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Article(id=1276601491909636811, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1276601397818814642, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-2561.2025.01.024, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1723392000000, receivedDateStr=2024-08-12, revisedDate=1724169600000, revisedDateStr=2024-08-21, acceptedDate=null, acceptedDateStr=null, onlineDate=1782295113780, onlineDateStr=2026-06-24, pubDate=1737734400000, pubDateStr=2025-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1782295113780, onlineIssueDateStr=2026-06-24, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1782295113780, creator=13701087609, updateTime=1782295113780, updator=13701087609, issue=Issue{id=1276601397818814642, tenantId=1146029695717560320, journalId=1235980609244409860, year='2025', volume='46', issue='1', pageStart='1', pageEnd='245', issueExtLink='null', onlineDate='null', pubDate='1737734400000', pubDateStr='2025-01-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1782295091347, creator='13701087609', updateTime=1782295207335, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1276601884408418422, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1276601397818814642, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1276601884408418423, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1276601397818814642, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=236, endPage=245, ext={EN=ArticleExt(id=1276601492182266573, articleId=1276601491909636811, tenantId=1146029695717560320, journalId=1235980609244409860, language=EN, title=Temporal and Spatial Characteristics and Influencing Factors of Agricultural Ecological Efficiency in Hainan Province, columnId=1237814980427444960, journalTitle=Chinese Journal of Tropical Crops, columnName=Post-harvest Treatment & Agricultural Ecology, runingTitle=null, highlight=null, articleAbstract=

Based on the panel data of 18 cities (counties) in Hainan, China from 2012 to 2022, combining the non-expected output super efficiency SBM model and Tobit regression mode, this paper analyzed the spatial and temporal evolution characteristics of agricultural eco-efficiency and influencing factors of agricultural ecological efficiency in cities (counties) of Hainan. From 2012 to 2022, the average agricultural eco-efficiency in Hainan showed obvious grading characteristics of central region>western region>eastern region. The agricultural eco-efficiency at the county scale of Hainan improved significantly year by year. The average agricultural eco-efficiency was 0.541, and the number of cities (counties) above the average value was 7. In terms of spatial change, the overall distribution characteristics of agricultural eco-efficiency were “spreading from the middle to the east and west”, and the distribution characteristics of full efficiency and high efficiency were block and chain. The cities (counties) with medium efficiency were distributed around the cities and counties with full efficiency and high efficiency. The trend lines in the north-south direction and the east-west direction showed the characteristics of inverted U-shape. The temporal and spatial evolution of agricultural eco-efficiency in Hainan at the provincial scale was influenced by several key factors, including the level of farmers’ income, intensity of agricultural mechanization, use of agricultural chemicals, and urbanization rate. At different regional scales, farmers’ income level was the main factor affecting agricultural eco-efficiency in the eastern region, while urbanization rate, intensity of agricultural chemical input use and farmland irrigation rate were the main factors affecting agricultural eco-efficiency in the central region. Urbanization rate, farmers’ income level, agricultural industrial structure, intensity of use of agricultural chemical inputs and farmland irrigation rate were the main factors affecting agricultural eco-efficiency in the western region. On the whole, the agricultural eco-efficiency of all cities (counties) in Hainan showed an upward trend, and there were some differences in the agricultural eco-efficiency among different regions. In the future, we should explore the priorities of agricultural development in different regions according to local conditions to effectively improve agricultural eco-efficiency.

, authors=null, authorsList=Weihong LIANG, Chunmei DENG, Lu YE, Yanqun LIU, Danyang WANG, Yuping LI, authorCompany=null, correspAuthors=Yuping LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1276601496091357929, articleId=1276601491909636811, tenantId=1146029695717560320, journalId=1235980609244409860, language=CN, title=海南省农业生态效率时空特征及影响因素研究, columnId=1237016045714723050, journalTitle=热带作物学报, columnName=采后处理与农业生态, runingTitle=null, highlight=null, articleAbstract=

基于海南省18个市（县）2012—2022年县域行政单元农业面板数据，运用非期望产出超效率SBM模型，结合空间相关性分析方法，分析海南省农业生态效率时空演变特征，并利用Tobit回归模型探究其影响因素。结果表明：（1）2012—2022年，海南省农业生态效率均值呈现中部地区>西部地区>东部地区的明显分级特征；海南省市（县）域尺度农业生态效率逐年明显改善，农业生态效率均值为0.541，达到均值以上的市（县）数为7个。（2）空间变化上，总体呈现中部向东西部扩散的空间分布特征，同时完全有效和效率较高呈现块状和链条式分布特征，效率中等类型市（县）围绕着完全有效和效率较高市（县）分布；南北方向和东西方向的投影趋势线均呈现倒“U”型特征。（3）在省域尺度下，农民收入水平、农业机械化强度、农业化学投入品使用强度和城镇化率是对海南省农业生态效率时空演变产生影响的主要因素；在不同区域尺度下，农民收入水平是对东部地区农业生态效率产生影响的主要因素，城镇化率、农业化学投入品使用强度和农田灌溉率是对中部地区农业生态效率产生影响的主要因素，城镇化率、农民收入水平、农业产业结构、农业化学投入品使用强度和农田灌溉率是对西部地区农业生态效率产生影响的主要因素。总体而言，海南省各市（县）农业生态效率整体呈上升趋势，各区域农业生态效率存在一定差异。未来应因地制宜探索不同地区农业发展重点，切实提升农业生态效率。

