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Data from: An evolutionary modelling approach to understanding the factors behind plant invasiveness and community susceptibility to invasion

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DataONE2011-05-25 更新2024-06-27 收录
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Ecologists have had limited success in understanding which introduced species may become invasive. An evolutionary model is used to investigate which traits are associated with invasiveness. Translocation experiments were simulated in which species were moved into similar but evolutionary younger communities. The main findings were that species that had previously been the most abundant in their original communities have significantly higher rates of establishment than did species that had previously occurred at low abundance in their original community. However if establishment did occur, previously abundant and previously low abundance species were equally likely to become dominant and were equally likely to exclude other species from their new community. There was a suggestion that the species that were most likely to establish and exclude others were “genetically” different. When species that had evolved in different simulations (but with identical environmental conditions), were transplanted into communities that had also evolved in different simulations of the same conditions, the outcomes were difficult to predict. Observed rates of establishment and subsequent competitive dominance were observed to be species and community combination specific. This evolutionary study represents a novel in silico attempt to tackle invasiveness in an experimental framework, and may provide a new methodology for tackling these issues.

生态学界在解析哪些外来物种可能演变为入侵物种方面,迄今仅取得有限进展。本研究借助演化模型,探究与入侵性相关的物种功能性状。研究模拟了物种移殖实验:将物种移植至结构相似但演化历程更短的群落中。主要研究结果显示:相较于原生群落中原本丰度较低的物种,原生群落中原本占据绝对优势的物种,其在新环境中的种群定殖率显著更高。但若物种成功定殖,则原生群落中原本优势与低丰度的物种,其成为群落优势种的概率无显著差异,且二者排斥新群落中其他物种的能力亦相当。另有研究提示,最易完成定殖并排斥其他物种的物种,其“遗传特性”存在差异。当在不同模拟场景(但环境条件完全一致)下演化得到的物种,被移植至同样在相同环境条件下通过不同模拟场景演化形成的群落中时,实验结果往往难以预测。观测结果显示,物种的定殖率及其后续获得的竞争优势地位,均具有物种-群落组合特异性。本项演化研究在实验框架下,以全新的虚拟实验(in silico)方式探究物种入侵性问题,或可为解决此类生态学难题提供全新的研究方法。
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2011-05-25
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