Nearshore Benthic Mapping in the Great Lakes: A Multi-Agency Data Integration Approach in Southwest Lake Michigan

The Laurentian Great Lakes comprise the largest assemblage of inland waterbodies in North America, with vast geographic, environmentally complex nearshore benthic substrate and associated habitat. The Great Lakes Water Quality Agreement, originally signed in 1972, aims to help restore and protect the basin, and ecosystem monitoring is a primary objective to support adaptive management, environmental policy, and decision making. Yet, monitoring ecosystem trends remains challenging, potentially hindering progress in lake management and restoration. Consistent, high-resolution maps of nearshore substrate and associated habitat are fundamental to support management needs, and the nexus of high-quality remotely sensed data with improvements to analytical methods are increasing opportunities for large-scale nearshore benthic mapping at project-relevant spatial resolutions. This study attempts to advance the integration of high-fidelity data (airborne imagery and lidar, satellite imagery, in situ observations, etc.) and machine learning to identify and classify nearshore benthic substrate and associated habitat using a case study in southwest Lake Michigan along Illinois Beach State Park, Illinois, USA. Data inputs and analytical methods were evaluated to better understand their implications with respect to the Coastal and Marine Ecological Classification Standard (CMECS) classification hierarchy, resulting in an approach that could be easily applied to other shallow coastal environments. Classification of substrate and biotic components were iteratively classified in two Tiers in which classes with increasing specificity were identified using different combinations of airborne and satellite data inputs. Classification accuracy assessments revealed that for the Tier 1 substrate component (3 classes), average overall accuracy was 90.10 ± 0.60% for 24 airborne data combinations and 89.77 ± 1.02% for 12 satellite data combinations, whereas the Tier 1 biotic component (2 classes) average overall accuracy was 93.58 ± 0.91% for 24 airborne data combinations and 92.67 ± 0.71% for 11 satellite data combinations. The Tier 2 result for the substrate component (2 classes) was 93.28% for 2 airborne data combinations and 95.25% for the biotic component (2 classes). The study builds on foundational efforts to move towards a more integrated data approach, whereby data strengths and limitations for mapping nearshore benthic substrate and associated habitat, expressed through classification accuracy, were evaluated within the context of the CMECS classification hierarchy, and has direct applicability to critical monitoring needs in the Great Lakes.

Distribution and density of Lutraria rhynchaena Jonas, 1844 relate to sediment while reproduction shows multiple peaks per year in Cat Ba-Ha Long Bay, Vietnam

Lutraria rhynchaena Jonas, 1844 is of great commercial interest, but its reserves have dramatically declined over recent decades. Therefore, there is an urgent need of scientific basis to propose effective fishery management measures and improve artificial aquaculture of the clam. In this study, we investigated the distribution and density of L. rhynchaena, sediment characteristics, and established the clam’s reproductive cycle through monthly observations from August 2017 to July 2018. The study results showed that distribution and density of clams are related to sediment types, and the sediment type of medium sand is likely the best benthic substrate for the clams. The spawning of clams occurred throughout the year with three spawning peaks in January, April and September. For the sustainable management of the clam resource in Cat Ba-Ha Long Bay, the fishery authorities can issue a ban on harvest of the clam in spawning peak months in January, April and September.

Manatee habitat characterization using side-scan sonar

Identifying benthic substrates is important to researchers studying aquatic organisms in fresh and salt water systems. Benthic substrates are often not visible from the surface making it necessary to find another method to gather these data. Previous research has demonstrated that low cost side-scan sonar is a reliable way to identify hard substrates, such as rock and gravel, in a small, freshwater stream. In this study, the reliability of the side-scan sonar to accurately identify softer substrates such as grass and mud was tested in a large, brackish lagoon system. A total area of 11.55 km2 was surveyed with the sonar. Videos and pictures were taken at various points to groundtruth the sonar images and provide a measure of accuracy. Five substrate types were identified: dense seagrass, sparse seagrass, mangrove soil, mangrove soil with rock, and silt. Unidentifiable substrates were classified as unknown. A manually zoned benthic substrate map was created from the sonar recordings. Dense seagrass was most accurately identified. Sparse seagrass was the least accurately identified. A bathymetric map was also created from the sonar recordings.

