Synthesizing population time-series data from the USA Long Term Ecological Research Network

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Author : Aldo Compagnoni

" The availability of large quantities of freely available data is revolutionizing the world of ecological research. Open data maximizes the opportunities to perform comparative analyses and meta-analyses. Such synthesis efforts will increasingly exploit “population data”, which we define here as time series of population abundance. Such population data plays a central role in testing ecological theory and guiding management decisions. One of the richest sources of open access population data is the USA Long Term Ecological Research (LTER) Network. However, LTER data presents the drawback common to all ecological time-series: extreme heterogeneity derived from differences in sampling designs. We experienced this heterogeneity first hand, upon embarking on our own comparative analysis of population data. Specifically, we noticed that heterogeneities in sampling design made datasets hard to compare, and therefore hard to search and analyze.

To alleviate these issues, we created popler (POPulation time series from Long-term Ecological Research): an online PostgreSQL database (henceforth “popler online database”), and associated R client (henceforth “popler R package”). popler accommodates raw population time-series data using the same structure for all datasets. "

Read the full post: https://ropensci.org/blog/2019/08/13/popler/

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