Examining the Links between Multi-Frequency Multibeam Backscatter Data and Sediment Grain Size

Publication history: Accepted - 13 April 2021Acoustic methods are routinely used to provide broad scale information on the geographical distribution of benthic marine habitats and sedimentary environments. Although single-frequency multibeam echosounder surveys have dominated seabed characterisation for decades, multifrequency approaches are now gaining favour in order to capture different frequency responses from the same seabed type. The aim of this study is to develop a robust modelling framework for testing the potential application and value of multifrequency (30, 95, and 300 kHz) multibeam backscatter responses to characterize sediments’ grain size in an area with strong geomorphological gradients and benthic ecological variability. We fit a generalized linear model on a multibeam backscatter and its derivatives to examine the explanatory power of single-frequency and multifrequency models with respect to the mean sediment grain size obtained from the grab samples. A strong and statistically significant (p < 0.05) correlation between the mean backscatter and the absolute values of the mean sediment grain size for the data was noted. The root mean squared error (RMSE) values identified the 30 kHz model as the best performing model responsible for explaining the most variation (84.3%) of the mean grain size at a statistically significant output (p < 0.05) with an adjusted r2 = 0.82. Overall, the single low-frequency sources showed a marginal gain on the multifrequency model, with the 30 kHz model driving the significance of this multifrequency model, and the inclusion of the higher frequencies diminished the level of agreement. We recommend further detailed and sufficient ground-truth data to better predict sediment properties and to discriminate benthic habitats to enhance the reliability of multifrequency backscatter data for the monitoring and management of marine protected areas.This research was funded by the Marine Institute under the Marine Research Programme by the Irish Government Cruise CE19007 Backscatter and Biodiversity of Shelf Sea Habitats (BaBioSSH) survey. Staffing was supported through the Marine Protected Area Monitoring and Management (MarPAMM) project, which is supported by the European Union’s INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPM) with matching funding from the Government of Ireland, the Northern Ireland Executive, and the Scottish Government, as well as the PhD studentship through a Vice Chancellor Research Scholarship of Ulster University (U.K.)

A review of new and existing non-extractive techniques for monitoring marine protected areas

Publication history: Accepted - 23 June 2023; Published - 19 July 2023.Ocean biodiversity loss is being driven by several anthropogenic threats and significant efforts are required to halt losses and promote healthy marine ecosystems. The establishment of a network of Marine Protected Areas (MPAs) can help restrict damaging activities and have been recognised as a potential solution to aid marine conservation. When managed correctly they can deliver both ecological and socio-economic benefits. In recent times, MPA designations have increased rapidly while many countries have set future MPA targets for the decades ahead. An integral element of MPA management is adequate monitoring that collects data to assess if conservation objectives are being achieved. Data acquired by monitoring can vary widely as can the techniques employed to collect such data. Ideally, non-destructive and non-invasive methods are preferred to prevent damage to habitats and species, though this may rule out a number of traditional extractive sampling approaches such as dredges and trawls. Moreover, advances in ocean observation technologies enable the collection of large amounts of data at high resolutions, while automated data processing is beginning to make analyses more logistically feasible and less time-consuming. Therefore, developments to existing marine monitoring techniques and new emerging technologies have led to a diverse array of options when choosing to implement an MPA monitoring programme. Here, we present a review of new and existing non-extractive techniques which can be applied to MPA monitoring. We summarise their capabilities, applications, advantages, limitations and possible future developments. The review is intended to aid MPA managers and researchers in determining the suitability of available monitoring techniques based on data requirements and site conditions.This research was funded through the Marine Protected Area Monitoring and Management (MarPAMM) project, which is supported by the European Union’s INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB) with matching funding from the Government of Ireland, the Northern Ireland Executive, and the Scottish Government. This research was also carried out with the support of the Marine Institute under the Marine Research Programme with the support of the Irish Government

Constraints on the origin and evolution of Iani Chaos, Mars

[1] The origin mechanisms and geologic evolution of chaotic terrain on Mars are poorly constrained. Iani Chaos, located at the head Ares Vallis, is among the most geomorphologically complex of the chaotic terrains. Its morphology is defined by (1) multiple, 1 to 2 km deep basins, (2) flat‐topped, fractured plateaus that are remnants of highland terrain, (3) knobby, fractured remnants of highland terrain, (4) plateaus with a knobby surface morphology, (5) interchaos grooved terrain, (6) interior layered deposits (ILDs), and (7) mantling material. Topography, the observed geomorphology, and measured fracture patterns suggest that the interchaos basins formed as a result of subsurface volume loss and collapse of the crust, likely owing to effusion of groundwater to the surface. Regional patterns in fracture orientation indicate that the basins developed along linear zones of preexisting weakness in the highland crust. Multiple overlapping basins and fracture systems point to multiple stages of collapse at Iani Chaos. Furthermore, the total estimated volume loss from the basins (104 km3) is insufficient to explain erosion of 104–105 km3 of material from Ares Vallis by a single flood. Comparisons with the chronology of Ares Vallis indicate multiple water effusion events from Iani Chaos that span the Hesperian, with termination of activity in the early Amazonian. Recharge of groundwater through preexisting fracture systems may explain this long‐lived, but likely episodic, fluvial activity. Late‐stage, early to middle Amazonian aqueous processes may have deposited the ILDs. However, the topography data indicate that the ILDs did not form within lacustrine environments

