Marine Scotland Science, Freshwater Fisheries Laboratory, Faskally, Pitlochry, PH16 5LB, United Kingdom.
Marine Scotland Science, Freshwater Fisheries Laboratory, Faskally, Pitlochry, PH16 5LB, United Kingdom.
Prev Vet Med. 2020 May;178:104985. doi: 10.1016/j.prevetmed.2020.104985. Epub 2020 Apr 6.
Losses due to mortality are a serious economic drain on Scottish salmon aquaculture and are a limitation to its sustainable growth. Understanding the changes in losses, and associated drivers, are required to identify risks to sustainable aquaculture. Data on losses were obtained from two open source data sets: monthly losses of biomass 2003-2018 and losses of salmon over production cycles (numbers input minus output harvest) 2002-2016. Monthly loss rates increased, accelerating after 2010, while losses per production cycle displayed no trend. Two modelling frameworks were investigated to produce an early warning tool for managers about potential increases in losses. Both linear regression and beta regression showed that monthly losses related to biomass and minimum winter air temperatures with high precision and low bias. These relationships apply at both the national and regional levels where the beta regression best fit model explain 82 % and 69 % of variation in mortality, some regional differences apply, particularly for the Northern Isles. The lack of trend in losses per production cycle may have been due to shorter production cycles as more salmon were harvested earlier, and possibly increasing losses of larger salmon (which affects biomass but not numbers lost). In the long-term, the models predict that milder winters and increased biomass will be associated with increased mortality, which will need to be managed. In the short-term, given relatively little year-to-year variation in biomass, minimum winter temperature is a powerful early warning of the likely extent of losses in the Scottish salmon farming industry.
死亡造成的损失是苏格兰鲑鱼养殖业的严重经济负担，也是其可持续增长的限制因素。了解损失的变化及其相关驱动因素，对于识别可持续水产养殖的风险至关重要。损失数据来自两个开源数据集：2003 年至 2018 年的生物量月度损失和 2002 年至 2016 年的生产周期内鲑鱼数量输入减输出收获的损失。每月损失率增加，2010 年后加速，而每个生产周期的损失没有趋势。研究了两种建模框架，以制作一个早期预警工具，供管理者了解损失增加的潜在风险。线性回归和贝塔回归都表明，月度损失与生物量和冬季最低空气温度有关，具有高精度和低偏差。这些关系适用于国家和地区层面，贝塔回归的最佳拟合模型解释了 82%和 69%的死亡率变化，一些地区差异适用，特别是北岛。每个生产周期的损失没有趋势，可能是由于生产周期缩短，更多的鲑鱼更早收获，以及可能更大的鲑鱼损失增加（这会影响生物量，但不会影响损失的数量）。从长期来看，模型预测温和的冬季和增加的生物量将与增加的死亡率相关，这需要加以管理。从短期来看，考虑到生物量的年际变化相对较小，冬季最低温度是苏格兰鲑鱼养殖行业损失程度的有力预警。
