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Latin american journal of aquatic research

versión On-line ISSN 0718-560X

Lat. Am. J. Aquat. Res. v.36 n.2 Valparaíso  2008

http://dx.doi.org/10.4067/S0718-560X2008000200007 

 

Lat. Am. J. Aquat. Res., 36(2): 245-257, 2008
DOI: 10.3856/vol36-issue 2-fulltext-7

RESEARCH ARTICLE

 

The use of the swept area method for assessing the seabob shrimp Xiphopenaeus kroyeri (Heller, 1862) biomass and removal rates based on artisanal fishery-derived data in southern Brazil: using depletion models to reduce uncertainty

El uso del método de area de barrido para la evaluación de la biomasa y tasas de remoción del camarón Xiphopenaeus kroyeri (Heller, 1862) a partir de datos de la pesca artesanal en el sur de Brasil: la utilización de modelos de reducción de stock para disminuir incertidumbres

 

Paulo R. Pezzuto*, José A. Alvarez-Perez & Roberto Wahrlich

Universidade do Vale do Itajaí, Centro de Ciencias Tecnológicas da Térra e do Mar, Rúa Uruguai 458, CEP 88.302-202, Itajaí, SC, Brazil. *(pezzuto@univali.br)


ABSTRACT. The seabob shrimp (Xiphopenaeus kroyeri) represents an important fishing resource for artisanal fishermen in coastal areas of southern Brazil. Stock assessments of this species ha ve generally relied on biomass dynamics models as applied to CPUE time-series, which (a) are only available for a small offshore fraction of the exploited population and (b) does not comprise patterns of the shallowest artisanal fishing grounds. This work explores the use of extensive catch and effort data derived from a small-scale trawl fishery to obtain swept-area estimates of abundance and removal rates in a limited coastal area of southern Brazil (Tijucas Bay, Santa Catarina State, 27°15'S-48°33'W). Data were obtained from 7,198 fishing trips monitored at the fishing communities between June 2004 and August 2005. Because three parameters of the swept-area equation (i.e. trawl velocity, catch efficiency and wing spread) were unknown, they were defined through a stochastic procedure and calibrated by estimates produced by a Leslie depletion model applied to concurrent catches obtained in one fishing ground. A 21.7% removal rate was estimated for the period June 2004-January 2005; this increased to nearly 34% between February and July 2005. This removal scenario predicted that a five-month fishery would suffice to remo ve 90% of the biomass available in the Tijucas Bay, nearing the 87% CPUE reduction observed in the same period. Whereas abundance and harvest rate estimates were likely affected by inadequate knowledge of the swept-area equation parameters, the similarity of these estimates with relative abundance indexes supports the convenience of the proposed method and justifies future efforts to improve its accuracy.

Keywords: stock assessment, swept-area, depletion, artisanal fisheries, Venaeidae, Xiphopenaeus kroyeri, Brazil.


RESUMEN. El camarón (Xiphopenaeus kroyeri) representa un importante recurso para pescadores artesanales en areas costeras del sur de Brasil. Evaluaciones de stock de esta especie generalmente resultan de modelos de dinámica de biomasa aplicados a series temporales de CPUE los cuales (a) están disponibles solamente para una pequeña fracción explotada en areas más alejadas de la costa y (b) que no contienen los patrones de los fondos someros de la pesca artesanal. Este trabajo analiza la utilidad de numerosos datos de captura y esfuerzo obtenidos en una pesquería de arrastre de pequeña escala para el estimado de abundancia y tasas de remoción, por el método de area de barrido, en un area costera reducida del sur de Brasil (bahía de Tijucas, Estado de Santa Catarina, 27°15'S-48°33'W). Los datos fueron obtenidos de 7.198 viajes de pesca monitoreados en comunidades pesqueras entre junio de 2004 y agosto de 2005. Debido al desconocimiento de tres parámetros de la ecuación del area de barrido (i.e. velocidad del arrastre, eficiencia y apertura horizontal de las redes), éstos fueron definidos por un procedimiento estocástico y calibrados por los estimados producidos por un modelo de reducción de stock de Leslie aplicado a capturas simultáneas obtenidas en una misma area de pesca. Se estimóuna tasa de remoción de 21,7% para el periodo junio 2004-enero 2005, que aumentó casi al 34% entre febrero y julio de 2005. Estos estimados permitieron pronosticar que cinco meses de pesquería serían suficientes para remover el 90% de la biomasa disponible en la bahía de Tijucas, lo que se aproxima al 87% de reducción de la CPUE observada durante el mismo período. Es probable que los estimados de abundancia y tasas de remoción hayan sido afectados por el conocimiento insuficiente de los referidos parámetros de la ecuación del area de barrido, la similitud con índices relativos de abundancia apoyan la utilidad del método planteado y justifica esfuerzos futuros que permitan mejorar su precisión.

