Abstract:
Across the global flora, photosynthetic and metabolic rates depend more strongly on leaf area than leaf mass. In contrast, intraspecific variation in these rates is strongly mass-dependent. These contrasting patterns suggest that the causes of variation in leaf mass per area (LMA) may be fundamentally different within vs. among species. We developed statistical modeling framework to decompose LMA into two conceptual components – metabolic LMAm (which determines photosynthetic capacity and dark respiration) and structural LMAs (which determines leaf toughness and potential leaf lifespan) – using leaf trait data from tropical forest sites in Panama and a global leaf-trait database. Decomposing LMA into LMAm and LMAs provides improved predictions of leaf trait variation (photosynthesis, respiration, and lifespan). We show that strong area-dependence of metabolic traits across species can result from multiple factors, including high LMAs variance and/or a slow increase in photosynthetic capacity with increasing LMAm. In contrast, strong mass-dependence of metabolic traits within species across light levels results from LMAm increasing from sun to shade. LMAm and LMAs were nearly independent of each other in both global and Panama datasets. Our results suggest that leaf functional variation is multi-dimensional and that biogeochemical models should treat metabolic and structural leaf components separately.
Speaker: Dr. Masatoshi Katabuchi
Affiliation: XTBG
Time: 4:30 PM, Tuesday, Oct. 25, 2022
Venue: ZOOM 会议平台 会议 ID：312 430 8960 会议密码 PWD：666666
ZOOM
会议 ID：312 430 8960
会议密码 PWD：666666
