
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
Ocean sprawl facilitates dispersal and connectivity of protected species
pmid: 30115932
pmc: PMC6095900
AbstractHighly connected networks generally improve resilience in complex systems. We present a novel application of this paradigm and investigated the potential for anthropogenic structures in the ocean to enhance connectivity of a protected species threatened by human pressures and climate change. Biophysical dispersal models of a protected coral species simulated potential connectivity between oil and gas installations across the North Sea but also metapopulation outcomes for naturally occurring corals downstream. Network analyses illustrated how just a single generation of virtual larvae released from these installations could create a highly connected anthropogenic system, with larvae becoming competent to settle over a range of natural deep-sea, shelf and fjord coral ecosystems including a marine protected area. These results provide the first study showing that a system of anthropogenic structures can have international conservation significance by creating ecologically connected networks and by acting as stepping stones for cross-border interconnection to natural populations.
- National Oceanography Centre United Kingdom
- Joint Nature Conservation Committee United Kingdom
- Huntsman Marine Science Centre Canada
- Joint Nature Conservation Committee United Kingdom
- Ministry of Trade, Industry and Fisheries Norway
Conservation of Natural Resources, Science, Climate Change, Network Meta-Analysis, Oil and Gas Industry, Models, Biological, 333, Article, Magnoliopsida, Animals, Computer Simulation, Ecosystem, Ecology, Q, R, Anthozoa, Larva, Medicine, North Sea, Animal Distribution, Algorithms
Conservation of Natural Resources, Science, Climate Change, Network Meta-Analysis, Oil and Gas Industry, Models, Biological, 333, Article, Magnoliopsida, Animals, Computer Simulation, Ecosystem, Ecology, Q, R, Anthozoa, Larva, Medicine, North Sea, Animal Distribution, Algorithms
