Abstract

Species distribution models (SDMs) are valuable tools for describing the occurrence of species and predicting suitable habitats. This study used generalized additive models (GAMs) and MaxEnt models to predict the relative densities of four cetacean species (sei whale Balaeanoptera borealis, southern right whale Eubalaena australis, Peale’s dolphin Lagenorhynchus australis, and Commerson’s dolphin Cephalorhynchus commersonii) in neritic waters (≤100 m depth) around the Falkland Islands, using boat survey data collected over three seasons (2017–2019). The model predictor variables (PVs) included remotely sensed environmental variables (sea surface temperature, SST, and chlorophyll-a concentration) and static geographical variables (e.g. water depth, distance to shore, slope). The GAM results explained 35 to 41% of the total deviance for sei whale, combined sei whales and unidentified large baleen whales, and Commerson’s dolphins, but only 17% of the deviance for Peale’s dolphins. The MaxEnt models for all species had low to moderate discriminatory power. The relative density of sei whales increased with SST in both models, and their predicted distribution was widespread across the inner shelf which is consistent with the use of Falklands’ waters as a coastal summer feeding ground. Peale’s dolphins and Commerson’s dolphins were largely sympatric across the study area. However, the relative densities of Commerson’s dolphins were generally predicted to be higher in nearshore, semi-enclosed, waters compared with Peale’s dolphins, suggesting some habitat partitioning. The models for southern right whales performed poorly and the results were not considered meaningful, perhaps due to this species exhibiting fewer strong habitat preferences around the Falklands. The modelling results are applicable to marine spatial planning to identify where the occurrence of cetacean species and anthropogenic activities may most overlap. Additionally, the results can inform the process of delineating a potential Key Biodiversity Area for sei whales in the Falkland Islands.

Highlights

  • The survey data and the predictor variables (PVs) were compiled into data frames for generalized additive modelling (GAMs: [26]), based on grids of 4 km and 7 km resolution; the latter was subsequently determined to provide a better fit to the data for each species, and was selected for the final modelling

  • For all of the cetacean species modelled in the Falklands, a 7 km resolution GAM produced better model fit than a finer resolution GAM (4 km resolution), indicating that finer resolutions may seem advantageous from a management perspective, they can create a false impression of precision

  • A 4 km resolution was the lowest spatial-scale considered in the GAM or MaxEnt models, because it represented the best available resolution of the Sea surface temperature (SST) and Chl-a satellite imagery

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Summary

Introduction

The delineation of discrete spatial areas that support high species densities is a fundamental component of effective marine spatial planning (MSP), when designating areas. This study applied two different SDM approaches to model areas of predicted suitable habitat for four cetacean species in neritic waters ( 100 m depth) around the Falkland Islands in the south-west Atlantic: (1) pooling of data into discrete spatial units (e.g. grid cells or line segments), in which the predicted occurrence was modelled as a function of environmental variables; and (2) presence-only point data that were modelled directly [15]. The latter approach is widely used when only presence data are available [16]. We used a boat survey dataset collected over three whale seasons (2017–2019) to model the predicted relative density of two baleen whale and two dolphin species across inner shelf waters, in order to inform KBA designation and conservation management planning

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