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Spatial epidemiology of Tabanus (Diptera: Tabanidae) vectors of Trypanosoma

Parasites & Vectors volume 18, Article number: 128 (2025) Cite this article

Abstract

Background

Trypanosoma are protozoa parasites that infect animals and can cause economic losses in cattle production. Trypanosoma live in the blood and are transmitted by hematophagous insects, such as flies in the genus Tabanus. Using ecological niche models, we explored the current geography of six common Tabanus species in Brazil, which are considered vectors of Trypanosoma vivax and Tr. evansi in the Neotropics.

Methods

We used georeferenced data and biotic and abiotic variables integrated using a fundamental ecological niche modeling approach. Modeling results from six Tabanus species were used to identify risk areas of Trypanosoma transmission in Latin America accounting for area predicted, landscape conditions, and density of livestock. We performed Jaccard, Schoener, and Hellinger metrics to indicate the ecological niche similarities of pairs of Tabanus species to identify known and likely vectors overlapping in distribution across geographies.

Results

Our results revealed significant ecological niche similarities for two Tabanus species (T. pungens and T. sorbillans), whereas T. triangulum and T. importunus have low ecological similarity. Ecological niche models predicted risk of Trypanosoma transmission across Neotropical countries, with the highest risk in southern South America, Venezuela, and central Mexico.

Conclusions

More than 1.6 billion cattle and 38 million horses are under a threat category for infection risk. Furthermore, we identified specific areas and livestock populations at high risk of trypanosomiasis in Latin America. This study reveals the areas, landscapes, and populations at risk of Trypanosoma infections in livestock in the Americas.

Graphical Abstract

Background

Tabanidae is a family commonly known as "horse flies" and “deer flies,” of which Tabanus is the most speciose genus with a worldwide distribution, with approximately 1440 species described globally [1]. Tabanus males are phytophagous while females are typically hematophagous for oocyte maturation, and after the ovogenesis process, they change to phytophagous [2]. During the feeding process, female Tabanus flies can transmit pathogens, such as Trypanosoma evansi and Tr. vivax, to their host [3,4,5]. In the Neotropical region (tropics in the Americas), Trypanosoma parasites cause a disease termed “surra” and “trypanosomiasis” in domestic animals. Trypanosoma parasites have been found in domestic animals, including dogs [6, 7] and livestock (mainly in cattle and horses) [8], and in wildlife, such as capybaras, coatis, marsupials, rodents, bats, armadillos, deer [8, 9], and native camelids [10].

In the Neotropical region, the genus Tabanus is represented by 200 species [11], many of which are recognized as principal vectors for zoonotic pathogens [3, 12,13,14,15]. Protozoa can be transmitted mechanically by female Tabanus adapted to hematophagy in horses, cattle, and wild animals [16]. In the Neotropical region, there are about 190 species of the genus Tabanus [11], and at least five of them could be identified as mechanical vectors (pathogen transmission between host to host) of Tr. evansi and Tr. vivax, including Tabanus claripennis, Tabanus importunus, Tabanus nebulosus, Tabanus pungens, Tabanus sorbillans, and Tabanus triangulum [3, 12,13,14,15]. These Tabanus species have important characteristics that make them effective vectors of pathogens. For instance, their large oral proboscis retains significant amounts of blood, and they are persistent biters; these features facilitate the transfer of pathogens during blood feeding [11, 17]. Additionally, these Tabanus species are present in large numbers in production herds and wild animal populations, such as capybaras and coatis, which are considered reservoirs of Trypanosoma species [16,17,18]. These six species have been identified as potential mechanical vectors for Tr. vivax and Tr. evansi [16, 17, 19]. These six Tabanus species are abundant in natural areas and farmland where domestic animals and wildlife reservoirs of Trypanosoma species co-occur [18,19,20]. Environmental factors, such as climate, are known to restrict the abundance and distribution of Tabanus species [19, 21, 22].

Animal trypanosomiasis, mainly bovine trypanosomiasis caused by Trypanosoma vivax, is indeed present in the Americas, and certain areas can be considered hotspots due to the prevalence and impact of the disease [23]. Although the relationships between climate and Tabanus are well documented [11, 24], little is known about the hotspots of trypanosomiasis transmission across the Americas. Nevertheless, inferences can be made that outbreaks are closely associated with the presence and abundance of horseflies Tabanus during specific times of the year and in particular locations [25,26,27]. Ecological niche modeling has been used to assess the distributional ecology and spatial epidemiology of pathogens [28], vectors [29,30,31], and disease reservoirs [32]. The aims of this study were to (i) asses geographic and environmental ranges of six Tabanus species considered disease Trypanosoma vectors in the Neotropics, (ii) determine niche overlap among Tabanus species, and (iii) elucidate the role of grassland and livestock density on the risk of trypanosomiasis transmission to livestock in Latin America.

