Historically, basking sharks have been widely reported throughout New Zealand waters. While previously observed in large numbers, only a few individuals are now reported annually, primarily as fisheries bycatch, potentially indicative of a recent reduction in basking shark abundance in New Zealand waters. It is unclear what caused changes in observations of New Zealand basking shark abundance, but overseas, observations are known to be highly variable across years, and their distribution and occurrence in the Northern Hemisphere have been shown to be influenced by environmental predictors such as thermal fronts, chlorophyll a (chl-a) concentration, and the abundance of prey (zooplankton). Habitat suitability models (HSMs) are capable of filling in knowledge gaps on spatial and temporal distributions and predict areas of suitable habitat for widely distributed species. Here, basking shark habitat suitability (HSI) around New Zealand was predicted by combining functionally relevant, high‐resolution (1km2 grid resolution) environmental and biotic (zooplankton prey species) data and opportunistic basking shark occurrence data (n = 369).
The relationship between environment variables, biotic variables and basking shark records was explored using ensemble predictions (Ensemble HSM) from Boosted Regression Tree (BRT) and Random Forest (RF) models. BRT and RF models were bootstrapped 200 times and an ensemble model was produced by taking weighted averages of the predictions from each model type. BRT and RF models performed well for predicting basking shark occurrence (AUC and TSS > 0.7). Nine variables were retained for the model, eight environmental predictors (Bathy, BPI broad, Chl-a, MLD, Turbidity, POCFlux, Slope, and SST) and one biotic predictor (Copepoda). The relative importance of each predictor and their influence on basking shark HSI were consistent across BRT and RF models. Vertical flux (POCFlux, 26.0%), slope (Slope, 14.1%), and turbidity (Turbidity, 10.6%) were the three most important variables in predicting basking shark HSI. Bathymetry (Bathy, 9.7%) and broadscale bathymetric position index (BPI broad, 9.6%) were also moderately important variables. High HSI was predicted in gently sloping and less complex seafloor topographies with high turbidity and at two depths - very close to shore and at depths between 200 and 550 m. There was a weak relationship between HSI and copepod densities, with low HSI occurring with low levels of copepod densities, a peak in HSI at moderate copepod densities (10-20 counts per 5 nautical miles), and a plateau in HSI values at the highest levels of copepod densities (>25 counts per 5 nautical miles).
Areas of high habitat suitability exhibited a core area for basking shark in the New Zealand Exclusive Economic Zone (EEZ) occurred along the continental slope, particularly along the 250 m contour along the North and South Islands; Mernoo Bank, Pukaki Rise, Puysegur, and around New Zealand’s offshore islands (Chatham Islands, Stewart Island, the Bounty Islands, and the Auckland Islands). Areas of high uncertainty (SD > 0.2) included most offshore waters north of 40°S, the deeper depths (>500 m) of the Hokitika Canyon, northern Chatham Rise, coastal waters off the East Coast South Island (Canterbury Bight), Foveaux Strait (between the South Island and Stewart Island) and Puysegur. High uncertainty beyond the core area was reported along deep sea features north of New Zealand, including the Kermadec Ridge and Trench, the Colville Ridge, the Norfolk Ridge, and the Lord Howe Rise.
Finucci, B., Stephenson, F., Petersen, G., Francis, M. and Pinkerton, M. 2020. Exploring the drivers of spatial distributions of basking sharks in New Zealand waters. POP2020-03 final report for the Conservation Services Programme, Department of Conservation. Prepared by the National Institute of Water and Atmospheric Research (NIWA), 50 p.