Distribution and habitat preferences of Bottlenose ...

Distribution and habitat preferences of Bottlenose Dolphins (Tursiops truncatus) SEABRA and Sperm Whales (Physeter macrocephalus) with respect to physiographic and oceanographic factors in the waters around the Azores (Portugal) Maria I. Seabra1, Monica Silva1,2, Sara Magalhães1, Rui Prieto1, Peter August3, Kathy Vigness-Raposa3, Virginie Lafon1, Ricardo S. Santos1 1 Dept. of Oceanography and Fisheries, University of the Azores || 2 University of St. Andrews || 3 Coastal Institute, University of Rhode Island

Background

Methods

Area

The Atlantic waters surrounding the Azores islands (Fig. 1) provide habitat for a great diversity of cetacean species. Unique settings make the Azores Archipelago a privileged area for cetacean habitat research. This region exhibits a highly dynamic physical and biological oceanography, along with a particular physiography characterized by lack of continental shelf and, presence of a great heterogeneity of topographic features, as submarine canyons and scattered seamounts. Until recently1, studies of cetacean distribution in the Azores have largely relied on opportunistic sightings, stranding, data from the past whaling era or limited survey data. Aiming to provide further insights on the ecological mechanisms acting on the distributional ecology of cetacean populations along the archipelago, a series of systematic boat-based surveys was conducted for a six-year period (1999-2004). Due to scientific and conservationist reasons, surveys design was focused on two commonly encountered species, the sperm whale and the bottlenose dolphin. Here we present the preliminary results for these two species. Habitat selection, high-use areas, applicability of geostatistical analyses, implications for management, environmental sampling limitations, and directions for future work are summarized.

Figure 1. Location of the Azores.

Figure 2. Transect lines carried out during 1999-2004 systematic boat-based surveys in the Azores Archipelago.

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Figure 4. Enlargement of the study area illustrating encounter rates for (A) bottlenose dolphins and (B) sperm whales, computed for each 1nm grid-square sampled. Darker colours represent higher values of encounter rate.

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Figure 6. Implications for management. (A) Overlay of Special Areas for Conservation (SACs) polygons to bottlenose dolphin probabilistic distribution; (B) Overlay of the polygon representing the whale-watching operational zone to mapped probability of presence of sperm whale, the main target species of the commercial activity. (Enlargements presented show Faial, Pico and S.Jorge islands).

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Results

Cetaceans were encountered 1590 times, of which 173 and 512 sightings were of bottlenose dolphin and sperm whale groups, respectively. Both species were encountered throughout the archipelago all year round, but the distribution of sightings was not uniform within the study area. The distribution histograms for the two species (Fig. 3) indicate inverse trends in relative abundance with respect to distance from shore, depth and slope (all χ2 < 0.05). Bottlenose dolphins showed significantly preferential use of categories of distances to shore less than 2 nm, depths bellow 750m and slopes from bellow 6º-10º. In contrast, sperm whales were associated with zones farther than 5nm from shore, depths above 1250 m and slopes lower than 6º. Overall, sighting rates (Fig. 4) were relatively low (3.11 ± 0.004 and 0.37 ± 0.0006, means ± SE for bottlenose dolphins and sperm whales, respectively, N = 5487 squares). However, both multiple logistic regression models were significant (all p-values for βi < 0.01) and exhibited a good fit (C > 0.7). Sea Surface Temperature (ºC)


Can particular environmental features reliably characterize sperm whale and bottlenose dolphin habitat?

Geostatistical analyses were applied to survey data in order to examine the relationships between environmental characteristics and cetacean distribution patterns, for each species separately. Location of group sightings and transect lines positions were introduced as vector layers in a geographic information system (GIS) environment. Sighting effort (Fig. 2) was measured as the distance travelled with Beaufort conditions less than 4. For spatial analyses, the study region was divided into 1 nautical mile squares. At each square containing a transect line, an encounter rate (ER) was assigned (calculated as the number of sightings per kilometer searched, i.e. 100 × (n/L), where n is number of sightings and L the number of km of sighting effort). ER was calculated for the whole period of study and on a monthly basis. All sampled grid-squares were classified as either 1 (sighting present, ER > 0) or 0 (sighting absent) and physiographic and oceanographic data were assigned to the center of each square. Bathymetry data were obtained from a digital dataset (1 minute resolution) and sea-bottom slope was computed as the gradient of maximum change in depth (0º-90º). A “distance from shore” layer was generated using the Euclidean distance to the closest point of land for each sighting location. High resolution sea surface temperature (AVHRR) and chlorophyll concentration (SeaWIFS) satellite derived measurements for the period of 2001-2004, were used to produce a set of monthly composite images, which were processed and integrated in a GIS database. Chi-square analyses assessed for the influence of static habitat characteristics on habitat selection for each species. To obtain predictive maps with the probabilistic distribution of suitable habitats as a function of topography, a logistic regression model was used. In the model, the probability of presence of each species was calculated as: p = ey / (1 + ey), where y = β0 + β1x1 + β2x2, βi are the regression coefficients and xi are the significant topographic variables selected by stepwise procedure. Monthly encounter rates were associated with the temporally correspondent oceanographic data, using Spearman correlation coefficients.

