1. References Amir, O. A., Berggren, P., Ndaro, S. G. M. and Jiddawi, N. S. (2005). Estuarine Coastal and Shelf Science 63/3: 429-437. Christiansen, F., Lusseau, D., Stensland, E. and Berggren, P. (2010). Endangered Species Research 11/1: 91-99. Gordon, J. C. D., Matthews, J. N., Panigada, S., Gannier, A., Borsani, J. F. and Di Sciara, G. N. (2000). Journal of Cetacean Research and Management 2/1: 27-36 Stensland, E., Carlen, I., Sarnblad, A., Bignert, A. and Berggren, P. (2006). Marine Mammal Science 22/3: 667-682. Distribution and ecology of Indo-Pacific bottlenose and humpback dolphins in Menai Bay, Zanzibar Andrew Temple 1, Nick Tregenza 2 & Per Berggren 1 ABU-18 TEMPLE Introduction A population of Indo-Pacific bottlenose dolphins (Tursiops aduncus) and humpback dolphins (Sousa sp.) inhabit the Menai Bay Conservation Area off the south-west coast of Zanzibar, Tanzania. Previous studies have investigated generalised distribution and the impacts of anthropogenic factors on distribution, abundance and behaviour (e.g. Stensland et al 2006; Christiansen et al 2010). However, the effects of biotic and abiotic factors remain largely unexplored. Here we begin to investigate these factors through a combination of bio-acoustic and remote sensing data. Methods C-PODs (Chelonia Ltd.) were deployed at 3 locations (Massoni, L’Oasis and Usine) between February and April 2013 (Fig 1). Locations were of similar deployment depth, off the island’s fringing reef, but each was subject to different levels of boat tourism. Dolphin occurrence was measured as Detection Positive Minutes (DPM). Factors analysed included: location, temperature, diel cycle, tide and seasonality. In addition primary production (as a proxy for prey abundance), sea surface temperature, bottom type and bathymetry were analysed from remote sensing and depth-sounder data. Analyses of anthropogenic impacts (fishing and tourism) were also studied for comparison with previous research. Results Differences in dolphin occurrence between locations measured as DPM (Table 1). Differences in occurrence between diel periods (Fig 2) but no significant difference in vocalisation rate (Click Trains/DPM) (Fig 3). Significant increase in foraging activity (identified by terminal buzz vocalisations) during hours of darkness (Fig 4). Significant differences in primary production, temperature, depth, sea floor slope and bottom type composition between sites (Table 1). No significant correlations with tidal cycle or season. Significant difference in mean vocalisation frequency (modal kHz) between locations (Table 1). Discussion Significant difference in dolphin occurrence between locations provides empirical confirmation of the distribution patterns reported in earlier works (Stensland et al 2006). No observed differences in vocalisation rates, as seen in other studies (e.g. Gordon et al 2000), mean differences in occurrence reflect dolphin abundance between areas. Increased foraging during hours of darkness suggest nocturnal prey species are important dietary constituents for these populations. Possible similarities with the dietary composition seen in northern Zanzibari populations (Amir et al 2005). Increased depth and slope at Usine, gives credence to apparent importance of nocturnal prey species, vertically migrating from adjacent deep water. Differences in the modal kHz of vocalisations between locations suggest differences in the vocal patterns or behaviour between species. May allow for future separation of species through acoustic data alone. Generalised distribution patterns (Stensland et al 2006), suggests Sousa sp. may vocalise at a lower frequency than Tursiops aduncus in this region. Conclusion This study suggests that dolphin distribution (relative occurrence) is likely controlled by prey distribution over large temporal scales and may be controlled by prey distribution and/or tourism on a smaller (diel) temporal scale. 1: Newcastle University, School of Marine Science and Technology,, Newcastle upon Tyne, NE1 7RU, UK. E-Mail: andrew.temple@ncl.ac.uk 2: Chelonia Ltd. Cetacean Monitoring Systems, UK. Figure 3. Click Trains (CT) per Detection Positive Minute (DPM) during diel periods for all study sites. Median with IQR and Range. Figure 1. Benthic cover and bathymetry maps for southern Menai Bay with study locations shown. Top left to bottom right, Massoni, L’Oasis and Usine. Figure 4. Detection Positive Minutes containing terminal buzz vocalisations (BPM) at each location. Figure 2. Diel variation Detection Positive Minutes (DPM) for the study period, sunrise and sunset time range displayed as large and small dashed lines respectively. Mean DPM ± 95% mean CI. Usine MassoniL’Oasis Table 1. Data for C-POD study locations, averages displayed as mean ± S.D.