4.7 Article

Spatial and temporal variability of macrophyte cover and productivity in the eastern Amazon floodplain: A remote sensing approach

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 114, Issue 9, Pages 1998-2010

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2010.04.007

Keywords

Radarsat-1; MODIS; Eastern Amazon; Hierarchical classification; Object-oriented classification; Herbaceous vegetation; Productivity

Funding

  1. NASA [LC-07/LC-32]
  2. NSERC

Ask authors/readers for more resources

Herbaceous aquatic macrophytes cover extensive areas on the floodplains of the Amazon basin and are an important habitat and input of organic carbon. These communities have large intra- and inter-annual variability, and characterization of this variability is necessary to quantify the role of macrophytes in the ecology and biogeochemistry of the floodplain. A novel approach for mapping the temporal evolution of aquatic vegetation in the Amazon floodplain, which could be adapted to other spatially and temporally changing environments, is presented Macrophyte cover varied seasonally and Inter-annually, ranging between 104 and 198 km(2) for the floodplain examined (total area, 984 km(2)). The observed evolution of plant distribution indicated a spatial and temporal partition of macrophyte communities into short-lived and annual groups. A simulation of macrophyte net primary production (NPP) based on the mapping results indicated that at least 3% of NPP could be attributed to the short-lived communities. The present results suggest that significant changes in the macrophyte's contribution to carbon cycling in the Amazon floodplain could occur as a result of the predicted increase in frequency of drought years for the Amazon system due to climate change. (C) 2010 Elsevier Inc. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available