DNA metabarcoding is a powerful new tool allowing characterization of species assemblages using high‐throughput amplicon sequencing. The utility of DNA metabarcoding for quantifying relative species ...abundances is currently limited by both biological and technical biases which influence sequence read counts. We tested the idea of sequencing 50/50 mixtures of target species and a control species in order to generate relative correction factors (RCFs) that account for multiple sources of bias and are applicable to field studies. RCFs will be most effective if they are not affected by input mass ratio or co‐occurring species. In a model experiment involving three target fish species and a fixed control, we found RCFs did vary with input ratio but in a consistent fashion, and that 50/50 RCFs applied to DNA sequence counts from various mixtures of the target species still greatly improved relative abundance estimates (e.g. average per species error of 19 ± 8% for uncorrected vs. 3 ± 1% for corrected estimates). To demonstrate the use of correction factors in a field setting, we calculated 50/50 RCFs for 18 harbour seal (Phoca vitulina) prey species (RCFs ranging from 0.68 to 3.68). Applying these corrections to field‐collected seal scats affected species percentages from individual samples (Δ 6.7 ± 6.6%) more than population‐level species estimates (Δ 1.7 ± 1.2%). Our results indicate that the 50/50 RCF approach is an effective tool for evaluating and correcting biases in DNA metabarcoding studies. The decision to apply correction factors will be influenced by the feasibility of creating tissue mixtures for the target species, and the level of accuracy needed to meet research objectives.
The production of marine protein from fishing and aquaculture is influenced by environmental conditions. Ocean temperature, for example, can change the growth rate of cultured animals, or the ...distribution of wild stocks. In turn these impacts may require changes in fishing or farming practices. In addition to short‐term environmental fluctuations, long‐term climate‐related trends are also resulting in new conditions, necessitating adjustment in fishing, farming and management approaches. Longer‐term climate forecasts, however, are seen as less relevant by many in the seafood sector owing to more immediate concerns. Seasonal forecasts provide insight into upcoming environmental conditions, and thus allow improved decision making. Forecasts based on dynamic ocean models are now possible and offer improved performance relative to statistical forecasts, particularly given baseline shifts in the environment as a result of climate change. Seasonal forecasting is being used in marine farming and fishing operations in Australia, including wild tuna and farmed salmon and prawns, to reduce uncertainty and manage business risks. Forecast variables include water temperature, rainfall and air temperature, and are considered useful up to approximately 4 months into the future, depending on the region and season of interest. Species‐specific habitat forecasts can also be made by combining these environment forecasts with biological habitat preference data. Seasonal forecasts are useful when a range of options are available for implementation in response to the forecasts. The use of seasonal forecasts in supporting effective marine management may also represent a useful stepping stone to improved decision making and industry resilience at longer timescales.
Advances in DNA sequencing technology have revolutionized the field of molecular analysis of trophic interactions, and it is now possible to recover counts of food DNA sequences from a wide range of ...dietary samples. But what do these counts mean? To obtain an accurate estimate of a consumer's diet should we work strictly with data sets summarizing frequency of occurrence of different food taxa, or is it possible to use relative number of sequences? Both approaches are applied to obtain semi‐quantitative diet summaries, but occurrence data are often promoted as a more conservative and reliable option due to taxa‐specific biases in recovery of sequences. We explore representative dietary metabarcoding data sets and point out that diet summaries based on occurrence data often overestimate the importance of food consumed in small quantities (potentially including low‐level contaminants) and are sensitive to the count threshold used to define an occurrence. Our simulations indicate that using relative read abundance (RRA) information often provides a more accurate view of population‐level diet even with moderate recovery biases incorporated; however, RRA summaries are sensitive to recovery biases impacting common diet taxa. Both approaches are more accurate when the mean number of food taxa in samples is small. The ideas presented here highlight the need to consider all sources of bias and to justify the methods used to interpret count data in dietary metabarcoding studies. We encourage researchers to continue addressing methodological challenges and acknowledge unanswered questions to help spur future investigations in this rapidly developing area of research.
