Studying the variables that describe the spatial ecology of threatened species allows us to identify and prioritize areas that are critical for species conservation. To estimate the home range and core area of the Endangered (EN) Amazon river dolphin Inia geoffrensis, 23 individuals (6♀, 17♂) were tagged during the rising water period in the Amazon and Orinoco river basins between 2017 and 2018. The satellite tracking period ranged from 24 to 336 d (mean ± SE = 107 ± 15.7 d), and river dolphin movements ranged from 7.5 to 298 km (58 ± 13.4 km). Kernel density estimates were used to determine minimum home ranges at 95% (K95 = 6.2 to 233.9 km2; mean = 59 ± 13.5 km2) and core areas at 50% (K50 = 0.6 to 54.9 km2; mean = 9 ± 2.6 km2). Protected areas accounted for 45% of the K50 estimated core area. We observed dolphin individuals crossing country borders between Colombia and Peru in the Amazon basin, and between Colombia and Venezuela in the Orinoco basin. Satellite tracking allowed us to determine the different uses of riverine habitat types: main rivers (channels and bays, 52% of recorded locations), confluences (32%), lagoons (9.6%), and tributaries (6.2%). Satellite monitoring allowed us to better understand the ecological preferences of the species and demonstrated the importance of maintaining aquatic landscape heterogeneity and spatial connectivity for effective river dolphin conservation.
Quantifying the abundance of species is essential for their management and conservation. Much effort has been invested in surveys of freshwater dolphins in the Amazon basin but river dimensions and complex logistics limit replication of such studies across the region. We evaluated the effectiveness of using unmanned aerial vehicles (UAVs) for surveying two Amazon dolphin species, the tucuxi Sotalia fluviatilis and pink river dolphin Inia geoffrensis, in tropical rivers. In 2016 we conducted drone and visual surveys over 80 km of the Juruá River in Brazil. The aerial surveys provided higher accuracy than human observers in counting individuals detected in groups. Compared to estimates derived from visual surveys, the use of UAVs could provide a more feasible, economical and accurate estimate of Amazon river dolphin populations. The method could potentially be replicated in other important areas for the conservation of these species, to generate an improved index of river dolphin populations in the Amazon.
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