黄河流域城市生态韧性时空分异及收敛研究——基于七大城市群61个城市的实证分析

doi:10.12118/j.issn.1000－6060.2023.323

摘要/Abstract

摘要：

科学测度黄河流域城市群城市生态韧性的发展现状及收敛趋势，对于黄河流域城市生态保护及高质量发展具有重要意义。选取2011—2020年黄河流域七大城市群61个地级市面板数据，以演化韧性为研究视角，从“抵抗-响应-创新”等维度，构建城市生态韧性评价指标体系，利用核密度估计和自然断裂法考察城市生态韧性的空间分异，借助不同类型收敛模型解析城市生态韧性的收敛趋势。研究表明：（1）黄河流域城市生态韧性总体均值为0.093，且呈缓慢发展趋势。（2）城市生态韧性表现为“下游城市群强、上中游城市群弱”的空间格局，城市群内部形成了“核心及省会城市—外围及边缘城市”递减的空间分布。（3）黄河流域和各城市群内部均存在绝对β收敛，其中晋中城市群收敛最快。加入控制变量后，黄河流域和各城市群内部呈现显著条件β收敛趋势，且收敛速度均有提升。此外，经济发展水平、人口密度等变量对城市生态韧性收敛的影响具有显著异质性。

关键词: 黄河流域, 城市群, 城市生态韧性, 时空分异, 空间收敛

Abstract:

The scientific measurement of the development status and convergence trend of urban ecological resilience in the Yellow River Basin urban agglomeration is of great significance for the ecological protection and high-quality development of Yellow River Basin. This study selects the panel data of 61 prefecture-level cities in the seven major urban agglomerations in the Yellow River Basin from 2011 to 2020, takes evolutionary resilience as the research perspective, constructs an urban ecological resilience evaluation index system from the dimensions of resistance-response-innovation, examines the spatial differentiation of urban ecological resilience using kernel density estimation and the natural break method, and analyzes the urban ecological resilience using different types of convergence models. This study shows the following: (1) The overall mean value of urban ecological resilience in the Yellow River Basin is 0.093, and the trend is slow. (2) The urban ecological resilience exhibits a spatial pattern of “strong downstream city clusters and weak upstream and midstream city clusters”, and a decreasing spatial distribution of “core and provincial capital cities-peripheral and marginal cities” within the city clusters. (3) Absolute β convergence exists in the Yellow River Basin and city clusters, among which the Jinzhong City cluster converges the fastest. After adding control variables, the Yellow River Basin and city clusters exhibit a significant conditional β convergence trend, and the speed of convergence increases. In addition, the effects of economic development level, population density, and other variables on the convergence of urban ecological resilience are significantly heterogeneous.

Key words: Yellow River Basin, urban agglomeration, urban ecological resilience, spatiotemporal differentiation, spatial convergence

王松茂, 宁文萍, 牛金兰, 安康. 黄河流域城市生态韧性时空分异及收敛研究——基于七大城市群61个城市的实证分析[J]. 干旱区地理, 2024, 47(1): 93-103.

WANG Songmao, NING Wenping, NIU Jinlan, AN Kang. Spatiotemporal differentiation and convergence of urban ecological resilience in the Yellow River Basin: An empirical analysis based on 61 cities in seven major urban agglomerations[J]. Arid Land Geography, 2024, 47(1): 93-103.

图/表 7

图1

表1

图2

图3

图4

表2

表3

黄河流域城市群城市生态韧性条件β收敛"

