Modeling future climate suitability for the western blacklegged tick, Ixodes pacificus, in California with an emphasis on land access and ownership.

In the western United States, Ixodes pacificus Cooley & Kohls (Acari: Ixodidae) is the primary vector of the agents causing Lyme disease and granulocytic anaplasmosis in humans. The geographic distribution of the tick is associated with climatic variables that include temperature, precipitation, and humidity, and biotic factors such as the spatial distribution of its primary vertebrate hosts. Here, we explore (1) how climate change may alter the geographic distribution of I. pacificus in California, USA, during the 21st century, and (2) the spatial overlap among predicted changes in tick habitat suitability, land access, and ownership. Maps of potential future suitability for I. pacificus were generated by applying climate-based species distribution models to a multi-model ensemble of climate change projections for the Representative Concentration Pathway (RCP) 4.5 (moderate emission) and 8.5 (high emission) scenarios for two future periods: mid-century (2026-2045) and end-of-century (2086-2099). Areas climatically-suitable for I. pacificus are projected to expand by 23% (mid-century RCP 4.5) to 86% (end-of-century RCP 8.5) across California, compared to the historical period (1980-2014), with future estimates of total suitable land area ranging from about 88 to 133 thousand km2, or up to about a third of California. Regions projected to have the largest area increases in suitability by end-of-century are in northwestern California and the south central and southern coastal ranges. Over a third of the future suitable habitat is on lands currently designated as open access (i.e. publicly available), and by 2100, the amount of these lands that are suitable habitat for I. pacificus is projected to more than double under the most extreme emissions scenario (from ~23,000 to >51,000 km2). Of this area, most is federally-owned (>45,000 km2). By the end of the century, 26% of all federal land in the state is predicted to be suitable habitat for I. pacificus. The resulting maps may facilitate regional planning and preparedness by informing public health and vector control decision-makers.

LYMESIM 2.0: An Updated Simulation of Blacklegged Tick (Acari: Ixodidae) Population Dynamics and Enzootic Transmission of Borrelia burgdorferi (Spirochaetales: Spirochaetaceae).

Lyme disease is the most commonly reported vector-borne disease in the United States, and the number of cases reported each year continues to rise. The complex nature of the relationships between the pathogen (Borrelia burgdorferi sensu stricto), the tick vector (Ixodes scapularis Say), multiple vertebrate hosts, and numerous environmental factors creates challenges for understanding and predicting tick population and pathogen transmission dynamics. LYMESIM is a mechanistic model developed in the late 1990s to simulate the life-history of I. scapularis and transmission dynamics of B. burgdorferi s.s. Here we present LYMESIM 2.0, a modernized version of LYMESIM, that includes several modifications to enhance the biological realism of the model and to generate outcomes that are more readily measured under field conditions. The model is tested for three geographically distinct locations in New York, Minnesota, and Virginia. Model-simulated timing and densities of questing nymphs, infected nymphs, and abundances of nymphs feeding on hosts are consistent with field observations and reports for these locations. Sensitivity analysis highlighted the importance of temperature in host finding for the density of nymphs, the importance of transmission from small mammals to ticks on the density of infected nymphs, and temperature-related tick survival for both density of nymphs and infected nymphs. A key challenge for accurate modeling of these metrics is the need for regionally representative inputs for host populations and their fluctuations. LYMESIM 2.0 is a useful public health tool that downstream can be used to evaluate tick control interventions and can be adapted for other ticks and pathogens.

Consensus and uncertainty in the geographic range of Aedes aegypti and Aedes albopictus in the contiguous United States: Multi-model assessment and synthesis.

