Dennis Emily B, Fagard-Jenkin Calliste, Morgan Byron J T
Butterfly Conservation Dorset UK.
School of Mathematics, Statistics and Actuarial Science University of Kent Kent UK.
Ecol Evol. 2022 Aug 22;12(8):e9200. doi: 10.1002/ece3.9200. eCollection 2022 Aug.
The generalized abundance index (GAI) provides a useful tool for estimating relative population sizes and trends of seasonal invertebrates from species' count data and offers potential for inferring which external factors may influence phenology and demography through parametric descriptions of seasonal variation. We provide an R package that extends previous software with the ability to include covariates when fitting parametric GAI models, where seasonal variation is described by either a mixture of Normal distributions or a stopover model which provides estimates of life span. The package also generalizes the models to allow any number of broods/generations in the target population within a defined season. The option to perform bootstrapping, either parametrically or nonparametrically, is also provided. The new package allows models to be far more flexible when describing seasonal variation, which may be dependent on site-specific environmental factors or consist of many broods/generations which may overlap, as demonstrated by two case studies. Our open-source software, available at https://github.com/calliste-fagard-jenkin/rGAI, makes these extensions widely and freely available, allowing the complexity of GAI models used by ecologists and applied statisticians to increase accordingly.
广义丰度指数（GAI）为根据物种计数数据估算季节性无脊椎动物的相对种群规模和趋势提供了一个有用的工具，并通过对季节变化的参数描述，为推断哪些外部因素可能影响物候和种群统计学提供了可能。我们提供了一个R包，它扩展了先前的软件，使其在拟合参数化GAI模型时能够纳入协变量，其中季节变化由正态分布的混合或提供寿命估计的中途停留模型来描述。该包还对模型进行了推广，以允许在定义的季节内目标种群中有任意数量的窝/代。此外，还提供了进行参数化或非参数化自助法的选项。新包在描述季节变化时使模型更加灵活，季节变化可能取决于特定地点的环境因素，或者由许多可能重叠的窝/代组成，两个案例研究证明了这一点。我们的开源软件可在https://github.com/calliste-fagard-jenkin/rGAI上获取，使这些扩展能够广泛且免费地使用，从而相应地增加了生态学家和应用统计学家使用的GAI模型的复杂性。
