27 research outputs found

    The expanding distribution of Ixodes scapularis and associated pathogens in the Chicago, IL, metropolitan area

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    The geographic distribution of Lyme disease in the United States has increased considerably since the first description of the illness in the 1970s. The primary vector of Lyme disease, the tick Ixodes scapularis (Acari: Ixodidae), has expanded its range concurrently with the disease including into urban landscapes. To investigate landscape factors that may influence the colonization of I. scapularis and its associated pathogens in an urban ecosystem, 45 sites were sampled along three transects spanning the urban-to-rural human land use gradient in the Chicago, Illinois, metropolitan area. I collected four species of ticks (88% were I. scapularis) which exhibited variable infection rates for six pathogens, including Borrelia burgdorferi, the causative agent of Lyme disease, and B. lonestari and B. miyamotoi, both reported for the first time in Illinois. Logistic regression modeling indicated the presence of I. scapularis was positively correlated with forest land cover and negatively correlated with developed land cover, while the presence of B. burgdorferi was positively correlated with forest land cover. Neither the presence of the tick or the pathogen were correlated with distance to the nearest major river way. This study suggests that the range of I. scapularis and its pathogens have expanded in the Chicago metropolitan area since previous studies were conducted, including into forested urban areas near to the urban core. As tick and pathogen continue to colonize new areas, active monitoring and increased public education will be needed to protect vulnerable human populations

    Datasheets

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    The zipped folder contains 9 csv files used for data analysis of tick counts. ALL_ALL refers to counts of all tick species for all treatments (a subset of five months). ALL_LC refers to counts of all tick species for Total exclosures vs. Control plots. RHPR_ALL and RHPR_LC are data for Rhipicephalus praetextatus for all treatments and Total vs. Control plots, respectively. RHPU_ALL and RHPU_LC are data for Rhipicephalus pulchellus. RHPV_ALL and RHPV_LC are data for Rhipicephalus pravus. Pathogens_CB_R contain data on Coxiella burnetii and Rickettsia pathogen infection in ticks. Column headers are Period: The month that ticks were collected, starting from October 2013. Level: The geographic location of the exclosure treatment. 1 = Southern, mesic region, 2 = Central, intermediate region, 3 = North, arid region. Replicate: Numbered 1-9, the identity of replicated plot treatments. Treatment: The type of exclosure - LMH = Total exclosure, CONT = control, MESO = exclusion of all herbivores >15kg, MEGA = exclusion of elephant and giraffe. Rain = Mean annual rainfall at each level (mm/year)

    Data from: Interacting effects of wildlife loss and climate on ticks and tick-borne disease

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    Both large-wildlife loss and climatic changes can independently influence the prevalence and distribution of zoonotic disease. Given growing evidence that wildlife loss often has stronger community-level effects in low-productivity areas, we hypothesized that these perturbations would have interactive effects on disease risk. We experimentally tested this hypothesis by measuring tick abundance and the prevalence of tick-borne pathogens (Coxiella burnetii and Rickettsia spp.) within long-term, size-selective, large-herbivore exclosures replicated across a precipitation gradient in East Africa. Total wildlife exclusion increased total tick abundance by 130% (mesic sites) to 225% (dry, low-productivity sites), demonstrating a significant interaction of defaunation and aridity on tick abundance. When differing degrees of exclusion were tested for a subset of months, total tick abundance increased from 170% (only mega-herbivores excluded) to 360% (all large wildlife excluded). Wildlife exclusion differentially affected the abundance of the three dominant tick species, and this effect varied strongly over time, likely due to differences among species in their host associations, seasonality, and other ecological characteristics. Pathogen prevalence did not differ across wildlife exclusion treatments, rainfall levels, or tick species, suggesting that exposure risk will respond to defaunation and climate change in proportion to total tick abundance. These findings demonstrate interacting effects of defaunation and aridity that increase disease risk, and they highlight the need to incorporate ecological context when predicting effects of wildlife loss on zoonotic disease dynamics

    Lung perfusion imaging in small animals using 4D micro-CT at heartbeat temporal resolution

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    Purpose: Quantitative in vivo imaging of lung perfusion in rodents can provide critical information for preclinical studies. However, the combined challenges of high temporal and spatial resolution have made routine quantitative perfusion imaging difficult in small animals. The purpose of this work is to demonstrate 4D micro-CT for perfusion imaging in rodents at heartbeat temporal resolution and isotropic spatial resolution

    Supplementary Materials from Interacting effects of wildlife loss and climate on ticks and tick-borne disease

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    Both large-wildlife loss and climatic changes can independently influence the prevalence and distribution of zoonotic disease. Given growing evidence that wildlife loss often has stronger community-level effects in low-productivity areas, we hypothesized that these perturbations would have interactive effects on disease risk. We experimentally tested this hypothesis by measuring tick abundance and the prevalence of tick-borne pathogens (<i>Coxiella burnetii</i> and <i>Rickettsia</i> spp<i>.</i>) within long-term, size-selective, large-herbivore exclosures replicated across a precipitation gradient in East Africa. Total wildlife exclusion increased total tick abundance by 130% (mesic sites) to 225% (dry, low-productivity sites), demonstrating a significant interaction of defaunation and aridity on tick abundance. When differing degrees of exclusion were tested for a subset of months, total tick abundance increased from 170% (only mega-herbivores excluded) to 360% (all large wildlife excluded). Wildlife exclusion differentially affected the abundance of the three dominant tick species, and this effect varied strongly over time, likely due to differences among species in their host associations, seasonality and other ecological characteristics. Pathogen prevalence did not differ across wildlife exclusion treatments, rainfall levels or tick species, suggesting that exposure risk will respond to defaunation and climate change in proportion to total tick abundance. These findings demonstrate interacting effects of defaunation and aridity that increase disease risk, and they highlight the need to incorporate ecological context when predicting effects of wildlife loss on zoonotic disease dynamics
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