Bradbury Ian R, Laurel Benjamin, Snelgrove Paul V R, Bentzen Paul, Campana Steven E
Marine Gene Probe Laboratory, Biology Department, Life Sciences Centre, Dalhousie University, Halifax, NS, Canada B3H 4J1.
Proc Biol Sci. 2008 Aug 7;275(1644):1803-9. doi: 10.1098/rspb.2008.0216.
We examine estimates of dispersal in a broad range of marine species through an analysis of published values, and evaluate how well these values represent global patterns through a comparison with correlates of dispersal. Our analysis indicates a historical focus in dispersal studies on low-dispersal/low-latitude species, and we hypothesize that these studies are not generally applicable and representative of global patterns. Large-scale patterns in dispersal were examined using a database of correlates of dispersal such as planktonic larval duration (PLD, 318 species) and genetic differentiation (FST, 246 species). We observed significant differences in FST (p<0.001) and PLD (p<0.001) between taxonomic groups (e.g. fishes, cnidarians, etc.). Within marine fishes (more than 50% of datasets), the prevalence of demersal eggs was negatively associated with PLD (R2=0.80, p<0.001) and positively associated with genetic structure (R2=0.74, p<0.001). Furthermore, dispersal within marine fishes (i.e. PLD and FST) increased with latitude, adult body size and water depth. Of these variables, multiple regression identified latitude and body size as persistent predictors across taxonomic levels. These global patterns of dispersal represent a first step towards understanding and predicting species-level and regional differences in dispersal, and will be improved as more comprehensive data become available.
我们通过分析已发表的数据来研究广泛海洋物种的扩散估计值，并通过与扩散相关因素进行比较，评估这些值在多大程度上代表全球模式。我们的分析表明，扩散研究在历史上侧重于低扩散/低纬度物种，并且我们假设这些研究通常不适用于全球模式，也不具有代表性。我们使用一个包含浮游幼虫持续时间（PLD，318种物种）和遗传分化（FST，246种物种）等扩散相关因素的数据库，研究了扩散的大规模模式。我们观察到不同分类群（如鱼类、刺胞动物等）之间的FST（p<0.001）和PLD（p<0.001）存在显著差异。在海洋鱼类中（超过50%的数据集），沉性卵的比例与PLD呈负相关（R2=0.80，p<0.001），与遗传结构呈正相关（R2=0.74，p<0.001）。此外，海洋鱼类内部的扩散（即PLD和FST）随着纬度、成体大小和水深的增加而增加。在这些变量中，多元回归确定纬度和体型是跨分类水平的持续预测因子。这些全球扩散模式是朝着理解和预测物种水平和区域扩散差异迈出的第一步，随着更多全面数据的获取，将会得到改进。