Methods

Selected Tabanus species

We selected Tabanus species according to literature data indicating the Tabanus potential to transmit Trypanosoma based on morphological, behavioral, and epidemiological information [3]. Tabanus importunus is a species with high vectorial potential, mentioned since the first investigations carried out by the Brazilian Dr. Adolph Lutz (1907) [33], which indicated it as a mechanical vector of Tr. evansi during a study carried out on Marajó Island in the state of Pará. Due to the population peak observed in the Brazilian Pantanal, a site with an outbreak of Tr. vivax, where this species was found to be the most abundant and therefore indicated as a protozoan vector [26, 32, 34]. Tabanus nebulosus is considered a "good vector" because it presents a time of blood feeding between 1 and 10 min, and it has been proven experimentally that between 17 and 19 individuals are enough for the transmission of Tr. vivax [12]. The number of flies of this species is not indicated as a single characteristic for the incidence of trypanosomiasis in farms [12]. In an epidemiological study with bovine herds conducted by Martins et al. [26], the most abundant species were: T. sorbillans, Tabanus palpalis, T. claripennis, and T. importunus. The authors associated the outbreak of trypanosomiasis with the horse flies’ population peak. The epidemiological studies related to protozoa Tr. vivax and Tr. evansi considered the abundance of Tabanus an important driver in the transmission of these parasites. Therefore, T. triangulum can be indicated as a possible mechanical vector of Trypanosoma in southern Brazil because it presents great abundance compared to the other Tabanus collected in this area [32, 35].

In addition to these species, epidemiological studies and Tabanidae collected in the Neotropical region found that Tabanus occidentalis was the most abundant species during collection, compared to other captured Tabanus species, suggesting that T. occidentalis may play an important role in transmission of Trypanosoma [26, 32, 34]. Nevertheless, T. occidentalis is a species that seems to have taxonomic problems [36, 37]. Tabanus occidentalis presents cryptic species and several subspecies and was removed from our study.

Occurrence data

Neotropical distributional data of vector Tabanus species (T. claripennis, T. importunus, T. nebulosus, T. pungens, T. sorbillans, and T. triangulum) were obtained manually from the Entomology Collection of the University of Tocantins, Entomology Collection of the University of Pará, and the Entomology Collection of the National Institute of Amazon Research. Data were also collected digitally from the Global Biodiversity Information Facility [38,39,40,41,42,43] and Species Link [44]. Additional records were recovered through the review of publications on the species available in Web of Science, Google Scholar, and SciELO (Additional file 1). We used all publications with the keywords: “Tabanus claripennis,” “Tabanus importunus,” “Tabanus nebulosus,” “Tabanus pungens,” “Tabanus sorbillans,” and “Tabanus triangulum” published during 1950 and 2020, retaining records with geographic coordinates. To avoid synonymy errors, species names were confirmed in the Catalogue of Neotropical Diptera, Tabanidae [11]. We used Google Earth software to determine geographical coordinates from records recovered from literature references with information of the capture location, keeping only information at the municipality or locality level, considering an uncertainty < 5 km2. We reduced bias effects (oversampled areas) and spatial correlation in occurrence data using spThin R package to filter occurrence records based on distance [45]. Distance to remove records was set according to the variable’s resolution used for model construction (~ 4.5km2), which resulted in a final occurrence dataset of each Tabanus species (Additional file 2).

Climate data

We used the 19 climatic variables data from WorldClim Global Climate Database 1.4 at 2.5 min (http://www.worldclim.org, [46]). We excluded variables 8, 9, 18, and 19, because they represent spatial artifacts [47], and instead used the remaining 15 variables to perform a principal component analysis (PCA) in NicheA software [48]. For model calibration we used the first six principal components (PC), which summarized > 99% of the variance from the original variables. We used an M hypothesis [49] to propose the likely accessible area of these species via 100-km buffers around each occurrence, which aimed to reduce the background effect on model calibration and selection or overfitting [50] (Additional file 3).

