喀斯特生态脆弱区贫困化时空动态特征与影响因素——以贵州省为例
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摘要
贵州省属于西南喀斯特生态脆弱与集中连片特困的复合区域,研究其贫困化的时空动态与影响因素,对该地区精准脱贫具有重要意义。以贫困发生率为指标,采用ESTDA框架对2003—2015年贵州省贫困化时空动态特征进行分析,并结合地理探测器分析其影响因素。结果表明:(1)贵州省贫困化具有显著的空间正相关性,出现了贫困化相似县域相邻分布的空间集聚效应,局部趋势上两级分化趋势明显,空间结构呈典型的"核心边缘"模式。(2)贫困化局部空间结构和空间依赖方向上都具有较强的稳定性;出现协同增长型的县域有53个,表明贫困化空间格局具有明显的空间整合性。(3)贫困化具有较强的局部空间关联模式和空间转移惰性,表现为一定的路径依赖或空间锁定特征。(4)各因素对贫困化的影响力存在一定差异,农民可支配收入是影响贫困化主要因素,海拔、坡度和植被覆盖度等自然因素影响较小;任意两个因素交互探测后对贫困化的影响均强于单个因素的影响,且解释力表现为非线性增强和双线性增强两种类型。
Guizhou Province is a composite of ecologically fragile areas of karst landscape and contiguous destitute areas, and examining the spatial and temporal dynamics of poverty and the factors that influence it has important theoretical and practical significance for targeted poverty alleviation in Guizhou Province. Taking the incidence of poverty as a research index, we analyzed the spatial-temporal dynamic evolution of poverty in Guizhou Province from 2003 to 2015 using the ESTDA framework, and analyzed the factors influencing the spatial pattern using the Geo-detector model. The main conclusions drawn from our analyses are as follows:(1) The poverty among counties shows significant positive spatial autocorrelation and we detected a spatial agglomeration effect of the neighboring distribution of similar counties in relation to poverty. At the local level, a two-level differentiation trend in county poverty is obvious, and the spatial structure of poverty shows a typical "core edge" model.(2) The local spatial structure and spatial dependence direction of poverty have strong stability. There are 53 counties showing collaborative growth, indicating that there is a strong spatial integration of poverty in Guizhou Province.(3) The spatial association model and spatial transfer inertia are characterized by a certain degree of path-dependence or spatial lock-in characteristics.(4) There are certain differences in the influence and significance of various factors relating to poverty. The disposable income per rural capita is the main factor affecting poverty, and the influences of altitude, slope, and vegetation coverage are relatively small. The influence of any two factors on poverty after interaction is stronger than that of any single factor, and the explanatory force shows two types of enhancement: nonlinear or bilinear.
Guizhou Province is a composite of ecologically fragile areas of karst landscape and contiguous destitute areas, and examining the spatial and temporal dynamics of poverty and the factors that influence it has important theoretical and practical significance for targeted poverty alleviation in Guizhou Province. Taking the incidence of poverty as a research index, we analyzed the spatial-temporal dynamic evolution of poverty in Guizhou Province from 2003 to 2015 using the ESTDA framework, and analyzed the factors influencing the spatial pattern using the Geo-detector model. The main conclusions drawn from our analyses are as follows:(1) The poverty among counties shows significant positive spatial autocorrelation and we detected a spatial agglomeration effect of the neighboring distribution of similar counties in relation to poverty. At the local level, a two-level differentiation trend in county poverty is obvious, and the spatial structure of poverty shows a typical "core edge" model.(2) The local spatial structure and spatial dependence direction of poverty have strong stability. There are 53 counties showing collaborative growth, indicating that there is a strong spatial integration of poverty in Guizhou Province.(3) The spatial association model and spatial transfer inertia are characterized by a certain degree of path-dependence or spatial lock-in characteristics.(4) There are certain differences in the influence and significance of various factors relating to poverty. The disposable income per rural capita is the main factor affecting poverty, and the influences of altitude, slope, and vegetation coverage are relatively small. The influence of any two factors on poverty after interaction is stronger than that of any single factor, and the explanatory force shows two types of enhancement: nonlinear or bilinear.