Palabras clave: evaluación de stock, area de barrido, reducción de stock, pesquería artesanal, Penaeidae, Xiphopenaeus kroyeri, Brasil.


INTRODUCTION

Fishing management greatly benefits from the availability of stock abundance estimates at any one time. In that sense, abundance survey procedures nave long been developed as experimental solutions to obtain direct estimates of current biomass levéis providing that (a) there is a complete understanding of the distri-bution of the target species and (b) the operation of a determined sampling gear produces realistic records of the species abundance in a known sampled area (Gunderson, 1993).

In the case of demersal species, trawls have been generally used as samplers under the assumption that they tend to represent the abundance of individuals present in an area that is "swept" as they are dragged on the seafloor. This rather simple concept has been the basis of the "swept-area" method largely employed in direct biomass assessment programs for bottom dwelling organisms worldwide (i.e. groundfish, shrimps, crabs, clams, and others) (Gunderson, 1993; Sparre & Venema, 1998). Accurate estimates, as provided by this method, however, are sensitive to spatial sampling designs and certain parameters of the trawl and trawling operation that determine both the precise extent of the sampled area and the gear efficiency (i. e. the ability to avoid escapement of individuals present in the sampled area). In important demersal fishing areas of the world, such uncertainties have been reduced in long-term abundance survey programs through improved sampling designs and understanding of the sampling gear behavior. In tropical and/or small-scale fisheries, however, mostly in the developing world, the structure and costs involved in the development of such programs are often limiting factors and direct abundance surveys, although methodologically applicable, are punctual, irregular, or non-existent (see Haimovici, 2007 for example).

The seabob shrimp, Xiphopenaeus kroyeri (Heller, 1862), occurs in coastal waters of the western Atlantic and is an important fishing resource throughout its entire latitudinal range from North Carolina (USA) to Santa Catarina (Brazil) (D'Incao, 1995). The species is the most abundant crustacean in commercial catches off Brazil, reaching, in 2005, around 26% of the country's total reported crustacean landings (MMA/ IBAMA, 2007). Catches originate mostly from ar-tisanal fishing done on board stern and double-rig trawlers in shallow areas (under 30 m deep); this ac-tivity is particularly important for the livelihood of coastal communities (Valentini, 2006; Santos et al, 2006). Despite being the subject of several sampling programs in different areas, specifically off the south-eastern and southern Brazilian coast (Nakagaki, et al., 1995; Branco et al, 1999; Fransozo et al, 2000; Castro et al, 2005; Natividade, 2006), local seabob shrimp abundances have never been directly assessed by the swept area method. Instead, stock assessments of this species and other penaied shrimps exploited off Brazil have been based on low-cost fishery-derived catch rate time-series analyses and the application of biomass dynamic models (e.g. Santos et al, 1973; Valentini et al, 1991; D'Incao et al, 2002). Recently, however, the reliability of these models for some stocks (i.e. the pink-shrimp Farfantepenaeuspaulensis and F. brasiliensis) has become uncertain due to changes in the fishing structure and dynamics (D'Incao et al, 2002), requiring that alternative ap-proaches be developed to assess shrimp resources in the región.

