Potential use of distinct biomarkers (trace metals, micronuclei, and nuclear abnormalities) in a heterogeneous sample of birds in southern Brazil

The analysis of metal concentrations in bird feathers and genotoxicity tests are tools used to evaluate anthropogenic impacts on ecosystems. We investigated the response of birds, used as bioindicators, to disturbances observed in three areas with distinctive environmental characteristics (natural, agricultural, and urban) in southern Brazil. For this purpose, we quantified metals (Mn, Cu, Cr, and Zn) in feathers and determined the number of micronuclei (MN) and other nuclear abnormalities (NA) in 108 birds from 25 species and 17 families captured in the study area. No significant differences was found in the metal concentrations and the number of MN and NA between the sampling areas. Zn and Cu concentrations were significantly higher in insectivorous than those in omnivorous birds. The Zn concentration was significantly different between some species, and the Cu concentration was significantly higher in juveniles than that in adults. The best generalized linear models showed that omnivorous birds had more MN and NA and that juveniles and birds with better body condition index had increased NA numbers. This study demonstrates that the analyzed variables contribute in different ways to the result of each biomarker, mainly due to particular ecological and physiological characteristics of each species. We conclude that wild birds have the potential to be used as environmental bioindicators in the study area, but future studies should focus on one or a few species whose ecological and physiological habits are well known.