引文
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[2] Liu Y S,Liu J L,Zhou Y.Spatio-temporal patterns of rural poverty in China and targeted poverty alleviation strategies.Journal of Rural Studies,2017,52:66- 75.
[3] 赵雪雁,马艳艳,陈欢欢,高志玉,薛冰.干旱区内陆河流域农村多维贫困的时空格局及影响因素——以石羊河流域为例.经济地理,2018,38(2):140- 147.
[4] 刘彦随,李进涛.中国县域农村贫困化分异机制的地理探测与优化决策.地理学报,2017,72(1):161- 173.
[5] 高帅,毕洁颖.农村人口动态多维贫困:状态持续与转变.中国人口?资源与环境,2016,26(2):76- 83.
[6] 刘彦随,周扬,刘继来.中国农村贫困化地域分异特征及其精准扶贫策略.中国科学院院刊,2016,31(3):269- 278.
[7] Jalan J,Ravallion M.Geographic poverty traps?A micro model of consumption growth in rural China.Journal of Applied Econometrics,2002,17(4):329- 346.
[8] Fischer M M,Stirb?ck C.Pan-European regional income growth and club-convergence:insights from a spatial econometric perspective.The Annals of Regional Science,2006,40(4):693- 721.
[9] Gray L C,Moseley W G.A geographical perspective on poverty-environment interactions.The Geographical Journal,2005,171(1):9- 23.
[10] Deaton B J,Niman E.An empirical examination of the relationship between mining employment and poverty in the Appalachian region.Applied Economics,2012,44(3):303- 312.
[11] Shoji M,Aoyagi K,Kasahara R,Sawada Y,Ueyama M.Social capital formation and credit access:evidence from Sri Lanka.World Development,2012,40(12):2522- 2536.
[12] Fafchamps M,Shilpi F.Subjective welfare,isolation,and relative consumption.Journal of Development Economics,2008,86(1):43- 60.
[13] Olivia S,Gibson J,Rozelle S,Huang J.Mapping poverty in rural china:how much does the environment matter?Environment and Development Economics,2011,16(2):129- 153.
[14] Imran M,Stein A,Zurita-milla R.Investigating rural poverty and marginality in Burkina Faso using remote sensing-based products.International Journal of Applied Earth Observation and Geoinformation,2014,26:322- 334.
[15] Agostini C A,Brown P H.Cash transfers and poverty reduction in Chile.Journal of Regional Science,2011,51(3):604- 625.
[16] Park A,Wang S G.Community-based development and poverty alleviation:an evaluation of China′s poor village investment program.Journal of Public Economics,2010,94(9/10):790- 799.
[17] 牛亚琼,王生林.甘肃省脆弱生态环境与贫困的耦合关系.生态学报,2017,37(19):6431- 6439.
[18] 祁新华,叶士琳,程煜,林荣平.生态脆弱区贫困与生态环境的博弈分析.生态学报,2013,33(19):6411- 6417.
[19] 刘艳华,徐勇.中国农村多维贫困地理识别及类型划分.地理学报,2015,70(6):993- 1007.
[20] 刘小鹏,李永红,王亚娟,郭占军,郑芳.县域空间贫困的地理识别研究——以宁夏泾源县为例.地理学报,2017,72(3):545- 557.
[21] Zhang Y T,Li J M,Chang S L,Li X,Lu J J.Spatial distribution pattern of Picea schrenkiana population in the Middle Tianshan Mountains and the relationship with topographic attributes.Journal of Arid Land,2012,4(4):457- 468.
[22] 周蕾,熊礼阳,王一晴,周秀慧,杨莉.中国贫困县空间格局与地形的空间耦合关系.经济地理,2017,37(10):157- 166.
