|BLACKMAN, CHRIS - Western Sydney University|
Submitted to: American Society of Agronomy Meetings
Publication Type: Abstract Only
Publication Acceptance Date: 6/15/2015
Publication Date: 6/15/2015
Citation: Gleason, S.M., Blackman, C.J. 2015. How well do plant hydraulic traits predict species’ distributions across the world. American Society of Agronomy Meetings. 284-3.
Technical Abstract: Climate–trait associations are becoming ever-more important as plant breeding and gene modification efforts enable the targeting of specific traits and specific genes. It is well-understood that climate represents a constraint to the evolution of plant species. Although this statement is intuitive, here we ask what is the outcome of this constraint on the structure and functioning of plants? In particular, how has the heterogeneous distribution of water across the earth’s terrestrial ecosystems affected the distribution of plant hydraulic traits present in those ecosystems. We gathered angiosperm trait data taken from published and unpublished reports and use simple linear models to predict mean climate values from mean trait values. We then evaluate which hydraulic traits appear most closely aligned with commonly measured and readily accessible climate measurements. Embolism resistance of leaves was strongly correlated with mean annual precipitation (MAP) across angiosperms from Chile and Australia (r2 = 0.68, n = 92). The predictive power of this variable was improved further (r2 = 0.72) when “aridity” (MAP / potential evaporation) was used as the climate variable. Across a subset of the world’s angiosperm species, embolism resistance of stem xylem was a poor predictor of habitat MAP (r2 = 0.06, n = 766), as well as aridity (r2 = 0.033; n = 766). However, the predictive power of this trait was markedly improved if the soil water potential (measured as “pre-dawn” leaf water potential) was used in the analysis, rather than MAT or aridity (r2 = 0.24, n = 202). Although plant hydraulic traits appear to be reasonably good predictors of climate, much across-species variation in climate remains unexplained by a single trait, i.e., bivariate axis. This suggests that other traits not examined in this study (e.g., capacitance, cuticle transpiration, biomass partitioning) may also represent important axes of variation.