Responses of aquatic macrophyte cover and productivity to flooding variability on the Amazon floodplain

Abstract

Macrophyte net primary productivity (NPP) is a significant but understudied component of the carbon budget in large Amazonian floodplains. Annual NPP is determined by the interaction between stem elongation (vertical growth) and plant cover changes (horizontal expansion), each affected differently by flood duration and amplitude. Therefore, hydrological changes as predicted for the Amazon basin could result in significant changes in annual macrophyte NPP. This study investigates the responses of macrophyte horizontal expansion and vertical growth to flooding variability, and its possible effects on the contribution of macrophytes to the carbon budget of Amazonian floodplains. Monthly macrophyte cover was estimated using satellite imagery for the 2003-2004 and 2004-2005 hydrological years, and biomass was measured in situ between 2003 and 2004. Regression models between macrophyte variables and river-stage data were used to build a semiempirical model of macrophyte NPP as a function of water level. Historical river-stage records (1970-2011) were used to simulate variations in NPP, as a function of annual flooding. Vertical growth varied by a factor of ca. 2 over the simulated years, whereas minimum and maximum annual cover varied by ca. 3.5 and 1.5, respectively. Results suggest that these processes act in opposite directions to determine macrophyte NPP, with larger sensitivity to changes in vertical growth, and thus maximum flooding levels. Years with uncommonly large flooding amplitude resulted in the highest NPP values, as both horizontal expansion and vertical growth were enhanced under these conditions. Over the simulated period, annual NPP varied by ca. 1.5 (1.06-1.63 TgCyr(-1) ). A small increasing trend in flooding amplitude, and by extension NPP, was observed for the studied period. Variability in growth rates caused by local biotic and abiotic factors, and the lack of knowledge on macrophyte physiological responses to extreme hydrological conditions remain the major sources of uncertainty.