Schedules of survival, growth and reproduction are key life-history traits. Data on how these traits vary among species and
populations are fundamental to our understanding of the ecological conditions that have shaped plant evolution. Because these
demographic schedules determine population growth or decline, such data help us understand how different biomes shape plant
ecology, how plant populations and communities respond to global change and how to develop successful management tools for
endangered or invasive species.
Matrix population models summarize the life cycle components of survival, growth and reproduction,
while explicitly acknowledging heterogeneity among classes of individuals in the population. Matrix models have comparable
structures, and their emergent measures of population dynamics, such as population growth rate or mean life expectancy, have
direct biological interpretations, facilitating comparisons among populations and species.
Thousands of plant matrix population
models have been parameterized from empirical data, but they are largely dispersed through peer-reviewed and grey literature,
and thus remain inaccessible for synthetic analysis. Here, we introduce the compadre Plant Matrix Database version 3.0, an
open-source online repository containing 468 studies from 598 species world-wide (672 species hits, when accounting for species
studied in more than one source), with a total of 5621 matrices. compadre also contains relevant ancillary information (e.g.
ecoregion, growth form, taxonomy, phylogeny) that facilitates interpretation of the numerous demographic metrics that can
be derived from the matrices.
Synthesis. Large collections of data allow broad questions to be addressed at the global
scale, for example, in genetics (genbank), functional plant ecology (try, bien, d3) and grassland community ecology (nutnet).
Here, we present compadre, a similarly data-rich and ecologically relevant resource for plant demography. Open access to this
information, its frequent updates and its integration with other online resources will allow researchers to address timely
and important ecological and evolutionary questions.