Ecosystem modeling as a framework to convert a multi-disciplinary research approach into a useful model for the Araçá Bay (Brazil)

• Autor(a) principal: Angelini, Ronaldo
• Data de Publicação: 2018
• Outros Autores: Contente, Riguel F., Rossi-Wongtschowski, Carmem Lúcia del Bianco, Soares, Lucy S.H., Schaeffer-Novelli, Yara, Lopes, Rubens M., Mancini, Patrícia Luciano, Colle, Marta, Amaral, Antonia Cecília Zacagnini
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRN
• Texto Completo: https://repositorio.ufrn.br/handle/123456789/30599
• topic: Parameterization; Phytoplankton; Phytobenthos; Mangrove; Detritus

A model-oriented research project can organize and systematize high quality sampling information and convert observed values into information needed to parameterize ecological models. In this paper, we describe the value parameterization process from an interdisciplinary project to the development of a food web model (using Ecopath) in order to comprehend the Araçá Bay ecosystem structure (Brazil) and to forecast the impact of a port expansion (São Sebastião Port) over a bay environment. Araçá Bay Ecopath model has 34 compartments, Phytoplankton, Phytobenthos, Mangrove, Zooplankton, 10 groups of benthos, 13 fish groups, Shrimp, Crabs, Turtles, two bird groups and two groups of Detritus. The model outputs showed that Araçá Bay is a mature and detritus-based ecosystem. It is highly influenced by the role of benthos groups which are responsible for a huge amount of detritus recycling due to their large biomass value. The simulation of port expansion (primary producers' reduction), using the Ecosim module, indicated negative impacts on almost all living groups and an increase in detritus accumulation, leading the entire bay ecosystem towards its collapse (in the short term). The interdisciplinary organized sampling process presented here is an example of how objectively planned sample design and modeling may guide scientists, local people and stakeholders' decisions with valuable integrated information and overall predictions in order to consider the sustainable use of natural areas and resources