Are functional traits good predictors of demographic rates? Evidence from five neotropical forests.

By Lourens Poorter, Stephen J. Wright, H. Paz, David D. Ackerly, Richard S. Condit, G. Ibarra‐Manríquez, Kyle E. Harms, J. Licona, M. Martínez‐Ramos, S. Mazer and 4 more. Ecology, 2008

738 citations recorded by the source corpus.

Subfields: Forestry, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/64cf05d679dc628e1ef9e2e485e9cc0e487de302

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Citations in the corpus

Conservative species drive biomass productivity in tropical dry forests (2016, background): “Moreover, life-history theory predicts that large species have lower inherent mortality and turnover (Pianka 1970; Poorter et al. 2008), and dense wood enhances resistance to stem breakage (Van Gelder, Poorter & Sterck 2006; Chave et al. 2009) and hydraulic failure especially in dry environments…”
Abiotic and biotic drivers of biomass change in a Neotropical forest (2017, background): “Although mortality may be well predictable at the individual scale (Chao et al. 2008), species scale (Poorter et al. 2008) and across stands at regional scale (Quesada et al. 2012), mortality across stands at a local scale may be more stochastic as it can be strongly determined by the death of one…”
Functional traits explain variation in plant life history strategies (2013, background): “SLA explained less variation in demographic rates than wood density or seed size (18, 23) and that SLA values are variable and context-dependent (42, 43).”
Linking functional traits and demographic rates in a subtropical tree community: the importance of size dependency (2014, background): “The majority of published studies employ species functional traits and demographic rates for a certain size class or quantify an average trait or rate from a wide range of size classes (Poorter et al. 2008; Martinez-Vilalta et al. 2010; Wright et al. 2010 but see McMahon, Metcalf & Woodall 2011).”
Flowering phenology and height growth pattern are associated with maximum plant height, relative growth rate and stem tissue mass density in herbaceous grassland species (2011, methodology): “Low SD allows for high RGR (King et al. 2005; Poorter, Bongers & Bongers 2006; Poorter et al. 2008), while high SD contributes to resistance to breakage and pathogen attack (Chave et al.”
Fibre wall and lumen fractions drive wood density variation across 24 Australian angiosperms (2013, background): “…be expected to negatively relate to wood density on the basis that higher investment in mass per volume should slow down growth (Enquist et al. 1999) and, while generally true, the correlation is not always strong (Poorter et al. 2008, 2010; Chave et al. 2009; Wright et al. 2010; Fan et al. 2012).”
The world‐wide ‘fast–slow’ plant economics spectrum: a traits manifesto (2014, background): “There is also considerable evidence that key traits of species in any given community vary significantly in relation to the typical light environment inhabited by each species and that such differences help explain performance differences that lead to those differing distributions (e.g. Grime 1965; ”
Functional traits shape ontogenetic growth trajectories of rain forest tree species (2011, background): “These traits represent complementary axes of tree ecological strategies in tropical forests (Table 1) and have been proposed to be important for tree performance through ontogeny (Westoby 1998; Weiher et al. 1999; Poorter et al. 2008).”
Being John Harper: Using evolutionary ideas to improve understanding of global patterns in plant traits (2018, background): “…with higher wood densities tend to have lower mortality rates and lower growth rates (Hietz, Rosner, Hietz- Seifert, & Wright, 2017; Kraft, Metz, Condit, & Chave, 2010; Kunstler et al., 2016; Poorter, 2008; Poorter et al., 2008), but higher ability to tolerate competition (Kunstler et al., 2016).”
Plant functional traits and the multidimensional nature of species coexistence (2015, background): “, interaction coefficients, relative yield, and competitive suppression) (25, 26).”
Community assembly by limiting similarity vs. competitive hierarchies: testing the consequences of dispersion of individual traits (2014, background): “…more often used in community-trait analyses (e.g. specific leaf area, SLA, of the LHS system) are often considered a proxy for growth rate based on their strong correlations (Reich, Walters & Ellsworth 1992; Wright & Westoby 1999; Shipley et al. 2005; Poorter et al. 2008; Donovan et al. 2010).”
Does functional trait diversity predict above‐ground biomass and productivity of tropical forests? Testing three alternative hypotheses (2015, background): “For the dominant species (those forming 60–80% of initial AGB), we measured eight functional traits of known importance for plant growth and survival (Poorter et al. 2008; Wright et al. 2010), and ecosystem biomass stocks and productivity (e.”
Functional traits and the growth-mortality trade-off in tropical trees. (2010, methodology): “Poorter et al. (2008) speculated that trait–performance relationships would be stronger for saplings than for the large trees that they considered.”
Plant functional type classifications in tropical dry forests in Costa Rica: leaf habit versus taxonomic approaches (2010, background): “Combinations of quantitative plant traits also have been shown to explain variation in litter decomposition (Santiago 2007), community assembly (Cavender-Bares, Kitajima&Bazzaz 2004), co-existence of tree species in diverse Amazonian forests (Kraft, Valencia & Ackerly 2008), demographic rates (Poort”