Introduction
Environmental discharges of many toxic compounds resulting from anthropogenic activities, such as pesticides, herbicides, and industrial and vehicular atmospheric emissions, are associated with the degradation of natural habitats (Olayemi et al. 2014;Baesse et al. 2019). These compounds release metals into the environment that, in high concentrations, can affect the health of various animal species, including birds (Pandiyan et al. 2020). The effects of metals on birds are related to changes in growth, reproduction, and, consequently, survival (Burger and Gochfeld 1995). Additionally, they can induce a genetic imbalance in these organisms due to their mutagenic and carcinogenic properties (Alimba and Bakare 2016;de Souza et al. 2017;Baesse et al. 2019).
In this context, quantification of metals and genotoxicity evaluation are frequently used tools of environmental monitoring in studies with birds. Birds are considered bioindicators of environmental quality at a global level (Solgi et al. 2020) Responsible Editor: Bruno Nunes * Joana Tomazelli joanatomazelli1@gmail.com Gunther Gehlen guntherg@feevale.br 1 because they quickly reflect environmental changes (Baesse et al. 2015), are easily found, live in many different habitats, and occupy distinct trophic levels (Becker 2003;Abbasi et al. 2015a;Solgi et al. 2020). Moreover, the collection of biological samples, like feathers and blood, is considered a nondestructive procedure (Burger and Gochfeld 2000;Braga et al. 2010).
Feathers are widely used in environmental studies because of its capability of metal accumulation (Solgi et al. 2020) via external deposition and internally through the bloodstream (Burger and Gochfeld 2000), reflecting long-term damage (Dauwe et al. 2000).
The micronucleus (MN) test (Baesse et al. 2015) and the nuclear abnormalities (NA) test (Quero et al. 2016) are used for genotoxicity evaluation. MN and NA are formed when organisms are exposed to genotoxic agents (Angeletti and Carere 2014). MN are small chromatin bodies located outside the nucleus and generated by chromosomal/spindle break or centromere dysfunction during cell division (Bonisoli-Alquati 2014). NA are nuclear malformations attributable to errors during the development of erythrocytes (de Mas et al. 2015). These alterations represent impacts on DNA (Baesse et al. 2015) and indicate recent exposure to contaminants (Santos et al. 2017).
Diet (Burger and Gochfeld 2000;de Mas et al. 2015;Abbasi et al. 2015a;Solgi et al. 2020), behavioral and feeding strategies (Costa et al. 2011;Tsarpali et al. 2020;Tasneem et al. 2020), and availability of food resources (Fritsch et al. 2012;Quero et al. 2016) are some factors responsible for metal contamination and changes in the number of MN and NA in birds. Birds from higher trophic levels present higher metal concentrations (Zolfaghari et al. 2007;Lodenius and Solonen 2013;Abbasi et al. 2015a) due to the biomagnification process (Burge and Gochfeld 1995;Tasneem et al. 2020). Food preferences might influence the levels of MN (Quirós et al. 2008) and the formation of NA (Quero et al. 2016). Quirós et al. (2008) found significant differences between nestlings of heron species that feed in aquatic and terrestrial habitats, reporting higher levels of MN in terrestrial species, which usually feed on insects. However, there is limited information about the relationship between MN and NA levels and diet in the literature.
Studies comparing the presence of metals, MN, NA, and the nutritional status of birds are scarce. High metal concentrations were found in the liver and kidney of owls with low lipid reserve (Esselink et al. 1995). However, this relationship was recently investigated in structures like feathers (Innangi et al. 2019), and more studies on the subject are needed. MN and NA were not correlated to the body condition (Tsarpali et al. 2020;Frixione and Rodríguez-Estrella 2020), but inferior health and/or nutritional status might increase the amount of damage to the cell nucleus (Santos et al. 2017).
Regarding wildlife exposure to chemical compounds, age class is an important factor to be considered (Squadrone et al. 2016). Studies indicate that metal concentration in several tissues is frequently higher in adult birds (Burge and Gochfeld 1995;Leonzio et al. 2009;Ackerman et al. 2019;Innangi et al. 2019;López-Perea et al. 2019), because of longterm exposure to contaminated environments and the consequent bioaccumulation (Grúz et al. 2018;Innangi et al. 2019). As the feathers of young individuals are recently formed and are less exposed to atmospheric conditions, they have lower concentrations of metals (Dauwe et al. 2000). Age is also an important factor for MN and NA. Different generations might present different levels of these alterations (Santos et al. 2017;Tsarpali et al. 2020). MN and NA increased with the reduction of the age class in aquatic birds (Santos et al. 2017), but few studies tried to establish this relationship.
The Sinos River Hydrographic Basin (SRHB), located in the eastern region of the state of Rio Grande do Sul, southern Brazil, had its vegetation cover altered by human activities that started after the arrival of European immigrants, and this process was intensified since the 1940s (Franz et al. 2010). Deforestation to open areas for agriculture and cattle grazing is the main cause for the reduction of the vegetation cover in the basin to 10% of its original area. Besides that, these activities also contributed to the reduction of water quality (Figueiredo et al. 2010). In the metropolitan area, the high population and industrial density, added to its associated environmental problems (atmospheric emissions, industrial wastewater, lack of basic sanitation, and intense vehicle traffic), contribute to the environmental degradation observed in this basin (Figueiredo et al. 2010). Previous studies with different bioindicators and biomarkers have shown an important environmental disturbance in the SRHB caused by multiple factors. In fish, high levels of metals and morphological changes have already been reported (Dalzochio et al. 2018). In plants (Tradescantia pallida var. purpurea), genotoxic damages influenced by low air quality were also observed .
In this context, although the SRHB is the study object of other authors, there is a lack of information concerning biomarkers and health general status in the avifauna. Therefore, it is important to analyze the response of birds to the environmental impacts occurring in this region. This study aimed to evaluate the effect of anthropogenic disturbance in wild birds that inhabit areas with different environmental characteristics across the SRHB by analyzing the concentration of trace metals (chromium (Cr), manganese (Mn), copper (Cu), and zinc (Zn) in feathers and the frequency of MN and NA in peripheral blood. Besides that, we evaluated whether there was a variation in metal concentrations and MN and NA frequencies between sampling point, trophic guild, species, body condition index (BCI), and age class. Finally, we assessed whether there was a contribution of the BCI in the variation of the biomarkers used. We hypothesized that birds inhabiting regions with less environmental impact would present lower metal concentrations and lower frequencies of MN and NA in comparison with birds inhabiting more impacted regions. Additionally, we tested whether trophic guild, species, age class, and birds with more lipid reserves respond in different ways to environmental disturbance.

Study area
The study was conducted in two cities, Taquara and Novo Hamburgo, which are part of the Sinos River Hydrographic Basin. Three sampling sites were defined, each located in a distinct environmental zone (natural, rural, and urban zones) (Fig. 1). The climate, according to the Köppen classification, is Cfa, with no defined dry season and average air temperature higher than 22°C in the hottest month (Peel et al. 2007). The areas are predominantly in the semideciduous seasonal forest domain (IBGE 2012).

Ilha River (municipality of Taquara)
Sampling site 1 (S1) is located near the source of the Ilha River (29°32′51.62′′S 50°37′34.14′′W), and its vegetation is typical of the highest altitude areas in the basin, i.e., it has a dense vegetation cover with the occurrence of exotic invasive species, such as the Japanese raisin tree (Hovenia dulcis) (Fontanella et al. 2009). Some elements of ombrophilous forest are observed in this region, as it is in an ecotone between this plant formation and the semideciduous seasonal forest (COMITESINOS 2016). This region is also characterized by surrounding areas with plantations of exotic species, such as Pinus sp. and Eucalyptus sp. There are also small farms and low population density.
Sampling site 2 (S2) is located near the mouth of the Ilha River (29°40′41.81′′S 50°44′25.30′′W). There are more houses and rural properties at this point than at S1, and activities such as cattle raising are carried out in the region. The vegetation has been changed due to greater anthropogenic action (Fontanella et al. 2009). Native vegetation at this sampling site is restricted to riparian vegetation, which is surrounded by rice plantations.