In this context, this work aimed to explore the ap-plicability of the swept area method for assessing local abundance of the seabob shrimp off the coast of Santa Catarina, southern Brazil, by using extensive geo-referenced fishery-derived catch and effort data. Major limitations regarding such applicability emerge in response to the lack of a proper sampling design and uncertainties about (a) the effective area swept, as determined by unknown wing spread and trawl veloc-ity, and (b) gear efficiency. As an approach to reduce such uncertainties, swept area abundance estimates were compared with concurrent depletion model ap-plications in an attempt to calibrate unknown parame-ters (Gunderson, 1993; Lasta & Iribarne, 1997). Total biomass estimates obtained after the calibration pro-cedures were confronted with monthly landings and used to calcúlate removal rates in the fishing grounds. The usefulness of this approach to obtain low-cost abundance and harvest rate estimates is discussed in light of the standard swept area method experimental procedures.

MATERIALS AND METHODS

Study area

Tijucas Bay is located in the central sector of the Santa Catarina State coast, southern Brazil (27°15'S-48°33'W). It encircles an area of 110,000 hectares of soft bottoms and is 10 m deep (Schettini & Klein, 1997; Abreu, 1998). The bay is bordered by the Porto Belo Peninsula and the township of Bombinhas to the north, by the township of Tijucas to the west, and the peninsula of Governador Celso Ramos to the south (Fig. 1). Subsistence and commercial artisanal fisheries are traditional activities in the región. Fishing communities are located around three cities in Tijucas Bay where shrimp trawling constitutes the main fishing practice (Wahrlich, 1999) (Fig. 1).


Biomass assessment

The study was based on the monitoring of the artisanal fleet trawling operations between June 2004 and Au-gust 2005. In the región, around 210 trawlers targeted seabob shrimps. Examining a sample of around 70 trawlers revealed that they generally have wooden hulls, are 4.0 to 10.7 m long (mean = 8.5 m ± 1.0 SD), and are powered by 17.2 HP engines (± 4.6 SD). These vessels opérate two nets simultaneously with mean head rope and footrope lengths of 9.75 m (SD = 2.0 m) directly attached to the doors. Door weights and cod-end mesh sizes are, in general, between 15-20 kg and 24-26 mm stretched, respectively. Fishing trips last 9.2 h on average (± 14.0 SD) (R. Wahrlich, pers. com.).

Fishing data were obtained by monitors selected and trained within each fishing community, using the methodology proposed by Bonilha et al. (1999). Catch and effort data were produced by both landing records and skipper interviews. Landing records covered all 7,198 trips carried out during the study period and included information on landing dates, boat ñames, and by-catch species. Skipper interviews were done for 1,527 trips (21.2% of the total) and provided de-tailed data on fishing effort (trawling hours, number of trawls per trip), by-catch species, and fishing grounds. The geographic distribution of fishing grounds cited by local fishermen during the interviews enabled us to divide the entire bay area into the eight sub-areas described in Table 1 and Figure 1. These data were transformed into catch per unit effort (CPUE in kg hour-1) and also used to allocate the total catches re-ported in the landing records in the sub-areas, follow-ing the equation:

where Cij is the total catch in the i-eth sub-area in the j'-eth month; Cj is the total catch reported in the landing records during the j-eth month; Clij is the catch reported during interviews in the i-eth sub-area and j-eth month; and Clj is the total catch reported during interviews in the j-eth month.


Total exploitable biomass was estimated during five different months: June 2004 and January, February, June, and July 2005. These months were selected following several criteria: (a) they corresponded to periods when overall catches were either very high or very low; (b) they were either cióse to or distant from the fishing closure period to which the fishery was subjected (March to May, until 2006), and (c) the fishing effort was broadly distributed throughout the largest possible number of sub-areas.

