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Fig. 4 in Do managed bees drive parasite spread and emergence in wild bees?

Fig. 4. Overview of parasite detection in managed bees in North America and likely instances of parasite transmission between managed and wild bumblebees.

Fig. 3 in Do managed bees drive parasite spread and emergence in wild bees?

Fig. 3. Overview of parasite detection in managed bees in Japan and likely instances of parasite transmission between managed and wild bumblebees.

Fig. 5 in Do managed bees drive parasite spread and emergence in wild bees?

Fig. 5. Overview of parasite detection in managed bees in the British Isles and likely instances of parasite transmission between managed and wild bumblebees.

Fig. 3 in Temporal stability of parasite distribution and genetic variability values of Contracaecum osculatum sp. D and C. osculatum sp. E (Nematoda: Anisakidae) from fish of the Ross Sea (Antarctica)

Fig. 3. Schematic representation of the hypothetic life-cycle of C. osculatum sp. D (a) and C. osculatum sp. E (b) in the Ross Sea.

Fig. 2 in Seasonal variation in the abundance and distribution of ticks that parasitize Microcebus griseorufus at the BezàMahafaly Special Reserve, Madagascar

Fig. 2. Differences in infestation rates at Parcel 1 by A) sex B) substrate C) males and substrate and D) females and substrate. * indicates P <0.05, **P <0.01; ***P <0.001 and compares variables on the x-axis.

Fig. 2 in Do managed bees drive parasite spread and emergence in wild bees?

Fig. 2. Highlighting the three main mechanisms that influence parasite infections between managed and wild bee populations. Arrows represent direction of potential parasite spread as a result of the mechanism.

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Fig. 1 in Reduced helminth parasitism in the introduced bank vole (Myodes glareolus): More parasites lost than gained

Fig. 1. Frequency distribution of intestinal helminth species richness in wood mice and bank voles examined in 2011 and 2012.

Fig. 1 in Do managed bees drive parasite spread and emergence in wild bees?

Fig. 1. The key factors that may drive disease emergence within and between populations of managed and wild bees. Adapted from Daszak et al. (2000).

Fig. 2 in Past, present and future of host‾parasite co-extinctions

Fig. 2. Comparison between helminth parasite diversity (for Acantocephala, Cestoda, Monogenea, Nematoda and Trematoda) in vertebrates (amphibians, birds, fish, mammals and reptiles) estimated using, respectively, the approach by Poulin and Morand (2004) (dark grey) and the more recent approach proposed by Strona and Fattorini (2014a) (light grey). Data were obtained from Table 1 in Strona and Fattorini (2014a).

Fig. 7 in Past, present and future of host‾parasite co-extinctions

Fig. 7. Schematic representation of the possible different parasitological consequences of a biological invasion. A: The invader loses its parasite and does not get local parasites; B: The invader loses its parasites and gets new ones from native hosts; C: The invader retains its parasites and these establish new symbioses with local species; D: The invader retains its parasites and acquire new parasites from local hosts; its parasites establish new symbioses with local host species; E: The invader does not lose its parasites, does not get new ones from native hosts, and its parasites do not expand their host range.

Fig. 6 in Past, present and future of host‾parasite co-extinctions

Fig. 6. Example of asymmetry of interactions as observed in all host parasite records available from FishPest dataset (Strona and Lafferty, 2012). The graph shows the relationship between the maximum specificity of the parasites using a certain host species, and the parasite richness on that host species. Boxplots correspond to different classes of hosts identified on the basis of the maximum specificity of their parasites. Thus, the first boxplot provides information on parasite species richness of all fish species whose most specific parasite uses just one host. It is apparent that specific parasites tend to use hosts harboring many parasites, while species-poor parasitofaunas are often composed by generalist parasites. Boxes indicate first and third quartiles, whiskers indicate range values, and horizontal lines indicate median values.

