Scholarly Works, Global Change Center
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Browsing Scholarly Works, Global Change Center by Content Type "Article - Refereed"
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- Assessing Ecosystem State Space Models: Identifiability and EstimationSmith, John W.; Johnson, Leah R.; Thomas, R. Quinn (Springer, 2023-03)Hierarchical probability models are being used more often than non-hierarchical deterministic process models in environmental prediction and forecasting, and Bayesian approaches to fitting such models are becoming increasingly popular. In particular, models describing ecosystem dynamics with multiple states that are autoregressive at each step in time can be treated as statistical state space models (SSMs). In this paper, we examine this subset of ecosystem models, embed a process-based ecosystem model into an SSM, and give closed form Gibbs sampling updates for latent states and process precision parameters when process and observation errors are normally distributed. Here, we use simulated data from an example model (DALECev) and study the effects changing the temporal resolution of observations on the states (observation data gaps), the temporal resolution of the state process (model time step), and the level of aggregation of observations on fluxes (measurements of transfer rates on the state process). We show that parameter estimates become unreliable as temporal gaps between observed state data increase. To improve parameter estimates, we introduce a method of tuning the time resolution of the latent states while still using higher-frequency driver information and show that this helps to improve estimates. Further, we show that data cloning is a suitable method for assessing parameter identifiability in this class of models. Overall, our study helps inform the application of state space models to ecological forecasting applications where (1) data are not available for all states and transfers at the operational time step for the ecosystem model and (2) process uncertainty estimation is desired.
- Bankfull shear velocity predicts embeddedness and silt cover in gravel streambedsCzuba, Jonathan A.; Hirschler, Mallory; Pratt, Elizabeth A.; Villamagna, Amy; Angermeier, Paul L. (Wiley, 2022-01)Excess fine sediment (<2 mm) deposition on gravel streambeds can degrade habitat quality for stream biota. Two measures of fine sediment deposition include embeddedness and silt cover (<62.5 mu m). Embeddedness measures fine sediment in interstitial pore spaces, whereas silt cover, primarily deposited during low flows, measures fine sediment draped on the streambed's surface. Here, we demonstrate that a baseline level of embeddedness and a maximum value of silt cover can be predicted from bankfull shear velocity, which can be estimated from river channel and streamflow characteristics, independently of knowing the sediment supply. We derive an equation for bankfull shear velocity that only requires knowing bankfull flow, channel width, and channel slope, which can be readily obtained in the United States from freely available, remotely sensed data. We apply this methodology to data collected at 30 sites in the Piedmont region of Virginia and North Carolina. This work is an important step in developing statistical models of stream ecosystems in which geophysical variables can predict embeddedness and silt cover, which commonly limit biotic assemblages.
- Climate change and infectious disease: a review of evidence and research trendsVan de Vuurst, Paige; Escobar, Luis E. (2023-05-16)Background Climate change presents an imminent threat to almost all biological systems across the globe. In recent years there have been a series of studies showing how changes in climate can impact infectious disease transmission. Many of these publications focus on simulations based on in silico data, shadowing empirical research based on field and laboratory data. A synthesis work of empirical climate change and infectious disease research is still lacking. Methods We conducted a systemic review of research from 2015 to 2020 period on climate change and infectious diseases to identify major trends and current gaps of research. Literature was sourced from Web of Science and PubMed literary repositories using a key word search, and was reviewed using a delineated inclusion criteria by a team of reviewers. Results Our review revealed that both taxonomic and geographic biases are present in climate and infectious disease research, specifically with regard to types of disease transmission and localities studied. Empirical investigations on vector-borne diseases associated with mosquitoes comprised the majority of research on the climate change and infectious disease literature. Furthermore, demographic trends in the institutions and individuals published revealed research bias towards research conducted across temperate, high-income countries. We also identified key trends in funding sources for most resent literature and a discrepancy in the gender identities of publishing authors which may reflect current systemic inequities in the scientific field. Conclusions Future research lines on climate change and infectious diseases should considered diseases of direct transmission (non-vector-borne) and more research effort in the tropics. Inclusion of local research in low- and middle-income countries was generally neglected. Research on climate change and infectious disease has failed to be socially inclusive, geographically balanced, and broad in terms of the disease systems studied, limiting our capacities to better understand the actual effects of climate change on health.