, authors=

梁伟红（1978—），女，硕士，副研究员，研究方向：农业数据分析。

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* 李玉萍（LI Yuping），E-mail：。
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梁伟红（1978—），女，硕士，副研究员，研究方向：农业数据分析。

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梁伟红（1978—），女，硕士，副研究员，研究方向：农业数据分析。

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(in Chinese), articleTitle=Spatial and temporal characteristics and influencing factors of agricultural eco-efficiency in Inner Mongolia, refAbstract=null), Reference(id=1276601879136170627, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, doi=null, pmid=null, pmcid=null, year=2022, volume=6, issue=3, pageStart=10, pageEnd=18, url=null, language=null, rfNumber=[28], rfOrder=51, authorNames=赵吉, 党国英, 唐夏俊, journalName=西南林业大学学报(社会科学), refType=null, unstructuredReference=赵吉, 党国英, 唐夏俊. 基于SBM-Tobit模型的中国农业生态效率时空差异及影响因素研究[J]. 西南林业大学学报(社会科学), 2022, 6(3): 10-18, articleTitle=基于SBM-Tobit模型的中国农业生态效率时空差异及影响因素研究, refAbstract=null), Reference(id=1276601879203279492, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, doi=null, pmid=null, pmcid=null, year=2022, volume=6, issue=3, pageStart=10, pageEnd=18, url=null, language=null, rfNumber=[28], rfOrder=52, authorNames=ZHAO J, DANG G Y, TANG X J, journalName=Journal of Southwest Forestry University (Social Sciences), refType=null, unstructuredReference=ZHAO J, DANG G Y, TANG X J. Spatial-temporal differences and influencing factors of agricultural eco-efficiency in China based on SBM-Tobit model[J]. Journal of Southwest Forestry University (Social Sciences), 2022, 6(3): 10-18. (in Chinese), articleTitle=Spatial-temporal differences and influencing factors of agricultural eco-efficiency in China based on SBM-Tobit model, refAbstract=null)], funds=[Fund(id=1276601873410945613, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, awardId=721RC630, language=CN, fundingSource=海南省自然科学基金高层次人才项目(721RC630), fundOrder=null, country=null), Fund(id=1276601873478054478, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, awardId=HNSK（YB）22-14, language=CN, fundingSource=海南省哲学社会科学规划课题(HNSK（YB）22-14), fundOrder=null, country=null), Fund(id=1276601873561940559, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, awardId=622MS115, language=CN, fundingSource=海南省自然科学基金项目(622MS115), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1276601857703277070, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, xref=null, ext=[AuthorCompanyExt(id=1276601857715859983, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, companyId=1276601857703277070, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Scientific and Technical Information, Chinese Academy of Tropical Agricultural Sciences / Key Laboratory of Practical Research on Tropical Crops Information Technology in Hainan, Haikou, Hainan 571101, China), AuthorCompanyExt(id=1276601857724248592, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, companyId=1276601857703277070, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国热带农业科学院科技信息研究所/海南省热带作物信息技术应用研究重点实验室，海南海口　571101)])], figs=[ArticleFig(id=1276601870504292925, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=EN, label=Fig. 1, caption=Average agricultural eco-efficiency of cities and counties in Hainan from 2012 to 2022, figureFileSmall=wAU76C02KTK4o3lK+dajMA==, figureFileBig=FxWA+Q6LnRx0bYmws4H28w==, tableContent=null), ArticleFig(id=1276601870592373310, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=CN, label=图1, caption=2012—2022年海南省各市（县）农业生态效率均值, figureFileSmall=wAU76C02KTK4o3lK+dajMA==, figureFileBig=FxWA+Q6LnRx0bYmws4H28w==, tableContent=null), ArticleFig(id=1276601870693036607, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=EN, label=Fig. 2, caption=Agricultural eco-efficiency in eastern, central and western Hainan from 2012 to 2022, figureFileSmall=mptDzm8NWSdYDz2D5NHTjw==, figureFileBig=8wrvI+F0n5F6nOrx1wfDgw==, tableContent=null), ArticleFig(id=1276601870764339776, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=CN, label=图2, caption=2012—2022年海南省东部、中部、西部地区农业生态效率值, figureFileSmall=mptDzm8NWSdYDz2D5NHTjw==, figureFileBig=8wrvI+F0n5F6nOrx1wfDgw==, tableContent=null), ArticleFig(id=1276601870844031553, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=EN, label=Fig. 3, caption=Spatial pattern of agricultural eco-efficiency in Hainan from 2012 to 2022, figureFileSmall=/JRkB6exnfUuN2HVTDLIPw==, figureFileBig=B4Lvm0x5Ey/W99gE8KweFA==, tableContent=null), ArticleFig(id=1276601870927917634, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=CN, label=图3, caption=2012—2022年海南省农业生态效率空间格局, figureFileSmall=/JRkB6exnfUuN2HVTDLIPw==, figureFileBig=B4Lvm0x5Ey/W99gE8KweFA==, tableContent=null), ArticleFig(id=1276601871053746755, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=EN, label=Fig. 4, caption=Overall trend of agricultural eco-efficiency in Hainan from 2012 to 2022

X-axis and Y-axis represent the trends of agroecological efficiency in east-west direction and north-south direction respectively; Z-axis represents the agroecological efficiency value.

