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110 results for “jaguar”
Figure 3 in First records of Brazilian three-banded armadillo (Tolypeutes tricinctus, Mammalia, Cingulata, Chlamyphoridae) predation by jaguar (Panthera onca, Mammalia, Carnivora, Felidae)
Figure 3. The carapace of an individual of Brazilian three-banded armadillo (Tolypeutes tricinctus) attacked by a jaguar (Panthera onca). (A) An overview of the carapace. (B) A close-up of the damaged scapular shield (broken scutes are circled in red). (C) The fitting of a P. onca canine tooth into a broken scute of the scapular shield. (D) The fitting of a P. onca canine tooth into the perforation in the pelvic shield. (E) The probable disposition of P. onca jaws during the bite, while respecting the maximum mandibular opening. (F) An individual of T. tricinctus rolled up parallel to the ground, demonstrating a possible position of the individual in which the bite could have occurred.
Figure 2 in First records of Brazilian three-banded armadillo (Tolypeutes tricinctus, Mammalia, Cingulata, Chlamyphoridae) predation by jaguar (Panthera onca, Mammalia, Carnivora, Felidae)
Figure 2. Record of a jaguar (Panthera onca) carrying a Brazilian three-band- ed armadillo (Tolypeutes tricinctus) in its mouth in the municipally of Brotas de Macaúbas, state of Bahia, Brazil.This photo is from a 15-second-long video recorded by camera trapping.
Figure 1 in First records of Brazilian three-banded armadillo (Tolypeutes tricinctus, Mammalia, Cingulata, Chlamyphoridae) predation by jaguar (Panthera onca, Mammalia, Carnivora, Felidae)
Figure 1. Location of the two areas (orange triangles) where the predation of Brazilian three-banded armadillo (Tolypeutes tricinctus) by jaguar (Panthera onca) was recorded in the Caatinga domain (green shaded area) in northeastern Brazil: Serra da Capivara National Park (SCNP) and an unprotected rural area in the municipally of Brotas de Macaúbas (BdM). The inset shows the two areas in relation to Brazilian states (gray shaded states refer to those in which the areas are located). The state divisions are from IBGE (2015), and the distribution of the Caatinga is from INSA (2014).
Mayan Jaguar
Mexican souvenir from tulum, Cancun a 3d scanned mayan jaguar using Matter and Form 3d scanner, feel free to download and print it. Source: Objaverse 1.0 / Sketchfab
When waterholes get busy, rare interactions thrive: Photographic evidence of a jaguar (Panthera onca) killing an ocelot (Leopardus pardalis)
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Development of a SNP panel for geographic assignment and population monitoring of jaguars (Panthera onca)
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Data from: Wildfire and drought alter the ecology of jaguars and co-occurring mammals in the world’s largest wetland
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International media coverage of the Bolivian jaguar trade
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Data from: Jaguar-white lipped peccary dynamic interaction index and landscape structures
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Data from: Human disturbance and the activity patterns and temporal overlap of tapirs and jaguars in reserves of NW Belize.
<p>Human disturbance from tourism and other non-consumptive activities in protected areas may be stressful to wildlife. Animals may move away in space or time to avoid human interaction. For species of particular conservation concern, such as Baird's tapirs (<i>Tapirus bairdii)</i> and jaguars (<i>Panthera onca</i>), a better understanding of how they respond to different levels and types of disturbance is needed in order to manage human visitation to parks in ways that minimize negative outcomes for wildlife. We describe the overlap of activity patterns of tapirs, jaguars, and humans at logged and unlogged sites and at places with low versus high human visitation using camera survey data from protected areas of northwest Belize, 2013-2016. Tapirs were nocturnal in all study sites, with >80 percent of all tapir detections occurring between 1900 h and 0500 h. Their activity patterns were not different in unlogged versus logged sites and did not change with increased human traffic. Jaguars were cathemeral across sites, but had more nocturnal activity at the site with the most human impact. Activity pattern overlap between tapirs and jaguars did not differ significantly between logged and unlogged sites, nor between areas with low and high human activity. Human traffic increased from 2013-2016 at most of the study locations. In conclusion, this camera trap dataset suggests that non-consumptive human disturbance does not alter the activity patterns of tapirs and jaguars in protected areas lacking hunting pressure.</p>
Data from: Deep learning improves taphonomic resolution: high accuracy in differentiating tooth marks made by lions and jaguars
