Areas Of Florida Research Articles

Impacts of red tide in peer-to-peer accommodations: A multi-regional input-output model

Increases in the incidence or severity of hazard events significantly alter the attractiveness of tourism destinations and tourism inflow. In 2018, a significant red tide event limited access to marine and coastal areas in Florida, heavily impacting the tourist sector. The purpose of this study was to estimate the economic impacts of red tides in the state economy through the shock in the Airbnb market. We combined microdata on Airbnb properties and water sample records and estimated that water sample indicating the presence of red tide conditions within a county decreases the average daily rate price of Airbnb rentals by $0.45 and the number of reservation days by 345. This event generated $317 million in sales revenue losses and resulted in the loss of nearly 2900 job-years throughout Florida. Knowledge of such consequences is essential to inform decision-making processes for policy makers and tourism management professionals.

The diet of Florida Box Turtles (Terrapene bauri) in a coastal ecosystem in southwestern Florida

North American Box Turtles are opportunistic generalists with omnivorous tendencies, but diets of box turtles are known to vary by population, region, and season. Relatively few studies have examined the diet of Florida Box Turtles (Terrapene bauri). By analyzing fecal samples and direct observations of feeding, we describe the diet of Florida Box Turtles in a coastal area in southern Florida. Fecal samples of turtles in this population contained four functional groups of plants and algae, 11 categories of animals, plus miscellaneous unidentifiable and mineral matter. Frequencies of occurrence differed significantly between wet and dry seasons but not between sexes. Seeds of the invasive Beach Cabbage (Scaevola taccada) were among the most frequently detected plant items, whereas Coffee Bean Snails (Melampus coffea) and ocypodid crabs were the most frequently encountered animal items.

Elemental composition of airborne particulate matter from coastal South Florida area influenced by African dust events

• The elements Pb, Zn, V, Ni, Cd, As, Cr, and Cu presented the highest EFs. • As, Ni, Cd and Pb levels were below the maximum levels set by EU and USEPA. • REE were used to identify African dust contributions to the local APM. • The oil-fired Port Everglades Power Plant played an important role in the APM. • Road dust and waste incineration emissions were the second APM source of importance. Airborne particulate matter (APM) is a complex mixture of dust, dirt, soot and smoke containing both organic and inorganic components as well as biological particles. APM below 10 µm can enter the respiratory track and are known to cause adverse health effects. African dust storms are responsible for the transport of large amount of APM across the Atlantic Ocean during summer months. Anthropogenic activities are also responsible for APM pollution contribution in coastal areas and could have potential effects on sensitive ecosystems. The present study evaluates the elemental composition of APM collected from a coastal area in South Florida. In this study, a high-volume air sampler equipped with Versapor filters and located near the Port of Fort Lauderdale was employed for APM collection from 2005 to 2010. APM chemical composition was analyzed for multiple elements by ICP-MS. Seven of the eleven metals listed by the EPA as hazardous air pollutants (Mn, Cd, Cr, Ni, Pb, As, Co and Se) were detected in the samples. Iron and aluminum were the most abundant elements found in all samples, followed by V and Ni, which are usually associated with anthropogenic pollution coming from fossil fuel combustion. Specific sources of APM pollution were identified by principal component analysis and using the U.S. EPA UNMIX model for environmental data analyses. Rare earth elements were used to identify contributions of geological material to the APM and African dust influence during the summer months.

GIS-automated delineation of hospital service areas in Florida: from Dartmouth method to network community detection methods

ABSTRACT Since the Dartmouth Hospital Service Areas (HSAs) were proposed three decades ago, there has been a large body of work using the unit in examining the geographic variation in health care in the U.S. for evaluating health care system performance and informing health policy. However, many studies question the replicability and reliability of the Dartmouth HSAs in meeting the challenges of an ever-changing and a diverse set of health care services. This research develops a reproducible, automated, and efficient GIS tool to implement Dartmouth method for defining HSAs. Moreover, the research adapts two popular network community detection methods to account for spatial constraints for defining HSAs that are scale flexible and optimize an important property such as maximum service flows within HSAs. A case study based on the state inpatient database in Florida from the Healthcare Cost and Utilization Project is used to evaluate the efficiency and effectiveness of the methods. The study represents a major step towards developing HSA delineation methods that are computationally efficient, adaptable for various scales (from a local region to as large as a national market) and automated without a steep learning curve for public health professionals.