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X轴、Y轴分别表示农业生态效率在东西方向和南北方向的趋势；Z轴表示农业生态效率值。

, figureFileSmall=wUqu90f4lqeNsjsBCht+8w==, figureFileBig=YYRtEO9lAwEguaFGCyCO5w==, tableContent=null), ArticleFig(id=1276601871187964485, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=EN, label=Tab. 1, caption=

Index system of agricultural eco-efficiency in Hainan

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标Primary index二级指标Secondary index变量及说明Variable explanation
要素投入劳动力投入农林牧渔业从业人员×(农业总产值/农林牧渔业总产值)（人）
机械投入农业机械总动力（kW）
水资源投入有效灌溉面积（hm2）
土地投入农作物总播种面积（hm2）
化肥投入化肥使用量（t）
农药投入农药使用量（t）
农膜投入农膜使用量（t）
期望产出农业产出农业总产值（万元）
非期望产出农业碳排放化肥、农药、农膜、农业播种、农业灌溉等碳源数据乘以对应系数的碳排放总和（t）[18]
污染物排放量化肥氮、磷流失，农药、农膜残留总量（t）[19]
), ArticleFig(id=1276601871263461958, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=CN, label=表1, caption=

海南省农业生态效率指标体系

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标Primary index二级指标Secondary index变量及说明Variable explanation
要素投入劳动力投入农林牧渔业从业人员×(农业总产值/农林牧渔业总产值)（人）
机械投入农业机械总动力（kW）
水资源投入有效灌溉面积（hm2）
土地投入农作物总播种面积（hm2）
化肥投入化肥使用量（t）
农药投入农药使用量（t）
农膜投入农膜使用量（t）
期望产出农业产出农业总产值（万元）
非期望产出农业碳排放化肥、农药、农膜、农业播种、农业灌溉等碳源数据乘以对应系数的碳排放总和（t）[18]
污染物排放量化肥氮、磷流失，农药、农膜残留总量（t）[19]
), ArticleFig(id=1276601871338959431, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=EN, label=Tab. 2, caption=

Global spatial auto-correlation Moran’s I of agricultural eco-efficiency in Hainan

, figureFileSmall=null, figureFileBig=null, tableContent=
项目Item2012201320142016201720182019202020212022
Moran’s I0.1350.0170.1260.2430.1520.1420.1690.1480.0710.188
Z值1.3710.5481.3742.2811.8071.4081.6431.4390.8902.114
P值0.1700.5840.1690.0220.0710.1590.1000.1500.3740.035
), ArticleFig(id=1276601871418651208, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=CN, label=表2, caption=

海南省农业生态效率全局空间自相关Moran’s I

, figureFileSmall=null, figureFileBig=null, tableContent=
项目Item2012201320142016201720182019202020212022
Moran’s I0.1350.0170.1260.2430.1520.1420.1690.1480.0710.188
Z值1.3710.5481.3742.2811.8071.4081.6431.4390.8902.114
P值0.1700.5840.1690.0220.0710.1590.1000.1500.3740.035
), ArticleFig(id=1276601871485760073, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=EN, label=Tab. 3, caption=

Tobit regression results of influencing factors of agricultural eco-efficiency in Hainan

, figureFileSmall=null, figureFileBig=null, tableContent=
解释变量Explanatory variable系数Coefficient标准差Standard deviationZ值Z valuae显著性水平Significance level
城镇化率（X1）–0.00690810.0039100–1.77*
农民收入水平（X2）0.00002967.96e-063.72***
农业规模化水平（X3）0.11006970.12197650.90
农业产业结构（X4）0.00600730.00435681.38
农业化学投入品使用强度（X5）–0.00009580.0000486–1.97**
农业机械密度（X6）0.01671380.00743742.25**
农田灌溉率（X7）0.00357310.00297441.20
), ArticleFig(id=1276601871557063242, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=CN, label=表3, caption=

海南省农业生态效率影响因素Tobit回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=
解释变量Explanatory variable系数Coefficient标准差Standard deviationZ值Z valuae显著性水平Significance level
城镇化率（X1）–0.00690810.0039100–1.77*
农民收入水平（X2）0.00002967.96e-063.72***
农业规模化水平（X3）0.11006970.12197650.90
农业产业结构（X4）0.00600730.00435681.38
农业化学投入品使用强度（X5）–0.00009580.0000486–1.97**
农业机械密度（X6）0.01671380.00743742.25**
农田灌溉率（X7）0.00357310.00297441.20
), ArticleFig(id=1276601873201230411, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=EN, label=Tab. 4, caption=

