Singh, W., Hjorleifsson, E., and Stefansson, G. 2011. Robustness of fish assemblages derived from three hierarchical agglomerative clustering algorithms performed on Icelandic groundfish survey data. – ICES Journal of Marine Science, 68: 189–200. Heatmaps are used to identify species–area assemblages based on Icelandic groundfish survey data. Hierarchical agglomerative clustering algorithms are widely applied for species assemblage studies and form the basis for heatmaps. First, the robustness of fish assemblages derived from three clustering algorithms, Average, Complete, and Ward's linkage, was examined. For statistical reliability, the use of a bootstrap resampling technique to generate the confidence values for the clusters is emphasized. Two cluster validity indices were used to measure the efficiency and the quality of the clusters. To examine the stability of the results, clustering was carried out across different sample sizes and levels of data smoothing. Second, cluster analysis was carried out using a different combination of data standardization and dissimilarity measure. Ward's linkage gave the most robust fish assemblages for both modes of data analyses. Four fish assemblages were identified which could be characterized according to the depth and the geographic distribution. This algorithm was then used to generate a heatmap to determine the species–area relationships. Specific areas were characterized by the identified species groups.
An approach is developed to estimate size of Iceland scallop shells from AUV photos. A small-scale camera based AUV survey of Iceland scallops was conducted at a defined site off West Iceland. Prior to height estimation of the identified shells, the distortions introduced by the vehicle orientation and the camera lens were corrected. The average AUV pitch and roll was and deg that resulted in error in ground distance rendering these effects negligible. A quadratic polynomial model was identified for lens distortion correction. This model successfully predicted a theoretical grid from a frame photographed underwater, representing the inherent lens distortion. The predicted shell heights were scaled for the distance from the bottom at which the photos were taken. This approach was validated by height estimation of scallops of known sizes. An underestimation of approximately cm was seen, which could be attributed to pixel error, where each pixel represented cm. After correcting for this difference the estimated heights ranged from cm. A comparison of the height-distribution from a small-scale dredge survey carried out in the vicinity showed non-overlapping peaks in size distribution, with scallops of a broader size range visible in the AUV survey. Further investigations are necessary to evaluate any underlying bias and to validate how representative these surveys are of the true population. The low resolution images made identification of smaller scallops difficult. Overall, the observations of very few small scallops in both surveys could be attributed to low recruitment levels in the recent years due to the known scallop parasite outbreak in the region.
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