- Climate change linked to vampire bat expansion and rabies virus spilloverVan de Vuurst, Paige; Qiao, Huijie; Soler-Tovar, Diego; Escobar, Luis E. (Wiley, 2023-10)Bat-borne pathogens are a threat to global health and in recent history have had major impacts on human morbidity and mortality. Examples include diseases such as rabies, Nipah virus encephalitis, and severe acute respiratory syndrome (SARS). Climate change may exacerbate the emergence of bat-borne pathogens by affecting the ecology of bats in tropical ecosystems. Here, we report the impacts of climate change on the distributional ecology of the common vampire bat Desmodus rotundus across the last century. Our retrospective analysis revealed a positive relationship between changes in climate and the northern expansion of the distribution of D. rotundus in North America. Furthermore, we also found a reduction in the standard deviation of temperatures at D. rotundus capture locations during the last century, expressed as more consistent, less-seasonal climate in recent years. These results elucidate an association between D. rotundus range expansion and a continental-level rise in rabies virus spillover transmission from D. rotundus to cattle in the last 50 years of the 120-year study period. This correlative study, based on field observations, offers empirical evidence supporting previous statistical and mathematical simulation-based studies reporting a likely increase of bat-borne diseases in response to climate change. We conclude that the D. rotundus rabies system exemplifies the consequences of climate change augmentation at the wildlife–livestock–human interface, demonstrating how global change acts upon these complex and interconnected systems to drive increased disease emergence.
- COVID-19 Reveals Vulnerabilities of the Food–Energy–Water Nexus to Viral PandemicsCalder, Ryan S. D.; Grady, Caitlin; Jeuland, Marc; Kirchhoff, Christine J.; Hale, Rebecca L.; Muenich, Rebecca L. (American Chemical Society, 2021)Food, energy, and water (FEW) sectors are inextricably linked, making one sector vulnerable to disruptions in another. Interactions between FEW systems, viral pandemics, and human health have not been widely studied. We mined scientific and news/media articles for causal relations among FEW and COVID-19 variables and qualitatively characterized system dynamics. Food systems promoted the emergence and spread of COVID-19, leading to illness and death. Major supply-side breakdowns were avoided (likely due to low morbidity/mortality among working-age people). However, COVID-19 and physical distancing disrupted labor and capital inputs and stressed supply chains, while creating economic insecurity among the already vulnerable poor. This led to demand-side FEW insecurities, in turn increasing susceptibility to COVID-19 among people with many comorbidities. COVID-19 revealed trade-offs such as allocation of water to hygiene versus to food production and disease burden avoided by physical distancing versus disease burden from increased FEW insecurities. News/media articles suggest great public interest in FEW insecurities triggered by COVID-19 interventions among individuals with low COVID-19 case-fatality rates. There is virtually no quantitative analysis of any of these trade-offs or feedbacks. Enhanced quantitative FEW and health models are urgently needed as future pandemics are likely and may have greater morbidity and mortality than COVID-19.
- A database of common vampire bat reportsvan de Vuurst, Paige; Diaz, M. Monica; Rodriguez-San Pedro, Annia; Allendes, Juan Luis; Brown, Natalie; Gutierrez, Juan David; Zarza, Heliot; de Oliveira, Stefan V.; Cardenas-Canales, Elsa; Barquez, Ruben M.; Escobar, Luis E. (Nature Portfolio, 2022-02-16)The common vampire bat (Desmodus rotundus) is a sanguivorous (i.e., blood-eating) bat species distributed in the Americas from northern Mexico southwards to central Chile and Argentina. Desmodus rotundus is one of only three mammal species known to feed exclusively on blood, mainly from domestic mammals, although large wildlife and occasionally humans can also serve as a food source. Blood feeding makes D. rotundus an effective transmissor of pathogens to its prey. Consequently, this species is a common target of culling efforts by various individuals and organizations. Nevertheless, little is known about the historical distribution of D. rotundus. Detailed occurrence data are critical for the accurate assessment of past and current distributions of D. rotundus as part of ecological, biogeographical, and epidemiological research. This article presents a dataset of D. rotundus historical occurrence reports, including >39,000 locality reports across the Americas to facilitate the development of spatiotemporal studies of the species. Data are available at https://doi.org/10.6084/ m9.figshare.15025296.
