Functional trait frameworks have been useful in understanding plant traits and their contributions to plant fitness. Recent work has used these traits to establish global spectrums of trade-offs between plant growth, resource acquisition, and lifespan. However, questions remain as to how robust these trait spectrums are at local scales with unique abiotic and biotic drivers. In this study we examined a suite of above and below ground physiological, morphological, and phenological traits and directly measured growth in 22 first year and mature coastal sage scrub forbs, grasses, and shrubs in Southern California to determine how trait relationships vary across functional type and compare with global patterns. We used correlation analysis to determine trait trade-offs and their relationships to growth, ANOVA to determine differences in functional type, linear regression for trait spectrum comparison, and principal components analysis to determine the major axes of variation and their relationships to growth.
Results/Conclusions
We found that trade-offs exist for many of the examined traits in both first year and mature plants and define an axis of fast to slow growth consistent with global trait spectrum data. However, we found that an expected strong correlation between SLA and Amass had a steeper slope in our data indicating potentially more extreme pressures driving trade-offs for these two traits. We also observed differences in the fast to slow growth trade-off between functional types with forbs and grasses adopting fast strategies and shrubs demonstrating more conservative ones. Principle components analysis reduced our data into 2 dominant axes - the first was defined by the slow to fast trade-off, while the second was defined by differences in resource allocation to above and below ground tissues. Understanding trade-offs in this resource-limited environment may help uncover the mechanisms related to establishment, community assembly and structure, and species distributions. Land managers especially could use these data to understand the species' realized niche space and integrate this into restoration practices.