海岛养殖户台风灾害适应性行为及其影响因素分析

doi:10.31497/zrzyxb.20220418

摘要/Abstract

摘要：

水产养殖是保障粮食安全、提升适应力需要关注的关键部门之一。农户层面的灾害适应性行为及其影响因素研究对增强养殖户灾害适应能力,确保养殖户生计安全、海岛可持续发展和渔村振兴具有重要价值。基于海岛水产养殖户调查数据对养殖户灾害全过程适应性行为进行研究,并运用Multivariate Probit模型实证分析了适应性行为的影响因素,结果表明：（1）较多地采用无悔反应和低悔战术,很少采用预先应对策略、更容易的早期策略以及未来获益策略使得大多数养殖户适应行为的成效不太显著。（2）同一因素对养殖户选择的多种适应策略有正负不同方向的显著影响,不同适应策略之间也存在着显著的互补和替代效应。（3）年龄、家庭劳动力、5年遭灾次数是养殖户适应行为的重要影响因素,投入、健康状况、灾害感知强度、收入、教育程度、社会资本都对养殖户采取的适应行为有显著影响。（4）海岛地区养殖户灾害适应行为的影响因素及其影响方向具有特殊性。研究识别了海岛养殖户台风灾害适应行为的关键影响因子和薄弱环节,结论可为政府和养殖户灾害适应策略的优化调整提供依据。

关键词: 养殖户适应性行为, 影响因素, 海岛, 台风灾害

Abstract:

The IPCC special report on global warming of 1.5 °C and the IPCC special report on climate change and land both identify aquaculture as one of the key sectors that requires attention on global food security and the upgrading of adaptation policy. Research on the disaster-adaptive behavior and its influencing factors at the farmer level is of great value for enhancing the adaptive capacity to disasters, ensuring the livelihood of aquaculture farmers, and the sustainable development of islands, so as to revitalize fishing villages. However, very few studies have been conducted at the farmer level. Using survey data obtained from 202 aquaculture farmers from the Zhoushan and Dongtou Island regions and applying multivariate probit model, this study analyzes the disaster adaptation strategies of aquaculture farmers during the whole process of disaster management and the influencing factors. The results showed that: (1) Diverse multilevel adaptive strategies were adopted in study areas to deal with typhoon disaster. Up-front strategies, simple early strategies and future-benefits strategies were used significantly less than no-regret reaction and low-regret tactics by aquaculture farmers, making most farmers' adaptation strategies less effective. More than half of the farmers are willing to adopt the up-front, simple early and future-benefits strategies in the future if conditions facilitate usage of these strategies. (2) Each factor affected adaptation strategies of aquaculture farmers negatively and positively at the same time, and there was also significant complementary and substitutive relationship among the adaptive strategies selected by the aquaculture farmers. (3) Age, family labor, and the number of disasters occurring in the past 5 years were important factors influencing aquaculture farmers' adaptive behavior. Input, health status, disaster perception, income, education level, and social capital also had a significant impact on farmers' adaptive behavior. (4) Some influencing factors and their effects on the disaster adaptation behavior of aquaculture farmers in Zhoushan Islands and Dongtou Islands were different from those in other regions, which highlight the uniqueness of island regions. This study identifies the key influencing factors and weakness of adaptation behavior toward typhoon disaster, and the conclusions provide useful insight into the optimization and adjustment of the government and farmers' adaptation strategies.

Key words: adaptation behavior of aquaculture farmers, influencing factors, island regions, typhoon disaster

袁海红, 吕旖, 张时婧. 海岛养殖户台风灾害适应性行为及其影响因素分析[J]. 自然资源学报, 2022, 37(4): 1089-1103.

YUAN Hai-hong, LYU Yi, ZHANG Shi-jing. Analysis of aquaculture farmers' adaptation behavior toward typhoon disaster in Zhoushan Islands and Dongtou Islands and its influencing factors[J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(4): 1089-1103.

