The benefits of contributing to the citizen science platform iNaturalist as an identifier.

As the number of observations submitted to the citizen science platform iNaturalist continues to grow, it is increasingly important that these observations can be identified to the finest taxonomic level, maximizing their value for biodiversity research. Here, we explore the benefits of acting as an identifier on iNaturalist.

Using transfer learning with a convolutional neural network to detect African manatee (Trichechus senegalensis) vocalizations.

African manatees (Trichechus senegalensis) are vulnerable, understudied, and difficult to detect. Areas where African manatees are found were acoustically sampled and deep learning techniques were used to develop the first African manatee vocalization detector. A transfer learning approach was used to develop a convolutional neural network (CNN) using a pretrained CNN (GoogLeNet). The network was highly successful, even when applied to recordings collected from a different location. Vocal detections were more common at night and tended to occur within less than 2 min of one another.

African manatee (Trichechus senegalensis) habitat suitability at Lake Ossa, Cameroon, using trophic state models and predictions of submerged aquatic vegetation.

The present study aims at investigating the past and current trophic status of Lake Ossa and evaluating its potential impact on African manatee health. Lake Ossa is known as a refuge for the threatened African manatees in Cameroon. Little information exists on the water quality and health of the ecosystem as reflected by its chemical and biological characteristics. Aquatic biotic and abiotic parameters including water clarity, nitrogen, phosphorous, and chlorophyll concentrations were measured monthly during four months at each of 18 water sampling stations evenly distributed across the lake. These parameters were then compared with historical values obtained from the literature to examine the dynamic trophic state of Lake Ossa. Results indicate that Lake Ossa's trophic state parameters doubled in only three decades (from 1985 to 2016), moving from a mesotrophic to a eutrophic state. The decreasing nutrient gradient moving from the mouth of the lake (in the south) to the north indicates that the flow of the adjacent Sanaga River is the primary source of nutrient input. Further analysis suggests that the poor transparency of the lake is not associated with chlorophyll concentrations but rather with the suspended sediments brought-in by the Sanaga River. Consequently, our model demonstrated that despite nutrient enrichment, less than 5% of the lake bottom surface sustained submerged aquatic vegetation. Thus, shoreline emergent vegetation is the primary food available for the local manatee population. During the dry season, water recedes drastically and disconnects from the dominant shoreline emergent vegetation, decreasing accessibility for manatees. The current study revealed major environmental concerns (eutrophication and sedimentation) that may negatively impact habitat quality for manatees. The information from the results will be key for the development of the management plan of the lake and its manatee population. Efficient land use and water management across the entire watershed may be necessary to mitigate such issues.