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Background: Kyasanur forest disease virus (KFDV) is a tick-borne flavivirus causing debilitating and potentially fatal disease in people in the Western Ghats region of India. The transmission cycle is complex, involving multiple vector and host species, but there are significant gaps in ecological knowledge. Empirical data on pathogen-vector-host interactions and incrimination have not been updated since the last century, despite significant local changes in land use and the expansion of KFD to new areas. Mathematical models predict that transovarial transmission, whereby adult female ticks pass KFDV infections to their offspring, plays an important role in the persistence of KFD, but this has not been shown in the wild. Here we set out to establish whether transovarial transmission of KFDV was occurring under natural field conditions by assessing whether host-seeking larvae were positive for KFDV. Methods: Ticks were sampled by dragging and flagging across a broad range of habitats within the agro-forest matrix at 49 sites in two districts: Shivamogga, Karnataka and Wayanad, Kerala (September 2018-March 2019), and larvae were tested for KFDV by PCR. Results: In total, larval ticks from 7 of the 49 sites sampled tested positive for KFDV, indicating that transovarial transmission is occurring. Of the 13 KFDV-positive larval samples, 3 came from around houses and gardens, 5 from crops (3 from harvested rice paddy and 2 from areca plantation), 1 from teak plantation and 4 (2 from 1 transect) from forests. Five different tick species were found to have KFDV-positive larvae: Haemaphysalis spinigera, H. bispinosa, Rhipicephalus annulatus, R. microplus and an unidentifiable species of Haemaphysalis (no close match in GenBank). Conclusions: Our empirical confirmation of transovarial transmission has important implications for understanding and predicting KFD dynamics, suggesting that ticks may act as a reservoir for KFDV. Moreover, small mammals and cattle may play crucial roles in transmission if small mammals are the main hosts for larvae infected via transovarial transmission, and cattle support large numbers of infected female adult ticks. This first report of transovarial transmission of KFDV, and within a hitherto undescribed range of vectors and habitats, will help disease managers improve KFD surveillance and mitigation strategies, ultimately leading to communities becoming more resilient to the risk of this tick-transmitted disease. [ABSTRACT FROM AUTHOR]

Abstract Background The risk posed to the United Kingdom by West Nile virus (WNV) has previously been considered low, due to the absence or scarcity of the main Culex sp. bridge vectors. The mosquito Culex modestus is widespread in southern Europe, where it acts as the principle bridge vector of WNV. This species was not previously thought to be present in the United Kingdom. Findings Mosquito larval surveys carried out in 2010 identified substantial populations of Cx. modestus at two sites in marshland in southeast England. Host-seeking-adult traps placed at a third site indicate that the relative seasonal abundance of Cx. modestus peaks in early August. DNA barcoding of these specimens from the United Kingdom and material from southern France confirmed the morphological identification. Conclusions Cx. modestus appears to be established in the North Kent Marshes, possibly as the result of a recent introduction. The addition of this species to the United Kingdom's mosquito fauna may increase the risk posed to the United Kingdom by WNV.

Background: Many mosquito-borne diseases exhibit substantial seasonality, due to strong links between environmental variables and vector and pathogen life-cycles. Further, a range of density-dependent and density-independent biotic and abiotic processes affect the phenology of mosquito populations, with potentially large knock-on effects for vector dynamics and disease transmission. Whilst it is understood that density-independent and density-dependent processes affect seasonal population levels, it is not clear how these interact temporally to shape the population peaks and troughs. Due to this, the paucity of high-resolution data for validation, and the difficulty of parameterizing density-dependent processes, models of vector dynamics may poorly estimate abundances, which has knock-on effects for our ability predict vector-borne disease outbreaks. Results: We present a rich dataset describing seasonal abundance patterns of each life stage of Culex pipiens, a widespread vector of West Nile virus, at a field site in southern England in 2015. Abundance of immature stages was measured three times per week, whilst adult traps were run four nights each week. This dataset is integrated with an existing delay-differential equation model predicting Cx. pipiens seasonal abundance to improve understanding of observed seasonal abundance patterns. At our field site, the outcome of our model fitting suggests interspecific predation on mosquito larvae and temperature-dependent larval mortality combine to act as the main sources of population regulation throughout the active season, whilst competition for resources is a relatively small source of larval mortality. Conclusions: The model suggests that density-independent mortality and interspecific predation interact to shape patterns of mosquito seasonal abundance in a permanent aquatic habitat and we propose that competition for resources is likely to be important where periods of high rainfall create transient habitats. Further, we highlight the importance of challenging population abundance models with data from across all life stages of the species of interest if reliable inferences are to be drawn from these models, particularly when considering mosquito control and vector-borne disease transmission. [ABSTRACT FROM AUTHOR]

