Sérgio Gomes da Silva,Francimeire Fernandes Ferreira,Gabriela Hrycyna,Alan Eriksson,Gustavo Graciolli,Gustavo Rodrigues Canale
Determinants of the composition of ectoparasitic flies of bats (Diptera: Streblidae, Nycteribiidae) in the Amazon and Cerrado landscape scales and ecotonal areas
Diptera,Diversity,Interspecific association,Metrics,Neotropical
The high diversity of bats in the Neotropics is primarily associated with various ectoparasite species on their bodies. Interactions between these animals need to be comprehensively investigated at landscape scales, focusing on understanding the patterns of diversity of species. We sought to evaluate, througt bat captures and ectoparasite sampling, the determinants of the composition of ectoparasitic flies species present in bats in in the Amazon and Cerrado biomes and ecotone areas. We used a generalized dissimilarity model (GDM) to verify what factors explained the composition of ectoparasitic flies of bats using landscape metrics, geographic distance, biome, and host composition. Twenty-four bat species haboured a total of 33 species of ectoparasitic flies. Host composition was the best predictor of fly composition, followed by the environmental variables and by biome. Geographical distance presented negligible effects. Studies on large scales tend to reveal a wide diversity of ectoparasitic flies. Host composition, as the best predictor of fly composition, may be associated with interspecific characteristics among species. We recommend studies focusing on the landscape to understand better the parasitic associations of bats and their distribution across environments. Supplementary Information The online version contains supplementary material available at 10.1007/s00436-023-07886-4.
Determinants of the composition of ectoparasitic flies of bats (Diptera: Streblidae, Nycteribiidae) in the Amazon and Cerrado landscape scales and ecotonal areas

The high diversity of bats in the Neotropics is primarily associated with various ectoparasite species on their bodies. Interactions between these animals need to be comprehensively investigated at landscape scales, focusing on understanding the patterns of diversity of species. We sought to evaluate, througt bat captures and ectoparasite sampling, the determinants of the composition of ectoparasitic flies species present in bats in in the Amazon and Cerrado biomes and ecotone areas. We used a generalized dissimilarity model (GDM) to verify what factors explained the composition of ectoparasitic flies of bats using landscape metrics, geographic distance, biome, and host composition. Twenty-four bat species haboured a total of 33 species of ectoparasitic flies. Host composition was the best predictor of fly composition, followed by the environmental variables and by biome. Geographical distance presented negligible effects. Studies on large scales tend to reveal a wide diversity of ectoparasitic flies. Host composition, as the best predictor of fly composition, may be associated with interspecific characteristics among species. We recommend studies focusing on the landscape to understand better the parasitic associations of bats and their distribution across environments.

The online version contains supplementary material available at 10.1007/s00436-023-07886-4.

The South American continent has a high diversity of bats (Diaz et al. 2021). There are 181 known bat species in Brazil (Garbino et al. 2020) in all biomes in the country. Among the Brazilian biomes, the Amazon and the Cerrado, along with their ecotonal zones, may be considered the largest savannah-forest transition worldwide (Marques et al. 2020). In these regions, there is a wide diversity of bats in the most diverse food niches, which include nectars, fruits, and insects (Kunz et al. 2011). Also, bats provide various ecosystem services, such as pollination, seed dispersal, and insect population control (Ramírez-Fráncel et al. 2022). Unfortunately, there is a significant gap in studies with bats in these regions (Bernard et al. 2011; Sabino-Santos et al. 2020). Bats commonly have ectoparasites on their bodies (Dáttilo et al. 2020). The intensity of this relationship may be associated with factors intrinsic to bats, such as age, sex, feeding habits, type of shelter, genetic characteristics, body size, and population density (Patterson et al. 2007). Additionally, extrinsic factors to the hosts, such as the size of the forest fragment, environmental integrity, and the characteristics of the surrounding matrices, also influence parasitism (Santos et al. 2012; Dick and Dittmar 2013). Among these ectoparasites, flies belonging to the family Nycteribiidae and Streblidae, known as bat flies, are obligated hematophagous species that occur exclusively in bats (Marshall 1982), including an evolutionary history associated with their hosts (Poinar and Brown 2012). Bat flies have a worldwide distribution; however, the great diversity occurs in the Neotropics (Dittmar et al. 2015). Many studies conducted in Brazil have obtained data on the relationship between ectoparasitic flies and their bat hosts. Most of these studies were conducted in Atlantic Forest and Cerrado biomes (Eriksson et al. 2011; Santos et al. 2013; Soares et al. 2013; Barbier and Graciolli 2016; Bezerra et al. 2016; Vasconcelos et al. 2016; Lourenço et al. 2016). However, data on bat ectoparasites in Amazonian regions are scarce (Hrycyna et al. 2019; Palheta et al. 2020). Studies with bat fly focusing on the ecotonal zone of the Amazon and Cerrado are unpublished. Understanding these relationships between bats and their ectoparasitic flies in the Amazon and Cerrado biomes is essential since there have been many changes in land use and environmental characteristics in these regions, with substantial impacts in recent decades (Lathuillière et al. 2016). These impacts include deforestation and forest destruction, often leaving only islands of vegetation surrounded by anthropic matrices (Fearnside 2005). In this region, this is so evident that it became known worldwide as the “arc of deforestation” and encompasses the states of Rondônia, Mato Grosso, and Pará (Gomez et al. 2015). Given the existing research gaps in the studies of bats and their ectoparasitic flies in these environments, it is important to conduct studies that aim to investigate the factors determining the composition of these flies on bats in fragmented landscapes. This is because these flies form complex networks of interactions with significantly specialized characteristics (Júnior et al. 2020) and have few investigations on a landscape scale. It should be noted that research on bat ectoparasites also tends to complement other areas, such as those related to public health, as ectoparasites may have associations with pathogens (Judson et al. 2015; Abundes-Gallegos et al. 2018). This perspective of understanding the mechanisms determining communities of ectoparasitic flies of bats in the Neotropics and knowing the diversity of these species in highly relevant biomes and their ecotonal areas is of utmost importance. Therefore, this study sought to answer which determinants explain the composition of ectoparasitic flies of bat communities in broad geographic landscapes in the Amazon, Cerrado, and ecotonal areas. We evaluated the effects of host composition, environmental factors, geographic distance, and biomes. Based on other studies (Barbier et al. 2019; Eriksson et al. 2020), we tested the hypothesis that host composition should be the most influential factor in the composition of the ectoparasitic fly community since it tends to have high host specificity, spending most of its life on the bat (Eriksson et al. 2020). We predict that environmental variables will have a moderate impact on the species composition of batflies. This is because batflies are not only highly reliant on their hosts but also influenced by the characteristics of the bat roost. Thus, bat fly communities should associate more with bat species composition. On the other hand, geographic distance would not have a significant influence on the composition of bat species (López-González et al. 2015; Varzinczak et al. 2018), and sampling in different biomes (Falcão et al. 2022), as already observed in other studies.

Our samplings were conducted on the western edge of the central region of Brazil, among different areas in the Amazon and Cerrado biomes and their ecotone. The definition of the sample areas consisted of onsite visits to the sample points and following recent redefinitions of the ecotone region between the biomes (see Marques et al. 2020). We selected 24 forest remnants distributed on our landscape scale, being eight in each phytophysiognomy (Amazon, ecotone, and Cerrado). Within each phytophysiognomy, the remnants had a minimum distance of 10 km from each other to avoid pseudoreplication. We also divided each set of eight remnants in each biome into four isolated remnants (surrounded by anthropic matrices) and four connected remnants (with forest connection corridors with other areas). The geographic distance varied between 397 km (Amazon and ecotone) and 183 km (ecotone and Cerrado) among the sampled phytophysiognomies (Fig. 1).

Bats were captured by exposing 10 mist nets (model 716/12P, 12 × 2.5 m, denier 75/2, 16 × 16 mm net, Ecotone Inc. Poland) with two sampling nights at each point, which were open for 6 h after dusk and searched every 15 min. At each point, sampling took place on the edge and another on the inside of each fragment, with a minimum distance from the edge to the inside of 100 m to reduce edge effects (Broadbent et al. 2008). The arrangement of the nets was conducted in possible flight corridors for the bats. Each captured bat was placed individually in a containment bag and subsequently sorted, with morphometric features (e.g., forearm, tibia, head body, tail, ear, nasal leaf) and body mass measured. Finally, bats were identified down to the species level through specific literature (Lim and Engstrom 2001; Gardner 2007; López-Baucells et al. 2016; Diaz et al. 2016, 2021). The collection of ectoparasites from bats was made manually using tweezers and inspecting the patagium and body, both dorsal and ventral. The ectoparasites of an individual bat were placed individually in microtubes with 70% alcohol and duly identified. Additionally, notes regarding the number of ectoparasites collected and the region of the bat found (patagium or body) (Graciolli and Bianconi 2007) were made on the field form. After that, the bats were photographed and released at the capture site except the testemunial specimens that were euthanized by deepening anesthesia with isoflurane (Sigma-Aldrich, St. Louis, MO, USA). These bats were fixed in 10% formaldehyde and placed in 70% alcohol and are kept in the scientific collection of the Federal Institute of Mato Grosso, Pontes e Lacerda. Ectoparasitic flies were identified in the laboratory using stereoscopic magnifying glasses and tweezers, following specific literature (Guerrero 1993; 1994a; b; 1995; 1996). We followed the recommendations of the American Society of Mammalogists guidelines for the use of wild animals in research, also to the recommendations for handling potentially hantavirus-infected animals (Mills et al. 1995; Sikes and Gannon 2011) and the guidelines for reducing the risks of transmission of SARS-CoV-2 from humans to bats (Moratelli et al. 2020).

In order to evaluate the determinants of the composition of ectoparasite communities, we extracted several landscape metrics from landscape raster files using maps provided by Mapbiomas (www.mapbiomas.org). Namely, the variables extracted were forest cohesion (cohesion_forest), the density of forest fragment (d_frag_forest), the proportion of campestral area (prop_campestral), the proportion of forest area (prop_forest), biome, the proportion of water (prop_water), the proportion of urban infrastructure (prop_infra_urban), the presence of water at the sampling site (water_site_collect), the number of fire focus in the last five years (n_focus_em_five), number of fire focus in the year of collection (n_focus_year_collect), number of fire focus in the last five years in the sampled fragment (focus_on_frag_in_five), number of fire focus in the last year in the sampled fragment (focus_on_frag_last_year), seasonality (seas), the density of the edge of the forest (d_edge_forest), forest shape (shape_forest), the proportion of pasture (prop_pasture), the proportion of other land-use classes (prop_no_veg), and the proportion of agriculture (prop_agric). Rasters have numbers that distinguish pixels and allow classification into classes. First, we used QGIS (2022) and the R program (2022) to convert the files into projected coordinates. Later, we cut the raster files using a buffer vector mask with a radius of 2000 m. This buffer size is based on biological data that predict the displacement distance of neotropical bats within their home ranges (Trevelin et al. 2013). Using the software R, we deal with the vector file, matrix file and the buffer file with the packages “rgdal,” “raster,” and “rgeos,” respectively (Bivand et al. 2022; Hijmans et al. 2022). Finally, the landscape metrics were calculated using the SpatialEco package (Evans et al. 2022).

