Defining value per unit effort in mixed métier fisheries

Fisheries Research, 2004

A generalized linear mixed model (GLMM) that treats year and spatial cell as fixed effects while treating vessel as a random effect is used to examine fishing power among chartered industry-based vessels and a research trawler, the FRV Miller Freeman, for bottom trawl surveys on the upper continental slope of U.S. West coast. A Bernoulli distribution is used to model the probability of a non-zero haul and the gamma distribution to model the non-zero catch rates of four groundfish species. The use of vessel as a random effect allows the data for the various vessels to be combined and a single continuous time-series of biomass indices to be developed for stock assessment purposes. The GLMMs fit the data reasonably well. Among the different models examined, the GLMM incorporating a random vessel × year effect had the smallest AIC and was thus chosen as the best model. Also, estimated random effects coefficients associated with the industry-based vessels and the FRV Miller Freeman for each year suggests that these vessels can be assumed to be from a common random effects distribution. These results suggest that combining data from the chartered industry-based vessels and from the research trawler may be appropriate to develop indices of abundance for stock assessment purposes. Finally, an evaluation of variances associated with abundance indices from the different models indicate that analyzing these data as a fixed effect GLM may underestimate the level of variability due to ignoring the grouped nature of tows within vessels. As such, use of a mixed model approach with vessel as a random effect is a reasonable approach to developing abundance indices and their variances.

ICES Journal of Marine Science, 2008

Mikkonen, S., Rahikainen, M., Virtanen, J., Lehtonen, R., Kuikka, S., and Ahvonen, A. 2008. A linear mixed model with temporal covariance structures in modelling catch per unit effort of Baltic herring. -ICES Journal of Marine Science, 65: 1645-1654.

Fisheries Research, 2004

Statistical methods are often used to analyse commercial catch and effort data to provide standardised fishing effort and/or a relative index of fish abundance for input into stock assessment models. Achieving reliable results has proved difficult in Australia's Northern Prawn Fishery (NPF), due to a combination of such factors as the biological characteristics of the animals, some aspects of the fleet dynamics, and the changes in fishing technology. For this set of data, we compared four modelling approaches (linear models, mixed models, generalised estimating equations, and generalised linear models) with respect to the outcomes of the standardised fishing effort or the relative index of abundance. We also varied the number and form of vessel covariates in the models. Within a subset of data from this fishery, modelling correlation structures did not alter the conclusions from simpler statistical models. The random-effects models also yielded similar results. This is because the estimators are all consistent even if the correlation structure is mis-specified, and the data set is very large. However, the standard errors from different models differed, suggesting that different methods have different statistical efficiency. We suggest that there is value in modelling the variance function and the correlation structure, to make valid and efficient statistical inferences and gain insight into the data. We found that fishing power was separable from the indices of prawn abundance only when we offset the impact of vessel characteristics at assumed values from external sources. This may be due to the large degree of confounding within the data, and the extreme temporal changes in certain aspects of individual vessels, the fleet and the fleet dynamics.

Canadian Journal of Fisheries and Aquatic Sciences, 2006

The scope of this paper is to quantify, for a wide selection of European fisheries, fishing tactics and strategies and to evaluate the benefits of adjusting the definition of fishing effort using these elements. Fishing tactics and strategies were identified by métiers choices and a series of indices. These indices have been derived to reflect shifts in tactics (within a fishing trip) and in strategies (within a year). The Shannon-Wiener spatial diversity indices of fishing tactics (FT_SW) and strategies (YE_SW) had the greatest impact on catch rates. In particular, FT_SW was always negatively correlated to catch rates. One may anticipate that during a fishing trip, vessels with high FT_SW have been searching fish aggregations for a long time, while vessels with low FT_SW have been more efficient in finding these aggregations. The linkage between YE_SW and catch rates was of a more complex nature. Adjusting fishing effort by means of (i) the métier effect and (ii) the indices of tactics and strategies generally led to a substantial gain in the precision of the relationship between fishing mortality and fishing effort.