Ecological niche models

Ecological niche models were calibrated and evaluated using MaxEnt 3.4.1 [51] via kuenm R package [52] using as predictors the first six PCs and randomly 50% of occurrence data for calibration and the remaining 50% for model evaluation [53]. We explored different parameters for candidate models (linear “l,” quadratic “q,” and product “p”) with combinations of response features (l, q, lq, lp, qp, lqp) and different regularization multiplier values (0.1, 0.3, 0.5, 0.7, 1, 3, 5, 7, 10) as a means to reconstruct the species fundamental niche [54]. Final parameters were chosen from all candidate models through their significance, performance, and complexity [52]. The final models were selected based on three criteria: (i) significance indicated by partial ROC [54, 55], (ii) performance delimited for omission rate at 5%, and (iii) model complexity and good fit to the data, according to the Akaike information criterion with a correction for small samples (AICc) [56]. Final models were summarized via 10 bootstrap replicates. The best model for each species was projected to the Neotropics. To identify extrapolative areas, we compare calibration areas and projection areas using MOP analysis, which indicates regions with extrapolative risk [57].

Niche ellipsoids and overlap

We used NicheA software [48] to generate niche ellipsoid models from the occurrence data of each Tabanus species as a proxy of fundamental ecological niches. We explored species distributions in environmental space linked to the geographic distribution as a proxy of the Hutchinson’s duality concept of the relationship between environmental and geographic space [48]. We built the environmental space in NicheA using the first three PCs and filtered occurrence data. We estimated the ellipsoid volume for each species, a measure of ecological generalist (broad niche or large volume) vs. specialist (narrow niche or low volume) species, and calculated the niche overlap for pairs of species.

Niche similarities

We quantified niche similarity on pairs of species using Schoener’s D and Hellinger’s I statistics, where values of 0 denoted niche models having no overlap and 1 denoting complete niche overlap [56]. Niche similarity measurements were done using ENM Tools v.1.3 [56], which analyzes niche similarity in geographic space by comparing one species to another regarding the amount and distribution of suitable pixels. Complementarily, we measured niche similarity in environmental space using the Jaccard index [58], estimated with of volume, and ellipsoid overlap, estimated in NicheA, where values of 0 denoted niche models having no overlap and 1 denoting complete niche overlap.

Risk mapping

Final Maxent models were binarized by threshold values equivalent to an omission error of E = 0.05. Subsequently, binary results were stacked for the six Tabanus species to indicate an ensemble model of areas of potential species distribution. Publicly available Neotropical grassland area data [59] were used to match regions climatically suitable to Tabanus species and with grass available for livestock. The resulting map was a proxy of areas of vector-borne disease risk for livestock.

The risk map denoted areas suitable to Tabanus species based on landscape (i.e. grassland) and abiotic conditions (i.e. climatic). To determine the capacities of our Tabanus risk map to inform disease transmission risk to cattle and horses, we fitted a linear model (estimated using OLS) to assess the association between the livestock density and Tabanus risk map. Because no a priori information was available, we assumed that patterns of association should be able to be captured under a linear relationship. Data of livestock density were obtained from Harvard Dataverse at 5 min resolution, including densities of cattle [60] and horses [61]. Standardized parameters of the linear model were obtained by fitting the model on a standardized version of the dataset. The 95% confidence intervals and p-values were computed using a Wald t-distribution approximation.

Results

The six Tabanus species studied were reported in the whole Neotropical region, together covering most Latin American countries (Additional file 3a and 3b). We recovered 622 filtered occurrence records for the six Tabanus species' ecological niche models (Additional file 2). Tabanus importunus presented the highest number of occurrences (n = 149), and the smallest amount was recorded for T. nebulosus (n = 60). We found that the six Tabanus species had broad distributions along Latin American countries in the Neotropics, including Brazil, Argentina, Paraguay, and Bolivia, while Tabanus triangulum was the species most geographically restricted, occurring only in Brazil, Bolivia, Argentina, Paraguay, and Uruguay.

We calibrated and evaluated 54 candidate models for each Tabanus species for a total of 324 ecological niche models covering diverse parameter and predictor combinations (Additional file 4). Model calibration experiments for all Tabanus species retrieved one final best model according to the predictive performance and fit metrics, except for T. nebulosus, for which three best models were identified (Additional file 4 and 5). The best models representing species' fundamental ecological niches and the average ensemble model for T. nebulosus were projected to the Neotropical region to identify areas potentially suitable for the species across the continent (Fig. 1A).

