哀牢山鸟类丰富度垂直分布格局的分析

KIZ OpenIR > 科研部门 > 鸟类学（杨晓君）

	哀牢山鸟类丰富度垂直分布格局的分析
其他题名	Elevational gradients of bird species richness in the Ailao Mountains
	胡莞钊
学位类型	硕士
导师	杨晓君
	2016-07
学位授予单位	中国科学院研究生院
学位授予地点	北京
关键词	物种丰富度海拔梯度插值法哀牢山
其他摘要	探讨和解释生物多样性的空间分布格局一直是生态学和生物地理学研究的热点问题之一，而插值法是该类研究中常用的一个物种丰富度估计方法。但插值法对于解释物种丰富度分布格局的影响及可能带来的偏差尚未得到充分评估。本研究以哀牢山鸟类为例，基于详细的野外调查数据和比较法，分析插值法对物种丰富度垂直分布格局及其解释机制的影响。结果显示基于观测值、稀疏法和Chao1非参数估计法的哀牢山鸟类物种丰富度垂直分布格局均为沿海拔先上升后下降的单峰格局，最高值出现在2000—2100 m海拔段。广域种和中域种物种丰富度也为单峰格局，狭域种的分布格局较不明显。实际蒸散量和中域效应分别较好地解释了哀牢山鸟类物种丰富度垂直分布格局，但两者的解释力都随物种分布宽度减小而减弱。面积和水体也是重要的解释因子，面积的解释力随物种分布宽度减小而增强。狭域种更多地受面积和人为干扰的影响。与观测值和其他两种估计方法相比，基于插值法的同样是单峰格局，但在大多数海拔段有更高的丰富度，曲线更加平滑，具有更小的波动性，峰值出现在更低的1500—1700 m海拔段。插值法对分布格局的解释机制的影响有：显著提高了实际蒸散量和中域效应的解释力；显著降低了面积的解释力；显著减轻了实际蒸散量或者中域效应和其它因子之间的抑制作用。对于不同的分布宽度类型，插值法对中域种影响最大。上述结果表明，插值法在弥补取样不足的同时，也会人为填充物种分布范围中的缺口，在某些区域增加实际没有分布的物种；并削弱造成这些分布范围缺口的非单调连续变量的解释力，同时减小这些变量对于其他变量的抑制作用，而提高受抑制变量的解释力。因此，我们认为在区域尺度上，插值法可能会导致物种丰富度分布格局及其解释机制的偏差。建议使用任何物种丰富度估计方法都应当基于详细和标准的野外实地调查；在插值法造成的较显著的物种丰富度变化时，谨慎判断物种缺失的可能原因是由于取样还是其他因子的影响；同时可以结合稀疏法、非参数估计法等较为稳健的估计方法，以获得可信的和合理的物种丰富度估计值。; Geographic species richness gradients and their underlying mechanisms have long been a major research focus in ecology and biogeography. In these studies, interpolation is a common approach to compensate for the unevenness or incompleteness in sampling effort. However, potential biases introduced by this estimation method remain unclear. Here, based on intensive field surveys of birds along the elevational gradients on the eastern slopes of the Ailao Mountains, we presented the first explicit examination of the influences of interpolation on identification and interpretation of elevational species richness gradients, and discussed potential causes and processes of these influences.Bird species richness based on observed data, rarefaction and Chao 1 non—parametric estimator all showed similar unimodal patterns in the Ailao Mountains, with a peak at the 2000—2100 m elevation band. Large and mediu—ranged species richness also showed hump—shaped patterns, but small—ranged species richness did not have an obvious pattern. Actual evapotranspiration (AET) and the mid—domain effect (MDE) separately provided a good potential explanation for the elevational species richness gradients, and their explanatory powers decreased with decreasing range sizes. Area and the proportion of water bodies were also correlated with species richness, and the explanatory power of area increased with decreasing range sizes. For small—ranged species, only area and the proportion of artificial surfaces were significant explanatory factors. Compared with observed, Chao1 estimated and rarefied richness, interpolated species richness was higher at most elevations and peaked at lower elevation between 1500 m and 1700 m, with considerably fewer fluctuations. Interpolation influences on interpretation of elevational species richness were as follows: (1) The independent effects of AET/MDE on interpolated richness were consistently and significantly larger than those on observed richness. (2) Interpolation consistently and significantly diminished the independent effects of area. (3) All joint effects between AET/MDE and other factors in models based on observed data were negative, and became smaller in magnitude or even positive in models based on interpolated data. These interpolation effects were particularly evident for medium—ranged species. Our results demonstrated that while compensating for biases in sampling effort, interpolation may also spuriously fill genuine distribution gaps, and tend to underestimate the effects of the non—monotonic or discontinuous influencing factors that are responsible for these gaps, and overestimate the effects of other factors actually suppressed by these factors. We conclude that at the regional scale, interpolation method is a potential source of bias in identifying and explaining species richness gradients. We suggest that intensive and standard field surveys are always essential and irreplaceable in improving our understanding of general diversity patterns, whatever estimation techniques are used; interpolation should be used with a careful examination of the species and plots that change substantially through this method, to roughly assess whether these gaps are genuine or sampling artefacts; different estimation methods (e.g. interpolation, rarefaction, non—parametric estimators) should be used together to reduce the biases of sampling and to gain a more accurate assessment of species richness.
学科领域	动物学
语种	中文
文献类型	学位论文
条目标识符	http://ir.kiz.ac.cn/handle/152453/11951
专题	科研部门_鸟类学（杨晓君）
作者单位	中国科学院昆明动物研究所
推荐引用方式 GB/T 7714	胡莞钊. 哀牢山鸟类丰富度垂直分布格局的分析[D]. 北京. 中国科学院研究生院,2016.

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