Parque Henrique Luís Roessler (Novo Hamburgo City)
The sampling site 3 (S3) corresponds to the Parque Henrique Luís Roessler, a municipal conservation unit (Municipal Legislation of Novo Hamburgo/RS2009), located in the urban area of the municipality of Novo Hamburgo (29°40′53.67′′S 51°6′33.38′′W). The unit is surrounded by streets, houses, and residential and commercial buildings. The native Fig. 1 Map with the location of the sampling points in the SRHB, state of Rio Grande do Sul, Brazil. Sampling sites 1 (S1-natural zone) and 2 (S2rural zone) are in the municipality of Taquara, whereas sampling site 3 (S3-urban zone) is in the municipality of Novo Hamburgo vegetation is characterized as an early stage of succession. Some exotic species are present, such as Pinus elliottii(Cappelatti and Schmitt 2009). There are three springs within the unit, all of them contaminated by the illegal discharge of domestic wastewater (Leuck 2010).

Capture of birds and data collection
Birds were captured between November 2019 and May 2020 with mistnets (9 m × 3 m, 15-mm mesh size). Each sampling site was sampled four times during this period for approximately 5 h in the morning. To avoid animal stress, the nets were checked every 15-30 min during the sampling period. Species identification followed Sigrist (2014). All individuals were marked with metallic rings supplied by CEMAVE-ICMBio to avoid resampling and grouped by taxa according to the Brazilian Ornithological Records Committee (Comitê Brasileiro de Registros Ornitológicos) (de Piacentini et al. 2015).
The age class determination was based on information from feather condition and other attributes from the plumage (molt and molt limits, shape of flight feathers, presence or absence of growing bars) (Ralph et al. 1996;Howell et al. 2003). Additional characteristics, such as skull ossification, iris and bill color, and commissure of the bill were also observed (Ralph et al. 1996). To categorize the age class of the birds, the system of classification based on the molting cycle-Wolfe-Ryder-Pyle (WRP) Johnson et al. 2011;Johnson and Wolfe 2017)-was used. Specimens were classified as juveniles when they were on, or presented signs of, the first cycle, i.e., they had juvenile plumage-acquired after leaving the nest-or formative plumage-acquired before reaching sexual maturity. Specimens that had finished the first cycle were classified as adults, and a third category, undetermined age, was defined to include those animals that were not confidently classified as either juveniles or adults.
Birds were grouped into three trophic guilds following the classification proposed by Wilman et al. (2014). This database defines trophic guilds based on the proportion of different food items consumed by each species. The guilds used in this study were: (1) insectivore, (2) herbivore/granivore, and (3) omnivore.
Body condition can be estimated by dividing body mass by any linear measure of body size (Labocha and Hayes 2012). Therefore, the BCI (body condition index) was defined as the body mass divided by the tarsus length. Individuals with a high index value have a larger skeleton size and probably have better lipidic reserves (Gaiotti et al. 2020). The length of the tarsus (in mm) was measured by a caliper rule, and the mass was inferred with a digital weighing scale (precision of 0.1 g).
A sample of blood, about 50-200 μL, was taken from the ulnar vein using a sterile needle (0.45 × 13 mm-subcutaneous standard). Blood smears (two slides per individual) were immediately made on glass slides (Braga et al. 2010), which were dried at environmental temperature and fixed in methanol for 10 min.
For the analysis of metals, some contour feathers were taken from both sides of the chest of each bird to reduce the possibility of harm (Burger and Gochfeld 2000). The feathers were placed in zipped plastic bags (Abbasi et al. 2015b), identified with a label containing the ring number of each bird and stored at room temperature.

