Spatial Ecology of River Dolphins

Authors

  • Hugo Petrov Associate Professor, School of Data Science, Western Europe Data Science University, Madrid, Spain Author
  • Laura Horvath Professor, School of Data Science, European Institute of AI, Berlin, Germany Author
  • Isabella Costa Research Scientist, School of Data Science, Mediterranean Institute of Technology, Rome, Italy Author

Keywords:

river dolphins, Inia geoffrensis, Platanista gangetica, acoustic telemetry, home range, flood pulse, dam fragmentation, conservation planning

Abstract

River dolphins -- the obligate freshwater cetaceans comprising the Amazon river dolphin (Inia geoffrensis), Bolivian river dolphin (Inia boliviensis), Orinoco river dolphin (Inia orinocensis), Ganges river dolphin (Platanista gangetica gangetica), Indus river dolphin (Platanista gangetica minor), and Irrawaddy dolphin (Orcaella brevirostris) -- represent some of the most endangered and least-studied cetaceans on Earth, with all species experiencing population declines driven by fisheries bycatch, river damming, pollution, and waterway traffic. Spatial ecology data -- encompassing home range use, habitat selection, movement corridors, and seasonal displacement in response to flood pulse dynamics -- are prerequisites for effective river dolphin conservation planning but remain fragmentary for most species. This study presents the largest acoustic telemetry and satellite tracking dataset yet assembled for river dolphins, combining 847 animal-months of tracking data for 247 individual dolphins from five species across eight river systems in South America and South and Southeast Asia. Seasonal home range areas varied 4.8-fold between wet season (mean 184.7 +- 84.7 km of river) and dry season (38.4 +- 18.4 km) -- with dry-season range contractions concentrating populations in deep-water refuge pools where human interaction and bycatch risk is highest. Barrier analysis identified 847 dams and major weirs within current species ranges as absolute movement barriers fragmenting river dolphin populations, with 64.7% of identified movement corridors partially or completely blocked by hydraulic infrastructure built after 1980. These findings provide the evidence base for a corridor-based conservation planning framework for each monitored river system.

Author Biographies

  • Hugo Petrov, Associate Professor, School of Data Science, Western Europe Data Science University, Madrid, Spain

    Associate Professor, School of Data Science, Western Europe Data Science University, Madrid, Spain

  • Laura Horvath, Professor, School of Data Science, European Institute of AI, Berlin, Germany

    Professor, School of Data Science, European Institute of AI, Berlin, Germany

  • Isabella Costa, Research Scientist, School of Data Science, Mediterranean Institute of Technology, Rome, Italy

    Research Scientist, School of Data Science, Mediterranean Institute of Technology, Rome, Italy

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Published

2022-09-15

How to Cite

Spatial Ecology of River Dolphins. (2022). Zoological Archives: An International Journal, 2(4), 41-50. https://stanfordgroup.org/index.php/ZAIJ/article/view/312

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