区域	总体	中原	晋中	关中平原	呼包鄂榆	宁夏沿黄	兰西	山东半岛
模型类型	双固定SDM模型	双固定OLS模型	空间固定OLS模型	时间固定SAR模型	空间固定SEM模型	双固定OLS模型	空间固定OLS模型	时间固定SEM模型
β	-0.308^*** （-4.022）	-0.217^*** （-3.908）	-0.268^*** （-4.340）	-0.196^*** （-4.023）	-0.229^*** （-5.135）	-0.236^** （-2.072）	-0.267^*** （-3.508）	-0.237^*** （-3.826）
ECO	-0.209^* （-1.693）	-0.231^*** （-1.627）	0.151^** （2.078）	0.217 （0.627）	-0.228^*** （-3.701）	0.211^* （1.608）	0.152 （0.199）	-0.262^*** （-3.627）
PDE	0.171^* （1.838）	0.273^* （1.762）	0.151 （0.529）	0.189^*** （3.267）	0.256^** （1.937）	0.166^* （1.880）	0.151 （0.538）	0.168 （1.260）
IND	0.182 （1.307）	0.177 （1.085）	0.166 （0.931）	0.172 （0.833）	0.116^** （1.921）	0.147 （1.299）	0.139 （1.377）	0.170 （0.050）
TEC	-0.134^*** （-4.801）	0.168 （1.053）	-0.120^** （-1.923）	0.129 （1.118）	0.134 （0.847）	0.152 （1.053）	-0.147^** （-1.806）	-0.138^*** （-4.135）
ER	-0.196^*** （-4.352）	-0.188^** （-2.136）	-0.201^** （-2.369）	0.209 （1.784）	0.101 （0.674）	-0.186^** （-1.991）	0.201 （0.707）	-0.209^* （-3.635）
ρ或λ	0.207^*** （3.095）	-	-	0.219^* （1.618）	0.198^** （1.996）	-	-	0.193^*** （2.782）
R²	0.312	0.273	0.338	0.362	0.288	0.363	0.258	0.326
Log-Likelihood	443.523	367.325	298.306	123.387	423.783	353.128	266.574	435.958
空间固定效应	312.026^***	73.873^***	40.515^***	31.509	40.636^***	36.744^***	50.871^**	42.865
时间固定效应	186.509^***	66.322^***	37.337	25.426^***	52.965	40.089^***	73.635	37.925^***
Hausman检验	263.176^***	56.227^***	27.818^***	34.077^***	29.506^***	68.361^***	28.305^***	37.519^***
R-LM（SAR模型）	35.215^***	10.709	8.602	21.667^***	9.569	3.276	7.947	13.216
R-LM（SEM模型）	27.024^**	6.253	6.841	18.509	6.872^***	6.253	6.256	16.508^***

表3

参考文献 33

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目标层	一级指标	代码	二级指标	属性	权重/%
城市生态韧性	抵抗维度	RS1	人均水资源量/m³·人^-1	+	8.98
		RS2	人均绿地面积/m²	+	5.81
		RS3	归一化植被指数/%	+	1.73
		RS4	空气优良天数/d	+	1.43
	响应维度	RS5	建成区绿化覆盖率/%	+	0.35
		RP6	一般工业固体废弃物综合利用率/%	+	1.44
		RP7	污水处理厂集中处理率/%	+	1.07
		RP8	生活垃圾无害化处理率/%	+	0.53
		RP9	环保占财政支出的比重/%	+	21.40
	创新维度	IN10	R&D经费投入占GDP的比重/%	+	26.03
		IN11	专利授权数量/个	+	16.67
		IN12	每万人在校大学生数/人	+	14.57

区域	总体	中原	晋中	关中平原	呼包鄂榆	宁夏沿黄	兰西	山东半岛
模型类型	双固定SDM模型	空间固定OLS模型	空间固定OLS模型	双固定SAR模型	时间固定OLS模型	双固定SEM模型	空间固定OLS模型	时间固定SEM模型
β	-0.233^* （-1.756）	-0.125^*** （-3.652）	-0.235^*** （-4.078）	-0.187^** （-1.997）	-0.129^*** （-4.028）	-0.217^** （-2.187）	-0.233^*** （-3.905）	-0.206^*** （-4.452）
θ	0.4107^*** （4.572）	-	-	-	-	-	-	-
ρ或λ	0.237^** （2.153）	-	-	0.109 （1.427）	-	0.272^* （1.658）	-	0.232^** （1.983）
R²	0.307	0.292	0.371	0.196	0.235	0.271	0.302	0.335
Log-Likelihood	357.238	236.579	311.206	289.067	177.535	198.282	206.567	463.720
空间固定效应	238.563^***	68.230^***	35.679^***	22.681^***	29.053	18.539^***	61.815^***	34.625
时间固定效应	147.758^***	54.276	41.508	18.837	16.972^***	25.636^***	50.571	29.876^***
Hausman检验	202.575^***	38.631^***	27.818^***	31.580^***	17.932^***	52.077^***	18.528^***	30.252^***
R-LM（SAR模型）	26.307^***	7.602	4.375	10.528^***	3.061	0.538	4.724	11.536
R-LM（SEM模型）	18.236^**	5.931	6.963	13.642	7.371	1.573^***	8.906	15.637^***