Abstract
In southern African waters, information about species distribution and habitat preferences of many cetacean species is limited, despite the recent economic growth that may affect them. We determined the relative importance of eight environmental variables (bathymetry, distance to shore, slope, chlorophyll-a, salinity, eastwards sea water velocity, northwards sea water velocity and sea surface temperature) as drivers of seasonal habitat preferences of Bryde’s whales (Balaenoptera brydei), humpback whales (Megaptera novaeangliae), southern right whales (Eubalaena australis) and sperm whales (Physeter macrocephalus). Using presence only data from multiple sources, we constructed predictive species distribution models (SDMs) consisting of ensembles of seven algorithms for these species during both summer and winter. Predicted distribution for all cetaceans was high in southern Africa and, in particular, within the South African Exclusive Economic Zone (EEZ). Predictive models indicated a more pronounced seasonal variation for humpback, sperm and southern right whales than for Bryde’s whales. Southern right whales occurred closer to shore during winter, humpback whales were more likely to occur along the east coast in winter and the west coast in summer, and sperm whales were more concentrated off the shelf in winter. Our study shows that ensemble models using historical, incidental and scientific data, in conjunction with modern environmental variables, can provide baseline knowledge on important environmental drivers of cetacean distribution for conservation purposes. Results of this study can further be used to help develop marine spatial plans and identify important marine mammal areas.
Highlights
Worldwide, cetaceans are increasingly threatened by anthropogenic activities (Williams et al, 2014; Braulik et al, 2017)
We model the seasonal distribution of four large commonly-encountered whale species in southern African waters using an ensemble of species distribution models (SDMs) with presence only data
Our results indicate that the predicted occurrence for the four cetaceans studied in this paper is widespread in South Africa, with a small percentage of their habitat being protected by the current marine protected areas (MPAs)
Summary
Cetaceans are increasingly threatened by anthropogenic activities (Williams et al, 2014; Braulik et al, 2017). Modelling cetacean distribution is challenging because of the dynamic nature of ocean environments, the often highly mobile nature of cetacean species, and the difficulty and expense of obtaining adequate species distribution information (Gregr & Trites, 2001; Redfern et al, 2006). This has led to the development of SDMs based on data from several sources (Torres et al, 2013; Waggitt et al, 2020). The use of such datasets has two important challenges, the first being that the data are often spatially biased (Aiello-Lammens et al, 2015) and the second being that absence data are seldom available (Hirzel et al, 2006; Purdon et al, 2020a)
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