Reviews in Aquaculture最新文献

Bacteria and phytoplankton play an essential role in processing organic and inorganic waste nutrients, making the nutrients reutilized by higher trophic levels in an aquatic food web. Understanding the complex interaction between the microbial food web, nutrients, and cultured animals is crucial to achieving optimum production while minimizing the negative impact of aquaculture production on the environment. Mathematical models have been known as a research tool to conceptualize real systems, beneficial as management and decision-support tools, and addressing predictive, exploratory, or normative questions. This study is a narrative review of 29 models published from 1984 to 2024 focusing on aquaculture production, particularly the dynamics of microorganisms in fish ponds and their influence on nutrient dynamics and fish growth performance. This study is structured to address several questions: What are the different nutrient inputs considered in farm scale models (FSMs)? What microorganisms are often included in FSMs? How to determine food web dynamics? How are the food web dynamics related to nutrient dynamics and fish growth dynamics? The application of food web dynamics in determining carrying capacity and feed formulation is discussed. Finally, this review discusses the importance of stoichiometry, the limitations of current knowledge, and important considerations for developing or selecting models that are suitable for intended users.

Aquaculture has been rapidly growing over the past few decades and has become an important contributor to global food security. As production increases, the intensification of production increases the risk of disease outbreaks. Infections caused by viral, bacterial, and parasitic pathogens represent a major threat to farm economy and growth. To minimize this threat, knowledge of the costs, benefits of prevention, and treatment of diseases is important. Despite the significant costs related to diseases, which are estimated to be 6 billion USD annually, only a limited number of studies have analyzed their economic impacts. A lack of a consistent framework in the literature for identifying the costs of diseases and the gains obtained from avoiding them also presents challenges for the sector in terms of providing a proper response. This paper provides an overview of 29 peer-reviewed articles that estimate economic losses due to diseases and/or quantify the economic gains of reducing them through management. The PRISMA methodology was used for article selections. This overview provides information to farmers and policy-makers on the magnitude of the potential costs and benefits of controlling diseases. The studies are diverse, especially with respect to diseases, economic impacts at different levels, and units of measurement. We have therefore classified them using a consistent framework. This review highlights the need for health management to mitigate disease costs and reduce risks so that aquaculture can both continue to be a growing food source and sustain the livelihood of farmers.

Rising global food demands and technological advancements have led to unprecedented growth in the aquaculture industry. This rapid expansion has facilitated the translocation of species beyond their native ranges. While farming non-native species boosts global food supply, it also poses environmental and socio-economic risks when escapees establish in non-native ecosystems. Using FAO data, we quantified and analysed global non-native aquaculture production, economic value, and monetary costs over space and time. Since 1950, one-third of the 560 species used in aquaculture (n = 160) have been farmed outside of their native ranges, totaling 571.6 million tonnes valued at USD 1.2 trillion. Both native and non-native production increased over time, with non-native species showing greater interannual variability. Fishes largely dominated total aquaculture production with 940 million tonnes, of which 182 million tonnes were non-native production (19%). Non-native algae and crustacean production exceeded that of native species, accounting for 67% and 55% of total production, respectively. Notably, non-native crustacean production has grown enormously in recent years, with a rate of change of over 11,000% since 2000, compared to the previous two decades. According to the InvaCost database, 27 non-native species have been associated with reported monetary costs due to their impacts as invasive species. Among them, nine major aquaculture species documented at least USD 6.4 billion in global total costs. To address the rising threats of biological invasions triggered by aquaculture escapees, enhanced biosecurity, stakeholder awareness, and promotion of sustainable use of native resource alternatives are needed.

Additional points are addressed in the Appendix. As a final note, we highlight the importance of openly disclosing potential conflicts of interests associated with this controversial topic. The review's authors omitted to mention that the reported project “Salmon Tracking 2030” is funded by the aquaculture companies in production areas 3 and 4 in western Norway (https://www.salmontracking.no/om/) and that the first author is a member of the board directors of Nova Sea, a salmon farming company in northern Norway (https://novasea.no/en/om-oss/#styre-og-ledelse).

All authors were responsible in conceptualization and writing – review and editing.

The authors are the current members of the EG of the TLS. Knut W. Vollset is a member of the Norwegian Scientific Advisory Committee for Atlantic Salmon (VRL). Ørjan Karlsen leads the Norwegian surveillance programme for salmon lice on wild salmonids (NALO). Knut W. Vollset, Ørjan Karlsen, Frank Nilsen, and Lars Qviller gave evidence as expert witnesses in a court case in 2021–2022 regarding the TLS.

Z. Zhu, A. Gross, P. B. Brown, and G. Luo, “Disinfection By-Products in Aquaculture: Sources, Impacts, Removal and Future Research,” Reviews in Aquaculture 17, no. 3 (2025): e70035, https://doi.org/10.1111/raq.70035.

The authors would like to correct the order of the author affiliations and to add a third affiliation for the first author.

In the article, the authors and their affiliations were reflected as follows:

Ze Zhu^1,2, Amit Gross¹, Paul B. Brown², Guozhi Luo^3,4

¹ Zuckerberg Institute for Water Research, Jacob Blaustein Institutes for Desert Research, Ben Gurion University of the Negev, Midreshet Ben Gurion, Israel

² Department of Forestry and Natural Resources, Purdue University, Indiana, USA

³ Shanghai Engineering Research Centre of Aquaculture, Shanghai Ocean University, Shanghai, China

⁴ Shanghai Collaborative Innovation Centre for Cultivating Elite Breeds and Green-Culture of Aquaculture Animals, Shanghai, China

The correct list should be:

Ze Zhu^1,2,3, Amit Gross², Paul B. Brown³, Guozhi Luo^1,4

¹ Shanghai Engineering Research Centre of Aquaculture, Shanghai Ocean University, Shanghai, China

² Zuckerberg Institute for Water Research, Jacob Blaustein Institutes for Desert Research, Ben Gurion University of the Negev, Midreshet Ben Gurion, Israel

³ Department of Forestry and Natural Resources, Purdue University, Indiana, USA

⁴ Shanghai Collaborative Innovation Centre for Cultivating Elite Breeds and Green-Culture of Aquaculture Animals, Shanghai, China