Fisheries Research, 2012

ABSTRACT A discrete choice model is applied to determine how fishing effort is allocated spatially and temporally by the English and Welsh North Sea beam trawl fleet. Individual vessels can fish in five distinct areas, and the utility of fishing in an area depends on expected revenue measured as previous success (value per unit effort) and experience (past fishing effort allocation), as well as perceived costs (measured as distance to landing port weighted by fuel price). The model predicts fisher location choice, and the predictions are evaluated using iterative partial cross validation by fitting the model over a series of separate time-periods (nine separate time-periods). Results show the relative importance of the different drivers that change over time. They indicate that there are three main drivers throughout the study, past annual effort, past monthly effort in the year of fishing, and fuel price, largely reflecting the fact that previous practices where success was gained are learned (i.e. experience) and become habitual, and that seasonal variations also dominate behaviour in terms of the strong monthly trends and variable costs. In order to provide an indication of the model's predictive capabilities, a simulated closure of one of the study areas was undertaken (an area that mapped reasonably well with the North Sea cod 2001 partial closure of the North Sea for 10 weeks of that year). The predicted reallocation of effort was compared against realized/observed reallocation of effort, and there was good correlation at the trip level, with a maximum 10% misallocation of predicted effort for that year.

Fisheries Research, 2012

Since the implementation of the Common Fisheries Policy of the European Union in 1983, the management of EU fisheries has been enormously challenging. The abundance of many fish stocks has declined because too much fishing capacity has been utilised on healthy fish stocks. Today, this decline in fish stocks has led to overcapacity in many fisheries, leading to incentives for overfishing. Recent research has shown that the allocation of effort among fleets can play an important role in mitigating overfishing when the targeting covers a range of species (multispecies-i.e., so-called mixed fisheries), while simultaneously optimising the overall economic performance of the fleets. The so-called FcubEcon model, in particular, has elucidated both the biologically and economically optimal method for allocating catches-and thus effort-between fishing fleets, while ensuring that the quotas are not exceeded. Until now, the FcubEcon modelling approach has assumed that there is a simplified linear relationship between effort and fishing mortality. The present study introduces an extension of the FcubEcon model, the so-called SOMER model, that allows this relationship to be non-linear by linking the biological catch equation with the economic production function. Furthermore, the SOMER model relaxes the assumption of the joint production of fishing metiers, unique and separately defined sub-fleets, to allow for more detail regarding the flexibility to target specific groups of species. Thereby, the SOMER model enables the managers to assess the alternative management scenarios more accurately than the existing models.

Fisheries Research, 2015

This study addresses a common assumption in fisheries science: that partial fishing mortality is directly proportional to fishing effort. It is important to challenge this a priori sensible assumption, as it is also built into many models and tools used by ICES to help provide advice and conserve fish stocks.

Fish and Fisheries, 2008

1987

Abstract The concept of fishing effort is central to fisheries economics and management. However, effort is an aggregate index of inputs which can be consistently formed only under the condition on production technology of homothetic separability of inputs. This paper develops the conditions under which effort can be consistently formed. It then provides the first empirical test for effort and jointness in inputs in a fishery by estimating a multiproduct function for the New England otter trawl fleet.

2016

Rising fuel and input costs are having a significant impact on the profitability of the fishing sector and increasing the need for vessels to improve operational efficiency. In particular, smaller vessels that do not have the economies of scale must maximize input-output efficiency to remain viable. There is also the consideration that improved fuel efficiency in fishing vessels will reduce the carbon footprint of the sector. Measuring vessel and fleet efficiency is important for these reasons, but it is also important to correctly measure efficiency to determine how best to manage a fleet and determine how ecosystem, regulatory and market changes will impact fleet viability and operability. This paper uses stochastic frontier analysis (SFA) to assess the efficiency of fishing vessels in the Irish demersal otter trawl nephrops fishery. Clear evidence of efficiency-heterogeneity across vessels in the fishery is reported, even when controlling for vessel-specific characteristics, such...