Use of SARIMA models to assess data-poor fisheries: a case study with a sciaenid fishery off Portugal

Research on assessment and monitoring methods has primarily focused on fisheries with long multivariate data sets. Less research exists on methods applicable to data-poor fisheries with univariate data sets with a small sample size. In this study, we examine the capabilities of seasonal autoregressive integrated moving average (SARIMA) models to fit, forecast, and monitor the landings of such data-poor fisheries. We use a European fishery on meagre (Sciaenidae: Argyrosomus regius), where only a short time series of landings was available to model (n=60 months), as our case-study. We show that despite the limited sample size, a SARIMA model could be found that adequately fitted and forecasted the time series of meagre landings (12-month forecasts; mean error: 3.5 tons (t); annual absolute percentage error: 15.4%). We derive model-based prediction intervals and show how they can be used to detect problematic situations in the fishery. Our results indicate that over the course of one year the meagre landings remained within the prediction limits of the model and therefore indicated no need for urgent management intervention. We discuss the information that SARIMA model structure conveys on the meagre lifecycle and fishery, the methodological requirements of SARIMA forecasting of data-poor fisheries landings, and the capabilities SARIMA models present within current efforts to monitor the world’s data-poorest resources.

Removing observational noise from fisheries-independent time series data using ARIMA models

Abundance indices derived from fishery-independent surveys typically exhibit much higher interannual variability than is consistent with the within-survey variance or the life history of a species. This extra variability is essentially observation noise (i.e. measurement error); it probably reflects environmentally driven factors that affect catchability over time. Unfortunately, high observation noise reduces the ability to detect important changes in the underlying population abundance. In our study, a noise-reduction technique for uncorrelated observation noise that is based on autoregressive integrated moving average (ARIMA) time series modeling is investigated. The approach is applied to 18 time series of finfish abundance, which were derived from trawl survey data from the U.S. northeast continental shelf. Although the a priori assumption of a random-walk-plus-uncorrelated-noise model generally yielded a smoothed result that is pleasing to the eye, we recommend that the most appropriate ARIMA model be identified for the observed time series if the smoothed time series will be used for further analysis of the population dynamics of a species.

The South China Sea: analyzing fisheries catch data in an ecosystem context

The South China Sea is an important fishing area with an annual harvest of some 5 million tonnes, or 10% of the catches jointly taken by the developing nations of the world. Details are given of a model of the area describing fisheries catches and biological interactions. The area, viewed as a large marine ecosystem, was divided into 10 subsystems; each subsystem was then linked with adjacent subsystems by predatory links, and detritus flows. An analysis was then made of catch statistics for each of the subsystems. It is believed that if all systems could be harvested at around the highest efficiency, an additional 5-6 million tonnes could be taken annually from the South China Sea; however, more refined analyses are needed to further investigate these possibilities. If linked with careful studies of the economic and human aspects of fishing, such analyses will provide guidelines for integrated fisheries management advice.

An approach to the assessment of the finfish fisheries of the Caribbean Community

This paper briefly outlines the implications of making a decision on the most appropriate alternative for carrying out stock assessments and the reasons for previous failures to conserve finfish stocks for sustainable use. The Mathews (1987) approach utilizing Age-Length Catch-Effort Keys (ALCEK) is briefly reviewed, and a suggested overall approach for the assessment of the finfish resources of the Caribbean community is outlined. With recent initiatives towards use of the precautionary approach and reference points, Carribean community countries are advised to revisit the question of the models to be utilized for the assessment of their fish stocks, paying due attention to the quantity, quality and applicability of data now being collected.