Fig. 1
figure 1

Risk maps of Tabanus-borne trypanosomiasis in the Neotropics. A Potential risk areas for distribution of Tabanus species from climate-based ecological niche models. Colors show the high (dark brown) and low (yellow) areas potentially suitable to richness of six Tabanus species. B Grassland natural areas [59] and cattle and horse areas [60, 61] in the Neotropical region. C Estimated distribution of Tabanus species in natural grassland areas. D Risk map showing the correlation between Tabanus species richness and livestock density denoting areas of high (dark brown) and low (yellow) disease transmission risk

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Our results showed species occupying broad environmental conditions as measured by the environmental volume occupied by the occurrences. Species of large geographic distribution were ecological generalists occupying large environmental volume (i.e. T. sorbillans volume = 212.93, T. nebulosus volume = 219.90, T. claripennis volume = 260.81). Other species had narrow niches and restricted geographic ranges and were considered specialist species (i.e. T. importunus volume = 59.89, T. triangulum volume = 85.08, T. pungens volume = 103.24). In general, different Tabanus species occurred in disparate environmental conditions and geographies (Fig. 2).

Fig. 2
figure 2

Hutchinson duality of six Tabanus species in the Netropical region. Potential distribution and niche overlap of six Tabanus species (dark blue: T. claripennis, green: T. importunus, pink: T. nebulosus, light pink: T. pungens, light blue: T. sorbillans, yellow: T. Triangulum, and red: niches overlap) in the environmental space available in the Neotropical region. The ellipsoids were constructed three dimensionally from the axes showing the conditions of principal component 1 (PC1: in X), principal component 2 (PC2: in Y), and principal component 3 (PC3: in Z). Maps showing the potential distribution between pairs of species and indicating the overlap between two of them (in red), according to each row and column of the matrix

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Our results indicated an asymmetrical distribution of Tabanus species in relation to their available environment (Fig. 3). Tabanus claripennis had the broadest geographic and environmental distribution, occurring between latitudes 22.40°N and 45.51°S. Based on species occurrence reports, the broadest temperature tolerance was found for T. triangulum with temperatures ranging from –6 to 40.9 °C. The species with the narrowest temperature tolerance was T. importunus with temperatures ranging from 9.1 to 35.7 °C, which was also the species tolerating the warmest temperatures. Regarding humidity, T. pungens was the species tolerating the broadest range of annual precipitation, from 12 to 4985 mm. Tabanus triangulum was the species showing the narrowest range of precipitation and strong tolerance to dry conditions (75–2219 mm).

Fig. 3
figure 3

Environmental distribution of six Tabanus species in the Neotropical region. Density plots of environmental preferences of Tabanus species. Frequency of records of six Tabanus species along latitude (A), longitude (B), annual mean temperature (values: T OC × 10) (C), maximum temperature of warmest month (values: T OC × 10) (D), minimum temperature of coldest month (values: T OC × 10) (E), and annual precipitation (values: mm3) (F)

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Niche overlap metrics revealed ecological similarity between a series of species pairs (Fig. 4). The highest niche similarity among all metrics (I, D, Jaccard indexes) was observed between T. sorbillans and T. pungens (Jaccard = 0.68, D = 0.91, and I = 0.99; Fig. 4). The lowest ecological similarity was detected in T. triangulum, with T. triangulum and T. importunus presenting the lowest niche similarity (Jaccard = 0.11, D = 0.08, and I = 0.14).

Fig. 4
figure 4

Similarity of ecological niches between pairs of Tabanus species. A Jaccard indexes. B Schoener’s (D, top of diagonal) and Hellinger’s (I, bottom of diagonal) statistics. Yellow = the greatest similarities between pairs of species; dark blues = the smallest

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Our vector-borne disease risk mapping combining ecological niche models and grasslands along the whole Neotropics estimated 1.35 M km2 at risk of Tabanus-borne diseases. The total number of livestock at risk for Tabanus-borne parasites was 1,638,506,972 cattle and 38,861,217 horses. The regions with the highest cattle and horse densities living in hotspots of risk included eastern Argentina, Uruguay, eastern Paraguay, and central, southern, and eastern Brazil, northern Colombia, western Venezuela, and central and southern Mexico (Fig. 1B). In contrast, potential Tabanus distribution was not predicted along the grassland in high altitudinal regions (e.g. Andes Mountains), cold regions (Patagonia), and dry areas in the Neotropics (e.g. northern Brazil and Mexico) (Fig. 1C, D). According to our MOP analysis, MaxEnt model extrapolation is represented along different areas in the Neotropics (according with the species, Additional file 6); however, our models include low suitability in these areas, mitigated by reducing model projection in MOP-detected areas.

The regression model between livestock density and richness of Tabanus species (Fig. 1D) explained a statistically significant but weak proportion of variance (F(1, 1,010,059) = 65,412.40, p < 0.001, adj. R2 = 0.06). The model’s intercept, corresponding to livestock density = 0, was at 4.36 (95% CI [4.36, 4.36], t(1,010,059) = 2735.91, p < 0.001). Within this model the effect of livestock density on Tabanus occurrence was statistically significant and positive (beta = 0.0001, 95% CI [0.0001, 0.00012], t(1,010,059) = 255.76, p < 0.001; Std. beta = 0.000128, 95% CI [0.0001, 0.00012]).

Discussion

This study estimated fundamental ecological niches, niche similarities, and geographic ranges for six Tabanus species implicated in pathogens transmission to cattle and horses in the Neotropics. We found that five ecological-generalist Tabanus species presented potential geographic distribution in areas with the highest cattle and horse production in the region. Our results generated epidemiological and ecological information about Tabanus in the Americas to explain likely vector-borne transmission risk of protozoan diseases, such as trypanosomiasis and anaplasmosis, and other diseases caused by virus and bacteria [3]. Results can be used to identify geographic hotspots where cattle and horses have a major risk of Tabanus-borne livestock diseases [62, 63]. To the best of our knowledge, this is the first study on the potential geographic distribution, environmental occupancy (mainly in highly diverse ecosystems such as Dry Chaco, Pantanal, Atlantic Forest, Humid Pampas, and Cerrado in South America; also, in the Yucatan Peninsula in Mexico), and niche similarity of Tabanus in the Neotropics.

Niche breadth

Differences between the distributions of Neotropical Tabanus species were related to environmental heterogeneity and biological factors. That is, although Tabanus species occurred along diverse environmental gradients, most reports occurred under similar and consistent environmental and geographic ranges (Figs. 2 and 3). Previous research revealed linkages between environmental conditions and biological aspects of Tabanus related to physiology and oogenesis, especially regarding variation in temperature, humidity, and rainfall [64, 65]. Environmental variation across the study region influenced the latitudinal gradients occupied by the different species (Figs. 1A, 3, and S3). Distributional bounds of Tabanus are constrained by physiological tolerances, related to acclimation capacity to survive and reproduce, which in turn affect population establishment and population size [66, 67]. Also, climate change can be an important drive for these physiological changes in populations dynamics on fine [68] and regional scales[69].

Environmental distribution

Our analyses differentiating species ecological generalists (e.g. T. claripennis) vs. specialists (e.g. T. triangulum) (Figs. 2 and 4) have direct implications for the epidemiological relevance of each species. For example, T. importunus was restricted to tropical regions with high temperatures such as those reported in Central America (e.g. Costa Rica and Panama) and some countries in South America (e.g. Colombia, Venezuela, Peru, Bolivia, Brazil, Paraguay, northern Argentina, French Guiana, and Guiana; Figs. 1A and 3). These findings are aligned with previous studies of Tabanus that found environmental constraints because of the high temperatures in dry areas of South America (e.g. Sertão Region in Brazil and dry regions in Chile; [19]).

Seasonality

Our model ensemble denoting Tabanus richness restricted by grassland landscapes (Fig. 1C, D) revealed likely hotspots of disease transmission risk. Our risk model is, however, temporally static. Temporal variation in temperature and precipitation is expected to influence Tabanus abundance and, in turn, transmission risk. For example, in French Guiana, on the border with Brazil, T. importunus population peaks last between 2 and 3 months and are regulated by seasonality [70]. Similarly, a study carried out in southern Brazil indicated a strong influence of temperature and relative humidity on seasonal variation in the occurrence and abundance of T. triangulum [21]. During the rainy season, T. importunus larval stage is maintained, reaching the adult stage with the onset of the dry season [71]. In some regions of Latin America, such as Midwest Brazil, with a warm and humid climate, environmental conditions allow large populations of T. importunus across the year, representing up to 45% of the local Tabanus richness [19].

Risk map

Our risk map combined information on Tabanus richness, grassland availability, and cattle and horses to identify fine-resolution transmission risk hotspots (Fig. 1B, D). A series of Tabanus species, including T. importunus, are commonly found in open landscapes dominated by pasture for cattle and horses [16, 17]. In contrast, T. claripennis and T. sorbillans prefer forested areas but can also occur in grassland [18]. The proximity between forested areas and pastures provides Tabanus with different food resources for adults. Male Tabanus feed on vegetable sap and flower nectar and pollen [72], while females also need animal blood, which may be available in wildlife and on livestock farms [3].

Cattle density

Our ecological niche models indicated that the six Tabanus species studied could co-occur in the same geographic areas (Fig. 1A). This prediction is supported by previous reports in Midwest Brazil (i.e. Mato Grosso do Sul), where T. claripennis, T. importunus, T. nebulosus, T. pungens, and T. sorbillans coexisted in the same areas and environments [18]. Co-occurrences of Tabanus species have been found to be a key factor positively influencing trypanosomiasis cases [4, 5, 73,74,75]; almost US $5 billion in losses because of trypanosomiasis were reported in Africa [76]. This infectious disease is related to different production processes: milk production (reduction until 25% in Brazil) [77], mortality loss (almost 15% of different livestock species in India) [78], and weight loss in cattle (almost 390 g per day in Colombia) [12]. Potential distribution of Tabanus species is linked to the presence of the pathogens Tr. vivax and Tr. evansi in livestock [13, 18, 79]. For example, Tabanus presence is an important factor regarding the presence Trypanosoma parasites across Brazil [8, 18, 75, 79,80,81,82,83,84]. In addition, Bolivia, Colombia, Peru, and Venezuela have records of trypanosomiasis outbreaks affecting livestock, causing economic losses to farmers [12, 85,86,87]. In affected areas, the presence of Tabanus correlates with the presence of livestock and wildlife infected with Tr. vivax and Tr. evansi [20]. Almost 234,000 livestock herds are at risk in northern Brazil [88] according to the suitability of Tabanus species and the risk map. Wildlife has been found to represent from 25 to 45% of naturally infected Trypanosoma cases [13, 81]. Our results indicate that the relationship between the density of production animals and the presence of Tabanus species is weak and that many other factors that were not considered in the model can influence the distribution of these horseflies [18, 70]. Future research should explore other alternative landscape variables [89] with the potential to play a role in the likelihood of transmission risk (e.g. distance to rivers, socio-economic conditions, age of the landscape conversion, wildlife diversity).

Implications

Trypanosomiasis has important implications for animal health in the Neotropical region where large outbreaks can generate devastating economic losses. For example, in the state of Espírito Santo, Brazil, a trypanosomiasis outbreak caused the death of livestock with an estimated economic loss of U$100,000 in just 1 month [90]. Incidence, distribution, and costs of trypanosomiasis in livestock could be underestimated, though. Our Tabanus risk maps will help address the underestimation of the burden of Tabanus-borne infectious diseases and can help direct vector control in localities defined as risk hotspots.

Conclusions

Potential distribution of the six Tabanus species is proposed as the basis to understand how variations in abiotic (e.g. temperature, precipitation) and biotic (e.g. grassland, livestock density) factors influence the spatial epidemiology of Tr. vivax and Tr. evansi. Beyond potential distribution of Tabanus, their abundance could be an important variable to explain transmission risk. Further studies could combine abundance data with ecological niche models for a more accurate reconstruction of the ecology and epidemiology of trypanosomiasis. This study reconstructed the ecological niche of six Tabanus species to better understand their distributional ecology and to identify hotpots of trypanosomiasis transmission risk in the Neotropics, a disease of humans and animals. Here, we give some critical considerations for the epidemiology of cattle and wildlife trypanosomiasis. Climate change, physiology, and biological interactions will be the focus of the next research on Tabanus for the needed One Health approach.

Availability of data and materials

No datasets were generated or analysed during the current study.

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Acknowledgements

We thank Inocêncio de Souza Gorayeb and Augusto Loureiro Henriques for Tabanus data. We thank Davi Mello Cunha Crescente Alves and Nine Paanwaris for their support in data analysis. We thank Alice Silveira da Silveira and Natália Vicenzi for their support in searching for species occurrence data. We thank A. Townsend Peterson and Reilly Brennan for comments and suggestions.

