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首页> 外文期刊>Journal of Insect Conservation >Can climatic variables improve phenological predictions for butterfly species?
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Can climatic variables improve phenological predictions for butterfly species?

机译：气候变量可以改善蝴蝶物种的酚类预测吗？

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摘要

Changes in butterfly phenology due to climate changes have led to the need for models based on factors other than calendar date to predict butterfly development, allowing those monitoring their populations to increase the effectiveness of field surveys. In this study, we developed two simple climatic models, one using yearly accumulated growing degree days (GDD) and the other using yearly accumulated shortwave radiation flux densities (SRAD), to determine if these variables can predict first emergence of three butterfly species with less error than an approach based on the average ordinal date of first observation at a site. Furthermore, we investigated whether combining our two models would increase our ability to predict the timing of first emergence. We determined that GDD models were better at predicting first emergence than were ordinal date models and SRAD models for all species tested; however, the actual variation among these models was so small that any additional effort required to develop GDD models would not justify their use as a replacement for the simpler ordinal date models at this time, although as climate changes they may become more useful. We also determined that combined models did not improve the ability to predict first emergence.
机译：由于气候变化导致蝴蝶候选的变化导致了基于日历日期以外的因素的模型的需求，以预测蝴蝶的发展，允许这些监测他们的人群以提高现场调查的有效性。在这项研究中，我们开发了两个简单的气候模型，一个使用年度累积的生长度（GDD）和另一个使用年累积的短波辐射助焊剂密度（SRAD），以确定这些变量是否可以预测三种蝴蝶物种的首先出现误差比基于站点上第一观察的平均序数日期的方法。此外，我们调查了组合我们的两个模型是否会增加我们预测首次出现时机的能力。我们确定GDD模型更好地预测首次出现，而不是测试所有物种的顺序模型和SRAD模型;然而，这些模型之间的实际变化是如此之小，因此在此时，开发GDD模型所需的任何额外努力都不会使其用作更换顺序日期模型的用途，尽管随着气候变化，它们可能变得更加有用。我们还确定组合模型没有提高预测首次出现的能力。

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