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59 results for “Manatee”
Bioacoustic Dataset of African and Florida Manatee Vocalizations for Machine Learning Applications, 2020-2022
This data package presents a comprehensive acoustic library of manatee vocalizations for machine learning (ML) and classifier development. It includes recordings from two species, African and Florida manatees, sampled across four locations. The species are combined due to the acoustic similarity of their vocalizations, providing a diverse and representative training set for ML algorithms. The dataset consists of 0.5-second WAV clips categorized as either containing manatee vocalizations (MV, n=18,129 clips) or not (Noise, n=23,444 clips). MV clips may include multiple vocalizations or truncated calls. All clips were manually verified by two researchers with expertise in manatee acoustics. Recordings were collected using stationary hydrophones deployed in natural habitats, with variable signal-to-noise ratios (SNR) resulting from changes in distance between the vocalizing manatees and the recorders. Background noise across sites is relatively low, with minimal anthropogenic noise; caution is advised when applying models to noisier environments. No dolphin species are believed to be present at the recording sites, and models trained on this dataset should be used cautiously in dolphin-inhabited regions to avoid false positives. If you use this dataset, please reach out to the listed contacts, we are interested in learning how it supports your work.
Manatee County Mosquito Control District entomological monitoring 2015
<p>Mosquito surveillance from the Manatee County Mosquito Control District Vector Surveillance program to survey mosquito populations.</p>
Manatee County Mosquito Control District entomological monitoring 2014
<p>Mosquito surveillance from the Manatee County Mosquito Control District Vector Surveillance program to survey mosquito populations.</p>
Manatee County Mosquito Control District entomological monitoring 2013
<p>Mosquito surveillance from the Manatee County Mosquito Control District Vector Surveillance program to survey mosquito populations.</p>
Manatee County Mosquito Control District entomological monitoring 2012
<p>Mosquito surveillance from the Manatee County Mosquito Control District Vector Surveillance program to survey mosquito populations.</p>
Manatee County Mosquito Control District entomological monitoring 2016
<p>Mosquito surveillance from the Manatee County Mosquito Control District Vector Surveillance program to survey mosquito populations.</p>
Dataset for: African manatee (Trichechus senegalensis) habitat suitability at Lake Ossa, Cameroon using trophic state models and predictions of submerged aquatic vegetation
<p>See research article here: https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.8202</p> <p>Aim: The present study aims at investigating the past and current trophic status of Lake Ossa and evaluating its potential impact on African manatee health.</p> <p>Location: 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.</p> <p>Methods: 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.</p> <p>Results: 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.</p> <p>Main conclusions: The current study revealed major environmental concerns (eutrophication and sedimentation) that may negatively impact habitat quality for manatees. Efficient land use and water management across the entire watershed may be necessary to mitigate such issues.</p>
FIGURE 6. SHSU 1-235 in First fossil manatees in Texas, USA: Trichechus manatus bakerorum from Pleistocene beach deposits along the Gulf of Mexico
FIGURE 6. SHSU 1-235, mandibular symphysis with partial left dentary ramus in dorsal (A), ventral (B), and anterior (C) views. The shallow dorsoventral depth and low, rounded ventrally projecting boss (arrow) are diagnostic features of the extinct morphotype Trichechus manatus bakerorum. Scale bar equals 2 cm.
FIGURE 5. SHSU 1-231 in First fossil manatees in Texas, USA: Trichechus manatus bakerorum from Pleistocene beach deposits along the Gulf of Mexico
FIGURE 5. SHSU 1-231, edentulous right anterior maxilla fragment in dorsal (A) and ventral (B) views. Note the resorbed anterior alveolar region typical of manatees. The rubber band was not removed because it was considered to be part of the history of the specimen. Scale bar equals 2 cm.
FIGURE 4. SHSU 1-027 in First fossil manatees in Texas, USA: Trichechus manatus bakerorum from Pleistocene beach deposits along the Gulf of Mexico
FIGURE 4. SHSU 1-027, edentulous left dentary in lingual (A) and labial (B) views. Scale bar equals 2 cm.
FIGURE 1 in First fossil manatees in Texas, USA: Trichechus manatus bakerorum from Pleistocene beach deposits along the Gulf of Mexico
FIGURE 1. Map showing manatee occurrences along the northwestern coast of the Gulf of Mexico. The two red stars mark the locations of fossil specimens from McFaddin Beach (to the northeast) and Corpus Christi Bay (to the southwest). The blue symbols indicate historical occurrences, including sightings (circles), caracasses (squares), and captured specimens (triangles). Historical distribution data are modified from Fertl et al. (2005). North at top.