Aedes (Stegomyia) aegypti (L.) and Ae. (Stegomyia) albopictus (Skuse) mosquitoes can transmit dengue, chikungunya, yellow fever, and Zika viruses. Limited surveillance has led to uncertainty regarding the geographic ranges of these vectors globally, and particularly in regions at the present-day margins of habitat suitability such as the contiguous United States. Empirical habitat suitability models based on environmental conditions can augment surveillance gaps to describe the estimated potential species ranges, but model accuracy is unclear. We identified previously published regional and global habitat suitability models for Ae. aegypti (n = 6) and Ae. albopictus (n = 8) for which adequate information was available to reproduce the models for the contiguous U.S. Using a training subset of recently updated county-level surveillance records of Ae. aegypti and Ae. albopictus and records of counties conducting surveillance, we constructed accuracy-weighted, probabilistic ensemble models from these base models. To assess accuracy and uncertainty we compared individual and ensemble model predictions of species presence or absence to both training and testing data. The ensemble models were among the most accurate and also provided calibrated probabilities of presence for each species. The quantitative probabilistic framework enabled identification of areas with high uncertainty and model bias across the U.S. where improved models or additional data could be most beneficial. The results may be of immediate utility for counties considering surveillance and control programs for Ae. aegypti and Ae. albopictus. Moreover, the assessment framework can drive future efforts to provide validated quantitative estimates to support these programs at local, national, and international scales.

Urban heat and air pollution: A framework for integrating population vulnerability and indoor exposure in health risk analyses.

Urban growth and climate change will exacerbate extreme heat events and air pollution, posing considerable health challenges to urban populations. Although epidemiological studies have shown associations between health outcomes and exposures to ambient air pollution and extreme heat, the degree to which indoor exposures and social and behavioral factors may confound or modify these observed effects remains underexplored. To address this knowledge gap, we explore the linkages between vulnerability science and epidemiological conceptualizations of risk to propose a conceptual and analytical framework for characterizing current and future health risks to air pollution and extreme heat, indoors and outdoors. Our framework offers guidance for research on climatic variability, population vulnerability, the built environment, and health effects by illustrating how health data, spatially resolved ambient data, estimates of indoor conditions, and household-level vulnerability data can be integrated into an epidemiological model. We also describe an approach for characterizing population adaptive capacity and indoor exposure for use in population-based epidemiological models. Our framework and methods represent novel resources for the evaluation of health risks from extreme heat and air pollution, both indoors and outdoors.

A Simple Model to Predict the Potential Abundance of Aedes aegypti Mosquitoes One Month in Advance.

The mosquito Aedes (Stegomyia) aegypti (L.) is the primary vector of dengue, chikungunya, and Zika viruses in the United States. Surveillance for adult Ae. aegypti is limited, hindering understanding of the mosquito's seasonal patterns and predictions of areas at elevated risk for autochthonous virus transmission. We developed a simple, intuitive empirical model that uses readily available temperature and humidity variables to predict environmental suitability for low, medium, or high potential abundance of adult Ae. aegypti in a given city 1 month in advance. Potential abundance was correctly predicted in 73% of months in arid Phoenix, AZ (over a 10-year period), and 63% of months in humid Miami, FL (over a 2-year period). The monthly model predictions can be updated daily, weekly, or monthly and thus may be applied to forecast suitable conditions for Ae. aegypti to inform vector-control activities and guide household-level actions to reduce mosquito habitat and human exposure.

Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique.

Malaria is a major cause of morbidity and mortality in Mozambique. We present a malaria early warning system (MEWS) for Mozambique informed by seven years of weekly case reports of malaria in children under 5 years of age from 142 districts. A spatio-temporal model was developed based on explanatory climatic variables to map exceedance probabilities, defined as the predictive probability that the relative risk of malaria incidence in a given district for a particular week will exceed a predefined threshold. Unlike most spatially discrete models, our approach accounts for the geographical extent of each district in the derivation of the spatial covariance structure to allow for changes in administrative boundaries over time. The MEWS can thus be used to predict areas that may experience increases in malaria transmission beyond expected levels, early enough so that prevention and response measures can be implemented prior to the onset of outbreaks. The framework we present is also applicable to other climate-sensitive diseases.

Effects of desiccation stress on adult female longevity in Aedes aegypti and Ae. albopictus (Diptera: Culicidae): results of a systematic review and pooled survival analysis.

