Associate Professor Santa Clara University, United States
All plants face tradeoffs in resource allocation, whether at the intra-organ level (e.g., investing in leaf area vs. leaf thickness) or inter-organ level (e.g., investing in leaf production vs. stem growth). Better understanding these tradeoffs promises to provide insight into the coordination of traits across the whole plant. Furthermore, spatial variation in climate is likely to influence these resource allocation strategies and associated traits. We ask whether trait-environment and allometric relationships can be used to predict how aboveground biomass allocations in grasses (family: Poaceae) respond to environmental change? Our approach was to develop the Stem-Leaf Allometry Model (SLAM), which seeks to predict how stem and leaf allocations change along environmental gradients and how this influences plant height and leaf characteristics. To parameterize SLAM, we measured leaf area, plant height, specific leaf area (SLA; leaf area/leaf dry mass), and specific stem length (SSL; stem length/stem dry mass) for dozens of grass species across 6 continents. For each species, we sampled at least 30 individuals which allowed us to explore both inter- and intra-specific variation in resource tradeoffs. In this talk, we report on early results and describe continuing efforts in this growing cross-continental trait collection network. We show that height is negatively correlated with SSL both within and across species, suggesting species face diminishing returns on biomass investments in stem growth. In other words, taller grasses require more biomass per cm of height than shorter grasses. A similar pattern of diminishing returns was observed across species for leaf area and SLA. However, within species, SLA was invariant with respect to leaf area or increased, suggesting increasing returns on investment. SLAM predictions parameterized for our most sampled species (Avena barbata) produced nonlinear negative relationships between height and leaf area for a given gram of biomass suggesting taller individuals produce less leaf area. Importantly, this tradeoff curve depends on precipitation such that a given allocation fraction will typically produce less height and slightly more leaf area as precipitation increases. This is counterintuitive given plants generally grow taller in wetter regions and would not make sense without considering the tradeoffs between height and leaf area. In conclusion, our study demonstrates that SLAM has the potential to make counter-intuitive predictions which can be readily tested against data. Applying our model to multiple species across broad environmental gradients will improve our understanding of plant growth responses to climate for this economically and ecologically important plant family.
