The study on the relationship between plant species diversity and soil factors in the bird island of Qinghai Lake indicated that this island was a low diversity district,its Shannon-Wienner index and species richness ...The study on the relationship between plant species diversity and soil factors in the bird island of Qinghai Lake indicated that this island was a low diversity district,its Shannon-Wienner index and species richness decreased with the increasing soil available K,water soluble salt concentration and pH,and there were significant linear and quadratic correlations between them.Stepwise linear regressions showed that soil available K and water soluble salt were the key factors to estimate Shannon-Wienner index and species richness in this island,respectively,and no correlation was found between species evenness and soil factors.展开更多
天津市北大港湿地自然保护区是东亚—澳大利西亚候鸟迁徙的必经之地。因为拥有丰富的水鸟资源,天津市北大港湿地被列为国际重要湿地。2017年3月至2019年11月,对北大港湿地的鸟类进行了野外调查,结合文献资料和观鸟记录,在北大港湿地共...天津市北大港湿地自然保护区是东亚—澳大利西亚候鸟迁徙的必经之地。因为拥有丰富的水鸟资源,天津市北大港湿地被列为国际重要湿地。2017年3月至2019年11月,对北大港湿地的鸟类进行了野外调查,结合文献资料和观鸟记录,在北大港湿地共记录到鸟类22目57科279种,其中有水鸟9目18科142种;在279种鸟类中,有国家一级重点保护鸟类11种,有国家二级重点保护鸟类36种,有3种、8种和14种鸟类分别为世界自然保护联盟(The International Union for Conservation of Nature,IUCN)受威胁物种红色名录中的极危物种、濒危物种和易危物种,有10种和29种鸟类分别为濒危野生动植物物种国际贸易公约(Convention on International Trade in Endangered Species,CITES)附录I和附录II的物种;从居留型上看,有留鸟19种、旅鸟174种、夏候鸟52种和冬候鸟28种,旅鸟和候鸟物种数量之和占记录到的鸟类总物种数量的91.04%,体现了北大港湿地作为迁徙候鸟重要栖息地的特点。北大港湿地水鸟群落的Shannon-Wiener多样性指数的最大值为3.064,表明该湿地的水鸟群落具有较高的物种多样性。加强对北大港湿地的保护和水鸟监测力度,可以为该国际重要湿地的可持续发展和该区域世界自然遗产地的申报提供科学依据。展开更多
文摘The study on the relationship between plant species diversity and soil factors in the bird island of Qinghai Lake indicated that this island was a low diversity district,its Shannon-Wienner index and species richness decreased with the increasing soil available K,water soluble salt concentration and pH,and there were significant linear and quadratic correlations between them.Stepwise linear regressions showed that soil available K and water soluble salt were the key factors to estimate Shannon-Wienner index and species richness in this island,respectively,and no correlation was found between species evenness and soil factors.
文摘天津市北大港湿地自然保护区是东亚—澳大利西亚候鸟迁徙的必经之地。因为拥有丰富的水鸟资源,天津市北大港湿地被列为国际重要湿地。2017年3月至2019年11月,对北大港湿地的鸟类进行了野外调查,结合文献资料和观鸟记录,在北大港湿地共记录到鸟类22目57科279种,其中有水鸟9目18科142种;在279种鸟类中,有国家一级重点保护鸟类11种,有国家二级重点保护鸟类36种,有3种、8种和14种鸟类分别为世界自然保护联盟(The International Union for Conservation of Nature,IUCN)受威胁物种红色名录中的极危物种、濒危物种和易危物种,有10种和29种鸟类分别为濒危野生动植物物种国际贸易公约(Convention on International Trade in Endangered Species,CITES)附录I和附录II的物种;从居留型上看,有留鸟19种、旅鸟174种、夏候鸟52种和冬候鸟28种,旅鸟和候鸟物种数量之和占记录到的鸟类总物种数量的91.04%,体现了北大港湿地作为迁徙候鸟重要栖息地的特点。北大港湿地水鸟群落的Shannon-Wiener多样性指数的最大值为3.064,表明该湿地的水鸟群落具有较高的物种多样性。加强对北大港湿地的保护和水鸟监测力度,可以为该国际重要湿地的可持续发展和该区域世界自然遗产地的申报提供科学依据。
文摘【目的】深度学习在鸟类物种识别的应用是目前的研究热点,为了进一步提高识别效果,提出一种基于鸟鸣声的Chirplet语图特征和深度卷积神经网络的鸟类物种识别方法。【方法】引入线性调频小波变换(Chirplet transform,CT)计算鸟鸣声信号的语图,输入深度卷积神经网络VGG16模型中,通过对语图进行分类实现鸟类物种的识别。以北京市松山国家自然保护区实地采集的18种鸟类为研究对象,利用Chirplet变换、短时傅里叶变换(short-time fourier transform,STFT)和梅尔频率倒谱变换(Mel frequency cepstrum transform,MFCT)计算得到3个不同的语图样本集,对比分别采用不同的语图样本集作为输入时鸟类物种识别模型的性能。【结果】结果表明:Chirplet语图作为输入时,测试集的平均识别准确率(mean average precision,MAP)达到0.987 1,相对于其他两种输入,得到了更高的MAP值,而且在训练时达到最大MAP值的迭代次数最小。【结论】采用不同的语图特征作为输入,直接影响深度学习模型的分类性能。本文计算的Chirplet语图的鸣声区域相比STFT语图和Mel语图更为集中,特征更明显。因此,Chirplet语图更适合于基于VGG16模型的鸟类物种识别,可以得到更高的MAP值和更快的识别效率。