- A database of global coastal conditionsCastaneda-Guzman, Mariana; Mantilla-Saltos, Gabriel; Murray, Kris A.; Settlage, Robert; Escobar, Luis E. (2021-11-26)Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth's surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies.
- The Distribution, Seasonal Abundance, and Environmental Factors Contributing to the Presence of the Asian Longhorned Tick (Haemaphysalis longicornis, Acari: Ixodidae) in Central Appalachian VirginiaCumbie, Alexandra N.; Whitlow, Amanda M.; Arneson, Alicia; Du, Zhiyuan; Eastwood, Gillian (Oxford University Press, 2022-05-30)Over the past decade, Haemaphysalis longicornis, the Asian longhorned tick, has undergone a geographic range expansion in the United States, from its historical range in east Asia. This tick has been characterized by its frequent parasitism of livestock, an ability to reproduce through parthenogenesis, and its ability to transmit a variety of vector-borne pathogens to livestock, wildlife, and human hosts in its native geographic range. Thus far in the United States, 17 states have reported H. longicornis populations, including 38 counties in Virginia. These numbers come from presence-absence reports provided to the U.S. Department of Agriculture, but little has been reported about this ticks' seasonality in Virginia or its habitat preferences. Our current study detected H. longicornis populations in seven of the nine surveyed counties in Virginia. Haemaphysalis longicornis were observed in multiple habitat types including mixed hardwood forests and pastures, with abundant H. longicornis populations detected at one particular pasture site in Wythe County. This study also attempted to investigate environmental conditions that may be of importance in predicting tick presence likelihood. While sample size limited the scope of these efforts, habitat type and climatic metrics were found to be important indicators of H. longicornis collection success and abundance for both the nymphal and larval life stages. This current study reports useful surveillance data for monitoring these tick populations as they become established in the western half of Virginia and provides insight into their current distribution and maintenance over a large study region.
- Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease predictionHolcomb, Karen M.; Mathis, Sarabeth; Staples, J. Erin; Fischer, Marc; Barker, Christopher M.; Beard, Charles B.; Nett, Randall J.; Keyel, Alexander C.; Marcantonio, Matteo; Childs, Marissa L.; Gorris, Morgan E.; Rochlin, Ilia; Hamins-Puértolas, Marco; Ray, Evan L.; Uelmen, Johnny A.; DeFelice, Nicholas; Freedman, Andrew S.; Hollingsworth, Brandon D.; Das, Praachi; Osthus, Dave; Humphreys, John M.; Nova, Nicole; Mordecai, Erin A.; Cohnstaedt, Lee W.; Kirk, Devin; Kramer, Laura D.; Harris, Mallory J.; Kain, Morgan P.; Reed, Emily M. X.; Johansson, Michael A. (2023-01-12)Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases).
- First Evidence of Powassan Virus (Flaviviridae) in Ixodes scapularis in Appalachian Virginia, USACumbie, Alexandra N.; Whitlow, Amanda M.; Eastwood, Gillian (American Society of Tropical Medicine and Hygiene, 2022-03-01)Here we report the first detection and confirmation of Powassan virus (POWV) (family: Flaviridae) in Ixodes scapularis ticks collected from Appalachian Virginia. Ixodes scapularis ticks were collected from vegetation across field sites in eight counties of western Virginia from June 2019 to April 2021. From these collections, one nymph and one adult male I. scapularis were determined to be positive for POWV using real-time RT-PCR and Sanger sequencing. Both positive ticks were collected from Floyd county, VA, at residential sites; the nymph in June 2020 and the adult male in April 2021. The presence of POWV in Virginia in its natural tick vector is crucial knowledge in beginning to understand the movement and transmission of this pathogen into new geographical areas and the risk it poses to medical and veterinary health.