Crustal structure and lateral variations in the Gulf of Mexico conjugate margins: From rifting to break-up

The Gulf of Mexico opened as a Late Triassic-Mid Jurassic continental rift that was first largely covered by the Mid-Jurassic Louann Salt and later split apart by a triangular-shaped oceanic crust. Salt in the Gulf of Mexico largely hampers the imaging and interpretation of underlying pre-salt and crustal geometries, which are fundamental for assessing the early kinematic evolution of the margin. To better define these deep geometries and their lateral variations, we built three seismic-based crustal-scale cross-sections across the Florida-Yucatan conjugate margins, in the areas where the Louann Salt is thinner. They were used, together with magnetic and gravity anomalies data, to build a crustal domains map for the study area. Cross-sections show a meaningful along-strike variation: the South Florida-East Yucatan area is characterized by a narrower rifted continental crust that evolves sharply to oceanic crust whereas in the North Florida and central-western Yucatan areas, the rifted continental crust is wider and the transition to the oceanic crust corresponds to a narrow magmatic or exhumed mantle domain. Bulk continental crust extension was determined using the area balancing method. Estimated horizontal extension values vary from a minimum of ∼120 km in the South Florida-East Yucatan conjugate to a minimum of ∼240 km in the North Florida-Central Yucatan conjugate, being systematically larger in the northern margin. Based on our observations and considering previous models, we propose that the study area evolved from an early rift involving magmatism, to a magma-poor margin, with continental break-up (OCT formation) being characterized by mantle exhumation and associated magmatism along the North Florida and central-western Yucatan areas. As in other analogues such as the Gulf of Guinea, the thick evaporite deposited during the late rift, while mantle was being exhumed.

Social disorganization and new HIV diagnoses, 2013-2017, Florida: Rural-urban differences.

To compare the role of neighborhood social disorganization factors on human immunodeficiency virus (HIV) diagnosis rates in urban and rural areas in Florida, we conducted an ecologic study of HIV diagnosis rates during 2013-2017 and social disorganization components, including concentrated disadvantage, ethnic heterogeneity, and residential instability. Indices of social disorganization components were obtained from principal component analyses of American Community Survey variables for 910 postal codes. Rural/urban classification was based on the United States Department of Agriculture Rural Urban Commuting Area codes. Using multivariable linear regression, the relationship between social disorganization indices and HIV diagnosis rates was assessed. The only social disorganization index that was significantly higher in rural than urban areas was concentrated disadvantage. In rural areas, the concentrated disadvantage index was significantly associated with HIV diagnosis rates (P = .007) when controlling for the other social disorganization factors but was no longer significant after additionally controlling for prevalence of people with an HIV diagnosis who were not virally suppressed. In urban areas, even after controlling for prevalence of people with HIV who were not virally suppressed, lower male-to-female population ratios and higher scores of residential instability, concentrated disadvantage, and LatinX/immigrant density indices were associated with higher HIV diagnosis rates (all P < .01). In addition to improving community levels of viral suppression, the community contextual environment, including the rurality of the environment, needs to be considered in strategies to end the HIV epidemic in the United States.

How COVID-19 Exposed Water Supply Fragility in Florida, USA

Healthcare demand for liquid oxygen during the COVID-19 pandemic limited the availability of oxygen needed for ozone disinfection of drinking water in several urban areas of Florida. While the situation reduced the state’s capacity to provide normal drinking water treatment for millions of people, calls for water conservation during the emergency period resulted in virtually no change in water consumption. Here, we point out that 38–40% of the potable water produced by one of the major utilities in Florida is not used for drinking water but instead is used for outdoor landscape irrigation. This suggests that emergency-level calls for reduced water use could have been made if outdoor irrigation was limited, but we present data showing that there was little change in public behavior, and the state was unable to meet necessary water use reductions during the emergency. This inability to meet short-term emergency water conservation needs foretells a long-term lack of resilience against other global change scenarios and suggests that much work is still needed to build resilience into Florida’s water future. We conclude this Viewpoint paper by calling for more urgent sociohydrological research to understand the coupled human-natural drivers of how water supplies respond to global change.