First, a generalized dissimilarity model (GDM; see details below) was conducted including all the environmental variables (cohesion_forest, d_frag_forest, prop_campestre, prop_forest, biome, prop_water, prop_urban_urban, water_local_collection, n_focus_in_five, n_focos_year_collection, focus_on_frag_in_five, focus_on_frag_last_year, season, d_edge_forest, forest_shape prop_pasture, prop_no_veg, and prop_agric) as predictors, and the community of ectoparasitic flies as the response variable. Only the predictor variables that presented an importance value greater than five (forest cohesion and d_frag_forest) were included in the final analysis (Supplementary Table 1), except for the variable biome, which is the main focus of our study. The importance of each predictor variable is calculated through the change in the percentage of explained deviation in the model containing the variable and the percentage of explained deviation calculated using 1000 permutations of the model without the variable (Manion et al. 2022). GDM models do not accept categorical explanatory variables. Therefore, the variables biome, seasonality, and connectivity were transformed into integer numerical values following the recommendation of Ferrier et al. (2007). The Amazon, Cerrado, and ecotonal samples received values of 2, 0, and 1, respectively. Samples from the dry season received a value of 0, and those from the rainy season received a value of 1. Finally, samples of isolated fragments received a value of 0, while connected fragments received a value of 1. The correlation between the variables selected was lower than 75% (Dormann et al. 2013).

A generalized dissimilarity model (GDM) was created to analyze the effect of selected environmental variables (see above), geographic distance, and host species composition on the community structure of ectoparasitic flies (response variable). The GDM model was chosen because, unlike multiple regression models (MRM), it allows for non-linear correlation between variables (Ferrier et al. 2007). Also, a comparative study between GDM and MRM models found a more credible response when analyzing the factors influencing communities of ectoparasitic fleas in small mammals (Maestri et al. 2017). The Bray–Curtis dissimilarity index was used for bat communities and ectoparasitic flies (Magurran 2004). The model significance was calculated through 1000 random permutations of the explained deviation (Manion et al. 2022). According to Borcard et al. (1992), the variance partition was calculated by comparing the percentages of explanations of the models for each independent variable and their possible combinations. The analyses were performed in R, version 4.2.1, with the packages “vegan” and “gdm” (Manion et al. 2022; Oksanen et al. 2022; R Core Team 2022).

We sampled 982 bat individuals of 48 species. Among these, we obtained records of at least the infestation of one species of ectoparasitic fly in 24 species (n = 425 individuals) of bats of the Phyllostomidae and Vespertilionidae families. In addition, we obtained 1450 ectoparasitic flies of the Nycteribiidae and Streblidae families distributed in 33 species in the Amazon, Cerrado, and ecotonal landscapes. The most abundant bat species that provided ectoparasitic flies were Carollia brevicauda (34.9%), C. perspicillata (24.1%), and Phyllostomus discolor (9.2%). Among the ectoparasitic flies, the species Trichobius joblingi (55.6%), T. dugesiodes (6.0%), and T. costalimai (6.0%) registered the highest abundance. The bat species had from 1 to 9 species of associated ectoparasitic flies. The number of flies per biome varied from 447 (ecotone) to 515 (Cerrado). The species richness of flies among biomes ranged from 22 (ecotonal areas) to 25 (Amazon), with species with unique records in the Amazon [Strebla christinae, S. consocia, S. machadoi, S. wiedemannii, Trichobius dugesii, T. sp. (longipes group), T. sp. (parasiticus complex group)], and ecotonal areas (Pseudrostrebla riberoi and Trichobius johnsonae), and Cerrado (Paradyschiria parvula, Stizostrebla longirostris, Strebla hertigi, S. mirabilis, Trichobioides perspicillatus, Trichobius costalimai, T. longipes, and T. parasiticus). Concerning the forest remnant, some species of ectoparasitic flies occurred only in isolated remnants [Paradyschiria parvula, Pseudrostrebla riberoi, Stizostrebla longirostris, S. christinae, Strebla wiedemannii, Trichobius longipes, T. parasiticus, Trichobius sp. (longipes group) and T. uniformis]. In contrast, other species were recorded only in connected remnants (Strebla consocia, S. machadoi, S. mirabilis, Trichobius caecus, T. dugesii, and T. johnsonae, T. sp. (parasiticus complex), and T. tiptoni) (Table 1). The community structure of ectoparasitic flies was strongly influenced by the host composition found in the sampled landscape (Table 2). Forest cohesion also influences, to a lesser extent, the composition of ectoparasitic flies, and the other variables hardly explain the composition of bat flies (Table 2). Among the environmental variables, forest cohesion and host composition were the predictors that had the most influence on the composition of bat ectoparasitic fly communities (Fig. 2). When we analyze the partition of their contribution, we reaffirm that the composition of host species has the most significant influence on the composition of the ectoparasitic flies, followed by the sum of the environmental variables. Therefore, associating these variables with the sum of the host species composition and the environmental variables explains better, unlike the other associations, which do little to explain the species composition of ectoparasitic flies of bats (Table 3).

