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Vegetation Development in a Tidal Marsh Restoration Project during a Historic Drought: A Remote Sensing Approach

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Tidal wetland restoration efforts can be challenging to monitor in the field due to unstable local conditions and poor site access. However, understanding how restored systems evolve over time is essential for future management of their ecological benefits, many of which are related to vegetation dynamics. Physical attributes, such as elevation and distance to channel play important roles in governing vegetation expansion in developing tidal wetlands. However, in Mediterranean ecosystems, drought years, wet years, and their resulting influence on salinity levels may also play a crucial role in determining the trajectory of restoration projects, but the influence of weather variability on restoration outcomes is not well-understood. Here, we use object-based image analysis (OBIA) and change analysis of high-resolution IKONOS and WorldView-2 satellite imagery to explore whether mean annual rates of change from mudflat to vegetation are lower during drought years with higher salinity (2011–2015) compared to years with lower salinity (2009–2011) at a developing restoration site in California's San Francisco Bay. We found that vegetation increased at a mean rate of 1,979 m2/year during California's historic drought, 10.4 times slower than the rate of 20,580 m2/year between 2009 and 2011 when the state was not in drought. Vegetation was significantly concentrated in areas closer to channel edges, where salinity stress is ameliorated, and the magnitude of the effect increased in the 2015 image. In our image analysis, we found that different distributions of water, mud, and algae between years led to different segmentation settings for each set of images, highlighting the need for more robust and reproducible OBIA strategies in complex wetlands. Our results demonstrate that adaptive monitoring efforts in variable climates should take into account the influence of weather on tidal wetland ecosystems, and that high-resolution remote sensing can be an effective means of assessing these dynamics.

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