<p>Taphonomists have long struggled with identifying carnivore agency in bone accumulation and modification. Now that several taphonomic techniques allow identifying carnivore modification of bones, a next step involves determining carnivore type. This is of utmost importance to determine which carnivores were preying on and competing with hominins and what types of interaction existed among them during prehistory. Computer vision techniques using deep architectures of convolutional neural networks (CNN) have enabled significantly higher resolution in the identification of bone surface modifications (BSM) than previous methods. Here, we apply these techniques to test the hypothesis that different carnivores create specific BSM that can enable their identification. To make differentiation more challenging, we selected two types of carnivores (lions and jaguars) that belong to the same mammal family and have similar dental morphology. We hypothesize that if two similar carnivores can be identified by the BSM they imprint on bones, then two more distinctive carnivores (e.g. hyenids and felids) should be more easily distinguished. The CNN method used here shows that tooth scores from both types of felids can be successfully classified with an accuracy greater than 82%. The first hypothesis was successfully tested. The next step will be to differentiate diverse carnivore types involving a wider range of carnivore-made BSM. The present study demonstrates that resolution increases when combining two different disciplines (taphonomy and artificial intelligence computing) in order to test new hypotheses that could not be addressed with traditional taphonomic methods.</p>
Data from: Corrigendum to: Deep learning improves taphonomic resolution: high accuracy in differentiating tooth marks made by lions and jaguars
<p>Corrigendum to "Deep learning improves taphonomic resolution: high accuracy in differentiating tooth marks made by lions and jaguars". In a previous paper, we presented some convolutional neural network (CNN) models to classify images of tooth scores made by lions and jaguars through deep learning computer vision. In that work, we reached an accuracy of 82% of the testing set correctly classified. However, such an accuracy is biased, since the original sample was highly unbalanced. Therefor, now we present the results which correct the problems of the previously published models by producing more balanced classifications and also by achieving higher accuracy.</p>
Data from: Robust inference on large-scale species habitat use with interview data: the status of jaguars outside protected areas in Central America
Evaluating range-wide habitat use by a target species requires information on species occurrence over broad geographic regions, a process made difficult by species rarity, large spatiotemporal sampling domains, and imperfect detection. We address these challenges in an assessment of habitat use for jaguars (Panthera onca) outside protected areas in Central America. Occurrence records were acquired within 12 putative corridors using interviews with knowledgeable corridor residents. We developed a Bayesian hierarchical occupancy model to gain robust inference, allowing for heterogeneity introduced in the sampling process over space and time, using records of jaguar occurrence prone to false positives and false negatives. Probability of false detection of jaguars increased with the number of interviews conducted per unit (from 5.42% to 7.74% given <4 and ≥4 observers per unit). True probability of detection (mean=0.58) increased with the number of days interviewees spent in a survey unit per year. Failing to account for false positives biased predicted habitat use high (˜1.8x), especially where occurrence records were sparse. Probability of site use by jaguars increased with greater forest cover, prey richness, and distance from human settlements, and decreased with greater agricultural cover, elevation, and distance from protected areas. Site use probabilities averaged 0.15-0.97 by corridor, providing relatively fine-scale resolution of predicted jaguar occurrence consistent with known patterns of jaguar gene flow across Central America. Model validation, accounting for both false positives and negatives in the observation process, indicated moderate correspondence between model-predicted observations and actual observations for withheld data (0.65, 95% CRI 0.59–0.71), with sensitivity and specificity rates of 0.69 (0.61 – 0.77) and 0.59 (0.50 – 0.68), respectively. These results demonstrate that reliable predictions can be achieved despite the complexity of large-scale, interview-based analyses of species occurrence. Synthesis and applications. Our Bayesian hierarchical occupancy model accommodated heterogeneity caused by typical sampling inequities and idiosyncrasies associated with interview data, yielding robust estimates of jaguar habitat use. Our approach is applicable to any wide-ranging and readily identifiable species and has particular utility for rare species in human-dominated landscapes where traditional survey techniques (e.g., camera traps) may be impractical.
