Using sub-meta-analyses to maintain independence among spatiotemporally-replicated demographic datasets

• Main Author: Alex Nicol-Harper
• Format: Lecture
• Language: English
• Published: Zenodo 2022
• Subjects: ESMARConf2022; evidence synthesis; meta-analysis; RStats; Common Eider
• Online Access: https://doi.org/10.5281/zenodo.6077985

We use population modelling to inform conservation for the common eider, a well-studied seaduck of the circumpolar Northern Hemisphere. Our models are parameterised by vital rates measuring survival and reproduction, which we collated through lit review and a call for data. We performed precision-weighted meta-analysis (Doncaster & Spake, 2018) for vital rates with >20 independent estimates: adult annual survival, clutch size (number of eggs laid) and hatching success (proportion of eggs producing hatchlings). We excluded estimates without associated sample size, and included variance estimates where provided/calculable, otherwise inputting the imputed mean variance. Random-effects error structure allowed for likely variation in population means across this species’ wide range; however, all I2 values were <1%, suggesting that most between-study variation was due to chance rather than true heterogeneity. In many cases, studies presented multiple estimates for a given vital rate – e.g. over different study areas and/or multiple years. Where appropriate, we conducted sub-meta-analyses to generate single estimates which could be handled equivalently to non-disaggregated estimates from other studies. These decisions align with the suggestions of Mengersen et al. (2013) and Haddaway et al. (2020) for maintaining independence among heterogeneous samples, and our workflow ensured that the overall meta-analysis was conducted on independent replicate observations for each vital rate.