Scientific trawling: reading an abundance index

A survey catch is a sample of the environment

Demersal fish live close to the seabed, where direct observation over large areas is difficult. A scientific trawl collects information about the species caught, their sizes and their distribution. It samples a limited area and does not retain every individual encountered. What comes aboard must therefore be interpreted in relation to the gear, location, depth and timing of the haul, rather than treated as a complete count of the local population.

Bertrand and colleagues’ 2002 publication and Spedicato and colleagues’ 2019 synthesis explain the MEDITS framework for Mediterranean surveys. They describe methods for making observations comparable and documenting changes in the survey process. They are methodological references, not a current assessment of stocks or a statement about their status in 2026. French participation makes the framework relevant to French environmental work, but does not make a pattern observed elsewhere a demonstrated trend along the French coast.

Put catches in relation to the area sampled

Two hauls can produce different catches simply because they swept different areas. Effective towing distance and the horizontal opening of the trawl contribute to the estimate of swept area. MEDITS uses this information to standardise catches, for example as numbers or kilograms per square kilometre. Numbers describe an abundance index, while weight describes a biomass index. Keeping these quantities separate helps readers understand what a reported increase actually represents.

Standardisation does not turn an index into an exhaustive census. Catchability depends on species, body size, behaviour, habitat and gear characteristics. Fish may avoid the trawl or escape through it. A change in catch can therefore reflect population change, availability to the gear or sampling conditions. These possibilities remain relevant even when the index has been calculated correctly, particularly if an apparent shift is based on a single survey rather than a sustained series.

Preserve the depth and seasonal comparison

The published MEDITS framework allocates stations within depth strata over trawlable grounds between 10 and 800 metres. This helps prevent changes in sampling coverage from masquerading as population trends. A combined index needs to account for the area represented by each stratum. Simply pooling catches would give disproportionate influence to areas sampled more frequently, rather than representing the defined survey area according to its sampling design.

Timing also matters. Reproduction, recruitment, movements and environmental conditions can change what the trawl encounters during a year. The 2019 synthesis describes a usual late-spring to summer survey window, alongside departures in some areas and years. A time series therefore needs the actual station dates, not just an annual label. A change in scheduling should be examined before a break in the index is attributed to fishing pressure or an environmental disturbance.

Read size distributions alongside numbers and weight

The same biomass index could come from a small number of large fish or a larger number of smaller animals. Size distributions add information that a total cannot provide. They can help examine the arrival of young fish, population composition and the representation of larger classes. However, an increase in small fish is not automatically a recruitment signal: identification, measurement thresholds and gear selectivity also need to be considered.

The standard trawl described in the references has a 20-millimetre stretched codend mesh, allowing juveniles of many species to be collected. That does not mean every developmental stage is sampled equally. Individuals escaping the gear remain absent from the measurements. Different animal groups may also use different length conventions, which must remain attached to the records. Combining measurements without checking those definitions can introduce a change that originates in data handling rather than in the fish population.

Record technical changes and environmental context

A replacement vessel, modified gear or a different estimate of trawl opening can alter the relationship between catches and population abundance. Spedicato and colleagues describe intercalibration and quality-control work, as well as situations in which survey conditions changed. Statistical standardisation may address some differences. It cannot automatically reconstruct an observation that was never made or represent a habitat that the gear could not sample. Those limitations should remain visible in any resulting interpretation.

Environmental observations can help explain the pattern being investigated. The 2019 synthesis highlights the value of environmental information, including surface and bottom temperatures, for understanding populations. Depending on the local question, additional salinity observations may clarify the hydrological setting. Such information supports hypotheses and comparison. An association with an abundance index does not independently establish mortality, migration or an altered growth rate, and should not be presented as proof of a particular mechanism.

State where the trend can reasonably apply

Before using an index in a conservation decision, review the species, depth coverage, season, gear, units and missing years. Untrawlable grounds and poorly retained animals set a clear boundary to inference. Complementary observations may cover other habitats or behaviours, provided their methods remain distinguishable. A zero catch means no individuals were caught in that sampling event; it does not demonstrate absence throughout the wider area or across all suitable habitats.

The value of a MEDITS series depends on continuity of method as well as the amount of data collected. Standardised catches, body sizes and context provide a stronger basis for interpretation than an isolated total, while retaining the limits of the sampling process. Our consultancy and advisory support can help aquatic environmental teams assess comparability, identify missing information and communicate conclusions that match the evidence, without presenting an index as a complete count of the sea.