Fig. 3 in Occurrence of endoparasites in wild Antillean manatees (Trichechus manatus manatus) in Colombia
Fig. 3. The phylogenetic tree including the here identified trematodes Chiorchis fabaceus and Nudacotyle undicola shows that they belong to the superfamilies Paramphistomatoidea and Pronocephaloidea, respectively. Fasciola hepatica (Fasciolidae) was used as the outgroup taxon.
Fig. 2 in Occurrence of endoparasites in wild Antillean manatees (Trichechus manatus manatus) in Colombia
Fig. 2. Illustrations of endoparasite stages identified in faecal samples of Antillean manatees (Trichechus manatus manatus) from Colombia: (A) Chiorchis fabaceus egg, (B) Eimeria manatus oocyst, (C) Eimeria nodulosa oocyst, (D) Nudacotyle undicola egg.
Fig. 1. A in Occurrence of endoparasites in wild Antillean manatees (Trichechus manatus manatus) in Colombia
Fig. 1. A) Clinical evaluation of a calf manatee as part of the conservation programme of the OMACHA Foundation in Colombia. B) Blood collection for health status evaluation. C) 'Ciénaga Grande de Lorica', Cordoba, flowers of water spinach (Ipomea aquatica), are a favorite manatee food.
Figure 14. The time that a in Manatee behavioral response to boats
Figure 14. The time that a manatee has to change its behavior (i.e., the time window from when a boat was first audible on the DTAG to when the boat reached its CPA to the manatee) plotted against boat speed at CPA. The criteria to be included in this analysis were: boat passed within 50 m of the manatee; boat did not change its speed class during the pass; it was either a single boat pass or the first within a series of boat passes; and personal watercraft (e.g., Jet Skis) were excluded.
Figure 4 in Manatee behavioral response to boats
Figure 4. The mean rate of change in roll (A), heading (B), depth (C), and fluking (D) for 16 tagged manatees during boat passes with a CPA <50 m, during boat passes with a CPA>50 m, and periods without boat noise. Categories with different letters are significantly different (P <0.05). Standard error of the mean (6 SEM) is represented by whiskers.
Figure 8 in Manatee behavioral response to boats
Figure 8. Model-estimated mean probability of a manatee making a change in depth (6 SEM) according to the order of the boat pass. "First" indicates that the boat pass was a single boat pass or the first boat pass in a series of overlapping boat passes. "Subsequent" indicates a boat pass after the first pass in a series of overlapping boat passes. Means sharing any common letters are not significantly different (P> 0.05). The fixed factor values used to generate these estimates are listed in Table 3.
Figure 11 in Manatee behavioral response to boats
Figure 11. Model-estimated mean time delay from start of boat pass until first change in manatee behavior (6 95% CI) in relation to the time available for change (i.e., time from start of pass to CPA). Results are broken out by fluking state at the start of the pass: high fluking state (orange) and low fluking state (purple). Intermediate fluking state was slightly lower but not significantly different from low fluking state (Fig. S4). The fixed factor values used to generate these estimates are listed in Table 3.
Figure 3 in Manatee behavioral response to boats
Figure 3. Visualization of the acoustic and sensor data recorded by a manatee-borne DTAG for a boat pass while the tagged manatee was resting at 3 m depth. The top plot (A) is a spectrogram (frequency vs. time) from the acoustic record; color denotes amplitude (dark red is loudest). The second plot (B) shows changes in pitch of the manatee's peduncle; the colored horizontal lines at the bottom of the plot depict fluking state: black indicates a period of fluking classified as low, green is intermediate, and red indicates high fluking behavior. The purple triangle indicates an increase in fluking rate. The third plot (C) shows the manatee's roll, the fourth (D) shows the manatee's heading (relative scale), and the bottom plot (E) shows the manatee's depth, all plotted against time (s) on the x-axis. The blue lines on the bottom three plots represent periods of time during which there was a substantial change in the corresponding parameter (e.g., depth). On the bottom plot (E), the first black vertical line on the left indicates the start of the boat pass (i.e., when it first becomes audible on DTAG record), the red line indicates the boat's closest point of approach (CPA), and the black line on the right indicates the end of the boat pass (i.e., no longer audible on the DTAG record). For this pass, the manatee changed its fluking behavior, roll, heading, and depth during the boat pass and the first change in behavior was an increase in fluking state at 5.5 s before CPA (arrow on plot B).
Figure 13 in Manatee behavioral response to boats
Figure 13. The time of a manatee's first change in behavior in relation to boat speed class for boat passes within 50 m of the manatee based on the raw data (n 5 64). (A) Time of behavioral change expressed relative to the start of the pass (i.e., when boat noise first became audible on the DTAG record). (B) Time of behavioral change expressed relative to the time at CPA of the boat. The CPA occurs at 0 s with negative values indicating changes in behavior that occurred before CPA and positive values indicating changes after CPA. The boxes represent the interquartile range, the horizontal line shows the median, and the whiskers indicate the 10th and 90th percentiles.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.