[23] 潘竟虎,赵宏宇,董磊磊.基于DMSP-OLS数据和可持续生计的中国农村多维贫困空间识别.生态学报,2018,38(17):6180- 6193.
[24] 陈烨烽,王艳慧,王小林.中国贫困村测度与空间分布特征分析.地理研究,2016,35(12):2298- 2308.
[25] 周扬,郭远智,刘彦随.中国县域贫困综合测度及2020年后减贫瞄准.地理学报,2018,73(8):1478- 1493.
[26] 王永明,王美霞,吴殿廷,赵林,丁建军.贵州省乡村贫困空间格局与形成机制分析.地理科学,2017,37(2):217- 227.
[27] 武鹏,李同昇,李卫民.县域农村贫困化空间分异及其影响因素——以陕西山阳县为例.地理研究,2018,37(3):593- 606.
[28] 文琦,施琳娜,马彩虹,王永生.黄土高原村域多维贫困空间异质性研究——以宁夏彭阳县为例.地理学报,2018,73(10):1850- 1864.
[29] 迟瑶,王艳慧,房娜.连片特困区贫困县农村基本公共服务与县域经济时空格局演变关系研究.地理研究,2016,35(7):1243- 1258.
[30] Rey S J,Janikas M V.STARS:space-time analysis of regional systems.Geographical Analysis,2006,38(1):67- 86.
[31] Ye X Y,Carroll M C.Exploratory space-time analysis of local economic development.Applied Geography,2011,31(3):1049- 1058.
[32] 陈起伟,熊康宁,兰安军.基于3S的贵州喀斯特石漠化遥感监测研究.干旱区资源与环境,2014,28(3):62- 67.
[33] 谢雅婷,周忠发,闫利会,牛颖超,王历.贵州省石漠化敏感区生态红线空间分异与管控措施研究.长江流域资源与环境,2017,26(4):624- 630.
[34] 贵州省第六次全国人口普查领导小组办公室.贵州省2010年人口普查资料.北京:中国统计出版社,2012.
[35] 贵州省统计局,国家统计局贵州调查总队.贵州统计年鉴2016.北京:中国统计出版社,2016.
[36] 马荣华,蒲英霞,马晓冬.GIS空间关联模式发现.北京:科学出版社,2007.
[37] Ye X Y,Rey S.A framework for exploratory space-time analysis of economic data.The Annals of Regional Science,2013,50(1):315- 339.
[38] Murray A T,Liu Y,Rey S J,Anselin L.Exploring movement object patterns.The Annals of Regional Science,2012,49(2):471- 484.
[39] Ye X Y.Comparative Space Time Dynamics[D].Santa Barbara:University of California,2010:34- 39.
[40] Rey S J.Spatial empirics for economic growth and convergence.Geographical Analysis,2001,33(3):195- 214.
[41] Elhorst J P.Matlab software for spatial panels.International Regional Science Review,2014,37(3):389- 405.
[42] 程叶青,王哲野,马靖.中国区域创新的时空动态分析.地理学报,2014,69(12):1779- 1789.
[43] Rey S J.Spatial analysis of regional income inequality//Goodchild M F,Janelle D G,eds.Spatially Integrated Social Science:Examples in Best Practice.Oxford:Oxford University Press,2004:280- 299.
[44] Wang J F,Li X H,Christakos G,Liao Y L,Zhang T,Gu X,Zheng X Y.Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region,China.International Journal of Geographical Information Science,2010,24(1):107- 127.
[45] Li X W,Xie Y F,Wang J F,Christakos G,Si J L,Zhao H N,Ding Y Q,Li J.Influence of planting patterns on Fluoroquinolone residues in the soil of an intensive vegetable cultivation area in northern China.Science of the Total Environment,2013,458- 460:63- 69.
[46] 王劲峰,徐成东.地理探测器:原理与展望.地理学报,2017,72(1):116- 134.
[47] 杨慧敏,罗庆,李小建.河南省县域贫困程度及影响因素分析.人文地理,2017,32(5):48- 55.
