# Spatial overlap of sea ice-associated predators and prey in western Hudson Bay

## TL;DR

The study maps how sea ice predators and prey overlap in western Hudson Bay to understand ecological relationships and inform conservation.

## Contribution

The study introduces a novel use of Getis-Ord hotspots to analyze spatial relationships among ice-associated Arctic species.

## Key findings

- Polar bear hotspots overlapped significantly with Arctic foxes and seals, but bearded and ringed seals had low overlap.
- Arctic foxes concentrated on nearshore ice, while polar bears and bearded seals used offshore areas.
- Systematic opportunistic observations provided low-cost insights into ecological patterns on sea ice.

## Abstract

Spatio-temporal distribution of species shapes community structure and ecosystem function, yet the mechanisms driving biological hotspots remain unclear in dynamic environments like sea ice. We computed Getis-Ord (Gi*) distribution hotspots based on four years of direct and indirect observations of polar bears (Ursus maritimus), Arctic foxes (Vulpes lagopus), ringed seals (Pusa hispida), and bearded seals (Erignathus barbatus) in western Hudson Bay, to identify spatial clustering and assess spatial relationships among these ice-associated species. We further mapped distribution hotspots of bear-hunting sign to examine predator-prey and intraguild relationships. Polar bears and bearded seals primarily used offshore areas, while Arctic foxes concentrated their activity on nearshore ice. Ringed seals built lairs throughout the study area but they mostly hauled out on landfast ice. The polar bear hotspot overlapped largely (30% − 49%) with those of the three other species. Particularly, 80% of the Arctic fox hotspot was included in the polar bear hotspot. In contrast, bearded seals and ringed seals had low overlap (18%), reflecting their different habitat preferences. Understanding current patterns in ice-associated species’ distributions and relationships is crucial to inform conservation actions and for predicting direct and indirect effects of Arctic warming. Our results help identify key ecological areas on sea ice and demonstrate how systematic collection of opportunistic observations can be combined to generate valuable ecological insights at low cost.