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Predicting distribution patterns and recent northward range shift of an invasive aquatic plant: Elodea canadensis in Europe

机译:预测入侵性水生植物的分布模式和近期向北移动:欧洲的加拿大伊乐藻

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Climate data and distribution data for the Canadian waterweed Elodea canadensis Michx. from North America, whole Europe and Finland were used to investigate the ability of bioclimatic envelope models to predict the distribution range and recent northward range shift of the species in Europe. Four different main types of models were developed using the North American data, including either three ?baseline? climate variables (growing degrees days, temperature of the coldest month, water balance) or an extended set of seven climate variables, both averaged either over a 30 year time slice or a longer 90 year time slice. Ten different random selections of pseudo-absences were generated from the North American data, on the basis of which ten separate generalized additive models (GAMs) were developed for each main model type. All the 40 developed GAMs were applied first to North America and then transferred to whole Europe and Finland. All the models showed a statistically highly significant accuracy in the three study areas. Although the differences among the four main model types were only minor, the two extended model types showed on average statistically better performance than the two baseline models based on Bayesian information criterion (BIC) values, the amount of deviance explained by the models, resubstitution validation and four-fold cross-validation in North America. They also provided slightly more accurate predictions of climatically suitable area for Elodea canadensis in Finland both in 1961?1984 and 1985?2006. However, the projections from the individual extended models were more variable than projections from the baseline models. Thus model predictions based on a variety of predictor variables but only one selection of pseudoabsences may be subject to biases, and outputs from multiple models should be investigated to better account for uncertainties in modelling. Overall, our results suggest that more attention should be paid to the careful selection of predictor variables and the use of multiple pseudo-absence sets in the ecological niche modelling in order to increase the reliability of the projections of the range shifts of invasive species.
机译:加拿大水草Elodea canadensis Michx的气候数据和分布数据。来自北美,整个欧洲和芬兰的研究人员用来研究生物气候覆盖模型预测欧洲物种分布范围和近期北移的能力。使用北美数据开发了四种不同的主要类型的模型,包括三种“基线”模型。气候变量(日生长程度,最冷月份的温度,水平衡)或一组扩展的七个气候变量,均在30年时间段或更长的90年时间段内平均。从北美数据中生成了十种不同的伪缺失随机选择,在此基础上为每种主要模型类型开发了十个单独的广义加性模型(GAM)。所有40种已开发的GAM都首先应用于北美,然后转移到整个欧洲和芬兰。在三个研究领域中,所有模型均显示出统计学上非常重要的准确性。尽管四种主要模型类型之间的差异很小,但基于贝叶斯信息标准(BIC)值,模型解释的偏差量,重新替代验证,两种扩展模型类型的平均表现比两种基线模型在统计学上更好。和北美的四重交叉验证。他们还提供了1961-1984年和1985-2006年芬兰加拿大Elodea canadensis气候适宜面积的稍微准确的预测。但是,单个扩展模型的预测比基线模型的预测更具可变性。因此,基于各种预测变量的模型预测可能会受到偏见的影响,但只有一个伪缺席选择会受到偏见,因此应研究来自多个模型的输出以更好地考虑建模中的不确定性。总体而言,我们的结果表明,应更加注意对预测变量的谨慎选择以及在生态位建模中使用多个伪缺失集,以增加入侵物种范围变化的预测的可靠性。

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