BACKGROUND: Transmission dynamics of mosquito-borne viruses such as dengue, Zika and chikungunya are affected by the longevity of the adult female mosquito. Environmental conditions influence the survival of adult female Aedes mosquitoes, the primary vectors of these viruses. While the association of temperature with Aedes mortality has been relatively well-explored, the role of humidity is less established. The current study's goals were to compile knowledge of the influence of humidity on adult survival in the important vector species Aedes aegypti and Ae. albopictus, and to quantify this relationship while accounting for the modifying effect of temperature. METHODS: We performed a systematic literature review to identify studies reporting experimental results informing the relationships among temperature, humidity and adult survival in Ae. aegypti and Ae. albopictus. Using a novel simulation approach to harmonize disparate survival data, we conducted pooled survival analyses via stratified and mixed effects Cox regression to estimate temperature-dependent associations between humidity and mortality risk for these species across a broad range of temperatures and vapor pressure deficits. RESULTS: After screening 1517 articles, 17 studies (one in semi-field and 16 in laboratory settings) met inclusion criteria and collectively reported results for 192 survival experiments. We review and synthesize relevant findings from these studies. Our stratified model estimated a strong temperature-dependent association of humidity with mortality in both species, though associations were not significant for Ae. albopictus in the mixed effects model. Lowest mortality risks were estimated around 27.5 °C and 21.5 °C for Ae. aegypti and Ae. albopictus, respectively, and mortality increased non-linearly with decreasing humidity. Aedes aegypti had a survival advantage relative to Ae. albopictus in the stratified model under most conditions, but species differences were not significant in the mixed effects model. CONCLUSIONS: Humidity is associated with mortality risk in adult female Ae. aegypti in controlled settings. Data are limited at low humidities, temperature extremes, and for Ae. albopictus, and further studies should be conducted to reduce model uncertainty in these contexts. Desiccation is likely an important factor in Aedes population dynamics and viral transmission in arid regions. Models of Aedes-borne virus transmission may be improved by more comprehensively representing humidity effects.

Modeling Climate Suitability of the Western Blacklegged Tick in California.

Ixodes pacificus Cooley & Kohls (Acari: Ixodidae), the primary vector of Lyme disease spirochetes to humans in the far-western United States, is broadly distributed across Pacific Coast states, but its distribution is not uniform within this large, ecologically diverse region. To identify areas of suitable habitat, we assembled records of locations throughout California where two or more I. pacificus were collected from vegetation from 1980 to 2014. We then employed ensemble species distribution modeling to identify suitable climatic conditions for the tick and restricted the results to land cover classes where these ticks are typically encountered (i.e., forest, grass, scrub-shrub, riparian). Cold-season temperature and rainfall are particularly important abiotic drivers of suitability, explaining between 50 and 99% of the spatial variability across California among models. The likelihood of an area being classified as suitable increases steadily with increasing temperatures >0°C during the coldest quarter of the year, and further increases when precipitation amounts range from 400 to 800 mm during the coldest quarter, indicating that areas in California with relatively warm and wet winters typically are most suitable for I. pacificus. Other consistent predictors of suitability include increasing autumn humidity, temperatures in the warmest month between 23 and 33°C, and low-temperature variability throughout the year. The resultant climatic suitability maps indicate that coastal California, especially the northern coast, and the western Sierra Nevada foothills have the highest probability of I. pacificus presence.

An Acarological Risk Model Predicting the Density and Distribution of Host-Seeking Ixodes scapularis Nymphs in Minnesota.

Ixodes scapularis is the vector of at least seven human pathogens in Minnesota, two of which are known to cause Lyme disease (Borrelia burgdorferi sensu stricto and Borrelia mayonii). In Minnesota, the statewide incidence of Lyme disease and other I. scapularis-borne diseases and the geographic extent over which cases have been reported have both increased substantially over the last two decades. These changes correspond with an expanding distribution of I. scapularis over a similar time frame. Because the risk of exposure to I. scapularis-borne pathogens is likely related to the number of ticks encountered, we developed an acarological risk model predicting the density of host-seeking I. scapularis nymphs (DON) in Minnesota. The model was informed by sampling 81 sites located in 42 counties in Minnesota. Two main foci were predicted by the model to support elevated densities of host-seeking I. scapularis nymphs, which included the seven-county Minneapolis-St. Paul metropolitan area and counties in northern Minnesota, including Lake of the Woods and Koochiching counties. There was substantial heterogeneity observed in predicted DON across the state at the county scale; however, counties classified as high risk for I. scapularis-borne diseases and counties with known established populations of I. scapularis had the highest proportion of the county predicted as suitable for host-seeking nymphs (≥ 0.13 nymphs/100 m2). The model provides insight into areas of potential I. scapularis population expansion and identifies focal areas of predicted suitable habitat within counties where the incidence of I. scapularis-borne diseases has been historically low.