Southern bluefin tuna (SBT) is a valuable species that has been subject to high exploitation rates since the 1950s. In 2011, the spawning stock biomass was estimated to be at a historically low ...level, at only 5% of pre-fished biomass. A key component for managing and rebuilding the stock is having reliable, fishery-independent estimates of juvenile abundance. This paper describes how such estimates have been constructed from aerial surveys of juvenile (age 2-4) SBT conducted annually in the Great Australian Bight from 1993-2000 and 2005-2009. During these surveys, observers flew along pre-set transect lines searching for surface schools of SBT. Data were collected on the location and biomass of SBT sightings, and on the environmental conditions present during the survey. Sea surface temperature (SST) was found to correlate with the size (biomass) of schools, and several environmental variables, SST and wind speed in particular, were found to correlate with the number of sightings (presumably by affecting the ability of observers to see surface schools as well as whether fish were present at the surface). In addition, observers changed over time and differed in their aptitude for spotting tuna. Thus, generalized linear mixed models (GLMMs) were used to standardize the sightings and biomass data to a common set of observers and environmental conditions in order to produce an annual time series of relative abundance estimates. These estimates, which form one of two key inputs to the management procedure used by the international Commission for the Conservation of Southern Bluefin Tuna to set the global catch quota, suggest juvenile abundance was highest in the first years of the survey (1993-1996), after which it declined and fluctuated around a level about four times lower.
Tag-recapture data have long been important data sources for fisheries management, with the capacity to inform abundance, mortality, growth and movement within stock assessments. Historically, this ...role has been fulfilled with low-tech conventional tags, but the relatively recent and rapid development of electronic tags has dramatically increased the potential to collect more high quality data. Stock assessment models have also been evolving in power and complexity recently, with the ability to integrate multiple data sources into unified spatially explicit frameworks. However, electronic tag technologies and stock assessment models have developed largely independently, and frameworks for incorporating these valuable data in contemporary stock assessments are nascent, at best. Movement dynamics of large pelagic species have been problematic to resolve in modern assessments, and electronic tags offer new opportunities to resolve some of these issues. Pragmatic ways of modeling movement are often not obvious, and basic research into discrete and continuous processes, for example, is ongoing. Experimental design of electronic tagging research has been driven mostly by ecological and biological questions, rather than optimized for stock assessment, and this is probably a complicating factor in integration of the data into assessment models. A holistic overview of the current state of assessment models, electronic tag technologies, and experimental design is provided here, with the aim to provide insight into how stock assessment and electronic tagging research can be conducted most effectively together.
Length and age at maturity are important life history parameters for estimating spawning stock biomass and reproductive potential of fish stocks. Bias in estimates of size and age at maturity can ...arise when disparate distributions of mature and immature fish within a population are not accounted for in the analysis. Here we investigate the spatial and temporal variability in observed size and age at maturity of female albacore tuna, Thunnus alalunga, using samples collected across the South Pacific. Maturity status was identified using consistent histological criteria that were precise enough to allow for mature but regenerating females to be distinguished from immature females during the non-spawning season, permitting year-round sampling for maturity estimation in albacore. Using generalised linear mixed models, we found that the proportion of mature females at length varied significantly with latitude and time of year. Specifically, females at northern latitudes (∼10-20°S, where spawning occurs) were mature at significantly smaller lengths and ages than females at southern latitudes (∼20-40°S), particularly during the spawning season (October-March). This variation was due to different geographic distributions of mature and immature fish during the year. We present a method for estimating an unbiased maturity ogive that takes into account the latitudinal variation in proportion mature at length during a given season (spawning or non-spawning). Applying this method to albacore samples from the western region of the South Pacific gave a predicted length at 50% mature of ∼87 cm fork length (4.5 years).
