Zoogeographical groups of non-commercial species

Photo: Frederik Broms, Norwegian Polar Institute.

Biotic ecosystem components - data from 2019
Typography
  • Smaller Small Medium Big Bigger
  • Default Helvetica Segoe Georgia Times

Non-commercial demersal fish species were grouped according to their biogeography to assess their relative abundance, trends and suitable habitats. Abundance of Arctic species seems to have increased in 2019 compared to the two previous years. This is probably due to high catches of Liparids. Zoogeographic grouping is consistent with their suitable habitats. Temperature is a major driver of the suitable habitats

During the 2019 Barents Sea Ecosystem Survey (BESS) 90 fish species from 28 families were recorded in pelagic and bottom trawl catches, some taxa were recorded at genus or family level only (Prokhorova et al 2020). The species were grouped into seven zoogeographic group (Widely Distributed, South Boreal, Boreal, Mainly Boreal, Arctic-Boreal, Mainly Arctic and Arctic) defined in Andriashev and Chernova (1995). In the following only bottom trawl catches of non-commercial fishes were used. Both demersal (including bentho-pelagic) and pelagic (neritopelagic, epipelagic, bathypelagic) species were included. The survey coverage at BESS in 2018 was poor (Prokhorova et al 2019) so we cannot easily compare the abundance and distribution of zoogeographical groups in 2019 with 2018, but we can compare with 2017 (Prokhorova et al 2018a, Prokhorova et al 2020). There seems to be an increase in the abundance (medium and maximum catches in bottom trawls) in Arctic and Mainly Arctic species in 2019 (Figure 3.7.1). The increase in arctic fishes in 2019 is mostly due very high catches of Liparis fabricii. This is consistent with the observed increase in 0-group liparids observed in the 2017 survey (Prokhorova et al 2018b). A paper is submitted to Fisheries Oceanography estimating the potential suitable habitats of the 33 most abundant fish species of Barents Sea using bottom trawl data from the ecosystem survey (2004-2017). It relies on the modelling of a high quantile (99th) of the biomass distribution of each of the 33 species in response to 10 potential predictors: bottom and surface temperatures and salinities, ice coverage, depth of the surface mixing layer, chlorophyll a concentrations and temporally fixed environmental conditions like sediment, slope and depth. The method identifies habitat variables that limit the fish distributions. The same analysis was run on the zoogeographic groups (species pooled, the common species excluded, see figures 3.7.2-3.7.7.

Figure 3.7.1. Distribution of non-commercial fish species from zoogeographic groups during the ecosystem survey 2017-2020. The size of circle corresponds to abundance (individuals per nautical mile, only bottom trawl stations were used, both pelagic and demersal species are included). Taken from survey reports (Prokhorova et al 2018a, Prokhorova et al 2019, Prokhorova et al 2020). Figure 3.7.1. Distribution of non-commercial fish species from zoogeographic groups during the ecosystem survey 2017-2020. The size of circle corresponds to abundance (individuals per nautical mile, only bottom trawl stations were used, both pelagic and demersal species are included). Taken from survey reports (Prokhorova et al 2018a, Prokhorova et al 2019, Prokhorova et al 2020).

What we designated as «arctic» are species from north and east limited in the south west by bottom temperature and salinity (Figure 3.7.2).

Figure 3.7.2. Arctic fishes (Amblyraja hyperborea, Aspidophoroides olrikii, Careproctus spp, , Eumicrotremus derjugini, Gaidropsarus argentatus, Liparis fabricii, Liparis tunicatus, Lycenchelys kolthoffi, Lycenchelys muraena, Lycodes adolfi, Lycodes eudipleurostictus, Lycodes frigidus, Lycodes luetkenii, Lycodes pallidus, Lycodes polaris, Lycodes reticulatus, Lycodes rossi, Lycodes seminudus, Lycodes squamiventer, Lycodonus flagellicauda, Paraliparis bathybius, Rhodichthys regina, Triglops nybelini) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum). Figure 3.7.2. Arctic fishes (Amblyraja hyperborea, Aspidophoroides olrikii, Careproctus spp, , Eumicrotremus derjugini, Gaidropsarus argentatus, Liparis fabricii, Liparis tunicatus, Lycenchelys kolthoffi, Lycenchelys muraena, Lycodes adolfi, Lycodes eudipleurostictus, Lycodes frigidus, Lycodes luetkenii, Lycodes pallidus, Lycodes polaris, Lycodes reticulatus, Lycodes rossi, Lycodes seminudus, Lycodes squamiventer, Lycodonus flagellicauda, Paraliparis bathybius, Rhodichthys regina, Triglops nybelini) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum).

