A baseline method for benchmarking mortality losses in Atlantic salmon (Salmo salar) production

Abstract

On-farm databases provide a large diversity of information regarding fish health and stock performance. Mortality records held in on-farm database are indicators of fish health status and of great interest for studying fish health, such as patterns of diseases. Mortality records from a Scottish Atlantic salmon production database of one company were used to develop a method of benchmarking production losses due to mortality. The records used concerned mortality loss numbers of Atlantic salmon in the seawater phase. The median, 10th and 90th percentiles of mortality were calculated for each week of production from 88 production recorded cycles. These values were used to delimit the range of a standard mortality curve through the production cycle. The effects of the different mortality losses from each cycle on production in terms of costs and time consumed were also described. Likewise, substantial interannual variation in mortality time series is described as well as the mortality variation associated with three diseases (Pancreas Disease, Cardiomyopathy Syndrome and Infectious Pancreatic Necrosis).

Perspectives on the Utilization of Aquaculture Coproduct in Europe and Asia: Prospects for Value Addition and Improved Resource Efficiency

“…The majority of mortality, both in numbers and biomass, is from unspecified causes throughout the course of the whole 148 production cycle. The results agree broadly with those reported by Soares et al (2011), who studied salmon mortality across over eighty farms in Scotland from one company, although that study found far more mortality attributable to disease. According to staff from the company that supplied the data, a certain amount of fish can be expected to die from no apparent attributable cause and this is common for all farmed salmon production.…”

“…This may be attributable to several causes, as diseases were not specified, but of most concern over the last decade, has been mortality and damage due to sea-lice. Despite development of in-feed treatments such as emamectin 150 benzoate and preventative measures such as fallowing and single year classes, sea-lice can still cause major losses in Scottish salmon farms (Soares et al 2011). Notifiable diseases such as IPN or ISA have been of little concern since the widespread uptake of vaccination programmes against these diseases.…”

Factors affecting variation in mortality of marine Atlantic salmon Salmo salar in Scotland

“…Such analyses have been performed to understand patterns of mortality and their causes in pigs (Chagnon et al 1991, Shankar et al 2009) and poultry (Carver et al 2000, Tabler et al 2004. A preliminary investigation into patterns of mortality in salmon was performed by Soares et al (2011), who found fluctuations in mortality rates and constructed a demonstrative benchmark for salmon mortality in Scotland.In this study, we built on this analysis to examine the causes of mortality and explanatory factors for variations in mortality, to determine whether this mortality benchmark can be generalised, or whether it is dominated by site-specific and unpredictable effects. We investigated which risk factors (such as temperature, age, or site) were associated with variation in mortality during the marine phase of Atlantic salmon production.…”

“…These databases have an important role to play in the investigation and understanding of diseases, since they store valuable data for epidemiologists and can allow quantification of production losses over time. Furthermore these data can facilitate development of effective disease control strategies (Menzies et al 1996, Crockford et al 1999) through epidemiology.One of the most important variables recorded at the farm level is fish mortality rate (MacIntyre 2008, Anonymous 2009, Soares et al 2011, which may include the cause of death, e.g. environmental problems, predators or disease (MacIntyre 2008, North et al 2008.…”

“…Mortality records are essential for investigating patterns of losses across the production cycle, to benchmark expected mortality across time and monitor progress towards production goals (Dewey 2008, Soares et al 2011. The identification of unusual mortality losses in fish production may help farm managers to identify and control health and management problems or to alert regulators to an emerging disease (Soares et al 2011(Soares et al , 2012.The analysis and the identification of risk factors can be used to identify the factors that contribute to variation in mortality and that can lead to fluctuations in normal mortality (i.e. benchmarking).…”