The diversity and abundance of ectoparasite flies found in the sampled landscape surpassed other studies that generally inventoried species of ectoparasite flies disregardful the phytophysiognomies (Amazon or Cerrado) (Santos et al. 2013; Barbier et al. 2016; Aguiar and Antonini 2016; Urbieta et al. 2020; Palheta et al. 2020). We also emphasized the great diversity found in the ecotone region between the Amazon and Cerrado biomes, which is an area sensitive to fragmentation processes that undergo constant advances with human actions in land use (Marques et al. 2020). Until then, no studies have focused on bat flies in the ectone between Amazon forest and Cerrado savannahs. Notwithstanding, our research focused on environments altered by land-use actions, unlike studies with bat flies in conserved areas, which tend to reveal greater diversity (Hrycyna et al. 2019). Our results also indicate the disparity between the number of interaction records of ectoparasitic fly species with bats. For example, the fly species Trichobius joblingi were present on 50% of bat species, while most of the remaining fly species ocuured on one or two bats species. The predominance of the T. joblingi fly is expected since it is the most commom bat ectoparasites found on.bats in the Neotropical region (Barbier and Graciolli 2016; Wenzel 1976). Its ccurrence in different bats species can be a indicative that this fly pursuit low host requirements, allowing for a low host-specificity. The flies of the Streblidae family were predominant in our study, with only one record of the Nycteriibidae family (Basilia carteri), as observed in other studies (Santos et al. 2013). The high number of the Streblidae family is associated with their distribution since they are more diverse in the Neotropics (Haelewaters et al. 2018) and have a specific association with bats of the Phyllostomidae family (Wenzel et al. 1966; Wenzel 1976), as we also observed. In contrast, the Nycteriibidae family is more diverse in the eastern hemisphere (Haelewaters et al. 2018). Moreover, its association includes other bat families, such as the Vespertilionidae family, as we observed in our study. The occurence of B. carteri on Eptsesicus furinalis was already reported by Urbieta et al. (2018) in a cerrado region. We also highlighted the record of the fly species Stizostrebla longirostris on the bat Lophostoma carrikeri, which had only been recorded in Brazil in the Cerrado of Maranhão (Diaz et al. 2009; Santos et al. 2013) and the state of Rio de Janeiro (Guerrero 1995). This makes our record the the southernmost in Cerrado. The effect of host composition we observed influencing the composition of ectoparasitic fly communities reflects the interspecific interactions between these species. Bat flies (Diptera: Nycteribiidae and Streblidae) spend most of their lives on their hosts and can die in a few hours if separated (Dittmar et al. 2015). Furthermore, many of these flies are highly host specific, and it is closely associated with only a single bat species, just as bats generally have a few different species of associated flies (Wenzel et al. 1966; Wenzel 1976; Dick and Gettinger 2005), as we observed in our study. Our study agrres with the review of published articles, that found a high relationship between the host and bat fly composition (Ericksson et al. 2020). In contrast, extensive research with bats in Panama reinforces the high specificity between flies and bats (Hiller et al. 2021). Some studies with bat fly at local scales also associate the more significant influence of the host species composition variable determinant explaining bat fly diversity (Barbier et al. 2019; Hernández-Martínez et al. 2018). The slightest explanation of the determinant environmental variable does not rule out its influence on the composition of bat fly communities since these factors require deep investigations to denote their relevance. An example is a study with fleas in rodents, which identified environmental variables related to air temperature and host rotation as determinants of parasite composition (Maestri et al. 2017). On a continental scale, the environmental variables most influenced were annual precipitation and temperature seasonality (Ericksson et al. 2020). On the other hand, a study with a sample design like ours on a smaller scale in the northeast region