图/表 7

图1

表1

图2

表2

表3

表4

表5

参考文献 37

[1]	陈文芳, 徐伟, 史培军. 长三角地区台风灾害风险评估. 自然灾害学报, 2011, 20(4):77-83.
	[CHEN W F, XU W, SHI P J. Risk assessment of typhoon disaster at county level in the Yangtze River Delta of China. Journal of Natural Disasters, 2011, 20(4):77-83.]
[2]	蔡榕硕, 刘克修, 谭红建. 气候变化对中国海洋和海岸带的影响、风险与适应对策. 中国人口·资源与环境, 2020, 30(9):1-8.
	[CAI R S, LIU K X, TAN H J. Impacts and risks of climate change on China's coastal zones and seas and related adaptation. China Population, Resources and Environment, 2020, 30(9):1-8.]
[3]	IPCC. Climate Change 2014: Impact, Adaptation, and Vulnerability. Cambridge: Cambridge University Press, 2014. http://www.ipcc.ch/report/ar5/wg2/.
[4]	FAO. The state of world fisheries and aquaculture 2020. Sustainability in action. Rome, 2020. https://doi.org/10.4060/ca9229en.
[5]	GALAPPATHTHI E K, ICHIEN S T, HYMAN A A, et al. Climate change adaptation in aquaculture. Reviews in Aquaculture, 2020, 12(4):2160-2176. doi: 10.1111/raq.12427
[6]	和田恬, 于滨铜, 李苗, 等. 为什么水产养殖保险会出现政府和市场的双重失灵: 基于粤浙沪川四省市的比较分析. 农林经济管理学报, 2018, 17(5):562-569.
	[HE T T, YU B T, LI M, et al. Why is aquaculture insurance repeatedly blocked in practice: Based on a comparative analysis of cities in Guangdong, Zhejiang, Shanghai and Sichuan. Journal of Agro-Forestry Economics and Management, 2018, 17(5):562-569.]
[7]	贾清茹. 山东省水产养殖保险市场需求研究. 泰安: 山东农业大学, 2017.
	[JIA Q R. Research on the dennand of aquaculture insurance market in Shandong province. Taian: Shandong Agricultural University, 2017.]
[8]	阎祥东. 沿海渔民、渔业、渔村转型与产业扶贫衔接: 内在联系、困境与实现路径. 中国渔业经济, 2020, 38(6):18-27.
	[YAN X D. Linkage of coastal fishermen, fishery, fishing village transformation and industrial poverty alleviation: Internal connections, dilemmas and implementation paths. Chinese Fisheries Economics, 2020, 38(6):18-27.]
[9]	林艺苹, 陈香. 台风灾害及其连锁效应研究: 以 “利奇马” 台风为例. 吉林化工学院学报, 2020, 37(7):80-86.
	[LIN Y P, CHEN X. Research on typhoon disaster and its chain effects: Taking typhoon "Lekima" as an example. Journal of Jilin Institute of Chemical Technology, 2020, 37(7):80-86.]
[10]	LEBEL L, LEBEL P, CHITMANAT C, et al. Managing the risks from the water-related impacts of extreme weather and uncertain climate change on inland aquaculture in Northern Thailand. Water International, 2018, 43(2):257-280. doi: 10.1080/02508060.2017.1416446
[11]	ARIMI K S. Determinants of climate change adaptation strategies used by fish farmers in Epe Local Government Area of Lagos State, Nigeria. Journal of the Science of Food and Agriculture, 2014, 94(7):1470-1476. doi: 10.1002/jsfa.6452
[12]	ONYENEKE R U, IGBERI C O, ALIGBE J O, et al. Climate change adaptation actions by fish farmers: Evidence from the Niger Delta region of Nigeria. Australian Journal of Agricultural and Resource Economics, 2020, 64(2):347-375. doi: 10.1111/1467-8489.12359
[13]	吴小影, 刘冠秋, 齐熙, 等. 气候变化对渔区感知指数, 生计策略和生态效应的影响. 生态学报, 2017, 37(1):313-320.
	[WU X Y, LIU G Q, QI X, et al. Ecological effects of climate change and livelihood adaptations in typical fishing areas: Perceptions of fishermen's households. Acta Ecologica Sinica, 2017, 37(1):313-320.]
[14]	张杰, 张学舒. 舟山群岛海水养殖业风险状况调查分析. 广东农业科学, 2012, 39(6):232-234.
	[ZHANG J, ZHANG X S. Investigation and analysis of risk status of marine aquaculture in Zhoushan Islands. Guangdong Agricultural Sciences, 2012, 39(6):232-234.]
[15]	向芸芸, 陈培雄, 杨辉, 等. 基于资源环境承载力的海岛生态系统适应性管理: 以温州市洞头区为例. 海洋环境科学, 2018, 37(4):552-560, 578.
	[XIANG Y Y, CHEN P X, YANG H, et al. Research on the management of island ecosystem based on resource and environment carrying capacity assessment: A case study in Dongtou district, Wenzhou city. Marine Environmental Science, 2018, 37(4):552-560, 578.]
[16]	AHMED N, DIANA J S. Does climate change matter for freshwater aquaculture in Bangladesh?. Regional Environmental Change, 2016, 16(6):1659-1669. doi: 10.1007/s10113-015-0899-6
[17]	DANG H L, LI E, NUBERG I, et al. Factors influencing the adaptation of farmers in response to climate change: A review. Climate and Development, 2019, 11(9):765-774. doi: 10.1080/17565529.2018.1562866
[18]	汪海欧, 於琍, 杨书运, 等. 气候变化适应及其影响因素研究: 山东胶州湾地区居民的实证分析. 中国农学通报, 2019, 35(11):103-109.
	[WANG H O, YU L, YANG S Y, et al. Climate change adaptation and its influencing factors in Jiaozhou Bay Area, Shangdong: An empirical analysis on local residents. Chinese Agricultural Science Bulletin, 2019, 35(11):103-109.]
[19]	王晓敏, 金建君, 高艺玮. 农户适应气候变化的行为及影响因素: 基于实验经济学方法的研究. 北京师范大学学报: 自然科学版, 2016, 52(4):501-505.
	[WANG X M, JIN J J, GAO Y W. Farmer coping behavior in climate change and affecting factors: Method of experimental economics. Journal of Beijing Normal University: Natural Science, 2016, 52(4):501-505.]