Washing, digestion, and detection of metals in feathers
The metals detected and quantified in this study were chosen because of their wide occurrence in the studied area (Fontanella et al. 2009;Nascimento et al. 2015;Dalzochio et al. 2017). To remove any contaminants deposited on the surface, the feathers were washed alternately with deionized water (1 min) and PA acetone (1 min) in decontaminated falcon tubes, which were shaken by hand (Veerle et al. 2004;Abdullah et al. 2015). This procedure was repeated three times. After washing, the feathers were dried at 80°C in an oven for 1 h (Abbasi et al. 2015a).
The procedure for digestion of feathers followed adaptations of the methodology proposed by Reglero et al. (2008). The feathers (average of 0.03 g) were initially immersed in a solution of HNO 3 (65%). Afterward, they were digested in a microwave accelerated reaction system (MARS6-CEM). Briefly, the feathers were calcined for 20 min until reaching the temperature of 180°C, maintained at 180°C for 15 more minutes, and then refrigerated for 15 min. Digested samples were diluted in a solution of 1520 μL of HNO 3 (65%) (Merck, Darmstadt, Germany) and 106 μL of Triton (Baker Analyzed®) and had the volume adjusted to 100 mL with Milli-Q H 2 O.
A graphite furnace atomic absorption spectrometer (GFAAS-Perkin Elmer AAnalyst 600) was used for metal detection following Dalzochio et al. (2017). To provide quality control data, solutions used to dilute processed samples in each batch of analysis were taken as blank. The concentration of metals in sample blank solutions was always below detection limits. Detection limits for metals Cr, Mn, Cu, and Zn were 0.006, 0.01, 0.01, and 0.3 μg g −1 , respectively.

Preparation and analysis of slides
In the laboratory, the slides were stained with Giemsa solution (5%) for 10-15 min. Afterward, they were codified and analyzed by a single person (Alimba and Bakare 2016) under an optical microscope at the highest magnification (1000×). For every bird, 3000 erythrocytes were analyzed (Hussain et al. 2012).
Criteria for the identification of MN and NA were adapted from Quero et al. (2016). Thus, MN were identified as oval or circular structures with 1/3 to 1/16 of the nucleus size, with the same focal plane, color, and texture as the nucleus, without bridges or chromatin overlaps (Tolbert et al. 1992) (Fig. 2).
Among the NA, nuclear buds had the same morphology as the MN but remained connected to the nucleus, without formation of chromatin bridges or a constriction at one extremity, and had between 1/4 and 1/3 of the size of the main nucleus (Thomas et al. 2009). Binucleated cells presented two nuclei about the same size and color, with or without contact between them (Thomas et al. 2009;Jindal and Verma 2015). Nuclei with a progressive narrowing and elongation at one extremity were considered nuclear tails (Kursa and Bezrukov 2008). Nucleoplasmic bridges were considered as two nuclear structures of the same color, having equal or different sizes, connected by a chromatin bridge (Tolbert et al. 1992). A nuclei was considered notched when it had a well-defined notch that extended to a considerable depth and was limited by the nuclear envelope (Carrasco et al. 1990; Alimba and Bakare 2016) (Fig. 2). Cases in which the nuclei morphology did not meet any of the pre-established criteria and/or raised doubts during the analysis were not included in the data.

Data analysis
To verify how much of the response variables (MN and NA) was explained by the predictor variables (sampling site, trophic guilds, species, BCI, and age classes), we used generalized linear models (GLMs). The Poisson distribution was used in the MN models, whereas the negative binomial distribution was used in the NA models to correct for data overdispersion. The link function used was the logarithm (link = log).
We built 27 candidate models for each response variable (n = 54), including null models (no effect). Model selection was performed according to the Akaike information criterion for small sample size (AICc) (Burnham and Anderson 2002), using the value of ΔAICc < 2 (difference of AIC between given model and the best model) and the weight (w-weight of the evidence in favor of each model) for comparisons. The significance of each factor and the percentage of variation explained by the best models were calculated by applying the ANOVA test on the residuals of models and subsequently applying the formula proposed by Ye et al. (2001), represented by the deviance of the variable divided by model residual deviance multiplied by 100.
For the statistical analysis of the metal data, we tested normality using the Shapiro-Wilk test and applied the nonparametric Kruskal-Wallis test followed by post hoc Dunn's test to compare medians between points, species, trophic guilds, and age classes. We used the Spearman correlation (r s ) to verify the existence of a correlation between metal concentrations and BCI. The analyses were performed using the packages "vegan," "AICcmodavg," and "MASS" in the software "R" (R Core Team 2018), with a significance level of p≤ 0.05. The graphs were made in GraphPad Prism 8.0.1.

