Abstract Mangrove trees are invading saltmarshes at subtropical ecotones globally, but the consequences of this vegetation shift for ecosystem sustainability remain unknown. Using the Coastal Wetland Equilibrium Model (CWEM) to simulate vegetation survival and sediment accretion, we predict that black mangroves,Avicennia germinans, can build soil elevation by 8 mm yr−1, four times greater than saltmarshes at the same site, a finding that is broadly consistent with field measurements of elevation change. Mangroves build elevation more rapidly than saltmarshes by producing much greater live and labile belowground biomass, but when mangroves drown, they abruptly lose elevation due to the large volume of quickly decomposing necromass following flood‐induced mortality. Under certain conditions, young mangroves can accumulate root mass faster than mature trees and, therefore, gain elevation more rapidly, but neither saltmarshes nor mangroves of any age survived a centenary sea‐level increase of 100 cm. The acceleration of sea‐level rise that coastal marshes are encountering raises the question of how coastal wetlands should be optimally managed and these results provide managers with predictive information on wetland building capacity of mangroves versus marshes.
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NEER: Mangrove Resilience on Sanibel Island:Subtitle
The focus of this project was to investigate the performance of mangroves as nature-based solutions for coastal protection. The data can be used by coastal and ecological engineers to capture physical dimensions of mangroves and correspondingly develop 3D models for numerical and experiments.
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- Award ID(s):
- 1939275
- PAR ID:
- 10599578
- Publisher / Repository:
- Designsafe-CI
- Date Published:
- Subject(s) / Keyword(s):
- Hurricane Ian Mangroves Florida Sanibel Island Terrestrial LiDAR Multispectral RAPID Facility
- Format(s):
- Medium: X
- Institution:
- Louisiana State University
- Sponsoring Org:
- National Science Foundation
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Abstract Mangroves are important ecosystems for coastal biodiversity, resilience and carbon dynamics that are being threatened globally by human pressures and the impacts of climate change. Yet, at several geographic range limits in tropical–temperate transition zones, mangrove ecosystems are expanding poleward in response to changing macroclimatic drivers. Mangroves near range limits often grow to smaller statures and form dynamic, patchy distributions with other coastal habitats, which are difficult to map using moderate‐resolution (30‐m) satellite imagery. As a result, many of these mangrove areas are missing in global distribution maps. To better map small, scrub mangroves, we tested Landsat (30‐m) and Sentinel (10‐m) against very high resolution (VHR) Planet (3‐m) and WorldView (1.8‐m) imagery and assessed the accuracy of machine learning classification approaches in discerning current (2022) mangrove and saltmarsh from other coastal habitats in a rapidly changing ecotone along the east coast of Florida, USA. Our aim is to (1) quantify the mappable differences in landscape composition and complexity, class dominance and spatial properties of mangrove and saltmarsh patches due to image resolution; and (2) to resolve mapping uncertainties in the region. We found that the ability of Landsat to map mangrove distributions at the leading range edge was hampered by the size and extent of mangrove stands being too small for detection (50% accuracy). WorldView was the most successful in discerning mangroves from other wetland habitats (84% accuracy), closely followed by Planet (82%) and Sentinel (81%). With WorldView, we detected 800 ha of mangroves within the Florida range‐limit study area, 35% more mangroves than were detected with Planet, 114% more than Sentinel and 537% more than Landsat. Higher‐resolution imagery helped reveal additional variability in landscape metrics quantifying diversity, spatial configuration and connectedness among mangrove and saltmarsh habitats at the landscape, class and patch scales. Overall, VHR satellite imagery improved our ability to map mangroves at range limits and can help supplement moderate‐resolution global distributions and outdated regional maps.more » « less
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