Meta-analysis is a powerful tool for combining and comparing results across primary studies to: 1) reach more powerful and robust conclusions; and 2) evaluate hypotheses that cannot be addressed in primary studies. As a result, meta-analysis plays a critical role in science and informs policy. For example, in ecology, meta-analysis has been used to understand how the strengths of species interactions vary across diverse environments, how marine organisms with different physiologies respond to ocean acidification, and how greenhouse gas emissions from soils alter feedbacks to global climate change. Despite the apparent simplicity of the steps involved, the number of practitioners, and the statistical rigor with which tools can be applied, MA faces challenges. Indeed, a meta-analyst must make decisions (sometimes explicitly, but often implicitly via defaults in some software packages) about each step when conducting a meta-analysis, including e.g., which metric of effect size to use, whether to use Bayesian approaches, and how to handle non-independence. Each decision can have dramatic effects. For example, different decisions can drastically affect estimated mean effects and inferences (e.g., changing P-values from significant ( < 0.05) to insignificant ( >0.40)). Although there has been extensive research on meta-analysis methods, only recently has the attention been turned to issues specifically germane to ecological data which come with unique challenges (e.g., small numbers of studies, few samples per study, and high among-study variation). Ecologists are becoming increasingly aware of such challenges and are evaluating the methods used in ecological meta-analyses to provide critically needed guidance for the discipline. To promote this advancement of the discipline, this OOS will highlight current issues being evaluated in the application of meta-analysis in ecology. Speakers will bring expertise on the sophisticated underlying conceptual and statistical machinery of meta-analysis but with the goal of addressing issues that are of interest to the general practitioner (most of whom do not have advanced statistical training). In their presentations, speakers will address a key issue confronted during a meta-analysis, review its importance, and/or present the current best practices to address it. This session will both yield "best practices" for ecologists to make the application of meta-analysis in ecology more reliable and robust and point the direction toward future advances.