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Fig. 3 in Do invasive cane toads affect the parasite burdens of native Australian frogs?

Fig. 3. (A) Prevalence (% of anurans infected) and (B) intensity (mean number of cysts and worms per infected host) of parasitic larval nematodes in cane toads and native anurans from northern NSW. Bars represent standard errors.

Fig. 2 in Do invasive cane toads affect the parasite burdens of native Australian frogs?

Fig. 2. (A) Prevalence (% of anurans infected) and (B) intensity (mean number of worms per infected host) of parasitic lungworms in anurans from cane toadpresent, and cane toad-absent areas in northern NSW. Bars represent standard errors.

Fig. 3. A in What drives population-level effects of parasites? Meta-analysis meets life-history

Fig. 3. A meta-regression (random effects model) of effect size against host average lifespan using the complete dataset (n = 60). The slope of this regression is significant (p = 0.05).

Fig. 2 in Networks and the ecology of parasite transmission: A framework for wildlife parasitology

Fig. 2. How do we use networks to understand the ecology of parasite transmission? Networks allow us to describe how the behaviour of individuals collectively affects the transmission of parasites within wildlife populations. They provide a flexible framework that enables analysis at three different levels; individual (panel A), dyadic (pair-wise associations) (panel B) and the network (population) level (panel C). Within each level of analysis, there are different metrics and analytical approaches that can be used to explore the ecology of parasite transmission.

Fig. 1 in Networks and the ecology of parasite transmission: A framework for wildlife parasitology

Fig. 1. What is a network? A network in its most elementary form is an adjacency matrix, where row and column labels represent the individuals in the network, and the remaining cells represent the pair-wise associations among individuals in the network (panel A). These associations can be weighted, as below (panel A), where stronger relationships are assigned a higher value (for example, the duration or frequency of contact). They can also be directed, to reflect the direction of the association; in this instance, the direction of possible parasite transmission. In this case, rows represent donor nodes, and columns represent recipient nodes (e.g., in panel A: from node C (donor) to node D (recipient), there is a score of 1). The matrix can be visualised as a network diagram (panel B), consisting of nodes, which represent the epidemiological unit of interest (usually individuals) connected together by a series of edges representing the measure of association (the potential for parasite transmission). In context of understanding the ecology of parasite transmission, edges represent a 'contact' between two hosts that provides an opportunity for parasite transfer. The weighting of edges represents the likelihood of parasite transmission (e.g., the frequency or intensity of contact among hosts). The definition of a contact will depend on the type of parasite considered, and how it is passed from one host to another.

Fig. 1. A in Neglected wild life: Parasitic biodiversity as a conservation target

Fig. 1. A conceptual framework for parasite conservation. Practitioners should establish conservation priorities (here we show the prioritization categories in Gómez et al., 2012) and design conservation strategies using a combination of interrelated approaches.

Fig. 1 in Co-invaders: The effects of alien parasites on native hosts

Fig. 1. Schematic diagram of processes involved in species invasions and coinvasions. (a) Free-living aliens. The light blue oval shape represents a new area, outside the natural range of the alien species, shown in red. Arrows indicate movement of alien species through the phases of introduction, establishment and invasion of the habitat of the native species, shown in blue. Vertical bars represent barriers to be overcome in each phase. (b) Parasitic aliens. The alien host species (in red) contains an alien parasite species. The alien parasite goes through the processes of introduction, establishment and spread with its original host and then switches to a native host species (in blue) to become a co-invader. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 1. 2D in Proteomic profile of Ortleppascaris sp.: A helminth parasite of Rhinella marina in the Amazonian region

Fig. 1. 2D gel containing the somatic extract of Ortleppascaris sp. larvae. See Table 1 for details.

Fig. 2 in A walk on the tundra: Host-parasite interactions in an extreme environment

Fig. 2. Representation of historical drivers for host and parasite distributions across North America during the Last Glacial Maximum and the post-Pleistocene. The map depicts the current geography of the continent showing an overlay of the maximum extent of past glaciations, pathways for expansion and episodic range shifts by ungulates and parasitic nematodes, and the contemporary distributions of caribou of the migratory Dolphin and Union herd, and of the sedentary Kangerlussuaq-Sisimiut and AkiaManiitsoq herds of West Greenland.

Fig. 1 in A walk on the tundra: Host-parasite interactions in an extreme environment

Fig. 1. The parasite fauna of Arctic ungulates has been shaped by historical and contemporary processes. Today, the Arctic today is characterized by extremes in temperature, high seasonality, and low host species diversity and abundance. Rapid climate warming is now a dominant feature that is altering host–parasite interactions in several ways. Temperatures directly affect parasite development and survival in the environment and in ectotherm hosts, and although warming temperatures may initially accelerate transmission, they may quickly exceed the upper thermal tolerance limits for some arctic parasites. Using the Metabolic Theory of Ecology, temperature dependencies can be modeled and generalized to provide broader insights across genera and ecological regions. Climate changes may also alter both host and parasite life-history strategies and phenology, including migration patterns, leading to non-linear changes and tipping points in transmission ecology. Climate warming and associated changes in the cryosphere also alters ecological barriers and corridors, leading to range shifts and new contact zones.

