The role of environmental filters and functional traits in predicting the root biomass and productivity in savannas and tropical seasonal forests

摘要

Accurate measures of plant biomass and productivity are important to predict the impacts caused by current anthropogenic changes in the carbon pool. Changes in the carbon pool may be decisive whether plant communities act as sinks or sources for carbon dioxide. However, there are not accurate assessments of savanna and seasonal forest biomass, particularly belowground, which is essential to evaluate their carbon stock. We tested whether we could use soil variables, fire frequency, topography, and functional traits to build simple models to predict the belowground system in savanna and seasonal forest. In central Brazil, we collected root biomass up to 100 cm deep and annual fine root productivity in the top 40 cm of soil with an ingrowth donut, in 100 plots in savanna and 20 plots in seasonal forest. We used increasing complexity general linear modeling to find the models predicting the root biomass and productivity. We found significant models in all cases, even though the explanatory power for the savanna was low. The main ecological forces related to the root biomass and productivity were soils poor in nutrients, foraging for potassium in the savanna and for nitrogen in the forest, drought, resistance to disturbance, and niche complementarity. Reliable estimates of root biomass might be used to replace direct but laborious excavation methods. The carbon stock of savanna and seasonal forest are large and should not be neglected when estimating the impacts caused by climate and land-use changes. (C) 2015 Elsevier B.V. All rights reserved.