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Assessing spatial patterns and density of a dolphin population through signature whistles

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AbstractSome dolphin species produce signature whistles, which may allow the identification of individual dolphins using passive acoustic monitoring (PAM). Identifying individuals by their sounds may enhance the opportunities for monitoring and addressing biological and ecological questions about these species. Here, we explored the potential of signature whistles to investigate ecological aspects of a resident bottlenose dolphin population. Using a limited data set, with few individuals recognized by signature whistles, combined with spatial capture‐recapture (SCR) methods, we investigated how effective such approach is describing spatial use patterns and estimating density for this population. The data were collected using 4–6 stationary bottom‐moored recorders. Since only eight signature whistles were identified, our density estimate may represent a subset of the entire population. However, even with only a few signature whistles identified, our results confirmed the center of the core area used by these dolphins as the area with the highest encounter probability. In addition, our results provided evidence that these dolphins have the same spatial use pattern at night as during the day. This study shows that SCR analysis of signature whistle data can improve our ecological knowledge and understanding of dolphin populations.
Title: Assessing spatial patterns and density of a dolphin population through signature whistles
Description:
AbstractSome dolphin species produce signature whistles, which may allow the identification of individual dolphins using passive acoustic monitoring (PAM).
Identifying individuals by their sounds may enhance the opportunities for monitoring and addressing biological and ecological questions about these species.
Here, we explored the potential of signature whistles to investigate ecological aspects of a resident bottlenose dolphin population.
Using a limited data set, with few individuals recognized by signature whistles, combined with spatial capture‐recapture (SCR) methods, we investigated how effective such approach is describing spatial use patterns and estimating density for this population.
The data were collected using 4–6 stationary bottom‐moored recorders.
Since only eight signature whistles were identified, our density estimate may represent a subset of the entire population.
However, even with only a few signature whistles identified, our results confirmed the center of the core area used by these dolphins as the area with the highest encounter probability.
In addition, our results provided evidence that these dolphins have the same spatial use pattern at night as during the day.
This study shows that SCR analysis of signature whistle data can improve our ecological knowledge and understanding of dolphin populations.

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