温度波动对云杉芽虫落叶景观尺度模式预测的影响

Emily Nicole Black, Deepa S Pureswaran, Katie Elizabeth Marshall
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摘要

昆虫的地理分布范围在很大程度上受其对包括温度在内的应激非生物条件的耐受性的影响。尽管许多关于昆虫热耐受性的研究都考虑了温度暴露,但温度暴露的频率正逐渐成为昆虫适应性的一个重要而通常被忽视的驱动因素。东部云杉芽虫(Choristoneura fumiferana)是加拿大针叶林中的一种鳞翅目落叶害虫,它的爆发会导致树木大规模死亡。研究表明,温度波动的频率会影响云杉芽虫在实验室中的越冬存活率;然而,温度波动对云杉芽虫落叶在景观层面上的影响尚未得到研究。我们采用物种分布模型的方法来评估温度波动对云杉芽虫落叶分布和严重程度的影响。我们将公开的 2006-2016 年魁北克云杉芽虫爆发地图与气候、温度波动和森林组成预测因子相结合,训练出一个物种分布模型。我们的模型评估了预测因子对云杉芽虫落叶的影响,并将这些结果与没有温度波动的模型进行了比较。此外,我们还使用使用温度波动预测因子和不使用温度波动预测因子训练的模型预测了 2041-2070 年气候变化条件下未来云杉芽虫的落叶情况,并对结果进行了比较,以确定温度波动对未来落叶预测的影响。我们发现,加入温度波动预测因子后,模型的性能有所提高,而且相对于其他类别的预测因子,这些预测因子的排名靠前。在气候变化条件下,使用温度波动预测因子训练的模型与不使用温度波动预测因子训练的模型相比,对魁北克省和安大略省落叶分布和严重程度的预测也大不相同。这些结果揭示了之前被忽视的温度波动对景观尺度云杉芽虫落叶的重要性,并支持将其纳入昆虫物种分布模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temperature fluctuations influence predictions of landscape-scale patterns of spruce budworm defoliation
The geographic range of insects is heavily influenced by their tolerance for stressful abiotic conditions, including temperature. While many studies on insect thermal tolerance consider temperature exposure, the frequency of temperature exposures is emerging as an important and generally overlooked driver of insect fitness. The (eastern) spruce budworm (Choristoneura fumiferana) is a lepidopteran defoliating pest of coniferous forests across Canada whose outbreaks lead to large-scale tree mortality. Studies have shown the frequency of temperature fluctuations affects spruce budworm overwintering survival rates in the laboratory; however, the influence of temperature fluctuations on spruce budworm defoliation at the landscape level has not been investigated. We used a species distribution model approach to evaluate the influence of temperature fluctuations on the distribution and severity of spruce budworm defoliation. We combined publicly available maps of spruce budworm outbreaks between 2006-2016 in Quebec with climate, temperature fluctuation, and forest composition predictors to train a species distribution model. Our model evaluated how predictors influence spruce budworm defoliation, and compared these results to a model trained without temperature fluctuations. Additionally, we predicted future spruce budworm defoliation under 2041-2070 climate change conditions using the models trained with and without temperature fluctuation predictors and compared the results to determine the effect of temperature fluctuations on future defoliation predictions. We found that model performance improved with the inclusion of temperature fluctuation predictors, and these predictors ranked highly, relative to predictors in other categories. The model trained with temperature fluctuation predictors also predicted vastly different defoliation distribution and severity across Quebec and Ontario than the model trained without them under climate change conditions. These results reveal the previously overlooked importance of temperature fluctuations on landscape-scale spruce budworm defoliation and support their inclusion in insect species distribution models.
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