ABSTRACT
Large uncertainties still dominate the hypothesis of an abrupt large-scale shift of the Amazon forest caused by climate change [Amazonian forest dieback (AFD)] even though observational evidence shows the forest and regional climate changing. Here, we assess whether mitigation or adaptation action should be taken now, later, or not at all in light of such uncertainties. No action/later action would result in major social impacts that may influence migration to large Amazonian cities through a causal chain of climate change and forest degradation leading to lower river-water levels that affect transportation, food security, and health. Net-present value socioeconomic damage over a 30-year period after AFD is estimated between US dollar (USD) $957 billion (×109) and $3,589 billion (compared with Gross Brazilian Amazon Product of USD $150 billion per year), arising primarily from changes in the provision of ecosystem services. Costs of acting now would be one to two orders of magnitude lower than economic damages. However, while AFD mitigation alternatives-e.g., curbing deforestation-are attainable (USD $64 billion), their efficacy in achieving a forest resilience that prevents AFD is uncertain. Concurrently, a proposed set of 20 adaptation measures is also attainable (USD $122 billion) and could bring benefits even if AFD never occurs. An interdisciplinary research agenda to fill lingering knowledge gaps and constrain the risk of AFD should focus on developing sound experimental and modeling evidence regarding its likelihood, integrated with socioeconomic assessments to anticipate its impacts and evaluate the feasibility and efficacy of mitigation/adaptation options.
Subject(s)
Conservation of Natural Resources/economics , Forestry/economics , Forestry/methods , Brazil , Climate Change , Computer Simulation , Ecosystem , Forests , Policy , Risk Assessment/methods , TreesABSTRACT
Considerando-se o atual estágio de desenvolvimento de sistemas especialistas e de sistemas baseados no conhecimento, em que a extraçäo de conhecimento é, às vezes, vista como uma referência técnica à concepçäo desses sistemas, proporciona-se neste trabalho um conjunto de reflexöes que däo uma melhor claridade psicológica ao assunto. No artigo, mostra-se como é visto o problema de extraçäo de conhecimentos pela Ergonomia e Inteligência Artificial; como a extraçäo pode ser obtida por diferentes objetivos e, finalmente, analisa-se o domínio da construçäo de um sistema de ajuda para decisäo. Privilegiamos este último objetivo, próprio da Ergonomia Cognitiva, porque somos conduzidos a tomar o quadro teórico da psicologia, que enfatiza uma multiplicidade de níveis de regulaçäo da atividade e de formas de conhecimentos tratados pelo operador, antes de abordar as questöes metodológicas de acesso a esses conhecimentos