银川市湿地景观演变及其驱动因素

doi:10.13866/j.azr.2021.03.27

摘要/Abstract

摘要：

基于1990—2019年Landsat TM/OLI遥感影像,采用面向对象分类方法提取银川市湿地景观信息,通过景观指数、冗余分析方法定量分析研究区湿地景观演变特征及其驱动因素。结果表明：（1）银川市湿地面积由1990年的264.86 km²减少到2019年的241.32 km²,减少了23.54 km²。与1990年相比,2019年的自然湿地面积减少了33.57 km²,人工湿地面积增加了10.03 km²。（2） 1990—2019年间,银川市湿地景观的破碎化程度下降、聚集程度降低、形状逐渐不规则化、多样性与异质性增加。（3）选取12个驱动因素指标进行冗余分析,社会经济因素是湿地景观演变的主导因素,非农业人口数、水产品产量、第二产业产值与建成区面积对湿地景观变化的影响最为显著,降水量、气温等自然因素作用相对较弱。研究结果可为银川市的湿地资源的合理利用与保护提供重要参考。

关键词: 湿地, 景观格局, 演变, 驱动因素, 银川市

Abstract:

Wetland is the transitional zone of aquatic and terrestrial ecosystems, and it is an ecosystem with the highest biodiversity and productivity on Earth. Recently, under the influence of climate change and human activities, the wetland ecosystem has rapidly degraded. Spatio-temporal dynamic monitoring of wetland plays a vital role in the sustainable development of wetland landscape. The object-oriented classification method was used to extract the wetland landscape information in Yinchuan based on the Landsat TM/OLI remote sensing images from 1990 to 2019. The landscape index and redundancy analysis methods were used to analyze the dynamic changes and their driving factors in wetlands. The results showed that Yinchuan’s wetland area decreased from 264.86 km² in 1990 to 241.32 km²in 2019, a decrease of 23.54 km². The area of natural wetlands in 2019 decreased by 33.57 km², while artificial wetlands increased by 10.03 km². In the past 30 years, PD and AI of the landscape patterns have decreased, while the LSI and SHDI increased. This indicated that the wetland landscape patterns has undergone significant changes, fragmentation and aggregation degree gradually decreased, patch shape tended to be more complicated, and landscape diversity and heterogeneity increased. Twelve driving factors were selected for redundancy analysis, and socio-economic factors played a dominant role in the wetland landscape change, including nonagricultural population and aquatic products yield, the output value of various industries, and developed areas of cities. Altogether, natural factors such as precipitation, temperature, and hours of sunshine change could also impact the wetland landscape change, which is relatively weak. The research results provide important references to protect and rationally use wetlands resources in Yinchuan.

Key words: wetland, landscape pattern, evolution, driving factors, Yinchuan

王晓峰,延雨,李月皓,张兴,符鑫鑫. 银川市湿地景观演变及其驱动因素[J]. 干旱区研究, 2021, 38(3): 855-866.

WANG Xiaofeng,YAN Yu,LI Yuehao,ZHANG Xing,FU Xinxin. Wetland landscape evolution and its driving factors in Yinchuan[J]. Arid Zone Research, 2021, 38(3): 855-866.

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一级分类	二级分类	说明
自然湿地	河流湿地	包括永久性河流、季节性或间歇性河流、洪泛平原湿地
	湖泊湿地	包括永久性淡水湖、季节性淡水湖和季节性咸水湖
	沼泽湿地	主要以草本植物为主的沼泽湿地
人工湿地	水库/坑塘	以蓄水、农业灌溉、城市景观等为主要目的的人工湿地
	水产养殖地	以鱼、虾等水产品养殖为目的的人工湿地
	沟渠	以输水、灌溉为目的的沟、渠