Mean biomass estimates per km2 (± 95% CI) were calculated for each sub-area using the swept-area method (Sparre & Venema, 1998). This procedure demanded the transformation of catch rates reported for each fishing trip (in kg hour-1) into biomass densi-ties (B, in kg km-2) using the equation proposed by Sparre & Venema (1998) modified as:

where CPUE is catch per unit effort (in kg of shrimp retained per trawling hour); Er is the trawl net efficiency, i.e. the fraction of shrimps available in the net's path that are actually retained in the net's cod-end; Fis the trawl velocity (in knots); Ct is the net's head rope length (in meters); Ca is the wing spread, i.e. the width of the path swept by the trawl expressed as a fraction of Ct; and "2" refers to the number of nets trawled during one fishing haul.

Mean stratified biomass (kg km-2) and total exploitable biomass (t) were estimated for the set of sub-areas visited by the fleet during each analyzed month, using a stratified random design in which each sub-area was considered to be a statistic stratum and the whole set of sub-areas visited in that month composed the total population. Equations used in the estimates followedKrebs(1989):

where is the stratified mean biomass per km2 ; Nh is the size of stratum (sub-area) h; h is the stratum number; is the observed mean biomass for stratum h; and N is the total population size . Total biomass in the strata considered was estimated as:

Standard errors for the stratified mean biomass and total biomass in the area were estimated, respectively, by the equations:

and

where is the variance in stratum h and nh is the sample size in stratum h.

Table 2 shows a summary of the number of trips included in each month's calculations.


In Equation 2, Ct was fixed as 9.75 m, which corresponds to the average head rope length used in the fleet. Since the other three parameters of this equation were unknown (efficiency, velocity, wing spread), these were defined through a stochastic procedure. Initially, a set of possible values to be tested for these parameters (Table 3) was chosen based on reference values available in the literature. Three trawl velocities were tested: 1.5, 2.0, and 2.5 knots, as derived from values recently reported for seabob shrimp artisanal boats in southeastern and southern Brazil (ranging from >1 to >2 knots) (Nakagaki et al, 1995; Branco et.al, 1999; Branco, 2005; Campos, 2006; Natividade, 2006). Efficiency values ranging from 0.4 to 1.0 (in 0.1 intervals) were chosen following Sparre & Venema (1998), finding that efficiency values frequently used in swept-area estimations vary between 0.5 and 1.0. Finally, wing spread coefficients (net open-ing/head rope length) between 0.6 and 0.8 (in 0.25 intervals) were tested, considering that, for the nets used in the seabob shrimp fishery, the doors are attached directly to the head and foot ropes, which tends to increase the horizontal opening of the net (Okonski &Martini, 1987).


Múltiple combinations of possible values for these parameters (5 wing spread coefficients x 3 velocities 7 efficiencies) generated 105 possible biomass estimates (± 95% CI) for each of the selected months. Biomass estimates below the total catch reported during each month were regarded as unrealistic. As a consequence, within the total universe of estimates, only those whose lower confidence intervals were higher than the total catch landed during each analyzed month (Table 2) were selected as potentially correct. The next step was to estimate which parameter combination, among those that produced the potentially correct biomass estimates, were the most realistic ones.

For that purpose, a depletion experiment was con-ducted (Hilborn & Walters, 1992) in order to obtain alternative shrimp biomass estimates in time periods and sub-areas where mean biomass estimates made using the swept-area method were also available. Be-cause a depletion experiment generates abundance estimates that refer to the beginning of the studied period, it was considered that the resulting biomass estimate should be necessarily higher than that produced by the swept-area method for concurrent sub-areas and time periods. The most robust combination of parameter values for Equation 2 was identified by contrasting the results generated by both methods; these were then used to calcúlate the final biomass estimates for all months and sub-areas considered.

