Role of benthic habitat distribution data in coastal water wind turbine site selection
| dc.contributor.author | Matti Sahla | |
| dc.contributor.author | Risto Kalliola | |
| dc.contributor.author | Michael Haltdin | |
| dc.contributor.organization | fi=maantiede|en=Geography | | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.17647764921 | |
| dc.contributor.organization-code | 2606901 | |
| dc.converis.publication-id | 2646926 | |
| dc.converis.url | https://research.utu.fi/converis/portal/Publication/2646926 | |
| dc.date.accessioned | 2022-10-28T14:02:25Z | |
| dc.date.available | 2022-10-28T14:02:25Z | |
| dc.description.abstract | <p id="abspara0010"> Environmentally concerned coastal zone management and marine spatial planning should minimize the risk of damaging sensitive benthic habitats. Since reliable maps of the underwater nature are scarce, planners often have to work with inconsistent data. We compare the outcomes of three hypothetical planning schemes with dissimilar input benthic ecology datasets in order to define suitable sites for shallow water wind turbine placement. The study is conducted in the northern Baltic Sea where the brown algae bladderwrack (<em>Fucus</em> spp.) forms important submerged habitats that can be disturbed by wind turbine construction. We evaluated the effects of the input data using two different approaches. In the first, we placed a maximum number of wind turbines at four different depth classes. After choosing the locations, we examined the potential area of affected <em>Fucus</em> habitats. In the second approach, we tested the accumulation of damage to <em>Fucus</em> habitats when adding new turbines to the research area by starting from the furthest available location of known important <em>Fucus</em> sites. Both approaches indicated that using data from airborne LIDAR helps coastal planners avoid the risk of unnecessary destruction of benthic key habitats. LIDAR surveys can help to optimize the locations for the detailed planning of vast areas in a way that point-based inventories or statistical predictive modeling cannot achieve.</p> <hr class="artHeader" id="absgraphicalabs00151" /> <p> </p> | |
| dc.format.pagerange | 78 | |
| dc.format.pagerange | 83 | |
| dc.identifier.jour-issn | 0964-5691 | |
| dc.identifier.olddbid | 185894 | |
| dc.identifier.oldhandle | 10024/168988 | |
| dc.identifier.uri | https://www.utupub.fi/handle/11111/42690 | |
| dc.identifier.url | http://www.sciencedirect.com/science/article/pii/S0964569116300254 | |
| dc.identifier.urn | URN:NBN:fi-fe2021042714745 | |
| dc.language.iso | en | |
| dc.okm.affiliatedauthor | Sahla, Matti | |
| dc.okm.affiliatedauthor | Kalliola, Risto | |
| dc.okm.discipline | 1171 Geosciences | en_GB |
| dc.okm.discipline | 1172 Environmental sciences | en_GB |
| dc.okm.discipline | 1171 Geotieteet | fi_FI |
| dc.okm.discipline | 1172 Ympäristötiede | fi_FI |
| dc.okm.internationalcopublication | not an international co-publication | |
| dc.okm.internationality | International publication | |
| dc.okm.type | A1 ScientificArticle | |
| dc.publisher.country | United Kingdom | en_GB |
| dc.publisher.country | Britannia | fi_FI |
| dc.publisher.country-code | GB | |
| dc.relation.doi | 10.1016/j.ocecoaman.2016.02.010 | |
| dc.relation.ispartofjournal | Ocean and Coastal Management | |
| dc.relation.volume | 124 | |
| dc.source.identifier | https://www.utupub.fi/handle/10024/168988 | |
| dc.title | Role of benthic habitat distribution data in coastal water wind turbine site selection | |
| dc.year.issued | 2016 |
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