Literature DB >> 33956835

Aerial survey estimates of polar bears and their tracks in the Chukchi Sea.

Paul B Conn1, Vladimir I Chernook2, Erin E Moreland1, Irina S Trukhanova3, Eric V Regehr4,5, Alexander N Vasiliev2, Ryan R Wilson4, Stanislav E Belikov6, Peter L Boveng1.   

Abstract

Polar bears are of international conservation concern due to climate change but are difficult to study because of low densities and an expansive, circumpolar distribution. In a collaborative U.S.-Russian effort in spring of 2016, we used aerial surveys to detect and estimate the abundance of polar bears on sea ice in the Chukchi Sea. Our surveys used a combination of thermal imagery, digital photography, and human observations. Using spatio-temporal statistical models that related bear and track densities to physiographic and biological covariates (e.g., sea ice extent, resource selection functions derived from satellite tags), we predicted abundance and spatial distribution throughout our study area. Estimates of 2016 abundance ([Formula: see text]) ranged from 3,435 (95% CI: 2,300-5,131) to 5,444 (95% CI: 3,636-8,152) depending on the proportion of bears assumed to be missed on the transect line during Russian surveys (g(0)). Our point estimates are larger than, but of similar magnitude to, a recent estimate for the period 2008-2016 ([Formula: see text]; 95% CI 1,522-5,944) derived from an integrated population model applied to a slightly smaller area. Although a number of factors (e.g., equipment issues, differing platforms, low sample sizes, size of the study area relative to sampling effort) required us to make a number of assumptions to generate estimates, it establishes a useful lower bound for abundance, and suggests high spring polar bear densities on sea ice in Russian waters south of Wrangell Island. With future improvements, we suggest that springtime aerial surveys may represent a plausible avenue for studying abundance and distribution of polar bears and their prey over large, remote areas.

Entities:  

Year:  2021        PMID: 33956835      PMCID: PMC8101751          DOI: 10.1371/journal.pone.0251130

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  13 in total

1.  Accommodating unmodeled heterogeneity in double-observer distance sampling surveys.

Authors:  D L Borchers; J L Laake; C Southwell; C G M Paxton
Journal:  Biometrics       Date:  2006-06       Impact factor: 2.571

2.  Invariant polar bear habitat selection during a period of sea ice loss.

Authors:  Ryan R Wilson; Eric V Regehr; Karyn D Rode; Michelle St Martin
Journal:  Proc Biol Sci       Date:  2016-08-17       Impact factor: 5.349

3.  Polar bear population dynamics in the southern Beaufort Sea during a period of sea ice decline.

Authors:  Jeffrey F Bromaghin; Trent L Mcdonald; Ian Stirling; Andrew E Derocher; Evan S Richardson; Eric V Regehr; David C Douglas; George M Durner; Todd Atwood; Steven C Amstrup
Journal:  Ecol Appl       Date:  2015-04       Impact factor: 4.657

4.  Variation in the response of an Arctic top predator experiencing habitat loss: feeding and reproductive ecology of two polar bear populations.

Authors:  Karyn D Rode; Eric V Regehr; David C Douglas; George Durner; Andrew E Derocher; Gregory W Thiemann; Suzanne M Budge
Journal:  Glob Chang Biol       Date:  2013-11-17       Impact factor: 10.863

5.  Spring fasting behavior in a marine apex predator provides an index of ecosystem productivity.

Authors:  Karyn D Rode; Ryan R Wilson; David C Douglas; Vanessa Muhlenbruch; Todd C Atwood; Eric V Regehr; Evan S Richardson; Nicholas W Pilfold; Andrew E Derocher; George M Durner; Ian Stirling; Steven C Amstrup; Michelle St Martin; Anthony M Pagano; Kristin Simac
Journal:  Glob Chang Biol       Date:  2017-11-06       Impact factor: 10.863

6.  Harvesting wildlife affected by climate change: a modelling and management approach for polar bears.

Authors:  Eric V Regehr; Ryan R Wilson; Karyn D Rode; Michael C Runge; Harry L Stern
Journal:  J Appl Ecol       Date:  2017-03-08       Impact factor: 6.528

7.  Conservation status of polar bears (Ursus maritimus) in relation to projected sea-ice declines.

Authors:  Eric V Regehr; Kristin L Laidre; H Resit Akçakaya; Steven C Amstrup; Todd C Atwood; Nicholas J Lunn; Martyn Obbard; Harry Stern; Gregory W Thiemann; Øystein Wiig
Journal:  Biol Lett       Date:  2016-12       Impact factor: 3.703

8.  Interrelated ecological impacts of climate change on an apex predator.

Authors:  Kristin L Laidre; Stephen Atkinson; Eric V Regehr; Harry L Stern; Erik W Born; Øystein Wiig; Nicholas J Lunn; Markus Dyck
Journal:  Ecol Appl       Date:  2020-02-04       Impact factor: 4.657

9.  Integrated Population Modeling Provides the First Empirical Estimates of Vital Rates and Abundance for Polar Bears in the Chukchi Sea.

Authors:  Eric V Regehr; Nathan J Hostetter; Ryan R Wilson; Karyn D Rode; Michelle St Martin; Sarah J Converse
Journal:  Sci Rep       Date:  2018-11-14       Impact factor: 4.379

10.  On Extrapolating Past the Range of Observed Data When Making Statistical Predictions in Ecology.

Authors:  Paul B Conn; Devin S Johnson; Peter L Boveng
Journal:  PLoS One       Date:  2015-10-23       Impact factor: 3.240

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  2 in total

1.  Demographic risk assessment for a harvested species threatened by climate change: polar bears in the Chukchi Sea.

Authors:  Eric V Regehr; Michael C Runge; Andrew Von Duyke; Ryan R Wilson; Lori Polasek; Karyn D Rode; Nathan J Hostetter; Sarah J Converse
Journal:  Ecol Appl       Date:  2021-10-26       Impact factor: 6.105

2.  An on-ice aerial survey of the Kane Basin polar bear (Ursus maritimus) subpopulation.

Authors:  Øystein Wiig; Stephen N Atkinson; Erik W Born; Seth Stapleton; Todd Arnold; Markus Dyck; Kristin L Laidre; Nicholas J Lunn; Eric V Regehr
Journal:  Polar Biol       Date:  2021-11-22       Impact factor: 2.310

  2 in total

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