Application of Google earth engine python API and NAIP imagery for land use and land cover classification: A case study in Florida, USA

The analysis of land use and land cover data provides invaluable support to a variety of land management and conservation activities. However, historically its application has been limited by high costs associated with data acquisition, analysis, and classification. In recent years, freely available satellite imagery and geospatial data sets and rapid advancement in data analysis capabilities provide immense opportunities to understand and solve the real-world environmental problems. Open-source platforms such as Google Earth Engine (GEE) provide a planetary-scale environmental science data and analyses capability at much greater efficiency and accuracy than the traditional workflows. We evaluated the GEE Python API utility for classifying the freely available NAIP aerial imagery of 2017 to derive the land use land cover (LULC) information of a Panhandle area of Florida, USA. We identified eight major LULC classes with an overall accuracy of 86% and Kappa value of 79%. We completed all remote sensing data analyses procedures including data retrieval, classification, and report preparation in the Jupyter notebook, an open-source web application. Computation time for the procedure was less than 15 min. Our results demonstrate the usefulness of this approach for conducting land use and land cover analysis using much less time, money, and human resources. The open-source nature of GEE Python API and its library of remote sensing data could benefit remote sensing projects throughout the world, especially where access to commercial image processing software packages and remote sensing data are limited.

Individual hurricane evacuation intentions during the COVID-19 pandemic: insights for risk communication and emergency management policies

The U.S. 2020 hurricane season was extraordinary because of a record number of named storms coinciding with the COVID-19 pandemic. This study draws lessons on how individual hurricane preparedness is influenced by the additional risk stemming from a pandemic, which turns out to be a combination of perceptions of flood and pandemic risks that have opposite effects on preparedness behavior. We conducted a survey in early June 2020 of 600 respondents in flood-prone areas in Florida to obtain insights into households’ risk perceptions and preparedness for the upcoming hurricane season under COVID-19. The results show that concerns over COVID-19 dominated flood risk perceptions and negatively impacted people’s evacuation intentions. Whereas hotel costs were the main obstacle to evacuating during Hurricane Dorian in 2019 in the same geographic study area, the main evacuation obstacle identified in the 2020 hurricane season is COVID-19. Our statistical analyses investigating the factors influencing evacuation intentions show that older individuals are less likely to evacuate under a voluntary order, because they are more concerned about the consequences of becoming infected by COVID-19. We observe similar findings based on a real-time survey we conducted in Florida with another group of respondents under the threat of Hurricane Eta at the end of the hurricane season in November 2020. We discuss the implications of our findings for risk communication and emergency management policies that aim to improve hurricane preparedness when dealing with additional health risks such as a pandemic, a situation that may be exacerbated under the future climate.

The OneFlorida Data Trust: a centralized, translational research data infrastructure of statewide scope.

The OneFlorida Data Trust is a centralized research patient data repository created and managed by the OneFlorida Clinical Research Consortium (“OneFlorida”). It comprises structured electronic health record (EHR), administrative claims, tumor registry, death, and other data on 17.2 million individuals who received healthcare in Florida between January 2012 and the present. Ten healthcare systems in Miami, Orlando, Tampa, Jacksonville, Tallahassee, Gainesville, and rural areas of Florida contribute EHR data, covering the major metropolitan regions in Florida. Deduplication of patients is accomplished via privacy-preserving entity resolution (precision 0.97–0.99, recall 0.75), thereby linking patients’ EHR, claims, and death data. Another unique feature is the establishment of mother-baby relationships via Florida vital statistics data. Research usage has been significant, including major studies launched in the National Patient-Centered Clinical Research Network (“PCORnet”), where OneFlorida is 1 of 9 clinical research networks. The Data Trust’s robust, centralized, statewide data are a valuable and relatively unique research resource.

Eight Species of Poaceae Are Hosting Different Genetic and Pathogenic Strains of Sugarcane Mosaic Virus in the Everglades Agricultural Area.

