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Can seedlings' physiological information improve vegetation distribution predictions at local scales?
Biological Invasions ( IF 2.8 ) Pub Date : 2020-04-17 , DOI: 10.1007/s10530-020-02266-w
F. Calleja , B. Ondiviela , A. Puente , J. A. Juanes

Physiological information has been successfully included in marine Species Distribution Models (SDM) before, but few have considered a previous development stage that could have affected the present-day distribution of the species at local scales. The aim of this study is to analyze the inclusion of physiological information of seedling survival on a correlative SDM based on adult present-day presences. The species were the invasive shrub Baccharis halimifolia and the native saltmarsh Juncus maritimus. For each species, five SDM were established using different approaches: using only experimentally derived physiological data, a correlative model with environmental predictors, additive combinations of presence/absence maps derived from the previous models, and a correlative model with the physiological data as a predictor variable. For B. halimifolia, the inclusion of the physiological data as a predictor variable yielded better results than with the other approaches; with J maritimus, this inclusion achieved an accuracy as high as the model with only environmental variables as predictors. The additive combinations generated less accurate models but offered possible advantages in future specialized studies. The results for B. halimifolia could extrapolate to other invasive species that rely on spreading high amounts of individuals and are more vulnerable in their early stages than in their growing and adult phases. Thus, this approach can improve the capacity for mapping invasive species’ distributions at local scales, and the conservation efforts to control biological invasions in estuaries and coastal ecosystems.



中文翻译:

幼苗的生理信息能否改善地方尺度的植被分布预测?

之前,生理信息已成功地包含在海洋物种分布模型(SDM)中,但是很少有人考虑过以前的发展阶段,该发展阶段可能会影响当前该物种在当地规模上的分布。这项研究的目的是分析基于成年当下存在的相关SDM中幼苗存活的生理信息。该物种是入侵灌木Baccharis halimifolia和本地盐沼Juncus maritimus。对于每个物种,使用不同的方法建立了五个SDM:仅使用实验得出的生理数据,具有环境预测因子的相关模型,从先前模型得出的存在/缺失图的加法组合以及以生理数据作为预测因子的相关模型变量。对于哈密​​瓜芽孢杆菌,将生理数据作为预测变量包括在内比其他方法产生了更好的结果。在J maritimus的帮助下,该包含项的准确性达到了仅以环境变量作为预测因子的模型的准确性。添加剂组合生成的模型精度较低,但在将来的专门研究中可能提供优势。结果为B. halimifolia可以推断为依赖大量散布的其他入侵物种,并且在早期阶段比在成年阶段和成年阶段更加脆弱。因此,这种方法可以提高在地方尺度上绘制入侵物种分布图的能力,并可以控制河口和沿海生态系统中的生物入侵。

更新日期:2020-04-20
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