Dynamic Models for Longitudinal Butterfly Data
Dynamic Models for Longitudinal Butterfly Data
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DOI：
10.1007/s13253-015-0216-3
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发表时间：
2016-03-01
影响因子：
1.4
通讯作者：
Brereton, Tom
中科院分区：
文献类型：
--
作者：
Dennis, Emily B.;Morgan, Byron J. T.;Brereton, Tom
我们提出的模型提供了纵向季节性昆虫计数数据的简洁描述。这种方法首次对育雏生产力的关键参数进行了估计。它可以应用于单化和二化物种。对于后者，每窝的生产力是单独估计的，这会产生新的指数来表明不同世代的贡献。这些模型基于离散分布，其期望反映季节性数据的基本性质。生产力以确定性、自回归的方式包含在内，使每个群体的数据成为前一个群体的数据的函数。集中的可能性会带来可观的效率增益。使用现象学模型和机械模型，包括天气和特定地点的协变量。插图是使用英国蝴蝶监测计划的数据提供的，但该方法是完全通用的。当对北移和温度进行生产力估计回归时，会发现一致的关联。例如，对于单性物种来说，在温和的冬季之后，生产力通常会降低，并且由于气候变化，所有物种的成虫平均羽化时间都随着时间的推移而变早。拟合动态模型的预测有可能提高对基本人口统计过程的理解。这对于英国蝴蝶等昆虫很重要，其中许多物种的数量正在减少。本文的补充材料可在线获取。
We present models which provide succinct descriptions of longitudinal seasonal insect count data. This approach produces, for the first time, estimates of the key parameters of brood productivities. It may be applied to univoltine and bivoltine species. For the latter, the productivities of each brood are estimated separately, which results in new indices indicating the contributions from different generations. The models are based on discrete distributions, with expectations that reflect the underlying nature of seasonal data. Productivities are included in a deterministic, auto-regressive manner, making the data from each brood a function of those in the previous brood. A concentrated likelihood results in appreciable efficiency gains. Both phenomenological and mechanistic models are used, including weather and site-specific covariates. Illustrations are provided using data from the UK Butterfly Monitoring Scheme, however the approach is perfectly general. Consistent associations are found when estimates of productivity are regressed on northing and temperature. For instance, for univoltine species productivity is usually lower following milder winters, and mean emergence times of adults for all species have become earlier over time, due to climate change. The predictions of fitted dynamic models have the potential to improve the understanding of fundamental demographic processes. This is important for insects such as UK butterflies, many species of which are in decline. Supplementary materials for this article are available online.