广东省耕地非粮化的时空分异及其驱动机制

doi:10.18402/resci.2022.03.05

摘要/Abstract

摘要：

粮食安全是保障国家经济发展和社会稳定的基石,日益严峻的耕地非粮化问题加剧了粮食安全风险,直接影响中国社会经济的可持续发展。本文从食物性生产的非粮化角度,选取广东省为研究区域,以县域为评价单元,运用社会经济统计数据及地理空间数据,集成Theil指数、空间自相关模型、随机森林模型、主成分分析和聚类分析等方法,从全省四大区域角度探讨了广东省2005和2019年耕地非粮化的时空演变特征、影响因素及其驱动类型。结果表明：①广东省耕地非粮化率由2005年的48.47%上升至2019年的54.65%,耕地非粮化程度由低度为主转向中度为主,且耕地非粮化利用空间差异呈现缩小态势,以珠三角的演变差异最为显著。②耕地非粮化的空间分布保持稳定的集聚状态,并以珠三角的高高集聚和东翼、西翼、山区的低低集聚为主。③路网密度、地均GDP对耕地非粮化存在显著的推动作用,农村第一产业劳动力占比、各县到省会城市距离是抑制耕地非粮化的重要因素。④耕地非粮化驱动类型以经济驱动型为主(44.63%),主要分布在珠三角;其次是农业支持型(33.06%),大多分布在山区;资源依赖型占比最少(22.31%),集聚在东、西两翼。研究结果有利于精准识别广东省耕地非粮化的时空特征,提升当地耕地非粮化的风险管控水平,对于农业可持续发展以及保证地区的粮食安全具有重要的理论与现实意义。

关键词: 耕地非粮化, 驱动机制, Theil指数, 随机森林, 广东省

Abstract:

Food security is the cornerstone of national economic development and social stability. The increasingly serious problem of cultivated land non-grain conversion intensifies the risk of food insecurity and directly affects the sustainable development of China's social and economic systems. From the perspective of non-grain production of food, this study selected Guangdong Province as the research area and county as the evaluation unit and based on socioeconomic statistics and geospatial data, using Theil index, spatial autocorrelation model, random forest model, principal component analysis, and cluster analysis to examine the spatiotemporal characteristics, influencing factors, and driving types of cultivated land non-grain conversion in 2005 and 2019. The results show that: (1) The non-grain rate of cultivated land in Guangdong Province increased from 48.47% in 2005 to 54.65% in 2019. The non-grain degree of cultivated land had changed from low to moderate, and the spatial differentiation of non-grain rate of cultivated land showed a decreasing trend, especially in the Pearl River Delta area. (2) The spatial distribution of non-grain cultivated land maintained a stable agglomeration state and showed high concentration in the Pearl River Delta area and low concentration in the east wing, west wing, and mountainous sub-regions of the province. (3) Road network density and GDP per square kilometer had significant promoting effects on cultivated land non-grain conversion, while the proportion of labor force in rural primary industry and distance between counties and provincial capital cities were important factors to restrain the cultivated land non-grain conversion. (4) The main driving type of cultivated land non-grain conversion was economy driven (44.63%), mainly distributed in the Pearl River Delta area. This was followed by agriculture supporting type (33.06%), mostly distributed in the mountainous areas. The resource dependency type was the least dominant (22.31%) and was concentrated in the east and west wing sub-regions. This research result is conducive to accurately identify the spatiotemporal characteristics of cultivated land non-grain conversion in Guangdong Province, improve the risk control level of local cultivated land non-grain conversion, and has important theoretical and practical significance for sustainable agricultural development and ensuring regional food security.

Key words: cultivated land non-grain conversion, driving mechanism, Theil index, Random Forest, Guangdong Province

张颖诗, 冯艳芬, 王芳, 陈子龙, 李晓航. 广东省耕地非粮化的时空分异及其驱动机制[J]. 资源科学, 2022, 44(3): 480-493.

ZHANG Yingshi, FENG Yanfen, WANG Fang, CHEN Zilong, LI Xiaohang. Spatiotemporal differentiation and driving mechanism of cultivated land non-grain conversion in Guangdong Province[J]. Resources Science, 2022, 44(3): 480-493.

