| Issue № 2 |
Original research |
pdf-version |
Forecasting the potential range of mackerel icefish (Champsoseptalus gunnari) in the Western Arctic
| Bakanev Sergey Victorovich | DSc, Polar Research Institute of Marine Fisheries and Oceanography (PINRO), 6, Knipovich St., Murmansk, 183763, Russia, mombus@gmail.com |
|
Keywords: Champsocephalus gunnari mackerel icefish species distribution modelling ensemble modelling biomod2 bipolar transfer ecological niche introduction Western Arctic |
Summary: The study theoretically assesses the environmental suitability of the Arctic seas of Russia for potential introduction of the Antarctic icefish (Champsocephalus gunnari), a potential cold-water aquaculture species with a unique physiology (lack of hemoglobin). Despite the external similarities of the polar conditions, a quantitative analysis of the transfer of an ecological niche between hemispheres has not been carried out previously. Ensemble models of the distribution of the species (10 algorithms, the biomod2 package) were constructed with a projection on the water area of the Western Arctic (65-90°N, 0-120° E) for the modern period, 2050 and 2090, according to the SSP5 8.5 scenario. At that, we based on data on the presence of the species near the island of South Georgia (1840 cells, 1986-2023) and abiotic predictors (depth, oxygen, distance to shore, bottom temperature, salinity. Results show that 98.9% of the Arctic area falls within the extrapolation zone of the model (MESS < 0), niche overlap indices are minimal (D = 0.097; I = 0.257). In modern conditions, the increased suitability of the environment (HSI 0.6–0.8) is confined to the coastal shelves of Arctic archipelagos. By 2090, zones with non‑zero HSI remain only around the Severnaya Zemlya with a marked decreased in values. The obtained forecasts are hypothetical due to the narrow range of training data (South Georgia only) and require expanding the sample to include all populations of the species, integrating physiological models, and accounting for biotic interactions. © Petrozavodsk State University |
Received on: 25 March 2026 Published on: 26 June 2026 | |
References
Andriyashev A. P. General review of the Antarctic bottom fish fauna, Trudy Zoologicheskogo instituta AN SSSR. 1986. T. 153. P. 9–45.
Araújo M. B., New M. Ensemble forecasting of species distributions, Trends in Ecology & Evolution. 2007. Vol. 22, No. 1. P. 42–47. DOI: 10.1016/j.tree.2006.09.010
Assis J., Fernández Bejarano S. J., Salazar V. W., Schepers L., Gouvêa L., Fragkopoulou E., Leclercq F., Vanhoorne B., Tyberghein L., Serrão E. A., Verbruggen H., De Clerck O. Bio-ORACLE v3.0. Pushing marine data layers to the CMIP6 Earth system models of climate change research, Global Ecology and Biogeography. 2024. Vol. 33, No. 4. Art. e13813.
Broennimann O., Fitzpatrick M. C., Pearman P. B., Petitpierre B., Pellissier L., Yoccoz N. G., Thuiller W., Fortin M, J., Randin C., Zimmermann N. E., Graham C. H., Guisan A. Measuring ecological niche overlap from occurrence and spatial environmental data, Global Ecology and Biogeography. 2012. Vol. 21, No. 4. P. 481–497. DOI: 10.1111/j.1466-8238.2011.00698.x
CC. et al.. Cambridge; New York: Cambridge University Press, 2022. 3056 p. DOI: 10.1017/9781009325844
Di Cola V., Broennimann O., Petitpierre B., et al. Ecospat: An R package to support spatial analyses and modeling of species niches and distributions, Ecography. 2017. Vol. 40. P. 774–787. DOI: 10.1111/ecog.02671
Dunbar M. J. Ecological Development in Polar Regions: A Study in Evolution. Englewood Cliffs: Prentice-Hall, 1968. 119 p.
Eastman J. T. Antarctic Fish Biology: Evolution in a Unique Environment. San Diego: Academic Press, 1993. 322 p.