Influence of sea turtle nesting on hunting behavior and movements of jaguars in the dry forest of northwest Costa Rica
Jaguars (Panthera onca) are opportunistic predators that prey on large profitable prey items, such sea turtles at nesting beaches. Here we use jaguar and sea turtle track count surveys, combined with satellite telemetry of one jaguar, to evaluate whether jaguar hunting behavior and movements are influenced by seasonal sea turtle nesting in the Sector Santa Rosa of Área de Conservación Guanacaste in northwest Costa Rica. We used Generalized Linear Models to evaluate the effect of moon phase and sea surface temperature on olive ridley (Lepidochelis olivacea) and green turtle (Chelonia mydas) nesting abundance, as well as the combination of these predictors on the frequency of jaguar predation activity (proximity to nesting beaches) and movements. For home range size and location analyses, we calculated Kernel Density Estimates for each season at three different temporal scales. Sea turtle nesting season influenced jaguar activity patterns, as well as sea turtle abundance was related to jaguar locations and predation events, but jaguar home range size (88.8 km2 overall) did not differ between nesting seasons or among temporal scales. Environmental conditions influenced sea turtle nesting and, as a consequence, also influenced jaguar movements and foraging activity. Our study defined the home range of a female jaguar in the tropical dry forest and its relationship to seasonally abundant turtles. Additional information related to the effect of tourism on jaguar-sea turtle interactions would improve conservation of these species at unique nesting beaches in the area.
Data from: Noninvasive individual and species identification of jaguars (Panthera onca), pumas (Puma concolor) and ocelots (Leopardus pardalis) in Belize, Central America using cross-species microsatellites and fecal DNA
There is a great need to develop efficient, noninvasive genetic sampling methods to study wild populations of multiple, co-occurring, threatened felids. This is especially important for molecular scatology studies occurring in challenging tropical environments where DNA degrades quickly and the quality of faecal samples varies greatly. We optimized 14 polymorphic microsatellite loci for jaguars (Panthera onca), pumas (Puma concolor) and ocelots (Leopardus pardalis) and assessed their utility for cross-species amplification. Additionally, we tested their reliability for species and individual identification using DNA from faeces of wild felids detected by a scat detector dog across Belize in Central America. All microsatellite loci were successfully amplified in the three target species, were polymorphic with average expected heterozygosities of HE = 0.60 ± 0.18 (SD) for jaguars, HE = 0.65 ± 0.21 (SD) for pumas and HE = 0.70 ± 0.13 (SD) for ocelots and had an overall PCR amplification success of 61%. We used this nuclear DNA primer set to successfully identify species and individuals from 49% of 1053 field-collected scat samples. This set of optimized microsatellite multiplexes represents a powerful tool for future efforts to conduct noninvasive studies on multiple, wild Neotropical felids.
Data from: Jaguar Movement Database: a GPS-based movement dataset of an apex predator in the Neotropics
The field of movement ecology has rapidly grown during the last decade, with important advancements in tracking devices and analytical tools that have provided unprecedented insights into where, when, and why species move across a landscape. Although there has been an increasing emphasis on making animal movement data publicly available, there has also been a conspicuous dearth in the availability of such data on large carnivores. Globally, large predators are of conservation concern. However, due to their secretive behavior and low densities, obtaining movement data on apex predators is expensive and logistically challenging. Consequently, the relatively small sample sizes typical of large carnivore movement studies may limit insights into the ecology and behavior of these elusive predators. The aim of this initiative is to make available to the conservation-scientific community a dataset of 134,690 locations of jaguars (Panthera onca) collected from 117 individuals (54 males and 63 females) tracked by GPS technology. Individual jaguars were monitored in five different range countries representing a large portion of the species' distribution. This dataset may be used to answer a variety of ecological questions including but not limited to: improved models of connectivity from local to continental scales; the use of natural or human-modified landscapes by jaguars; movement behavior of jaguars in regions not represented in this dataset; intraspecific interactions; and predator-prey interactions. In making our dataset publicly available, we hope to motivate other research groups to do the same in the near future. Specifically, we aim to help inform a better understanding of jaguar movement ecology with applications towards effective decision making and maximizing long-term conservation efforts for this ecologically important species.
Jaguar Warrior Mask
Source: Objaverse 1.0 / Sketchfab
Jaguar
Ejercicio 2. Clase Fotogrametría Digital, ENAH. Source: Objaverse 1.0 / Sketchfab
Figure 1 in Space use and movement in western Paraguay of jaguar (Panthera onca)
Figure 1: Map showing the location of Paraguay in South America, the distribution of the Dry and Humid Chaco and Pantanal in western Paraguay (Olson et al. 2001) and study areas where jaguar movements were monitored.
Figure 2 in Space use and movement in western Paraguay of jaguar (Panthera onca)
Figure 2: Home range and movement parameters of male and female jaguars in the Dry Chaco and Humid Chaco/Pantanal. Boxes show the median and 25 and 75% percentiles with whiskers representing the data range within 1.5 times the distance of the box. Table 2: Probabilities based upon posterior distributions, that home range and movement parameters are different between sex and ecosystem, between sexes within systems, and between same sexes between systems.
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Allen Brain Atlas
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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.