Marine renewable developments in Scottish waters: review of benthic ecological surveying

Almost universally available as single beam data and widely available as multibeam, swath data.

Useful for showing pinnacles, shoals, banks, troughs, canyons, kettle holes etc.

Vast majority of water depth features and conditions in Scottish waters are stable over time so data has long utilisation window.

May help demark extent of mineralised biogenic reefs on the seabed, if high resolution data is collected.

Main issues are extent of coverage and resolution of data. Care needs to be taken to ensure that the right benchmarks are used such as LAT and global projections.

Need to take account of long-term sea-level rise.

Usually, no ecological information arising.

Provides indication of the density and structure of seabed materials enabling better differentiation of rocks and sediment types.

May help demark extent and depth of mineralised biogenic reefs on the seabed.

Requires skilled interpretation.

Potential for wider ecological interactions from sound emissions with sound sensitive species such as Cetaceans Usually, no ecological information arising.

Verifies remote sensing methods.

Enables further analysis to take place (see Section 6.3 and Table 6.2).

[Plus - see also below for biological and chemical sampling].

Small spatial extent with all vertical samplers, low accuracy and precision with drag samplers.

Grab and box cores often fail where stones are mixed into sediments.

[Plus - see also below for biological and chemical sampling].

Provides generally good resolution data over a wide area, enabling local variation to be better understood.

Generally greater detail than most geophysical data.

Data can be easily shared digitally.

Through water visibility in seabed use may be variable.

Can be time consuming to review.

Intertidal walkover surveys are one of the easiest surveys to undertake, they provide a wide mix of useful data and insights as soon as it is undertaken and can adapt to finding immediately.

Diver surveys in shallow waters can provide quick, insightful and adaptable survey capacity, especially where conditions are too shallow or complex for vessel navigation, where there are thick kelp beds, rocky seabed areas and where site or route finding may be enhanced by an adaptable survey strategy.

Intertidal walkovers may be more difficult to undertake along cliff-backed shorelines and around remote islands. In such locations close inspection from a small boat or aerial drone surveillance may be options.

Diver based surveys, are more complex in terms of mobilisation and back-up safety resources needed.

Time-effective to gain good visual insights over a relatively wide area. When deployed on ROV platform with direct feedback to surface then dynamic search strategies can be employed for seeking out and characterising seabed features, habitats and even particular species or assemblages.

Can be combined with manually triggered or timelapse high resolution still photography and or some sample recovered using ROV manipulator arms.

With enough power and data storage there is no limit to duration and coverage.

If camera is flown or held above the seabed then low impact.

Under turbid conditions or with high plankton concentrations visibility can be impaired and reflected light from suspended particulates can be an issue in deeper, darker waters. The resolution of video images is often less than still images. High data storage capacity required.

Sledge or seabed rover-based systems will damage sensitive habitats.

When set-up well and with high (>10 megapixels (MP)) and ultra-high resolution (>20 MP); still photos can give very good images for mobile and epifaunal ID. Some signs of infauna (siphons, shell edges, burrows, faecal deposits etc.) can also be seen.

Vertical shots can be useful for counting and coverage area estimation where lasers are used.

Oblique landscapes and seascapes can be very effective for understanding context.

A non-intrusive method of sample generation.

Still images are more memory efficient than video.

May be used for stakeholder engagement (e.g., public, fishers, NGOs, regulators).

Still camera set-ups often do not have surface feedback, so shot set-up can be more random. Combining stills with a video feed is likely the best combination.

As above for physical habitat characterisation – plus:

Enables subsequent taxonomic identification, morphological measurement, fecundity assessment, food/stomach item analysis, biochemical, chemical and DNA analysis.

Reduces some uncertainties linked to remote sampling methods and can verify assumptions and judgements made.

As above for physical habitat characterisation – plus:

Careful treatment needed to preserve specimens for later analysis.

Care needed to avoid damaging specimens.

Sieving techniques select a certain size restriction of the fauna for the analysis.

Tends to focus on infauna using grabs and does not deal with mobile, widely spaced or rarely occurring species, where trawls may be more appropriate.

Number of samples obtained and area sampled generally lower than for imagery methods.

As above for habitat characterisation and biology – plus:

Fills gaps linked to remote sampling methods and can verify assumptions and judgements made regarding why certain species may be present/absent such as organic material status, oxygen levels, any toxicant levels etc.

As above for habitat characterisation and biology – plus:

Sample gathering needs to adopt strict QC standards from the outset specifically relevant to any subsequent analysis being planned to avoid contamination.

The utilisation of either direct observations, remotely gathered images and/or other supporting data by experienced subject experts provides an insightful approach to habitat characterisation. The ability to contextualise any determinations is particularly useful. It is also likely that a more nuanced insight into the conditions and any pressures or trends can be considered and provided as well.

Getting specialists for direct observations to all locations can be challenging, particularly in deep and/or turbid waters, areas with strong currents, large waves, beaches with cliff backdrops and steep shorelines and across multiple locations in archipelagic geography.

The availability of suitably competent and experienced surveyors may be limited. Outputs can be subjective and lack a quantitative element to provide easy scaling or performance/suitability metrics.

A relatively simple data analysis tool which gives insights into seabed morphology and dynamics, as well as geological structure and can inform physical habitat extent estimations for rocky and possibly biogenic reefs, dynamic sediment features etc.

Needs high resolution bathymetry data to be most useful.

Accepted standardised, quantitative and robust methodologies for sediment characterisation.

Limited in application within tidal MRE industry. Cannot be conducted on hard seabed features.

Accepted, standardised, quantitative and robust methodologies for identifying macrobenthic assemblages. Outputs include cluster analysis, diversity, richness and evenness which can indicate habitat condition.

