Selecting stocking density in different climatic seasons: A decision theory approach to intensive aquaculture

Villanueva-Poot, Raúl; Araneda, Marcelo; Vela, Miguel A.; Seijo, Juan Carlos

doi:10.1016/j.aquaculture.2012.12.014

Cited by 33 publications

(15 citation statements)

References 38 publications

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“…This study used a management strategy where farmers optimized the number of fish stocked per batch across the year depending on the predicted temperature to prevent any drop of oxygen below the limit during the production cycle. The relevance of this strategy is supported by studies from Seginer and Halachmi (2008) and Villanueva et al (2013) who showed, using modelling, that stocking density varies from batch to batch according to environmental variation, i.e. rearing temperature.…”

Section: Accepted Manuscriptmentioning

confidence: 98%

Influence of water temperature on the economic value of growth rate in fish farming: The case of sea bass (Dicentrarchus labrax) cage farming in the Mediterranean

et al. 2016

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Please note that this is an author-produced PDF of an article accepted for publication following peer review. The definitive publisher-authenticated version is available on the publisher Web site. cage farming system depends on temperature. This result is important for the development of breeding objectives maximizing economic return in fish breeding programs. Statement of relevance The economic impact of improving growth rate in sea cage farming system depends on temperature. This result is important for the development of breeding objectives maximizing economic return in fish breeding programs. Highlights ► First study to calculate the economic value of growth rate in different temperature conditions in the Mediterranean ► When the average temperature is 18 °C, the economic impact of growth rate is null. ► When the average temperature is 19.5 °C or 21 °C, the economic impact of growth rate is positive. ► First study to show the importance of variation in ambient seawater temperatures for breeding programs in fish

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Section: Accepted Manuscriptmentioning

confidence: 98%

Influence of water temperature on the economic value of growth rate in fish farming: The case of sea bass (Dicentrarchus labrax) cage farming in the Mediterranean

et al. 2016

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“…Another contribution in this study was the approach to estimate mortality even though Equation () has been widely reported among the aquaculture literature involving the instant mortality parameter. In farms where mortality is high at the beginning of the process and declines subtly during the cycle, the exponential extinction equation is used considering such rate ( e.g., Villanueva, Araneda, Vela, & Seijo, ). In contrast, mortality in CB BFTA occurs during the first 40 days and stabilizes rapidly afterwards with values close to 0.…”

Section: Discussionmentioning

confidence: 99%

Growth and survival model of Pacific bluefin tuna ( Thunnus orientalis ) for capture‐based aquaculture in Mexico

et al. 2019

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Capture‐based aquaculture (CBA) is a strategy to capture wild aquatic organisms for rearing. The most iconic species produced under this scheme are bluefin tunas. In Mexico, CBA of this species is developed with Pacific bluefin tunas (PBFT). The parametrization of a biological production function able to describe biomass dynamics during the production cycle is one of the strategies that can help optimize production. The objective of this study was to explain biomass dynamics in capture‐based Pacific Bluefin tuna aquaculture in Mexican waters through parameterization of a growth and survival model. This study also assessed the impact of uncertain intrinsic CBA variables (i.e. seed weight, number of stocked individuals and sea surface temperature [SST] variability). The model was parameterized with production records of 47 net pens in two production sites (an offshore and an inshore facility) during three cycles. The results suggested that production performance was related to SST given that this factor affected survival, mainly during the first ≈40 days after stocking. The risk analysis showed that stocking during the second half of the fishing season from June to August increased the likelihood of matching or exceeding the Key Performance Indicator (KPI) defined regarding biomass increase per pen.

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“…In this sense, understanding and management of an aquaculture operation is a complex problem because of its multifactorial nature (Bjørndal et al 2004). Management requires considering biological, economic and technological variables (Pitel 1990;Mart ınez-Cordero & Leung 2004;Lorentzen 2008;Hillier & Lieberman 2010) as well as different states of nature that are beyond the control of the producer (Villanueva et al 2013). For these reasons, there is a natural area of opportunity for the application of MCDM analysis in this field (Sylvia 1997), as these tools would allow 'at the moment' of any decision, to weigh these considerations in a transparent and defensible way.…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

“…profitability, jobs, time) in the face of varying states of nature (Villanueva et al . ; i.e. future events out of control of the decision‐maker), it will be a problem of mono‐criterial decision‐making.…”

Section: Introductionmentioning

confidence: 99%

“…When it is necessary to make a choice between different courses of action, considering just one criterion to assess the performance of the result (e.g. profitability, jobs, time) in the face of varying states of nature (Villanueva et al 2013; i.e. future events out of control of the decision-maker), it will be a problem of mono-criterial decision-making.…”

Section: Introductionmentioning

confidence: 99%

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Opportunities for strengthening aquaculture industry through multicriteria decision‐making

Vergara‐Solana

Araneda²,

Ponce‐Díaz

2018

Reviews in Aquaculture

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In operations research, there are methodological tools included in decision theory that can help decision‐makers understand and systematize the decision‐making process. Decisions can be classified either as mono‐criterial, when only one criterion or goal is considered to evaluate its performance or multicriterial, which takes into account the interaction between two or more goals or criteria that can be in conflict. Natural resource management and finance are some important examples where the implementation of this type of tools has benefited the decision‐making process because they allow a number of criteria or objectives to be weighted in a transparent manner to assist when one or more decision‐makers are involved. Despite this, its application was not common in aquaculture; however, in recent years, efforts have increased exponentially. This work seeks to identify opportunity areas for development of new aquaculture‐related research through the implementation of multicriterial decision‐making methods (MCDM). To achieve this, a comprehensive bibliometric analysis was performed to detect MCDM applications that have been implemented in aquaculture industry (24 documents that were grouped into eight applications). Later, this information was complemented through the analysis of selected applications in natural resources management, specifically in fisheries, animal husbandry and agriculture. We propose 23 research topics relevant to the aquaculture industry that can be addressed by the methodologies in MCDM.

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Selecting stocking density in different climatic seasons: A decision theory approach to intensive aquaculture

Cited by 33 publications

References 38 publications

Influence of water temperature on the economic value of growth rate in fish farming: The case of sea bass (Dicentrarchus labrax) cage farming in the Mediterranean

Influence of water temperature on the economic value of growth rate in fish farming: The case of sea bass (Dicentrarchus labrax) cage farming in the Mediterranean

Growth and survival model of Pacific bluefin tuna ( Thunnus orientalis ) for capture‐based aquaculture in Mexico

Opportunities for strengthening aquaculture industry through multicriteria decision‐making

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