Tobit regression results of influencing factors of agricultural eco-efficiency in different regions of Hainan province

, figureFileSmall=null, figureFileBig=null, tableContent=
解释变量Explanatory variable东部地区Eastern region中部地区Central region西部地区Western region
城镇化率（X1）–0.00358000–0.02880000*0.00896000***
(0.00231000)(0.01720000)(0.00342000)
农民收入水平（X2）0.00003440***–0.000001910.00001430*
(0.00001040)(0.00002370)(0.00000775)
农业规模化水平（X3）–0.033300000.270000000.45600000***
(0.25300000)(0.53200000)(0.08680000)
农业产业结构（X4）0.00872000–0.016100000.01340000***
(0.00703000)(0.01460000)(0.00215000)
农业化学投入品使用强度（X5）–0.00002970–0.00038500***–0.00014300***
(0.00003760)(0.00013900)(0.00004700)
农业机械密度（X6）–0.004940000.04930000–0.00920000
(0.01110000)(0.03130000)(0.00596000)
农田灌溉率（X7）0.001740000.03070000**0.03330000***
(0.00302000)(0.01430000)(0.00666000)
), ArticleFig(id=1276601873276727884, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276601491909636811, language=CN, label=表4, caption=

海南省不同区域农业生态效率影响因素Tobit回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=
解释变量Explanatory variable东部地区Eastern region中部地区Central region西部地区Western region
城镇化率（X1）–0.00358000–0.02880000*0.00896000***
(0.00231000)(0.01720000)(0.00342000)
农民收入水平（X2）0.00003440***–0.000001910.00001430*
(0.00001040)(0.00002370)(0.00000775)
农业规模化水平（X3）–0.033300000.270000000.45600000***
(0.25300000)(0.53200000)(0.08680000)
农业产业结构（X4）0.00872000–0.016100000.01340000***
(0.00703000)(0.01460000)(0.00215000)
农业化学投入品使用强度（X5）–0.00002970–0.00038500***–0.00014300***
(0.00003760)(0.00013900)(0.00004700)
农业机械密度（X6）–0.004940000.04930000–0.00920000
(0.01110000)(0.03130000)(0.00596000)
农田灌溉率（X7）0.001740000.03070000**0.03330000***
(0.00302000)(0.01430000)(0.00666000)
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海南省农业生态效率时空特征及影响因素研究
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梁伟红 , 邓春梅 , 叶露 , 刘燕群 , 王丹阳 , 李玉萍 *
热带作物学报 | 采后处理与农业生态 2025,46(1): 236-245
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热带作物学报 |采后处理与农业生态 2025 , 46 (1) : 236 -245
海南省农业生态效率时空特征及影响因素研究
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梁伟红, 邓春梅, 叶露, 刘燕群, 王丹阳, 李玉萍*
作者信息
  • 中国热带农业科学院科技信息研究所/海南省热带作物信息技术应用研究重点实验室，海南海口　571101
通讯作者:
* 李玉萍（LI Yuping），E-mail：。
Temporal and Spatial Characteristics and Influencing Factors of Agricultural Ecological Efficiency in Hainan Province
Weihong LIANG, Chunmei DENG, Lu YE, Yanqun LIU, Danyang WANG, Yuping LI*
Affiliations
  • Institute of Scientific and Technical Information, Chinese Academy of Tropical Agricultural Sciences / Key Laboratory of Practical Research on Tropical Crops Information Technology in Hainan, Haikou, Hainan 571101, China
出版时间: 2025-01-25 doi: 10.3969/j.issn.1000-2561.2025.01.024
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摘要
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基于海南省18个市（县）2012—2022年县域行政单元农业面板数据，运用非期望产出超效率SBM模型，结合空间相关性分析方法，分析海南省农业生态效率时空演变特征，并利用Tobit回归模型探究其影响因素。结果表明：（1）2012—2022年，海南省农业生态效率均值呈现中部地区>西部地区>东部地区的明显分级特征；海南省市（县）域尺度农业生态效率逐年明显改善，农业生态效率均值为0.541，达到均值以上的市（县）数为7个。（2）空间变化上，总体呈现中部向东西部扩散的空间分布特征，同时完全有效和效率较高呈现块状和链条式分布特征，效率中等类型市（县）围绕着完全有效和效率较高市（县）分布；南北方向和东西方向的投影趋势线均呈现倒“U”型特征。（3）在省域尺度下，农民收入水平、农业机械化强度、农业化学投入品使用强度和城镇化率是对海南省农业生态效率时空演变产生影响的主要因素；在不同区域尺度下，农民收入水平是对东部地区农业生态效率产生影响的主要因素，城镇化率、农业化学投入品使用强度和农田灌溉率是对中部地区农业生态效率产生影响的主要因素，城镇化率、农民收入水平、农业产业结构、农业化学投入品使用强度和农田灌溉率是对西部地区农业生态效率产生影响的主要因素。总体而言，海南省各市（县）农业生态效率整体呈上升趋势，各区域农业生态效率存在一定差异。未来应因地制宜探索不同地区农业发展重点，切实提升农业生态效率。