Fig. 1 in Experimental manipulation reveals few subclinical impacts of a parasite community in juvenile kangaroos

Fig. 1. Mean faecal egg counts for control and anthelmintic-treated juvenile eastern grey kangaroos in two periods post-capture (12–33 days) and initial treatment (40– 90 days) at the Anglesea Golf Club, Victoria, Australia, from March to May 2012. Bars indicate standard errors. It was not always possible to sample each individual in each period; numbers on columns indicate sample size for each time period.

Fig. 2 in Co-invaders: The effects of alien parasites on native hosts

Fig. 2. (a) Relative proportions of taxa represented in 98 examples of co-introduced parasites: prokaryotes (viruses and bacteria); protozoans; helminths (platyhelminths, nematodes and acanthocephalans); arthropods (crustaceans, arachnids); and a miscellaneous group including fungi, myxozoans, annelids, molluscs and pentasomids. (b) Relative proportions of alien hosts represented in 98 examples of cointroductions: molluscs; arthropods; fishes; mammals; and other vertebrates (amphibians, reptiles and birds). (c) Number of co-introduced parasite species with direct and indirect life cycles which have switched (black bars) or not switched (white bars) from alien to native host species.

Fig. 4 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy

Fig. 4. Predicted mean and standard error body condition scores show associations with infection presence and season, with co-infected buffalo in much lower condition in the early wet season (Table S2). Coccidia infection status is represented with C– and C+; nematode infection status is represented with N– and N+.

Fig. 5 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy

Fig. 5. Season and co-infection differences in nematode aggregation. (a) Aggregation patterns in calves (b) and non-calves. (c) In non-calves, the distribution of nematode parasites in the late wet season shows that k is not significantly different in coccidia positive vs. negative buffalo. (d) In the early wet season coccidia positive buffalo have a truncated distribution, resulting in significantly reduced aggregation. Arrows indicate nematode intensity values in the tail of the distribution of coccidia negative buffalo. Coccidia infection status is represented with C– and C+.

Fig. 3 in Global diversity of fish parasitic isopod crustaceans of the family Cymothoidae

Fig. 3. Representative cymothoid forms. Mothocya (A); Olencira (B); Norileca (C); Anilocra (D); Nerocila (E); Telotha (F); Cymothoa (G); Cinusa (H); Ceratothoa (I); Agarna (J, K). Scale bars = 5 mm.

Fig. 2 in Global diversity of fish parasitic isopod crustaceans of the family Cymothoidae

Fig. 2. Different attachment sites of cymothoids. External or scale attaching (A), flesh-burrowing (B) buccal dwelling (C, E, F) and gill attaching (D).

Fig. 3 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy

Fig. 3. Patterns of parasite egg/oocyst counts with co-infection for (a) nematodes and (b) coccidia. (c), the mean nematode intensity in calves is higher in early wet season than in the late wet season independent of co-infection with coccidia. (d) Co-infection with coccidia alters the seasonal patterns of nematode intensity in non-calf buffalo (>1 year, juvenile through senescent). Calf vs. non-calf division is based on model paramters (Table 1).

Fig. 2 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy

Fig. 2. Age specific patterns of parasite prevalence with co-infection. (a) Prevalence of nematodes is higher in buffalo co-infected with coccidia (C+) compared to coccidia negative buffalo (C–) in all age categories (N = 33, 318, 166, 272, 162 for calf, juvenile, subadult, adult and senescent C– buffalo; N = 58, 237, 55, 54, 20 for C+ buffalo). (b) Prevalence of coccidia is higher in buffalo co-infected with nematodes (N+) compared to nematode negative buffalo (N–) in calf, juvenile, subadult, and senescent buffalo but not adult buffalo (N = 13, 107, 92, 144, 56 for calf, juvenile, subadult, adult and senescent N– buffalo; N = 38, 448, 129, 208, 100 for N+ buffalo).

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Fig. 5 in Heartworm and seal louse: Trends in prevalence, characterisation of impact and transmission pathways in a unique parasite assembly on seals in the North and Baltic Sea

Fig. 5. Scanning electron microscopic images of E. horridus attached to seal skin and fur. A: E. horridus utilizing a hair follicle of harbour seal skin. B: E. horridus attached to seal hair with the head pointing towards seal skin. C: E. horridus with six claws attached to seal fur. D: Close up of an unattached claw of E. horridus. Asterisks positioned on nits of E. horridus. Sale bars: A 200 μm, B 400 μm, C 400 μm, D 100 μm.

Fig. 4 in Global diversity of fish parasitic isopod crustaceans of the family Cymothoidae

Fig. 4. Number of marine Cymothoidae in biogeographic regions (Marine Ecoregions of the World). Data from Poore and Bruce (2012).