Stock identity of horse mackerel (Trachurus trachurus) in the Northeast Atlantic and Mediterranean Sea : Integrating the results from different stock identification approaches

The complexity of small-scale fisheries makes it difficult to predict the allocation of fishing effort among alternative target species in mixed fisheries, resulting in limitation for fisheries management. One reason for the diffi- culty is that fishing effort has been assumed as an aggregate of different components, without consideration of fishers' decisions. In this paper, we use discrete choice models to identify factors involved in fishers' decisions about selecting target species on a daily basis. We analyze catch data, by species and fisher, from three fishing communities of Yucatan, Mexico, to contrast the following models: (i) random selection, (ii) economic motivation, and (iii) changes in resource availability. Our results show that fishers do not operate at random but consider information on resource avail- ability and revenues generated from previous trips before selecting or shifting a target. We compare the results among communities and also use the proposed models to predict changes in fishing effort levels given changes in species price and catch per unit effort. We stress the importance of understanding fishers' behavior when it comes to developing ap- propriate management policies. Resume : La complexite des pecheries artisans rend difficile la determination de la distribution de l'effort de peche entre les especes cibles alternatives dans les pecheries multispecifiques et en consequence, les propositions d'amenage- ment des pecheries sont souvent limitees. Un des problemes est que l'effort de peche a ete considere comme un en- semble de differents composants mais sans prendre en compte la decision des pecheurs. Dans le present article nous utilizons modeles de choix discret afin d' identifier les facteurs involucres dan les decisions des pecheurs pour la selec- tion journaliere des especes cibles. Nous analysons des donnees de captures journalieres provenant de trois communau- tes de pecheurs du Yucatan, Mexique, pour tester les modeles suivants : (i) comportement aleatoire, (ii) motivation economique et (iii) changement dans la disponibilite des ressources. Nos resultats montrent que les pecheurs n'agissent pas de maniere fortuite. Ils prennent en compte l'information sur la disponibilite des ressource et sur les revenus obte- nus durant les campagnes de peche anterieures realisees avant la selection ou le changement d'espece cible. Nous no- tons aussi des differences de comportement entre les pecheurs des trois communautes et nouns utilizons aussi les modeles pour predire le niveau d'effort conjoint produisant des changements dans le prix des especes et dans les captu- res par unite d'effort. Nous mettons l'accent sur l'importance de bien analyser le comportement des pecheurs afin de mieux comprendre la dynamique des flottilles qui doit servir de support pour le developpement de mesures d'amenagement appropriees.

Short-term decisions of small-scale fishers selecting alternative target species: a choice model

The importance of comparative studies in stock analysis

Because it is unrealistic to assess fishes in all locations, models are needed to characterize the nursery habitats of flatfish species. Descriptive habitat models of species presence and categorical analysis regression tree (CART) models of species abundance have been developed in previous studies. Based on collections around Kodiak Island, Alaska in 1991 and 1992, these models have been developed for: age-0 flathead sole (Hippoglossoides elassodon); age-0 Pacific halibut (Hippoglossus stenolepis); age-1 yellowfin sole (Pleuronectes asper); and age-0 rock sole (Pleuronectes bilineatus). In 1995, collections were made in bays along the Alaska Peninsula (an area never before sampled for juvenile flatfishes) and were compared with the previous models developed for Kodiak Island in 1991 and 1992. Very simple descriptive models for Kodiak Island ( Norcross et al., 1995 , Neth. J. Sea Res. 34: 161–175) accurately predicted the abundance along the Alaska Peninsula of flathead sole (78%), Pacific halibut (96%), yellowfin sole (75%) and rock sole (99%) in specific depth ranges and on specific substrate types. More complex CART models of species abundance ( Norcross et al., 1997 , Fish. Bull. (US) 95: 504–520) were more precise but not as accurate as the descriptive models because some parameters were not always available at the test locations. Flathead sole were found at temperatures ≤ 8.9°C on mud and mixed mud substrates in similar proportions in 1995 (66%) as in 1991–92 (71%). Similarly, Pacific halibut were ≤ 7.9 km inside bays and at depths ≤ 40 m in 93% of the sites of this study, compared with 89% previously. Seventy-five per cent of yellowfin sole were at depths ≤ 28 m on mixed substrates in both study periods. Rock sole were found on sand and muddy sand substrates at temperatures above 8.7°C in 52% of the sites in present and 69% of the sites in previous studies. This field test demonstrated that both descriptive and CART models were very useful at identifying juvenile habitat parameters, but are insufficient for areas not previously sampled. The resource-selection models verified the importance of a subset of parameters used in earlier models and provided a statistical means (78–87% correct) for prediction of fish distribution in similar areas of the eastern North Pacific.

Comparison of models for defining nearshore flatfish nursery areas in Alaskan waters

Managers of migratory striped bass stocks that mix along the Atlantic coast of the USA require periodic estimates of the relative contributions of the individual stocks to coastal mixed-stock fisheries; however, to date, a standard approach has not been adopted. We compared the performances of alternative stock identification approaches, using samples taken from the same sets of fish. Reference (known) samples were collected from three Atlantic coast spawning systems: the Hudson River, Chesapeake Bay, and the Roanoke River. Striped bass of mixed-stock origin were collected from eastern Long Island, New York, and were used as test (unknown) samples. The approaches applied were discriminant analysis of morphometric data and of meristic data, logistic regression analysis of combined meristic and morphometric data, discriminant analysis of scale-shape features, discriminant analysis of immunoassay data, and mixed-stock analysis of mitochondrial DNA (mtDNA) data. Overall correct classification rates o...

An Empirical Comparison of Stock Identification Techniques Applied to Striped Bass

We examined the applicability of logistic regression to stock identification studies and compared its performance on two data sets to that of linear and quadratic discriminant functions. Logistic regression can be used to model a categorical dependent variable associated with continuous or discrete independent variables, and is preferred to discriminant analyses when the explanatory variables are not multivariate normal. Our examples were American shad (Alosa sapidissima) from the Connecticut River and Hudson River estuaries, and striped bass (Morone Saxatilis) from the Hudson River, Chesapeake Bay, and Roanoke River estuaries. In the examples we used a resampling method to assess classification and allocation errors of the two methods on new data. For the shad data, the logistic model classified significantly more fish correctly, and provided a significantly better estimate of stock composition. For the striped bass data, the two methods classified about the same proportion of fish correctly, but the log...

Comparison of Logistic Regression and Discriminant Analyses for Stock Identification of Anadromous Fish, with Application to Striped Bass (Morone saxatilis) and American Shad (Alosa sapidissima)

Michael H. Prager

Papers

Comparison of Logistic Regression and Discriminant Analyses for Stock Identification of Anadromous Fish, with Application to Striped Bass (Morone saxatilis) and American Shad (Alosa sapidissima)