农业生态效率  /  影响因素  /  超效率SBM模型  /  Tobit模型  /  海南省

Based on the panel data of 18 cities (counties) in Hainan, China from 2012 to 2022, combining the non-expected output super efficiency SBM model and Tobit regression mode, this paper analyzed the spatial and temporal evolution characteristics of agricultural eco-efficiency and influencing factors of agricultural ecological efficiency in cities (counties) of Hainan. From 2012 to 2022, the average agricultural eco-efficiency in Hainan showed obvious grading characteristics of central region>western region>eastern region. The agricultural eco-efficiency at the county scale of Hainan improved significantly year by year. The average agricultural eco-efficiency was 0.541, and the number of cities (counties) above the average value was 7. In terms of spatial change, the overall distribution characteristics of agricultural eco-efficiency were “spreading from the middle to the east and west”, and the distribution characteristics of full efficiency and high efficiency were block and chain. The cities (counties) with medium efficiency were distributed around the cities and counties with full efficiency and high efficiency. The trend lines in the north-south direction and the east-west direction showed the characteristics of inverted U-shape. The temporal and spatial evolution of agricultural eco-efficiency in Hainan at the provincial scale was influenced by several key factors, including the level of farmers’ income, intensity of agricultural mechanization, use of agricultural chemicals, and urbanization rate. At different regional scales, farmers’ income level was the main factor affecting agricultural eco-efficiency in the eastern region, while urbanization rate, intensity of agricultural chemical input use and farmland irrigation rate were the main factors affecting agricultural eco-efficiency in the central region. Urbanization rate, farmers’ income level, agricultural industrial structure, intensity of use of agricultural chemical inputs and farmland irrigation rate were the main factors affecting agricultural eco-efficiency in the western region. On the whole, the agricultural eco-efficiency of all cities (counties) in Hainan showed an upward trend, and there were some differences in the agricultural eco-efficiency among different regions. In the future, we should explore the priorities of agricultural development in different regions according to local conditions to effectively improve agricultural eco-efficiency.

