Realistic representations of plant carbon exchange processes are necessary to reliably simulate biosphere-atmosphere feedbacks. These processes are known to vary over time and space, though the drivers of the underlying rates are still widely debated in the literature. Here, we measured leaf carbon exchange in >500 individuals of 98 species from the Neotropics to high boreal biomes to determine the drivers of photosynthetic and dark respiration capacity. Covariate abiotic (long- and short-term climate) and biotic (plant type, plant size, ontogeny, water status) data were used to explore significant drivers of temperature-standardized leaf carbon exchange rates. Using model selection, we found the previous week's temperature and soil moisture at the time of measurement to be a better predictor of photosynthetic capacity than long-term climate, with the combination of high recent temperatures and low soil moisture tending to decrease photosynthetic capacity. Non-trees (annual and perennials) tended to have greater photosynthetic capacity than trees, and, within trees, adults tended to have greater photosynthetic capacity than juveniles, possibly as a result of differences in light availability. Dark respiration capacity was less responsive to the assessed drivers than photosynthetic capacity, with rates best predicted by multi-year average site temperature alone. Our results suggest that, across large spatial scales, photosynthetic capacity quickly adjusts to changing environmental conditions, namely light, temperature, and soil moisture. Respiratory capacity is more conservative and most responsive to longer-term conditions. Our results provide a framework for incorporating these processes into large-scale models and a data set to benchmark such models.
Keywords: J max; R d; V cmax; V pmax; carbon cycle; carboxylation; climate; electron transport; photosynthesis; soil moisture.
© 2018 by the Ecological Society of America.