A systematic review of the production chain of the Arapaima gigas, the giant fish of the Amazon
Authors: Ferreira Gleriani , Marcovitch Jacques , Val Adalberto Luis 
Published: January 2020

Purpose

The development of the Amazon region depends on the organisation and improvement of production chains able to benefit forest species and animals. The purpose of this paper is to map and categorise the studies developed on the Arapaima gigas, a commercialisable fish native to the Amazon, responding to the following research questions: first, which links of the production chain have most of the studies on the pisciculture of the Amazon region? Second, is environmental performance being approached in studies on production chains in the Amazon region? To reach the objective, the authors used the systematic literature review (SLR) method. The authors analysed a sample of 121 articles published in 95 journals between 1981 and 2018. The research contains bibliometric and contents analyses. The main conclusions include the identification of various possibilities of studies throughout the different production chains in the Amazon region; the multidisciplinarity of research on a single species in the Amazon region; the importance of empirical studies in the construction of knowledge about the natural behaviour of the species; the need for integration and sharing of knowledge to create an efficient and competitive production chain. As a limitation, this study encompasses a broad spectrum of issues in the literature, therefore, it was only possible to offer a general overview of these issues. At the same time, this broad and intentional approach presents a comprehensive framing of the themes and phenomena that occur at each link of the production chain of Amazon fish farming.

Design/methodology/approach

This research consists in an SLR with organised, transparent and replicable procedures as recommended in the literature (Littell et al., 2008). The SLR is suited to the mapping of areas where there is a high level of uncertainty and new studies are necessary (Petticrew and Roberts, 2006). This research method is especially useful when dealing with a large volume of information (Tranfield et al., 2003). The use of SLR limits researcher bias by trying to evaluate and select relevant studies on the study theme (Petticrew and Roberts, 2006).

Findings

There are a number of possibilities for studies of the different production chains in the Amazon region; the results of mapping the production chains help to prioritise “what” should be researched in the Amazon region to promote more effective impacts for all stakeholders; research on pisciculture in the Amazon region can be used as a diagnostic tool for public policy formulators; the development of corporate environmental management is intrinsically linked to the process of analysis and understanding of the operations and costs that arise in different links of the production chain.

Research limitations/implications

As a limitation, this study encompasses a broad spectrum of issues in the literature, therefore, it was only possible to offer a general overview of these issues.

Practical implications

In terms of practical implications, it is possible to note that the dispersion of themes found in this study confirms the plurality of the richness of the Amazon and suggests that research institutions should be able to commit to the drafting of integrated planning of science, as well as compilation of the results reached. It is also important to highlight Brazil’s role in the leadership of research in the Amazon region compared to other countries.

Originality/value

The aim of the paper was twofold: to supply a focussed review of the literature on the production chain of a species in Amazon pisciculture and to identify a research agenda capable of overcoming the gaps that impede the development of this chain. More specifically, this study reviewed the available research on the chain in question to analyse the links that have the largest volume of studies and to orient future research.