agricultural ecological efficiency  /  influencing factors  /  super-efficiency SBM model  /  Tobit model  /  Hainan province
梁伟红, 邓春梅, 叶露, 刘燕群, 王丹阳, 李玉萍. 海南省农业生态效率时空特征及影响因素研究. 热带作物学报, 2025 , 46 (1) : 236 -245 . DOI: 10.3969/j.issn.1000-2561.2025.01.024
Weihong LIANG, Chunmei DENG, Lu YE, Yanqun LIU, Danyang WANG, Yuping LI. Temporal and Spatial Characteristics and Influencing Factors of Agricultural Ecological Efficiency in Hainan Province[J]. Chinese Journal of Tropical Crops, 2025 , 46 (1) : 236 -245 . DOI: 10.3969/j.issn.1000-2561.2025.01.024
正文
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我国是农业大国，用全球11%的农业用地保障了世界18%的人口粮食供给，在国际上的基础地位尤为重要[1]。21世纪以来，我国农业经济高速增长，2000—2020年农业总产值年均增长率达5.94%[2]。然而在农业经济快速增长的同时，也产生了农业碳排放增加、农业面源污染加剧、农业生态系统退化等一系列问题[3]。在国家大力提倡绿色农业发展的背景下，如何扭转农业生产模式向绿色、高质量的可持续发展模式转换，保障农业经济和生态协调发展，已经成为当前农业发展面临的重要问题。农业生态效率是评估农业生产经济和生态综合效益的重要手段，近年来受到国内外学者的广泛关注。就评价方法而言，聂弯等[4]系统总结了农业生态效率的评价方法及其在不同尺度的应用。在研究方法上，主要有比值法[5]、生命周期评价法[6]、指标体系法[7-8]和模型分析法[9-10]等。TONE提出的超效率SBM模型被广泛应用于农业生态效率测算中，最初主要考虑将期望产出纳入指标体系，后来，为了进一步探究农业生态效率，很多学者将农业碳排放和农业面源污染等非期望产出纳入指标体系测算农业生态效率，该模型已经逐渐成为测度评价农业生态效率的主要模型[11-14]。在影响因素方面，主要采用灰色关联度模型、Tobit模型、空间面板STIRPAT模型等进行研究，其中应用最多的是Tobit回归模型[15-16]。研究尺度上，逐渐从全国、省级等层面逐渐转向市（县）层面甚至乡（镇）层面上，这说明农业生态效率研究越来越受到学者的重视。
近年来，作为全国重要的“菜篮子”“果盘子”供应地的海南省非常重视绿色农业的发展，2019年获评“国家农业绿色发展先行区”，制定了《海南省国家农业绿色发展规划（2019—2025年）》等一系列政策。但由于海南农业耕地复种指数高，化肥农药施用量较大、农业生产废弃物残留对土壤地力及农业生态环境造成一定破坏。因此，农业生态效率的提高对促进海南热带高效农业的可持续发展具有重要的意义。本研究基于海南省县域（三沙市除外）尺度数据，运用非期望产出SBM模型及面板Tobit模型测算2012—2022年海南省农业生态效率并分析其影响因素，以期为海南热带高效农业发展制定农业生态产业管理政策提供参考依据。
1　材料与方法
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1.1　研究区域与数据来源
研究区域为海南岛海口市、三亚市、五指山市、文昌市、琼海市、万宁市、定安县、屯昌县、澄迈县、临高县、儋州市、东方市、乐东黎族自治县、琼中黎族自治县、保亭黎族自治县、陵水黎族自治县、白沙黎族自治县、昌江黎族自治县18个市（县）。
数据主要来源于《中国农村统计年鉴》《海南省统计年鉴》以及各市（县）历年统计年鉴、统计公报、政府公布公开数据等材料，部分指标数据依据原始数据计算得出，个别缺失数据根据指标特征及数据趋势，通过插值法和几何增长率法等进行合理补充。
1.2　方法
1.2.1　非期望产出超效率SBM模型
采用考虑非期望产出的超效率SBM模型对海南省18个市（县）的农业生态效率水平进行测度，其具体模型表达公式如下：
式中，φ表示农业生态效率值；n表示海南省18个市（县）即18个决策单元；m、s1、s2分别表示投入、期望产出、非期望产出指标个数；、和分别为投入、期望产出和非期望产出的松弛变量；xik、、分别表示决策单元k的第i项投入、第w项期望产出、第g项的非期望产出值；Q为各个决策单元的权重向量。参照相关学者的研究[17]，将海南省各市（县）农业生态效率测算的结果划分为5个等级：φ<0.2为效率低，0.2≤φ<0.4为效率较低，0.4≤φ<0.6为效率中等，0.6≤φ<1为效率较高，φ≥1为效率完全有效。本研究运用Matlab软件，利用非期望产出的SBM模型，对海南省县域尺度农业生态效率进行测度分析。
根据已有研究并结合海南实际，选择10项投入产出指标来评价农业生态效率，其中投入指标包括劳动力、资源（土地、水资源）、环境（化肥、农药和地膜）。选取农业总产值来反映期望产出；为使农业生态效率测算结果更加准确和科学，选取农业碳排放和污染物排放来综合反映非期望产出（表1）。
1.2.2　全局空间自相关分析
全局空间自相关从宏观层面上判断农业生态效率在海南有无聚集性。为进一步研究海南省18个市（县）农业生态效率是否存在空间效应，对其进行全局空间自相关分析，全局空间自相关是根据海南省县域地理位置和农业生态效率值来研究全局空间依赖性和空间集聚程度，通常采用莫兰指数（Moron’s I）来衡量，其具体运算公式如下：
式中，Xi和Xj分别为第i个和第j个县域空间单元的农业生态效率值，为均值，n为观测单元18个市（县）单元数量，S2为样本方差；Wij为空间权重矩阵，代表县域间的邻近关系，当县域i与县域j有公共边界或节点时，Wij=1；当无公共边界或节点时，Wij=0，则相邻2个县域空间无空间关联。通过测算得出的莫兰指数、Z得分和P值确定海南省县域农业生态效率是否具有空间上的相关性，Moron’s I取值范围为[–1，1]，Moron’s I<0表示负相关，Moron’s I>0表示正相关，Moron’s I=0表示不相关，越接近–1或1则表示相关性越强。
