1. Marine aquaculture relies on coastal habitats that will be affected by climate change. This review assesses current knowledge of the threats and opportunities of climate change for aquaculture in the UK and Ireland, focusing on the most commonly farmed species, blue mussels (Mytilus edulis) and Atlantic salmon (Salmo salar).
2. There is sparse evidence to indicate that climate change is affecting aquaculture in the UK and Ireland. Impacts to date have been difficult to discern from natural environmental variability, and the pace of technological development in aquaculture overshadows effects of climatic change. However, this review of broader aquaculture literature and the likely effects of climate change suggests that over the next century, climate change has the potential to directly impact the industry.
3. Impacts are related to the industry's dependence on the marine environment for suitable biophysical conditions. For instance, changes in the frequency and strength of storms pose a risk to infrastructure, such as salmon cages. Sea-level rise will shift shoreline morphology, reducing the areal extent of some habitats that are suitable for the industry. Changes in rainfall patterns will increase the turbidity and nutrient loading of rivers, potentially triggering harmful algal blooms and negatively affecting bivalve farming. In addition, ocean acidification may disrupt the early developmental stages of shellfish.
4. Some of the most damaging but least predictable effects of climate change relate to the emergence, translocation and virulence of diseases, parasites and pathogens, although parasites and diseases in finfish aquaculture may be controlled through intervention. The spread of nuisance and non-native species is also potentially damaging.
5. Rising temperatures may create the opportunity to rear warmer water species in theUKand Ireland. Market forces, rather than technical feasibility, are likely to determine whether existing farmed species are displaced by new ones
Abstract:Increasing recognition of the deleterious environmental effects of excessive fine sediment delivery to watercourses means that reliable sediment source assessment represents a fundamental component of catchment planning targeting the protection of freshwater resources and their ecological integrity. Sediment tracing or fingerprinting approaches have been increasingly used to provide catchment scale sediment source information, but there is a need to continue refining existing procedures especially with respect to uncertainty analysis during mass balance modelling. Consequently, an updated Monte Carlo numerical modelling framework was devised and tested, incorporating both conventional and robust statistics coupled with random and Latin Hypercube Sampling (LHS) together with local and genetic algorithm (GA) optimisation. A sediment sourcing study undertaken in the River Axe catchment, southwest England, suggested that the use of robust statistics and LHS with GA optimisation generated the best performance with respect to predicting measured bed sediment geochemistry in six out of eight model applications. On this basis, the catchment-wide average median sediment source contributions were predicted to be 38 AE 1% (pasture topsoils), 3 AE 1% (cultivated topsoils), 37 AE 1% (damaged road verges) and 22 AE 1% (channel banks/subsurface sources). Using modelling frameworks which provide users with flexibility to compare local and global optimisation during uncertainty analysis is recommended for future sediment tracing studies.
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