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1. Ixodes Scapularis monitoring data compiled from 6 studies

   https://doi.org/10.5281/zenodo.6540831  

   Christie, Rowan ; Stack, Kaitlin Whitney ; Perrone, Julia ; Bahlai, Christie ( January 2022 , Zenodo)

   This dataset lists 289 blacklegged tick population datasets from 6 studies that record abundance. These datasets were found by inputing keywords Ixodes Scapularis and tick in data repositories including Long Term Ecological Research data portal, National Ecological Observatory Network data portal, Google Datasets, Data Dryad, and Data One. The types of tick data recorded from these studies include density (number per square meter for example), proportion of ticks, count of ticks found on people. The locations of the datasets range from New York, New Jersey, Iowa, Massachusetts, and Connecticut, and range from 9 to 24 years in length. These datasets vary in that some record different life stages, geographic scope (county/town/plot), sampling technique (dragging/surveying), and different study length. The impact of these study factors on study results is analyzed in our research.

   Funding:

   RMC is supported by the National Institute of General Medical Sciences of the National Institutes of the Health under Award Number R25GM122672. CAB, JP, and KSW are supported by the Office of Advanced Cyberinfrastructure in the National Science Foundation under Award Number #1838807. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the National Science Foundation.

   {"references": ["Ellison A. 2017. Incidence of Ticks and Tick Bites at Harvard Forest since 2006. Environmental Data Initiative. https://doi.org/10.6073/pasta/71f12a4ffb7658e71a010866d1805a84. Dataset accessed 6/25/2019", "New York State Department of Health Office of Public Health. 2019. Deer Tick Surveillance: Adults (Oct to Dec) excluding Powassan virus: Beginning 2008. https://health.data.ny.gov/Health/Deer-Tick-Surveillance-Nymphs-May-to-Sept-excludin/kibp-u2ip", "New York State Department of Health Office of Public Health. 2019. Access Nymph Deer Tick Collection Data by County (Excluding Powassan Virus). https://health.data.ny.gov/Health/Deer-Tick-Surveillance-Nymphs-May-to-Sept-excludin/kibp-u2ip", "Ostfeld RS, Levi T, Keesing F, Oggenfuss K, Canham CD (2018) Data from: Tick-borne disease risk in a forest food web. Dryad Digital Repository. https://doi.org/10.5061/dryad.d1c8046", "Oliver JD, Bennett SW, Beati L, Bartholomay LC (2017) Range Expansion and Increasing Borrelia burgdorferi Infection of the Tick Ixodes scapularis (Acari: Ixodidae) in Iowa, 1990\u20132013. Journal of Medical Entomology 54(6): 1727-1734. https://doi.org/10.1093/jme/tjx121", "The Connecticut Agricultural Experiment Station. (n.d.). Summaries of tick testing. CT.gov. Retrieved May 12, 2022, from https://portal.ct.gov/CAES/Fact-Sheets/Tick-Summary/Summaries-of-Tick-Testing", "Jordan, R. A., & Egizi, A. (2019). The growing importance of lone star ticks in a Lyme disease endemic county: Passive tick surveillance in Monmouth County, NJ, 2006 - 2016. PloS one, 14(2), e0211778. https://doi.org/10.1371/journal.pone.0211778"]} 

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2. Longer study length, standardized sampling techniques, and broader geographic scope leads to higher likelihood of detecting stable abundance patterns in long term black-legged tick studies

   https://doi.org/10.7717/peerj.13916  

   Christie, Rowan ; Stack Whitney, Kaitlin ; Perrone, Julia ; Bahlai, Christie A. ( January 2022 , PeerJ)