Detection of metals
The concentrations of the analyzed metals were not significantly different between sampling points (Online Resource 3). Significant differences were observed for Zn and Cu between some species, trophic guilds, age classes, and BCI. Zn concentrations were higher in Myiothlypis leucoblephara compared to Turdus albicollis (p < 0.05) and Turdus rufiventris (p < 0.05). Insectivores presented higher Zn (p < 0.05) and Cu (p < 0.05) concentrations than omnivores. The undetermined age class presented higher Zn concentrations compared to adult individuals (p < 0.01), and juvenile individuals presented higher Cu concentrations than adults (p < 0.01) (Online Resource 4). Only Zn and Cu were significantly correlated with the BCI, both negative and weak correlations (Zn: r s = −0.33, p < 0.01, Cr: r s = −0.22, p < 0.05). Figure 2a-i illustrate the MN and NA found in birds captured in the study. A total of 76 MN and 3267 NA were recorded in 46.8% and 99% of the birds, respectively. Considering the number of captured individuals, the overall mean frequency of MN was 0.70/3000 (or 2.33/10,000) and the overall mean frequency of NA was 5/3000 (or 16.68/10,000). The most frequent NA were notched nuclei (95.4%), followed by binucleated cells (82.4%), nuclear buds (62.0%), nucleoplasmic bridges (49.1%), and nuclear tails (26.8%) (Fig. 2m). While MN had varied frequencies, NA had similar numbers between sampling points (Online Resource 2).
The best supported GLM Poisson model showed that the omnivore guild contributed significantly and positively to data variation, being responsible for the increase in the number of MN (Table 1). In all negative binomial GLM, the variable BCI significantly and positively influenced the number of NA, showing that birds with better body conditions have more NA. The presence of the herbivore/granivore guild decreased, whereas the omnivore guild increased the NA in some models. The adult and undetermined age classes reduced significantly the NA number in the second model, indicating that juveniles have more NA than other age classes (Table 1).
The ANOVA test results of the MN model showed that the trophic guild was significant and explained 7.64% of the model (Table 2). In the NA GLM, the ANOVA test showed that trophic guild and BCI were significant and explanatory in all models. Age class also had a significant contribution to the explanation of the second and fourth-best models. The third best-ranked model explained the highest percentage of data variation (NA~age classes + trophic guild * BCI = 31.81%) ( Table 2).

Trace metals
The overall mean Zn concentration in feathers recorded in this study (437.77 ± 241.25 μg g −1 ) is similar to those recorded by Abdullah et al. (2015) in feathers of herons from polluted aquatic environments in Pakistan (226 to 529 μg g −1 ). However, the species M. leucoblephara presented a mean concentration of 762.82 ± 309.06 μg g −1 , which is significantly higher compared to T. rufiventri and T. albicollis (352.97 ± 132.00 and 336.18 ± 93.54 μg g −1 , respectively). These values are higher than concentrations found in the feathers of a passerine bird from a DDT-contaminated area in Africa (207.45 and 291.51μg g −1 ) (Baker et al. 2017). According to Tasneem et al. (2020), high concentrations of this metal in feathers might be related to deposition from exogenous sources, but Abdullah et al. (2015) argue that when there is a high concentration of Zn in the organism, it can be deposited in feathers as a way of excretion.
The metal Mn presented an overall mean concentration of 29.63 ± 16.74 μg g −1 , which is comparable to the value found in a passerine species living in a gradient of industrial pollution (means from 17.4 to 43.8 μg g −1 ) (Janssens et al. 2001) and in an aquatic bird species (16 to 21.9 μg g −1 ) (Abdullah et al. 2015). However, Baker et al. (2017) found concentrations ranging from 15.73 to 78.38 μgg −1 in Passer domesticus. The concentrations observed in the present study are high compared to values reported in the literature but are not high enough to indicate manganese contamination. Manganese is an essential metal that participates in a series of biochemical reactions in the organisms (Abdullah et al. 2015), but exogenous contamination can occur through vehicular pollution, contaminated dust, and food intake (Burge and Gochfeld 1995;Abdullah et al. 2015). The metal Cr presented an overall mean concentration of 2.41 ± 1.84 μg g −1 . This metal might have neurotoxic effects on birds, and Burger and Gochfeld (2000) assert that concentrations higher than 2.80 μg g −1 in feathers indicate contamination. Contamination by Cr in birds is related to diet (Grúz et al. 2018) and contact with emissions from anthropogenic sources, such as the leather industry (Abdullah et al. 2015). The overall mean Cu concentration found in the present study (7.84 ± 4.55 μg g −1 ) is low compared to bird feathers sampled in polluted areas (Manjula et al. 2015;Baker et al. 2017). According to Baker et al. (2017), exogenous contamination by this metal is related to anthropogenic sources, such as emissions from fossil fuels and industrial activities. Nevertheless, our results for these metals are similar to those recorded in passerine birds that inhabit an urban area in Pakistan (Cr, 1.11 ± 0.70 to 1.95 ± 0.16 and Cu, 2.19 ± 0.81 to 4.14 ± 0.20 μg g −1 ) (Abbasi et al. 2015b).

