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粟一帆,李卫明.基于多项式拟合与广义加性模型的桥边河大型底栖无脊椎动物生境适宜性研究.生态学报,2020,(16).http://dx.doi.org/10.5846/stxb201909201973  
基于多项式拟合与广义加性模型的桥边河大型底栖无脊椎动物生境适宜性研究
Study on Habitat Suitability of Qiaobian River Benthic Macroinvertebrates: Comparison of polynomial curve fitting and generalized additive model
投稿时间:2019-09-20  修订日期:2020-04-21
DOI: " target="_blank" title="转向doi官网查询:http://dx.doi.org">10.5846/stxb201909201973
关键词      
Key Words      
基金项目国家自然科学基金项目(面上项目,重点项目,重大项目)溪流鱼类生境对梯级小水电拆坝的响应机制(51979149)
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  lwm000001@126.com 
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摘要:
探寻精度高,适用性好的水生生物生境适宜性评估模型,为修复受水电开发影响的河流生物栖息地提供支撑,本研究以长江一级支流桥边河为例,采用典范对应分析和Pearson相关性分析,筛选出影响桥边河大型底栖无脊椎动物优势种河蚬生境质量的关键水质因子和其他环境因子,利用广义加性模型与多项式拟合构建生境因子与生物选择的关系。结果表明:①影响桥边河大型底栖无脊椎动物优势种生境质量的主要因子为CODMn、TN、DO、Tur(浊度)和Dep(水深);其中CODMn、TN、Tur、Dep与大型底栖无脊椎动物分布成负相关,DO与大型底栖无脊椎动物分布成正相关;②桥边河流域河蚬的最适宜CODMn含量为1.228 mg/L,CODMn含量升高导致河蚬生境适宜性降低。最适宜TN含量为0.269 mg/L,TN含量升高导致河蚬生境适宜性急剧下降。最适宜DO含量为11.170 mg/L,DO与河蚬生境适宜性呈显著正相关。最适宜Dep为0.3 m,Dep与河蚬生境质量成负相关。最适宜Tur为1.130 NTU,一定范围内Tur的升高导致河蚬生境适宜性降低,但超过某一限定值时,河蚬生境适宜性存在回升的趋势;③线性拟合情况下两种方法均适用;非线性拟合情况下广义加性模型较优于传统多项式拟合模型,且GAM模型在处理离散程度大的数据集时,可以很好的规避多项式拟合过程中出现的过拟合现象。研究显示,GAM模型可以更加精确、合理的模拟生境因子与生物选择之间的关系,对河流生境质量评价和生境修复工作具有重要的实际意义。
Abstract:
The model of habitat suitability of aquatic organisms with high precision and good applicability is of great significance to watershed water resources management and river ecological restoration. In this paper, Canonical correlation analysis (CCA) and Pearson correlation analysis were applied to identify the key habitat factors that influence the habitat quality of benthic macroinvertebrates residing in Qiaobian River, a tributary of the Yangtze. Meanwhile, generalized additive model (GAM) and polynomial fitting model were applied to construct habitat suitability relationship between vital habitat factors and dominant taxa. The results indicated that: (1) Five factors, including CODMn、TN、DO、Tur and Dep, had significant effects on Corbicula fluminea, the dominant species of Qiaobian River. The Corbicula fluminea was negatively correlated with CODMn、TN、Tur and Dep and positively correlated with DO. (2) The optimum CODMn of the Corbicula fluminea in the Qiaobian River was 1.228 mg/L, with the value of CODMn increasing, resulting in decreased habitat suitability for the Corbicula fluminea. The optimal value of TN was 0.269 mg/L, the value of TN increased, resulting in a sharp decline in the habitat suitability of Corbicula fluminea. The optimum value of DO was 11.170 mg/L, the value of DO had a significant positive correlation with the habitat suitability of Corbicula fluminea. The optimum Dep was 0.3 m, and the Dep factor was negatively correlated with the habitat quality. The optimum value of Tur was 1.130 NTU, and the increase of Tur within a certain range led to the decrease of habitat suitability of Corbicula fluminea, but when the value exceeded a certain limit, the habitat suitability of Corbicula fluminea increased. (3) While both methods were applicable in the case of linear fitting, generalized additive model is better than polynomial fitting model in the case of nonlinear fitting, and GAM model can avoid the over-fitting phenomenon in the process of polynomial fitting when dealing with data sets with large discretization degree. The research shows that GAM model can more accurately and reasonably simulate the relationship between habitat factors and biological selection, which has important practical significance for river habitat quality evaluation and habitat restoration.

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