Eastman J. T., McCune A. R. Fishes on the Antarctic continental shelf: evolution of a marine species flock?, Journal of Fish Biology. 2000. Vol. 57, Suppl. A. P. 84–102. DOI: 10.1111/j.1095-8649.2000.tb02246.x
Egginton S., Skilbeck C., Scheirer A., Resende A. Skeletal muscle adaptations in a naturally hypertrophied heart: long-term acclimation to temperature and lifestyle in Antarctic and sub-Antarctic notothenioid fish, Journal of Experimental Biology. 2002. Vol. 205, No. 3. P. 361–374. DOI: 10.1242/jeb.205.3.361
Elith J., Kearney M., Phillips S. The art of modelling range-shifting species, Methods in Ecology and Evolution. 2010. Vol. 1, No. 4. P. 330–342. DOI: 10.1111/j.2041-210X.2010.00036.x
Elith J., Leathwick J. R. Species distribution models: ecological explanation and prediction across space and time, Annual Review of Ecology, Evolution, and Systematics. 2009. Vol. 40. P. 677–697. DOI: 10.1146/annurev.ecolsys.110308.120159
Everson I. (ed.). Krill: biology, ecology and fisheries. Oxford: Blackwell Science, 2000. 372 p.
Franklin J. Mapping species distributions: spatial inference and prediction. Cambridge: Cambridge University Press, 2010. 340 p.
Grinnell J. The niche relationships of the California thrasher, The Auk. 1917. Vol. 34, No. 4. P. 427–433. DOI: 10.2307/4072271
Guisan A., Zimmermann N. E. Predictive habitat distribution models in ecology, Ecological Modelling. 2000. Vol. 135, No. 2–3. P. 147–186. DOI: 10.1016/S0304-3800(00)00354-9
Hijmans R. J., Phillips S., Leathwick J., Elith J. Dismo: species distribution modeling. 2015. R Package Version 1.0-12. URL: http://CRAN.R-project.org/package=dismo (data obrascheniya: 26.03.2026).
Hollyman P., Hill S., Laptikhovsky V., Belchier M., Gregory S., Clement A., Collins M. A long road to recovery: dynamics and ecology of the marbled rockcod (Notothenia rossii, family: Nototheniidae) at South Georgia, 50 years after overexploitation, ICES Journal of Marine Science. 2021. Vol. 78, No. 9. P. 3328–3341. DOI: 10.1093/icesjms/fsab150
Hutchinson G. E. Concluding remarks, Cold Spring Harbor Symposia on Quantitative Biology. 1957. Vol. 22. P. 415–427. DOI: 10.1101/SQB.1957.022.01.039
IPBES. Global assessment report on biodiversity and ecosystem services, Eds. E. S. Brondízio, J. Settele, S. Díaz, H. T. Ngo. Bonn: IPBES Secretariat, 2019. 1148 p. DOI: 10.5281/zenodo.3831673
Kearney M., Porter W. Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges, Ecology Letters. 2009. Vol. 12, No. 4. P. 334–350. DOI: 10.1111/j.1461-0248.2008.01277.x
Kock K, H., Duhamel G., Hureau J. C. Biology and status of exploited Antarctic fish stocks: A review, BIOMASS Scientific Series. 1985. Vol. 6. P. 1–143.
Kock K, H., Everson I. Biology and ecology of mackerel icefish Champsocephalus gunnari: an Antarctic fish lacking haemoglobin, Comparative Biochemistry and Physiology. Part A: Molecular & Integrative Physiology. 1997. Vol. 118, No. 4. P. 1067–1077.
Leroy B., Meynard C. N., Bellard C., Courchamp F. Virtualspecies, an R package to generate virtual species distributions, Ecography. 2016. Vol. 39, No. 6. P. 599–607. DOI: 10.1111/ecog.01388
Merow C., Smith M. J., Edwards T. C., Guisan A., McMahon S. M., Normand S., Thuiller W., Wüest R. O., Zimmermann N. E., Elith J. What do we gain from simplicity versus complexity in species distribution models?, Ecography. 2014. Vol. 37, No. 12. P. 1267–1281. DOI: 10.1111/ecog.00845
Molnar J. L., Gamboa R. L., Revenga C., Spalding M. D. Assessing the global threat of invasive species to marine biodiversity, Frontiers in Ecology and the Environment. 2008. Vol. 6, No. 9. P. 485–492. DOI: 10.1890/070064
Near T. J., Dornburg A., Kuhn K. L., Job J. A., Zardus J., Miya M., Cheng C. H. C. Ancient climate change, antifreeze, and the evolutionary diversification of Antarctic fishes, Proceedings of the National Academy of Sciences. 2012. Vol. 109, No. 9. P. 3434–3439. DOI: 10.1073/pnas.1115169109
Owens H. L., Campbell L. P., Dornak L. L., Saupe E. E., Barve N., Soberón J., Ingenloff K., Lira-Noriega A., Hensz C. M., Myers C. E., Peterson A. T. Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas, Ecological Modelling. 2013. Vol. 263. P. 10–18. DOI: 10.1016/j.ecolmodel.2013.04.011
Peterson A. T. Predicting the geography of species' invasions via ecological niche modeling, Quarterly Review of Biology. 2003. Vol. 78, No. 4. P. 419–433. DOI: 10.1086/378926
Peterson A. T., Soberón J., Pearson R. G., Anderson R. P., Martínez-Meyer E., Nakamura M., Araújo M. B. Ecological niches and geographic distributions. Princeton: Princeton University Press, 2011. 328 p.