- Forecasting ecosystem services to guide coastal wetland rehabilitation decisionsCalder, Ryan S. D.; Shi, Congjie; Mason, Sara A.; Olander, Lydia P.; Borsuk, Mark E. (Elsevier, 2019-10-01)Coastal wetlands provide diverse ecosystem services such as flood protection and recreational value. However, predicting changes in ecosystem service value fr0k from restoration or management is challenging because environmental systems are highly complex and uncertain. Furthermore, benefits are diverse and accrue over various timescales. We developed a generalizable mathematical coastal management model to compare restoration expenditures to ecosystem service benefits and apply it to McInnis Marsh, Marin County, California, USA. We find that benefits of restoration outweigh costs for a wide range of assumptions. For instance, costs of restoration range from 8–30% of the increase in ecosystem service value over 50 years depending on discount rate. Flood protection is the dominant monetized service for most payback periods and discount rates, but other services (e.g., recreation) dominate on shorter timescales (>50% of total value for payback periods ≤4 years). We find that the range of total ecosystem service value is narrower than overall variability reported in the literature, supporting the use of mechanistic methods in decision-making around coastal resiliency. However, the magnitude and relative importance of ecosystem services are sensitive to payback period, discount rate and risk tolerance, demonstrating the importance of probabilistic decision analysis. This work provides a modular, transferrable tool to that can also inform coastal resiliency investments elsewhere.
- Geohealth Policy Benefits Are Mediated by Interacting Natural, Engineered, and Social ProcessesCalder, Ryan S. D.; Schartup, Amina T. (American Geophysical Union, 2023-08-29)Interest in health implications of Earth science research has significantly increased. Articles frequently dispense policy advice, for example, to reduce human contaminant exposures. Recommendations such as fish consumption advisories rarely reflect causal reasoning around tradeoffs or anticipate how scientific information will be received and processed by the media or vulnerable communities. Health is the product of interacting social and physical processes, yet predictable responses are often overlooked. Analysis of physical and social mechanisms, and health and non-health tradeoffs, is needed to achieve policy benefits rather than “policy impact.” Dedicated funding mechanisms would improve the quality and availability of these analyses.
- Graphical models and the challenge of evidence-based practice in development and sustainabilityCalder, Ryan S. D.; Alatorre, Andrea; Marx, Rebecca S.; Mallampalli, Varun; Mason, Sara A.; Olander, Lydia P.; Jeuland, Marc; Borsuk, Mark E. (Elsevier, 2020-08-01)Governments and social benefit organizations are expected to consider evidence in decision-making. In development and sustainability, evidence spans disciplines and methodological traditions and is often inconclusive. Graphical models are widely promoted to organize interdisciplinary evidence and improve decision-making by considering mediating variables. However, the reproducibility, objectivity and benefits for decision-making of graphical models have not been studied. We evaluate these considerations in the setting of energy services in the developing world, a contemporary development and sustainability imperative. We develop a database of relevant causal relations (313 concepts, 1337 relationships) asserted in the literature (561 peer-reviewed articles). We demonstrate that high-level relationships of interest to practitioners feature less consistent evidence than the causal relationships that underpin them, supporting increased use of problem decomposition through graphical modeling approaches. However, adding such detail increases complexity exponentially, introducing a hazard of overparameterization if evidence is not available to match the level of mechanistic detail.
- Horsenettle (Solanum carolinense) fruit bacterial communities are not variable across fine spatial scalesHeminger, Ariel R.; Belden, Lisa K.; Barney, Jacob N.; Badgley, Brian D.; Haak, David C. (PeerJ, 2021-11-08)Fruit house microbial communities that are unique from the rest of the plant. While symbiotic microbial communities complete important functions for their hosts, the fruit microbiome is often understudied compared to other plant organs. Fruits are reproductive tissues that house, protect, and facilitate the dispersal of seeds, and thus they are directly tied to plant fitness. Fruit microbial communities may, therefore, also impact plant fitness. In this study, we assessed how bacterial communities associated with fruit of Solanum carolinense, a native herbaceous perennial weed, vary at fine spatial scales (<0.5 km). A majority of the studies conducted on plant microbial communities have been done at large spatial scales and have observed microbial community variation across these large spatial scales. However, both the environment and pollinators play a role in shaping plant microbial communities and likely have impacts on the plant microbiome at fine scales. We collected fruit samples from eight sampling locations, ranging from 2 to 450 m apart, and assessed the fruit bacterial communities using 16S rRNA gene amplicon sequencing. Overall, we found no differences in observed richness or microbial community composition among sampling locations. Bacterial community structure of fruits collected near one another were not more different than those that were farther apart at the scales we examined. These fine spatial scales are important to obligate out-crossing plant species such as S. carolinense because they are ecologically relevant to pollinators. Thus, our results could imply that pollinators serve to homogenize fruit bacterial communities across these smaller scales.
