The Florida Keys, a delicate archipelago of sub-tropical islands extending from the south-eastern tip of Florida, host the vast majority of the only coral barrier reef in the continental United States. Abiotic as well as microbial components of the surrounding waters are pivotal for the health of reef habitats, and thus could play an important role in understanding the development and transmission of coral diseases in Florida. In this study, we analyzed microbial community structure and abiotic factors in waters around the Florida Reef Tract. Both, bacterial and eukaryotic community structure were significantly linked with variations in temperature, dissolved oxygen and total organic carbon values. High abundances of copiotrophic bacteria as well as several potentially harmful microbes, including coral pathogens, fish parasites and taxa that have been previously associated with Red Tide and shellfish poisoning were present in our datasets and may have a pivotal impact on reef health in this ecosystem.

Florida geologic units and soils contain a wide range in concentrations of naturally-occurring arsenic. The average range of bulk rock concentrations is 1 to 13.1 mg/kg with concentrations in accessary minerals being over 1,000 mg/kg. Soils contain natural arsenic concentrations of between 0.18 and 2.06 mg/kg with organic-rich soils having the highest concentrations. Anthropogenic sources of arsenic have added about 610,000 metric tons of arsenic into the Florida environment since 1970, thereby increasing background concentrations in soils. The anthropogenic sources of arsenic in soils include: pesticides (used in Florida beginning in the 1890’s), fertilizers, chromated copper arsenate (CCA)-treated wood, soil amendments, cattle-dipping vats, chicken litter, sludges from water treatment plants, and others. The default Soil Cleanup Target Level (SCTL) in Florida for arsenic in residential soils is 2.1 mg/kg which is below some naturally-occurring background concentrations in soils and anthropogenic concentrations in agricultural soils. A review of risk considerations shows that adverse health impacts associated with exposure to arsenic is dependent on many factors and that the Florida cleanup levels are very conservative. Exposure to arsenic in soils at concentrations that exceed the Florida residential cleanup level in residential environments does not necessarily pose a meaningful public health risk.

The production and quality of Phaseolus vulgaris (snap bean) have been negatively impacted by leaf crumple disease caused by two whitefly-transmitted begomoviruses; cucurbit leaf crumple virus (CuLCrV) and sida golden mosaic Florida virus (SiGMFV), which often appear as a mixed infection in Georgia. Host resistance is the most economical management strategy against whitefly-transmitted viruses. Currently, information is not available with respect to resistance to these two viruses in commercial cultivars. In two field seasons (2018 and 2019), we screened Phaseolus sp. genotypes (n = 84 in 2018; n = 80 in 2019; most of the genotypes were common in both years with a few exceptions) for resistance against CuLCrV and/or SiGMFV. Twenty genotypes with high- to moderate-levels of resistance (disease severity ranging from 5-50%) to CuLCrV and/or SiGMFV were identified. Twenty-one genotypes were found to be highly susceptible with a disease severity of ≥66%. Adult whitefly counts differed significantly among snap bean genotypes for both years. The whole genome of these Phaseolus sp. (n=82) genotypes was sequenced and genetic variability among them was identified. Over 900 giga-base (Gb) of filtered data were generated and >88% of the resulting data were mapped to the reference genome, and SNP and Indel variants in Phaseolus genotypes were obtained. A total of 645,729 SNPs and 68,713 Indels including 30,169 insertions and 38,543 deletions were identified, which were distributed in 11 chromosomes with chromosome 02 harboring the maximum number of variants. These phenotypic and genotypic information will be helpful in genome-wide association studies that will aid in identifying genetic basis of resistance to these begomoviruses in Phaseolus sp.

Ensembles of Species Distribution Models (SDMs) represent the geographic ranges of pathogen vectors by combining alternative analytical approaches and merging information on vector occurrences with more extensive environmental data. Biased collection data impact SDMs, regardless of the target species but no studies have compared the differences in the distributions predicted by the ensemble models when different sampling frameworks are used for the same species. We compared Ensemble SDMs for two important Ixodid tick vectors, Amblyomma americanum and Ixodes scapularis in mainland Florida, USA, when inputs were either convenience samples of ticks, or collections obtained using the standard protocols promulgated by the U.S. Centers for Disease Control and Prevention. The Ensemble SDMs for the convenience samples and standard surveys showed only a slight agreement (Kappa = 0.060, A. americanum; 0.053, I. scapularis). Convenience sample SDMs indicated A. americanum and I. scapularis should be absent from 34.5% and 30.9% of the state where standard surveys predicted the highest likelihood of occurrence of the respective vectors. Ensemble models from standard surveys predicted 81.4% and 72.5% (A. americanum and I. scapularis) of convenience sample sites. Omission errors by standard survey SDMs, of the convenience collections, frequently were associated with adjacency to at least one SDM or errors in geocoding algorithms that failed to correctly locate convenience samples. These geocoding errors emphasize commonly overlooked needs to explicitly evaluate and improve data quality for vector survey data used in spatial models.