COS 55-8 - Deconstructing leaf trait variation along tropical environmental gradients

Tuesday, August 8, 2017: 4:00 PM
C125-126, Oregon Convention Center
Lisa Patrick Bentley1, Imma Oliveras2, Nikolaos Fyllas3, Roberta E. Martin4, Agne Gvozdevaite5, Alexander Shenkin6, Norma Salinas7, Theresa Peprah8, Beatriz Marimon9, Ben Hur Marimon-Junior9, Stephen Adu-Bredu10, Gregory P. Asner4, Sandra Díaz11, Brian J. Enquist12 and Yadvinder Malhi13, (1)Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, United Kingdom, (2)Environmental Change Institute School of Geography and the Environment, University of Oxford, Oxford, United Kingdom, (3)Forest Research Institute, Hellenic Agricultural Organization, Greece, (4)Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, (5)University of Oxford, United Kingdom, (6)University of Oxford, Oxford, United Kingdom, (7)Sección Química, Universidad San Antonio Abad del Cusco, Lima, Peru, (8)CSIR-Forestry Research Institute of Ghana, Ghana, (9)Universidade do Estado de Mato Grosso, Brazil, (10)Biodiversity Conservation & Ecosystem Services, Forestry Research Institute of Ghana, Kumasi, Ghana, (11)Instituto Multidisciplinario de Biología Vegetal, Universidad Nacional de Córdoba, Córdoba, Argentina, (12)Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, (13)Environmental Change Institute, University of Oxford, Oxford, United Kingdom

Due to the importance of integrating traits into models of community and ecosystem function, especially in light of current and future climate and land use change, functional traits are measured across contrasting environments. To characterize and partition multiple sources of plant functional trait variation across gradients, we examined environmental, taxonomic and intraspecific sources of variation on a set of key leaf traits (photosynthetic, structural and nutrient) along three environmental gradients in the tropics: an altitudinal gradient in Peru, a precipitation gradient in Ghana, and a water-stress gradient in Brazil. We focused on these sites as these remote regions are often understudied in analyses of trait variation, but have a vital role in global carbon and nutrient cycling. We addressed the following objectives: (1) How is variance of photosynthetic, structural and nutrient traits partitioned among environmental, taxonomic and intraspecific components along different environmental gradients? (2) Are the main sources of variation in photosynthetic, structural and nutrient traits consistent across these environmental gradients? (3) How much of the variability is attributable to species turnover compared to abiotic effects? Traits were empirically sampled across the gradients from 2013-2015 using standardized methodology. Traits and their source of variance were then analyzed with a multilevel nested linear mixed effects analysis.


For photosynthetic traits, environmental variance components were largest along the rainfall gradient compared to the vegetation and elevation gradient. For photosynthetic traits and morphological traits, taxonomic variance was importance across all gradients, with species level variance being most important along vegetation gradient. Intraspecific variation was similar across gradients for photosynthetic traits, but greater than 50% for stomatal conductance along the vegetation gradient. Across all photosynthetic traits, variation at the taxonomic level was the most important in explaining total trait variation. In particular, variation at the tree level, compared to the species, genus, or family level explained the most variation. Across all leaf structural and chemical traits, the intraspecific and taxonomic associated values for each foliar trait were generally similar across the environmental gradients, and most of the traits had consistent intraspecific and taxonomic associated effects across environmental gradients. Most pairwise relationships showed significant relationships between intraspecific component, and to less extent between the taxonomic component. Our results can be used to help develop predictive mechanistic models of how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world.