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Fig. 3 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA

Fig. 3. Average intensity of (a) Cyathocotyle bushiensis (Cb) and (b) Sphaeridiotrema spp. (Sg) metacercariae in each of the waterbodies studied in northcentral Minnesota during nine seasons in 2011‾2013 with 95% confidence intervals. Note that waterbody specific y-axis scales are used to highlight differences within a waterbody.

Fig. 1 in Diversity and prevalence of hemoparasites of wading birds in southern Florida, USA

Fig. 1. Plasmodium (Novyella) sp. stages observed in blood smear of a Glossy Ibis from Florida, USA that matched haplotype pMYCAME02. Representative trophozoites (*), erythrocytic meronts (arrow), macrogametocytes (double arrow), and microgametocytes (arrowhead) are marked. Some erythrocytes were infected with multiple parasites, e.g., (a) a cell with 4 trophozoites, (h) a cell with three early meronts, and (t) a cell with two early meronts. Scale bar = 10 Mm.

Fig. 2 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA

Fig. 2. Average prevalence of (a) Cyathocotyle bushiensis (Cb) and (b) Sphaeridiotrema spp. (Sg) metacercariae in each of the waterbodies studied in northcentral Minnesota during nine seasons in 2011‾2013 with 95% confidence intervals.

Fig. 1 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA

Fig. 1. Map of study area in northcentral Minnesota depicting the study lakes with county boundaries, within the state and USA.

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Fig. 1 in Prevalence survey and first molecular characterization of Echinococcus granulosus in France

Fig. 1 Origin of the hydatid cysts samples. In grey are the department surveyed. The numbers of cattle or sheep indicate the number and breeding species of infected animals by E. granulosus in each department

Fig. 2 in Prevalence of Borrelia burgdorferi sensu lato and Borrelia miyamotoi in ixodid ticks in the Far East of Russia

Fig. 2. Phylogenetic analysis of the nucleotide sequences of Borrelia 16S rRNA gene fragment of 733 bp long (A) and 5S‾23S ITS of 211–218 bp long (B) using Mega 6.06 software, UPGMA algorithm and 1,000 replications. Phylogenetic trees constructed by means of 5 alternative algorithms (Maximum likelihood, NeighborJoining, Minimum-Evolution, UPGMA and Maximum Parsimony) show similar topologies and reasonable bootstrap support. Nucleotide sequences of Borrelia isolates determined in our study are shown in bold. The number of identical sequences of Borrelia isolates determined in these ixodid ticks is shown in parentheses. Branches corresponding to the reference strains are underlined.

Fig. 3. A in Wild horse populations in south-east Australia have a high prevalence of Strongylus vulgaris and may act as a reservoir of infection for domestic horses

Fig. 3. A box and whisker plot (with individual data points) of the total strongyle egg counts across the different populations, showing the highest FECs were from samples from Bogong High Plains and Tin Mines, both alpine heathland habitats. Overall 89% of samples had FECs> 500 EPG, classed as 'high level shedders'.

Fig. 1 in Prevalence and co-infection with tick-borne Anaplasma phagocytophilum and Babesia spp. in red deer (Cervus elaphus) and roe deer (Capreolus capreolus) in Southern Norway

Fig. 1. Phylogenetic tree of Babesia isolates and samples of this study (●), based on fragments of 18S rRNA, generated using the Maximum-Likelihood clustering method in MEGA 6 software (1000 replicates; bootstrap values indicated at the nodes). Abbreviations: AU - Austria, BE - Belgium, CA - Canada, DE - Germany, FR - France, HU - Hungary, IT - Italy, JP - Japan, LT - Lithuania, NO - Norway, PL - Poland, RU - Russia, SK - Slovakia, SP - Spain, TU - Turkey, US - United States.

Fig. 3 in Persistent low avian malaria in a tropical species despite high community prevalence

Fig. 3. Maximum likelihood phylogenetic inference of (A) Haemoproteus and (B) Plasmodium from the Australasian region. Sequences were included if they were at least 479 nucleotides in length and were found to be unique from a pairwise distance analysis (see methods). Bootstrap support values are shown if greater than 50. Dots indicate the 14 lineages that were detected in this study and their colour denotes the bird species they occurred within [Purple = PCFW (M. c. coronatus), Red = RBFW (M. melanocephalus), Yellow = BSR (P. cerviniventris), Grey = WGH (L. unicolor)]. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2 in Persistent low avian malaria in a tropical species despite high community prevalence

