Sea level rise threatens coastal wetlands worldwide, and restoration projects are implementing strategies that decrease vulnerability to this threat. Vegetation monitoring at sites employing new restoration strategies and determination of appropriate monitoring techniques improve understanding of factors leading to restoration success. In Central California, soil addition raised a degraded marsh plain to a high elevation expected to be resilient to sea level rise over the next century. We monitored plant survival and recruitment using area searches, transect surveys, and unoccupied aircraft systems (UAS) imagery. We used random forest modeling to examine the influence of nine environmental variables on vegetation colonization and conducted targeted soil sampling to examine additional factors contributing to vegetation patterns. Limited pre-construction vegetation survived soil addition, likely due to the sediment thickness (mean = 69 cm) and placement method. After 1 year, about 10% of the initially bare area saw vegetation reestablishment. Elevation and inundation frequency were particularly critical to understanding restoration success, with greatest vegetation cover in high-elevation areas tidally inundated < 0.85% of the time. Soil analysis suggested greater salinity stress and ammonium levels in poorly-vegetated compared to well-vegetated areas at the same elevation. We found that both transect and UAS methods were suitable for monitoring vegetation colonization. Field transects may provide the best approach for tracking early vegetation colonization at moderate-sized sites under resource limitations, but UAS provide a complementary landscape perspective. Beyond elucidating patterns and drivers of marsh dynamics at a newly restored site, our investigation informs monitoring of marsh restoration projects globally.

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As coastal ecosystems become widely recognized for their capacity to sequester carbon (blue carbon), standard accounting methodologies for the generation of carbon credits are being developed. To ensure the applicability of these standards across blue carbon ecosystems, we investigated organic carbon provenance and burial in salt marshes and seagrass meadows of an arid, upwelling-dominated Eastern Pacific lagoon. We found low carbon density in benthic sediments of Bahía de San Quintín (5.9 AE 0.5 mg C cm À3 ), only marginally higher in Zostera marina beds (6.9 AE 0.5 mg C cm À3 ), likely due to remineralization and hydrodynamically driven export of seagrass material, resulting in low carbon burial rates (4.5 AE 2.5 g C m À2 yr À1 ). Sediment organic carbon is mainly controlled by the fraction of fine sediment and its source is largely allochthonous, although sources differ spatially. Salt marshes at San Quintín derive 40% of their organic matter from autochthonous material and exhibit higher carbon burial rates (up to 414.7 AE 28.6 g C m À2 yr À1 ) and sediment carbon densities (32.0 AE 0.7 mg C cm À3 ) compared to benthic sediments. This study emphasizes the connectivity of blue carbon habitats with marsh plant detritus supplementing benthic carbon burial and incorporation of detrital eelgrass in marsh sediments. Our findings highlight the importance of allochthonous organic matter for carbon sequestration in blue carbon habitats, suggesting standard accounting practices that deduct allochthonous organic matter would miss the full potential for carbon burial.

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Coastal wetlands comprise important global carbon sinks; however, anthropogenic disturbance accompanied with accelerating sea level rise threaten their continued survival. In this study, we quantified habitat disturbance to salt marshes in Barnegat Bay, New Jersey, resulting from the construction of ponds for mosquito control. Geographic object‐based image analysis of high‐resolution four‐band aerial imagery revealed that over 7,000 ponds were constructed in the marsh complex with pond densities as high as 290 ponds per km2. Physical disturbance from pond creation and sediment dispersal extended to over 17% of the bay's tidal wetlands. By tracking recolonization of vegetation, we estimated that it took 5 years for 51% vegetation recovery and 10 years for 69% recovery, with complete recover (100%) not expected for more than 50 years. This suggests that efforts to extend the lifespan of drowning coastal wetlands through sediment additions might disrupt carbon dioxide assimilation, as effects of disturbance persist. Focusing on greenhouse gas exchange, our work found that areas of marsh vegetation contribute to carbon assimilation (−42 g C · m−2 · year−1), while ponds and areas of bare peat created by pond excavation were associated with carbon emissions (44 and 125 g C · m−2 · year−1, respectively). These results suggest that the conversion of wetlands to ponds—which is a significant driver of coastal wetland loss worldwide—may convert coastal wetlands from greenhouse gas sinks to sources. Additionally, quantifying the area of vegetation within a marsh (vs. bare ground or open water) is important for quantifying their greenhouse gas mitigation function.

Seagrass meadows are globally important habitats, protecting shorelines, providing nursery areas for fish, and sequestering carbon. However, both anthropogenic and natural environmental stressors have led to a worldwide reduction seagrass habitats. For purposes of management and restoration, it is essential to produce accurate maps of seagrass meadows over a variety of spatial scales, resolutions, and at temporal frequencies ranging from months to years. Satellite remote sensing has been successfully employed to produce maps of seagrass in the past, but turbid waters and difficulty in obtaining low-tide scenes pose persistent challenges. This study builds on an increased availability of affordable high temporal frequency imaging platforms, using seasonal unmanned aerial vehicle (UAV) surveys of seagrass extent at the meadow scale, to inform machine learning classifications of satellite imagery of a 40 km2 bay. We find that object-based image analysis is suitable to detect seasonal trends in seagrass extent from UAV imagery and find that trends vary between individual meadows at our study site Bahía de San Quintín, Baja California, México, during our study period in 2019. We further suggest that compositing multiple satellite imagery classifications into a seagrass probability map allows for an estimation of seagrass extent in turbid waters and report that in 2019, seagrass covered 2324 ha of Bahía de San Quintín, indicating a recovery from losses reported for previous decades.

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