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Abstract There is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesize time series of structured population models from 162 populations of 62 plants, mostly herbaceous species from temperate biomes, to link plant population growth rates (λ) to precipitation and temperature drivers. We expect: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; and (2) a higher climate sensitivity in short-lived rather than long-lived species. We find that precipitation anomalies have a nearly three-fold larger effect onλthan temperature. Species with shorter generation time have much stronger absolute responses to climate anomalies. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning. 

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 itsRclient, the library popler.popleraccommodates 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. ThisRlibrary 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.popleris 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 theRlibrary popler is a resource for data synthesis efforts in population ecology. The common structure ofpoplersimplifies 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.