2018 ESA Annual Meeting (August 5 -- 10)

PS 54-90 - Are more variable species closer to “optimum” across an environmental gradient?

Friday, August 10, 2018
ESA Exhibit Hall, New Orleans Ernest N. Morial Convention Center
Rachel M. Mitchell, School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, Justin P. Wright, Biology, Duke University, Durham, NC and Gregory M. Ames, Biology Department, Duke University, Durham, NC
Background/Question/Methods

The ability to understand how plant traits respond to environmental drivers is critical to being able to predict diversity and distributions of species in a changing world. It is hypothesized that environmental filtering drives species towards an “optimum” trait expression, typically characterized by the community weighted trait mean (CWM), under a given set of environmental conditions. However, recent research has indicated that species can show high levels of intraspecific variability (ITV) in trait values, and that some species show greater variability in functional traits than others. At present, it is unclear whether this differing degree of intraspecific variability allows some species to better respond to prevailing conditions, and express trait values closer to “optimum”. Using trait data from 51 species collected at Ft. Bragg, North Carolina, USA, we asked two questions relating trait variability, and optimality. 1) Do species that express higher variability in specific leaf area (SLA, as measured by the coefficient of variation (CV)) tend to be nearer the CWM on plots where they occur than species with lower CVs? And 2) Do more variable species have a larger range of “optimal” conditions along a soil-moisture gradient, as quantified with Huisman-Olff-Fresco (HOF) models?

Results/Conclusions

Species trait variability for SLA ranged from 0.02 to 0.48. Overall, there was a very weak positive correlation between trait variability, and similarity to the CWM on each plot (P = 0.003, R2 = 0.006). Results of HOF models found wide variability in optimal environmental conditions along the soil-moisture gradient, but more variable species did not necessarily have a greater range of optimal conditions, according to the model. These results indicate that intraspecific trait variability in SLA is not exclusively shaped by prevailing abiotic conditions, and thus trait expression is not necessarily near the “optimum” as quantified by the CWM for any given set of conditions. Furthermore, trait variability does not necessarily correlate with a wider range of “optimum” environmental conditions. These results argue for further research into mechanisms are shaping ITV, and particular focus should be placed on how biotic- and microsite-level conditions shape trait expression within and across species.