Modelling the effects of environmental conditions on the acoustic occurrence and behaviour of Antarctic blue whales.

Fannie W Shabangu,Ken P Findlay,Dawit Yemane,Kathleen M Stafford,Paul Ensor,Gianni Pavan

doi:10.1371/journal.pone.0172705

Abstract

Harvested to perilously low numbers by commercial whaling during the past century, the large scale response of Antarctic blue whales Balaenoptera musculus intermedia to environmental variability is poorly understood. This study uses acoustic data collected from 586 sonobuoys deployed in the austral summers of 1997 through 2009, south of 38°S, coupled with visual observations of blue whales during the IWC SOWER line-transect surveys. The characteristic Z-call and D-call of Antarctic blue whales were detected using an automated detection template and visual verification method. Using a random forest model, we showed the environmental preferences pattern, spatial occurrence and acoustic behaviour of Antarctic blue whales. Distance to the southern boundary of the Antarctic Circumpolar Current (SBACC), latitude and distance from the nearest Antarctic shores were the main geographic predictors of blue whale call occurrence. Satellite-derived sea surface height, sea surface temperature, and productivity (chlorophyll-a) were the most important environmental predictors of blue whale call occurrence. Call rates of D-calls were strongly predicted by the location of the SBACC, latitude and visually detected number of whales in an area while call rates of Z-call were predicted by the SBACC, latitude and longitude. Satellite-derived sea surface height, wind stress, wind direction, water depth, sea surface temperatures, chlorophyll-a and wind speed were important environmental predictors of blue whale call rates in the Southern Ocean. Blue whale call occurrence and call rates varied significantly in response to inter-annual and long term variability of those environmental predictors. Our results identify the response of Antarctic blue whales to inter-annual variability in environmental conditions and highlighted potential suitable habitats for this population. Such emerging knowledge about the acoustic behaviour, environmental and habitat preferences of Antarctic blue whales is important in improving the management and conservation of this highly depleted species.

Highlights

Antarctic blue whales Balaenoptera musculus intermedia were widely distributed in the Southern Ocean prior to commercial whaling [1,2,3]
Results of call rates were thereafter assigned into day (06:00 to 18:00 local time) and night (18:00 to 06:00) depending on their recording time before fitting to the models, such day/night differentiation reflected the survey mode of the vessel rather than Antarctic summer light regimes as visual monitoring only took place from 06:00–18:00 each day
The Random forest (RF) modelling enabled the explicit interpretation of the complex relationships between blue whales and their environment from our long term acoustic data set

Summary

General introduction

Antarctic blue whales Balaenoptera musculus intermedia were widely distributed in the Southern Ocean prior to commercial whaling [1,2,3]. The current population status of Antarctic blue whale remains critically low five decades after the end of whaling; there are recent signs of population increase [4,5] These whales feed predominantly in the euphausiidrich waters of the Southern Ocean during the austral summer through autumn; and they have been presumed to fast during their over-wintering periods in low latitudes [3,6]. We present the results of analyses on the call type distribution (as call occurrence) and acoustic behaviour (as call rates) of Antarctic blue whales as a function of satellite-derived environmental parameters using the circumpolar passive acoustic measurements during the Southern Ocean Whale and Ecosystem Research (SOWER) program of the International Whaling Commission (IWC), hereafter IWC SOWER. Random forest (RF) model reveals the response of Antarctic blue whales to environmental variability and highlight the importance of environmental variability in monitoring the status of Antarctic blue whales

Acoustic data Developing and testing detectors

Modeling blue whale occurrence and behaviour Environmental data used

Blue whales in the Antarctic environment

Findings

Conclusions