首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Habitat history improves prediction of biodiversity in rainforest fauna
【24h】

Habitat history improves prediction of biodiversity in rainforest fauna

机译:生境历史改善了对热带雨林动物群生物多样性的预测

获取原文
获取原文并翻译 | 示例
           

摘要

Patterns of biological diversity should be interpreted in light of both contemporary and historical influences; however, to date, most attempts to explain diversity patterns have largely ignored history or have been unable to quantify the influence of historical processes. The historical effects on patterns of diversity have been hypothesized to be most important for taxonomic groups with poor dispersal abilities. We quantified the relative stability of rainforests over the late Quaternary period by modeling rainforest expansion and contraction in 21 biogeographic subregions in northeast Australia across four time periods. We demonstrate that historical habitat stability can be as important, and in endemic low-dispersal taxa even more important, than current habitat area in explaining spatial patterns of species richness. In contrast, patterns of endemic species richness for taxa with high dispersal capacity are best predicted by using current environmental parameters. We also show that contemporary patterns of species turnover across the region are best explained by historical patterns of habitat connectivity. These results clearly demonstrate that spatially explicit analyses of the historical processes of persistence and colonization are both effective and necessary for understanding observed patterns of biodiversity.
机译:应该根据当代和历史的影响来解释生物多样性的模式;但是,迄今为止,大多数解释多样性模式的尝试都很大程度上忽略了历史或无法量化历史过程的影响。据推测,对多样性模式的历史影响对于分散能力较弱的生物分类群最为重要。通过对澳大利亚东北部四个时间段内21个生物地理分区的雨林扩张和收缩进行建模,我们量化了第四纪后期雨林的相对稳定性。我们证明,在解释物种丰富度的空间格局时,历史栖息地的稳定性可能比当前栖息地面积更重要,并且在地方性低扩散分类群中甚至更重要。相比之下,通过使用当前的环境参数可以最好地预测具有高分散能力的分类单元的地方物种丰富度模式。我们还表明,通过栖息地连通性的历史模式可以最好地解释该地区当代物种更新的模式。这些结果清楚地表明,对持久性和殖民化历史过程的空间明确分析对于理解观察到的生物多样性模式既有效又必要。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号