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基于地理探测器的四川省茶产业时空格局变化及驱动因素研究

曹杰 林正雨 陈春燕 刘远利 高文波 邵周玲

曹杰, 林正雨, 陈春燕, 刘远利, 高文波, 邵周玲. 基于地理探测器的四川省茶产业时空格局变化及驱动因素研究[J]. 中国生态农业学报 (中英文), 2022, 30(0): 1−13 doi: 10.12357/cjea.20220278
引用本文: 曹杰, 林正雨, 陈春燕, 刘远利, 高文波, 邵周玲. 基于地理探测器的四川省茶产业时空格局变化及驱动因素研究[J]. 中国生态农业学报 (中英文), 2022, 30(0): 1−13 doi: 10.12357/cjea.20220278
CAO J, LIN Z Y, CHEN C Y, LIU Y L, GAO W B, SHAO Z L. Spatiotemporal pattern of tea industry in Sichuan province and their driving forces based on the geographical detector[J]. Chinese Journal of Eco-Agriculture, 2022, 30(0): 1−13 doi: 10.12357/cjea.20220278
Citation: CAO J, LIN Z Y, CHEN C Y, LIU Y L, GAO W B, SHAO Z L. Spatiotemporal pattern of tea industry in Sichuan province and their driving forces based on the geographical detector[J]. Chinese Journal of Eco-Agriculture, 2022, 30(0): 1−13 doi: 10.12357/cjea.20220278

基于地理探测器的四川省茶产业时空格局变化及驱动因素研究

doi: 10.12357/cjea.20220278
基金项目: 国家重点研究计划课题(2020YFD1100601), 四川省杰出青年科技人才项目(2020JDJQ0073), 四川省重点研发项目(2021YFYZ0028)和四川省财政自主创新专项项目(2022ZZCX036)资助
详细信息
    作者简介:

    曹杰, 主要研究方向为农业资源利用与区域农业发展研究。E-mail: 2435711812@qq.com

    通讯作者:

    林正雨, 主要研究方向为农业资源利用与区域农业发展研究。E-mail: 1456875524@qq.com

  • 中图分类号: F323.1;F304.5

Spatiotemporal pattern of tea industry in Sichuan province and their driving forces based on the geographical detector

Funds: This study was supported by the National Key Research and Development Project of China (2020YFD1100601), the Program for Distinguished Young Technology Talents of Sichuan Province (2020JDJQ0073), the Provincial Key Research and Development Project of Sichuan Province (2021YFYZ0028) and Sichuan Provincial Financial Independent Innovation Project (2022ZZCX036).
More Information
  • 摘要: 茶产业时空格局形成和演变是自然因素和人类活动共同作用的结果, 理解茶产业时空格局变化过程, 揭示不同自然—社会经济驱动因子对茶产业时空格局演变的作用机制, 对区域茶叶种植结构调整具有重要意义。本文基于1980—2019年四川省县区尺度茶叶生产统计年鉴数据, 运用产业集中度、探索性空间数据分析和产业重心模型分析了四川省茶产业时空格局演化过程, 对研究区内海拔、土壤酸碱度、年降水量、年活动积温、生长季日平均气温、越冬期日极端最低气温、生长季日极端最高气温等自然因素, 土地利用强度、乡村劳动力、化肥、农药、灌溉等生产要素以及人均可支配收入、科技、政策等社会经济要素进行离散分层并确定最优尺度单元, 基于地理探测器探讨了各驱动因子对四川省茶产业分布的解释力以及交互作用。结果表明: 从时间上看, 四川省茶产业规模总体呈上升趋势, 区位基尼系数均大于0.5, 空间特征呈现出高度集聚, 且集聚程度随时间波动上升。从空间上看, 全局莫兰指数均大于0, 县域尺度上表现出明显的空间集聚, 且相邻县域之间相互影响, 热点区主要分布在川南地区和成都平原区南部, 茶产业重心整体上向西迁移。可变面域问题会影响地理探测器建模结果, 对连续型因子离散化和空间单元尺度优化, 得到最优参数。单个因子对茶产业空间影响程度排前三的是, 土地利用强度(0.91)、乡村劳动力(0.87)、化肥(0.86); 影响因子相互作用主要表现为非线性增强和双因子增强, 生产与社会经济因子平均交互作用最大(0.8870), 四川省茶产业表现出生产要素驱动为主的空间格局。基于此, 本研究认为应重视: 1)关注生长季缺水, 突发性强降水以及低温冻害对茶树的影响; 2)加强“宜机采”茶园建设, 树立绿色茶园绿色发展概念; 3)提升良种普及率以及推广新技术, 保障用地、劳动力、化肥、农药等生产要素的稳定投入。
  • 图  1  四川省地理分区

    Figure  1.  Geographical regions map of Sichuan Province

    图  2  1980—2019年四川省茶产业面积时序变化

    Figure  2.  Temporal changes of tea industry area in Sichuan Province from 1980 to 2019

    图  3  1980—2019年四川省茶产业空间集聚特征

    Figure  3.  Agglomeration characteristics of tea industry space in Sichuan Province from 1980 to 2019

