Providing a framework for seagrass mapping in United States coastal ecosystems using high spatial resolution satellite imagery.

Seagrasses have been widely recognized for their ecosystem services, but traditional seagrass monitoring approaches emphasizing ground and aerial observations are costly, time-consuming, and lack standardization across datasets. This study leveraged satellite imagery from Maxar's WorldView-2 and WorldView-3 high spatial resolution, commercial satellite platforms to provide a consistent classification approach for monitoring seagrass at eleven study areas across the continental United States, representing geographically, ecologically, and climatically diverse regions. A single satellite image was selected at each of the eleven study areas to correspond temporally to reference data representing seagrass coverage and was classified into four general classes: land, seagrass, no seagrass, and no data. Satellite-derived seagrass coverage was then compared to reference data using either balanced agreement, the Mann-Whitney U test, or the Kruskal-Wallis test, depending on the format of the reference data used for comparison. Balanced agreement ranged from 58% to 86%, with better agreement between reference- and satellite-indicated seagrass absence (specificity ranged from 88% to 100%) than between reference- and satellite-indicated seagrass presence (sensitivity ranged from 17% to 73%). Results of the Mann-Whitney U and Kruskal-Wallis tests demonstrated that satellite-indicated seagrass percentage cover had moderate to large correlations with reference-indicated seagrass percentage cover, indicative of moderate to strong agreement between datasets. Satellite classification performed best in areas of dense, continuous seagrass compared to areas of sparse, discontinuous seagrass and provided a suitable spatial representation of seagrass distribution within each study area. This study demonstrates that the same methods can be applied across scenes spanning varying seagrass bioregions, atmospheric conditions, and optical water types, which is a significant step toward developing a consistent, operational approach for mapping seagrass coverage at the national and global scales. Accompanying this manuscript are instructional videos describing the processing workflow, including data acquisition, data processing, and satellite image classification. These instructional videos may serve as a management tool to complement field- and aerial-based mapping efforts for monitoring seagrass ecosystems.

Spatial heterogeneity in sediment and carbon accretion rates within a seagrass meadow correlated with the hydrodynamic intensity.

The majority of the carbon stored in seagrass sediments originates outside the meadow, such that the carbon storage capacity within a meadow is strongly dependent on hydrodynamic conditions that favor deposition and retention of fine organic matter within the meadow. By extension, if hydrodynamic conditions vary across a meadow, they may give rise to spatial gradients in carbon. This study considered whether the spatial gradients in sediment and carbon accretion rates correlated with the spatial variation in hydrodynamic intensity within a single meadow. Field measurements were conducted in three depth zones across a Zostera marina L. (eelgrass) meadow in Nahant Harbor, Massachusetts. Four sediment cores were collected in each zone, including one outside the meadow (control) and three within the meadow at increasing distances from the nearest meadow edge. Sedimentation and carbon accretion rates were estimated by combining the measurements of dry bulk density, organic carbon fraction (%OC), 210Pb, and 226Ra. Tilt current meters measured wave velocities within each zone, which were used to estimate turbulent kinetic energy (TKE). Both sediment and carbon accretion rates exhibited spatial heterogeneity across the meadow, which were correlated with the spatial variation in near-bed TKE. Specifically, both accretion rates increased with decreasing TKE, which was consistent with diminished resuspension associated with lower TKE. A method is proposed for using spatial gradients in hydrodynamic intensity to improve the estimation of total meadow accretion rates.

An assessment of marine, estuarine, and riverine habitat vulnerability to climate change in the Northeast U.S.

Climate change is impacting the function and distribution of habitats used by marine, coastal, and diadromous species. These impacts often exacerbate the anthropogenic stressors that habitats face, particularly in the coastal environment. We conducted a climate vulnerability assessment of 52 marine, estuarine, and riverine habitats in the Northeast U.S. to develop an ecosystem-scale understanding of the impact of climate change on these habitats. The trait-based assessment considers the overall vulnerability of a habitat to climate change to be a function of two main components, sensitivity and exposure, and relies on a process of expert elicitation. The climate vulnerability ranks ranged from low to very high, with living habitats identified as the most vulnerable. Over half of the habitats examined in this study are expected to be impacted negatively by climate change, while four habitats are expected to have positive effects. Coastal habitats were also identified as highly vulnerable, in part due to the influence of non-climate anthropogenic stressors. The results of this assessment provide regional managers and scientists with a tool to inform habitat conservation, restoration, and research priorities, fisheries and protected species management, and coastal and ocean planning.