Sugarcane mosaic virus (SCMV) was detected by reverse transcription polymerase chain reaction in eight different species of the Poaceae family in the Everglades Agricultural Area (EAA) of south Florida: broadleaf signalgrass (Urochloa platyphylla), Columbus grass (Sorghum almum), goosegrass (Eleusine indica), maize (Zea mays), sorghum (Sorghum bicolor), St. Augustine grass (Stenotaphrum secundatum), southern crabgrass (Digitaria ciliaris), and sugarcane (Saccharum interspecific hybrids). Based on their coat protein (CP) gene sequence, 62 isolates of SCMV from Florida and 29 worldwide isolates representing the known genetic diversity of this virus were distributed into eight major phylogenetic groups. SCMV isolates infecting Columbus grass, maize, and sorghum in Florida formed a unique group, whereas virus isolates infecting sugarcane in the United States (Florida and Louisiana) clustered with isolates from other countries. Based on the entire genome coding region, SCMV isolates infecting sugarcane in Florida were closest to virus isolates infecting sorghum species or St. Augustine grass. Virus isolates from Columbus grass, St. Augustine grass, and sugarcane showed different virulence patterns after mechanical inoculation of Columbus grass, St. Augustine grass, and sugarcane plants, thus proving that these isolates were different pathogenic strains. Sugarcane was symptomless and tested negative for SCMV by tissue blot immunoassay after inoculation with crude sap from SCMV-infected Columbus grass, indicating that Columbus grass was not a reservoir for SCMV infecting sugarcane in the EAA. Close CP sequence identity between isolates of SCMV from Columbus grass, maize, and sorghum suggested that the same virus strain was naturally spreading between these three plants in south Florida.

Environmental Fate and Behavior of the Herbicide Glyphosate in Sandy Soils of Florida Under Citrus Production

Chemical weed control using herbicide glyphosate to manage emerged weeds is an important production practice in Florida citrus. Despite the extensive use of glyphosate in citrus orchards, very limited information is available on its environmental fate and behavior in Florida soils that are predominantly sandy in nature. Hence, the study’s objective was to understand the adsorption-desorption, dissipation dynamics, and vertical movement or leaching of glyphosate in sandy soils in citrus orchards. Laboratory, field, and greenhouse experiments were conducted at Southwest Florida Research and Education Center in Immokalee, Florida. The adsorption-desorption behavior of glyphosate in the soils from three major citrus production areas in Florida was studied utilizing a batch equilibrium method. The dissipation of glyphosate was tracked in the field following its application at the rate of 4.20 kg ae ha−1. Soil leaching columns in greenhouse conditions were used to study the vertical movement of glyphosate. The results suggest that glyphosate has a relatively lower range of adsorption or binding (Kads = 14.28–30.88) in the tested soil types. The field dissipation half-life (DT50) of glyphosate from surface soil was found to be ∼26 days. Glyphosate moved vertically or leached into the soil profile, up to 40 cm in the soil column, when analyzed 40 days after herbicide application. The primary degradation product of glyphosate, i.e., aminomethyl phosphonic acid (AMPA), was also detected up to the depth of 30 cm below the soil surface, indicating the presence of microbial metabolism of glyphosate in the soil.

Community of Bark and Ambrosia Beetles (Coleoptera: Curculionidae: Scolytinae and Platypodinae) Infesting Brazilian Peppertree Treated With Herbicide and the Volatile Tree Response.

Brazilian peppertree, Schinus terebinthifolia Raddi (Anacardiaceae), is one of the most invasive weeds of natural and agricultural areas of Florida, Hawaii, and Texas (USA). Herbicides are the main tool used to manage populations of this weed. Faunal inventories of the insects associated with invasive populations of the weed have mostly listed leaf-feeding phytophagous, pollinator, or predacious species. Among these, bark and ambrosia beetles were collected only once from S. terebinthifolia in the invaded range and there are no reports from the native range. A diverse assemblage of bark and ambrosia beetles, many well-known economic pests of ornamentals, was reared from S. terebinthifolia bolts collected at a restoration site in Florida that had been treated with herbicide (triclopyr ester). A similar collection of beetles was captured on ethanol-baited sticky traps. No beetles emerged from bolts of untreated trees, almost none emerged from those wounded with a machete (3.1% of total), whereas nearly all the beetles collected emerged from bolts that had been treated with herbicide (62.3%) or the combination wounded + herbicide (34.6%). Ethanol was detected from the herbicide and wound + herbicide-treated bolts suggesting this was the attractive kairomone. Abundant amounts of other volatiles were collected from all bolts, especially from the wounded treatment, but no association was detected between volatile emissions and beetle infestation. Further studies are needed to determine whether invasive populations of S. terebinthifolia treated with herbicides constitute reservoirs for pest bark and ambrosia beetles that may spill over onto neighboring ornamental hosts.

