The compadrePlant Matrix Database: an open online repository for plant demography

Abstract

Summary1. 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 *Correspondence author. E-mails: salguero@demogr.mpg.de; compadre-contact@demogr.mpg.de † Joint senior author. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. 2015, 103, 202-218 doi: 10.1111/1365-2745.12334 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. Journal of Ecology2. 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. 3. 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 opensource 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. 4. 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.

Fast–slow continuum and reproductive strategies structure plant life-history variation worldwide

“…The rate of shrinking of individual plants (retrogressive growth, ρ) is negatively loaded onto PCA 2. Mature life expectancy (L ω ), the period between age of sexual maturity (L α ) and mean life expectancy (21), is a poor contributor to PCA 1 or 2 and is the main driver of PCA 3 (loading = −0.84) (SI Appendix, Table S4). …”

“…Transitioning from negative to positive scores on PCA 2 (hereafter, the reproductive strategy axis), plants attain greater lifetime reproductive success and frequency of reproduction and tend to shrink less. The difference in the way size typically is measured in herbs (helophytes, geophytes, and hemicryptophytes) vs. trees (nano-/meso-/megaphanerophytes) (21,22,26,27) does not appear to explain the orientation of retrogressive growth in the PCA space, because this pattern remains consistent in analyses of either group separately (SI Appendix, Table S7). More generally, a robust and consistent association and loading of the life-history traits described above emerges when different subsets of plant growth forms (27), major habitats (28), and taxonomic classes are considered separately (SI Appendix, Tables S6 and S7), suggesting a global pattern throughout the plant kingdom.…”

“…Tropical and subtropical species seem to attain greater longevities than species in arid, temperate, and alpine or arctic regions, a result that may be caused by to the dominance of long-lived trees in tropical communities (29) and/or the nonrandom sampling of demographic studies in these habitats (SI Appendix, Table S5) (16,21). Tall plants such as megaphanerophytes (maximum height >25 m; e.g., Canadian hemlock, Tsuga canadensis) and mesophanerophytes (maximum height 10-25 m; e.g., black pine, Pinus nigra) tend to have greater fastslow axis scores than smaller species such as hemicryptophytes (whose shoot apical meristems are at ground level; e.g., Mead's milkweed, Asclepias meadii) and geophytes (whose shoot apical meristems are below ground; e.g., garlic, Allium sativum) (F 7, 395 = 34.88; P < 0.001) (Fig.…”

The next generation of action ecology: novel approaches towards global ecological research

“…Some databases can even be called from within statistical environments such as R and processed directly, such as the recent launching of high-resolution demographic records of ca. 600 plant species worldwide via the COMPADRE Plant Matrix Database (Salguero-Gómez et al 2015).…”

Sunning themselves in heaps, knots, and snarls: The extraordinary abundance and demography of island watersnakes

“…At the same time, analytical methods for generating demographic parameter estimates have improved and increased in sophistication (Halstead, Wylie, Coates, Valcarcel, & Casazza, 2012; White & Burnham, 1999). Consequently, demographic parameter estimates are becoming available for a widening range of taxa (Mesquita et al., 2015; Salguero‐Gómez et al., 2015, 2016), offering the possibility of improved interpretation and generalization, including evaluations of r ‐ K , slow‐fast, and pace‐of‐life syndromes (Bielby et al., 2007; Dunham, Miles, & Reznick, 1988; Gaillard et al., 1989, 2005; Gangloff et al., 2017; Hille & Cooper, 2015; Réale et al., 2010; Ricklefs & Wikelski, 2002; Wiersma, Muñoz‐Garcia, Walker, & Williams, 2007) and niche classification (Pianka, Vitt, Pelegrin, Fitzgerald, & Winemiller, 2017; Winemiller, Fitzgerald, Bower, & Pianka, 2015). …”