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Fig. 3 in Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds

Fig. 3. Bayesian phylogenetic tree of haemosporidian mtDNA cytochrome b haplotypes isolated from Alaskan grouse and ptarmigan species. Node tips are labeled with abbreviation for parasite genus (Haem = Haemoproteus, Leuc = Leucocytozoon, and Plas = Plasmodium), followed by the lineage name, GenBank accession number for each lineage, and avian (Phas = Phasianidae, Anat = Anatiade, Turd = Turdidae, Paru = Parulidae, Scol = Scolopacidae, Embe = Emberizidae, and Frin = Fringillidae) or invertebrate (Simu = Simuliidae) host family. All haplotypes identified in this study are highlighted in red and asterisks following tip labels indicate a lineage that was isolated from Alaskan bird hosts. Numbers on branches indicate posterior probabilities from our analysis. All reference sequences were obtained from the National Center for Biotechnology Information website or the MalAvi database. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Fig. 2. Minimum spanning network for haemosporidian mtDNA cytochrome b in Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds

Fig. 2. Minimum spanning network for haemosporidian mtDNA cytochrome b haplotypes isolated from Alaskan grouse and ptarmigan species. Dark circles represent un-sampled nodes. All circles are proportional to the frequency at which the haplotypes were detected. Lines between nodes are drawn to scale based on the number of nucleotide mutations unless otherwise indicated by hash marks.

Fig. 5 in Past, present and future of host‾parasite co-extinctions

Fig. 5. Graph showing the relationship between fish parasite specificity and the corresponding average vulnerability of the hosts used by those parasites. Data were obtained using the same data and procedure as in Strona et al. (2013), computing mean host vulnerability values for different parasite host range classes. Differently from Strona et al. (2013), however, classes were defined using a logarithmic progression instead of a geometric one, resulting in an even tighter relationship between log(host range) and mean host vulnerability (rs = 0.93; p <0.05).

Fig. 3 in Past, present and future of host‾parasite co-extinctions

Fig. 3. Distribution of parasite specificity expressed as the logarithm of host range size in fish (A) and terrestrial vertebrates (B). Data for fish parasites (Acantocephala, Cestoda, Monogenea, Nematoda and Trematoda) were collected from FishPest (Strona and Lafferty, 2012). Data for parasites of terrestrial vertebrates (Acantocephala, Cestoda, Nematoda and Trematoda for amphibians, birds, mammals and reptiles) were collected from the Natural Museum History database (http://www.nhm.ac.uk). Since (as to June 11th 2015) all amphibians in the database are erroneously classified as reptiles, information was corrected using Catalogue of Life (http://www.catalogueoflife.org/). Y-axes indicate parasite species numbers.

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Fig. 1 in Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds

Fig. 1. Map of Alaskan sampling regions assembled from multiple game management units and sub-units. Regions were grouped for analysis of haemosporidian prevalence as follows: southcoastal (Kenai Peninsula and southeastern Alaska; GMUs 1C, 1D, 2, 7, 15A, 15B, and 15C), southcentral (Anchorage area and Matanuska-Susitna Valley; GMUs 13A, 13D, 14A, 14C, 16A, and 16B), southwestern (Bristol Bay, Alaska Peninsula, and eastern Aleutian islands; 9D, 9E, and 17C), southern interior (south side of Alaska Range; GMUs 12, 13B, and 13E), northern interior (north side of Alaska Range; GMUs 20A-20E and 25C), and Seward Peninsula (GMU 22C).

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Fig. 3 in Behavioral, physiological and morphological correlates of parasite intensity in the wild Cururu toad (Rhinella icterica)

Fig. 3. Association between locomotor performance and pulmonary parasite intensity in Rhinella icterica (N = 20; r = –0.49, P = 0.03). SVL = snout-vent length.

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Fig. 2 in Temporal and demographic blood parasite dynamics in two free-ranging neotropical primates

Fig. 2. Individual infection status by parasite by year. Strength and thickness of lines are scaled to the number of individuals that took a given infection trajectory from one year to the next. Two diagonal lines span 2012‾2014 because those individuals were not sampled in 2013. The + symbols represent every infection or non-infection found across all individuals in the study.

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Fig. 3 in Temporal and demographic blood parasite dynamics in two free-ranging neotropical primates

Fig. 3. Parasite species richness by species, age class and sex. Colors represent females (black) and males (gray).