Descriptions of the U.S. Gulf of Mexico Reef Fish Bottom Longline and Vertical Line Fisheries Based on Observer Data

In July 2006, a mandatory observer program was implemented to characterize the commercial reef fish fishery operating in the U.S. Gulf of Mexico. The primary gear types assessed included bottom longline and vertical line (bandit and handline). A total of 73,205 fish (183 taxa) were observed in the longline fishery. Most (66%) were red grouper, Epinephelus morio, and yellowedge grouper, E. flavolimbatus. In the vertical line fishery, 89,015 fish (178 taxa) were observed of which most (60%) were red snapper, Lutjanus campechanus, and vermilion snapper, Rhomboplites aurorubens. Based on surface observations of discarded under-sized target and unwanted species, the majority of fish were released alive; minimum assumed mortality was 23% for the vertical line and 24% for the bottom longline fishery. Of the individuals released alive in the longline fishery, 42% had visual signs of barotrauma stress (air bladder expansion/and or eyes protruding). In the vertical line fishery, 35% of the fish were released in a stressed state. Red grouper and red snapper size composition by depth and gear type were determined. Catch-per-unit-effort for dominant species in both fisheries, illustrated spatial differences in distribution between the eastern and western Gulf. Hot Spot Analyses for red grouper and red snapper identified areas with significant clustering of high or low CPUE values.

Measuring Fishing Capacity and Utilization with Commonly Available Data: An Application to Alaska Fisheries

Due to a lack of data on vessel costs, earnings, and input use, many of the capacity assessment models developed in the economics literature cannot be applied in U.S. fisheries. This incongruity between available data and model requirements underscores the need for developing applicable methodologies. This paper presents a means of assessing fishing capacity and utilization (for both vessels and fish stocks) with commonly available data, while avoiding some of the shortcomings associated with competing “frontier” approaches (such as data envelopment analys

Estimating overall fish bycatch in U.S. commercial fisheries

Bycatch, or the unintended capture of fish, marine mammals, sea turtles, and seabirds by fishing gear, occurs to some degree in most fisheries. The recently released National Marine Fisheries Service’s (NMFS) U.S. National Bycatch Report provides information on bycatch in U.S. commercial fisheries by fishery and species. The report also provides national statistics in the form of national bycatch ratio and a national bycatch estimate. We describe the methods used to develop these statistics and compare them to similar studies. We conclude that the national bycatch ratio and national bycatch estimates developed by NMFS represent the best available information on bycatch in U.S. fisheries. However, given changes in bycatch management over time, as well as inter-annual variability in bycatch levels and a high percentage of fisheries for which data on bycatch are not currently available, we recommend that NMFS continue to support bycatch data collection and reporting efforts to improve the quality and quantity of bycatch data and estimates available to fisheries managers and scientists over time. This will enable NMFS to meet its requirements for bycatch reporting under the Magnuson-Stevens Act (MSA), as well as requirements for bycatch minimization under the MSA, Marine Mammal Protection Act, and Endangered Species Act.

Evaluating the quality of bycatch data and bycatch estimates among disparate fisheries

In 2006, the National Marine Fisheries Service, NOAA, initiated development of a national bycatch report that would provide bycatch estimates for U.S. commercial fisheries at the fishery and species levels for fishes, marine mammals, sea turtles, and seabirds. As part of this project, the need to quantify the relative quality of available bycatch data and estimation methods was identified. Working collaboratively with fisheries managers and scientists across the nation, a system of evaluation was developed. Herein we describe the development of this system (the “tier system”), its components, and its application. We also discuss the value of the tier system in allowing fisheries managers to identify research needs and efficiently allocate limited resources toward those areas that will result in the greatest improvement to bycatch data and estimation quality.

Does the California market squid (Loligo opalescens) spawn naturally during the day or at night? A note on the successful use of ROVs to obtain basic fisheries biology data

The California market squid (Loligo opalescens Berry), also known as the opalescent inshore squid (FAO), plays a central role in the nearshore ecological communities of the west coast of the United States (Morejohn et al., 1978; Hixon, 1983) and it is also a prime focus of California fisheries, ranking first in dollar value and tons landed in recent years (Vojkovich, 1998). The life span of this species is only 7−10 months after hatching, as ascertained by aging statoliths (Butler et al., 1999; Jackson, 1994; Jackson and Domier, 2003) and mariculture trials (Yang, et al., 1986). Thus, annual recruitment is required to sustain the population. The spawning season ranges from April to November and spawning peaks from May to June. In some years there can be a smaller second peak in November. In Monterey Bay, the squids are fished directly on the egg beds, and the consequences of this practice for conservation and fisheries management are unknown but of some concern (Hanlon, 1998). Beginning in April 2000, we began a study of the in situ spawning behavior of L. opalescens in the southern Monterey Bay fishing area.

