The University of Queensland, Ecology Centre, St Lucia, Queensland 4072, Australia.
Conserv Biol. 2011 Aug;25(4):758-66. doi: 10.1111/j.1523-1739.2011.01670.x. Epub 2011 Apr 11.
Estimating the abundance of migratory species is difficult because sources of variability differ substantially among species and populations. Recently developed state-space models address this variability issue by directly modeling both environmental and measurement error, although their efficacy in detecting declines is relatively untested for empirical data. We applied state-space modeling, generalized least squares (with autoregression error structure), and standard linear regression to data on abundance of wetland birds (shorebirds and terns) at Moreton Bay in southeast Queensland, Australia. There are internationally significant numbers of 8 species of waterbirds in the bay, and it is a major terminus of the large East Asian-Australasian Flyway. In our analyses, we considered 22 migrant and 8 resident species. State-space models identified abundances of 7 species of migrants as significantly declining and abundance of one species as significantly increasing. Declines in migrant abundance over 15 years were 43-79%. Generalized least squares with an autoregressive error structure showed abundance changes in 11 species, and standard linear regression showed abundance changes in 15 species. The higher power of the regression models meant they detected more declines, but they also were associated with a higher rate of false detections. If the declines in Moreton Bay are consistent with trends from other sites across the flyway as a whole, then a large number of species are in significant decline.
估算迁徙物种的数量很困难,因为不同物种和种群的变异性来源有很大差异。最近开发的状态空间模型通过直接对环境和测量误差进行建模来解决这个变异性问题,尽管它们在检测下降方面的效果在经验数据中还没有得到充分验证。我们将状态空间模型、广义最小二乘法(带有自回归误差结构)和标准线性回归应用于澳大利亚昆士兰州东南部莫尔顿湾湿地鸟类(涉禽和燕鸥)数量的数据中。该湾有 8 种具有国际重要意义的水鸟,是东亚-澳大利亚候鸟大迁徙的主要终点之一。在我们的分析中,我们考虑了 22 种迁徙物种和 8 种留鸟。状态空间模型确定了 7 种候鸟的数量明显下降,1 种候鸟的数量明显增加。15 年来,候鸟数量下降了 43-79%。具有自回归误差结构的广义最小二乘法显示 11 种物种的数量发生了变化,标准线性回归显示 15 种物种的数量发生了变化。回归模型的更高功率意味着它们检测到更多的下降,但它们也与更高的错误检测率相关。如果莫尔顿湾的下降与整个迁徙路线上其他地点的趋势一致,那么大量物种正处于显著下降的状态。