Commercial fishing involves locating fish in a variable environment, and a fisher's historical experience with environmental conditions and the influence on fish distribution underpins their economic ...efficiency. However, in many regions, changing environments are reducing the utility of this experience. In the Great Australian Bight, recent environmental changes have modified the summer distribution of southern bluefin tuna (SBT, Thunnus maccoyii). This has affected the timing and location of fishing activity and contributed to economic impacts, at the same time as international competition is lowering value of the catch. The SBT purse-seine fishery is managed under a strict quota, so catching more fish is not an option to reduce fixed costs; instead fish must be caught more efficiently in a changing environment. Following discussion with industry stakeholders, we developed a seasonal forecast system based on a three stage process. We first assessed needs through discussions with industry. We then developed a SBT habitat forecast system based on a seasonal environmental forecasting model (POAMA: the Predictive Ocean Atmosphere Model for Australia) coupled with a habitat preference model for SBT (developed using data from tagged fish). Based on a historical evaluation of the environmental forecasting model and the habitat model, we expect temperature-based habitat forecasts to have useful skill up to two months into the future during the months of interest. The final stage involved forecast delivery via an industry-specific website and engagement with stakeholders, which led to improved presentation and contextualization of the forecasts. The forecasts, which are updated daily, are now being used by SBT fishers and have proven a useful aid in their decision-making.
Tag–recapture data contain valuable information about individual fish growth, which can enhance the estimation of growth parameters. Tag–recapture data are especially useful when age-determination ...uncertainties throw age-based growth estimates and stock assessments into question, as is the present situation with several important gadoid stocks. Length-based (GROTAG method) and age-based (LEP method) growth functions were fit to a large data set of tagged and recaptured cod (Gadus morhua) from an artificial reef in the western Baltic Sea to calculate improved growth parameter estimates. The LEP method allowed integration of different data formats, including tag–recapture, length frequency, and length-at-age, to estimate a more robust and comprehensive growth function (von Bertalanffy growth parameters: L
∞
= 154.56 cm, k = 0.11, t
0
= –0.13). Two heavily exploited cod stocks inhabit the Baltic Sea, subsisting at the upper thermal and lower salinity limits of the species. Otolith shape analyses indicated that, unexpectedly, individuals from both populations were resident at the reef. Compared with cod populations elsewhere, cod in the western Baltic Sea grow relatively slowly and with weak seasonal fluctuations in growth rates, potentially due to adverse conditions for growth.
A changing climate, in particular a warming ocean, is likely to impact marine industries in a variety of ways. For example, aquaculture businesses may not be able to maintain production in their ...current location into the future, or area-restricted fisheries may need to follow the fish as they change distribution. Preparation for these potential climate impacts can be improved with information about the future. Such information can support a risk-based management strategy for industries exposed to both short-term environmental variability and long-term change. In southern Australia, adverse climate impacts on valuable seafood industries have occurred, and they are now seeking advice about future environmental conditions. We introduce a decision tree to explain the potential use of long-term climate projections and seasonal forecasts by these industries. Climate projections provide insight into the likely time in the future when current locations will no longer be suitable for growing or catching particular species. Until this time, seasonal forecasting is beneficial in helping industries plan ahead to reduce impacts in poor years and maximise opportunities in good years. Use of seasonal forecasting can extend the period of time in which industries can cope in a location as environmental suitability declines due to climate change. While a range of short-term forecasting approaches exist, including persistence and climatological forecasts, only dynamic model forecasts provide a viable option for managing environmental risk for marine industries in regions where climate change is reducing environmental suitability and creating novel conditions.
Abstract Age-reading protocols for tuna species using annual growth zones in thin-cut transverse otolith sections have produced greater age estimates than previous methods. Lifespan estimates for ...yellowfin (YFT) and bigeye (BET) tuna (Thunnus albacares and T. obesus) were validated up to 16–18 years in the western North Atlantic Ocean using bomb 14C dating and the current study extends the approach to YFT and BET of the western and central Pacific Ocean (WCPO). Archived otoliths from young-of-the-year (YOY) tuna caught in the WCPO were analysed for 14C to establish a reference chronology covering 30 years (1989–2019). This YOY 14C time series exhibited strong concordance with existing coral-otolith 14C references for the tropical-subtropical Pacific Ocean and was combined as a single chronology. Otolith cores from YFT aged 1–14 years and BET aged 1–13 years from presumed annual counts were analysed for 14C. These measurements aligned with the reference chronology for the calculated hatch years for both species. These findings provide strong evidence that growth zones in thin-sectioned otoliths are deposited annually for YFT and BET of the WCPO and that age interpretation is correct using the current age reading protocol with little to no bias.
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