Dataset Information

Modeling Potential Habitat for Amblyomma Tick Species in California.

ABSTRACT: The Amblyomma genus of ticks comprises species that are aggressive human biters and vectors of pathogens. Numerous species in the genus are undergoing rapid range expansion. Amblyomma ticks have occasionally been introduced into California, but as yet, no established populations have been reported in the state. Because California has high ecological diversity and is a transport hub for potentially parasitized humans and animals, the risk of future Amblyomma establishment may be high. We used ecological niche modeling to predict areas in California suitable for four tick species that pose high risk to humans: Amblyomma americanum, Amblyomma maculatum, Amblyomma cajennense and Amblyomma mixtum. We collected presence data in the Americas for each species from the published literature and online databases. Twenty-three climatic and ecological variables were used in a MaxEnt algorithm to predict the distribution of each species. The minimum temperature of the coldest month was an important predictor for all four species due to high mortality of Amblyomma at low temperatures. Areas in California appear to be ecologically suitable for A. americanum, A. maculatum, and A. cajennense, but not A. mixtum. These findings could inform targeted surveillance prior to an invasion event, to allow mitigation actions to be quickly implemented.

SUBMITTER: Pascoe EL

PROVIDER: S-EPMC6681388 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modeling Potential Habitat for Amblyomma Tick Species in California.

Pascoe Emily L EL Marcantonio Matteo M Caminade Cyril C Foley Janet E JE

Insects 20190708 7

The Amblyomma genus of ticks comprises species that are aggressive human biters and vectors of pathogens. Numerous species in the genus are undergoing rapid range expansion. Amblyomma ticks have occasionally been introduced into California, but as yet, no established populations have been reported in the state. Because California has high ecological diversity and is a transport hub for potentially parasitized humans and animals, the risk of future Amblyomma establishment may ...[more]

PMID: 31288467

Similar Datasets

Project description:The distribution, abundance and seasonal activity of vector species, such as ticks and mosquitoes, are key determinants of vector-borne disease risk, and are strongly influenced by abiotic and habitat conditions. Despite the numerous species of tick vectors in the heavily populated North American West Coast, all but Ixodes pacificus, the primary vector of the Lyme disease spirochete, is poorly characterized with regard to seasonal activity patterns and fine scale drivers of distribution and abundance, particularly in heavily populated regions of southern California. This lack of knowledge inhibits both scientific understanding and public health efforts to minimize vector exposure and risk of pathogen transmission to humans. Here we address this gap by characterizing the abiotic and habitat drivers of the distribution, abundance, and diversity of the vector tick community using fine scale temporal surveys over two seasons (2014 and 2015) across coastal and inland regions of Santa Barbara County, CA. We also characterize patterns of seasonal activity of the more common vector species to understand seasonality in risk of vector exposure, and specifically focus on human encounter risk using standardized tick drags as our method of collection. Leveraging plot-level habitat and abiotic variables in partial least squares regression analysis, we find the seven different vector species collected in this study have divergent drivers of activity and abundance. For example, I. pacificus is strongly associated with dense forest habitats and cool and moist microclimates, while Dermacentor occidentalis and Dermacentor variabilis, competent vectors of Rocky Mountain Spotted Fever, were found to be more tolerant of higher average temperatures and more open habitats. These results suggest that I. pacificus may be expected to experience reductions in geographic distribution and seasonal activity under projected land cover and climate change in coastal southern California, while D. occidentalis may experience more limited effects. We discuss implications for changing tick-borne disease risk associated with pathogens transmitted by Ixodes as well as Dermacentor species ticks in the western US, and contrast these predictions with eastern North America.

Project description:Our objective of this study was to explore the bacterial microbiome in fresh or fresh-frozen adult Amblyomma maculatum (Gulf Coast ticks) using extracts enriched for microbial DNA. We collected 100 questing adult A. maculatum, surface disinfected them, and extracted DNA from individual ticks collected the same day or after storage at -80?°C. Because only extracts with microbial DNA concentrations above 2?ng/?L were considered suitable for individual analysis, we expected fewer samples to meet these requirements. Of individual ticks extracted, 48 extracts met this minimum concentration. We pooled 20 additional extracts that had lower concentrations to obtain seven additional pools that met the minimum DNA concentration. Libraries created from these 55 samples were sequenced using an Illumina MiSeq platform, and data sets were analyzed using QIIME to identify relative abundance of microorganisms by phylum down to genus levels. Proteobacteria were in greatest abundance, followed by Actinobacteria, Firmicutes, and Bacteroidetes, at levels between 1.9% and 6.4% average relative abundance. Consistent with the Francisella-like endosymbiont known to be present in A. maculatum, the genus Francisella was detected at highest relative abundance (72.9%; SE 0.02%) for all samples. Among the top ten genera identified (relative abundance???0.5%) were potential extraction kit contaminants, Sphingomonas and Methylobacterium, the soil bacterium Actinomycetospora, and the known A. maculatum-associated genus, Rickettsia. Four samples had Rickettsia at greater than 1% relative abundance, while nine additional samples had Rickettsia at low (0.01-0.04%) relative abundance. In this study, we used the entire microbe-enriched DNA extract for whole ticks for microbiome analysis. A direct comparison of the microbiome in microbe-enriched DNA and total genomic DNA extracts from halves of the same tick would be useful to determine the utility of this extraction method in this system. We anticipate that future tick microbiome studies will be valuable to explore the influence of microbial diversity on pathogen maintenance and transmission, and to evaluate niche-specific microbiomes within individual tick tissues.

Project description:Technological advances increase opportunities for novel wildlife survey methods. With increased detection methods, many organizations and agencies are creating habitat suitability models (HSMs) to identify critical habitats and prioritize conservation measures. However, multiple occurrence data types are used independently to create these HSMs with little understanding of how biases inherent to those data might impact HSM efficacy. We sought to understand how different data types can influence HSMs using three bat species (Lasiurus borealis, Lasiurus cinereus, and Perimyotis subflavus). We compared the overlap of models created from passive-only (acoustics), active-only (mist-netting and wind turbine mortalities), and combined occurrences to identify the effect of multiple data types and detection bias. For each species, the active-only models had the highest discriminatory ability to tell occurrence from background points and for two of the three species, active-only models preformed best at maximizing the discrimination between presence and absence values. By comparing the niche overlaps of HSMs between data types, we found a high amount of variation with no species having over 45% overlap between the models. Passive models showed more suitable habitat in agricultural lands, while active models showed higher suitability in forested land, reflecting sampling bias. Overall, our results emphasize the need to carefully consider the influences of detection and survey biases on modeling, especially when combining multiple data types or using single data types to inform management interventions. Biases from sampling, behavior at the time of detection, false positive rates, and species life history intertwine to create striking differences among models. The final model output should consider biases of each detection type, particularly when the goal is to inform management decisions, as one data type may support very different management strategies than another.

Dataset Information

Modeling Potential Habitat for Amblyomma Tick Species in California.

Publications

Modeling Potential Habitat for <i>Amblyomma</i> Tick Species in California.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets