Abstract

Abstract Biogenic habitats are foundational habitats for species assemblages and drive a range of ecosystem functions. The Hauraki Gulf/Tiikapa Moana is the most intensively used coastal area in Aotearoa/New Zealand, and decades of commercial fishing, sedimentation and industrialization have degraded biogenic habitats in the Gulf. In response, the marine spatial plan ‘Sea Change’ includes proposals to create new and extend existing marine protected areas (MPAs) and restrict the area open to mobile bottom‐impact fishing methods to conserve and help the recovery of biogenic habitats. To assess the benefits of different spatial planning scenarios for biogenic habitats, information on their spatial distribution is needed, but data limitations are a significant challenge. Here, an approach is detailed that maximized the information extracted from limited species occurrence data, by incorporating expert knowledge to develop and evaluate models of biogenic habitat‐forming taxa. Ensemble habitat suitability models (using boosted regression tree and random forest models) were created for 20 biogenic habitat groups. Using withheld data for validation, area under curve (AUC) scores ranged from 0.58 to 0.95 and true skill statistics (TSS) ranged from 0.37 to 0.84, though three models were further evaluated as insufficient representations of known ecological habitats by expert assessors. Models produced here provide substantially increased information to inform progress on implementation of the Sea Change plan. Two stakeholder processes have been held, resulting in the development of spatial plans for bottom trawl mitigation that are currently under public consultation. Systematic surveys that gather abundance and high‐resolution environmental data should be a priority to improve the utility of predictive models and inform future management processes in the Hauraki Gulf, and funding has been allocated to support additional data collection to determine the effectiveness of spatial management measures in the Hauraki Gulf.

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