预测在不断变化的世界中的昆虫动态.
1Department of Biological Sciences, Kent State University, Kent, OH 44242, USA; Environmental Science and Design Research Institute, Kent State University, Kent, OH 44242, USA.
Current opinion in insect science
|October 20, 2023
概括
预测昆虫对环境变化的反应是复杂的. 基于特征的模型为更普遍的预测提供了一个有希望的方法,强调仔细的数据评估和代模型的改进.
科学领域:
- 生态生态学 生态生态学
- 环境科学 环境科学
- 昆虫学 昆虫学是一门学科.
背景情况:
- 由于昆虫的多样性和各种各样的监测方法,预测环境压力下的昆虫种群动态具有挑战性.
- 目前的预测模型,包括相关,机械和综合方法,经常与异质性作斗争,缺乏通用性,特别是单一物种模型.
研究的目的:
- 探索挑战和潜在的解决方案,准确预测昆虫对环境压力的反应随着时间的推移.
- 突出基于特征的方法的实用性,作为模型精度和通用性之间的妥协.
主要方法:
- 审查现有的昆虫预测模型,包括相关,机械和综合类型.
- 讨论从空间模型推断时间过程以及广泛社区测量的局限性.
- 强调基于特征的方法的重要性,以捕捉响应范围.
主要成果:
- 生态数据的异质性往往阻止了广泛模型中的机械解释.
- 单个物种模型提供精确但有限的概括性预测.
- 基于特征的方法提供了一个平衡,掩盖了更少的响应范围,同时提供了洞察力.
结论:
- 对于所有建模方法来说,仔细评估时间自关联,最小数据需求和采样偏差的数据对于所有建模方法至关重要.
- 预测模型需要严格的测试,包括近期预测和代修订,以提高未来的准确性.
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