Pesticide risk assessment for “listed” (threatened and endangered) plant species is hampered by a lack of quantitative demographic information. Demographic information for nonlisted plant species could provide risk-assessment data and inform recovery plans for listed species; however, it is unclear how representative demography of the former would be for the latter. We performed a comparison of plant demographic traits and elasticity metrics to explore how similar these are between listed and nonlisted species. We used transition matrices from the COMPADRE Plant Matrix Database to calculate population growth rate (λ), net reproductive rate (Ro), generation time (Tg), damping ratio (ρ), and summed elasticities for survival (stasis), growth, fertility (reproduction), and evenness of elasticity (EE). We compared these across species varying in conservation status and population trend. Phylogenetic generalized least squares (PGLS) models were used to evaluate differences between listed and nonlisted plants. Overall, demographic traits were largely overlapping for listed and nonlisted species. Population trends had a significant impact on most demographic traits and elasticity patterns. The influence of Tg on elasticity metrics was consistent across all data groupings. In contrast, the influence of λ on elasticity metrics was highly variable, and correlated in opposite directions in growing and declining populations. Our results suggested that population models developed for nonlisted plant species may be useful for assessing the risks of pesticides to listed species. Environ Toxicol Chem 2019;38:2043–2052.
Bibliographical noteFunding Information:
The Supplemental Data are available on the Wiley Online Library at DOI: 10.1002/etc.4472. In addition, the Supplemental Data including R codes will be archived in the University of Minnesota data repository. We are grateful for funding provided by Syngenta Crop Protection and the University of Minnesota. We thank R. Salguero-G?mez for guidance on using the COMPADRE database, D. Mwangola (University of Minnesota) for support with the statistical models, C. Accolla, M. Vaugeois, A. Moore, and A. Schmolke for discussions.
© 2019 SETAC
- Ecological risk assessment
- Endangered Species Act
- Herbaceous plants
- Population modeling