5 resultados para logistic model

em SAPIENTIA - Universidade do Algarve - Portugal


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Fishing trials with monofilament gill nets and longlines using small hooks were carried out at the same fishing grounds in Cyclades (Aegean Sea) over 1 year. Four sizes of MUSTAD brand, round bent, flatted sea hooks (Quality 2316 DT, numbers 15, 13, 12 and 11) and four mesh sizes of 22, 24, 26 and 28 turn nominal bar length monofilament gill nets were used. Significant differences in the catch size frequency distributions of the two gears were found for four out of five of the most important species caught by both the gears (Diplodus annularis, Diplodus vulgaris, Pagellus erythrinus, Scorpaena porcus and Serranus cabrilla), with longlines catching larger fish and a wider size range than gill nets. Whereas longline catch size frequency distributions for most species for the different hook sizes were generally highly overlapped, suggesting little or no differences in size selectivity, gill net catch size frequency distributions clearly showed size selection, with larger mesh sizes catching larger fish. A variety of models were fitted to the gill net data, with the lognormal providing the best fit in most cases. A maximum likelihood method was also used to estimate the parameters of the logistic model for the longline data. Because of the highly overlapped longline catch size frequency distributions parameters could only be estimated for two species. This study shows that the two static gears have different impacts in terms of size selection. This information will be useful for the more effective management of these small-scale, multi-species and multi-gear fisheries. (C) 2002 Elsevier Science B.V. All rights reserved.

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Fishing trials with monofilament gill nets and longlines using small hooks were carried out in Algarve waters (southern Portugal) over a one-year period. Four hook sizes of "Mustad" brand, round bent, flatted sea hooks (Quality 2316 DT, numbers 15, 13, 12 and 11) and four mesh sizes of 25, 30, 35 and 40 mm (bar length) monofilament gill nets were used. Commercially valuable sea breams dominated the longline catches while small pelagics were relatively more important in the gill nets. Significant differences in the catch size frequency distributions of the two gears were found for all the most important species caught by both gears (Boops boops, Diplodus bellottii, Diplodus vulgaris, Pagellus acarne, Pagellus erythrinus, Spondyiosoma cantharus, Scomber japonicus and Scorpaena notata), with longlines catching larger fish and a wider size range than nets. Whereas longline catch size frequency distributions for most species for the different hook sizes were generally highly overlapped, suggesting little or no differences in size selectivity, gill net catch size frequency distributions clearly showed size selection. A variety of models were fitted to the gill net and hook data using the SELECT method, while the parameters of the logistic model were estimated by maximum likelihood for the longline data. The bi-normal model gave the best fits for most of the species caught with gill nets, while the logistic model adequately described hook selectivity. The results of this study show that the two static gears compete for many of the same species and have different impacts in terms of catch composition and size selectivity. This information will I;e useful for the improved management of these small-scale fisheries in which many different gears compete for scarce resources.

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Trammel net size selectivity was studied for the most important metiers in four southern European areas: the Cantabrian Sea (Atlantic, Basque Country, Spain), the Algarve (Atlantic, southern Portugal), the Gulf of Cadiz (Atlantic, Spain) and the Cyclades Islands (Mediterranean, Aegean Sea, Greece). These metiers were: cuttlefish (Sepia officinalis) and soles (Solea senegalensis, Microchirus azevia, Synaptura lusitanica) in the Algarve and the Gulf of Cadiz, sole (Solea solea) in the Cantabrian Sea and mixed fin-fish in the Cyclades. In each area, experimental trammel nets of six different types (combinations of two large outer panel mesh sizes and three small inner panel meshes) were constructed. Fishing trials were carried out on a seasonal basis (four seasons in the Cantabrian Sea, Algarve and Cyclades and two seasons in the Gulf of Cadiz) with chartered commercial fishing vessels. Overall, size selectivity was estimated for 17 out of 28 species for which sufficient data were available. Trammel nets generally caught a wide size range of the most important species, with length frequency distributions that were skewed to the right and/or bi-modal. In many cases the length frequency distributions of the different nets were highly overlapped. The Kolmogorov-Smirnov test also showed that the large outer panel meshes generally had no effect in terms of size selectivity, while the opposite was true for the small inner panel ones. Six different selectivity models (normal scale, normal location, gamma, log-normal, bi-modal and gamma semi-Wileman) were fitted to data for the most abundant species in the four areas. For fish, the bi-modal model provided the best fits for the majority of the data sets, with the uni-modal models giving poor fits in most cases. For Sepia officinalis, where trammelling or pocketing was the method of capture in 100% of the cases, the logistic model fitted by maximum likelihood was judged to be more appropriate for describing the size selective properties of the trammel nets. Our results, which are among the first ones on trammel net selectivity in European waters, will be useful for evaluating the impacts of competing gear for the socio-economically important small-scale static gear fisheries. (c) 2006 Elsevier B.V All rights reserved.

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A longline 'metier' using small hooks for 'red' sea breams (Pagellus acarne and Pagellus erythrinus) in the Algarve (south of Portugal) was studied. Experimental longlining was carried out with three sizes of "Mustad" round bend, flatted, spade end Quality 2316 DT hooks (numbers 11, 13 and 15) and two types of bait: razor shell (Ensis siliqua) and mud shrimp (Upogebia pusilla). A total of 3 328 fish and at least 36 species were caught with 33 600 hooks fished in 28 longline sets. Five species of sea breams (Sparidae) accounted for 79% of the catch: Pagellus acarne, Pagellus erythrinus, Diplodus vulgaris, Spondyliosoma cantharus, and Boops boops. High catch rates of 20-30 fish per 100 hooks were made in a number of 1 200 hook longline sets, with total catch weights of 40 to more than 60 kg per set. In general, the smallest hook (number 15) had the highest catch rate. Bait type did not significantly affect the catch size distributions. Although more fish were caught with the razor shell bait, higher catch rates of 'red' sea breams were obtained with mud shrimp. Catch rates were also affected by the location of the fishing grounds and the time of the set, with the highest catch rates obtained when the longline was set within two hours before sunrise. A wide size range was caught for each species, with highly overlapped catch size frequency distributions for the three hook sizes used. Except for Spondyliosoma cantharus, few illegal-sized fish were caught, even with the smallest hook. The logistic model fitted by maximum likelihood was used to describe hook selectivity for Diplodus vulgaris, Pagellus acarne, Pagellus erythrinus, and Spondyliosoma cantharus. (C) Ifremer-Elsevier, Paris.

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Modelling species distributions with presence data from atlases, museum collections and databases is challenging. In this paper, we compare seven procedures to generate pseudoabsence data, which in turn are used to generate GLM-logistic regressed models when reliable absence data are not available. We use pseudo-absences selected randomly or by means of presence-only methods (ENFA and MDE) to model the distribution of a threatened endemic Iberian moth species (Graellsia isabelae). The results show that the pseudo-absence selection method greatly influences the percentage of explained variability, the scores of the accuracy measures and, most importantly, the degree of constraint in the distribution estimated. As we extract pseudo-absences from environmental regions further from the optimum established by presence data, the models generated obtain better accuracy scores, and over-prediction increases. When variables other than environmental ones influence the distribution of the species (i.e., non-equilibrium state) and precise information on absences is non-existent, the random selection of pseudo-absences or their selection from environmental localities similar to those of species presence data generates the most constrained predictive distribution maps, because pseudo-absences can be located within environmentally suitable areas. This study showsthat ifwe do not have reliable absence data, the method of pseudo-absence selection strongly conditions the obtained model, generating different model predictions in the gradient between potential and realized distributions.