Simulation of alternative management strategies for red algae, luga roja, (Gigartina skottsbergii Setchell and Gardner) in southern Chile

The objective of this study was to examine the response of a Gigartina skottsbergii population, a commercial red algal species from southern Chile, to different management strategies using a simulation model. The impact of present harvesting techniques, varying the recommended size at harvest and the rate of harvest were evaluated. Model development followed Grant et al. (Ecology and Natural Resource Management: Systems Analysis and Simulation. Wiley, New York, 1997) and the data base was obtained from available literature. The model simulates population dynamics of G. skottsbergii and in terms of both number of fronds and biomass per size class. Model predicts an annual pattern of variation for biomass determined by variations in seasonal factors. However, biomass has a 2 year cycle of alternate years with high biomass and low biomass. This production cycle can be attributed to changes in population size structure and density, and to the existence of discrete recruitment events. Results predicted from using different management strategies suggest that commercial harvest should be based on selection for larger fronds and restricted harvest period. Under this scenario harvest rate can be relaxed since no important changes in harvest biomass were predicted when increasing harvest rate from 50 to 90%, at least in the short term. However, it is recommendable to keep it low (50%) as a preventive mechanism, since results suggest that in the long term, a harvest rate of 50% could produce larger harvested biomass. The existence of a biennial cycle of biomass production suggests that populations should be harvested in rotation. Several aspects of the model must be improved in order to obtain better prediction of both specific values as well as dynamics. These include winter recruitment, frond breakage, longevity of larger sized fronds, and a more complete analysis of changes in the size structure of the population.