This report provides a comprehensive overview of biological inputs for assessment of the risk of New Zealand commercial fisheries to New Zealand seabird populations and was generated as part of Fisheries New Zealand project PRO2019-10. The biological inputs were reviewed and updated where necessary, focusing on high-risk or highly abundant species, and restructured for the updated model formulation. The risk assessment model is described in an accompanying AEBR.

This project developed an operating stock assessment model and tested management procedures for pāua quota management area (QMA) PAU 4. Spatial length-based models were conditioned on assumed catch time series, producing stock trajectories and assumed status. Application of control rules led to variable outcomes at the statistical-area scale, but averaged out at a larger scale; trends were stable at the QMA-scale, with a low risk of further declines under trialled harvest control rules.

As part of the development of spatially explicit fisheries risk assessment methodologies for chondrichthyans, spatial distribution modelling methodologies were tested on carpet shark, school shark, great white shark, and green turtle as well as on one simulated dataset. Eight recommendations were made for future distribution models including the need to model a year x space interaction as well as both the probability of presence and catch rate, and the usefulness of simulations.

The spatially explicit fisheries risk assessment (SEFRA) of Hector’s and Māui dolphins was updated and outputs were reported for Hector’s dolphins in three local-scale areas: the north coast of the South Island, the Kaikōura coast, and the south coast of the South Island. This analysis included a substantial revision of the model used to estimate the spatial distribution of the dolphins, as well as an update of the fisheries data required by the SEFRA model.

The study summarised diets of top predators in New Zealand waters and estimated the spatial-temporal distribution of many of their prey species caught in inshore fisheries. These were consistent with previous estimates and with existing information and could be used as inputs in other processes such as spatial risk assessment models. Care should be taken for species such as squid or hoki where only the shallow part of their range was included and species groups such as jack mackerel or rattail.

Video observation was continued in the 2019 and 2020 fishing years to improve observer coverage of the FMA 1 bottom longline fishery. Footage collection in 2020 was impacted by several operational issues related to new EM systems. Multiple reviews identified that many seabird captures were missed during the first review of the footage. Nevertheless, video observation was effective in increasing observation of the fishery, with 65 seabird captures recorded by video monitoring in 2020.

This project developed a food-web model to explore the potential ecosystem effects of changes to small and medium-sized pelagic fish (including jack mackerels, anchovy, pilchards, sprat, yelloweye mullet, blue mackerel, yellow-tailed scad/kōheru) in the Hauraki Gulf. We found that the response of the ecosystem to changes in the abundances of pelagic fishes depended strongly on the extent to which top predators (seabirds, whales/dolphins, fish) are flexible in their diets.

This project estimated the at-sea distribution within the New Zealand EEZ of 11 seabird taxa considered to be most at risk from captures by New Zealand commercial fishing. Predictive habitat models fitted to spatial information were used to predict at-sea distribution of each taxon for each month. Seabird tracking data were used to derive monthly proportions of birds within the EEZ, which were nearly always lower than those assumed by the most recent multispecies seabird spatial risk assessment.

This project, funded by the Ministry for Primary Industries (MPI), sought to help New Zealand Plant Producers Incorporated (NZPPI) develop a structured approach for optimising use of fungicides against myrtle rust in nurseries.

Variables that could potentially influence non-protected species bycatch in surface longlining were assessed. For example, seabird captures were influenced by variables such as moon phase and start month, as well as fishing behaviour-related variables, such as whether the tori line was over the bait entry point. A main conclusion from a post-hoc workshop was that a set of mandatory variables is required to reduce data scarcity limiting the assessment of mitigation measures.

Design Report for Napier Port and Ahuriri Inner Harbour

BiosecurityNew Zealand TechnicalPaperNo: 20212/10