图/表 14

图1

表1

广东省耕地非粮化的影响因素选择

影响因子	指标释义	性质
土地面积（X₁）	研究区的土地总面积/km²,反映研究区的土地资源总量	-
耕地面积（X₂）	研究区的耕地总面积/hm²,反映耕地资源的丰缺程度	-
人均耕地面积（X₃）	耕地总面积与总人口之比/（亩/人）,反映人均耕地资源的稀缺程度	-
旱地占比（X₄）	旱地面积占耕地总面积比例/%,反映耕地内部利用结构	+
有效灌溉面积（X₅）	在一般年景下当年能够进行正常灌溉的耕地面积/hm²,反映耕地抗旱能力,揭示耕地水源保证条件	-
坡度（X₆）	县域平均坡度/°,反映研究区地形的平均陡缓程度和耕作条件,利用DEM数据计算	-
高程（X₇）	县域平均海拔/m,反映研究区的海拔特征,利用DEM数据计算	-
粮食单位产出量（X₈）	耕地全年所生产的粮食总量与耕地总面积之比/（t/hm²）,反映耕地单位生产能力	+
地均GDP（X₉）	GDP与土地总面积之比/（亿元/km²）,反映土地生产效益	+
农业总产值（X₁₀）	农、林、牧、渔业全部产品的总量/万元,反映农业生产总规模	-
农村第一产业劳动力占比（X₁₁）	乡村第一产业从业人数占总从业人数比例/%,反映乡村劳动力结构	-
农村居民人均可支配收入（X₁₂）	农村居民可用于自由支配的收入,包括消费支出和储蓄/元	-
人口密度（X₁₃）	人口总量与土地总面积之比（人/km²）,反映人口密集程度	+
路网密度（X₁₄）	研究区内所有道路的总长度与区域总面积之比/（km/km²）,反映交通便捷程度	+
各县到省会城市距离（X₁₅）	各县的几何中心到广州市越秀区几何中心的距离/km,反映省会城市的吸引能力	-
各县到所在市中心距离（X₁₆）	各县的几何中心到所在市中心城区几何中心的距离/km,反映研究区与所在市的连接程度	-

表1

表2

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表3

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图4

图5

表4

表5

图6

图7

表6

图8

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区域	最大值		最小值		平均值
区域	2005年	2019年	2005年	2019年	2005年	2019年
珠三角	100.00	100.00	20.56	21.42	65.43	73.54
东翼	65.14	65.23	17.13	25.96	35.49	39.05
西翼	66.70	67.79	22.83	28.21	41.64	45.68
山区	61.99	65.29	14.56	21.16	36.47	43.02
广东省	100.00	100.00	14.56	21.16	48.47	54.65

	珠三角	东翼	西翼	山区	区域内	区域间	全省
2005年	0.0286	0.0080	0.0050	0.0136	0.0552	0.0395	0.0947
2019年	0.0164	0.0041	0.0041	0.0105	0.0351	0.0376	0.0727

主成分	特征值	贡献率/%	累计贡献率/%
1	3.85	24.06	24.06
2	3.62	22.60	46.66
3	3.51	21.92	68.58
4	1.42	8.89	77.47

影响因子	第1主成分	第2主成分	第3主成分	第4主成分
土地面积（X₁）	0.739	0.234	0.475	-0.099
耕地面积（X₂）	0.922	0.072	0.098	0.237
人均耕地面积（X₃）	0.425	0.073	0.636	0.310
旱地占比（X₄）	-0.059	0.158	0.711	0.030
有效灌溉面积（X₅）	0.908	0.238	0.055	0.069
坡度（X₆）	0.017	-0.147	-0.877	0.218
高程（X₇）	-0.020	-0.176	-0.901	-0.124
粮食单位产出量（X₈）	-0.210	0.150	0.624	-0.106
地均GDP（X₉）	0.212	0.865	0.121	0.222
农业总产值（X₁₀）	0.868	0.216	-0.187	0.015
农村第一产业劳动力占比（X₁₁）	0.408	0.407	0.498	0.351
农村居民人均可支配收入（X₁₂）	0.285	0.644	-0.118	-0.385
人口密度（X₁₃）	0.278	0.832	0.267	0.147
路网密度（X₁₄）	0.312	0.822	0.330	0.269
各县到省会城市距离（X₁₅）	0.140	0.236	-0.062	0.863
各县到所在市中心距离（X₁₆）	0.400	0.079	0.142	0.694

要素	指标	经济驱动型	资源依赖型	农业支持型
非粮化程度	非粮化率/%	66.66	46.87	43.69
	低度占比/%	22.22	33.33	52.50
	中度占比/%	33.33	62.96	40.00
	高度占比/%	44.45	3.71	7.50
耕地资源	耕地面积占比/%	10.00	19.24	11.03
耕地资源	水田占比/%	57.50	61.03	69.24
社会经济	地均GDP/（亿元/km²）	4.32	1.04	0.13
社会经济	乡村第一产业劳动力占比/%	25.87	41.66	53.08
交通区位	路网密度/（km/km²）	2.65	1.26	0.39
交通区位	各县到省会城市距离/km	110.26	367.74	225.48