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Rivera-Monroy, V. H., Danielson, T. M., Castañeda-Moya, E., Marx, B. D., Travieso, R., Zhao, X., et al. (2019). Long-term demography and stem productivity of Everglades mangrove forests (Florida, USA): Resistance to hurricane disturbance. Forest Ecology and Management, 440, 79–91.
Abstract: Mangrove wetlands along coastal regions in neotropical northern latitudes are exposed to frequent hurricanes and therefore depend on resistant and resilient attributes to persist after these extreme events. However, few long-term studies have documented mangrove forest dynamics following hurricane disturbance to determine how species-specific phenotypic plasticity, species range shifts, and environmental stress interact to determine recovery trajectories. We present here a comprehensive analysis of Hurricane Wilma’s (hereafter, “Wilma”) impact (category 3, October 2005) on mangrove forest demography and aboveground net productivity in the Everglades, Florida (USA). We determined spatiotemporal patterns over a 15-year period (5 pre- and 10 post-Wilma) in three impacted sites on a productivity gradient along the Shark River Estuary. Hurricane resistance was evident in the low cumulative tree mortality and long-term recovery from defoliation (∼10 years). Aboveground standing carbon stocks were not significantly reduced, as mortality ranged only from 3 to 10%. A negative linear relationship between Leaf Net Primary Productivity (NPPL) and foliar residence time along the estuary shows that an increase in foliar production results in shorter residence time, which is defined by the interannual variation in NPPL rates and recovery periods across sites. We propose this relationship as a proxy of canopy recovery in latitudinal comparative studies across mangrove ecotypes and coastal settings. This work advances ecological disturbance theory and ecological modeling of mangrove forests; specifically, we provide quantitative relationships among structural properties and dynamic processes to validate agent-based demographic and biogeochemical models to forecast the impact of natural and human disturbances on mangrove wetlands under climate change.