five

Long-term Stand Dynamics in Central Massachusetts 1500-2000

收藏
DataONE2018-01-24 更新2024-06-25 收录
下载链接:
https://search.dataone.org/view/https://pasta.lternet.edu/package/metadata/eml/knb-lter-hfr/29/19
下载链接
链接失效反馈
官方服务:
资源简介:
The long-term impact of human land-use is among the most important factors influencing the development of vegetation in New England, a region which experienced extensive agricultural clearance in the 19th century and subsequent reforestation during this century. We employed stand-level pollen stratigraphies and tree-ring chronologies to examine the post-settlement dynamics of hemlock stands which have never been pastured or plowed, representing among the least disturbed parts of the central Massachusetts landscape. Although the sites are currently dominated by large Tsuga canadensis individuals and give the impression of great age and stability, our results indicate that they have dynamic developmental histories driven by exogenous disturbance factors, including logging, forest pathogens, catastrophic wind disturbance, and fire. Sites containing pre-settlement pollen assemblages indicate stand compositions at this time which were substantially different from each other and from modern assemblages. Pollen assemblages similar to those of modern stands were not established in any of our sites until the 20th century and the mechanisms by which these assemblages arose was considerably different in each stand, indicating great flexibility of forest response to a variety of disturbance types.

人类土地利用的长期影响是影响新英格兰(New England)地区植被发育的最重要因素之一。该区域在19世纪经历了大规模的农业开垦,并于本世纪随后开展了森林恢复。本研究采用林分水平花粉地层学(stand-level pollen stratigraphies)与树木年轮年代学(tree-ring chronologies),对从未经放牧或翻耕的铁杉林分(hemlock stands)的定居后动态进行了分析,这些林分代表了马萨诸塞州中部受干扰程度最低的区域之一。尽管这些样地目前以高大的加拿大铁杉(Tsuga canadensis)个体占优,且给人以古老且稳定的直观印象,但研究结果表明,它们的发育历史具有动态性,由采伐、森林病原物、灾难性风扰以及火灾等外源干扰因子驱动。含有定居前花粉组合的样地显示,彼时的林分组成彼此间差异显著,且与现代花粉组合也存在较大差异。直至20世纪,本研究所有样地才形成与现代林分相似的花粉组合,且各林分形成此类组合的机制存在显著差异,这表明森林对多种干扰类型的响应具有极强的灵活性。
创建时间:
2019-04-05
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作