Automated flight planning of high-density urban air mobility

Advanced Air Mobility (AAM) is an emerging concept for transporting people and cargo in urban, rural, regional, and interregional settings using revolutionary new aircraft. Urban Air Mobility (UAM), a part of AAM, focused on transport passengers in low-altitude urban airspace, has attracted extensive attention among industry, government, academia, and the public. Compared to existing commercial flights, AAM operations are expected to be at higher density; thus, an AAM system needs to be scalable, safe, and autonomous. Third-party service providers are recommended for offering air traffic management and information sharing services given the anticipated high density of UAM operations. To this end, we propose an Automated Flight Planning System (AFPS) that could be employed by such service providers. In the AFPS, a Low-Altitude Airspace Management System (LAMS) is proposed to automatically generate a route network with the capability of avoiding obstacles and obstructions in low-altitude airspace. The main components of this tool are the generation of a 3D map with LiDAR data, construction of a nodal network based on the map by using the visibility graph method, and initiation of 3D shortest paths. Given the requests of flight operations, i.e., origin, destination, departure time, the Low-Altitude Traffic Management System (LTMS) will design pre-departure conflict-free 4D trajectories and provide flexibilities of en-route maneuvering by taking system cost and equity among operators into consideration. In this study, a flight-level assignment strategy is proposed to solve the trajectory deconfliction problem in LTMS. In addition, a Nash Social Welfare Program (NSWP) is introduced to maintain fairness among different operators if the service is provided to multiple operators of UAM. A case study of the Tampa Bay area in Florida is used to demonstrate the operability of the proposed AFPS, and animations are built to visualize the optimized conflict-free operations of UAM in the study area.

Discovery of Known and Novel Viruses in Wild and Cultivated Blueberry in Florida through Viral Metagenomic Approaches.

Southern highbush blueberry (interspecific hybrids of Vaccinium corymbosum L.) is cultivated near wild V. corymbosum as well as closely related species in Florida, USA. The expansion of blueberry cultivation into new areas in Florida and deployment of new cultivars containing viruses can potentially increase the diversity of viruses in wild and cultivated V. corymbosum. In this study, viral diversity in wild and cultivated blueberries (V. corymbosum) is described using a metagenomic approach. RNA viromes from V. corymbosum plants collected from six locations (two cultivated and four wild) in North Central Florida were generated by high throughput sequencing (HTS) and analyzed using a bioinformatic analysis pipeline. De novo assembled contigs obtained from viromes of both commercial and wild sites produced sequences with similarities to plant virus species from a diverse range of families (Amalgaviridae, Caulimoviridae, Endornaviridae, Ophioviridae, Phenuiviridae, and Virgaviridae). In addition, this study has enabled the identification of blueberry latent virus (BlLV) and blueberry mosaic associated ophiovirus (BlMaV) for the first time in Florida, as well as a tentative novel tepovirus (blueberry virus T) (BlVT) in blueberry. To the best of our knowledge, this is the first study that compares viral diversity in wild and cultivated blueberry using a metagenomic approach.

Toward suburbs: Examining neighborhood-level changes in naturally occurring affordable housing stock in Florida, USA

Due to a severe shortage of affordable housing in the United States, insufficient funding for housing programs, and the growing importance of preserving market-affordable rental units, it becomes increasingly imperative for housing scholars and policymakers to capture neighborhood-level changes in unsubsidized privately-owned affordable rental housing stock, also widely called naturally occurring affordable housing (NOAH) stock. In this study, first, we propose a unique way to estimate changes in the number of NOAH units at a neighborhood level by using the Comprehensive Housing Affordability Strategy and other secondary datasets. Second, applying this approach, we analyze neighborhood-level changes in NOAH stock based on the four largest core-based statistical areas in Florida from 2000 to 2016 with a particular emphasis on identifying the relative growth of NOAH units in suburban neighborhoods. Results derived from multivariate census-tract-level regressions reveal that although a large proportion of NOAH units is still located in urban neighborhoods, newly generated NOAH tends to be disproportionately located in suburban neighborhoods. The proposed approach to estimating changes in NOAH stock can help local municipalities that desire to identify neighborhood-level needs for affordable housing preservation align resources with changes in NOAH stock within a metropolitan area.

