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Macroecological approaches can provide valuable insight into the epidemiology of globally distributed, multi-host pathogens. Toxoplasma gondii is a protozoan that infects any warm-blooded animal, including humans, in almost every habitat worldwide. Toxoplasma gondii infects its hosts through oocysts in the environment, carnivory of tissue cysts within intermediate host prey and vertical transmission. These routes of infection enable specific predictions regarding the ecological and life history traits that should predispose specific taxa to higher exposure and, thus infection rates of T . gondii . Using T . gondii prevalence data compiled from 485 studies representing 533 free-ranging wild mammalian species, we examined how ecological (habitat type, trophic level) and life history (longevity, vagility, gestation duration and torpor) traits influence T . gondii infection globally. We also compared T . gondii prevalence between wild and domesticated species from the same taxonomic families using data compiled from 540 studies of domestic cattle, sheep, and pigs. Across free-ranging wildlife, we found the average T . gondii prevalence was 22%, which is comparable to the global human estimate. Among ecological guilds, terrestrial species had lower T . gondii prevalence than aquatic species, with freshwater aquatic taxa having an increased prevalence compared to marine aquatic species. Dietary niches were also influential, with carnivores having an increased risk compared to other trophic feeding groups that have reduced tissue cyst exposure in their diet. With respect to influential life history traits, we found that more vagile wildlife species had higher T . gondii infection rates, perhaps because of the higher cumulative risk of infection during movement through areas with varying T . gondii environmental loads. Domestic farmed species had a higher T . gondii prevalence compared to free-ranging confamilial wildlife species. Through a macroecological approach, we determined the relative significance of transmission routes of a generalist pathogen, demonstrating an increased infection risk for aquatic and carnivorous species and highlighting the importance of preventing pathogen pollution into aquatic environments. Toxoplasma gondii is increasingly understood to be primarily an anthropogenically-associated pathogen whose dissemination is enhanced by ecosystem degradation and human subsidisation of free-roaming domestic cats. Adopting an ecosystem restoration approach to reduce one of the world’s most common parasites would synergistically contribute to other initiatives in conservation, feline and wildlife welfare, climate change, food security and public health.

Weather and land use can significantly impact mosquito abundance and presence, and by consequence, mosquito-borne disease (MBD) dynamics. Knowledge of vector ecology and mosquito species response to these drivers will help us better predict risk from MBD. In this study, we evaluated and compared the independent and combined effects of weather and land use on mosquito species occurrence and abundance in Eastern Ontario, Canada. Data on occurrence and abundance (245,591 individuals) of 30 mosquito species were obtained from mosquito capture at 85 field sites in 2017 and 2018. Environmental variables were extracted from weather and land use datasets in a 1-km buffer around trapping sites. The relative importance of weather and land use on mosquito abundance (for common species) or occurrence (for all species) was evaluated using multivariate hierarchical statistical models. Models incorporating both weather and land use performed better than models that include weather only for approximately half of species (59% for occurrence model and 50% for abundance model). Mosquito occurrence was mainly associated with temperature whereas abundance was associated with precipitation and temperature combined. Land use was more often associated with abundance than occurrence. For most species, occurrence and abundance were positively associated with forest cover but for some there was a negative association. Occurrence and abundance of some species (47% for occurrence model and 88% for abundance model) were positively associated with wetlands, but negatively associated with urban ( Culiseta melanura and Anopheles walkeri ) and agriculture ( An . quadrimaculatus , Cs . minnesotae and An . walkeri ) environments. This study provides predictive relationships between weather, land use and mosquito occurrence and abundance for a wide range of species including those that are currently uncommon, yet known as arboviruses vectors. Elucidation of these relationships has the potential to contribute to better prediction of MBD risk, and thus more efficiently targeted prevention and control measures.

Macroecological approaches can provide valuable insight into the epidemiology of globally distributed, multi-host pathogens. Toxoplasma gondii is a zoonotic protozoan that infects any warm-blooded animal, including humans, in almost every ecosystem worldwide. There is substantial geographical variation in T. gondii prevalence in wildlife populations and the mechanisms driving this variation are poorly understood. We implemented Bayesian phylogenetic mixed models to determine the association between species’ ecology, phylogeny and climatic and anthropogenic factors on T. gondii prevalence. Toxoplasma gondii prevalence data were compiled for free-ranging wild mammal species from 202 published studies, encompassing 45 079 individuals from 54 taxonomic families and 238 species. We found that T. gondii prevalence was positively associated with human population density and warmer temperatures at the sampling location. Terrestrial species had a lower overall prevalence, but there were no consistent patterns between trophic level and prevalence. The relationship between human density and T. gondii prevalence is probably mediated by higher domestic cat abundance and landscape degradation leading to increased environmental oocyst contamination. Landscape restoration and limiting free-roaming in domestic cats could synergistically increase the resiliency of wildlife populations and reduce wildlife and human infection risks from one of the world’s most common parasitic infections.

