社会-经济-自然复合生态系统生态位评价模型——以四川省为例

在深入分析区域资源、环境、社会、经济综合系统基础上,建立了四川省2001—2010年社会-经济-自然复合生态系统生态位评价指标体系,复合生态系统综合生态位包括资源、环境、经济和社会4个子系统生态位。将耦合投影寻踪模型应用于复合生态系统生态位评价,其中,采用并行模拟退火算法对评价模型参数进行优化。研究结果表明:2001年—2010年四川省复合生态位呈现先降后升的趋势,复合生态位评价值从2001年3.1325下降到2005年的2.8499,从2005年开始,复合生态位逐渐增加,到2010年增加到3.3304。表明环境重视程度的提高,环保意识的加强,促进了复合生态位的提高,区域自然生态和环境得以改善。最佳投影方向各分量的大小反映了各评价指标对生态位评价等级的影响程度,值越大则对应的评价指标对生态位评价等级的影响程度越大。区域生态位评价等级指标的影响程度最大的10项中有4项是环境生态位子系统指标,表明环境生态位子系统对综合生态位影响最大。发展过程中经济生态位子系统和社会生态位子系统指标值相关系数为0.9957,表明两子系统基本上是保持同步发展。而经济生态位和环境生态位子系统指标值相关系数为-0.9346,呈现明显的负相关关系。资源子系统呈现上升趋势。模拟退火优化的投影寻踪耦合模型应用于复合生态位评价,具有实用性和可行性,为区域生态管理科学决策提供重要依据。

An ecological niche evaluation model of social, economic, and natural complex ecosystems: a case study in Sichuan Province

Human societies are essentially composed of three different systems:social, economic, and natural. Studies on the ecological niche of social, economic, and natural complex ecosystems has significant importance on the activities and lives of humans in a complex ecosystem and the sustainable development of land. In this study, a set of indicator systems were established to evaluate the ecological niche of a complex ecosystem in Sichuan Province from 2001 to 2010, based on the evaluation index theory of sustainable development, urban livability, and human development. The integrated ecological niche of the complex ecosystem included four sub-niches:natural resources, environment, economy, and society. These sub-niches comprised many single-item indicators. A coupling projection pursuit model, in which a parallel-simulated annealing algorithm was employed in parameters of optimization, was applied to quantitatively analyze and assess the ecological niche of the complex ecosystem and each sub-niche. Our results indicate that the ecological niche of the complex ecosystem in Sichuan Province first decreased from 3.1325 in 2001, to 2.8499 in 2005, and then increased to 3.3304 by 2010. Our results indicate that, as public awareness of environmental protection increases, the regional ecological niche index also increases. Additionally, the ecological and environmental situation has improved. The correlation coefficient between the economic niche system and the social niche system was 0.9957, indicating that the two sub-niches develop in synchrony. In contrast, the correlation coefficient between the economic niche system and the environment niche system was -0.9346, suggesting an obvious negative correlation. In total, the resource sub-niche system displayed an upward trend. The best projection direction value reflects the impact of each regional ecological niche evaluation index in the projection pursuit model. The large index value of the ecological niche evaluation corresponds with a great impact on the ecological niche. Four indicators of the environmental-ecological sub-niche have significant impacts on the regional ecological niche. This can further influence the weight of the regional ecological niche evaluation index based on the value of the best projection direction. The ten most influential regional ecological niche evaluation indicators are (from most influential to least influential):Industrial soot emissions > industrial dust emissions > industrial sulfur dioxide emissions > per capita energy yield > total industrial waste water emissions > non-agricultural population accounts for the proportion of the total population > rate of plant coverage in urban areas > per capita revenue > population density > drought affected areas. Of these, four indicators belong to the environmental-ecological niche sub-system, which shows that this system has an essential influence on the entire ecological niche of the area. In comparison, the traditional polygon synthesis index method was used to evaluate the ecological niche in Sichuan Province. The results are in agreement with those calculated by the current projection pursuit algorithm, which verified the correctness of our improved algorithm. Furthermore, the projection pursuit algorithm may be used to discover the rules among data through automatic exploration, and thus has excellent potential in data analysis and processing applications. This algorithm may be used to avoid the subjective one-sidedness of the traditional evaluation method of weight determination. The projection pursuit model, optimized by simulated annealing, is practical and feasible in composite niche evaluation. This model is able to provide an important basis for scientific decision making in regional ecological management.