者关系的增加趋势趋于平缓，正向效应出现由增到减的过渡阶段；空间上H-H聚集区呈增加趋势，分布格局由分散变为集中；2015年后，L-L和H-L聚集区缓慢增加，L-H聚集区缓慢减少。研究结果可为塔里木河流域土地资源合理利用、景观生态保护提供科学参考。

关键词: 景观生态风险, 人类活动, 时空关联, 塔里木河流域

Abstract:

Human activity is an essential factor in the intensification of regional ecological risk. Hence, it is urgent to discuss the impact of human activity intensity (HAI) on the landscape ecological risk. This paper took the Tarim River Basin as the research object. Based on the land use, population spatial distribution, and night light data during five periods from 2000 to 2020, it introduces the comprehensive index of land use degree to improve the evaluation system of HAI and quantitatively evaluates the temporal and spatial changes of landscape ecological risk (LER) in the basin under robust human activity. Combined with the Copula function and bivariate local spatial autocorrelation model, the spatiotemporal correlation between LER and HAI is revealed. The results showed that (1) The HAI in the Tarim River Basin enhanced markedly in the past 20 years, and extensive human activities were mainly distributed in the oasis areas with rich water resources. The intensity of human activities in the basin increased, with the proportion of low-intensity areas diminished by 17.88% and that of medium-high-intensity areas elevated by 3.57%. (2) The overall LER in the Tarim River Basin was characterized by a high surrounding area and a low central area, and the high-risk area was mainly distributed in the oasis areas with more frequent human activities. The LER in the basin intensified before 2015, which slowed down after 2010, and gradually emerged after 2015. (3) The HAI and LER were positively correlated during the past 20 years, and the positive effect of human activities on LER was enhanced. After 2010, the increasing correlation between the two flattened, and a positive effect appeared in the stage of transition from increase to decrease. The H-H cluster area elevated in space, and the distribution pattern changed from dispersion to concentration. After 2015, the L-L and H-L cluster areas slowly increased, unlike the L-H cluster areas. The results can provide a scientific reference for the rational use of land resources and protection of the landscape ecology in the Tarim River Basin.

Key words: landscape ecological risk, human activity, spatio-temporal correlation, Tarim River Basin

杨荣钦, 肖玉磊, 池苗苗, 穆振侠. 近20 a塔里木河流域人类活动及景观生态风险时空变化[J]. 干旱区研究, 2024, 41(6): 1010-1020.

YANG Rongqin, XIAO Yulei, CHI Miaomiao, MU Zhenxia. Temporal and spatial variations of human activities and landscape ecological risks in the Tarim River Basin, China, during the last 20 years[J]. Arid Zone Research, 2024, 41(6): 1010-1020.

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2000年	2020年
2000年	耕地	林地	草地	水域	建设用地	未利用土地	总计
耕地	-	1098.66	1425.45	203.65	1297.06	542.65	4567.47
林地	2071.37	-	5722.53	272.24	76.65	1808.06	9950.85
草地	12165.10	6037.15	-	3734.20	289.33	86713.10	108938.87
水域	490.03	231.77	7353.46	-	71.48	15430.09	23576.83
建设用地	822.63	85.20	68.18	8.33	-	36.20	1020.54
未利用土地	4680.59	1418.17	84866.90	5705.87	845.78	-	97517.29
总计	20229.72	8870.95	99436.50	9924.28	2580.30	104530.09	245571.85

年份	平均 ERI	LER各等级面积占比/%
年份	平均 ERI	低风险	较低风险	中风险	较高风险	高风险
2000年	0.075	5.79	39.25	31.64	17.37	5.94
2005年	0.075	5.86	39.09	31.19	17.84	6.03
2010年	0.077	3.95	38.51	27.48	19.78	10.28
2015年	0.078	3.93	37.98	26.72	20.24	11.14
2020年	0.078	3.91	38.42	27.49	20.15	10.03

函数类型	2000年	2005年	2010年	2015年	2020年
Frank Copula	9.50	27.57	26.66	22.60	23.18
Clayton Copula	17.34	36.57	28.92	24.75	24.87
Gumbel Copula	14.22	37.62	51.95	45.32	45.71
t Copula	10.22	29.71	31.04	26.67	27.25
Gaussian Copula	13.18	37.38	48.84	41.18	40.82