摘要
池塘养殖在中国渔业生产体系中占有重要的位置,它具有食物供给、空气(气温)调节、文化休憩服务等多重生态服务价值,同时也会对环境造成一定的负面影响,即存在环境成本。为进一步厘清池塘养殖生态服务价值的变化规律,本文基于前期研究成果,在构建池塘养殖生态服务价值评估体系的基础上,采用市场价值法(MVM)、旅行成本法(TCM)、条件价值评估法(CVM)、影子工程法(SEM)等方法对上海嘉定、青浦、奉贤地区的池塘养殖生态服务价值进行了系统评估,并分析了池塘养殖生态服务价值的时空分布差异,对因地制宜促进池塘养殖产业的发展提出了建议。结果表明:1)2011年,嘉定、青浦、奉贤3区的池塘养殖生态服务价值分别为0.822 8亿元、8.462 8亿元和15.588 4亿元,相当于各区池塘养殖产业经济价值的2.69倍、1.94倍和2.17倍,约合94.08万元.hm 2、20.00万元.hm 2和32.73万元.hm 2,池塘养殖生态服务价值巨大且时空分布差异明显;2)嘉定、青浦、奉贤未实现的池塘养殖生态服务价值是各区池塘养殖食物供给净价值的5.46倍、1.23倍、0.46倍,具有巨大的潜在生态经济效益;3)受养殖经济效率时间变化的影响,2010—2011年研究区常规鱼类养殖规模大幅减少,青虾、南美白对虾逐渐成为主要的养殖品种;4)池塘养殖生态服务价值时间分布集中且波动明显,大部分服务价值集中于第3季度,其中文化休憩服务价值主要集中于4—9月,空气调节价值主要集中于7—12月,而气温调控价值集中于5—9月;5)养殖规模对生态服务价值的时空分布具有重要影响,池塘养殖生态服务价值整体服从规模效应,但不同类型的生态服务价值的时间分布规律并不统一。养殖经营者应积极调整池塘养殖经营战略,大力发展休闲渔业,提高池塘生态服务价值的实现化程度,政府需要制定并执行必要的生态补偿政策。
Pond aquaculture was a critical fishery production system in China. At present, eco-service value research focused on the positive aspects while negative service values (e.g., environmental cost) were neglected. Pond aquaculture performed multiple functions, including aquatic product supply, air conditioning and temperature adjustment, culture recreation services, etc. At the same time, this system can also bring forth environmental costs. For further clarification of changes in eco-service values and to realize sustainable development of pond aquaculture, this paper established a comprehensive coo-service value evaluation system. On this basis, coo-service values and their the spatial-temporal variations in pond aquaculture eco-service values in Shanghai (including Jiading, Qingpu and Fengxian Districts) were estimated by Market Valuation Method (MVM), Travel Cost Method (TCM), Contingent Valuation Method (CVM) and Shadow Engineering Method (SEM). The main results of the paper were summarized as follows: 1) The total values of pond aquaculture eco-service in Jiading, Qingpu and Fengxian Districts were approximately 8.228×107 Yuan.a-1, 8.462 8×108 Yuan.a-1 and 1.558 84×109 Yuan.a-1, respectively. This respectively amounted to 9.408×105Yuan.hm-2.a-1, 2.000× 105 yuan-hm-2.a-1 and 3.273×105 yuan.hrn-2.a-1; which were 2.69, 1.94 and 2.17 times of pond aquaculture economic values in 201 1. This showed that significant differences existed among the spatial-temporal variations in pond aquaculture. 2) Pond aquaculture eco-service values were high, but this huge potential values were not optimally exploited. Unrealized eco-service values were respectively about 5.46, 1.23 and 0.46 times of net food supply values in the Jiading, Qingpu and Fengxian Districts. 3) Driven by temporal variations in economic efficiency, pond aquaculture varieties were adjusted from 2010 to 2011. Conventional fish aquaculture reduced significantly while freshwater shrimp and Penaeus vannamei became the main aquaculture species in the studied districts. 4) There was significant difference and flucturation in temporal variations in eco-service values due to different spatial distributions among eco-services. Recreation culture service value was highest from April to September, air conditioning value highest from July to December and temperature adjustment value highest from May to September. 5) Pond scales had significant impact on spatial-temporal variations in eco-service values. Pond aquaculture eco-service value was subjected to scale economy. Spatial-temporal distributions of different types of eco-service values were dissimilar and no clear general mechanism was noted. It was necessary to adjust and optimize management strategies of pond aquaculture based on the eco-service value distributions and to develop recreational fisheries to improve eco-service values. It is important for government to develop and implement necessary ecological compensation policy to achieve environmental equity and sustainable development.
出处
《中国生态农业学报》
CAS
CSCD
北大核心
2013年第2期217-226,共10页
Chinese Journal of Eco-Agriculture
基金
国家自然科学基金项目(70973075)
上海市教育委员会科研创新项目(09ZZ169)资助
关键词
上海地区
池塘养殖
生态服务价值
时空差异
产业调整
经济效益
Shanghai, Pond aquaculture, Eco-service value, Spatial-temporal variation, Industrial adjustment, Economic efficiency