[20]	朱红根, 周曙东. 南方稻区农户适应气候变化行为实证分析: 基于江西省36县(市)346份农户调查数据. 自然资源学报, 2011, 26(7):1119-1128.
	[ZHU H G, ZHOU S D. Factors influencing Southern rice farmers adapting to climate change behavior-based on 346 household survey data of 36 counties in Jiangxi province. Journal of Natural Resources, 2011, 26(7):1119-1128.]
[21]	宋臻, 史兴民. 雨养农业区农户的气候变化适应行为及影响因素路径分析. 地理科学进展, 2020, 39(3):461-473. doi: 10.18306/dlkxjz.2020.03.011
	[SONG Z, SHI X M. Path analysis of influencing factors of farmers' adaptive behaviors to climate change in the rain-fed agricultural areas. Progress in Geography, 2020, 39(3):461-473.]
[22]	NDAMANI F, WATANABE T. Determinants of farmers' adaptation to climate change: A micro level analysis in Ghana. Scientia Agricola, 2016, 73(3):201-208. doi: 10.1590/0103-9016-2015-0163
[23]	童庆蒙, 张露, 张俊飚. 基于湖北省十个代表县(市)的农户适应气候变化的偏向特征与影响因素分析. 中国农业大学学报, 2019, 24(1):194-205.
	[TONG Q M, ZHANG L, ZHANG J B. An analysis of oriented characteristics and influential factors of farmers' adaptation to climate change in 10 representative counties and cities of Hubei province. Journal of China Agricultural University, 2019, 24(1):194-205.]
[24]	NDIRITU S W, KASSIE M, SHIFERAW B. Are there systematic gender differences in the adoption of sustainable agricultural intensification practices? Evidence from Kenya. Food Policy, 2014, 49:117-127. doi: 10.1016/j.foodpol.2014.06.010
[25]	TRINH T Q, RAÑOLA JR R F, CAMACHO L D, et al. Determinants of farmers' adaptation to climate change in agricultural production in the central region of Vietnam. Land Use Policy, 2018, 70:224-231. doi: 10.1016/j.landusepol.2017.10.023
[26]	TARFA P Y, AYUBA H K, ONYENEKE R U, et al. Climate change perception and adaptation in Nigeria's Guinea Savanna: Empirical evidence from farmers in Nasarawa State, Nigeria. Appl Ecol Environ Res, 2019, 17(3):7085-7112.
[27]	MULWA C, MARENYA P, KASSIE M. Response to climate risks among smallholder farmers in Malawi: A multivariate probit assessment of the role of information, household demographics, and farm characteristics. Climate Risk Management, 2017, 16:208-221. doi: 10.1016/j.crm.2017.01.002
[28]	靳乐山, 魏同洋, 胡振通. 牧户对气候变化的感知与适应: 以内蒙古四子王旗查干补力格苏木为例. 自然资源学报, 2014, 29(2):211-222.
	[JIN L S, WEI T Y, HU Z T. Herdsmen's perceptions and adaption to climate change: A case study in Chaganbulige, Siziwang Banner, Inner Mongolia. Journal of Natural Resources, 2014, 29(2):211-222.]
[29]	尹莎, 陈佳, 杨新军. 社会—生态系统重构背景下农户适应行为及影响机理. 人文地理, 2020, 35(2):112-121.
	[YIN S, CHEN J, YANG X J. Adaptive behavior of farming household and influential mechanism in the background of social-ecological system reconstruction. Human Geography, 2020, 35(2):112-121.]
[30]	王亚茹, 赵雪雁, 张钦, 等. 高寒生态脆弱区农户的气候变化适应策略: 以甘南高原为例. 地理研究, 2016, 35(7):1273-1287. doi: 10.11821/dlyj201607005
	[WANG Y R, ZHAO X Y, ZHANG Q, et al. Farmers' climate change adaptation strategies in an ecologically vulnerable alpine region: A case of Gannan Plateau. Geographical Research, 2016, 37(7):1273-1287.]
[31]	崔永伟, 杜聪慧, 侯麟科. 气候变化下农业适应行为的现状及研究进展. 世界农业, 2012, (11):25-29.
	[CUI Y W, DU C H, HOU L K. Current status and research progress on agricultural adaptation to climate change. World Agriculture, 2012, (11):25-29.]
[32]	CAPPELLARI L, JENKINS S P. Multivariate probit regression using simulated maximum likelihood. The Stata Journal, 2003, 3(3):278-294. doi: 10.1177/1536867X0300300305
[33]	张小宇, 刘金全. “泰勒规则” 在中国经济运行中的经验证据. 财经研究, 2010, (11):127-134.
	[ZHANG X Y, LIU J Q. "Taylor Rule" and its empirical test in China's economy. Journal of Finance and Economics, 2010, (11):127-134.]
[34]	张杰, 张学舒, 姜华帅. 浙江温州地区海水养殖业风险状况及对策研究. 现代渔业信息, 2011, 26(11):3-5.
	[ZHANG J, ZHANG X S, JIAGN H S. Risk status of marine aquaculture in Wenzhou area in Zhejiang province and study to countermeasure. Modern Fisheries Information, 2011: 26(11):3-5.]
[35]	吴丹丹, 马仁锋, 王腾飞, 等. 中国沿海 “渔业, 渔民, 渔村” 转型研究进展. 世界科技研究与发展, 2016, 38(6):1343.
	[WU D D, MA R F, WANG T F, et al. Progress on transition of fishery, fishermen and fishing village in China coastal area. World Sci-Tech R & D, 2016, 38(6):1343.]
[36]	粮农组织. 2018年世界渔业和水产养殖状况: 实现可持续发展目标. 罗马, 2018: 134.
	[FAO. The State of World Fisheries and Aquaculture. Food and Agriculture Organization of the United Nations. Rome, Italy, 2018: 134.]
[37]	马志雄, 张银银, 丁士军. 失地农户生计策略多样化研究. 华南农业大学学报: 社会科学版, 2016, 15(3):54-61.
	[MA Z X, ZHANG Y Y, DING S J. Research on livelihood diversification of rural households encountered by land lost farmers. Journal of South China Agricultural University: Social Science Edition, 2016, 15(3):54-61.]

