This report presents an assessment of the orange roughy stock off the west coast of the South Island (ORH 7B) in 2020. There was a fishery from 1985 to 1992, with the TACC peaking at 1708 t between 1989 and 1995, and the fishery was closed from October 2007. The assessment used two acoustic biomass estimates (2017, 2019) and a 2019 age frequency, completely rejecting the assumptions used in previous assessments that CPUE was directly proportional to biomass and that recruitment followed the assumed recruitment curve. This assessment is considered preliminary as work was stopped due to the conclusion that the acoustic surveys had probably missed a substantial proportion of the spawning biomass.

This report provides a 2020 update of 2014 and 2017 assessments of the East and South Chatham Rise orange roughy stock, to enable an HCR-derived recommended catch limit for 2020–21. Three age-structured Bayesian population models were fitted to biomass and composition data. Virgin biomass (B0) was estimated as 300 000–350 000 t and 2020 stock status from the base case model was 36% B0 (± 95% CIs of 30 to 41%). With a vulnerable biomass of 157 000 t, the HCR-derived recommended catch limit was 6348 t for 2020–21, with a slowing increasing population over future years.

This report summarises commercial catch and effort statistics for rock lobsters, which are also known in New Zealand as “crayfish” or “kōura”.

The summaries presented in this document cover the rock lobster legal fishing years (1 April–31 March) for April 1979 to March 2023.

There are nine Quota Management Areas (QMAs) that cover all inshore waters of the North Island, the South Island, and the Chatham Islands. There are 43 smaller statistical areas that lie within these nine QMAs. The summaries are ordered by QMA, with each QMA identified by a three-letter code and a number. The rock lobster code is CRA, so the nine QMAs are labelled CRA 1 to CRA 9.

The first three tables for each CRA QMA summarise, by statistical area and fishing year, (1) number of vessels, (2) catch, and (3) effort. The last category is defined as the total number of rock lobster pots lifted within each fishing year and statistical area. The fourth table summarises catch by month and fishing year for the entire QMA, and a fifth table gives the monthly catch by statistical area for just the final fishing year, which is 2022–23 in this document.

The sixth table for each QMA summarises catch-per-unit-effort (CPUE) by statistical area and fishing year. CPUE in this table is defined as the catch (in kilograms) from the second table divided by the number of potlifts in the third table. There is a seventh table providing CPUE that has gone through a mathematical procedure called “standardisation” which attempts to factor out aspects of the CPUE which might change over time. The standardisation procedure has been suspended beginning with 2019–20 because there are comparability issues associated with the changeover from paper forms to electronic reporting.

Within the dairy sector, several databases exist that have recorded farms, animals, and milk production over time, as well as feed use both through time and seasonally. This report assesses the feasibility of combining these databases to provide monthly estimates of feeds (grown on farm and imported) eaten by dairy cows from 1990 to 2020 for different types of farm systems and regions of New Zealand.

The purpose of this project was to evaluate the potential number of livestock carried on lifestyle blocks and blocks of land not included in the sampling frame of the Agricultural Production Survey (APS) and to evaluate the potential impacts on these stocks on agricultural greenhouse gas emissions.

This study estimated the post-release survival of inshore finfish with current commercial minimum legal sizes—blue cod, blue moki, butterfish, kingfish, red moki, red cod, sand flounder, snapper, tarakihi, trevally, and yellowbelly flounder—and those currently allowed to be returned under disposal code X— kingfish, rig, sand flounder, school shark, rough skate, smooth skate, and spiny dogfish.

A questionnaire was developed and circulated to fishers, fishery observers, and scientists with knowledge of each species to obtain their estimates of at-release survival (i.e., the probability the fish/shark was alive when put back into water) and post-release survival (the probability an individual was both alive at release and survived following release). Estimates were obtained for each gear type as well as fishing categories within each gear type, e.g., duration, depth, and bag size. For some species, estimates of post- release survival were informed by literature on the survival of same or similar species.

These data were used with fishery characterisations to model the survival for each species. For species with a minimum legal size, both at-release and post-release survival estimates were used, whereas for those species released under disposal code X, which may only be released if alive and likely to survive, only the post-release survival estimates were used.

The post-release survival from longlines for snapper, kingfish, and rough skate (assuming they are released alive) was “medium-high”, i.e., the lower bootstrapped 90% confidence range was lower than 0.50, but greater than 0.25, and upper 90% confidence range exceeded 0.75. The same survival range was estimated for snapper caught in pots. For snapper, this result was based on expert knowledge and incorporated literature-based mean values based on empirical studies for this species in New Zealand.

However, for rough skate, the result was based on the informed opinion of 2 science experts only (at-vessel survival was assumed to be 100%) and without the benefit of literature-based empirical estimates as none exist for this species. If at-release survival estimates are included for kingfish, the range decreases to “medium”. For blue cod, and other sharks, skates, and rays, survival from capture on bottom longline was “medium-low”. Red cod survival was “low”, and an “uncertain” outcome was applied to smooth skate and blue moki due to the lack of available knowledge. For species such as spiny dogfish and school shark, the lower range of perceived survival was at least partially a result of the wide range of depths where these species are discarded, which includes deepwater fisheries with larger vessels and potentially different handling practices.

Post-release survival of most species from trawl gear was perceived to be “medium-low” at best, with 90% confidence range either spanning 0.25 up to but less than 0.75, or else between 0.25 and 0.5. Blue cod, red cod, flatfish, and tarakihi were considered in the “low” range, where the 90% confidence range did not exceed 0.25. Survival of both rough and smooth skates in trawl gear was “uncertain”, based on the lack of empirical data for these species and the wide range of estimates for related species in overseas fisheries. Where bottom trawl with a Modular Harvest System cod-end was considered as a separate gear, the lack of available data on this gear type meant survival was considered “uncertain”. For set net, the perceived survival of all species where this gear was considered an important method, was “medium-low”.

