Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
427
datasets available to search
ShareScore release 0.9.0
Dataset results
427 results for “Ectoparasite”
Fig. 6 in Redescription of Argulus mongolianus (Crustacea: Branchiura: Argulidae), an Ectoparasite of Freshwater Fishes in East Asia, with Its First Record from Japan
Fig. 6. Argulus mongolianus, adult female (A and B), NSMT-Cr 29369, and adult male (C and D), NSMT-Cr 29370, from Micropterus salmoides in Lake Izunuma, Miyagi Prefecture, Japan. Ethanol-preserved specimens. A, C, Habitus, dorsal view; B, D, habitus, ventral view. The adult female and male were both collected on 2 June 2020 and photographed on 2 October 2021. Scale bars: A, 2 mm; B, 1 mm.
Fig. 3 in Redescription of Argulus mongolianus (Crustacea: Branchiura: Argulidae), an Ectoparasite of Freshwater Fishes in East Asia, with Its First Record from Japan
Fig. 3. Argulus mongolianus, adult female (different specimen shown in Fig. 1), NSMT-Cr 29371, from Micropterus salmoides in Lake Izunuma, Miyagi Prefecture, Japan. A, First leg, ventral view; B, distal part of endopod of first leg, ventral view; C, second leg, ventral view; D, third leg, ventral view; E, fourth leg, ventral view; F. natatory lobe, ventral view. Scale bars: A, C–E, 0.5 mm; B, F, 0.1 mm.
Fig. 5 in Redescription of Argulus mongolianus (Crustacea: Branchiura: Argulidae), an Ectoparasite of Freshwater Fishes in East Asia, with Its First Record from Japan
Fig. 5. Argulus mongolianus, adult male, NSMT-Cr 29372, from Micropterus salmoides in Lake Izunuma, Miyagi Prefecture, Japan. A, First leg, ventral view; B, distal part of endopod of first leg, ventral view; C, second leg, ventral view; D, third leg, ventral view; E, fourth leg, ventral view. Scale bars: A, C–E, 0.5 mm; B, 0.1 mm.
Fig. 3 in Molecular detection of Wolbachia endosymbiont in reptiles and their ectoparasites
Fig. 3 Phylogenetic relationship of Wolbachia detected in this study (in bold) and other available from GenBank belonging to different supergroups based on a partial sequence of the 16S rRNA gene. Evolutionary analysis was conducted on 1000 bootstrap replications using Maximum Likelihood method and Kimura 2-parameter model with discrete Gamma distribution (+ G) to model evolutionary rate differences among sites selected by best-fit model. GenBank accession number and host species are indicated
Fig. 4 in Body Size And Ectoparasitic Infestations In The Mediterranean Pond Turtle, Mauremys Leprosa (Testudines, Geoemydidae), In Majen Belahriti Pond (North-Eastern Algeria)
Fig. 4. Linear regression of body weight (BW) on carapace length (CL) for Mauremys leprosa (N = 43).
Figure 3 in Host conservation through their parasites: molecular surveillance of vector-borne microorganisms in bats using ectoparasitic bat flies
Figure 3. Comparison of detected microorganism prevalence (prevalence of infection) between bats and bat flies. Different bars represent hosts (black), all bat flies (dark grey), and consensus fly results, meaning that at least one infected fly individual was present on the host (light grey).
Figure 2 in Host conservation through their parasites: molecular surveillance of vector-borne microorganisms in bats using ectoparasitic bat flies
Figure 2. Prevalence of Bartonella spp., Polychromophilus spp., and Trypanosoma spp. infection in nycteribiid flies collected from 28 bats, which carried between 2 and 7 flies. Black: all flies are infected, dark grey: all flies are non-infected, light grey: both infected and non-infected flies occurred on the same host.
Figure 1 in Host conservation through their parasites: molecular surveillance of vector-borne microorganisms in bats using ectoparasitic bat flies
Figure 1. Number of detected vector-borne microorganisms in bats (A) and bat flies (B). Black colour corresponds to Miniopterus natalensis (A), and Nycteribia schmidlii scotti (B), whereas grey shows Miniopterus schreibersii (A) and Nycteribia schmidlii (B).
Fig. 2 in Trichodinid Ectoparasites (Ciliophora: Peritrichia) of Non-native Pumpkinseed (Lepomis gibbosus) in Europe
Fig. 2. Trichodina cf. heterodentata Dunkan, 1977. A – silver impregnated photomicrograph; B – dentical diagram. Scale: 20 μm.
Fig 1. Trichodina acuta Lom, 1961. A in Trichodinid Ectoparasites (Ciliophora: Peritrichia) of Non-native Pumpkinseed (Lepomis gibbosus) in Europe
Fig 1. Trichodina acuta Lom, 1961. A – silver impregnated photomicrograph; B – dentical diagram. Scale: 20 μm.
FIGURE 1 in Ectoparasitic flies (Diptera, Streblidae) on bats (Mammalia, Chiroptera) in a dry tropical forest in the northern Colombia
FIGURE 1: Study sites of host-ectoparasite relationship between Streblidae and bats in Colombia. Darker areas correspond to higher altitudes.
