FCE LTER Journal Articles


Knowledge of the spatial and temporal changes caused by episodic disturbances and seasonal variability is essential for understanding the dynamics of mangrove forests at the landscape scale, and for building a baseline that allows detection of the effects of future environmental change. In combination with LiDAR data, we calculated four vegetation indices from 150 Landsat TM images from 1985 to 2011 in order to detect seasonal changes and distinguish them from disturbances due to hurricanes and chilling events in a mangrove-dominated coastal landscape. We found that normalized difference moisture index (NDMI) performed best in identifying both seasonal and event-driven episodic changes. Mangrove responses to chilling and hurricane events exhibited distinct spatial patterns. Severe damage from intense chilling events was concentrated in the interior dwarf and transition mangrove forests with tree heights less than 4 m, while severe damage from intense hurricanes was limited to the mangrove forest near the coast, where tree heights were more than 4 m. It took 4–7 months for damage from intense chilling events and hurricanes to reach their full extent, and took 2–6 yr for the mangrove forest to recover from these disturbances. There was no significant trend in the vegetation changes represented by NDMI over the 27-yr period, but seasonal signals from both dwarf and fringe mangrove forests were discernible. Only severe damage from hurricanes and intense chilling events could be detected in Landsat images, while damage from weak chilling events could not be separated from the background seasonal change.


© 2016 Zhang et al. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

DOI: 10.1002/ecs2.1366

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DEB-1237517, #DBI-0620409, and #DEB-9910514. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.