Crop yield prediction prior to harvest is important for crop income and insurance projections, and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and predictor variables, especially at the field scale. In this study, an artificial neural network (ANN) method was used: (1) to evaluate the relative importance of predictor variables for the prediction of within-field corn and soybean end-of-season yield and (2) to evaluate the performance of the ANN models with a minimal optimized variable dataset for their capacity to predict corn and soybean yield over multiple years at the within-field level. Several satellite derived vegetation indices (normalized difference vegetation index—NDVI, red edge NDVI and simple ratio—SR) and elevation derived variables (slope, flow accumulation, aspect) were used as crop yield predictor variables, hypothesizing that the different variables reflect different crop and site conditions. The study identified the SR index and the slope as the most important predictor variables for both crop types during two training and testing years (2011, 2012). The dates of the most important SR images, however, were different for the two crop types and corresponded to their critical crop developmental stages (phenology). The relative mean absolute errors were overall smaller for corn compared to soybean: all of the 2011 corn study fields had errors below 10%; 75% of the fields had errors below 10% in 2012. The errors were more variable for soybean. In 2011, 37% of the fields had errors below 10%, while in 2012, 100% of the fields had errors below 20%. The results are promising and can provide yield estimates at the farm level, which could be useful in refining broader scale (e.g., county, region) yield projections.

Mosquito-borne diseases pose ongoing global health concerns, demanding more cost-efficient methods to detect pathogens to support enhanced surveillance efforts. This study introduces an adapted TRIzol-based high-throughput RNA extraction protocol, tailored for the detection of California serogroup viruses in pooled mosquito samples in a rapid and cost-effective manner. This approach provided consistent RNA yields and sensitive viral detection relative to two commercial extraction kits (QIAGEN RNeasy Mini Kit and MACHEREY–NAGEL NucleoSpin RNA Plus Kit). The incorporation of a user-friendly and non-spiking-based RT-qPCR internal control designed for the 18S rRNA gene in mosquitoes minimizes potential false positives/negatives, improving the fidelity of viral detection outcomes. Effective RNA yields, purity, and successful target amplification across 25 mosquito species and varied pool sizes (1–50 mosquitoes per tube) affirm the reliability of our approach. The extraction method is cost-effective, with an incurred cost of $0.58 CAD per sample, in contrast to the $5.25 CAD cost per sample of the two kits, rendering it promising for mosquito-borne disease surveillance initiatives.

Mosquito-borne diseases (MBDs) are emerging in response to climate and land use changes. As mosquito (Diptera: Culicidae) habitat selection is often contingent on water availability for egg and larval development, studies have recognized water quality also influences larval habitats. However, underlying species-, genera-, and mosquito level preferences for water quality conditions are varied. This systematic review and meta-analysis aimed to identify, characterize, appraise, and synthesize available global data on the relationships between water quality and mosquito presence and abundance (MPA); with the goal to further our understanding of the geographic expansion of MBD risks. A systematic review was conducted to identify studies investigating the relationships between water quality properties and MPA. Where appropriate, random-effects meta-analyses were conducted to provide pooled estimates for the association between the most reported water quality properties and MPA. The most reported water quality parameters were pH (87%), nitrogen concentrations (56%), turbidity (56%), electrical conductivity (54%), dissolved oxygen (43%), phosphorus concentrations (30%), and alkalinity (10%). Overall, pH (P = 0.05), turbidity (P < 0.0001), electrical conductivity (P = 0.005), dissolved oxygen (P < 0.0001), nitrogen (P < 0.0001), and phosphorus (P < 0.0001) showed significantly positive pooled correlations with MPA, while alkalinity showed a nonsignificant null pooled correlation (P = 0.85). We observed high heterogeneity in most meta-analyses, and climate zonation was shown to influence the pooled estimates. Linkages between MPA and water quality properties will enhance our capacity to predict MBD risks under changing environmental and land use changes. Graphical Abstract