The application of a depletion experiment required the "closed stock" assumption, i.e. during particular fishing periods in localized areas, losses due to natural mortality or emigration, and gains by recruitment or immigration can be considered insignificant (Hilborn & Walters, 1992). Consequently, under such a "depletion scenario", all shrimp population losses were caused by fishing remováis. If these assumptions were valid, the rate at which the shrimp stock abundance declined as controlled catches were produced by the fishing effort allowed the projection of the amount of catch required to deplete the stock completely. This amount corresponded to an estimate of abundance in the beginning of the experiment.

In this study, the depletion scenario was not experimental, but identified from direct observations of catch rates and landings from 135 fishing trips con-ducted by seabob shrimp trawlers, which concentrated their operations in sub-area 2 during the first 24 days of June 2005. This same data set was used to produce biomass estimates by the swept-area method taking Equation 2 parameter combinations, previously regarded as the most realistic ones from the stochastic procedure describe abo ve. The initial stock abundance calculation was conducted using a Leslie estimator, which considers the following simplified population model:

where the stock biomass in time period t (Bt) results from the biomass at the beginning of the period (B0) minus the catch aecumulated during the time period immediately anterior to t (Kt-l). Considering that CPUE during t (Ut) is an index of the stock relative abundance in t, then:

where q is the catchability (or efficieney) coefficient and:

This equation expresses a linear relationship between CPUE during any time period t (dependent variable) and the catch aecumulated in the time period immediately anterior to t (independent variable). A linear model was fitted to the relationships of these variables during the depletion scenario, which resulted in the estimation of the intercept (qB0) and slope (q) parameters, as well as B0, which derives from their ratio.

During the depletion experiment, all fishing trips recorded in one day were pooled to produce daily catch, effort, and CPUE values. A linear model was then fitted to the daily CPUEs (Ut) and catches aecumulated previous to day t (Kt-l) (dependent and independent variables, respectively) using a Monte Cario procedure in which linear parameters were estimated repeatedly 500 times, each of them including all but one randomly selected day. For each trial, initial biomass (B0) and the escapement rate were calculated, the latter resulting from the difference between B0 and the total catch during the depletion period, expressed as a proportion of B0. A frequeney distribution of the estimates allowed the calculation of median values as well as 95% confidence intervals, which were compared then with the biomass estimates produced simul-taneously by the swept-area method.

RESULTS

Total catch and mean catch rates

Monitored monthly landings of the seabob shrimp in Tijucas Bay varied from a minimum of 1.2 ton in November 2004 to a máximum of 171.5 ton in June 2005. Production oscillated irregularly during the studied period, with peaks in June 2004 and February and June 2005 (Fig. 2). It is necessary to point out, however, that catches recorded between March and May 2005 were underestimated because most illegal operations conducted during the fishing closure period were not reported. Mean catch rates oscillated between a minimum of 2.0 kg h-1 in November 2004 to a máximum of 19.3 kg h-1 in March 2005, in a eyelie temporal pattern. The highest catch rates were recorded between February and June, stabilizing around 2.5 kg h-1 between July and January (Fig. 2).


Biomass assessment

Most combinations of the values indicated in Table 3 produced biomass estimates above monthly landings (i.e. the entire simulation procedure resulted in 96, 105, 60 and 82 plausible biomass estimates for June 2004 and January, February, and July 2005, respectively). As such, this procedure preved to be of little use in the definition of a single set of parameters that could be applied in final biomass estimates. As an exception, in June 2005, only eight combinations were round to produce plausible biomass estimates (Table 4); they were considered essential to the identification of the most likely values of these parameters.


Within the eight possible combinations, the parameters showed reduced internal variability (Table 4). As such, trawl velocity was fixed at 1.5 knots, the value oceurring in all but one combination. A wing spread value of 0.65 was adopted because 75% of the combinations included either that exact value or were within its 10% vicinity. As for the trawl net efficieney parameter, both likely values (0.4 and 0.5) were considered equally. This choice was crucial since, all other parameters being fixed, biomass estimates were shown to be highly sensitive to this parameter. In fact, a 10% difference in net efficiency would lead to 25% variability in biomass, as evidenced in the first two cases of Table 4. Therefore, a definitive choice of the net efficiency parameter value was dependent on the results of the depletion analysis.


