We evaluated three mathematical procedures to estimate the parameters of the relationship between weight and length for Cichla monoculus: least squares ordinary regression on log-transformed data, non-linear estimation using raw data and a mix of multivariate analysis and fuzzy logic. Our goal was to find an alternative approach that considers the uncertainties inherent to this biological model. We found that non-linear estimation generated more consistent estimates than least squares regression. Our results also indicate that it is possible to find consistent estimates of the parameters directly from the centers of mass of each cluster. However, the most important result is the intervals obtained with the fuzzy inference system. Keywords: allometric model, Cichla, fuzzy logic, parameter estimation.O uso da lógica fuzzy para estimar os parâmetros da relação entre peso e comprimento ResumoEmpregamos três procedimentos matemáticos, regressão com mínimos quadrados ordinários com dados log-transformados, estimação não-linear e uma combinação de análise multivariada e lógica fuzzy para estimar os parâmetros da relação peso × comprimento para Cichla monoculus. Nosso objetivo foi apresentar uma abordagem alternativa que considere as incertezas inerentes ao modelo. Observamos que as estimativas da estimação não-linear foram mais consistentes que as obtidas por regressão linear sobre dados log-transformados. Nossos resultados também mostraram que é possível obter estimativas dos parâmetros diretamente dos centros de máximos formados dos grupos por uma análise de agrupamento k-means. No entanto, os resultados mais importantes foram os intervalos obtidos com o sistema de inferência fuzzy.Palavras-chave: modelo alométrico, Cichla, logica fuzzy, estimação de parâmetros.

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We use a compartmental model to project scenarios for the spread of COVID-19 in the city of Manaus, with different degrees of social distancing and isolation of infectious individuals. In a scenario without any containment measures, our projections point to more than 50,000 (simultaneously) infectious individuals before the end of April 2020. Only in a scenario with strict and extensive social distancing (lockdown), implemented and observed as of March 23 rd , 2020, would this number be less than 50,000 in the first half of June. Furthermore, an increase in the number of tests or in the collective awareness among the population regarding the importance of strict distancing measures would have only had a significant impact if implemented before the end of March.

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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The increase in temperature resulting from global climate change can directly affect the survival of fish and therefore population parameters such as natural mortality (M). The estimation of this parameter and the understanding of the uncertainties in its estimates are enormous challenges for studies that evaluate fish stocks. In addition, the effects of increases in temperature may be associated with life strategies. Therefore, the fuzzy set theory was used to evaluate the effects of temperature increase on the natural mortality of fish, considering different life strategies. The model showed that the increase in temperature increased the uncertainties in M estimates for all species, regardless of the life strategy. However, opportunistic species present greater uncertainties in estimates of M compared to equilibrium species. The patterns found in uncertainties of M associated with species groupings by life strategies can be used in holistic approaches for the assessment and management of recently exploited fisheries resources or for those with limited biological data.