- The Influence of Southwestern Virginia Environmental Conditions on the Potential Ability of Haemaphysalis longicornis, Amblyomma americanum, and Amblyomma maculatum to Overwinter in the RegionWhitlow, Amanda Marie; Schürch, Roger; Mullins, Donald E.; Eastwood, Gillian (MDPI, 2021-11-06)Ticks are susceptible to environmental conditions and, to ensure survival during winter conditions, they adopt a wide variety of physiological and behavioral adaptations including utilization of a suitable niche with insulation (e.g., leaf coverage). To investigate the potential overwintering survival of three tick populations emerging within Appalachian Virginia (Haemaphysalis longicornis, Amblyomma americanum, and Amblyomma maculatum), both a laboratory experiment assessing super-cooling points and a two-factor (elevation and insulation coverage) field experiment assessing overwintering survivability were conducted across a natural southwestern Virginian winter (2020–2021). Dermacentor variabilis adults were included in this study as an example of a well-established species in this region known to overwinter in these conditions. Our study indicated that A. americanum and H. longicornis wintering tolerance is based on life stage rather than external factors such as insulation (e.g., leaf litter) and elevation. Amblyomma maculatum was more likely to survive without insulation. The ability to withstand the extreme temperatures of new regions is a key factor determining the survivability of novel tick species and is useful in assessing the invasion potential of arthropod vectors.
- La Crosse Virus Circulation in Virginia, Assessed via Serosurveillance in Wildlife SpeciesFaw, Lindsey R.; Riley, Jennifer; Eastwood, Gillian (MDPI, 2023-06-30)Mosquito-borne La Crosse virus (LACV; family: Peribunyaviridae) is the leading cause of pediatric arboviral encephalitis in the United States, with clinical cases generally centered in the Midwest and Appalachian regions. Incidence of LACV cases in Appalachian states has increased, such that the region currently represents the majority of reported LACV cases in the USA. The amount of reported LACV cases from Virginia, however, is minimal compared to neighboring states such as North Carolina, West Virginia, and Tennessee, and non-Appalachian regions of Virginia are understudied. Here we examine the hypothesis that LACV is circulating widely in Virginia, despite a low clinical case report rate, and that the virus is circulating in areas not associated with LACV disease. In this study, we screened local mammalian wildlife in northwestern counties of Virginia using passive surveillance via patients submitted to wildlife rehabilitation centers. Blood sera (527 samples; 9 species, 8 genera) collected between October 2019 and December 2022 were screened for neutralizing antibodies against LACV, indicating prior exposure to the virus. We found an overall LACV seroprevalence of 1.90% among all wild mammals examined and reveal evidence of LACV exposure in several wild species not generally associated with LACV, including eastern cottontails and red foxes, along with established reservoirs, eastern gray squirrels, although there was no serological evidence in chipmunks. These data indicate the circulation of LACV in Virginia outside of Appalachian counties, however, at a lower rate than reported for endemic areas within the state and in other states.
- A Landscape Epidemiological Approach for Predicting Chronic Wasting Disease: A Case Study in Virginia, USWinter, Steven N.; Kirchgessner, Megan S.; Frimpong, Emmanuel A.; Escobar, Luis E. (2021-08-24)Many infectious diseases in wildlife occur under quantifiable landscape ecological patterns useful in facilitating epidemiological surveillance and management, though little is known about prion diseases. Chronic wasting disease (CWD), a fatal prion disease of the deer family Cervidae, currently affects white-tailed deer (Odocoileus virginianus) populations in the Mid-Atlantic United States (US) and challenges wildlife veterinarians and disease ecologists from its unclear mechanisms and associations within landscapes, particularly in early phases of an outbreak when CWD detections are sparse. We aimed to provide guidance for wildlife disease management by identifying the extent to which CWD-positive cases can be reliably predicted from landscape conditions. Using the CWD outbreak in Virginia, US from 2009 to early 2020 as a case study system, we used diverse algorithms (e.g., principal components analysis, support vector machines, kernel density estimation) and data partitioning methods to quantify remotely sensed landscape conditions associated with CWD cases. We used various model evaluation tools (e.g., AUC ratios, cumulative binomial testing, Jaccard similarity) to assess predictions of disease transmission risk using independent CWD data. We further examined model variation in the context of uncertainty. We provided significant support that vegetation phenology data representing landscape conditions can predict and map CWD transmission risk. Model predictions improved when incorporating inferred home ranges instead of raw hunter-reported coordinates. Different data availability scenarios identified variation among models. By showing that CWD could be predicted and mapped, our project adds to the available tools for understanding the landscape ecology of CWD transmission risk in free-ranging populations and natural conditions. Our modeling framework and use of widely available landscape data foster replicability for other wildlife diseases and study areas.