Long-term datasets of integrated environmental variables, co-located together, are relatively rare. The UK Environmental Change Network (ECN) was launched in 1992 and provides the UK with its only long-term integrated environmental monitoring and research network for the assessment of the causes and consequences of environmental change. Measurements, covering a wide range of physical, chemical and biological "driver" and "response" variables are made in close proximity at ECN terrestrial sites using protocols incorporating standard quality control procedures. This paper describes the datasets (there are nineteen published ECN datasets) for these co-located measurements, containing over twenty years of data (1993–2015). The data and supporting documentation are freely available from the NERC Environmental Information Data Centre under the terms of the Open Government Licence using the following DOI’s: Meteorology Meteorology: https://doi.org/10.5285/fc9bcd1c-e3fc-4c5a-b569-2fe62d40f2f5 (Rennie et al., 2017a) Biogeochemistry Atmospheric nitrogen chemistry: https://doi.org/10.5285/baf51776-c2d0-4e57-9cd3-30cd6336d9cf (Rennie et al., 2017b) Precipitation chemistry: https://doi.org/10.5285/18b7c387-037d-4949-98bc-e8db5ef4264c (Rennie et al., 2017c) Soil solution chemistry: https://doi.org/10.5285/b330d395-68f2-47f1-8d59-3291dc02923b (Rennie et al., 2017d) Stream water chemistry: https://doi.org/10.5285/fd7ca5ef-460a-463c-ad2b-5ad48bb4e22e (Rennie et al., 2017e) Stream water discharge: https://doi.org/10.5285/8b58c86b-0c2a-4d48-b25a-7a0141859004 (Rennie et al., 2017f) Invertebrates Moths: https://doi.org/10.5285/a2a49f47-49b3-46da-a434-bb22e524c5d2 (Rennie et al., 2017g) Butterflies: https://doi.org/10.5285/5aeda581-b4f2-4e51-b1a6-890b6b3403a3 (Rennie et al., 2017h) Carabid beetle: https://doi.org/10.5285/8385f864-dd41-410f-b248-028f923cb281 (Rennie et al., 2017i) Spittle bugs: https://doi.org/10.5285/aff433be-0869-4393-b765-9e6faad2a12b (Rennie et al., 2018) Vegetation Baseline: https://doi.org/10.5285/a7b49ac1-24f5-406e-ac8f-3d05fb583e3b (Rennie et al., 2016a) Coarse grain: https://doi.org/10.5285/d349babc-329a-4d6e-9eca-92e630e1be3f (Rennie et al., 2016b) Woodland: https://doi.org/10.5285/94aef007-634e-42db-bc52-9aae86adbd33 (Rennie et al., 2017j) Fine grain: https://doi.org/10.5285/b98efec8-6de0-4e0c-85dc-fe4cdf01f086 (Rennie et al., 2017k) Vertebrates Frogs: https://doi.org/10.5285/4d8c7dd9-8248-46ca-b988-c1fc38e51581 (Rennie et al., 2017l) Birds (Breeding bird survey): https://doi.org/10.5285/5886c3ba-1fa5-49c0-8da8-40e69a10d2b5 (Rennie et al., 2017m) Birds (Common bird census): https://doi.org/10.5285/8582a02c-b28c-45d2-afa1-c1e85fba023d (Rennie et al., 2017n) Bats: https://doi.org/10.5285/2588ee91-6cbd-4888-86fc-81858d1bf085 (Rennie et al., 2017o) Rabbits and deer: https://doi.org/10.5285/0be0aed3-f205-4f1f-a65d-84f8cfd8d50f (Rennie et al., 2017p). [ABSTRACT FROM AUTHOR]

We isolated Candida dubliniensis from a nonhuman source, namely, tick samples from an Irish seabird colony. The species was unambiguously identified by phenotypic and genotypic means. Analysis of the 5.8S rRNA gene showed that the environmental isolates belong to C. dubliniensis genotype 1. [ABSTRACT FROM AUTHOR]