RESUMO
Increased human demand on the marine environment and associated biodiversity threatens sustainable delivery of ecosystem goods and services, particularly for shallow shelf-sea habitats. As a result, more attention is being paid to quantifying the geographical range and distribution of seabed habitats and keystone species vulnerable to human pressures. In this study, we develop a workflow based on unsupervised K-Means classification units and Generalized Linear Models built from multi-frequency backscatter analyses (95, 300 kHz), bathymetry and bathymetry derivatives (slope) to predict different levels of sandeel densities in Hempton's Turbot Bank Special Area of Conservation (SAC). For Hyperoplus lanceolatus densities, the performance of single frequency verses multi-frequency models is compared. Relatively high agreement between K-Means clustering outputs (from 95 kHz and multi-frequency models) and ground-truthed sandeel densities is noted. Moreover, Root Mean Squared Error (RMSE) values in this instance demonstrate that single-frequency models are favoured over the multi-frequency model in terms of predictive ability. This is mostly linked to the species strong affinity for sedimentary environments whose variability is better captured by the lower frequency system. Generally, these results provide important information about species-habitat relationships and pinpoint bedform features where sandeels are likely to be found and whose variability is potentially linked to the bathymetry domain. The workflow developed in this study also provides a proof of concept to support the design of a robust species-specific monitoring plan in marine protected areas. Most importantly, we highlight how decisions made during sampling, data handling, analysis could impact the final outputs and interpretation of Species Distribution Models and benthic habitat mapping.
Assuntos
Conservação dos Recursos Naturais , Ecossistema , Monitoramento Ambiental , Animais , Monitoramento Ambiental/métodos , Biodiversidade , Linguados/fisiologiaRESUMO
Carbon capturing coastal and marine habitats around the world are decreasing in extent every year, habitats found in abundance in Small Island Developing States' territories. However, these habitats are under threat by increased levels of economic activities and extreme weather events. Consequently, as those ecosystems become scarce their value is expected to increase. In this paper the "value of information", the increase in knowledge that renders a system or a function more valuable, from marine habitat mapping is presented through the (monetary) valuation of one regulating service provided by the newly mapped habitats. Mapping a section of a channel with a multibeam echosounder revealed more seagrass resources than in previous studies. Using values for both the Social Cost of Carbon and Abatement Cost methods, from the literature we estimate the value of the carbon sequestration and storage service these seagrass meadows provide. The impacts of hurricanes in the newly mapped seagrasses were also investigated. Despite the costs of mapping, monitoring and of projected losses of ecosystem services provision due to hurricanes, net benefits over a time period of 50â¯years were considerably larger. The new information provided highlights carbon capturing habitats as more important, enabling the "value of information" to inform policymaking.
Assuntos
Alismatales/fisiologia , Sequestro de Carbono , Conservação dos Recursos Naturais , Ecossistema , Dispersão Vegetal , Ilhas Virgens Britânicas , Conservação dos Recursos Naturais/economiaRESUMO
Man-made structures including rigs, pipelines, cables, renewable energy devices, and ship wrecks, offer hard substrate in the largely soft-sediment environment of the North Sea. These structures become colonised by sedentary organisms and non-migratory reef fish, and form local ecosystems that attract larger predators including seals, birds, and fish. It is possible that these structures form a system of interconnected reef environments through the planktonic dispersal of the pelagic stages of organisms by ocean currents. Changes to the overall arrangement of hard substrate areas through removal or addition of individual man-made structures will affect the interconnectivity and could impact on the ecosystem. Here, we assessed the connectivity of sectors with oil and gas structures, wind farms, wrecks, and natural hard substrate, using a model that simulates the drift of planktonic stages of seven organisms with sedentary adult stages associated with hard substrate, applied to the period 2001-2010. Connectivity was assessed using a classification system designed to address the function of sectors in the network. Results showed a relatively stable overall spatial distribution of sector function but with distinct variations between species and years. The results are discussed in the context of decommissioning of oil and gas infrastructure in the North Sea.
Assuntos
Organismos Aquáticos/crescimento & desenvolvimento , Ecossistema , Monitoramento Ambiental , Peixes/crescimento & desenvolvimento , Animais , Humanos , Larva/crescimento & desenvolvimento , Mar do Norte , Energia RenovávelRESUMO
Beaufort's Dyke is a disused ordnance disposal ground within the North Channel of the Irish Sea. Over 1 million tonnes of ordnance were disposed of in the dyke over a 40 year period representing a substantial volume of trace metal pollutants introduced to the seabed. Utilising particle transport modelling software we simulated the potential transport of metal particles from Beaufort's Dyke over a 3 month period. This demonstrated that Beaufort's Dyke has the potential to act as a source for trace metal contamination to areas beyond the submarine valley. Trace metal analysis of sediments from the Dyke and surrounding National Marine Monitoring Programme areas demonstrate that the Dyke is not the most contaminated site in the region. Particle transport modelling enables the transport pathways of trace metal contaminants to be predicted. Implementation of the technique in other munitions disposal grounds will provide valuable information for the selection of monitoring stations.