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sperm whale bottlenose dolphins

sperm whale bottlenose dolphins

Figure 7. Examples illustrating processed monthly composite images of (A) seasurface temperature (SST) and (B) chlorophyll a concentration for the study area. Box plots show mean (± SE) and min-max range of the oceanographic conditions associated with each species sightings. This was computed considering all available values assigned to monthly sampled 1 nm grid-squares over 2001-2004, in which presence of each species was recorded. Bottlenose dolphins (n = 6635); Sperm whales (n = 8410).


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Figure 3. Spatial distribution of sightings locations and encounter rates (ER) for both species relatively to physiographic factors . The sighting maps and encounter rates distribution plots with respect to (A) nearest distance from shore, (B) depth and (C) slope are aligned horizontally. Striped bars: bottlenose dolphins; Blue bars: sperm whales.

Figure 5. Predicted habitat maps for (A) bottlenose dolphins and (B) sperm whales (enlargement showing the central group of islands of the Azores Archipelago). Shaded areas depict probability of sighting presence (0 to 1), for effort grid-squares. Maps are based on logistic regression models constructed from survey data as a function of topography. Equations for bottlenose dolphins and sperm whales, respectively: y = -2.3597 + (-0.00181) depth + 0.00486 slope; y = -4.8566 + 0.00321depth + (-1.02 x 10-6) depth*slope

Predicted maps (Fig. 5) were in agreement with chi-square analyses, indicating that coastal shallow areas with steep slopes provide habitat for bottlenose dolphins, whereas offshore deeper waters are critical for sperm whales. Simple visual inspection may be useful, when looking at the proximity of high-use areas of bottlenose dolphins and several Special Areas for Conservation or when proposing a decentralization policy of the exponentially developing whale-watching activity (Fig. 6). Positive relationships were found, between bottlenose dolphin encounter rate and chlorophyll concentration (R = 0.025116, p < 0.05, N = 6635) and between sperm whale encounter rate and SST (R = 0.099187, p < 0.01, N = 8410). However, low values of the correlation coefficients indicated low explanatory power of these parameters (confirmed with residuals regression analysis), which may reflect a limitation effect of the considerable lack of data from the satellite images for winter months and zones close to the shore, where must of the sampling was performed. High variability of SST and chlorophyll concentration was found in both time and space and for each species sighting conditions (Fig. 7). Such findings may suggest that cetaceans distribution may be responding to the oceanography dynamics in a way that cannot be assessed by looking at the absolute values of these parameters. To account for this type of relative variability2, future work should focus on other derived oceanographic variables, such as gradients (fronts) and anomalies.

Conclusions • Geostatistical analysis proved

to be useful on elucidating habitat preference and ecology of both species, highlighting the importance of certain areas for conservation.

References

• Distinctive patterns of habitat selection shown by both species are related to the local topography,

• Produced habitat maps provide a comprehensive, easily interpretable, first tool for conservation and management issues that are typically based on static environmental features.

1 Silva, M.A.; Prieto, R.; Magalhães, S.; Cabecinhas, R.; Cruz, A.; Gonçalves, J.M. & Santos, R.S. 2003. Occurrence and distribution of cetaceans in the waters around the Azores (Portugal), Summer and Autumn 1999-2000. Aquatic Mammals, 29 (1):88-98. 2 Baumgartner, M.F. Cole T.V.N., Clapham P.J., Mate B.R. North Atlantic right whale habitat in the lower Bay of Fundy and on the SW Scotian Shelf during 1999-2001. Marine Ecology Progress Series, 267: 137-154

Acknowledgments This study is integrated under the scope of the research project CETAMARH “Ecology and population structure of bottlenose dolphins and sperm whales in the Azores: assessing the relationship with habitat features” (POCTI/BSE/38991/2001), founded by FCT/MCT - Portuguese Ministry of Science. Special thanks to Mark Baumgartner, Peter Cornillon and James Yoder, for the precious comments. Thanks also go to Fernando Tempera, Roland Duhaime, Charles La Bash, Ricardo Medeiros and Greg Bonynge. A short-term staying of the first author at the University of Rhode Island was supported by the Luso-American Foundation.