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Dryad

Large marine predator aerial survey data for Hauraki Gulf, New Zealand

Data files

May 01, 2023 version files 2.48 MB

Abstract

Large marine predators, such as cetaceans and sharks, play a crucial role in maintaining biodiversity patterns and ecosystem health. Despite the recognised importance of these animals and their over-representation as threatened species, distribution data at appropriate temporal and spatial scales is often lacking or insufficient for effective conservation. 

Here, we present sightings of large marine megafauna recorded from a replicate systematic aerial survey undertaken in the Hauraki Gulf, Aotearoa New Zealand during a full year. Using flexible machine learning models (Boosted Regression Tree models), we use these sightings data to investigate relationships between large marine predator occurrence (Bryde’s whales, common and bottlenose dolphins, bronze whalers, pelagic and immature hammerhead sharks) and spatially explicit environmental and biotic variables to predict species richness of large marine predators and investigate their fine-scale spatiotemporal distribution patterns. All models were considered informative (all, AUC > 0.78), and temporally dynamic variables, such as the distribution of prey, were important in predicting the occurrence of the study species and species groups. 

Our approach and data highlight the value of multi-species surveys and the importance of considering temporally variable abiotic and biotic drivers for understanding biodiversity patterns when informing ecosystem-scale conservation planning and dynamic ocean management.

We provide data files of:

  • Locations of species presence / pseudo absence location over time (in .csv format) and associated environmental and biotic variables for Bryde’s whales, common and bottlenose dolphins, bronze whaler, pelagic and immature hammerhead sharks.
  • Monthly estimates of 14 high-resolution spatially explicit environmental and biotic variables (1 km grid resolution): Bathymetry; Slope; Distance from shore; Distance to 40m depth; Sand; Mud; Gravel; Seabed disturbance; Tidal current; Chlorophyll a; Sea surface temp; Distance to plankton; Distance to prey (saved as .R data)
  • Model objects, R code, and model outputs of the Boosted Regression Tree modelling.
  • Predicted monthly distributions (and associated spatially explicit uncertainty) of Bryde’s whales, common dolphins, bottlenose dolphins, bronze whaler sharks, pelagic sharks, immature hammerhead sharks, and richness of large marine predators in the Hauraki Gulf, New Zealand, (January to December). Monthly richness estimates of large marine predators.