Comparing sea ice habitat fragmentation metrics using integrated step selection analysis

Abstract Habitat fragmentation occurs when continuous habitat gets broken up as a result of ecosystem change. While commonly studied in terrestrial ecosystems, Arctic sea ice ecosystems also experience fragmentation, but are rarely studied in this context. Most fragmentation analyses are conducted u...

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Bibliographic Details
Published in:Ecology and Evolution
Main Authors: Biddlecombe, Brooke A., Bayne, Erin M., Lunn, Nicholas J., McGeachy, David, Derocher, Andrew E.
Other Authors: World Wildlife Fund, Canadian Wildlife Federation, Natural Sciences and Engineering Research Council of Canada, Quark Expeditions
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2020
Subjects:
Arctic
Hudson
Hudson Bay
Sea ice
Ursus maritimus
Online Access:http://dx.doi.org/10.1002/ece3.6233
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fece3.6233
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.6233
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ece3.6233
Description
Summary:Abstract Habitat fragmentation occurs when continuous habitat gets broken up as a result of ecosystem change. While commonly studied in terrestrial ecosystems, Arctic sea ice ecosystems also experience fragmentation, but are rarely studied in this context. Most fragmentation analyses are conducted using patch‐based metrics, which are potentially less suitable for sea ice that has gradual changes between sea ice cover, than distinct “long‐term” patches. Using an integrated step selection analysis, we compared the descriptive power of a patch‐based metric to a more novel metric, the variation in local spatial autocorrelation over time. We used satellite telemetry data from 39 adult female polar bears ( Ursus maritimus ) in Hudson Bay to examine their sea ice habitat using Advanced Microwave Scanning Radiometer 2 data during sea ice breakup in May through July from 2013–2018. Spatial autocorrelation resulted in better model fits across 64% of individuals, although both metrics were more effective in describing movement patterns than habitat selection. Variation in local spatial autocorrelation allows for the visualization of sea ice habitat at complex spatial and temporal scales, condensing a targeted time period of habitat that would otherwise have to be analyzed daily.

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