    图  4  1980—2019年四川省茶产业空间热点分布

    Figure  4.  Spatial hot spot distribution of tea industry in Sichuan Province from 1980 to 2019

    图  5  不同空间格网下各因素对茶叶空间格局的决定力(q值)及其排名变化

    图中15个影响因子分别是: X1 (海拔), X2 (土壤酸碱度), X3 (年降水量), X4 (年活动积温), X5 (生长季日平均气温), X6 (越冬期日极端最低气温), X7 (生长季日极端最高气温), X8 (土地利用强度), X9 (乡村劳动力), X10 (化肥), X11 (农药), X12 (灌溉), X13 (人均可支配收入), X14 (科技), X15 (政策)。There are 15 influence factors as follows: X1 (elevation), X2 (pH), X3 (annual precipitation), X4 (accumulated temperature), X5 (average temperature of growing season), X6 (extreme minimum temperature of overwintering period), X7 (extreme maximum temperature of growing season), X8(land use intensity), X9 (labor), X10 (fertilizer), X11 (pesticides), X12 (irrigation), X13 (per capita disposable), X14 (technology), X15 (policy).

    Figure  5.  Scale effects on the q values and the ranks of the factors

    图  6  影响因子对四川茶产业空间的驱动分析结果

    Figure  6.  Driving analysis of influence factors on tea industry in Sichuan Province

    表  4  基于先验知识对四川茶产业空间影响因子分类

    Table  4.   Classify the quantitative variables of tea industry in Sichuan Province by prior knowledge

    要素
    Variable
    切割值
    Cutting values
    赋值
    Value
    海拔
    Elevation (X1)
    <200 m1
    200~500 m2
    500~1000 m3
    >1000 m4
    土壤酸碱度
    Hydrogen ion concentration of soil (X2)
    0~5.51
    5.5~6.52
    6.5~7.53
    7.5~8.54
    >8.55
    人均可支配收入
    Per capita disposable (X13)
    0~20%1
    20%~40%2
    40%~60%3
    60%~80%4
    80%~100%5
    政策
    Policy (X15)
    1、2、3、4、5
    下载: 导出CSV

    表  1  1980—2019年四川省茶产业空间Moran’s I指数变化

    Table  1.   Changes of Moran’s I of tea industry space in Sichuan Province from 1980 to 2019

    年份 Year198019851990199520002005201020152019
    Moran’s I0.480.470.450.400.340.380.420.420.42
    Z11.3411.4810.709.718.459.3010.049.909.38
    P0.010.010.010.010.010.010.010.010.01
    下载: 导出CSV

    表  2  1980—2019年四川省茶产业空间重心迁移变化

    Table  2.   Change of center of gravity of tea industry area in Sichuan Province from 1980 to 2019

    年份
    Year
    坐标 Coordinate重心迁移距离
    Moving distance center
    of gravity (km)
    年份
    Year
    坐标 Coordinate重心迁移距离
    Moving distance center
    of gravity (km)
    经度 Longitude纬度 Latitude经度 Longitude纬度 Latitude
    1980104.7130.082006104.2930.083.71
    1985104.7830.2318.042007104.2830.101.59
    1990104.8830.1216.002008104.2830.072.73
    1995104.7130.1319.052009104.3030.035.03
    1996104.7530.209.272010104.2830.012.93
    1997104.6530.2010.572011104.3129.957.47
    1998104.6830.212.962012104.3429.963.40
    1999104.5130.1220.992013104.3529.961.04
    2000104.6030.149.942014104.3429.925.24
    2001104.6630.2311.992015104.2629.8810.05
    2002104.4730.1522.432016104.4829.9626.29
    2003104.3930.119.542017104.5429.986.66
    2004104.3430.136.122018104.5429.980.89
    2005104.3130.114.152019104.5729.974.20
    下载: 导出CSV

    表  3  四川省茶产业空间地理探测因子

    Table  3.   Indicators of geographical detector on tea industry space in Sichuan Province

    类型
    Category
    影响因子
    Influence factors
    因子意义
    The significance of factors
    自然要素
    Physical factors
    海拔
    Elevation (X1)
    通过温度间接影响茶叶生长
    Indirectly affecting tea growth
    土壤酸碱度
    Hydrogen ion concentration of soil(X2)
    茶叶生长在酸性土壤环境
    Acid soil is suitable for tea growth
    年降水量
    Annual precipitation (X3)
    一年总的水分条件
    Moisture conditions
    年活动积温
    Accumulated temperature (X4)
    积温越多, 年生长期越长
    Accumulated heat of tea during its growth
    生长季日平均气温
    Average temperature of growing season (X5)
    15~23 ℃范围内, 茶梢生长快
    The suitable is between 15~23 ℃
    越冬期日极端最低气温
    Extreme minimum temperature of overwintering period (X6)
    ≤−10 ℃, 四川主要栽培的茶树品种不能存活
    Tea varieties planted in Sichuan cannot survive at ≤−10 ℃
    生长季日极端最高气温
    Extreme maximum temperature of growing season (X7)
    受到热害导致生长停滞甚至死亡
    Excessive temperature will inhibit tea
    生产要素
    Production
    factors
    土地利用强度
    Land use intensity (X8)
    反映地区茶叶种植的土地投入指标
    Directly bearing on tea production
    乡村劳动力
    Labor (X9)
    茶叶生产需要大量的劳动力
    Tea production requires a lot of labor
    化肥
    Fertilizer (X10)
    化肥投入是提升茶叶生产不断的重要原因
    Fertilizer can increase tea yield
    农药
    Pesticides (X11)
    农药投入能抑制病虫害发生, 提高茶叶产量
    Controlling the insects
    灌溉
    Irrigation (X12)
    衡量农业生产单位和地区水利化程度和农业生产稳定程度
    Guaranteeing water supply for tea production
    社会经济要素
    Socioeconomic factors
    人均可支配收入
    Per capita disposable (X13)
    收入反映出消费能力, 评价市场需求
    Reflecting consumption ability
    科技
    Technology (X14)
    科技与单产有直接关系, 用单产衡量科技
    Increasing tea per unit area yield
    政策
    Policy (X15)
    政策对茶叶生产空间影响
    The agricultural policy is an important factor
    下载: 导出CSV