变量	代码	变量描述	平均值	标准差
户主年龄	X1	实际年龄/岁	55.52	8.46
教育程度	X2	按受教育年限/年,文盲=0;小学=6;初中=9;高中=12;大学及以上=16	7.72	2.86
健康状况	X3	健康=1;间歇性小病=3;长期慢性病=4;患有大病=7	1.78	1.75
投入/养殖面积	X4	实际投入/万元/15亩以下=1;15~30亩=2;30~50亩=3;50~80亩=4;80亩以上=5	2.85/21.81	1.05/20.47
家庭劳动力	X5	实际从事养殖业的人数/人	1.5	0.62
5年平均收入	X6	实际收入/万元	12.05	17.6
灾害损失	X7	实际损失/万元	8.69	18.85
灾害感知	X8	未来台风灾害对养殖业的危害程度：很小=1;小=2,一般=3,大=4,很大=5	4.45	0.74
五年遭灾次数	X9	实际次数/次	3.77	1.19
社会资本	X10	有亲友帮助,是为1,否为0;与村民聚在一起商讨相关应对措施,是为1,否为0;彼此互相帮助应对台风,是为1,否为0;政府或社区开展了应对台风的培训,是为1,否为0;参与渔农业合作组织,是为1,否为0;是否加入宗教等民间团体,是为1,否为0;是否与大学科研机构合作,是为1,否为0	1.37	1.14