Building a set of criteria for selection of natural clam beds (Lutraria rhynchaena, Jonas 1844) as broodstock source for seed production and gene conservation in Cat Ba - Ha Long bay

Building on a set of criteria used as a scientific basis for conservation zoning of natural marine resources is essential. In this study, we propose the set of criteria to select the suitable natural clam beds of Lutraria rhynchaena for protection priority from 16 sites in Cat Ba - Ha Long bay. Research results have built a set of 13 different criteria, including area, density, benthic substrate, food organisms, turbidity, water flow, water depth, predators, salinity, benthic organisms, pollution, area location and zoning conflicts. The criteria are divided into 5 groups, in which the area and density have the highest coefficent of 5, followed by the zoning conflict with the coefficient of 4, the pollution with the coefficient of 3, the efficient of benthic substrate and water flow is 2, the remaining criteria have a same coefficient of 1. The highest points are evaluated at Tung Sau bed (station 12) with a score of 254 points, followed by Van Boi beach (station 7) with a score of 235 points, the bed is in Trinh Nu Cave (Station 13) with a score of 229 points, which are proposed to be prioritized sites for conservation.

SPATIAL COMPOSITION OF BENTHIC SUBSTRATE AROUND BONTOSUA ISLAND

Coral reefs and seagrass are natural fortress for small islands from waves and ocean currents. The spatial distribution of these benthic substrate should be known and monitored regularly. This study aims were to map existing benthic substrates on the reef flat of Bontosua Island, determine the spatial composition and develop index ratio. Benthic substrates were surveyed using geotagging technique. Their distribution were estimate using Quickbird image that was rectified and classified using ISOcluster method and validate by 240 selected photos. The seagrass were surveyed at 8 stasions to record percent cover and species composition. Depth profiles were track along 10 reef flat line segment. Bontosua Island has an elongated shape from South to Northwest. This study had produced a benthic substrate distribution map with thematic accuracy 76%. Total area able to map were 54.2 hectares. About 43% benthic substrates at Bontosua were mixture of coral rubble, seagrass and algae, 20% was mixture of rubble and algae, 16% dominated by seagrass, 13% mixture of sand and seagrass and 8% substrate were dominated by live coral. There were eight seagrass species found with average percent cover 37.2 ± 12.5 percent. The spatial ratio of live coral, seagrass and mixed substrate for West side reef flat was 2:20:49 and 1:9:9 for East side. This indicate that the distribution of benthic substrates on the West side is much wider than on the East side. This approach potentially applied to study the relationship between benthic substrate composition and the deformation of small islands.

Touch sensation by pectoral fins of the catfish Pimelodus pictus

Mechanosensation is fundamental to many tetrapod limb functions, yet it remains largely uninvestigated in the paired fins of fishes, limb homologues. Here we examine whether membranous fins may function as passive structures for touch sensation. We investigate the pectoral fins of the pictus catfish ( Pimelodus pictus ), a species that lives in close association with the benthic substrate and whose fins are positioned near its ventral margin. Kinematic analysis shows that the pectoral fins are held partially protracted during routine forward swimming and do not appear to generate propulsive force. Immunohistochemistry reveals that the fins are highly innervated, and we observe putative mechanoreceptors at nerve fibre endings. To test for the ability to sense mechanical perturbations, activity of fin ray nerve fibres was recorded in response to touch and bend stimulation. Both pressure and light surface brushing generated afferent nerve activity. Fin ray nerves also respond to bending of the rays. These data demonstrate for the first time that membranous fins can function as passive mechanosensors. We suggest that touch-sensitive fins may be widespread in fishes that maintain a close association with the bottom substrate.