Predator-prey overlap in three dimensions: cod benefit from capelin coming near the seafloor

Spatial overlap between predator and prey is a prerequisite for predation, but the degree of overlap is not necessarily proportional to prey consumption. This is because many of the behavioural processes that precede ingestion are non-linear and depend on local prey densities. In aquatic environments, predators and prey distribute not only across a surface, but also vertically in the water column, adding another dimension to the interaction. Integrating and simplifying behavioural processes across space and time can lead to systematic biases in our inference about interaction strength. To recognise situations when this may occur, we must first understand processes underlying variation in prey consumption by individuals. Here we analysed the diet of a major predator in the Barents Sea, the Atlantic cod (Gadus morhua), aiming to understand drivers of variation in cod’s feeding on its main prey capelin (Mallotus villosus). Cod and capelin only partly share habitats, as cod mainly reside near the seafloor and capelin inhabit the free water masses. We used data on stomach contents from ~2000 cod individuals and their surrounding environment collected over 12 years, testing hypotheses on biological and physical drivers of variation in cod’s consumption of capelin, using Generalized Additive Models. Specifically, effects of capelin abundance, capelin depth distribution, bottom depth, and cod abundance on capelin consumption were evaluated at a resolution scale of 2 km. We found no indication of food competition as cod abundance had no effect on capelin consumption. Capelin abundance had small effects on consumption, while capelin depth distribution was important. Cod fed more intensively on capelin when capelin came close to the seafloor, especially at shallow banks and bank edges. Spatial overlap as an indicator for interaction strength needs to be evaluated in three dimensions instead of the conventional two when species are partly separated in the water column.

Methods
The data was collected by Norwegian vessels participating in the Norwegian-Russian Barents Sea Ecosystem Survey in 2004-2015. The survey covers the entire ice-free Barents Sea in August-October each year and follows a regular grid design with sampling stations spaced approximately 65 km apart, collecting data on environmental conditions, species composition and abundance for several trophic levels. We selected stations from areas where cod and capelin overlap spatially (Fall, et al. 2018), i.e., stations were both species were observed. At each station, a CTD (Conductivity-Temperature-Depth) probe is lowered to measure depth-specific temperature, a Campelen 1800 demersal shrimp trawl is used for near-bottom sampling over a distance of 1.4 km (0.75 nautical miles, nmi), and a pelagic trawl (‘Harstad trawl’, Godø, et al. 1993) samples the upper approximately 60 m of the water column. Continuously during the survey, Simrad EK60 echo sounders with 18, 38, 120 and 200 kHz split beam transducers (on some vessels Simrad EK500 during the first years) record fish echoes along the survey tracks. The acoustic backscatter at 38 kHz is manually allocated to target groups based on species-specific acoustic signatures and the catch composition in pelagic and bottom trawls, then stored at a horizontal resolution of 1.9 km (1 nmi) and a vertical resolution of 10 m. One individual cod from each 5-cm length group present in the bottom trawl catch is randomly chosen for sampling of age, sex, mass, length, maturity stage, and stomach contents. The stomachs are frozen on board, and the contents identified to the lowest possible taxonomic level in a laboratory on land. Prey items are assigned a qualitative digestion stage from 1-5, where 1 corresponds to undigested prey and 5 to prey that is so heavily digested that it is unidentifiable by visual inspection. Prey categories are weighed (wet mass) and, if possible, counted and length measured. The dataset contains stomach data from cod in the size range 30-70 cm. Empty stomachs (9.2%) were excluded from the analyses, leaving 1944 stomachs from 455 stations across the 12 years.

The following covariates are included in the dataset: capelin density, capelin weighted median depth, cod density, cod length (for each individual within the station), and bottom depth (measured by the vessel-mounted echosounder at the start of trawling). The local capelin density (in units of Nautical Area Scattering Coefficient; m2/nmi2, integrated throughout the water column) was taken from the acoustic segment of 1.9 km length that had the highest temporal overlap with each trawl haul. This included acoustic recordings from before, during and after trawling. For a more intuitive representation of prey density, we converted the acoustic values to number of individuals/km2 based on the length distribution in the closest pelagic trawl hauls taken during the survey, and the relationship between capelin length and acoustic target strength (Gjøsæter, et al. 1998). For capelin weighted depth, we used the same acoustic segment resolved in 10 m depth channels to calculate the weighted median depth of the capelin backscatter at each trawl location. This depth was then standardised with respect to time of day at each trawl location by fitting a Generalised Additive model from which capelin depth was predicted for a fixed time of day (see Standardisation of capelin vertical distribution in the methods section of the article). The local cod density (number of individuals ≥ 30 cm/km2) was estimated from each demersal trawl haul using standard methods for cod swept area calculation in the Barents Sea, which assume that the effective sweep width of the trawl increases with cod size up to 62 cm (Mehl, et al. 2014).