- Life Cycle Impact Assessment of Iron Oxide (Fe3O4/γ-Fe2O3) Nanoparticle Synthesis RoutesRahman, Asifur; Kang, Seju; McGinnis, Sean; Vikesland, Peter J. (2022)The synthesis of superparamagnetic iron oxide nanoparticles (FeOx-NPs) has rapidly developed over the past decade due to their wide-ranging applications in research and technology. However, at present there exists very limited knowledge about the environmental impacts of the various input materials and the energy required for different FeOx-NP synthesis approaches. In this study, we used cradle-to-gate life cycle assessment (LCA) to analyze and compare the environmental impacts of FeOx-NPs produced via seven common synthesis routes. Four different functional units (i.e., mass, mean particle size, specific surface area, and saturation magnetization) were used to normalize the environmental impacts and evaluate the corresponding changes. Overall, physical and biological synthesis routes exhibited high environmental impacts due to their higher input material and energy requirements. Interestingly, biological syntheses had the highest environmental impacts due to their reliance on bacterial culture media. All of the chemical synthesis routes had lower environmental impacts except the thermal decomposition method, which had higher environmental impacts due its use of non-polar organic solvents during synthesis. The lab-scale LCA inventory data and analysis presented here addresses the existing data gaps and helps guide future research for FeOx-NP synthesis under industrial conditions. The information generated by this effort aids in the identification of environmentally friendly and sustainable production pathways for FeOx-NPs.
- Linked within-host and between-host models and data for infectious diseases: a systematic reviewChilds, Lauren M.; El Moustaid, Fadoua; Gajewski, Zachary J.; Kadelka, Sarah; Nikin-Beers, Ryan; Smith, John W. Jr.; Walker, Melody; Johnson, Leah R. (PeerJ, 2019-06-19)The observed dynamics of infectious diseases are driven by processes across multiple scales. Here we focus on two: within-host, that is, how an infection progresses inside a single individual (for instance viral and immune dynamics), and between-host, that is, how the infection is transmitted between multiple individuals of a host population. The dynamics of each of these may be influenced by the other, particularly across evolutionary time. Thus understanding each of these scales, and the links between them, is necessary for a holistic understanding of the spread of infectious diseases. One approach to combining these scales is through mathematical modeling. We conducted a systematic review of the published literature on multi-scale mathematical models of disease transmission (as defined by combining within-host and between-host scales) to determine the extent to which mathematical models are being used to understand across-scale transmission, and the extent to which these models are being confronted with data. Following the PRISMA guidelines for systematic reviews, we identified 24 of 197 qualifying papers across 30 years that include both linked models at the within and between host scales and that used data to parameterize/calibrate models. We find that the approach that incorporates both modeling with data is under-utilized, if increasing. This highlights the need for better communication and collaboration between modelers and empiricists to build well-calibrated models that both improve understanding and may be used for prediction.
- Modeling Temperature Effects on Population Density of the Dengue Mosquito Aedes aegyptiEl Moustaid, Fadoua; Johnson, Leah R. (MDPI, 2019-11-07)Mosquito density plays an important role in the spread of mosquito-borne diseases such as dengue and Zika. While it remains very challenging to estimate the density of mosquitoes, modelers have tried different methods to represent it in mathematical models. The goal of this paper is to investigate the various ways mosquito density has been quantified, as well as to propose a dynamical system model that includes the details of mosquito life stages leading to the adult population. We first discuss the mosquito traits involved in determining mosquito density, focusing on those that are temperature dependent. We evaluate different forms of models for mosquito densities based on these traits and explore their dynamics as temperature varies. Finally, we compare the predictions of the models to observations of Aedes aegypti abundances over time in Vitòria, Brazil. Our results indicate that the four models exhibit qualitatively and quantitatively different behaviors when forced by temperature, but that all seem reasonably consistent with observed abundance data.