Predictability of demographic rates based on phylogeny and biological similarity.

Conservation biology : the journal of the Society for Conservation Biology [Conserv Biol] 2018 Dec; Vol. 32 (6), pp. 1290-1300. Date of Electronic Publication: 2018 Aug 29.

Lack of demographic data for most of the world's threatened species is a widespread problem that precludes viability-based status assessments for species conservation. A commonly suggested solution is to use data from species that are closely related or biologically similar to the focal species. This approach assumes similar species and populations of the same species have similar demographic rates, an assumption that has yet to be thoroughly tested. We constructed a Bayesian hierarchical model with data on 425 plant species to predict demographic rates (intrinsic rate of population growth, recruit survival, juvenile survival, adult survival, and fecundity) based on biological traits and phylogenetic relatedness. Generally, we found small effects of species-level traits (except woody polycarpic species tended to have high adult survival rates that increased with plant height) and a weak phylogenetic signal for 4 of the 5 demographic parameters examined. Patterns were stronger in adult survival and fecundity than other demographic rates; however, the unexplained variances at both the species and population levels were high for all demographic rates. For species lacking demographic data, our model produced large, often inaccurate, prediction intervals that may not be useful in a management context. Our findings do not support the assumption that biologically similar or closely related species have similar demographic rates and provide further evidence that direct monitoring of focal species and populations is necessary for informing conservation status assessments.
(© 2018 Society for Conservation Biology.)

English

Publisher: Blackwell Publishing, Inc. on behalf of the Society for Conservation Biology Country of Publication: United States NLM ID: 9882301 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1523-1739 (Electronic) Linking ISSN: 08888892 NLM ISO Abbreviation: Conserv Biol Subsets: MEDLINE

Conservation of Natural Resources* , Endangered Species*, Animals ; Bayes Theorem ; Demography ; Phylogeny

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