What we designated as «Mainly-arctic» are: Species mainly from north limited in the south by ice and surface temperature and sensitive to shallow depth (Figure 3.7.2).

Figure 3.7.3. Mainly Arctic fishes (Cottunculus microps, Eumicrotremus spinosus, Gymnocanthus tricuspis, Liparis bathyarcticus) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum).  Figure 3.7.3. Mainly Arctic fishes (Cottunculus microps, Eumicrotremus spinosus, Gymnocanthus tricuspis, Liparis bathyarcticus) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum).

What we designated as « arctic-boreal » are: Species from north and east limited in the south west by temperature (Figure 3.7.4). The difference with the Arctic group may be a question of depth preferences.

Figure 3.7.4. Arctic boreal fishes (Leptagonus decagonus, Triglops pingelii) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum). Figure 3.7.4. Arctic boreal fishes (Leptagonus decagonus, Triglops pingelii) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum).

What we designated as « mainly boreal» are: Widespread species not really limited by the environmental conditions in the Barents Sea.

Figure 3.7.5. Mainly boreal fishes (Amblyraja radiata, Anarhichas denticulatus, Anarhichas lupus, Anarhichas minor, Artediellus atlanticus, Bathyraja spinicauda, Brosme brosme, Cyclopterus lumpus, Glyptocephalus cynoglossus, Hippoglossoides platessoides, Hippoglossus hippoglossus, Leptoclinus maculatus, Lethenteron camtschaticum, Limanda limanda, Lumpenus lampretaeformis, Lycodes esmarkii, Lycodes gracilis, Myoxocephalus scorpius, Pleuronectes platessa, Pollachius virens, Rajella fyllae) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum). Figure 3.7.5. Mainly boreal fishes (Amblyraja radiata, Anarhichas denticulatus, Anarhichas lupus, Anarhichas minor, Artediellus atlanticus, Bathyraja spinicauda, Brosme brosme, Cyclopterus lumpus, Glyptocephalus cynoglossus, Hippoglossoides platessoides, Hippoglossus hippoglossus, Leptoclinus maculatus, Lethenteron camtschaticum, Limanda limanda, Lumpenus lampretaeformis, Lycodes esmarkii, Lycodes gracilis, Myoxocephalus scorpius, Pleuronectes platessa, Pollachius virens, Rajella fyllae) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum).

What we designated as «boreal» are: Species from the south limitied in the north by temperature and that avoid depth (Figure 3.7.6).

Figure 3.7.6. Boreal fishes (Anisarchus medius, Argentina silus, Chimaera monstrosa, Enchelyopus cimbrius, Liparis liparis, Lycenchelys sarsii, Macrourus berglax, Microstomus kitt, Molva molva, Pollachius pollachius, Rajella lintea, Sebastes viviparus, Triglops murrayi, Trisopterus esmarkii, Phrynorhombus norvegicus) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum). Figure 3.7.6. Boreal fishes (Anisarchus medius, Argentina silus, Chimaera monstrosa, Enchelyopus cimbrius, Liparis liparis, Lycenchelys sarsii, Macrourus berglax, Microstomus kitt, Molva molva, Pollachius pollachius, Rajella lintea, Sebastes viviparus, Triglops murrayi, Trisopterus esmarkii, Phrynorhombus norvegicus) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum).

What we designated as «south-boreal» are: Species from the south limited in the north by temperature and that avoid depth (Figure 3.7.7). These species appear to have very similar suitable habitats as the boreal species (Figure 3.7.7).

Figure 3.7.7. South boreal fishes (Gadiculus argenteus, Lophius piscatorius, Merlangius merlangus, Merluccius merluccius, Phycis blennoides) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum). Figure 3.7.7. South boreal fishes (Gadiculus argenteus, Lophius piscatorius, Merlangius merlangus, Merluccius merluccius, Phycis blennoides) data from ecosystem survey 2013. Top: max predicted abundance, bottom: symbols show limiting habitat factors: green if they are temporally fixed (sediment, depth, slope), blue if they are temporally dynamic (all other parameters), grey if they are only weakly limiting (predicted maximum biomass >= 25% of the species-predictor QGAM model maximum).

To sum up, there seem to be an increase in abundance of Arctic species in 2019 compared to the years after 2013. Some very high catches of Liparis fabricii is mainly responsible for this increase.

Logo ICES