Modeling the Environmental Suitability for Aedes (Stegomyia) aegypti and Aedes (Stegomyia) albopictus (Diptera: Culicidae) in the Contiguous United States.

The mosquitoes Aedes (Stegomyia) aegypti (L.)(Diptera:Culicidae) and Ae. (Stegomyia) albopictus (Skuse) (Diptera:Culicidae) transmit dengue, chikungunya, and Zika viruses and represent a growing public health threat in parts of the United States where they are established. To complement existing mosquito presence records based on discontinuous, non-systematic surveillance efforts, we developed county-scale environmental suitability maps for both species using maximum entropy modeling to fit climatic variables to county presence records from 1960-2016 in the contiguous United States. The predictive models for Ae. aegypti and Ae. albopictus had an overall accuracy of 0.84 and 0.85, respectively. Cumulative growing degree days (GDDs) during the winter months, an indicator of overall warmth, was the most important predictive variable for both species and was positively associated with environmental suitability. The number (percentage) of counties classified as environmentally suitable, based on models with 90 or 99% sensitivity, ranged from 1,443 (46%) to 2,209 (71%) for Ae. aegypti and from 1,726 (55%) to 2,329 (75%) for Ae. albopictus. Increasing model sensitivity results in more counties classified as suitable, at least for summer survival, from which there are no mosquito records. We anticipate that Ae. aegypti and Ae. albopictus will be found more commonly in counties classified as suitable based on the lower 90% sensitivity threshold compared with the higher 99% threshold. Counties predicted suitable with 90% sensitivity should therefore be a top priority for expanded mosquito surveillance efforts while still keeping in mind that Ae. aegypti and Ae. albopictus may be introduced, via accidental transport of eggs or immatures, and potentially proliferate during the warmest part of the year anywhere within the geographic areas delineated by the 99% sensitivity model.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales.

BACKGROUND: The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. METHODS: We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. RESULTS: We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. CONCLUSIONS: The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Host-Seeking Phenology of Ixodes pacificus (Acari: Ixodidae) Nymphs in Northwestern California in Relation to Calendar Week, Woodland Type, and Weather Conditions.

Local knowledge of when humans are at elevated risk for exposure to tick vectors of human disease agents is required both for the effective use of personal protection measures to avoid tick bites and for implementation of control measures to suppress host-seeking ticks. Here, we used previously published data on the seasonal density of host-seeking Ixodes pacificus Cooley and Kohls nymphs, the primary vectors of Lyme disease spirochetes in the far western USA, collected across a broad habitat and climate gradient in northwestern California to identify predictors of periods of time within the year when questing nymphal density is elevated. Models based on calendar week alone performed similarly to models based on calendar week and woodland type, or meteorological variables. The most suitable model for a given application will depend on user objectives, timescale of interest, and the geographic extent of predictions. Our models sought not only to identify when seasonal host-seeking activity commences, but also when it diminishes to low levels. Overall, we report a roughly 5-7 month period in Mendocino County during which host-seeking nymphal densities exceed a low threshold value.

Modeling the Geographic Distribution of Ixodes scapularis and Ixodes pacificus (Acari: Ixodidae) in the Contiguous United States.

