Abstract

Identification of species’ Biologically Important Areas (BIAs) is fundamental to conservation planning and species distribution models (SDMs) are a powerful tool commonly used to do this. Presence‐only data are increasingly being used to develop SDMs to aid the conservation decision‐making process. The application of presence‐only SDMs for marine species’ is particularly attractive due to often logistical and economic costs of obtaining systematic species’ distribution data. However, robust model validation is important for conservation management applications that require accurate and reliable species’ occurrence data (e.g., spatially explicit risk assessments). This is commonly done using a random subset of the data and less commonly with fully independent test data. Here, we apply a spatial block cross‐validation (CV) approach to validate a MaxEnt presence‐only model using independent presence/absence survey data for a highly mobile, marine species (humpback whale, Megaptera novaengliae) in the Great Barrier Reef (GBR). A MaxEnt model was developed using opportunistic whale sightings (2003–2007) and then used to identify areas differing in habitat suitability (low, medium, high) to conduct a systematic, line‐transect, aerial survey (2012) and derive a density surface model. A spatial block CV buffering strategy was used to validate the MaxEnt model, using the opportunistic sightings as training data and independent aerial survey sightings data as test data. Moderate performance measures indicate MaxEnt was reliable in identifying the distribution patterns of a mobile whale species on their breeding ground, indicated by areas of high density aligned to areas of high habitat suitability. Furthermore, we demonstrate that MaxEnt models can be useful and cost‐effective for designing a sampling scheme to undertake systematic surveys that significantly reduces sampling effort. In this study, higher quality information on whale reproductive class (calf vs. non‐calf groups) was obtained that the presence‐only data lacked, while sampling only 18% of the GBR World Heritage Area. The validation approach using fully independent data provides greater confidence in the MaxEnt model, which indicates significant overlap with the main breeding ground of humpback whales and the inner shipping route. This is important when evaluating presence‐only models within certain conservation management applications, such as spatial risk assessments.

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