Genetic analysis of the interaction between Allium species and arbuscular mycorrhizal fungi

The response of Alliumcepa, A. roylei, A. fistulosum, and the hybrid A. fistulosum × A. roylei to the arbuscular mycorrhizal fungus (AMF) Glomus intraradices was studied. The genetic basis for response to AMF was analyzed in a tri-hybrid A. cepa × (A. roylei × A. fistulosum) population. Plant response to mycorrhizal symbiosis was expressed as relative mycorrhizal responsiveness (R′) and absolute responsiveness (R). In addition, the average performance (AP) of genotypes under mycorrhizal and non-mycorrhizal conditions was determined. Experiments were executed in 2 years, and comprised clonally propagated plants of each genotype grown in sterile soil, inoculated with G. intraradices or non-inoculated. Results were significantly correlated between both years. Biomass of non-mycorrhizal and mycorrhizal plants was significantly positively correlated. R′ was negatively correlated with biomass of non-mycorrhizal plants and hence unsuitable as a breeding criterion. R and AP were positively correlated with biomass of mycorrhizal and non-mycorrhizal plants. QTLs contributing to mycorrhizal response were located on a linkage map of the A. roylei × A. fistulosum parental genotype. Two QTLs from A. roylei were detected on chromosomes 2 and 3 for R, AP, and biomass of mycorrhizal plants. A QTL from A. fistulosum was detected on linkage group 9 for AP (but not R), biomass of mycorrhizal and non-mycorrhizal plants, and the number of stem-borne roots. Co-segregating QTLs for plant biomass, R and AP indicate that selection for plant biomass also selects for enhanced R and AP. Moreover, our findings suggest that modern onion breeding did not select against the response to AMF, as was suggested before for other cultivated species. Positive correlation between high number of roots, biomass and large response to AMF in close relatives of onion opens prospects to combine these traits for the development of more robust onion cultivars

Mapping benthic habitat using acoustic remote sensing

Backscatter imagery from multibeam echosounders (MBES) is increasingly used for benthic habitat mapping. This research explores MBES backscatter classification using QTC-Multiview on data from Stanton Banks (UK) and Cashes Ledge (USA). Image-processing algorithms are used to extract values from samples of backscatter data, which are reduced by principal components analysis and are objectively clustered. This process is initially evaluated using 2005 data from Stanton Banks and compared with ground-truth data to determine their biological validity. Low-levels of agreement are observed between acoustic class and ground- truth data «35%); video is determined to be the most spatially appropriate method for comparison. Subsequently, the area was resurveyed in 2006 using the same MBES with different operational parameters, acquiring low- and high-density data coverage. Percentage agreement between classifications was 78%, determined to be due to operational parameters as opposed to environmental change. Agreement with ground truth data improved from 71 % to 77% with increased data density. In 2008, a 2 km2 area was resurveyed at two different orientations and vessel speeds within the same 24 hr period. Classification revealed 53% similarity at 4 rns-1 and 49% at 2 rns-1 from opposing orientations. The same orientations surveyed at different speeds were between 68% (k=0.583) and 53% (k=0.384) similar. These results suggest that both orientation and speed are significant considerations in image-based classification. Finally, the significance of water-column biomass in backscatter classification was examined at Cashes Ledge using MBES data from kelp beds. Two approaches were examined for detecting the presence of macrophytes; image-based and manual picking. Comparison with video data revealed comparable success, with both methods most successful at predicting Laminaria sp. (77.3%-82.6% correct) in shallow water «30m). This research demonstrates the significance of MBES backscatter and image-based classification as potential tools for the emergent discipline of benthic habitat mapping.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An evaluation of supervised and unsupervised classification techniques for marine benthic habitat mapping using multibeam echosounder data

Marine habitat mapping provides information on seabed substrata and faunal community structure to users including research scientists, conservation organizations, and policy makers. Full-coverage acoustic data are frequently used for habitat mapping in combination with video ground-truth data in either a supervised or unsupervised classification. In this investigation, video ground-truth data with a camera footprint of 1 m2 were classified to level 4 of the European Nature Information System habitat classification scheme. Acoustic data with a horizontal resolution of 1 m2 were collected over an area of 130 km2 using a multibeam echosounder, and processed to provide bathymetry and backscatter data. Bathymetric derivatives including eastness, northness, slope, topographic roughness index, vector rugosity measure, and two measures of curvature were created. A feature selection process based on Kruskal–Wallis and post hoc pairwise testing was used to select environmental variables able to discriminate ground-truth classes. Subsequently, three datasets were formed: backscatter alone (BS), backscatter combined with bathymetry and derivatives (BSDER), and bathymetry and derivatives alone (DER). Two classifications were performed on each of the datasets to produce habitat maps: maximum likelihood supervised classification (MLC) and ISO Cluster unsupervised classification. Accuracy of the supervised habitat maps was assessed using total agreement, quantity disagreement, and allocation disagreement. Agreement in the unsupervised maps was assessed using the Cramer's V coefficient. Choice of input data produced large differences in the accuracy of the supervised maps, but did not have the same effect on the unsupervised maps. Accuracies were 46, 56, and 49% when calculated using the sample and 52, 65, and 51% when using an unbiased estimate of the population for the BS, BSDER, and DER maps, respectively. Cramer's V was 0.371, 0.417, and 0.366 for the BS, BSDER, and DER maps, respectively