In addition to serving as vectors of several other human pathogens, the black-legged tick, Ixodes scapularis Say, and western black-legged tick, Ixodes pacificus Cooley and Kohls, are the primary vectors of the spirochete (Borrelia burgdorferi) that causes Lyme disease, the most common vector-borne disease in the United States. Over the past two decades, the geographic range of I. pacificus has changed modestly while, in contrast, the I. scapularis range has expanded substantially, which likely contributes to the concurrent expansion in the distribution of human Lyme disease cases in the Northeastern, North-Central and Mid-Atlantic states. Identifying counties that contain suitable habitat for these ticks that have not yet reported established vector populations can aid in targeting limited vector surveillance resources to areas where tick invasion and potential human risk are likely to occur. We used county-level vector distribution information and ensemble modeling to map the potential distribution of I. scapularis and I. pacificus in the contiguous United States as a function of climate, elevation, and forest cover. Results show that I. pacificus is currently present within much of the range classified by our model as suitable for establishment. In contrast, environmental conditions are suitable for I. scapularis to continue expanding its range into northwestern Minnesota, central and northern Michigan, within the Ohio River Valley, and inland from the southeastern and Gulf coasts. Overall, our ensemble models show suitable habitat for I. scapularis in 441 eastern counties and for I. pacificus in 11 western counties where surveillance records have not yet supported classification of the counties as established.

On the Seasonal Occurrence and Abundance of the Zika Virus Vector Mosquito Aedes Aegypti in the Contiguous United States.

INTRODUCTION: An ongoing Zika virus pandemic in Latin America and the Caribbean has raised concerns that travel-related introduction of Zika virus could initiate local transmission in the United States (U.S.) by its primary vector, the mosquito Aedes aegypti. METHODS: We employed meteorologically driven models for 2006-2015 to simulate the potential seasonal abundance of adult Aedes aegypti for fifty cities within or near the margins of its known U.S. range. Mosquito abundance results were analyzed alongside travel and socioeconomic factors that are proxies of viral introduction and vulnerability to human-vector contact.     RESULTS: Meteorological conditions are largely unsuitable for Aedes aegypti over the U.S. during winter months (December-March), except in southern Florida and south Texas where comparatively warm conditions can sustain low-to-moderate potential mosquito abundance. Meteorological conditions are suitable for Aedes aegypti across all fifty cities during peak summer months (July-September), though the mosquito has not been documented in all cities. Simulations indicate the highest mosquito abundance occurs in the Southeast and south Texas where locally acquired cases of Aedes-transmitted viruses have been reported previously. Cities in southern Florida and south Texas are at the nexus of high seasonal suitability for Aedes aegypti and strong potential for travel-related virus introduction. Higher poverty rates in cities along the U.S.-Mexico border may correlate with factors that increase human exposure to Aedes aegypti.     DISCUSSION: Our results can inform baseline risk for local Zika virus transmission in the U.S. and the optimal timing of vector control activities, and underscore the need for enhanced surveillance for Aedes mosquitoes and Aedes-transmitted viruses.

Willingness to Pay for Mosquito Control in Key West, Florida and Tucson, Arizona.

Mosquito-borne illnesses like West Nile virus (WNV) and dengue are growing threats to the United States. Proactive mosquito control is one strategy to reduce the risk of disease transmission. In 2012, we measured the public's willingness to pay (WTP) for increased mosquito control in two cities: Key West, FL, where there have been recent dengue outbreaks, and Tucson, AZ, where dengue vectors are established and WNV has been circulating for over a decade. Nearly three quarters of respondents in both cities (74% in Tucson and 73% in Key West) would be willing to pay $25 or more annually toward an increase in publicly funded mosquito control efforts. WTP was positively associated with income (both cities), education (Key West), and perceived mosquito abundance (Tucson). Concerns about environmental impacts of mosquito control were associated with lower WTP in Key West. Expanded mosquito control efforts should incorporate public opinion as they respond to evolving disease risks.

WHATCH'EM: A Weather-Driven Energy Balance Model for Determining Water Height and Temperature in Container Habitats for Aedes aegypti.

