6 resultados para agent-based model

em Aquatic Commons


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Soil erosion is a natural process that occurs when the force of wind, raindrops or running water on the soil surface exceeds the cohesive forces that bind the soil together. In general, vegetation cover protects the soil from the effects of these erosive forces. However, land management activities such as ploughing, burning or heavy grazing may disturb this protective layer, exposing the underlying soil. The decision making process in rural catchment management is often supported by the predictive modelling of soil erosion and sediment transport processes within the catchment, using established techniques such as the Universal Soil Loss Equation [USLE] and the Agricultural Nonpoint Source pollution model [AGNPS]. In this article, the authors examine the range of erosion models currently available and describe the application of one of these to the Burrishoole catchment on the north-west coast of Ireland, which has suffered heavy erosion of blanket peat in recent years.

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The Burrishoole catchment is situated in County Mayo, on the northwest coast of the Republic of Ireland. Much of the catchment is covered by blanket peat that, in many areas, has become heavily eroded in recent years. This is thought to be due, primarily, to the adverse effects of forestry and agricultural activities in the area. Such activities include ploughing, drainage, the planting and harvesting of trees, and sheep farming, all of which are potentially damaging to such a sensitive landscape if not managed carefully. This article examines the sediment yield and hydrology of the Burrishoole catchment. Flow and sediment concentrations were measured at 8-hourly intervals from 5 February 2001 to 8 November 2001 with an automatic sampler and separate flow gauge, and hourly averages were recorded between 4 July 2002 and 6 September 2002 using an automatic river monitoring system [ARMS]. The authors describe the GIS-based model of soil erosion and transport that was applied to the Burrishoole catchment during this study. The results of these analyses were compared, in a qualitative manner, with the aerial photography available for the Burrishoole catchment to see whether areas that were predicted to contribute large proportions of eroded material to the drainage network corresponded with areas where peat erosion could be identified through photo-interpretation.

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Predicting and under-standing the dynamics of a population requires knowledge of vital rates such as survival, growth, and reproduction. However, these variables are influenced by individual behavior, and when managing exploited populations, it is now generally realized that knowledge of a species’ behavior and life history strategies is required. However, predicting and understanding a response to novel conditions—such as increased fishing-induced mortality, changes in environmental conditions, or specific management strategies—also require knowing the endogenous or exogenous cues that induce phenotypic changes and knowing whether these behaviors and life history patterns are plastic. Although a wide variety of patterns of sex change have been observed in the wild, it is not known how the specific sex-change rule and cues that induce sex change affect stock dynamics. Using an individual based model, we examined the effect of the sex-change rule on the predicted stock dynamics, the effect of mating group size, and the performance of traditional spawning-per-recruit (SPR) measures in a protogynous stock. We considered four different patterns of sex change in which the probability of sex change is determined by 1) the absolute size of the individual, 2) the relative length of individuals at the mating site, 3) the frequency of smaller individuals at the mating site, and 4) expected reproductive success. All four pat-terns of sex change have distinct stock dynamics. Although each sex-change rule leads to the prediction that the stock will be sensitive to the size-selective fishing pattern and may crash if too many reproductive size classes are fished, the performance of traditional spawning-per-recruit measures, the fishing pattern that leads to the greatest yield, and the effect of mating group size all differ distinctly for the four sex-change rules. These results indicate that the management of individual species requires knowledge of whether sex change occurs, as well as an understanding of the endogenous or exogenous cues that induce sex change.

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Abstract—Fisheries often target individuals based on size. Size-selective fishing can create selection differentials on life-history traits and, when those traits have a genetic basis, may cause evolution. The evolution of life history traits affects potential yield and sustainability of fishing, and it is therefore an issue for fishery management. Yet fishery managers usually disregard the possibility of evolution, because little guidance is available to predict evolutionary consequences of management strategies. We attempt to provide some generic guidance. We develop an individual-based model of a population with overlapping generations and continuous reproduction. We simulate model populations under size-selective fishing to generate and quantify selection differentials on growth. The analysis comprises a variety of common life-history and fishery characteristics: variability in growth, correlation between von Bertalanffy growth parameters (K and L∞), maturity rate, natural mortality rate (M), M/K ratio, duration of spawning season, fishing mortality rate (F), maximum size limit, slope of selectivity curve, age at 50% selectivity, and duration of fishing season. We found that each characteristic affected the magnitude of selection differentials. The most vulnerable stocks were those with a short spawning or fishing season. Under almost all life-history and fishery characteristics examined, selection differentials created by realistic fishing mortality rates are considerable.