Dinámica poblacional y explotación de la almeja púrpura, Amiantis purpurata L
By: Morsan, Enrique.
Contributor(s): Orensanz, José Maria [Director] | Cazzaniga, Néstor [Co-director].Series: Tesis Doctoral. Publisher: Bahía Blanca Universidad Nacional del Sur 2000Description: 116 p.Subject(s): Biología Marina | almeja púrpura | amiantis purpurata | Population dynamics | Artisanal fishing | Clam fisheries | Fishery biology | Pesca artesanal | Pesquerías de mariscos | Atlántico Sudoccidental | Golfo San Matías | ArgentinaOnline resources: PDF Texto completo en Oceandocs
Tesis doctoral realizada en el Instituto de Biología Marina y Pesquera "Alfonsina Storni" (IBMPAS). San Antonio Oeste, Río Negro, Argentina.
The purple clam, Amiantis purpurata, inhabits the warm-temperate waters of the southwestern Atlantic, from Espírito Santo (Brazil) to the San Matías Gulf (Argentina). There are no previous studies dealing with its biology and populations dynamics. Astock located in Playa Villarino (San Antonio Este, San Matías Gulf) supports the only artisanal fishery targeting this species. Some peculiar aspects of its dynamics revealed by this study have significant implications for management: 1. It constitutes the southernmost population of this species, and appears to be isolated from other populations located to the north 2. Individuals are slow-growing 3. It seems to be composed of just one or a few annual classes, which are older than 10 years . 4. The spatial distribution is highly contagious, with most individuals concentrated in high density patches (up to 10000 gr / m²). The present study is the first to address the spatial and temporal dynamics of an Amiantis purpurata population, including a description of the fishing process. The datawere obtained between 1981 and 1996. Field work and data analysis have two main components: a)Periodic visits to a study site, a bed known as El Molino, where samples consisting of 0.25 m² sampling units were obtained by divers b) A survey of the whole area, where 150 samples were taken in 1994, according to a systematic sampling design. The spatial distribution of clams was analysed in relation to environmental factors (sediment composition and depth), and modelled using geostatistical methods for mapping density and to estimate the absolute biomass. Geostatistical analyses consists on two main steps: 1) Modelling and identification of the spatial structure of one variable (density or biomass in this case) using a function of spatial covariance (variogram) 2) Linear estimation or prediction of the value of the variable in any non-sampled point of the space to obtain a map (“kriging”). Spatial distribution was highly contagious: half of the population live at densities up to 240 ind / m². Patches were more dense where the predominant fraction of the sediment is fine sand (89,4% of the area). The resulting map shows the location and extension of the patches in the study area; they conform a strip where the highest concentrations are oriented parallel to the coast line, interrupted by small shoals. Density decreases gradually offshore, being highest in the western sector of the bed. The average biomass was 3369 g/m²; estimated total biomass was 53,290 tons. The age of the individuals was determined by combining a technique for producing thin shell sections and repeated sampling at a fix station between 1980 and 1995. The years elapsed between visits matched the accumulation of rings; additionally, the pattern of internal growth bands was cross-checked with the external bands. The external pattern (coincident with the internal bands) was determined to be annual. Most of the population was composed of two cohorts, settled in 1979 and 1980. An study on individual growth was conducted at El Molino using two complementary approaches: the evolution of the size frequency distributions (SFD) in the period 1980 – 1995, and the measurement of growth rings at two different times (1982 and 1994). A model of individual growth was fitted to two data sets: SFDs and high (At) of each ring. Models were fitted and compared using the likelihood ratio test. Results of those comparisons were as follows: 1) Between annual classes (1979 and 1980 cohorts, and extinct polycohort group 1965-1974, based on the 1982 sample) 2) Between two locations of different depth within El Molino. Differences between sites were more significant than between the annual classes 1979 and 1980. Parameters estimated for the extinct polycohort group (1965–1974) indicate that size-at-age was higher for all age groups. Growth at the study area (the southern portion of the geographical distribution of the purple clam) was compared with estimates from other geographical regions from Uruguay to San Matías Gulf. There was a clear latitudinal gradient in the estimated growth rate: La Pedrera (Uruguay) > Monte Hermoso > La Chiquita > El Molino. Differences among the three first were sligth, while differences between El Molino and the rest was pronounced. The hypothesis of food-mediated density-dependence of growth rate is consistent with slow growth in the Villarino population: 1) there is a negative correlation between mean size and density when sites across the bed are compared (data from 1982, 1983 and 1995) and 2) growth rate did not decrease linearly with age, but had a minimum when the cohorts were six to ten years old. This period is coincident with the back-calculated maximum biomass of the cohorts. The age structure of the entire population was assessed by means of counting annual growth rings in all the clams collected during a systematic survey of the whole bed (N = 3099). The study revealed that the 1979 and 1980 year-classes were present throughout most of the area; other cohorts (1978 and juveniles of the 1994 year-class) were found only in restricted sectors of the bed. The spatial distribution of each cohort was modelled separately by means of geostatistical techniques. This made evident the extension and orientation of different aggregations, and their prominent features, which were explored with a variographic analysis. Natural mortality (M) was estimated by means of two techniques: a) From the density trend between1982 and 1995 in a sector of El Molino b) By direct observation of the age-at-death on valves collected “in situ” throughout the entire bed (n = 2113). Using the first approach the coefficient of natural mortality was estimated to beMˆ 0.182 yr-1 (0.140-0.224, P < 0.01). Estimates based on the reading of shells from dead individual were much smaller (Mˆ 0.048yr−1 ), presumably due to a taphonomic bias introduced by the post-mortem dynamics of the valves (transport and diagenesis). The fishery has two components: Hand gathering along the beach (intertidal zone), where up to 25 groups of fishers (3 - 12 fishers per group) have worked simultaneously A diving fishery in the subtidal zone Information on catch, fishing effort, and economic yield was obtained for both components. In the intertidal fishery variation in catch per unit effort (CPUE) was analysed by means of depletion methods in order to explain fisher’s decisions leading to change of fishing area. Catches during 1996 amounted to 371 tons in the intertidal and in 82.1 tons in the subtidal. Commercial divers operated in five different zones. The CPUE data was analysed with relation to density, economic yield, and spatial allocation of fishing effort; the latter was related to concentration profiles derived from the population's spatial distribution study. An economic utility threshold was identified; only 16.4% of the clams are dispersed over 67.9% of the bed, where fishing would not be profitable. Annual fishing mortality coefficient (F) estimated for the diving fishery was 0.0045/yr-1, corresponding to a fishing effort of 2940 diving hours. Harvest strategies were analysed varying F and age at first catch as controls in the context of yield-perrecruit models. A management scheme was proposed that consists of: 1) Partitioning the entire area of the bed into three subareas, enabling the diving fishery to operate in only one of them, 2) Keeping two of the subareas as reproductive reserve (no fishing) 3) No control of fishing effort within the open sector while the fishery is active 4) Conduct periodic assessments of the stock in order to identify eventual recruitment events.