Globally, mosquito‐borne diseases (MBD) cause the highest morbidity and mortality in humans and animals. Currently, in Canada, endemic MBDs that are significant public health problems are all zoonoses and are caused primarily by West Nile virus, Eastern equine encephalitis virus, and Californian serogroup viruses, including the Jamestown Canyon and the Snowshoe hare viruses. The transmission cycles of these viruses are changing, linked to global population movements (including vectors) and climate and land use changes. Here, we present the state of knowledge, related to MBDs in Canada, as well as salient surveillance approaches carried out to monitor them and their infection rates. We propose a few theoretical and operational research avenues in order to improve our understanding of transmission cycle changes, as well as the potential of new surveillance tools such as citizen science, metagenomics, artificial intelligence, and remote sensing to help reduce disease burdens on Canadians. This will support public and animal health responses to these zoonoses and help proactively manage such diseases under changing environmental conditions.

Background The freshwater microbiome regulates aquatic ecological functionality, nutrient cycling, pathogenicity, and has the capacity to dissipate and regulate pollutants. Agricultural drainage ditches are ubiquitous in regions where field drainage is necessary for crop productivity, and as such, are first-line receptors of agricultural drainage and runoff. How bacterial communities in these systems respond to environmental and anthropogenic stressors are not well understood. In this study, we carried out a three year study in an agriculturally dominated river basin in eastern Ontario, Canada to explore the spatial and temporal dynamics of the core and conditionally rare taxa (CRT) of the instream bacterial communities using a 16S rRNA gene amplicon sequencing approach. Water samples were collected from nine stream and drainage ditch sites that represented the influence of a range of upstream land uses. Results The cross-site core and CRT accounted for 5.6% of the total number of amplicon sequence variants (ASVs), yet represented, on average, over 60% of the heterogeneity of the overall bacterial community; hence, well reflected the spatial and temporal microbial dynamics in the water courses. The contribution of core microbiome to the overall community heterogeneity represented the community stability across all sampling sites. CRT was primarily composed of functional taxa involved in nitrogen (N) cycling and was linked to nutrient loading, water levels, and flow, particularly in the smaller agricultural drainage ditches. Both the core and the CRT were sensitive responders to changes in hydrological conditions. Conclusions We demonstrate that core and CRT can be considered as holistic tools to explore the temporal and spatial variations of the aquatic microbial community and can be used as sensitive indicators of the health and function of agriculturally dominated water courses. This approach also reduces computational complexity in relation to analyzing the entire microbial community for such purposes.

Background Water is considered a source for the transmission of Arcobacter species to both humans and animals. This study was conducted to assess the prevalence, distribution, and pathogenicity of A. butzleri strains, which can potentially pose health risks to humans and animals. Cultures were isolated from surface waters of a mixed-use but predominately agricultural watershed in eastern Ontario, Canada. The detection of antimicrobial resistance (AMR) and virulence-associated genes (VAGs), as well as enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) assays were performed on 913 A. butzleri strains isolated from 11 agricultural sampling sites. Results All strains were resistant to one or more antimicrobial agents, with a high rate of resistance to clindamycin (99%) and chloramphenicol (77%), followed by azithromycin (48%) and nalidixic acid (49%). However, isolates showed a significantly ( p  < 0.05) high rate of susceptibility to tetracycline (1%), gentamycin (2%), ciprofloxacin (4%), and erythromycin (5%). Of the eight VAGs tested, cia B, mvi N, tly A, and pld A were detected at high frequency (> 85%) compared to irg A (25%), hec B (19%), hec A (15%), and cj 1349 (12%) genes. Co-occurrence analysis showed A. butzleri strains resistant to clindamycin, chloramphenicol, nalidixic acid, and azithromycin were positive for cia B, tly A, mvi N and pld A VAGs. ERIC-PCR fingerprint analysis revealed high genetic similarity among strains isolated from three sites, and the genotypes were significantly associated with AMR and VAGs results, which highlight their potential environmental ubiquity and potential as pathogenic. Conclusions The study results show that agricultural activities likely contribute to the contamination of A. butzleri in surface water. The findings underscore the importance of farm management practices in controlling the potential spread of A. butzleri and its associated health risks to humans and animals through contaminated water. Highlights 1. Arcobacter butzleri was highly prevalent in agricultural surface water. 2. Strains were highly resistant to antimicrobial agents. 3. Virulence genes were detected at a high frequency. 4. High genetic similarity and association among strains from various sites.