Abstract

Abstract Deep-sea marine fishes support important fisheries but estimates of their distributions are often incomplete as the data behind them may reflect fishing practices, access rights, or political boundaries, rather than actual geographic distributions. We use a simple suitable habitat model based on bottom depth, temperature, and salinity to estimate the potential distribution of Greenland halibut (Reinhardtius hippoglossoides). A large presence-only dataset is examined using multivariate kernel densities to define environmental envelopes, which we link to spatial distribution using a pan-Arctic oceanographic model. Occurrences generally fit the model well, although there were gaps in the predicted circum-Arctic distribution likely due to limited survey activity in many of the ice-covered seas around the Arctic Ocean. Bottom temperature and depth were major factors defining model fit to observations, but other factors, such as ecosystem interactions and larval drift could also influence distribution. Model predictions can be tested by increasing sampling effort in poorly explored regions and by studying the connectivity of putative populations. While abundances of Greenland halibut in the High Arctic are currently low, some areas are predicted to be suitable habitat for this species, suggesting that on-going sea-ice melt may lead to fisheries expansion into new areas.

Highlights

  • Understanding the distribution of fishes is important for the efficient and sustainable management of fisheries

  • The separation of realized and available TD-spaces for the North Atlantic at temperatures between À2C and 0C was caused by fish caught north and east of Iceland (Figure 3)

  • The suitable habitat model” (SHM) were based on the assumption that only abiotic conditions such as bottom depth, temperature, and salinity would restrict the distribution of Greenland halibut

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Summary

Introduction

Understanding the distribution of fishes is important for the efficient and sustainable management of fisheries. The data to generate distribution estimates are often collected directly from fisheries and national research surveys. Modelling the VC International Council for the Exploration of the Sea 2021.

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