中国沿海省区海洋生态效率空间格局演化及影响因素分析

doi:10.13249/j.cnki.sgs.2019.04.011

摘要/Abstract

摘要：

采用考虑非期望产出的SBM模型对中国沿海11省区（不包括港澳台地区）海洋生态效率进行测算,借助重心模型定量刻画了2001~2015年沿海省区海洋生态效率空间格局演化特征,并基于VAR模型探究空间格局演化与其影响因素之间的动态关系。结果表明：① 沿海省区海洋生态效率呈现上升趋势,天津、上海、江苏、福建、广东海洋生态效率由相对无效跃升至相对有效,辽宁、山东、海南由相对无效上升至相对低效,河北、浙江、广西始终处于相对无效水平。② 海洋生态效率重心移动路径可分为“2001~2006年东北方向迁移阶段”和“2006~2015年西南方向迁移阶段”,但重心移动范围主要位于长三角地区。③ 针对海洋生态效率空间格局演化影响因素的分析表明,海洋产业结构对海洋生态效率的影响呈正负波动态势但以正向促进为主,随着产业结构的不断优化,负向作用不断减弱;海洋科技水平对海洋生态效率会产生显著的正向推动作用和持续效益,在海洋生态效率变动的初期刺激作用尤为强烈;环境规制作为末端处理对海洋生态效率的影响并不显著。

关键词: 海洋生态效率, 重心模型, VAR模型, 沿海省区

Abstract:

：This article measures the marine ecological efficiency of 11 coastal regions in China with the SBM model considering the undesirable output. The center of gravity model is applied to projecting and visualizing the evolution of spatial pattern of marine ecological efficiency from 2001 to 2015. On this basis, the VAR model is introduced to explore the dynamic relationship between spatial evolution of marine ecological efficiency and its influence factors.The results showed that: 1) The marine ecological efficiency of coastal provinces is generally low but shows an upward trend. Among them, the marine ecological efficiency of Tianjin, Shanghai, Jiangsu, Fujian and Guangdong jumped from relatively ineffective to relatively effective, and Liaoning,Shandong and Hainan rose from relatively ineffective to relatively inefficient, while Hebei, Zhejiang and Guangxi remained relatively ineffective. 2) The transition process of the gravity center of marine ecological efficiency can be divided into "northeast migration phase from 2001 to 2006" and "southwest migration phase from 2006 to 2015", however, the movement range of of the center of gravity is mainly located in the Yangtze River Delta region. 3) By analyzing the influence factors on the evolution of spatial pattern of marine ecological efficiency, we can find out that the impact of marine industrial structure on marine ecological efficiency has fluctuations between positive and negative but mainly positive. As the industrial structure is continuously optimized, the negative effect is weakened over time. Marine science and technology have a significant positive effect and sustained benefits on marine ecological efficiency, especially in the initial stage of the change of marine ecological efficiency. As a terminal treatment, the effect of environmental regulation on the marine ecological efficiency is not significant.

Key words: marine ecological efficiency, barycenter model, VAR model, coastal regions of China

中图分类号:

盖美, 展亚荣. 中国沿海省区海洋生态效率空间格局演化及影响因素分析[J]. 地理科学, 2019, 39(4): 616-625.

Mei Gai, Yarong Zhan. Spatial Evolution of Marine Ecological Efficiency and Its Influential Factors in China Coastal Regions[J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(4): 616-625.

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目标层	准则层	指标层	指标解释及计算
投入	资源	海洋生物资源系数	具体说明请见公式①
		海水化学资源标准量	具体说明请见公式②
		海洋矿产资源标准量	具体说明请见公式③
	资本	海洋固定资本存量	具体说明请见公式（1）
	人力	涉海从业人员	从《中国海洋统计年鉴》^[20]获得
产出	期望产出	海洋生产总值	从《中国海洋统计年鉴》^[20]获得
	非期望产出	沿海地区工业废水排放中的化学需氧量、氨氮排放量	从《中国环境统计年鉴》^[26]获得
		沿海地区工业废气排放中的二氧化硫、烟粉尘排放量	从《中国环境统计年鉴》^[26]获得

省份	2001年	2003年	2005年	2007年	2009年	2011年	2013年	2015年
天津	0.090	0.136	0.223	0.261	0.342	0.504	0.719	1.000
河北	0.080	0.096	0.121	0.250	0.218	0.280	0.339	0.393
辽宁	0.101	0.129	0.168	0.249	0.298	0.392	0.462	0.529
上海	0.157	0.191	0.349	0.538	0.611	0.738	1.000	1.000
江苏	0.091	0.132	0.180	0.291	0.374	0.517	0.666	1.000
浙江	0.102	0.132	0.158	0.178	0.234	0.276	0.317	0.390
福建	0.140	0.185	0.197	0.254	0.327	0.477	0.628	1.000
山东	0.105	0.137	0.170	0.260	0.332	0.418	0.526	0.623
广东	0.120	0.137	0.225	0.266	0.337	0.476	0.638	1.000
广西	0.097	0.085	0.116	0.161	0.201	0.270	0.307	0.380
海南	0.100	0.112	0.143	0.186	0.216	0.268	0.341	0.414
全国	0.108	0.134	0.187	0.263	0.317	0.420	0.540	0.703

预测期	标准误差	海洋生态效率	海洋产业结构	海洋科技支撑能力	环境规制
1	0.087291	100.0000	0.000000	0.000000	0.000000
2	0.145331	77.94765	14.80597	7.112295	0.134084
3	0.155663	79.51105	13.49888	6.711822	0.278251
4	0.156729	78.62873	13.80305	7.257021	0.311202
5	0.160084	78.44338	13.23761	7.966028	0.352987
6	0.163419	78.89708	12.88941	7.824911	0.388597
7	0.165299	78.47688	13.08834	8.044011	0.390775
8	0.165630	78.23466	13.25014	8.125937	0.389263
9	0.166024	78.2619	13.24389	8.106213	0.388004
10	0.166714	78.27585	13.20672	8.128495	0.388932