The mosquito virus vector Aedes (Ae.) aegypti exploits a wide range of containers as sites for egg laying and development of the immature life stages, yet the approaches for modeling meteorologically sensitive container water dynamics have been limited. This study introduces the Water Height and Temperature in Container Habitats Energy Model (WHATCH'EM), a state-of-the-science, physically based energy balance model of water height and temperature in containers that may serve as development sites for mosquitoes. The authors employ WHATCH'EM to model container water dynamics in three cities along a climatic gradient in México ranging from sea level, where Ae. aegypti is highly abundant, to ~2100 m, where Ae. aegypti is rarely found. When compared with measurements from a 1-month field experiment in two of these cities during summer 2013, WHATCH'EM realistically simulates the daily mean and range of water temperature for a variety of containers. To examine container dynamics for an entire season, WHATCH'EM is also driven with field-derived meteorological data from May to September 2011 and evaluated for three commonly encountered container types. WHATCH'EM simulates the highly nonlinear manner in which air temperature, humidity, rainfall, clouds, and container characteristics (shape, size, and color) determine water temperature and height. Sunlight exposure, modulated by clouds and shading from nearby objects, plays a first-order role. In general, simulated water temperatures are higher for containers that are larger, darker, and receive more sunlight. WHATCH'EM simulations will be helpful in understanding the limiting meteorological and container-related factors for proliferation of Ae. aegypti and may be useful for informing weather-driven early warning systems for viruses transmitted by Ae. aegypti.

Meteorologically Driven Simulations of Dengue Epidemics in San Juan, PR.

Meteorological factors influence dengue virus ecology by modulating vector mosquito population dynamics, viral replication, and transmission. Dynamic modeling techniques can be used to examine how interactions among meteorological variables, vectors and the dengue virus influence transmission. We developed a dengue fever simulation model by coupling a dynamic simulation model for Aedes aegypti, the primary mosquito vector for dengue, with a basic epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model. Employing a Monte Carlo approach, we simulated dengue transmission during the period of 2010-2013 in San Juan, PR, where dengue fever is endemic. The results of 9600 simulations using varied model parameters were evaluated by statistical comparison (r2) with surveillance data of dengue cases reported to the Centers for Disease Control and Prevention. To identify the most influential parameters associated with dengue virus transmission for each period the top 1% of best-fit model simulations were retained and compared. Using the top simulations, dengue cases were simulated well for 2010 (r2 = 0.90, p = 0.03), 2011 (r2 = 0.83, p = 0.05), and 2012 (r2 = 0.94, p = 0.01); however, simulations were weaker for 2013 (r2 = 0.25, p = 0.25) and the entire four-year period (r2 = 0.44, p = 0.002). Analysis of parameter values from retained simulations revealed that rain dependent container habitats were more prevalent in best-fitting simulations during the wetter 2010 and 2011 years, while human managed (i.e. manually filled) container habitats were more prevalent in best-fitting simulations during the drier 2012 and 2013 years. The simulations further indicate that rainfall strongly modulates the timing of dengue (e.g., epidemics occurred earlier during rainy years) while temperature modulates the annual number of dengue fever cases. Our results suggest that meteorological factors have a time-variable influence on dengue transmission relative to other important environmental and human factors.

Two methods for estimating limits to large-scale wind power generation.

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 10(5) km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m(-2), whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m(-2), with VKE capturing this combination in a comparatively simple way.

Modeling the Present and Future Geographic Distribution of the Lone Star Tick, Amblyomma americanum (Ixodida: Ixodidae), in the Continental United States.

The Lone star tick (Amblyomma americanum L.) is the primary vector for pathogens of significant public health importance in North America, yet relatively little is known about its current and potential future distribution. Building on a published summary of tick collection records, we used an ensemble modeling approach to predict the present-day and future distribution of climatically suitable habitat for establishment of the Lone star tick within the continental United States. Of the nine climatic predictor variables included in our five present-day models, average vapor pressure in July was by far the most important determinant of suitable habitat. The present-day ensemble model predicted an essentially contiguous distribution of suitable habitat extending to the Atlantic coast east of the 100th western meridian and south of the 40th northern parallel, but excluding a high elevation region associated with the Appalachian Mountains. Future ensemble predictions for 2061-2080 forecasted a stable western range limit, northward expansion of suitable habitat into the Upper Midwest and western Pennsylvania, and range contraction along portions of the Gulf coast and the lower Mississippi river valley. These findings are informative for raising awareness of A. americanum-transmitted pathogens in areas where the Lone Star tick has recently or may become established.