of Brazil did not find rain influences the prevalence and average intensity and abundance of ectoparasitic flies of bats (Barbier et al. 2019). The strong effect of host species composition and the negligible effect of the geographic distance on bat flies species composition seems to be a rule in the Neotropical region (Barbier et al. 2019, Ericksson et al. 2020). However, the influence of different environmental variables in different regions and scales deserves attention. Microclimate inside roosts and the exposition of the free stages of parasite to detrimental environment condition can be a local determinant of bat flies species composition (Dittmar et al. 2009; Pilosof et al 2012; Eriksson et al. 2023). Our results show more ectoparasitic flies (n = 908) in the connected remnants than in the isolated ones (n = 549). However, the richness of the connected ones (n = 26) was lower than that of the isolated ones (n = 27), which may be associated with the composition of the hosts, which would explain the similarity in the richness of flies among the remnants. We suggest that the environmental variable with the most significant observed influence, forest cohesion, which refers to the connections between the sampled forest remnants, may indicate the importance of this variable in the composition of ectoparasite communities. This is because connected forest environments may have a better ecological structure, consequently allowing for a greater diversity of bats and their ectoparasitic flies, as already observed in other studies (Pilosof et al. 2012; Frank et al. 2016; Ramalho et al. 2018). The determinant geographical distance did little to explain the composition of communities of ectoparasitic flies on bats. The compilation by Ericksson et al. (2020) also did not find this relationship. On the other hand, some studies have identified geographic distance as a relevant scale for bat community composition (Stevens et al. 2007; López-González et al. 2015; Varzinczak et al. 2018). However, considering our study on a broad geographical scale of this interaction between bats and their flies, it is necessary to turn to the interpretation of the strategies of association, dispersion, and mobility of the ectoparasitic flies as a primordial factor for the results found. This may be associated with the host effect, which correlates the species richness of bats with ectoparasite flies, commonly observed in host–parasite associations (Kamiya et al. 2014). Another critical point to highlight is the mobility of the hosts themselves, as bats use flights to travel, with large distances covered and few species endemic to specific regions in Brazilian biomes (Nogueira et al. 2014; Esbérard et al. 2017). The same applies to the biome determinant, as Falcão et al. (2022) observed between the Caatinga and Cerrado biomes, who did not find a strong influence of phytophysiognomies in the analysis of networks of interactions between bats-ectoparasites. The partition of variables makes it clear that the determinant composition of hosts and the environmental variable, emphasizing forest cohesion, determine the composition of ectoparasitic flies in bats in the sampled region. This reinforces the importance of landscape-scale studies involving different phytophysiognomies and their ecotonal zones in understanding how bat species and parasitic associations are distributed across environments (Peixoto et al. 2018; Ericksson et al. 2020).

The wide diversity of ectoparasite flies found on bats in our study in fragmented areas reinforces the importance of landscape-scale studies in understanding the interaction patterns and effects that determine the composition of these ectoparasites. The host composition stands out as the explanation for the composition of ectoparasite flies in the sampled landscapes, which may be associated with the specificity of the host–parasite relationship. The explanation of environmental variables and almost no effect of geographic distance and biome can be related to the specific characteristics of bats and their morphoecological structure. Studies of bats and their interactions in Neotropical landscapes sensitive to fragmentation processes are essential for understanding patterns and conservation strategies for the ecological stability of these species.

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