Figure 3 depicts the linear model fitted to the Ut and Kt-l relationship, showing that more than 50% of the CPUE variability was explained by shrimp accu-mulated catches and the consequent abundance decline of the stock during the selected depletion period.


Initial biomass and escapement rates, as estimated by the Monte Cario procedure, exhibited low variability (Fig. 3). The median biomass estimated for sub-area 2 during the first 24 days of June was 38,557.3 kg (Table 5). Considering that the total catch recorded in this sub-area during this period was 35,140.1 kg, the median estimated escapement rate was 0.14 (Upper CI 95% 0.28 - Lower CI 95% 0.06).


When comparing the biomass values as estimated by both the swept-area and depletion procedures (Table 5), it can be seen that a trawl net efficiency of 0.5 produced a mean biomass estímate slightly lower than that produced by the depletion experiment. Thus, this efficiency value was adopted as the most plausible for Equation 2 and the final biomass estimates were produced for all other sub-areas and months (Table 6). Because the sub-areas were not evenly visited by the fleet during the study period (Table 2), the five last monthly biomass estimates were not totally comparable, but are only valid within their respective sub-areas. On the other hand, direct comparisons were possible between June 2004 and February 2005 and between January and Jury 2005 since, in those paired months, the fleet visited exactly the same grounds (Table 2). Table 6 reveals that the total biomass increased from 31.8 ton in January to 50.2 ton in Jury 2005, and decreased from 271.3 ton to 150.7 ton between June 2004 and February 2005.


Constrasting the estimated biomass (Table 6) with the recorded monthly catches (Table 2) shows that, between June 2004 and January 2005, on average, the harvest rate of the available biomass reached 21.7% per month; between February and Jury 2005, however, this rate increased to nearly 34% (Table 6).

DISCUSSION

The standard application of the swept-area method to estimate density and abundance of demersal stocks involves crucial assumptions about (a) the availability of the stock to the trawl and the trawling operations, (b) the probability of escapement of the organisms through vulnerability and selectivity processes, (c) precise knowledge of the sampled area and that of the stock distribution, and (d) the representativeness of the sampling design. When only commercial fishing data is available, some of the above assumptions are jeopardized by the profit-oriented nature of the "sampling procedure"; i.e. they are highly biased towards high-density areas, comprising sometimes only a fraction of the whole stock distribution area. Additionally, the actual sampled area may also be of great uncertainty because trawl and trawling parameters may be extremely variable among sampling units (i.e. trawlers) or basically unknown. All things considered, biomass estimates made using the swept-area method have been usually limited to specifically designed experimental procedures (Gunderson, 1993).

Nevertheless small-scale artisanal fisheries, associ-ated with significant social but not economic value, may hardly justify the effort, structure, and costs involved in the establishment of such sampling procedures. All too often, such fisheries are characteristic of highly diversified tropical areas in the developing world, where limitations even increase. In that sense, attempts to develop alternative procedures that involve low-cost data generation and provide at least referential values for absolute biomass seem highly justified.

Due to strong data limitations, the assessment and management of seabob shrimp in the southeastern/southern coast of Brazil has been based on the application of the Graham-Schaefer biomass dynamic model, mostly fitted to the CPUE patterns obtained by the São Paulo State industrial fleet (Valentini et al., 1991; D'Incao et al., 2002). As a consequence, the seabob shrimp trawl fishery (both artisanal and industrial) that is conducted along over 2,300 km of coastal habitats, including the interior of bays, is submitted to management actions that are strongly dependent on a small offshore fraction of the exploited population and that hardly incorporates local peculiarities. In that sense, the present analysis explored the applicability of extensive fishing data to obtain absolute biomass estimates of the seabob shrimp within Tijucas Bay, Santa Catarina, as a contribution to future local community-based management practices.