Fig. 2. (A) Malarial parasite prevalence across years in four bird species, buff-sided robin (BSR, n = 66), purple-crowned fairy-wren (PCFW, n = 731), red-backed fairy-wren (RBFW, n = 78), white-gaped honeyeater (WGH, n = 25). Fisher's exact P-values test for annual differences in infection within each bird species. (B) Longitudinal sampling of infected PCFW adults (individuals presented were sampled more than twice and were identified as infected with Haemoproteus or Plasmodium). Dotted lines indicate uncertainty in years when no sample was available. Each individual was infected with a single lineage. (C) Percentage of individual PCFW infected within each age category. (D) Local phylogenetic relationship between parasite lineages, colours refer to host species as for (A). Maximum likelihood tree was inferred using GTR + G + I with 1000 bootstrap replicates; novel lineages are indicated by *. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Persistent low avian malaria in a tropical species despite high community prevalence

Fig. 1. Map of Australia and the Kimberly region. Sampling was conducted at the Australian Wildlife Conservancy's Mornington Wildlife Sanctuary (17̊31′S, 126̊6'E). Star indicates the location of the field site where samples were collected.

Fig. 2 in Wild horse populations in south-east Australia have a high prevalence of Strongylus vulgaris and may act as a reservoir of infection for domestic horses

Fig. 2. Microscopic view of the different eggs. A = Anoplocephala spp. eggs, S <90 = strongyle eggs <90 μm length, S> 90 = strongyle eggs ≥90 μm length, P = Parascaris spp. eggs.

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Fig. 2 in Prevalence of Capillaria plica in Danish wild carnivores

Fig. 2. The prevalence of Capillaria plica infections in red foxes per region of Denmark (positive red foxes/total number of red foxes examined). The origin of five red foxes was unknown.

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Fig. 1. A in Prevalence of Capillaria plica in Danish wild carnivores

Fig. 1. A typical barrel-shaped Capillaria plica egg in urine sediment from a red fox. The egg show a slightly pitted shell and two opercules with polar plugs. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

opencc-by-4.0Dec 2018View details →

Fig. 1 in Molecular characterization and prevalence of Halarachne halichoeri in threatened southern sea otters (Enhydra lutris nereis)

Fig. 1. (A) Scanning electron microscopy of adult Halarachne halichoeri showing opisthosoma (abdomen) with slight constriction only at the anterior end and dorsal shield broader posteriorly than anteriorly with linguiform caudal tip. (B) Scanning electron microscopy of larvae Halarachne halichoeri with postanal setae (bristles) longer than adanal setae.

opencc-by-4.0Apr 2018View details →

Fig. 5 in Prevalence and molecular characterisation of Acanthocephala in pinnipedia of the North and Baltic Seas

Fig. 5. Maximum likelihood tree based on COI sequences using the Jones-TaylorThornton (JTT) model. The log likelihood is −2479.70. The percentage of trees based on 1000 bootstrap replicates in which the associated taxa clustered together is shown next to the branches. GenBank accession numbers of analysed amino acid sequences are listed in Table 2.

opencc-by-4.0Apr 2018View details →

Fig. 1 in Prevalence and molecular characterisation of Acanthocephala in pinnipedia of the North and Baltic Seas

Fig. 1. Prevalence of acanthocephalan infections in harbour and grey seals from the German North and Baltic Seas between 1996 and 2012. Notations indicate the Acanthocephala positive and total number of examined Phoca vitulina (Pv) and Halichoerus grypus (Hg). Connecting lines indicate statistically significant differences between annual prevalences after Holm–Bonferroni correction (P ≤ 0.001).

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Fig. 1 in Variable changes in nematode infection prevalence and intensity after Rabbit Haemorrhagic Disease Virus emerged in wild rabbits in Scotland and New Zealand

Fig. 1. Differences in mean intensity of nematode parasite infection in rabbits sampled seasonally from New Zealand and Scotland before the spread of RHDV (a), rabbits sampled seasonally from Sotland before and after RHDV (b), and rabbits sampled in autumn season from New Zealand and Scotland before and after RHDV (c). Nematode parasites included T. retortaeformis (i) G. strigosum (ii) and P. ambiguus (iii) found in rabbits sampled in spring (Spr), summer (Sum), autumn (Aut) and winter (Win).

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Fig. 3 in Prevalence and molecular characterisation of Acanthocephala in pinnipedia of the North and Baltic Seas

Fig. 3. Phylogenetic analysis of the ribosomal ITS1-5.8S-ITS2-complex using the Maximum Likelihood method based on the Kimura 2-parameter model. The log likelihood is −16,028.00. The percentage of trees based on 1000 bootstrap replicates in which the associated taxa clustered together is shown next to the branches. GenBank accession numbers of analysed nucleotide sequences are listed in Table 1.