A GIS analysis of coastal development and trends in bottlenose dolphin strandings in Charleston, SC: implications for coastal marine spatial planning

Bottlenose dolphins (Tursiops truncatus) inhabit estuarine waters near Charleston, South Carolina (SC) feeding, nursing and socializing. While in these waters, dolphins are exposed to multiple direct and indirect threats such as anthropogenic impacts (egs. harassment with boat traffic and entanglements in fishing gear) and environmental degradation. Bottlenose dolphins are protected under the Marine Mammal Protection Act of 1972. Over the years, the percentage of strandings in the estuaries has increased in South Carolina and, specifically, recent stranding data shows an increase in strandings occurring in Charleston, SC near areas of residential development. During the same timeframe, Charleston experienced a shift in human population towards the coastline. These two trends, rise in estuarine dolphin strandings and shift in human population, have raised questions on whether the increase in strandings is a result of more detectable strandings being reported, or a true increase in stranding events. Using GIS, the trends in strandings were compared to residential growth, boat permits, fishing permits, and dock permits in Charleston County from 1994-2009. A simple linear regression analysis was performed to determine if there were any significant relationships between strandings, boat permits, commercial fishing permits, and crabpot permits. The results of this analysis show the stranding trend moves toward Charleston Harbor and adjacent rivers over time which suggests the increase in strandings is related to the strandings becoming more detectable. The statistical analysis shows that the factors that cause human interaction strandings such as boats, commercial fishing, and crabpot line entanglements are not significantly related to strandings further supporting the hypothesis that the increase in strandings are due to increased observations on the water as human coastal population increases and are not a natural phenomenon. This study has local and potentially regional marine spatial planning implications to protect coastal natural resources, such as the bottlenose dolphin, while balancing coastal development.

Incremental Linear Discriminant Analysis Using Sufficient Spanning Sets and Its Applications

This paper presents an incremental learning solution for Linear Discriminant Analysis (LDA) and its applications to object recognition problems. We apply the sufficient spanning set approximation in three steps i.e. update for the total scatter matrix, between-class scatter matrix and the projected data matrix, which leads an online solution which closely agrees with the batch solution in accuracy while significantly reducing the computational complexity. The algorithm yields an efficient solution to incremental LDA even when the number of classes as well as the set size is large. The incremental LDA method has been also shown useful for semi-supervised online learning. Label propagation is done by integrating the incremental LDA into an EM framework. The method has been demonstrated in the task of merging large datasets which were collected during MPEG standardization for face image retrieval, face authentication using the BANCA dataset, and object categorisation using the Caltech101 dataset. © 2010 Springer Science+Business Media, LLC.