Pollock L. J., Tingley R., Morris W. K., Golding N., O'Hara R. B., Parris K. M., Vesk P. A., McCarthy M. A. Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM), Methods in Ecology and Evolution. 2014. Vol. 5, No. 5. P. 397–406. DOI: 10.1111/2041-210X.12180
Polyakov I. V., Alkire M. B., Bluhm B. A., Brown K. A., Carmack E. C., Chierici M., Danielson S. L., Ellingsen I., Ershova E. A., Gårdfeldt K., Ingvaldsen R. B., Pnyushkov A. V., Slagstad D., Wassmann P. Borealization of the Arctic Ocean in response to anomalous advection from sub-Arctic seas, Frontiers in Marine Science. 2020. Vol. 7. Art. 491. DOI: 10.3389/fmars.2020.00491
Portner H. O., Storch D., Heilmayer O. Constraints and trade-offs in climate-dependent adaptation: energy budgets and growth in a latitudinal cline, Scientia Marina. 2005. Vol. 69. P. 271–285. DOI: 10.3989/scimar.2005.69s2271
Ruud J. T. Vertebrates without erythrocytes and blood pigment, Nature. 1954. Vol. 173, No. 4410. P. 848–850. DOI: 10.1038/173848a0
Soberón J., Peterson A. T. Interpretation of models of fundamental ecological niches and species' distributional areas, Biodiversity Informatics. 2005. Vol. 2. P. 1–10. DOI: 10.17161/bi.v2i0.4
Thuiller W., Lafourcade B., Engler R., Araújo M. B. BIOMOD – a platform for ensemble forecasting of species distributions, Ecography. 2009. Vol. 32, No. 3. P. 369–373. DOI: 10.1111/j.1600-0587.2008.05742.x
Tingley M. W., Monahan W. B., Beissinger S. R., Moritz C. The push and pull of climate change causes heterogeneous shifts in avian elevational ranges, Global Change Biology. 2014. Vol. 18, No. 11. P. 3279–3290. DOI: 10.1111/j.1365-2486.2012.02784.x
Whitehouse M. J., Meredith M. P., Rothery P., Atkinson A., Ward P., Korb R. E. Rapid warming of the ocean around South Georgia, Southern Ocean, during the 20th century: forcings, characteristics and implications for lower trophic levels, Deep-Sea Research Part I: Oceanographic Research Papers. 2008. Vol. 55, No. 10. P. 1218–1228. DOI: 10.1016/j.dsr.2008.06.002
Zadvorkin A. S. Formation of the fishery and trade complex: economic consolidation of management organization, Voprosy rybolovstva. 2025. T. 26, No. 1. P. 153–158. DOI: 10.36038/0234-2774-2025-26-1-153-1581
Zurell D., Elith J., Schröder B. Predicting to new environments: tools for visualizing model behaviour and impacts on mapped distributions, Diversity and Distributions. 2012. Vol. 18, No. 6. P. 628–634. DOI: 10.1111/j.1472-4642.2012.00887.x
Zurell D., Franklin J., König C., Becker P. D., Durán A. P., Gravel D., Guisan A., Moor H., Rajagopal V., Schlagler J., Thuiller W., Cabeza M. A standard protocol for reporting species distribution models, Ecography. 2020. Vol. 43, No. 9. P. 1261–1277. DOI: 10.1111/ecog.04960
© 2011 - 2026
Petrozavodsk State University
technical support - RCNIT
The editor-in-chief - Andrey Korosov
ecopri@petrsu.ru