This exercise required the combination of the swept-area method and depletion estimators as a strategy for reducing the previously mentioned shortcomings and improving absolute abundance estimates. This approach is not uncommon, particularly in invertebrate stock assessments. For example, Otto (1986), Iribarne et al. (1991), and Lasta & Iribarne (1997) combined classical depletion models (Leslie & Davis, 1939; DeLury, 1947) to estímate gear efficiency in abundance surveys designed for the king crab off Alaska and scallops off Argentina. Similarly, exercises nave also been conducted in other crab and bivalve fisheries by using catch-survey analyses (CSA) and remo val and index-removal estimators, all derived from the classical depletion models (Collie & Kruse, 1998; Chen et al, 1998, Gedamke et al, 2005). Finally, an application of depletion models to calibrate gear efficiency of fishing data-derived abundance estimates can be found in a study by Dallagnolo (2008) on the stock assessment of deep-water shrimps off Brazil.

The present procedure applied to the small-scale seabob shrimp fishery off southern Brazil produced abundance estimates that have been found to be coherent with relative abundance patterns generally described for the species, as will be discussed below. Despite the fundamental limitations related to uncertainties regarding the most relevant parameters of the swept-area equation, the method explored was particularly promising because such uncertainties could be further reduced by field observations, which could provide accurate data on trawl velocities and wing spread coefficients, for example. Because the studied trawl fleet is relatively homogeneous and fishing occurs in a limited area, these observations would be easy to obtain and could be regarded as representative of local fishing characteristics.

Absolute biomass estimates obtained in this work suggest that shrimp abundance available to the trawl fishery in Tijucas Bay exhibits a cyclic pattern. In February, the shrimp seems to recruit in the fishery, keeping the stock biomass elevated until June. There-after, abundance tends to decline until the end of the year when it is replaced by a new recruitment and the cycle starts again. Despite the catch reduction produced by the effect of the fishing season closure (March to May), this pattern is confirmed both by catch and catch rate temporal profiles (Fig. 2). The observed cyclicity seems to be characteristic of the species since it has been reported historically by different indices even before the development of an industrial fleet capacity over this resource, which took place in São Paulo State (southeastern Brazil) in the early 1970s (Valentini et al, 1991). In fact, between 1944 and 1945, the artisanal shrimp fleet that operated in the Santos Bay obtained the highest catch rates between May and June and the lowest rates between September and October (Santos et al, 1968). Tremel (1968) observed that the monthly production landed in Santa Catarina State between 1963 and 1967 was highest in the first semester, declining sharply thereaf-ter. More recent scientific surveys conducted off the coast of São Paulo, Paraná, and Santa Catarina states have shown that seabob shrimp catch rates tended to be higher between late austral summer and early winter (Nakagaki & Negreiros-Fransozo, 1998; Branco et al, 1999; Branco, 2005; Natividade, 2006). Finally, mean monthly landings calculated between 1998 and 2005 in São Paulo and Santa Catarina States between 2001 and 2006 showed the highest values in the first semester of the year (except for the fishing closure period), in particular during June (Fig. 4).


