Chapter title |
Expert Elicitation Methods in Quantifying the Consequences of Acoustic Disturbance from Offshore Renewable Energy Developments
|
---|---|
Chapter number | 27 |
Book title |
The Effects of Noise on Aquatic Life II
|
Published in |
Advances in experimental medicine and biology, January 2016
|
DOI | 10.1007/978-1-4939-2981-8_27 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2980-1, 978-1-4939-2981-8
|
Authors |
Donovan, Carl, Harwood, John, King, Stephanie, Booth, Cormac, Caneco, Bruno, Walker, Cameron, Carl Donovan, John Harwood, Stephanie King, Cormac Booth, Bruno Caneco, Cameron Walker |
Editors |
Arthur N. Popper, Anthony Hawkins |
Abstract |
There are many developments for offshore renewable energy around the United Kingdom whose installation typically produces large amounts of far-reaching noise, potentially disturbing many marine mammals. The potential to affect the favorable conservation status of many species means extensive environmental impact assessment requirements for the licensing of such installation activities. Quantification of such complex risk problems is difficult and much of the key information is not readily available. Expert elicitation methods can be employed in such pressing cases. We describe the methodology used in an expert elicitation study conducted in the United Kingdom for combining expert opinions based on statistical distributions and copula-like methods. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 35 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 10 | 29% |
Researcher | 8 | 23% |
Student > Master | 5 | 14% |
Student > Bachelor | 2 | 6% |
Professor | 1 | 3% |
Other | 1 | 3% |
Unknown | 8 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 16 | 46% |
Environmental Science | 7 | 20% |
Biochemistry, Genetics and Molecular Biology | 1 | 3% |
Decision Sciences | 1 | 3% |
Social Sciences | 1 | 3% |
Other | 0 | 0% |
Unknown | 9 | 26% |