基于灰色拓扑理论的草地生态系统损害基线动态预测

生态环境损害鉴定评估是生态环境损害赔偿制度有效执行的关键。生态环境损害基线贯穿生态环境损害鉴定评估的整个过程,是生态环境损害确认与损害修复的重要依据与标准。历史数据法是损害基线确认的优先采用方法,以损害发生前3年平均值作为静态基线值,难以体现基线的动态性与不确定性,因此生态环境损害基线的动态研究尤为重要。选取净初级生产力(NPP)作为草地生态系统损害表征指标,以锡林浩特市巴彦宝力格矿区未开发建设前2000—2008年NPP历史数据为基础,运用灰色拓扑模型对矿区2009—2011年年均NPP基线值进行动态预测,并将其与静态基线值进行比较,探讨该方法的可行性。结果表明:灰色拓扑模型建模精度高,相对误差小,该模型预测平均相对误差为2.88%,且2009—2011年的拟合曲线与实际变化曲线相一致,将该模型预测结果作为动态基线值比静态基线值更能反映现实情况。构建的植被NPP基线动态预测方法为基线的确定提供一种解决思路,具有一定的应用价值与科学合理性。

The damage baseline of the grassland ecosystem based on grey topology theory: A dynamic prediction study

Evaluation of the ecological/environmental damage is critical for the effective implementation of the ecological/environmental damage compensation system. The baseline is a critical gauge and standard for damage validation and successful restoration, which runs through the entire process of the ecological/environmental damage assessment. The method of historical data, which uses the average value of 3 years before the damage occurred, is preferentially used to ascertain the static baseline. However, reflecting the dynamics and uncertainty of the baseline is challenging. Thus, it is imperative to explore the dynamic baseline of the ecological/environmental damage. In this study, we selected the net primary productivity (NPP) as an indicator of the grassland ecosystem damage. Based on the historical data of NPP (2000-2008) before the development in the Bayanbaolige mining area, we estimated the dynamic baselines of NPP between 2009 and 2011 using the grey topological model and assessed the availability of the method by comparing with the static baseline values. The grey topological prediction model exhibited high modeling accuracy and small relative error. Compared with the actual values from 2000 to 2008, the average relative error was 2.88%. Meanwhile, the fitting curve of 2009-2011 was consistent with the actual curve. The findings of the grey topological model as dynamic baselines were better than that of the static baseline in presenting the real situation. In conclusion, the prediction method of the grey topological model offers a possible solution to the baseline determination, which has application value and scientific rationality.