   Background Understanding how study design and monitoring strategies shape inference within, and synthesis across, studies is critical across biological disciplines. Many biological and field studies are short term and limited in scope. Monitoring studies are critical for informing public health about potential vectors of concern, such as Ixodes scapularis (black-legged ticks). Black-legged ticks are a taxon of ecological and human health concern due to their status as primary vectors of Borrelia burgdorferi , the bacteria that transmits Lyme disease. However, variation in black-legged tick monitoring, and gaps in data, are currently considered major barriers to understanding population trends and in turn, predicting Lyme disease risk. To understand how variable methodology in black-legged tick studies may influence which population patterns researchers find, we conducted a data synthesis experiment. Materials and Methods We searched for publicly available black-legged tick abundance dataset that had at least 9 years of data, using keywords about ticks in internet search engines, literature databases, data repositories and public health websites. Our analysis included 289 datasets from seven surveys from locations in the US, ranging in length from 9 to 24 years. We used a moving window analysis, a non-random resampling approach, to investigate the temporal stability of black-legged tick population trajectories across the US. We then used t-tests to assess differences in stability time across different study parameters. Results All of our sampled datasets required 4 or more years to reach stability. We also found several study factors can have an impact on the likelihood of a study reaching stability and of data leading to misleading results if the study does not reach stability. Specifically, datasets collected via dragging reached stability significantly faster than data collected via opportunistic sampling. Datasets that sampled larva reached stability significantly later than those that sampled adults or nymphs. Additionally, datasets collected at the broadest spatial scale (county) reached stability fastest. Conclusion We used 289 datasets from seven long term black-legged tick studies to conduct a non-random data resampling experiment, revealing that sampling design does shape inferences in black-legged tick population trajectories and how many years it takes to find stable patterns. Specifically, our results show the importance of study length, sampling technique, life stage, and geographic scope in understanding black-legged tick populations, in the absence of standardized surveillance methods. Current public health efforts based on existing black-legged tick datasets must take monitoring study parameters into account, to better understand if and how to use monitoring data to inform decisioning. We also advocate that potential future forecasting initiatives consider these parameters when projecting future black-legged tick population trends. 

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3. The wild life of ticks: Using passive surveillance to determine the distribution and wildlife host range of ticks and the exotic Haemaphysalis longicornis, 2010–2021

   https://doi.org/10.1186/s13071-022-05425-1  

   Thompson, Alec T. ; White, Seth A. ; Doub, Emily E. ; Sharma, Prisha ; Frierson, Kenna ; Dominguez, Kristen ; Shaw, David ; Weaver, Dustin ; Vigil, Stacey L. ; Bonilla, Denise L. ; et al ( September 2022 , Parasites & Vectors)

   We conducted a large-scale, passive regional survey of ticks associated with wildlife of the eastern United States. Our primary goals were to better assess the current geographical distribution of exoticHaemaphysalis longicornisand to identify potential wild mammalian and avian host species. However, this large-scale survey also provided valuable information regarding the distribution and host associations for many other important tick species that utilize wildlife as hosts.

   Ticks were opportunistically collected by cooperating state and federal wildlife agencies. All ticks were placed in the supplied vials and host information was recorded, including host species, age, sex, examination date, location (at least county and state), and estimated tick burden. All ticks were identified to species using morphology, and suspectH. longicorniswere confirmed through molecular techniques.

   In total, 1940 hosts were examined from across 369 counties from 23 states in the eastern USA. From these submissions, 20,626 ticks were collected and identified belonging to 11 different species. Our passive surveillance efforts detected exoticH. longicornisfrom nine host species from eight states. Notably, some of the earliest detections ofH. longicornisin the USA were collected from wildlife through this passive surveillance network. In addition, numerous new county reports were generated forAmblyomma americanum,Amblyomma maculatum,Dermacentor albipictus,Dermacentor variabilis, andIxodes scapularis.

   This study provided data on ticks collected from animals from 23 different states in the eastern USA between 2010 and 2021, with the primary goal of better characterizing the distribution and host associations of the exotic tickH. longicornis;however, new distribution data on tick species of veterinary or medical importance were also obtained. Collectively, our passive surveillance has detected numerous new county reports forH. longicornisas well asI. scapularis.Our study utilizing passive wildlife surveillance for ticks across the eastern USA is an effective method for surveying a diversity of wildlife host species, allowing us to better collect data on current tick distributions relevant to human and animal health.