Funding

RM was supported by FAPERGS MSc scholarship and CAPES PhD scholarship. Research reported in this publication was supported by CONAHCYT Investigadoras e Inestigadores por México 2022(2) and by CONAHCYT Ciencia Basica y de Frontera grant CBF 2023–2024 2899. DJG was supported by Fulbright Visiting Scholar Program (Senior Scholar). Proyectos VIEP-2024. RFK was supported by CNPq grant 308908/2016-3. TKK received a research grant from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq-310214/2021–1). LEE was supported by the National Science Foundation CAREER (2235295) and HEGS (2116748) awards. Research reported in this publication was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K01AI168452. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Authors and Affiliations

  1. Programa de Pós-Graduação em Parasitologia, Departamento de Microbiologia e Parasitologia, Instituto de Biologia, Universidade Federal de Pelotas, Campus Universitário, s/n, Capão do Leão, Rio Grande do Sul, CEP: 96010-900, Brazil

    Roberta Marques & Rodrigo Ferreira Krüger

  2. Laboratorio de Biodiversidad, Centro de Agroecología y Ambiente, Instituto de Ciencias de la Benemérita Universidad Autónoma de Puebla, Puebla, México

    Roberta Marques & Daniel Jiménez-García

  3. Laboratorio Nacional CONAHCYT de Biología del Cambio Climático, Veracruz, México

    Daniel Jiménez-García

  4. Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, USA

    Luis E. Escobar

  5. Laboratório de Entomologia, Coordenação de Ciências Biológicas, Universidade Federal do Tocantins, Caixa Postal: 136, Rua 03, Qd 17 s/n, Jardim dos Ipês, Porto Nacional, Tocantins, CEP 77500-000, Brazil

    Roberta Marques & Tiago Kütter Krolow

  6. Laboratório de Ecologia de Parasitos e Vetores, Departamento de Microbiologia e Parasitologia, Instituto de Biologia, Universidade Federal de Pelotas, Campus Universitário, s/n, Capão do Leão, Rio Grande do Sul, CEP: 96010-900, Brazil

    Rodrigo Ferreira Krüger

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  1. Roberta Marques
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  2. Daniel Jiménez-García
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  3. Luis E. Escobar
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  4. Tiago Kütter Krolow
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  5. Rodrigo Ferreira Krüger
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Contributions

Conceptualization: RM, RFK. Data Curation: RM, TKK. Analysis: RM, DJG. Investigation: RM, RFK, DJG. Methodology: RM, DJG, LEE. Project Administration: RM. Supervision: RM, RFK. Writing – Original Draft: RM. Writing – Review and Editing: RM, RFK, DJG, TKK, LEE. All authors read and approved the final manuscript.

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Correspondence to Roberta Marques or Daniel Jiménez-García.

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Supplementary Information

13071_2025_6708_MOESM1_ESM.doc

Supplementary Material 1. List of the references used to collect occurrence data of the six Tabanus species in the Neotropical region.

13071_2025_6708_MOESM2_ESM.doc

Supplementary Material 2. List of the occurrence records georeferenced in the Neotropical region of the six Tabanus species used in ecological niche modeling. These occurrences are results after the filter of the 5-km area. The coordinates are represented in decimal degrees.

13071_2025_6708_MOESM3_ESM.doc

Supplementary Material 3. Tabanus species occurrences (black points) in the Neotropical region and the 100-km buffer (M = pink circles) used in the calibration models.

13071_2025_6708_MOESM4_ESM.doc

Supplementary Material 4. Models calibrated and evaluated for each Tabanus species, according to significance, performance, and low complexity. Final models selected according to these criteria are shown in the last column.

13071_2025_6708_MOESM5_ESM.doc

Supplementary Material 5. Best models selected by evaluation based on pROC (statistical significance), omission rate OR (performance), and AICc (complexity). All models were calibrated and projected using principal components from 15 climatic variables from the WorldClim Global Climate Database 1.4.

13071_2025_6708_MOESM6_ESM.doc

Supplementary Material 6. MOP analysis of extrapolation risk from the calibration area under the Neotropical region projection. Blue areas represent levels of similarity between calibration areas and the projection areas. Red values represent strict extrapolative areas.

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Marques, R., Jiménez-García, D., Escobar, L.E. et al. Spatial epidemiology of Tabanus (Diptera: Tabanidae) vectors of Trypanosoma. Parasites Vectors 18, 128 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13071-025-06708-z

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Keywords

Parasites & Vectors

ISSN: 1756-3305

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