基于最大熵和广义相加模型分析厦门有害藻华影响下滨海旅游环境价值损失的关键参数

Study on the key parameters of environmental value loss of coastal tourism under the influence of harmful algal blooms in Xiamen based on maximum entropy and generalized additive model

中文关键词:  有害藻华；滨海旅游；模型分析；环境价值；支付意愿  厦门

英文关键词:Harmful algal bloom  Coastal tourism  Model analysis  Environmental value  Willingness to pay  Xiamen

中文摘要:

      有害藻华是海洋生态灾害中最突出的问题，威胁滨海旅游等海洋经济可持续发展。如何有效评估有害藻华对滨海旅游环境价值损失的影响，是推动生态环境保护与旅游资源开发协调发展的前提和基础。目前国内外广泛使用条件价值法，通过设置假想情景，根据受访者是否愿意为修复环境支付费用及其多少来定量转换环境损失价值。因此，受访者支付意愿及其程度是影响环境损失价值的关键参数。但是，受访者的支付意愿和最大支付额度受多种复杂因素影响，常规统计分析方法难以厘清其主要因素。本文创新性引入最大熵MaxEnt和广义相加GAMs模型，分别从是否愿意支付的定性分析和支付额度多少的定量分析两个方面，阐明厦门有害藻华影响下滨海旅游环境价值损失评估中影响这两个关键参数的主要因素。与传统统计分析方法相似，不论是MaxEnt还是GAMs模型都认为收入水平、对景点满意程度、受教育程度和年龄是解释支付意愿和支付额度的主要影响因素。但是，模型分析结果给出的显著性和重要性排序发现游客对有害藻华的科学认识确实会显著影响其支付意愿，但是对支付额度的影响有限。本文通过研究受访者对生态灾害的环境态度及其对支付意愿和支付额度的影响，为准确评估海洋生态灾害造成的环境价值损失提供科学依据。

英文摘要:

      Harmful algal blooms are the most prominent problem in marine ecological disasters, threatening the sustainable development of marine economy such as coastal tourism. How to effectively evaluate the impact of harmful algal blooms on the environmental value of coastal tourism is the premise and foundation of promoting the coordinated development of ecological environment protection and tourism resources development. At present, the conditional value method is widely used at home and abroad to quantitatively convert the value of environmental loss by setting up a hypothetical scenario for assessing whether the respondents are willing to pay for the repair of the environment. Therefore, respondents' willingness to pay and its value are the key parameters affecting the value of environmental loss. However, the respondents' willingness to pay and maximum value of payment are affected by many complex factors, and it is difficult to clarify the main factors by conventional statistical analysis methods. This paper creatively introduces the maximum entropy (MaxEnt) and generalized additive models (GAMs) to clarify the main factors affecting these two key parameters from the qualitative analysis of whether they are willing to pay and the quantitative analysis of the amount of payment. Similar to the traditional statistical analysis methods, both MaxEnt and gams models believe that income level, satisfaction with scenic spots, education and age are the main influencing factors to explain the willingness to pay and the amount of payment. However, according to the significance and importance ranking given by the model analysis results, it is found that tourists' scientific understanding of harmful algal blooms will indeed significantly affect their willingness, but the impact on the value is limited. This paper suggests that the respondents' environmental attitude towards ecological disasters affects their willingness to pay and value, so as to provide a scientific basis for accurately assessing the loss of environmental value caused by marine ecological disasters.