Matrix population models (MPMs) are an important tool for biologists seeking to understand the causes and consequences of variation in vital rates (e.g. survival, reproduction) across life cycles. Empirical MPMs describe the age‐ or stage‐structured demography of organisms and usually represent the life history of a population during a particular time frame at a specific geographical location. The COMPADRE Plant Matrix Database and COMADRE Animal Matrix Database are the most extensive resources for MPM data, collectively containing >12,000 individual projection matrices for >1,100 species globally. Although these databases represent an unparalleled resource for researchers, land managers and educators, the current computational tools available to answer questions with MPMs impose significant barriers to potential COM(P)ADRE database users by requiring advanced knowledge to handle diverse data structures and program custom analysis functions. To close this knowledge gap, we present two interrelated R packages designed to (a) facilitate the use of these databases by providing functions to acquire, quality control and manage both the MPM data contained in COMPADRE and COMADRE, and a user's own MPM data (
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, 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. The combination of the online database and the
- Award ID(s):
- 1655499
- NSF-PAR ID:
- 10457227
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 11
- Issue:
- 2
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- p. 258-264
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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