1.2.3　面板Tobit模型
为了能够深入探索海南省农业生态效率的影响因素及其影响关系，参考相关专家学者的研究结果[15-16]，建立以农业生态效率值为因变量，影响因素为自变量的Tobit随机效应模型：
式中，被解释变量Tit表示第i个市（县）第t年的农业生态效率，且以受限的方式取值，当Tit>0时，取实际观测值，当Tit≤0时，观察值均截取为0，其中i（i=1，2，3，…18）代表海南省18个市（县），即决策单元；0b表示截距项，kb为估计系数，Xk为解释变量，即影响因素，k为影响因素的个数，Xk， it表示影响因素X，其中Xk为实际观测值，git表示随机误差。采用Stata 16软件，应用Tobit模型对海南省农业生态效率相关样本数据进行回归分析。
2　结果与分析
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2.1　海南省农业生态效率时序演化特征分析
2.1.1　市（县）级层面
2012—2022年海南省18个市（县）农业生态效率由低效率水平向高效率水平逐渐演变。2012年，海口、乐东和东方3个市（县）处于低效率水平，澄迈、儋州、东方、临高、陵水、琼海、三亚和万宁8个市（县）处于较低效率水平，昌江、定安和琼中3个县达到中等效率水平，仅有白沙、保亭、屯昌和五指山4个市（县）达到完全有效水平。到2022年，无市（县）处于较低效率水平及以下，仅有文昌处于中等效率水平，为0.539，海口处于较高水平效率值，为0.663，其他市（县）均达到完全有效水平。2012—2022年，五指山除2014年农业生态效率处于较高水平外，其他年份一直处于完全有效水平。基于海南市（县）尺度下的2012—2022年农业生态效率均值为0.541，表示实际产出水平相当于潜在产出水平的54.1%，各市（县）农业生态效率均值有较大差别，达到平均值以上的市县主要有昌江、五指山、白沙、定安、屯昌、琼中、保亭7个市（县）（图1）。
2.1.2　不同区域层面
基于2012—2022年海南省18个市（县）农业生态指标相关数据，测度海南省18个市（县）农业生态效率值。为了更直观了解不同区域的农业生态效率差异，通过分析发现海南东部、中部、西部地区11年来农业生态效率均呈现增长趋势，但也出现明显分级特征，即中部地区>西部地区>东部地区的分级特征。其中，中部地区的农业生态效率均值为0.765，达效率较高水平，主要是因为该区域具有优越的自然资源条件，是重点生态功能区；其次，东部地区和西部地区的农业生态效率均值差距不明显，分别为0.442和0.417，均处于中等效率水平。从时序上来看，中部地区呈现先降后升的趋势，西部和东部地区呈现明显快速提升趋势，中部地区在2012—2015年间呈现下降趋势，随后从2016年的0.692提升到2022年的1.03，达到完全有效状态；西部地区从2012年的0.259提升到2022年的1.034，也达到完全有效状态；东部地区从2012年的0.253提升到2022年的0.901，达到较高有效状态（图2）。
2.2　海南省农业生态效率空间变化特征
2.2.1　空间格局分析
选取2012年、2014年、2016年、2018年、2020年和2022年6个时间节点，利用ArcGIS软件对海南省各市（县）农业生态效率的空间分布和区域差异进行空间可视化处理（图3）。按照自然间断法将其分为效率低、效率较低、效率中等、效率较高和效率完全有效5个等级。从图3可以看出海南省农业生态效率总体呈现中部向东西部扩散的趋势。效率完全有效的市（县）数量由2012年的白沙、屯昌、五指山、保亭4个市（县）增至2022年的除海口和文昌以外的16个市（县），上升300%；效率较高的市（县）数量2012—2021年期间呈稳步增长趋势，而2022年仅海口1个市（县）为效率较高；效率中等和效率较低的市（县）数量分布呈现明显先升后降的趋势，效率中等和效率较低市（县）数量最高峰分别于2015年达到9个和2017年的10个。而出现效率低的年限仅在2012—2014年，且市（县）数均低于5个。说明海南省县域尺度农业生态效率逐年有明显改善。同时完全有效和效率较高呈现块状和链条式分布特征，效率中等类型市（县）围绕完全有效和效率较高市（县）分布，意味着海南省县域农业生态效率可能存在一定程度的空间依赖性。
为进一步了解海南省县域农业生态效率趋势走向，应用ArcGIS趋势分析工具，将各县域2012年、2014年、2016年、2018年、2020年和2022年的农业生态效率值作为高度属性转换为空间三维趋势图（图4）。由图4可知，6个时间截面上南北方向和东西方向农业生态效率的投影趋势线均呈现倒“U”型特征，而且呈现明显的南高北低、东低西高的趋势特征。
2.2.2　空间相关性分析
在空间自相关分析中，Z值是标准差的倍数，用于衡量莫兰指数（Moron’s I）与随机分布期望值之间的偏差。Z值的大小可以确定空间模式的显著性。P值表示概率，用于评估观测到的空间模式是由随机过程产生的可能性大小。由表2可知，2012—2022年海南省县域农业生态效率全局Moron’s I均大于0，说明海南省县域农业生态效率具有空间相关性，但仅有2016年、2017年和2022年表现为集聚格局。局部空间自相关分析结果显示，农业生态效率空间关联模式具有显著的空间变异特征。
2.3　农业生态效率影响因素分析
2.3.1　指标选取
通过梳理和归纳相关研究，发现影响农业生态效率的因素有很多，从整个农业发展角度来看，农业前期投入的要素均有可能对农业生态效率产生影响。借鉴、参考相关学者的研究[20-23]，并结合海南省县域数据的可获得性，选取城镇化率（%）、农民收入水平（元）、农业规模化水平（hm2/人）、农业产业结构（%）、农业化学投入品使用强度（kg/hm2）、农业机械密度（kW/hm2）、农田灌溉率（%）7个影响因素作为农业生态效率的影响因素研究的主要解释变量。
2.3.2　省域尺度农业生态效率影响因素分析
