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opencc-zeroJan 2022View details →

Pacific Parasites Data - Life history mediates the association between parasite abundance and geographic features

1. Though parasites are ubiquitous in marine ecosystems, predicting the abundance of parasites present within marine ecosystems has proven challenging due to the unknown effects of multiple interacting environmental gradients and stressors. Furthermore, parasites often are considered as a uniform group within ecosystems despite their significant diversity. 2. We aim to determine the potential importance of multiple predictors of parasite abundance in coral reef ecosystems, including reef area, island area, human population density, chlorophyll-a, host diversity, coral cover, host abundance, and island isolation. 3. Using a model selection approach within a database of more than 1200 individual fish hosts and their parasites from 11 islands within the Pacific Line Islands archipelago, we reveal that geographic gradients, including island area and island isolation, emerged as the best predictors of parasite abundance. 4. Life history moderated the relationship; parasites with complex life cycles increased in abundance with increasing island isolation, while parasites with direct life cycles decreased with increasing isolation. Direct life cycle parasites increased in abundance with increasing island area, though complex life cycle parasite abundance was not associated with island area. 5. This novel analysis of a unique dataset indicates that parasite abundance in marine systems cannot be predicted precisely without accounting for the independent and interactive effects of each parasite's life history and environmental conditions.

Fig. 4 in Relationship of Dung Beetle (Coleoptera: Scarabaeidae and Geotrupidae) Abundance and Parasite Control in Cattle on Pastures throughout Maryland

Fig. 4. Random Forests (RF) predictor-based variable importance for total abundance of Onthophagus taurus, O. hecate, O. pennsylvanicus, Labarrus pseudolividus, and Blackburneus stercorosus in A) 2013 and B) 2015. Horizontal axes represent the eight predictor variables included in each RF model. Variable importance measures are reported as percentage increase in mean standard error (MSE) of model accuracy when the given predictor was removed from the model. Asterisks indicate significant predictors.

Fig. 3 in Relationship of Dung Beetle (Coleoptera: Scarabaeidae and Geotrupidae) Abundance and Parasite Control in Cattle on Pastures throughout Maryland

Fig. 3. Yearly totals by month and farm type for Blackburneus stercorosus in A) 2013, B) 2015 and Labarrus pseudolividus in C) 2013, D) 2015. Sampling months include May (M), June (first J), July (second J), August (A), September (S), and October (O). Mean abundance ± SE per month is shown across all sites (total abundance, gray bars), for sites that did not use chemicals (NCU, black), and for those with chemical usage (CU, blue). Letters are used to indicate the significant differences in total abundance among months. "SI" indicates a significant interaction between "month" and "farm type".

Fig. 2 in Relationship of Dung Beetle (Coleoptera: Scarabaeidae and Geotrupidae) Abundance and Parasite Control in Cattle on Pastures throughout Maryland

Fig. 2. Yearly abundance totals by month and farm type for dominant scarabaeine species: Onthophagus taurus in A) 2013 and B) 2015; O. pennsylvanicus in C) 2013 and D) 2015; and O. hecate in E) 2013 and F) 2015. Sampling months include May (M), June (first J), July (second J), August (A), September (S), and October (O). For each month, mean ± SE for total abundance measurements is shown with gray bars, as well as for sites using no chemicals (NCU, black) and those with chemical usage (CU, blue). Letters are used to indicate the significant differences in total abundance among months. Models with significant interactions (farm type*month) are indicated with a red "SI".

