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Additional file 1: Table S1. SIMPER analysis of the major bacterial OTUs driving differences between sample treatments (mosquito species and life stage). The Bray-Curtis average dissimilarity between sample treatments was >1% for 18 bacterial taxa. Overall average dissimilarity. CXP.EG – Cx. pipiens egg raft samples; CXP.MG – Cx. pipiens midgut samples; CXR.EG – Cx. restuans egg raft samples; CXR.MG – Cx. restuans midgut samples. Figure S1. Rarefaction curve analysis of observed richness of bacterial OTUs of samples from Cx. pipiens and Cx. restuans midgut and egg samples. Figure S2. Venn diagrams showing the number of unique and shared bacterial OTUs between egg and midgut samples of Cx. restuans and Cx. pipiens. a Venn analysis of bacterial OTUs from all four sample types. b Venn analysis of bacterial OTUs from Cx. pipiens and Cx. restuans midgut samples. c Venn analysis of bacterial OTUs from Cx. pipiens and Cx. restuans egg samples. d Venn analysis of bacterial OTUs from Cx. pipiens eggs and midguts. e Venn analysis of Cx. restuans egg and midgut samples.

Lyme disease, the most prevalent vector-borne disease in North America, is increasing in incidence and geographic distribution as the tick vector, Ixodes scapularis, spreads to new regions. We re-construct the spatial-temporal invasion of the tick and human disease in the midwestern U.S., a major focus of Lyme disease transmission, from 1967 to 2018, to analyse the influence of spatial factors on the geographic spread. A regression model indicates that three spatial factors—proximity to a previously invaded county, forest cover and adjacency to a river—collectively predict tick occurrence. Validation of the predictive capability of this model correctly predicts counties invaded or uninvaded with 90.6% and 98.5% accuracy, respectively. Reported incidence increases in counties after the first report of the tick; based on this modelled relationship, we identify 31 counties where we suspect I. scapularis already occurs yet remains undetected. Finally, we apply the model to forecast tick establishment by 2021 and predict 42 additional counties where I. scapularis will likely be detected based upon historical drivers of geographic spread. Our findings leverage resources dedicated to tick and human disease reporting and provide the opportunity to take proactive steps (e.g. educational efforts) to prevent and limit transmission in areas of future geographic spread.

Ecological traps occur due to a mismatch between a habitat's attractiveness and quality, wherein organisms show preference for low-quality habitats over other available high-quality habitats. Our previous research identified leaf litter from common blackberry (Rubus allegheniensis) as a natural ecological trap for an important vector for West Nile virus (Culex pipiens), attracting mosquitoes to oviposit in habitats deleterious to the survival of their larvae. Here we demonstrate that manipulation of leaf litter in stormwater catch basins, an important source of disease vector mosquitoes in urban environments, can increase Cx. pipiens oviposition but reduce survival. In a series of experiments designed to elucidate the mechanisms that explain the attractive and lethal properties of this native plant, behavioural bioassays suggest that oviposition site selection by Cx. pipiens is mediated primarily by chemical cues as leaves decompose. However, we also show that juvenile mosquito survival mainly is related to the suitability of the bacterial community in the aquatic habitat for mosquito nutritional needs, which does not appear to create a cue that influences oviposition choice. This mismatch between oviposition cues and drivers of larval habitat quality may account for the ecological trap phenomenon detected in this study. Our findings provide new insights into potential mechanistic pathways by which ecological traps may occur in nature and proof-of-concept for a new ‘attract-and-kill’ tool for mosquito control.

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.

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.