回归结果显示，城镇化率和农业化学投入品使用强度对海南省农业生态效率均呈显著负相关，分别通过了10%和5%的显著性检验；农民收入水平和农业机械密度对海南省农业生态效率呈显著正相关，分别通过了1%和5%的显著性检验；其他变量对海南省农业生态效率均具有正向作用，但作用不显著（表3）。从省级层面分析结果说明，随着城镇化的推进，农业人口向城镇转移，虽然为城镇建设提供了劳动力，促进了经济发展，但是这种劳动力的转移会影响农业生产的方式和效率，从而对农业生态效率产生负面影响。同时海南省农业投入品还存在过量或不合理使用情况。海南省机械化的投入对当地农业产值的增加和农业生态效率的刺激作用明显。
2.3.3　海南省不同区域农业生态效率影响因素的回归分析
考虑到海南省区域内部的自然地理和社会经济的异质性，本研究按照东部、中部和西部地区3个区域，进一步研究不同区域的影响因素对农业生态效率作用的差异性，以各地区数据分别用Stata 16软件带入模型得到回归结果（表4）。回归结果显示，海南省东部、中部及西部各区域农业生态效率的影响因素强度表现不一。农民收入水平在1%的显著性水平上对东部地区农业生态效率产生正向影响。城镇化率在10%的显著水平上对中部地区农业生态效率产生负向影响，农业化学投入品使用强度在1%的显著水平上对中部地区农业生态效率产生负向影响，农田灌溉率在5%的显著水平上对中部地区农业生态效率产生正向影响。城镇化率、农业规模化水平、农业产业结构和农田灌溉率在1%的显著水平上对西部地区农业生态效率产生正向影响，农民收入水平在10%的显著水平上对西部地区农业生态效率产生正向影响，农业化学投入品使用强度在1%的显著水平上对西部地区农业生态效率产生负向影响。
3　讨论
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本研究基于市（县）域尺度探究了海南省农业生态效率及其影响因素。从影响因素来看，农业产业结构、农民收入水平、农业规模化水平对提升农业生态效率具有正向作用，农业化学投入品使用强度对提升农业生态效率有负向作用，这与现有大部分学者的研究结论[14,24]基本一致。但城镇化率负向作用于农业生态效率，农业机械密度正向作用于农业生态效率的研究结论与现有相关研究[20,23,25]的结论有偏差，这主要是因为这二者选择的空间尺度不同，以及农业技术发展水平、研究样本所处的城镇化阶段不同。海南省应强化农业技术发展及推广，推动农业资源节约化利用。以绿色发展理念为指导，转变农业生产方式，从节水、节肥、节药等方面推动农业资源节约化利用，进一步提升农业资源的利用效率[26]。应继续抓好中部地区农业与生态协调发展，保证该区域农业生态效率完全有效水平。同时在推动海南省西部地区市（县）农业产业结构优化的过程中，不仅要关注农业本身的发展，还需将农业与旅游、文化等产业深度融合，形成“农业+”的发展新模式。
此外，本研究仍具有一定的局限性，海南畜禽养殖业污染也是农业污染的一个重要来源，而本研究在农业生态效率测度中主要采用种植业，未采用畜禽水产养殖业的相关数据。此外，在分析农业生态效率影响因素的过程中，国内不同学者有将农业财政支农、城乡收入比、农业从业人员受教育水平等指标[27-28]纳入影响因素分析的研究，而本研究中因海南省及各市（县）部分因素量化数据较难收集，农业生态效率影响因素分析还不够全面，今后的研究可将系列指标纳入相关指标体系，使本研究更具指导价值。
4　结论
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（1）基于2012—2022年海南省18个市（县）域面板数据，采用超效率SBM模型对农业生态效率进行分析，结果表明，2012—2022年海南省农业生态效率均值呈现中部地区>西部地区>东部地区的明显分级特征，且随着时间推移，东部地区和西部地区呈明显增长趋势；从市（县）级层面来看，海南省县域尺度农业生态效率逐年明显改善，农业生态效率均值为0.541，达平均值以上的市（县）主要有昌江、五指山、白沙、定安、屯昌、琼中、保亭7个市（县）。
（2）从空间变化特征上来看，海南省农业生态效率总体呈现中部向东西部扩散的空间分布特征，同时完全有效和效率较高呈现块状和链条式分布特征，效率中等类型市（县）围绕着完全有效和效率较高市（县）分布，且呈现明显的北低南高、西高东低的趋势特征。
（3）通过面板Tobit回归模型对海南省农业生态效率演变的影响因素分析表明，城镇化率、农业化学投入品使用强度与农业生态效率呈显著负相关，对海南省整体农业生态效率具有抑制作用，而农民收入水平和农业机械密度与农业生态效率呈显著正向驱动作用，农民收入水平的增加和机械化的投入对当地农业产值的增加和农业生态效率的刺激作用明显，对农业生态效率具有促进作用。而且不同区域影响因素强度表现不一，其中农业投入品使用强度对三大区域农业生态效率均产生负向影响。
基金
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  • 海南省自然科学基金高层次人才项目(721RC630)
  • 海南省哲学社会科学规划课题(HNSK（YB）22-14)
  • 海南省自然科学基金项目(622MS115)
文献
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2025年第46卷第1期
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doi: 10.3969/j.issn.1000-2561.2025.01.024
  • 接收时间：2024-08-12
  • 首发时间：2026-06-24
  • 出版时间：2025-01-25
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  • 收稿日期：2024-08-12
  • 修回日期：2024-08-21
基金
海南省自然科学基金高层次人才项目(721RC630)
海南省哲学社会科学规划课题(HNSK（YB）22-14)
海南省自然科学基金项目(622MS115)
作者信息
    中国热带农业科学院科技信息研究所/海南省热带作物信息技术应用研究重点实验室，海南海口　571101

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* 李玉萍（LI Yuping），E-mail：。
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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