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MEPS prepress abstract   -  DOI: https://doi.org/10.3354/meps13683

Scalability and performance tradeoffs in quantifying relationships between elevation and tidal wetland plant communities

James R. Holmquist*, Lisa Schile-Beers, Kevin Buffington, Meng Lu, Thomas J. Mozdzer, Jefferson Riera, Donald E. Weller, Meghan Williams, J. Patrick Megonigal

*Corresponding author:

ABSTRACT: Elevation is a major driver of plant ecology and sediment dynamics in tidal wetlands, so accurate and precise spatial data are essential for assessing wetland vulnerability to sea-level rise and making forecasts. We performed survey-grade elevation and vegetation surveys of the Global Change Research Wetland, a brackish microtidal wetland in Maryland (USA) in Chesapeake Bay estuary, to both intercompare unbiased digital elevation model (DEM) creation techniques and to describe niche partitioning of several common tidal wetland plant species. We identified a tradeoff between scalability and performance in creating unbiased DEMs, with more data intensive methods, such as kriging performing better than three more scalable methods involving post-processing of light detection and ranging (LiDAR)-based DEMs. The LiDAR Elevation Correction with Normalized Difference Vegetation Index (LEAN) method provided a compromise between scalability and performance, although it underpredicted variability in elevation. In areas where native plants dominated, the sedge Schoenoplectus americanus occupied more frequently flooded areas (median = 0.22, 95% range = 0.09 to 0.31 meters relative to North America Vertical Datum of 1988 [m NAVD88]) and the grass Spartina patens less frequently flooded (0.27, 0.1 to 0.35 m NAVD88). Non-native Phragmites australis dominated at lower elevations than the native graminoids, but had a wide flooding tolerance, encompassing both their ranges (0.19, –0.05 to 0.36 m NAVD88). The native shrub Iva frutescens also dominated at lower elevations (0.20, 0.04 to 0.30 m NAVD88), despite being previously described as a high marsh species. These analyses not only provide valuable context for the temporally rich but spatially restricted data collected at a single well-studied site, but also provide broad insight into mapping techniques and species zonation.