Micronuclei and nuclear abnormalities
The overall mean frequency of MN found in the present study (0.70/3000 or 2.33/10,000) is similar to the data in the literature. Baesse et al. (2019) found a mean of 1.04 MN/10,000 and Baesse et al. (2015) reported a mean of 1.30 MN/5000 (or 2.6 MN/10,000) in forest fragments of different sizes close to urban areas. In coffee farms with different sizes and different productive capacities, the mean was 3 MN/10,000 (Souto et al. 2018), which is higher than the values reported in other studies, but the evaluated environments and the chosen species might have contributed to this value.
The NA most frequently found in this study (notched nucleus and binucleated cells) were also the most representative abnormalities in a community of birds from a desert environment (Quero et al. 2016) and in a falcon species from an island environment (Tsarpali et al. 2020). Notched nucleus was the second most frequent NA found in a falcon species in an agricultural area (Frixione and Rodríguez-Estrella 2020), but the causes and mechanisms behind the formation of this abnormality are unknown (Quero et al. 2016). The presence of NA in birds such as the Japanese quail (Coturnix japonica) has been related to exposure to contaminants such as lead (Pb) (Suljević et al. 2021) and other heavy metal complexes (Suljević et al. 2020). In this species, binucleated cells were associated with exposure to landfill leachate (Alimba and Bakare 2016) and atrazine (Hussain et al. 2012). In Australian parakeets (Melopsittacus undulatus), binucleated cells were associated with exposure to tannery effluents ) and abamectin (de Faria et al. 2018). These chemical substances might inhibit cytokinesis during cell division (Alimba and Bakare 2016), affecting its final stages (de Faria et al. 2018). Studies conducted in the laboratory show that some specific pollutants are related to the formation of MN and NA in birds (Hussain et al. 2012;de Faria et al. 2018). In the natural environment, these pollutants are mixed, which makes it impossible to comprehend their individual effects. Even so, some studies show that higher rates of MN formation occur in birds that inhabit areas close to urbanization, which are exposed to metal pollution mainly from vehicular traffic (Baesse et al. 2019), and in birds that inhabit areas with agricultural production, where pesticides that have several metals in their composition are used (Souto et al. 2018). In coffee farms, Cu in synergy with other metals was associated with an increased rate of MN formation in birds (Souto et al. 2018). Therefore, although we have not found a direct interaction between the concentration of metals and the formation of MN and NA in birds, this relationship cannot be completely disregarded.

Influence of the sampling points
Although our sampling points are located in regions with different environmental characteristics, which are impacted by different levels of anthropogenic pressure, our results did not indicate different levels of contamination between these regions. None of the evaluated metals or the frequency of MN and NA presented significant differences between sampling points. Moreover, all metals presented the highest concentrations on S1, and this sampling point had the second highest frequency of MN, followed by S2. Thus, this sampling point, located in a region that apparently has a lower degree of impacts, might be contaminated by a wide range of pollutants that could enter even preserved areas through air movement (Abbasi et al. 2015b), as already reported by Alves et al. (2018) in the SRBH.
Even though we did not find any significant relationship, the impact on birds that inhabit urban areas was evidenced by a higher frequency of MN in S3. Stocker (2019) reports higher levels of MN in birds that live near the airport area in Porto Alegre, Brazil, when compared to captive animals. Baesse et al. (2019) found a larger number of MN in forest fragments close to urbanization, suggesting that the greater the vehicle traffic near the fragment, the larger the number of MN in birds. Sasamori et al. (2012) assessing the genotoxic potential of the air using Tradescantia pallida as a bioindicator in S3 found a higher frequency of MN in this place when compared to a control group, suggesting that pollution from motor vehicles might be the source of the genotoxic agent in this region.
However, based on our results, there is no clear distinction between potential genotoxicity and metal contamination in birds between sampling points. Other studies performed in the basin attribute the alterations in the levels of biomarkers to sources of pollution from anthropogenic origin Rocha-Uriartt et al. 2015;Dalzochio et al. 2017;Dalzochio et al. 2018). In the upper and middle sections of the basin, the water is contaminated by pesticides and hydrocarbons from agricultural activities, whereas in the lower section, contamination is due to the discharge of domestic wastewater and industrial effluents from the most populated areas (Bianchi et al. 2017). In this section, Alves et al. (2015) found metals such as barium (Ba) and Zn in the particulate matter of atmospheric air, and Illi et al. (2017) found high levels of Pb, Cr, and Zn accumulated in plants of the species Lolium multiflorum, evidencing the air pollution by industrial processes and vehicular traffic. Additionally, many vegetated areas in the basin are degraded, which make them more susceptible to the infiltration of pollutants dispersed by the atmospheric air, leaving the organisms exposed (Rocha-Uriartt et al. 2015). Thus, although this is the first study using biomarkers in birds, our results are similar to those found in the literature, and they show the impact that the various anthropogenic activities that occur in the basin have on wild birds.

