Emerging Sensor Platforms Allow for Seagrass Extent Mapping in a Turbid Estuary and from the Meadow to Ecosystem Scale

Abstract

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.

Beyond habitat boundaries: Organic matter cycling requires a system‐wide approach for accurate blue carbon accounting

“…6). Furthermore, the perennial eelgrass meadows at San Quintín undergo seasonal growth cycles with higher shoot density, aboveground biomass, and larger meadow extent in summer compared to winter (Cabello‐Pasini et al 2003; Krause et al 2021). A seasonal reduction of the seagrass canopy could facilitate sediment resuspension in winter and reverse any canopy effect on sediment and OM trapping that might occur in summer, as indicated by similar median grain size and sorting in vegetated and unvegetated sediments.…”

“…Water depth is mostly shallow (<3 m) with navigable channels spanning the length of both of its arms. Approximately 30% of the areal extent of Bahía de San Quintín is colonized by eelgrass Z. marina with subtidal and vast intertidal meadows (Krause et al 2021). The eelgrass population undergoes a seasonal growth cycle with peak shoot density and biomass in September (Cabello‐Pasini et al 2003).…”

Global historical trends and drivers of submerged aquatic vegetation quantities in lakes

“…Hydroacoustics, however, have the advantage of being a tridimensional assessment of SAV quantities by reporting both SAV height and coverage across depths, thus simultaneously providing an estimation of SAV extent and biomass (Botrel et al, 2022; Duarte, 1987). Additionally, these techniques are best suited in turbid waters as in these conditions, only reasonable SAV detection is achieved from object‐based image analysis and optic sensors are typically blind at only 1‐ or 2‐m depth (de Grandpré et al, 2022; Krause et al, 2021; Rowan & Kalacska, 2021). Sonar technology is also becoming more accessible including the use of unmanned boats (e.g., Goulon et al, 2021), with improved recreational‐grade sonars and automatic cloud‐based postprocessing (Buscombe, 2017; Helminen et al, 2019; Howell & Richardson, 2019) that will allow for greater aerial coverage, faster sampling, and reduced cost.…”

The reproducibility of remotely piloted aircraft systems to monitor seasonal variation in submerged seagrass and estuarine habitats

“…Remote sensing applications for seagrass monitoring are generally used to measure seagrass extent (Lyons et al 2013), whereas wading/snorkel/SCUBA approaches reveal smaller scale and higher resolution details such as shifts in percent cover of seagrass, shoot density, and species composition (i.e., presence of macroalgae; Fourqurean et al 2001;Short et al 2006). More recently, remotely piloted aircraft systems (RPAS; i.e., drones) have been applied to monitor seasonal variation in seagrass extent and structure (Chand and Bollard 2022;Krause et al 2021) due to their ability to collect high resolution images frequently and at a relatively low cost and their potential to automate part of the work (Colefax et al 2018;Joyce et al 2018). By reducing monitoring costs, RPAS present a promising approach for seagrass monitoring because seagrass monitoring is widespread and conducted by groups that are resource and time limited, including academics, non-profit, and government entities seeking to optimize monitoring resources.…”

“…Additionally, seagrass blades may fold over at low tide or when there is a fast current, increasing the likelihood of overestimating seagrass density. While recent studies have provided roadmaps of ideal environmental conditions for RPAS surveys of seagrass (e.g., Joyce et al 2018;Nahirnick et al 2019b;Tait et al 2019;Yang et al 2020), studies evaluating the efficacy of surveys have generally focused on one-time occurrences in tropical regions (e.g., Ellis et al 2020) or portions of a meadow (Barrell and Grant 2015;Duffy et al 2018;Ellis et al 2020;Konar and Iken 2018;Krause et al 2021). In temperate regions, high environmental variability, including rapid shifts in cloud cover, wind, and chemistry of estuarine waters (e.g., tannins), challenges RPAS surveys (Nahirnick et al 2019a(Nahirnick et al , 2019b.…”