Fig. 1 in Relationship of Dung Beetle (Coleoptera: Scarabaeidae and Geotrupidae) Abundance and Parasite Control in Cattle on Pastures throughout Maryland

Fig. 1. Yearly abundance totals by month and farm type pooled across all scarabaeine and aphodiine species. Sampling months include May (M), June (first J), July (second J), August (A), September (S), and October (O). For each month, mean abundance ± SE across all farms (total abundance) is shown with gray bars. Letters indicate a significant difference. Mean abundance ± SE by farm type is also shown; sites using no chemicals (NCU) are black, and those with chemical usage (CU) are blue. Models with significant interactions (farm type*month) are indicated with a red "SI". Plots are as follows: A) Scarabaeine species in 2013, B) Aphodiine species in 2013, C) Scarabaeine species in 2015, and D) Aphodiine species in 2015.

opencc-zeroOct 2021View details →

Abundance of lungworm parasites in invasive cane toads from burned and unburned sites

The frequency and severity of wildfires are increasing due to anthropogenic modifications to habitats and to climate. Post-fire landscapes may advantage invasive species via multiple mechanisms, including changes to host-parasite interactions. We surveyed the incidence of endoparasitic lungworms (Rhabdias pseudosphaerocephala) in invasive cane toads (Rhinella marina) in near-coastal sites of eastern Australia, a year after extensive fires in this region. Both the prevalence of infection, and number of worms in infected toads, increased with toad body size in unburned areas. In contrast, parasite load decreased rather than increased with toad body size in burned areas. By killing moisture-dependent free-living lungworm larvae, the intense fires may have liberated adult cane toads from a parasite that can substantially reduce the viability of its host. Smaller toads, which are restricted to moist environments, did not receive this benefit from fires.

opencc-zeroDec 2022View details →

Data for: Genomic heterozygosity is associated with parasite abundance, but the effects are not mediated by host condition

Whether, when, and how genetic diversity buffers individuals and populations against infectious disease risk is a critical and open question for understanding wildlife disease and zoonotic disease risk. Several, but not all, studies have found negative relationships between infection and heterozygosity in wildlife. Since they can host multiple zoonotic infections, we sampled a population of wild deer mice (Peromyscus maniculatus), sequenced their genomes, and examined their fecal samples for coccidia and nematode eggs. We analyzed coccidia infection status, abundance, and coinfection status in relation to per-locus and per-individual measures of heterozygosity, as well as identified SNPs associated with infection status. Since heterozygosity might affect host condition, and condition is known to affect immunity, it was included as a co-variate in the per-individual analyses and as response variable in relation to heterozygosity. Not only did coccidia-infected individuals have lower levels of genome-wide per-locus diversity across all metrics, but we found an inverse relationship between genomic diversity and severity of coccidia infection. We also found weaker evidence that coinfected individuals had lower levels of private allelic variation than all other groups. In the per-individual analyses, relationships between heterozygosity and infection were marginal but followed the same negative trends. Condition was negatively correlated with infection, but was not associated with heterozygosity, suggesting that effects of heterozygosity on infection were not mediated by host condition in this system. Association tests identified multiple loci involved in the inflammatory response, with a particular role for NF-κB signaling, supporting previous work on the genetic basis of coccidia resistance. Taken together, we find that increased genome-wide neutral diversity, the presence of specific genetic variants, and improved condition positively impact infection status. Our results underscore the importance of considering host genomic variation as a buffer against infection, especially in systems that can harbor zoonotic diseases.

opennotspecifiedNov 2017View details →

FIG. 2 in Host-parasite relationships between a Malagasy fruit bat (Pteropodidae) and associated bat fly (Diptera: Nycteribiidae): seasonal variation of host body condition and the possible impact of parasite abundance

FIG. 2. Body Condition Index (BCI) of R. madagascariensis in the Grotte des Chauves-souris, Parc National d'Ankarana, based on five different field sessions and separated into the different age and sex classes. AF = adult female, AM = adult male, NF = neonate female, NM = neonate male, SAF = sub-adult female, SAM = sub-adult male

opennotspecifiedNov 2017View details →

FIG. 1 in Host-parasite relationships between a Malagasy fruit bat (Pteropodidae) and associated bat fly (Diptera: Nycteribiidae): seasonal variation of host body condition and the possible impact of parasite abundance

FIG. 1. Location map of the study site, Grotte des Chauves-souris, in the Parc National d'Ankarana, northern Madagascar