    表  5  基于最优离散对四川茶产业空间影响因子分类

    Table  5.   Classify the quantitative variables of tea industry in Sichuan Province by optimal classification algorithms

    要素
    Variable
    q值 The q values
    5678910
    年降水量 Annual precipitation (X3)0.26430.26460.26070.26480.26310.2642
    年活动积温 Accumulated temperature (X4)0.11040.10980.13170.13600.13870.1466
    生长季日平均气温 Average temperature of Growing season (X5)0.13390.16390.17100.20910.23020.2244
    越冬期日极端最低气温 Extreme minimum temperature of overwintering perio (X6)0.12030.12340.12120.12100.14250.1570
    生长季日极端最高气温 Extreme maximum temperature of growing season (X7)0.12420.13870.13690.14910.15720.1628
    土地利用强度 Land use intensity (X8)0.90320.91080.88600.88930.88960.8897
    乡村劳动力 Labor (X9)0.86130.84250.83920.84830.84850.8487
    化肥 Fertilizer (X10)0.78860.83410.83240.85840.85890.8589
    农药 Pesticides (X11)0.73600.74110.72530.74110.75530.7573
    灌溉 Irrigation (X12)0.09430.15690.11560.12930.14760.1611
    科技 Technology(X14)0.28050.27540.29950.31200.41190.3012
    下载: 导出CSV

    表  6  影响因子对四川茶叶空间的交互作用

    Table  6.   Interactive effects of influence factors on tea industry in Sichuan Province

    自然要素 Physical factors生产要素 Production factors社会经济要素 Socioeconomic factors
    X1X2X3X4X5X6X7X8X9X10X11X12X13X14X15
    X10.2202
    X20.29190.1149
    X30.45670.43680.3125
    X40.31100.27930.45480.1733
    X50.27380.30270.45910.34690.2236
    X60.28690.28720.4626*0.26950.31530.1812
    X70.25920.24760.44390.43080.33910.36290.1607
    X80.94230.92140.92580.9507*0.92350.94650.92830.9112
    X90.92990.89090.91250.92620.90660.91520.90860.93240.8684
    X100.91190.91660.93720.93660.90950.94570.92420.94970.94470.8650
    X110.88290.79450.84180.88140.84090.87480.87890.93910.93430.93090.7472
    X120.31320.29430.52970.37780.34010.36860.35960.9644*0.95270.93730.94210.1729
    X130.37180.25430.46100.30790.34470.31820.38530.96010.91780.95430.89840.47060.1441
    X140.55020.56160.73230.59930.65670.59420.62390.97520.97140.9779*0.94990.66310.63200.4285
    X150.78030.75440.8062*0.77620.76600.77340.79130.94250.90800.93410.91120.87070.76790.8493*0.7365
      下划线表示交互作用为非线性增强, 其余交互作用均为双因子增强; "*"表示每类因子交互作用中的最大值; 图中15个影响因子分别是: X1 (海拔), X2 (土壤酸碱度), X3 (年降水量), X4 (年活动积温), X5 (生长季日平均气温), X6 (越冬期日极端最低气温), X7 (生长季日极端最高气温), X8 (土地利用强度), X9 (乡村劳动力), X10 (化肥), X11 (农药), X12 (灌溉), X13 (人均可支配收入), X14 (科技), X15 (政策)。Underline “ ” denotes nonlinear enhancement of factors A and B; The symbol "*"denotes the largest interaction of each type. There are 15 influence factors as follows: X1 (elevation), X2 (pH), X3 (annual precipitation), X4 (accumulated temperature), X5 (average temperature of growing season), X6 (extreme minimum temperature of overwintering period), X7 (extreme maximum temperature of growing season), X8(land use intensity), X9 (labor), X10 (fertilizer), X11 (pesticides), X12 (irrigation), X13 (per capita disposable), X14 (technology), X15 (policy).
    下载: 导出CSV
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  • 收稿日期:  2022-04-14
  • 录用日期:  2022-09-30
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  • 网络出版日期:  2022-11-25

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