年份	指标	河流湿地/%	湖泊湿地/%	沼泽湿地/%	水库/坑塘/%	水产养殖地/%	沟渠/%	OA/%	Kappa
1990	UA	83.33	80.56	77.78	88.10	87.90	85.71	85.65	0.80
1990	PA	88.24	80.47	84.85	86.05	88.62	80.00	85.65	0.80
1995	UA	76.19	85.23	79.07	83.70	88.37	76.47	84.66	0.79
1995	PA	80.00	80.65	77.27	88.28	86.86	81.25	84.66	0.79
2000	UA	76.92	84.48	84.09	87.94	85.37	84.62	85.71	0.81
2000	PA	83.33	85.96	82.22	86.11	87.50	78.57	85.71	0.81
2005	UA	81.82	80.77	82.61	89.22	82.76	77.78	85.09	0.79
2005	PA	85.71	81.55	83.82	88.46	81.36	82.35	85.09	0.79
2010	UA	82.61	83.33	78.43	88.95	81.03	86.67	84.91	0.79
2010	PA	86.36	80.81	86.96	87.50	82.46	81.25	84.91	0.79
2015	UA	80.77	85.09	81.40	87.39	84.81	78.95	84.75	0.80
2015	PA	80.77	83.62	81.40	89.66	82.72	83.33	84.75	0.80
2019	UA	85.71	77.11	84.85	91.96	80.85	76.92	87.43	0.78
2019	PA	80.00	84.21	84.85	89.94	80.85	83.33	87.43	0.78

年份	面积及占比	河流湿地	湖泊湿地	沼泽湿地	水库/坑塘	水产养殖地	沟渠	总计
1990	面积/km²	111.88	37.13	14.65	21.98	57.73	21.49	264.86
1990	比例/%	42.24	14.02	5.53	8.30	21.80	8.11	100
1995	面积/km²	90.86	37.32	15.05	20.22	66.43	20.31	250.20
1995	比例/%	36.32	14.92	6.02	8.08	26.55	8.12	100
2000	面积/km²	76.29	34.21	16.52	18.77	64.25	22.32	232.36
2000	比例/%	32.83	14.72	7.11	8.08	27.65	9.61	100
2005	面积/km²	71.19	43.76	15.87	17.38	74.70	21.69	244.60
2005	比例/%	29.11	17.89	6.49	7.11	30.54	8.87	100
2010	面积/km²	73.37	46.66	14.99	17.62	68.55	31.33	252.52
2010	比例/%	29.06	18.48	5.93	6.98	27.15	12.41	100
2015	面积/km²	70.10	52.07	11.43	16.41	61.13	30.07	241.19
2015	比例/%	29.06	21.59	4.74	6.80	25.34	12.47	100
2019	面积/km²	72.23	46.99	10.87	18.76	59.93	32.54	241.32
2019	比例/%	29.93	19.47	4.50	7.77	24.83	13.49	100

年份	PD/(个·km^-2)	LSI	AI/%	SHDI
1990	6.99	70.98	97.85	0.74
1995	6.96	72.10	97.81	0.77
2000	5.42	65.69	97.87	0.77
2005	4.52	68.23	97.82	0.78
2010	4.66	73.27	97.71	0.79
2015	4.51	78.04	97.49	0.78
2019	5.01	81.18	97.40	0.78

排序轴	特征值	湿地景观-驱动因素相关系数	湿地景观变化累积百分比	湿地景观-驱动因素关系变化累积百分比	特征值总和	典型特征值总和	蒙特卡罗置换检验
排序轴	特征值	湿地景观-驱动因素相关系数	湿地景观变化累积百分比	湿地景观-驱动因素关系变化累积百分比	特征值总和	典型特征值总和	第一排序轴显著性检验	所有排序轴显著性检验
Axis1	0.62	0.99	61.60	66.20	1.00	0.93	F=25.66 P=0.001	F=17.69 P=0.001
Axis2	0.23	0.95	84.30	90.60
Axis3	0.04	0.90	88.70	95.40
Axis4	0.04	0.85	92.70	99.70