    

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4. Rainfall Manipulation Study Vegetation Data from the Chihuahuan Desert Grassland and Creosote Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (2003-2011)

   https://doi.org/10.6073/pasta/361fbce9ce7d4d9530e34b4a8ee3c02e  

   Pockman, William ( January 2013 , Environmental Data Initiative)

   The overall goal of the rainfall manipulation project is to understand the coupled ecological and hydrological responses of a grassland, shrubland and a mixed grass-shrub vegetation community to extended periods of increased or decreased rainfall. Rainfall manipulation plots have been established in each of these three vegetation communities in the Five Points area of Sevilleta National Wildlife Refuge. In each vegetation community, three control plots, three drought treatment plots, and three water addition plots have been installed, each approximately 10 x 15 m in size. In each plot, vertical profiles of soil moisture probes have been installed under each cover type (canopy and interspace in grassland and shrubland; grass canopy, shrub canopy and interspace at the ecotone (mixed grass-shrub) site). The probes measure differences in infiltration and soil water content and potential associations with these different cover types. In addition, TDR probes have been installed diagonally in each cover type to integrate the water content of the top 15 cm of soil. Each plot contains 18, 1m2 quads made up of 6, 1m2 quads along each of the 3 transects located across each plot. Each spring and fall, the following parameters are measured in every quad: live plant cover, height, and abundance by species; dead plant cover; soil cover; litter cover; and rock cover. Data collection began in the drought and control plots in the spring of 2002. Data collection began in the water addition plots in the spring of 2004.In the grassland and shrubland communities, all nine currently established plots are located together. The three drought plots were located under a single large roof with a 0.5 m path separating each plot (drought treatments ended in 2006). The control plots and water addition plots are similarly grouped, but without the shelter structure. In the ecotone community, the plots are in three groups; each group is comprised of one drought plot, one water addition plot, and one control plot. Control plots received no experimental treatment, while the sliding roofs over the drought plots were used to divert precipitation, producing a long-term drought. The roofs covering the drought plots were lowered when there was no precipitation so that the amount of sunlight received by the drought plots was minimally affected. Water addition was intended to impose a complementary increase in water supply on the water addition plots.  

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5. Linking Lyme disease ecology and epidemiology: reservoir host identity, not richness, determines tick infection and human disease in California

   https://doi.org/10.1088/1748-9326/ac9ece  

   MacDonald, Andrew J ; McComb, Sofie ; Sambado, Samantha ( November 2022 , Environmental Research Letters)

   Abstract Understanding the community ecology of vector-borne and zoonotic diseases, and how it may shift transmission risk as it responds to environmental change, has become a central focus in disease ecology. Yet, it has been challenging to link the ecology of disease with reported human incidence. Here, we bridge the gap between local-scale community ecology and large-scale disease epidemiology, drawing from a priori knowledge of tick-pathogen-host ecology to model spatially-explicit Lyme disease (LD) risk, and human Lyme disease incidence (LDI) in California. We first use a species distribution modeling approach to model disease risk with variables capturing climate, vegetation, and ecology of key reservoir host species, and host species richness. We then use our modeled disease risk to predict human disease incidence at the zip code level across California. Our results suggest the ecology of key reservoir hosts—particularly dusky-footed woodrats—is central to disease risk posed by ticks, but that host community richness is not strongly associated with tick infection. Predicted disease risk, which is most strongly influenced by the ecology of dusky-footed woodrats, in turn is a strong predictor of human LDI. This relationship holds in the Wildland-Urban Interface, but not in open access public lands, and is stronger in northern California than in the state as a whole. This suggests peridomestic exposure to infected ticks may be more important to LD epidemiology in California than recreational exposure, and underlines the importance of the community ecology of LD in determining human transmission risk throughout this LD endemic region of far western North America. More targeted tick and pathogen surveillance, coupled with studies of human and tick behavior could improve understanding of key risk factors and inform public health interventions. Moreover, longitudinal surveillance data could further improve forecasts of disease risk in response to global environmental change. 

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