[48] 张世兵,丰凤.贵州省农民工城市化对农村的减贫效应.经济地理,2016,36(11):141- 145.
[2] Liu Y S,Liu J L,Zhou Y.Spatio-temporal patterns of rural poverty in China and targeted poverty alleviation strategies.Journal of Rural Studies,2017,52:66- 75.
[3] 赵雪雁,马艳艳,陈欢欢,高志玉,薛冰.干旱区内陆河流域农村多维贫困的时空格局及影响因素——以石羊河流域为例.经济地理,2018,38(2):140- 147.
[4] 刘彦随,李进涛.中国县域农村贫困化分异机制的地理探测与优化决策.地理学报,2017,72(1):161- 173.
[5] 高帅,毕洁颖.农村人口动态多维贫困:状态持续与转变.中国人口?资源与环境,2016,26(2):76- 83.
[6] 刘彦随,周扬,刘继来.中国农村贫困化地域分异特征及其精准扶贫策略.中国科学院院刊,2016,31(3):269- 278.
[7] Jalan J,Ravallion M.Geographic poverty traps?A micro model of consumption growth in rural China.Journal of Applied Econometrics,2002,17(4):329- 346.
[8] Fischer M M,Stirb?ck C.Pan-European regional income growth and club-convergence:insights from a spatial econometric perspective.The Annals of Regional Science,2006,40(4):693- 721.
[9] Gray L C,Moseley W G.A geographical perspective on poverty-environment interactions.The Geographical Journal,2005,171(1):9- 23.
[10] Deaton B J,Niman E.An empirical examination of the relationship between mining employment and poverty in the Appalachian region.Applied Economics,2012,44(3):303- 312.
[11] Shoji M,Aoyagi K,Kasahara R,Sawada Y,Ueyama M.Social capital formation and credit access:evidence from Sri Lanka.World Development,2012,40(12):2522- 2536.
[12] Fafchamps M,Shilpi F.Subjective welfare,isolation,and relative consumption.Journal of Development Economics,2008,86(1):43- 60.
[13] Olivia S,Gibson J,Rozelle S,Huang J.Mapping poverty in rural china:how much does the environment matter?Environment and Development Economics,2011,16(2):129- 153.
[14] Imran M,Stein A,Zurita-milla R.Investigating rural poverty and marginality in Burkina Faso using remote sensing-based products.International Journal of Applied Earth Observation and Geoinformation,2014,26:322- 334.
[15] Agostini C A,Brown P H.Cash transfers and poverty reduction in Chile.Journal of Regional Science,2011,51(3):604- 625.
[16] Park A,Wang S G.Community-based development and poverty alleviation:an evaluation of China′s poor village investment program.Journal of Public Economics,2010,94(9/10):790- 799.
[17] 牛亚琼,王生林.甘肃省脆弱生态环境与贫困的耦合关系.生态学报,2017,37(19):6431- 6439.
[18] 祁新华,叶士琳,程煜,林荣平.生态脆弱区贫困与生态环境的博弈分析.生态学报,2013,33(19):6411- 6417.
[19] 刘艳华,徐勇.中国农村多维贫困地理识别及类型划分.地理学报,2015,70(6):993- 1007.
[20] 刘小鹏,李永红,王亚娟,郭占军,郑芳.县域空间贫困的地理识别研究——以宁夏泾源县为例.地理学报,2017,72(3):545- 557.
[21] Zhang Y T,Li J M,Chang S L,Li X,Lu J J.Spatial distribution pattern of Picea schrenkiana population in the Middle Tianshan Mountains and the relationship with topographic attributes.Journal of Arid Land,2012,4(4):457- 468.
[22] 周蕾,熊礼阳,王一晴,周秀慧,杨莉.中国贫困县空间格局与地形的空间耦合关系.经济地理,2017,37(10):157- 166.
[23] 潘竟虎,赵宏宇,董磊磊.基于DMSP-OLS数据和可持续生计的中国农村多维贫困空间识别.生态学报,2018,38(17):6180- 6193.
