Department of Plant Biology, Michigan State University, East Lansing, Michigan, 48824, USA.
Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, Michigan, 48824, USA.
Am J Bot. 2023 Mar;110(3):1-11. doi: 10.1002/ajb2.16140. Epub 2023 Mar 4.
Researchers often use ecological niche models to predict where species might establish and persist under future or novel climate conditions. However, these predictive methods assume species have stable niches across time and space. Furthermore, ignoring the time of occurrence data can obscure important information about species reproduction and ultimately fitness. Here, we assess compare ecological niche models generated from full-year averages to seasonal models.
In this study, we generate full-year and monthly ecological niche models for Capsella bursa-pastoris in Europe and North America to see if we can detect changes in the seasonal niche of the species after long-distance dispersal.
We find full-year ecological niche models have low transferability across continents and there are continental differences in the climate conditions that influence the distribution of C. bursa-pastoris. Monthly models have greater predictive accuracy than full-year models in cooler seasons, but no monthly models can predict North American summer occurrences very well.
The relative predictive ability of European monthly models compared to North American monthly models suggests a change in the seasonal timing between the native range to the non-native range. These results highlight the utility of ecological niche models at finer temporal scales in predicting species distributions and unmasking subtle patterns of evolution.
研究人员经常使用生态位模型来预测物种在未来或新的气候条件下可能建立和持续存在的位置。然而,这些预测方法假设物种在时间和空间上具有稳定的生态位。此外,忽略发生时间数据会掩盖有关物种繁殖和最终适应度的重要信息。在这里,我们评估比较了从全年平均值生成的生态位模型与季节性模型。
在这项研究中,我们为欧洲和北美的甘蓝菜生成了全年和每月的生态位模型,以观察在长距离扩散后,物种的季节性生态位是否会发生变化。
我们发现,全年生态位模型在跨大陆的可转移性较低,并且在影响甘蓝菜分布的气候条件方面存在着大陆差异。在较凉爽的季节,每月模型比全年模型具有更高的预测准确性,但没有任何一个每月模型可以很好地预测北美的夏季发生情况。
与北美每月模型相比,欧洲每月模型的相对预测能力表明,从原生范围到非原生范围的季节性时间发生了变化。这些结果突出了在更精细的时间尺度上使用生态位模型预测物种分布和揭示微妙的进化模式的效用。