Dynamics of bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna in Hawaii’s pelagic fisheries: analysis of tagging data with a bulk transfer model incorporating size-specific attrition

Tag release and recapture data of bigeye (Thunnus obesus) and yellowfin tuna (T. albacares) from the Hawaii Tuna Tagging Project (HTTP) were analyzed with a bulk transfer model incorporating size-specific attrition to infer population dynamics and transfer rates between various fishery components. For both species, the transfer rate estimates from the offshore handline fishery areas to the longline fishery area were higher than the estimates of transfer from those same areas into the inshore fishery areas. Natural and fishing mortality rates were estimated over three size classes: yellowfin 20–45, 46–55, and ≥56 cm and bigeye 29–55, 56–70, and ≥71 cm. For both species, the estimates of natural mortality were highest in the smallest size class. For bigeye tuna, the estimates decreased with increasing size and for yellowfin tuna there was a slight increase in the largest size class. In the Cross Seamount fishery, the fishing mortality rate of bigeye tuna was similar for all three size classes and represented roughly 12% of the gross attrition rate (includes fishing and natural mortality and emigration rates). For yellowfin tuna, fishing mortality ranged between 7% and 30%, the highest being in the medium size class. For both species, the overall attrition rate from the entire fishery area was nearly the same. However, in the specific case of the Cross Seamount fishery, the attrition rate for yellowfin tuna was roughly twice that for bigeye. This result indicates that bigeye tuna are more resident at the Seamount than yellowfin tuna, and larger bigeye tunas tend to reside longer than smaller individuals. This may result in larger fish being more vulnerable to capture in the Seamount fishery. The relatively low level of exchange between the Sea-mount and the inshore and longline fisheries suggests that the fishing activity at the Seamount need not be of great management concern for either species. However, given that the current exploitation rates are considered moderate (10–30%), and that Seamount aggregations of yellowfin and bigeye tuna are highly vulnerable to low-cost gear types, it is recommended that further increases in fishing effort for these species be monitored at Cross Seamount.

Estimation of bycatch in shrimp trawl fisheries: a comparison of estimation methods using field data and simulated data

Bycatch, or the incidental catch of nontarget organisms during fi shing operations, is a major issue in U.S. shrimp trawl fisheries. Because bycatch is typically discarded at sea, total bycatch is usually estimated by extrapolating from an observed bycatch sample to the entire fleet with either mean-per-unit or ratio estimators. Using both field observations of commercial shrimp trawlers and computer simulations, I compared five methods for generating bycatch estimates that were used in past studies, a mean-per-unit estimator and four forms of the ratio estimator, respectively: 1) the mean fish catch per unit of effort, where unit effort was a proxy for sample size, 2) the mean of the individual fish to shrimp ratios, 3) the ratio of mean fish catch to mean shrimp catch, 4) the mean of the ratios of fish catch per time fished (a variable measure of effort), and 5) the ratio of mean fish catch per mean time fished. For field data, different methods used to estimate bycatch of Atlantic croaker, spot, and weakfish yielded extremely different results, with no discernible pattern in the estimates by method, geographic region, or species. Simulated fishing fleets were used to compare bycatch estimated by the fi ve methods with “actual” (simulated) bycatch. Simulations were conducted by using both normal and delta lognormal distributions of fish and shrimp and employed a range of values for several parameters, including mean catches of fish and shrimp, variability in the catches of fish and shrimp, variability in fishing effort, number of observations, and correlations between fish and shrimp catches. Results indicated that only the mean per unit estimators provided statistically unbiased estimates, while all other methods overestimated bycatch. The mean of the individual fish to shrimp ratios, the method used in the South Atlantic Bight before the 1990s, gave the most biased estimates. Because of the statistically significant two- and 3-way interactions among parameters, it is unlikely that estimates generated by one method can be converted or corrected to estimates made by another method: therefore bycatch estimates obtained with different methods should not be compared directly.