| 1. |
- Amundin, Mats, et al.
(författare)
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Estimating the abundance of the critically endangered Baltic Proper harbour porpoise (Phocoena phocoena) population using passive acoustic monitoring
- 2022
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Ingår i: Ecology and Evolution. - : Wiley. - 2045-7758. ; 12:2
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Tidskriftsartikel (refereegranskat)abstract
- Knowing the abundance of a population is a crucial component to assess its conservationstatus and develop effective conservation plans. For most cetaceans, abundanceestimation is difficult given their cryptic and mobile nature, especially when thepopulation is small and has a transnational distribution. In the Baltic Sea, the numberof harbour porpoises (Phocoena phocoena) has collapsed since the mid-20thcenturyand the Baltic Proper harbour porpoise is listed as Critically Endangered by the IUCNand HELCOM; however, its abundance remains unknown. Here, one of the largestever passive acoustic monitoring studies was carried out by eight Baltic Sea nationsto estimate the abundance of the Baltic Proper harbour porpoise for the first time. Bylogging porpoise echolocation signals at 298 stations during May 2011–April2013,calibrating the loggers’ spatial detection performance at sea, and measuring the clickrate of tagged individuals, we estimated an abundance of 71–1105individuals (95% CI,point estimate 491) during May–Octoberwithin the population's proposed managementborder. The small abundance estimate strongly supports that the Baltic Properharbour porpoise is facing an extremely high risk of extinction, and highlights theneed for immediate and efficient conservation actions through international cooperation.It also provides a starting point in monitoring the trend of the populationabundance to evaluate the effectiveness of management measures and determine itsinteractions with the larger neighboring Belt Sea population. Further, we offer evidencethat design-basedpassive acoustic monitoring can generate reliable estimatesof the abundance of rare and cryptic animal populations across large spatial scales.
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| 2. |
- Rimavičius, Tadas, et al.
(författare)
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Automatic benthic imagery recognition using a hierarchical two-stage approach
- 2018
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Ingår i: Signal, Image and Video Processing. - London : Springer. - 1863-1703 .- 1863-1711. ; 12:6, s. 1107-1114
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Tidskriftsartikel (refereegranskat)abstract
- The main objective of this work is to establish an automated classification system of seabed images. A novel two-stage approach to solving the image region classification task is presented. The first stage is based on information characterizing geometry, colour and texture of the region being analysed. Random forests and support vector machines are considered as classifiers in this work. In the second stage, additional information characterizing image regions surrounding the region being analysed is used. The reliability of decisions made in the first stage regarding the surrounding regions is taken into account when constructing a feature vector for the second stage. The proposed technique was tested in an image region recognition task including five benthic classes: red algae, sponge, sand, lithothamnium and kelp. The task was solved with the average accuracy of 90.11% using a data set consisting of 4589 image regions and the tenfold cross-validation to assess the performance. The two-stage approach allowed increasing the classification accuracy for all the five classes, more than 27% for the “difficult” to recognize “kelp” class. © 2018, Springer-Verlag London Ltd., part of Springer Nature.
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