平潭县植物多样性研究及其植被景观建模
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摘要
景观多样性业已成为景观生态学在生物多样性研究中的一个重点,本文依托景观生态学理论,对平潭县主要植物群落物种多样性进行了野外调查,并对其进行分析,同时结合卫星遥感影像,对研究区植被景观多样性进行了研究,运用BP神经网络建立了研究区植被景观人工神经网络模型,并对研究区植被景观多样性与自然和社会经济因素间关系进行了拟合,在此基础上对平潭县植被景观形成机制进行了分析,并提出针对平潭的植被建设优化对策。
通过研究得到如下结论：
(1)研究区主要植物群落的总体物种多样性较低,以人工植物群落低于半自然和自然灌丛为特征,群落生长型物种多样性表现为乔木层低于灌木层低于草本层。与物种多样性有关的均匀度指数也反映了相同趋势的人工林和天然灌丛的差异。(2)平潭县植被景观以木麻黄林和次生相思树林为主要构成部分,林地多分布于沿海地带,景观斑块大小以细粒为主,形状指数总体较小,景观异质性较差,各类景观要素所占比例不协调。(3)基于Matlab平台,对研究区植被景观建立了BP神经网络模型,选用居民点个数、风力级别和距海边距离三个因素作为输入变量,植被景观蔓延度指数、分维数和多样性指数作为输出变量,结果表明,该模型的精度高,平均误差为7.44%,最小误差仅为0.18%,在此基础上,将训练好的模型用来对植被景观与自然和社会经济因素的关系进行拟合,得到了较好的效果,说明该模型对植被景观格局的定量分析和预测具有一定的指导意义。
Landscape diversity has become a major concern of landscape ecology in biodiversity research. Relying on landscape ecology theory, this paper did field investigation and analysis about species diversity of main plant community in Pingtan County and combined with satellite remote sensing image, vegetation landscape diversity was discussed in the study area. Using BP neural network, artificial neural network model of vegetation landscape in the area was established and the relationship between vegetation landscape diversity and natural and socio-economic factors are fitted. On this basis, formation mechanism of vegetation landscape in Pingtan County was analyzed and solutions of vegetation construction optimization were put forward.
Conclusions are as follows:(1) The overall species diversity of main plant community is lower in the research area characterized by that artificial plant community is less than semi-natural shrub and growth type species diversity shows tree layer< shrub layer< herb layer. Evenness index which is related to species diversity also reflects the differences between artificial forests and natural shrub land which have the same trend. (2) Casuarina equisetifolia forests and secondary Acacia spp are the main component parts of vegetation landscape in Pingtan County. The woodland is widely distributed along the coast. Landscape patches are mainly fine-grained, shape index is generally small, landscape heterogeneity is worse and various landscape components are not in harmonious proportions. (3) Based on Matlab platform, BP neural network model of vegetation landscape was set up. Number of settlements, wind scale and distance from the coast are chosen as the input variables and contagion (CONTAG) index, dimension and diversity index are output variables. The results indicate that the model has high precision with average error 7.44% and minimum error 0.18%. Then the well-trained model was used to fit the relationship between vegetation landscape diversity and natural and socio-economic factors. It demonstrates that the model might be useful in the quantitative analysis and prediction of vegetation landscape patterns.
通过研究得到如下结论：
(1)研究区主要植物群落的总体物种多样性较低,以人工植物群落低于半自然和自然灌丛为特征,群落生长型物种多样性表现为乔木层低于灌木层低于草本层。与物种多样性有关的均匀度指数也反映了相同趋势的人工林和天然灌丛的差异。(2)平潭县植被景观以木麻黄林和次生相思树林为主要构成部分,林地多分布于沿海地带,景观斑块大小以细粒为主,形状指数总体较小,景观异质性较差,各类景观要素所占比例不协调。(3)基于Matlab平台,对研究区植被景观建立了BP神经网络模型,选用居民点个数、风力级别和距海边距离三个因素作为输入变量,植被景观蔓延度指数、分维数和多样性指数作为输出变量,结果表明,该模型的精度高,平均误差为7.44%,最小误差仅为0.18%,在此基础上,将训练好的模型用来对植被景观与自然和社会经济因素的关系进行拟合,得到了较好的效果,说明该模型对植被景观格局的定量分析和预测具有一定的指导意义。
Landscape diversity has become a major concern of landscape ecology in biodiversity research. Relying on landscape ecology theory, this paper did field investigation and analysis about species diversity of main plant community in Pingtan County and combined with satellite remote sensing image, vegetation landscape diversity was discussed in the study area. Using BP neural network, artificial neural network model of vegetation landscape in the area was established and the relationship between vegetation landscape diversity and natural and socio-economic factors are fitted. On this basis, formation mechanism of vegetation landscape in Pingtan County was analyzed and solutions of vegetation construction optimization were put forward.
Conclusions are as follows:(1) The overall species diversity of main plant community is lower in the research area characterized by that artificial plant community is less than semi-natural shrub and growth type species diversity shows tree layer< shrub layer< herb layer. Evenness index which is related to species diversity also reflects the differences between artificial forests and natural shrub land which have the same trend. (2) Casuarina equisetifolia forests and secondary Acacia spp are the main component parts of vegetation landscape in Pingtan County. The woodland is widely distributed along the coast. Landscape patches are mainly fine-grained, shape index is generally small, landscape heterogeneity is worse and various landscape components are not in harmonious proportions. (3) Based on Matlab platform, BP neural network model of vegetation landscape was set up. Number of settlements, wind scale and distance from the coast are chosen as the input variables and contagion (CONTAG) index, dimension and diversity index are output variables. The results indicate that the model has high precision with average error 7.44% and minimum error 0.18%. Then the well-trained model was used to fit the relationship between vegetation landscape diversity and natural and socio-economic factors. It demonstrates that the model might be useful in the quantitative analysis and prediction of vegetation landscape patterns.
引文
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[19]傅伯杰,陈利顶.景观多样性的类型及其生态意义[J].地理学报,1996,51(5)：454-462.
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[26]Bisseleua D.Herve B.and Stefan Vidal, Plant biodiversity and vegetation structure in traditional cocoa forest gardens in southern Cameroon under different management,Biodiversity and Conservation,2008,Volume 17,number 8:1821-1835.
[27]马建伟、徐瑞松.秦岭金矿区植被景观异常遥感影像特征及影响植物反射光谱异常原因分析[J].国土资源遥感,1996,4(1)：23-29.
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