An adaptable technique for comparative image assessment: Application to crosswell electromagnetic survey design for fluid monitoring

Reservoir integrity stewardship accompanying carbon capture and sequestration considers fluid extraction and reinjection as a risk-mitigating method against overpressuring that could lead to caprock damage and ensuing [Formula: see text] leakage. Crosswell electromagnetics offers a technically viable monitoring method with the spatial volume coverage necessary for reservoir-encompassing pressure management. However, a certain logistic dilemma for deep gas sequestration into saline and thus electrically conductive aquifers is that crosswell magnetic-field measurements underperform in the imaging of more resistive plume bodies, further exacerbated when vertical arrays intersect, as opposed to surround, plumes. Comparative synthetic-data plume imaging of such scenarios rates the information content of magnetic-field versus electric-field 3D crosswell layouts for reservoir and infrastructure conditions of a representative pilot site in a coastal area in Florida. The image quality of the resulting plume replications can be ranked numerically through a newly proposed semblance qualifier, appraising the model goodness of fit to a given reference. In contrast to common least-squares measures for goodness of fit, the semblance formulation uses classifying logistic function types, thus enabling a better distinction of predefined anomaly features.

Time on the Market and Probability of Sale Using a Generalized Geometric Hazard Model

Abstract This study makes two main contributions to the applied econometrics literature. First, it shows how the all-important marginal effects for time on the market and probability of sale can be obtained from any hazard model. Second, it extends the generalization of the geometric due to Gómez-Déniz, E. 2010. “Another Generalization of the Geometric Distribution.” Test 19: 399–415 to include covariates for use in the estimation of time on the market and probability of sale regressions in real estate, thus creating an entirely new hazard model based on probability of sale rather than time on the market. For the generalized geometric we develop expressions for the marginal effects (with approximate standard errors) for both the probability of sale and time on the market. This formulation allows the impact of changes in independent variables on both the probability of sale and time on the market to be determined from a single regression model. For comparison, we also obtain these two sets of marginal effects for the popular Weibull hazard model. The geometric, generalized geometric, and Weibull hazard models, along with two sets of marginal effects for each, are estimated using data on condominium listings in a metropolitan area in Florida.

Using 3D Rule-Based Modeling to Interactively Visualize “Complete Streets” Design Scenarios

“Complete Streets” has successfully emerged, and is increasingly being adopted around the U.S.A., as a transportation policy and design approach that aims to support the needs of all road users. Requiring complex street design configurations, Complete Streets initiatives can benefit from the power of three-dimensional (3D) visualization to share the design vision with stakeholders and citizens. Traditional modeling techniques present some challenges to respond to such needs because of low modeling efficiency. However, 3D procedural modeling, also known as rule-based modeling, provides exciting opportunities to overcome such challenges. This study investigates 3D rule-based modeling as a scenario-oriented street design tool. It employs a case study approach that utilizes a set of rules designed for Complete Streets and applies rule-based modeling to visually compare design scenarios using a study area in Florida. Findings show that the rule-based modeling approach is proven to effectively visualize scenario-oriented street designs. Its ability to modify design parameters easily and generate scenarios rapidly, enables effective visual comparison of alternatives. Its ability to be customized and extended makes it applicable to thousands of communities around the country that are looking to implement Complete Streets designs. Finally, with the ability to support 3D web-based visualization and virtual reality, the rule-based approach can serve as an effective integrated collaboration platform. The Complete Streets rules are available and can be utilized by practitioners immediately. For researchers, the rule-based street modeling approach adds another tool in their methodological toolbox that can help bridge modeling and visualization with Complete Streets research.

Phylogenetic and phenotypic characterization of Fusarium oxysporum f. sp. niveum isolates from Florida-grown watermelon.

Fusarium wilt of watermelon (Citrullus lanatus) caused by Fusarium oxysporum f. sp. niveum (Fon), has become an increasing concern of farmers in the southeastern USA, especially in Florida. Management of this disease, most often through the use of resistant cultivars and crop rotation, requires an accurate understanding of an area’s pathogen population structure and phenotypic characteristics. This study improved the understanding of the state’s pathogen population by completing multilocus sequence analysis (MLSA) of two housekeeping genes (BT and TEF) and two loci (ITS and IGS), aggressiveness and race-determining bioassays on 72 isolates collected between 2011 and 2015 from major watermelon production areas in North, Central, and South Florida. Multilocus sequence analysis (MLSA) failed to group race 3 isolates into a single large clade; moreover, clade membership was not apparently correlated with aggressiveness (which varied both within and between clades), and only slightly with sampling location. The failure of multilocus sequence analysis using four highly conserved housekeeping genes and loci to clearly group and delineate known Fon races provides justification for future whole genome sequencing efforts whose more robust genomic comparisons will provide higher resolution of intra-species genetic distinctions. Consequently, these results suggest that identification of Fon isolates by race determination alone may fail to detect economically important phenotypic characteristics such as aggressiveness leading to inaccurate risk assessment.