The species-method survival confidence ranges presented in this report are based on the best currently available expert knowledge and thorough reviews of the current survival literature; as such, these ranges are unlikely to be improved upon without further investment in release survival research.

Jack mackerels (JMA) support significant commercial fisheries in New Zealand, with over 75% of the total jack mackerel catch taken by trawl fisheries off the west coasts of the North Island and South Island, in JMA 7. Three jack mackerel species are found in New Zealand waters, namely Trachurus declivis, T. murphyi, and T. novaezelandiae.

New Zealand commercial catches of jack mackerels have been recorded under the general code JMA. Therefore species-specific catch information is not available from the fishery data. Estimates of proportions of the three Trachurus species in the catch, based on observer data which includes separate codes for each species, are essential for assessment of the individual stocks.

This report updates the data collected by the New Zealand observer sampling programme from trawl landings of jack mackerels in JMA 7 with the data collected during the 2021–22 fishing year, including estimates of species proportions and sex ratios in the landings, catch-at-length (fork length, cm), and catch-at-age for these species.

Estimated proportions of catch by species based on observer data have historically shown that T. declivis comprises 61–73% of the catch for all statistical areas, followed by T. novaezelandiae at 21–33%, and T. murphyi at 2–8%. In 2021–22, proportions of T. declivis, T. novaezelandiae, and T. murphyi were 77%, 23%, and less than 1%, respectively.

Sampled sex ratios of T. declivis and T. novaezelandiae were close to a sex ratio of 1:1 in the 2021–22 fishing year, and sex ratios for T. murphyi were biased towards females (56%) in 2021–22.

Trachurus declivis and T. novaezelandiae fish in the observer data indicated decreasing proportions of larger and older fish in the commercial catch in recent years, whereas the length and age data for T. murphyi indicated the catch mainly comprised large, older fish, with little evidence of younger fish coming through.

This project estimated survival of six pelagic species (southern bluefin tuna, Pacific bluefin tuna, swordfish, blue shark, mako shark, and porbeagle shark) following release from commercial fishing gear to inform a government review of their landing exceptions.

Fishery characterisations revealed that the main fishing gears responsible for discarded fish were surface longline (all species) and trawl (swordfish, mako, and porbeagle).

Literature reviews were conducted to document current knowledge on the status of an individual when brought to the vessel and ‘post-release’ survival (i.e., survival in the weeks to months following release) from these methods, as well as the factors that affect survival of each species. The key results were:

Bluefin tunas (including southern bluefin tuna and Pacific bluefin tuna) and swordfish typically have high post-release survival following capture by surface longline, with most studies reporting survival rates of 88% or greater for bluefin tunas and 50–88% for swordfish.
Blue shark have high at-vessel and post-release survival following capture by surface longline, with most studies reporting at-vessel and post-release survival rates of > 80%.

Mako have moderate to high at-vessel and post-release survival following capture by surface longline, with most studies reporting at-vessel and post-release survival rates ranging from about 50–87% and 56–94%, respectively.
Porbeagle have moderate to high at-vessel survival and variable post-release survival following capture by surface longline, with estimates of 56–79% and 25–90% for at-vessel and post-release survival, respectively.
There have been no comparable studies documenting at-vessel or post-release survival of swordfish, mako, or porbeagle from trawl.

A questionnaire was developed and circulated to fishers, fishery observers, and scientists with knowledge of each species to obtain their estimates of at-release survival (i.e., the probability the fish/shark was alive when put back into water), post-release survival, and combined survival (the probability an individual was both alive at release and survived following release) of the three shark species, and post-release survival of the thee fish species (in accordance with their current landing exceptions).

Questionnaire responses were used to derive survival probability range estimates for each species, with separate analyses conducted that included and excluded information from the literature.

For individuals released after capture by surface longline, the results of this analysis indicated post-release survival for southern bluefin tuna, Pacific bluefin tuna, and swordfish is likely to be high; blue shark are likely to have high at-release and post-release survival, and a medium-high combined survival; mako are likely to have medium at-release and medium-high post-release survival (reduced to medium if excluding information from the literature in the analysis), and low-medium combined survival; and porbeagle are likely to have low at-release survival, low-medium post-release survival, and low combined survival.

Post-release survival of swordfish released from trawl gear was likely to be low, and mako and porbeagle caught by trawl were likely to have low at-release, post-release, and combined survival.

These results, however, resulted from a small number of survey responses (only one respondent for trawl gear) and often without any comparable supporting published studies.

Survival estimates presented here should thus be interpreted with caution.

Same as you do with your family’s Emergency Survival Kit, think first about the basics for your livestock and horses – food, water and warmth.

Photo surveys are used to estimate abundance of scampi in New Zealand and provide important information for stock assessments.

Readers identify features in the survey photos as burrows or scampi. A statistical model is applied to produce an estimate of abundance for each survey. The statistical model takes into account differences between readers’ interpretation of features (what looks like a burrow to one reader may not to another) and differences in interpreting features over time (e.g., a reader may become more skilled at interpreting features over time, or technology could improve).

This report provides a review of the statistical model applied to produce an estimate of abundance from scampi photo surveys. The review found no concerns with the model or how it is being applied. Two readers re-read images from recent survey years to test if the adjustment over time has been appropriate. The results of the re-reads supported the model results.

Further work is suggested, including contracting a specialist statistician to provide greater theoretical understanding of the model and assumptions.