Species identification (ID) and sample work up efficiency needs to be consistent and at a high level of accuracy. High level of taxonomy skills required.

Accepted, standardised and robust methodologies for conducting seabed imagery analysis.

Camera and lighting technology is constantly improving.

Imaging reference catalogues (such as BIIGLE) are open source and widely available/adaptable to the requirements of the imagery.

Large datasets are time consuming to analyse.

Image quality affected by environmental conditions on site can lead to difficulties when analysing and determining species/habitats.

Analyst bias when recording taxonomic and habitat information.

Cryptic and mobile/transient/ infaunal species are typically under-recorded.

Accepted standardised and relatively robust methodologies for identifying concentrations of chemical parameters.

Quality control for environmental chemistry is challenging and the handling of samples once gathered can vary between laboratories leading to inconsistent results.

Spatial variability can be quite high at typical sampling scales (e.g., grab based)

Real-time profiling, measuring and quantification of biomass on subsea structure.

Useful for helping to understand the distribution of species across complex hard structures.

Less dependent upon good visibility for gathering data.

Due to dynamic model building, less dependent upon platform stability, increasing weather window options.

Requires training and experience. High level of skilled personnel required both at sea and on land.

Fine scale detailing may be lost compared to high resolution photography.

Onsite time needed to gather data longer than other techniques, may increase vessel costs.

False colour output from sensor.

Various modelling software packages available.

Very useful for helping to understand the distribution of species across complex hard structures.

Possible application for establishing detailed understanding of seabed coverage mosaics over a larger survey area (e.g., 10 m²).

Data intensive with long processing times.

Typically conducted post survey.

Requires training and experience. Moderate level of skilled personnel required.

Needs good water column visibility.

Works best where there are strong visual indicators of community composition on/at the surface.

Onsite time needed to gather data longer than other techniques, may increase vessel costs.

Provides evidence on occurrence of cryptic, rare, and transient/mobile species and benthic species that are difficult to detect and sample using traditional methods.

Non-disruptive method.

Adaptive to sediment and water column assemblages.

Applicable for validating whether previously unrecorded invasive/introduced species have migrated to or colonised a location.

As the catalogue of DNA profiled species grows it could provide a relatively rapid check over time of biodiversity within an overall area or from a particular habitat type.

Dedicated laboratories are increasing, and industry standards have recently been produced.

Detects occurrence only. Cannot be used to quantify abundance reliably.

Skilled and experienced personnel required to interpret results.

Requires training and laboratory experience.

Attribution of a positive result to a particular location varies depending upon how/where sample is taken (water vs sediment; duration of DNA in environment).

Provide evidence on transient/mobile species that may be under-sampled using traditional methods.

Non-intrusive method.

Open-source statistical software to conduct maximum entropy (Maxent) modelling.

Requires some training. Low skill level required.

Sample new or under-represented cohort of demersal/benthic species in terms of mobile predators and scavengers.

Timelapse may help give insight into surface seabed processes such as burrowing, sediment turnover, rates of specimen movement.

Could be applied to monitoring of deposited biofouling impacts.

No standardisation.

Not suitable in strong currents.

Bias to scavenger and opportunistic species.

No standardised analytical methodology.

Area over which observed species are recorded is unclear.

Does not sample non-predatory mobile fauna.

Requires a return to the site after a period of time to recover the system and data. This can lead to extra cost and challenging logistics.

Recovery of untethered seabed equipment can be unreliable.

Broad classification of the key habitats based on the physical nature of the seabed.

Can be displayed visually on mapping software.

Widely used and standardised classification schemes are used which are interchangeable (MHC/EUNIS).

Does not factor in the biology.

Mixed and coarse sediments can be difficult to differentiate.

Relies on the quality of the imagery and the analysts’ experience.

Fine scale classification of the key habitats based on both the physical and biological nature of the seabed.

Can be displayed visually on mapping software.

Widely used and standardised classification schemes are used which are interchangeable (MHC/EUNIS).

Relies on the quality of the imagery and the analysts’ taxonomic experience.

Assumption that every sample will fit into a specific classification.

Subjective and outputs can differ between analysts.

Moderate skill and training are required.

Identification of all features (species and habitats) of conservation interest, e.g., Annex I, PMF and OSPAR features.

Some well-established and standardised guidance and methods for categorising/ quantifying the distribution and quality of features.

Utilises mapping software that ranges from freely available to expensive.

Subjective and outputs can differ between analysts.

Moderate skill and training are required.

Relies on in-house or nationally established methods for analysing features that may draw upon available applicable guidance.

Relies on the availability and quality of the data to provide confidence scores.

The drawing of digital maps can visually display the extent and heterogeneity of habitats and biotopes throughout an area.

Digital maps are drawn in mapping software that ranges from freely available to expensive.

Subjective and outputs can differ between analysts.

Moderate skill and training are required.

Relies on the availability and quality of the data to provide confidence scores.

Can be a time-consuming process for intensive sampling regimes.

A faster alternative to digitally drawn maps.

More suitable over expansive areas.

Requires enough data to run and validate the model.

Requires enough of each type of BSH observed to provide statistically significant results.

Lack of standardisation. Many methods are available and accepted.

Less suitable for predicting biological information (biotopes).

Moderate skill and training are required.

Many applications for sourcing and organising existing and new data, searching data, calculating key parameters, presentation of results and generating useful outputs.

Feedback of good data back into AI-based systems to help with decision making (e.g., route and site finding; carbon accounting; biodiversity net gain assessments).

Concerns that quality control systems for AI are not yet well developed.

In most cases major investment needed to set-up a reliable AI system in terms of coding, testing, and quality assurance.

Danger of losing key skills such as taxonomic identification if AI used indiscriminately.