This population feature can be partly explained by the species life history which, along the southeastern and southern Brazilian coast, has been characterized by: (a) two reproductive periods during the year, a principal one in spring and a secondary one in late summer and autumn; (b) the predominance of young individuals in summer and/or autumn catches and large individuals in the second semester; (c) first maturation at nearly six months of age and; (d) an approximately 1.5-year life span (Vieira, 1947; Tremel, 1968; Severino-Rodrigues et al, 1993; Nakagaki & Negreiros-Fransozo, 1998; Fransozo et al, 2000; Branco, 2005; Castro et al, 2005; Campos, 2006; Natividade, 2006). Because these life history patterns are consistent throughout the entire distribution area, the traditional hypothesis commonly supported by local fishermen in which the catch rate cycles observed in Tijucas Bay were related to north-ward migratory movements seems unlikely. Alternatively, some authors (e.g. Castro et al, 2005) suggested that the spring reproduction event may occur in deeper waters, limiting the availability of the resource in the fishing grounds exploited by the artisanal fleet. The latter hypothesis, however, is not supported by other studies that have shown that, even in spring, catches in shallow waters are highest (e.g. Natividade, 2006), or that mature females are frequently caught in the fishing grounds (e. g. Tremel, 1968). Although further investigation is required to elucídate shrimp within-year abundance fluctuations, a third plausible -explanation raised by the present study is that they reflect the elevated natural mortality expected in a short-lived species boosted by intense remováis through local fishing.

Since the 1980s, the species has been included in an annual March-May closure season implemented to protect the pink-shrimp (Farfantepenaeus spp.) coastal recruitment migration. Such inclusion not only followed a precautionary action but also derived principally from the fact that coastal trawling for seabob shrimp would eventually produce catches of seaward-migrating pink-shrimp recruits. In the 1990s, however, the seabob shrimp stock abundance dropped 29% (D'Incao et al, 2002), motivating the implementation of a specific annual closure season between October 1 and December 31 from 2006 on.

In order to be effective, however, this measure requires that a sufficiently abundant portion of the biomass recruited in the summer survive throughout the year in order to reach the legally protected reproductive period in spring. A comparison of the available biomass levéis estimated in this study with the monthly catches recorded in the Tijucas Bay area suggested that the harvest rates may be excessively high and actually limit the abundance of the spring spawning biomass. If a simple stock biomass decay is simulated (considering negligible growth, mortality, and migrations), it can be predicted that, under a 21.7% monthly removal scenario, such as that observed between June 2004 and January 2005, the stock biomass early in the year would be reduced to less than 50% in only three months of fishery and to less than 10% in nine months (Table 7). If the 34.4% removal rate predicted by the present analysis in 2005 is considered, this scenario becomes even more severe as a five-month fishery would suffice to remove 90% of the biomass available in Tijucas Bay. In fact, the real figures reported in the región have shown that spring mean catch rates (2.2 kg h-1) are 87% lower than those recorded in autumn (17.08 kg h-1) (Fig. 2). That suggests that both removal scenarios previously hy-pothesized may not be far from reality and that the seabob shrimp fishery in Tijucas Bay is virtually lim-ited to a six-month season. More importantly, it im-plies that the effectiveness of the newly implemented management strategy aimed at protecting spawning biomass during the main reproductive period of the species might be jeopardized by excessive levéis of fishing mortality that reduce the spawning biomass to limiting levéis before the reproductive period.


Whereas such conclusions are largely affected by the methodological uncertainties previously high-lighted, the coincidence of both a relative abundance index and absolute biomass estimates supports the convenience of the proposed method and justifies the efforts discussed to improve its accuracy through a better understanding of the physical and operational features of the artisanal seabob shrimp trawl fleet.

ACKNOWLEDGEMENTS

The authors are thankful to the team of fishing data collectors and the people of the fishing communities of Tijucas Bay for making available information indispensable to this study. Oceanographers Gislei Cibele Bail, Ricardo Hoinkis, and Tiago Dallegrave Ingletto were critical to data collection supervisión in the field and raw data standardization. We are in-debted to Rafael Medeiros Sperb for the GIS analysis and the estimation of fishing areas. This study was funded by the National Fund for the Environment (Ministry of the Environment, Brazil; Agreement Contract FNMA CVI 025/2003) and National Council for Scientific and Technological Development (CNPq) research grants to JAAP (Process 306184/2007-9) and PRP (Process 310820/2006-5).

 

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Received: 12 Jun 2006; Accepted: 8 August 2008