编号	灾前、灾中适应措施	形式	频数/户	占比/%
1	池塘内多蓄海水	技术	29	25.66
2	疏通排洪沟	技术	62	54.87
3	调整饲料、使用药物增强体质与抗应激能力	技术	96	84.96
4	检查相关设备,做好饲料及药品储备	技术	61	53.98
5	在养殖区周围筑起堤坝	基础设施	16	14.16
6	提前获取灾害预警信息	信息	198	98.02
7	争取政府支援	制度	3	1.5
8	与邻居等共同商讨应对策略	信息与制度	33	16.3
9	加固相关设施	基础设施	105	52.0
10	多样化收入来源	经济	21	10.3
11	养殖品种多样化	技术	101	50
12	购买保险	经济	10	4.95
13	将养殖产品转移到相对安全的区域	基础设施	6	3.0

编号	灾后适应措施	形式	频数/户	占比/%
1	及时排水换水、消毒和水质调节等各种措施预防病虫害发生	技术	110	97.35
2	提高机体的免疫力,加强投喂优质饵料	技术	88	77.87
3	合理配置、使用增氧机	技术	34	30.09
4	对动物死体及时深埋处理,并做好隔离的各项工作,防止腐烂传播疾病	技术	12	10.62
5	重新购买苗种养殖	技术	23	11.4
6	重新修建破坏的设施	基础设施	149	73.76
7	向亲友和银行借贷	经济	61	15.35
8	政府补贴和救济	制度	3	1.49
9	保险赔偿	经济与制度	10	4.95
10	大学、科研机构或民间团体的帮助	经济与技术	6	2.97

预期适应行为	频数/户	占比/%
扩大水产养殖业规模	23	11.39
缩小水产养殖业规模	27	13.37
暂继续目前的养殖规模,未来看收益情况决定扩大、缩小、或转行	118	58.42
放弃水产养殖	31	15.35
改变养殖品种	3	1.49
如果有合适的科技产品,愿意更多应用科技	80	39.6
如果有合适的保险产品,愿意购买保险	103	50.99
迁出本海岛	0	0

因变量	养殖品种多样化			加固设施				生计多样化
解释变量	系数	dy/dx		系数		dy/dx		系数	dy/dx
年龄	0.098^***	0.024		-0.019		-0.006		-0.022	-0.004
教育程度	0.098^**	0.024		-0.078^**		-0.031		0.056	0.008
健康状况	-0.043	-0.005		0.097^*		0.026		-0.055	-0.009
投入	0.035^***	0.008		0.013^*		0.004		0.002	0.001
家庭劳动力	-0.862^***	-0.234		0.13		0.034		0.049	0.014
5年平均收入	-0.031^***	-0.006		0.019^***		0.006		-0.003	-0.001
灾害损失	0.007	0.001		-0.014		-0.004		-0.017	-0.003
灾害感知	0.108	0.033		-0.605^***		-0.209		0.303	0.041
5年遭灾次数	-0.016	0.003		-0.033		-0.014		-0.215^*	-0.03
社会资本	0.206^*	0.052		-0.058		-0.019		0.011	0.007
常数	-6.000^***			3.866^***				-0.993
因变量	重修损坏设施			重买苗种养殖				借贷
解释变量	系数	dy/dx		系数		dy/dx		系数	dy/dx
年龄	-0.044^***	-0.015		-0.068^***		-0.009		-0.037^***	-0.013
教育程度	-0.079^*	-0.028		-0.06		-0.013		0.022	0.008
健康状况	0.07	0.017		-0.136		-0.015		0.227^***	0.078
投入	-0.006	-0.001		-0.016		-0.002		0.014^**	0.005
家庭劳动力	0.241	0.062		0.452^**		0.066		0.139	0.036
5年平均收入	0.017^***	0.003		-0.014		-0.001		0.008	0.003
灾害损失	-0.017^*	-0.001		0.017^**		0.002		-0.006	-0.002
灾害感知	-0.117	-0.037		0.269		0.014		0.004	0.021
5年遭灾次数	0.331^***	0.095		0.321^**		0.047		0.245^***	0.085
社会资本	-0.272^***	-0.057		0.069		0.008		-0.017	-0.004
常数	2.683^**			0.0574				0.259
协方差矩阵	DT		RF		DL		RD			RS
DT
RF	-0.576^***
DL	0.215		-0.116
RD	-0.382^***		0.338^***		0.631^***
RS	-0.475^***		-0.168		-0.302^*		0.112
DC	-0.045		0.165		0.153		0.282^**			0.038
Log pseudo Likelihood=-510.2,Likelihood ratio test of rho21=rho31=rho41=rho51=rho61=rho32=rho42=rho52=rho62=rho43=rho53=rho63=rho54=rho64=rho65=0, chi²(15)=73.352, Prob>chi²=0.0000