[24] 陈烨烽,王艳慧,王小林.中国贫困村测度与空间分布特征分析.地理研究,2016,35(12):2298- 2308.
[25] 周扬,郭远智,刘彦随.中国县域贫困综合测度及2020年后减贫瞄准.地理学报,2018,73(8):1478- 1493.
[26] 王永明,王美霞,吴殿廷,赵林,丁建军.贵州省乡村贫困空间格局与形成机制分析.地理科学,2017,37(2):217- 227.
[27] 武鹏,李同昇,李卫民.县域农村贫困化空间分异及其影响因素——以陕西山阳县为例.地理研究,2018,37(3):593- 606.
[28] 文琦,施琳娜,马彩虹,王永生.黄土高原村域多维贫困空间异质性研究——以宁夏彭阳县为例.地理学报,2018,73(10):1850- 1864.
[29] 迟瑶,王艳慧,房娜.连片特困区贫困县农村基本公共服务与县域经济时空格局演变关系研究.地理研究,2016,35(7):1243- 1258.
[30] Rey S J,Janikas M V.STARS:space-time analysis of regional systems.Geographical Analysis,2006,38(1):67- 86.
[31] Ye X Y,Carroll M C.Exploratory space-time analysis of local economic development.Applied Geography,2011,31(3):1049- 1058.
[32] 陈起伟,熊康宁,兰安军.基于3S的贵州喀斯特石漠化遥感监测研究.干旱区资源与环境,2014,28(3):62- 67.
[33] 谢雅婷,周忠发,闫利会,牛颖超,王历.贵州省石漠化敏感区生态红线空间分异与管控措施研究.长江流域资源与环境,2017,26(4):624- 630.
[34] 贵州省第六次全国人口普查领导小组办公室.贵州省2010年人口普查资料.北京:中国统计出版社,2012.
[35] 贵州省统计局,国家统计局贵州调查总队.贵州统计年鉴2016.北京:中国统计出版社,2016.
[36] 马荣华,蒲英霞,马晓冬.GIS空间关联模式发现.北京:科学出版社,2007.
[37] Ye X Y,Rey S.A framework for exploratory space-time analysis of economic data.The Annals of Regional Science,2013,50(1):315- 339.
[38] Murray A T,Liu Y,Rey S J,Anselin L.Exploring movement object patterns.The Annals of Regional Science,2012,49(2):471- 484.
[39] Ye X Y.Comparative Space Time Dynamics[D].Santa Barbara:University of California,2010:34- 39.
[40] Rey S J.Spatial empirics for economic growth and convergence.Geographical Analysis,2001,33(3):195- 214.
[41] Elhorst J P.Matlab software for spatial panels.International Regional Science Review,2014,37(3):389- 405.
[42] 程叶青,王哲野,马靖.中国区域创新的时空动态分析.地理学报,2014,69(12):1779- 1789.
[43] Rey S J.Spatial analysis of regional income inequality//Goodchild M F,Janelle D G,eds.Spatially Integrated Social Science:Examples in Best Practice.Oxford:Oxford University Press,2004:280- 299.
[44] Wang J F,Li X H,Christakos G,Liao Y L,Zhang T,Gu X,Zheng X Y.Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region,China.International Journal of Geographical Information Science,2010,24(1):107- 127.
[45] Li X W,Xie Y F,Wang J F,Christakos G,Si J L,Zhao H N,Ding Y Q,Li J.Influence of planting patterns on Fluoroquinolone residues in the soil of an intensive vegetable cultivation area in northern China.Science of the Total Environment,2013,458- 460:63- 69.
[46] 王劲峰,徐成东.地理探测器:原理与展望.地理学报,2017,72(1):116- 134.
[47] 杨慧敏,罗庆,李小建.河南省县域贫困程度及影响因素分析.人文地理,2017,32(5):48- 55.
[48] 张世兵,丰凤.贵州省农民工城市化对农村的减贫效应.经济地理,2016,36(11):141- 145.