Fig. 2 in Enhanced understanding of ectoparasite-host trophic linkages on coral reefs through stable isotope analysis
Fig. 2. Stable carbon and nitrogen isotope data for Haemulon flavolineatum blood vs. P3 (A and B), blood vs. adult gnathiids (C and D), and P3 vs. adult gnathiids (E and F). Solid triangles represent males and P3s, open triangles represent females. Error bars represent 1 SE of N = 5 individual P3 gnathiids analysed from each fish. Dashed line represents 1:1 linear relationship.
Fig. 1 in Enhanced understanding of ectoparasite-host trophic linkages on coral reefs through stable isotope analysis
Fig. 1. Mean δ13C and δ15N (±1 Standard Error) values of gnathiids (open squares), (A) Haemulon flavolineatum heart (grey diamond), blood (white diamond), and muscle (black diamond), Pederson shrimp (Ancylomenes pedersoni, open triangle), and Anilocra isopods (cross), (B) Stegastes diencaeus heart (grey diamond), and muscle (black diamond), and Pederson shrimp (open triangle), and (c) Holocentrus adscenscionis heart (grey diamond), and muscle (black diamond), and Anilocra isopods (cross).
Fig. 7 in Using occupancy models to investigate the prevalence of ectoparasitic vectors on hosts: An example with fleas on prairie dogs
Fig. 7. Probabilities of flea occupancy (W) for black-tailed prairie dogs (Cynomys ludovicianus) in differing body condition during May–September 2011, at the Vermejo Park Ranch, New Mexico. The solid line depicts estimates of occupancy and dotted lines depict 95% confidence intervals.
Fig. 4 in Using occupancy models to investigate the prevalence of ectoparasitic vectors on hosts: An example with fleas on prairie dogs
Fig. 4. Model-averaged probabilities for detecting fleas (p) on a black-tailed prairie dog (Cynomys ludovicianus) during May–September 2011, at the Vermejo Park Ranch, New Mexico. Bars depict 95% confidence intervals.
Fig. 3 in Using occupancy models to investigate the prevalence of ectoparasitic vectors on hosts: An example with fleas on prairie dogs
Fig. 3. Indices for and estimates of flea prevalence on prairie dogs inside old colonies. The estimates are model-averaged values from occupancy models that accounted for imperfect detection of fleas. The naïve indices do not consider imperfect detection. Gains in precision (95% confidence interval) when estimating prevalence are depicted on the right. Confidence intervals for the estimates of prevalence during July–September are very small.
Fig. 2 in Using occupancy models to investigate the prevalence of ectoparasitic vectors on hosts: An example with fleas on prairie dogs
Fig. 2. The robust design for occupancy models of flea prevalence on black-tailed prairie dogs (Cynomys ludovicianus). Prairie dogs were sampled during primary occasions in different months of the year (May–September 2012). Each primary occasion comprised three secondary occasions (combings) during which fleas might be detected (p = probability of detection, given presence). A prairie dog was ''open'' to colonization by fleas between primary occasions. Once a prairie dog was colonized, it was occupied by fleas during all subsequent primary occasions (thus, the extinction probability, E, was fixed at zero, once a prairie dog was occupied by fleas). Closure was assumed during the secondary occasions, but we used behavioral covariates to account for removal of fleas from hosts during each secondary combing (REMOVAL1 and REMOVAL2, see text). In the example encounter history, a '1' indicates that at least one flea was detected during a combing event, and a '0' indicates that no fleas were detected.
Fig. 5 in Using occupancy models to investigate the prevalence of ectoparasitic vectors on hosts: An example with fleas on prairie dogs
Fig. 5. Model-averaged probabilities of flea occupancy (W) and flea colonization (γ) for black-tailed prairie dogs (Cynomys ludovicianus) in old and young colonies, and natural and translocation colonies during May–September 2011, at the Vermejo Park Ranch, New Mexico (see Fig. 1 and text for colony descriptions). Bars depict 95% confidence intervals. We do not report estimates of colonization for September, because few prairie dogs were sampled in that month.
Fig. 1 in Using occupancy models to investigate the prevalence of ectoparasitic vectors on hosts: An example with fleas on prairie dogs
Fig. 1. Map of the study area within the Vermejo Park Ranch, Colfax County, New Mexico, showing old and young, and natural and translocation colonies of black-tailed prairie dogs (Cynomys ludovicianus). Gray areas indicate extent of prairie dog colonies in 2009.
Fig. 1 in Testing the robustness of transmission network models to predict ectoparasite loads. One lizard, two ticks and four years
Fig. 1. Transmission networks generated with (a) a short time window of infection; and (b) a long time window of infection, from the GPS location data of the lizards in the study population in 2010. Nodes represent individual lizards and edges between nodes are directed towards the lizard that is at risk of infection. The edges are weighted as described in the main text and the thicker the line the more weight is associated with that edge.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.