Abstract

Abstract Population dynamics play a central role in the historical and current development of fundamental and applied ecological science. The nascent culture of open data promises to increase the value of population dynamics studies to the field of ecology. However, synthesis of population data is constrained by the difficulty in identifying relevant datasets, by the heterogeneity of available data and by access to raw (as opposed to aggregated or derived) observations. To obviate these issues, we built a relational database, popler, and its R client, the library "popler". popler accommodates the vast majority of population data under a common structure, and without the need for aggregating raw observations. The "popler" R library is designed for users unfamiliar with the structure of the database and with the SQL language. This R library allows users to identify, download, explore and cite datasets salient to their needs. We implemented popler as a PostgreSQL instance, where we stored population data originated by the United States Long Term Ecological Research (LTER) Network. Our focus on the US LTER data aims to leverage the potential of this vast open data resource. The database currently contains 305 datasets from 25 LTER sites. popler is designed to accommodate automatic updates of existing datasets, and to accommodate additional datasets from LTER as well as non‐LTER studies. The combination of the online database and the R library "popler" is a resource for data synthesis efforts in population ecology. The common structure of popler simplifies comparative analyses, and the availability of raw data confers flexibility in data analysis. The "popler" R library maximizes these opportunities by providing a user‐friendly interface to the online database.

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