Data from: Intraspecific trait variation across multiple scales: the leaf economics spectrum in coffee
Martin, Adam R. et al. (2017), Data from: Intraspecific trait variation across multiple scales: the leaf economics spectrum in coffee, Dryad, Dataset, https://doi.org/10.5061/dryad.4t3r6
Understanding species differences in plant functional traits has been critical in developing a mechanistic understanding of terrestrial ecological processes. Greater attention is now being placed on understanding the extent, causes and consequences of intraspecific trait variation (ITV).
ITV is especially important in governing ecological processes in cropping systems, where only a small number of species or genotypes exist in high abundances. However, it remains unclear if key principles of trait-based ecology – namely the leaf economics spectrum (LES) – also describe intraspecific variation in crop functional biology. There also remains a need to understand whether ITV within crops is random, or structured across environmental, management-related or biological levels of organization in agroecosystems.
We employed a nested design field survey to evaluate ITV in leaf traits in coffee (Coffea arabica), one of the world's most widespread tropical crops. We evaluated ITV in eight physiological, morphological and chemical leaf traits, across five nested categorical levels (sites, management systems, spatial location, plant identity, branch identity). We compared patterns of LES trait covariation in coffee, to interspecific patterns observed across over 700 wild plant species.
Patterns of bivariate and multivariate ITV in coffee were broadly consistent with, but considerably weaker than, interspecific patterns associated with the LES, indicating that crops may systematically diverge from global patterns of trait trade-offs observed in wild plants.
Physiological traits varied most widely (coefficient of variation (cv) 42–107%), followed by morphological traits (cv = 15–38%) and chemical traits (cv = 3–11%). Physiological ITV was best explained by the site in which a coffee plant was growing (17–55% explained), while ITV for chemical traits was best explained by management treatments within sites (25–36%); morphological ITV was higher even at the individual tree level or branch level and remained largely unexplained.
Our results support the hypothesis that artificial selection and high-resource agricultural environments lead crops to systematically deviate from patterns of leaf trait covariation observed across wild plants species. Coupled with an understanding of how different traits vary systematically across multiple levels of biological organization, these findings help integrate ITV into future analyses of agroecosystem structure and function.