Influence of trophic guilds
In this study, trophic guilds had a relevant contribution to results but were related to metal concentrations and genotoxicity in different ways. Insectivores presented significantly higher Zn and Cu concentrations than omnivores. GLM results indicated that a generalist diet (omnivore) is related to the increase in the number of MN and NA.
Our results agree with studies that found higher levels of metals in insectivorous birds in comparison with omnivorous birds (Leonzio et al. 2009;Gong et al. 2012;Abbasi et al. 2015b;Ackerman et al. 2019). Besides that, we observed that a particular insectivorous species had a significantly higher concentration of Zn than omnivorous birds. However, food intake is not the primary source of Zn contamination in birds (Philpot et al. 2019) because the transference of this metal through the food chain is modified by homeostatic mechanisms to maintain adequate physiological levels (Gong et al. 2012). The Zn concentration found in this guild (465.61 ± 221.38 μg g −1 ) is higher than in insectivorous passerines in Pakistan (41.58 to 51.04 μg g −1 ) (Abbasi et al. 2015b) and in other insectivorous birds from the same country (75.25 μg g −1 ) (Abbasi et al. 2015a).
The Cu concentration in the insectivore guild was low (9.20 ± 5.99 μg g −1 ), but it was higher than values reported in insectivorous passerines (1.04 to 1.58 μg g −1 ) and other insectivorous birds from Pakistan (2.88 μg g −1 ) (Abbasi et al. 2015a, b). The detection of high Cu concentrations could be related to exogenous contamination (Leonzio et al. 2009). A recent study with samples from the food chain and levels of metals in feathers, muscle, and blood indicate that there is no trophic transference of Cu between terrestrial bird species (Tasneem et al. 2020).
Due to the nature of the analyzed metals, it is not possible to conclude that the significance of the results is related to contamination through the diet. Environmental characteristics (Fritsch et al. 2012) and the interaction of birds with it might influence the food items that will be consumed and consequently influence the availability of metals (Abbasi et al. 2015a;Berglund 2018) because species have distinct foraging characteristics and behaviors and can explore different areas when searching for food (Fritsch et al. 2012;Berglund 2018).
Omnivorous birds can change their diet when exposed to adverse environmental conditions (Willis 1979). In forests, omnivores can forage near the edges, which are favored because of the plant heterogeneity found in these areas (Bispo and Scherer-Neto2010). Besides that, due to their feeding plasticity, omnivorous populations tend to stabilize or grow in fragmented environments (Anjos et al. 2004). Therefore, animals belonging to this guild can adapt better to different environments and explore a wide range of food resources in different strata, which exposes them to a range of contaminants.
In this regard, studies relating the presence of MN and/or NA to the diet of birds are scarce. Souto et al. (2018) tested the hypothesis that insectivorous birds would have more MN in coffee farms, because of the large number of insects in these places. However, the omnivore guild had the highest MN frequency, contrary to their hypothesis and supporting our results. Similarly, Oliveira (2020) observed that, in two different environments (conserved and agricultural), omnivores presented the highest frequencies of MN, and no significant NA differences was found.
The herbivore/granivore guild did not show significant influence on the MN number, but, when associated with the BCI, this guild contributed negatively to the increase in NA in some GLM. Plants have lower concentrations of metals when compared with insects (Gong et al. 2012). Therefore, herbivores/granivores might be less susceptible to contamination through the food chain. The sample size of this guild, however, was not representative in this study.

