Quantifying the causes and consequences of variation in satellite-derived population indices: a case study of emperor penguins

Sara Labrousse, David Iles, Lise Viollat, Peter Fretwell, Philip N. Trathan, Daniel P. Zitterbart, Stephanie Jenouvrier, Michelle LaRue

Research output: Contribution to journalArticlepeer-review

Abstract

Very high-resolution satellite (VHR) imagery is a promising tool for estimating the abundance of wildlife populations, especially in remote regions where traditional surveys are limited by logistical challenges. Emperor penguins Aptenodytes forsteri were the first species to have a circumpolar population estimate derived via VHR imagery. Here we address an untested assumption from Fretwell et al. (2012) that a single image of an emperor penguin colony is a reasonable representation of the colony for the year the image was taken. We evaluated satellite-related and environmental variables that might influence the calculated area of penguin pixels to reduce uncertainties in satellite-based estimates of emperor penguin populations in the future. We focused our analysis on multiple VHR images from three representative colonies: Atka Bay, Stancomb-Wills (Weddell Sea sector) and Coulman Island (Ross Sea sector) between September and December during 2011. We replicated methods in Fretwell et al. (2012), which included using supervised classification tools in ArcGIS 10.7 software to calculate area occupied by penguins (hereafter referred to as ‘population indices’) in each image. We found that population indices varied from 2 to nearly 6-fold, suggesting that penguin pixel areas calculated from a single image may not provide a complete understanding of colony size for that year. Thus, we further highlight the important roles of: (i) sun azimuth and elevation through image resolution and (ii) penguin patchiness (aggregated vs. distributed) on the calculated areas. We found an effect of wind and temperature on penguin patchiness. Despite intra-seasonal variability in population indices, simulations indicate that reliable, robust population trends are possible by including satellite-related and environmental covariates and aggregating indices across time and space. Our work provides additional parameters that should be included in future models of population size for emperor penguins.

Original languageEnglish (US)
JournalRemote Sensing in Ecology and Conservation
DOIs
StateAccepted/In press - 2021

Bibliographical note

Funding Information:
Geospatial support for this work was provided by the Polar Geospatial Center under NSF‐OPP awards 1043681 and 1559691. NCAR‐ PPC visitor funds and Ian Nisbet that supported the internship of LV. WWF‐UK supported PNT and PTF under grant GB095701. DZ was supported by The Penzance Endowed Fund and The Grayce B. Kerr Fund in Support of Assistant Scientists. To SJ, ML, SL, LV, NSF OPP 1744794. We thank Rose Foster‐Dyer for analysing one image of Coulman Island for comparison and to Frédéric Le Manach for figure designs.

Funding Information:
Geospatial support for this work was provided by the Polar Geospatial Center under NSF‐OPP awards 1043681 and 1559691. NCAR‐PPC visitor funds and Ian Nisbet that supported the internship of LV. WWF‐UK supported PNT and PTF under grant GB095701. DZ was supported by The Penzance Endowed Fund and The Grayce B. Kerr Fund in Support of Assistant Scientists. To SJ, ML, SL, LV, funding was provided by NSF OPP 1744794.

Publisher Copyright:
© 2021 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London.

Keywords

  • Emperor penguin
  • VHR imagery
  • intra-seasonal variability
  • population estimates
  • population trend
  • satellite imagery

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