This study used a model of individual eco-physiological response to environmental and climate factors to derive population level outcomes of fish stocks. These simulations were used to investigate how fisheries stock assessments are influenced by climate and bottom-up variability in production parameters. The assessments generally provided unbiased estimates of stock status even though there were annual and decadal fluctuations in all production-related parameters.

The Foveaux Strait oyster (OYU 5) stock assessment model was reviewed. Development of a disease sub-model to provide projections of future disease mortality will greatly improve assessments. B0 and stock reference points may be overestimated. Conceptual models of climatic, environmental, habitat, disease, and biological drivers of oyster production highlight several knowledge gaps. An understanding of disease processes and new time series data will underpin better stock projections.

This report investigated the spatial and temporal structure of arrow squid (Nototodarus sloanii and N. gouldi) in New Zealand. Five potential stocks were defined. Estimates of growth rate were consistent with previous estimates. Spatial-temporal standardised CPUE fortnightly indices were developed and could be predicted relatively well by environmental variables. Preliminary population models showed recruitment was well estimated but initial biomass was highly uncertain.

While effects of organic enrichment on inshore, soft-sediment communities are well studied, little is known about how finfish farm-derived impacts will manifest in open ocean environments. This report identifies key species that may be affected by open ocean aquaculture and describes physiological indicators that may provide insight into organism health. This is the first of several project objectives that work toward developing environmental health measures for use in offshore environments.

We examined the influence of water quality at the time of juvenile settlement on subsequent adult flatfish abundance as indexed by commercial catches in the Manukau and Kaipara harbours. Generalised linear models including time-lagged water quality variables indicated an overall negative association between water clarity and flatfish catch, and overall positive association between total phosphorus and flatfish catch in both harbours, suggesting these variables may affect flatfish recruitment.

This project sought to understand and model the effects of environmental variability on the function of the marine ecosystems of the Subantarctic region of New Zealand and adjacent waters, focusing on key megafauna and fished species using this region. We found evidence for long-term changes in atmospheric/oceanic climate, with differential effects on productivity comparing regions, and with associated effects on the productivity and distribution of some of the study species.

This is a guidance document to inform the development and implementation of benthic monitoring of salmon farms in the Marlborough Sounds, New Zealand. It was first published in 2015, revised in 2019, and further revised in this version after an out-of-cycle review in 2022. It aims to provide consistent and clear requirements for the benthic monitoring and management of existing farms, based around an agreed set of environmental quality standards with accompanying rationale.

Spatial analyses are increasingly being undertaken on fishery and fishery related data in the New Zealand region. This paper proposes a standard CRS and a common origin for grids to enable data from any analyses to be overlaid, combined, and reused while minimising resampling requirements and reprojection/overlay artefacts.

To develop an assessment approach using spatially explicit catch, abundance, and harvest rate estimates for inshore finfish stocks, spatial patterns of relative density were estimated fitting research vessel survey data to environmental covariates using Generalised Additive Models for nine species. The density estimates were converted to absolute abundance using estimates of research survey catching efficiency. In addition, the eSAFE method used the relative density estimates directly.