Marine biodiversity and ecosystem functions are known to relate to a large number of environmental factors such as depth, latitude or primary productivity. These can be measured and expressed as continuous explanatory variables. In contrast, “habitat” is normally expressed in categorical terms, as one of a selection of pre-determined types. The identification and protection of specific habitats has become a central driver of conservation policy.
More recently, research has begun to identify the effects of the mixture of different habitats within an underwater landscape, showing that the history, size and shape of patches, and the nature of the boundaries between, them have important effects on biodiversity and animal behaviour.
The proposed work will focus on two types of underwater landscape. The temperate waters around Scotland have been affected by human use, resulting in habitat damage and fragmentation. Ecosystem services from Scotland’s seas include the provision of fish and shellfish, and the role of seafloor habitats in carbon sequestration and coastal protection. Understanding how habitat mosaics function as a landscape is important to efforts to manage fisheries and restore degraded biodiversity.
In contrast, the coastal waters of Antarctica are affected by a natural disruptor, ice scour. Ice has powerful structuring effects on polar marine communities, creating a mosaic of areas with different disturbance (scour) histories. Ice scour is changing as a result of climate change, so understanding its role is important to predicting the future state of Antarctic biodiversity.
The project will use field data from these contrasting underwater environments to identify how patch characteristics, and their arrangement in the underwater landscape, affect biodiversity and animal behaviour. This work will allow us to predict the effects of future seabed change, whether through climate change or human activity.
The project will take advantage of new data analysis techniques and underwater photography to create seabed maps, and relate landscape characteristics to biodiversity metrics.