Influence of body condition
Our results revealed a negative association between Zn and Cu with the increase of the BCI, even though it had a small relevance. The negative association of metals such as selenium (Se) (López-Perea et al. 2019) and mercury (Hg) (Ackerman et al. 2019) in blood and cadmium (Ca) and barium (Ba) in feathers (Innangi et al. 2019) with the body condition is also reported in the literature. Ackerman et al. (2019) suggest two hypotheses to explain these observations. The first considers that metal concentrations might be reduced because they are diluted as body mass increases. The second hypothesis considers the opposite relationship, observing that the highest metal concentrations are found in birds with worse body conditions. The latter supports the statement of Lodenius and Solonen (2013) that malnutrition might be responsible for physiological stress and worse body condition, increasing the metal concentration at the expense of body condition. These discussions support our results, as we observed insectivorous birds (with the lowest BCI) presenting the highest Zn and Cu concentrations.
Regarding genotoxicity, BCI and trophic guilds contributed to increasing the number of NA, according to the GLM and the ANOVA test on model residuals. Our results indicate that omnivorous birds (with higher BCI) have more NA. Frixione and Rodríguez-Estrella (2020), studying a falcon species in an area of agricultural production, did not find a significant relationship between MN and NA frequencies with the body condition index, but smaller birds presented higher frequencies of NA (Frixione and Rodríguez-Estrella 2020). Souto et al. (2018) showed that the size of a bird influenced the number of MN, explaining 95% of MN frequency.
The variation of body condition might be related to the reproductive period, in which birds expend more energy (Kitaysky et al. 1999), but it is directly related to the diet (Brown and Sherry 2006). Birds with specialized feeding habits (insectivores) might be affected by fluctuations in resource availability, so that a generalist diet is favored because it has greater flexibility (Teles et al. 2017). In addition to these factors, the accumulation of heavy metals in tissues of Passer domesticus has been related to changes in morphometric characters (Albayrak and Pekgöz 2021). These authors also observed that Zn, for example, negatively affects the body mass and feather size (in males), influencing the birds' body condition as a consequence.

Influence of age class
The undetermined age class presented a higher concentration of Zn than the adults, but few individuals represented this age class. In this study, Cu concentrations were higher in juveniles than those in adults (9.18 ± 4.26 and 6.31 ± 3.13 μg g −1 , respectively), contrary to the information available in the literature.
Copper is an essential metal that is required in low concentrations in birds (Grúz et al. 2018). Besides that, it has an affinity with keratin, a protein involved in the development of feathers and growth (Baker et al. 2017). Metal accumulation in the feathers of juvenile birds might occur during growth when the nestling receives food from its parents, which might be different from the adult diet (Fritsch et al. 2012;Grúz et al. 2018). Berglund et al. (2011) reported that nestlings of a passerine species presented higher levels of essential elements (cadmium, nickel, and zinc) in their liver compared to adult females in a polluted environment. Fritsch et al. (2012) found higher metal concentrations in juveniles than in adults of a passerine species in a gradient of polluted areas. Among the explanations, the authors highlight the hypothesis of a foraging behavior, in which younger and less experienced individuals would not consume the same food items consumed by adults (Fritsch et al. 2012).
The age class influenced the number of NA in the second-bestGLM and the significance of the ANOVA test based on model residuals. Birds in the undetermined age class and adult birds presented lower number of NA compared to juveniles. Santos et al. (2017) reported that juveniles of white stork (Ciconia ciconia) in the process of rehabilitation presented higher frequencies of NA and MN than adults. In a falcon species, the MN frequency in juveniles was higher than that in adults (Tsarpali et al. 2020). Zúñiga-González et al. (2000) comment that this result might be attributable to the reticuloendothelial system (involved with the removal of old erythrocytes from the blood), which only matures in older birds so that juveniles would not be able to eliminate damaged and old erythrocytes as efficiently as adults.

Conclusion
We defined the field sampling based on previous studies in which many bird species were captured and, during the analysis of biomarkers, some of them revealed the potential to be used as bioindicators of environmental quality. However, we observed that, in our study area, this kind of "random" capture was not effective. This is partially because only a few species had similar sampling sizes in all sampling sites, which did not allow comparisons between individuals of the same species from different sites, making it difficult to evaluate their bioindicator potential. Our samples predominantly consisted of a few individuals from many different species with different interspecific biological and ecological characteristics (behavior, diet, availability of food resources, preferences for distinct foraging areas) and also potential physiological differences (absorption, retention, and excretion of contaminants), producing different responses to the exposure to contaminants.
This study was a pioneer in using wild birds in the SRHB region and, despite the limitations described, we concluded that trophic guilds, age classes, and BCI significantly influenced the accumulation of trace metals and the frequency of MN and NA. However, it was not possible to determine the exact interaction among the biomarkers used to understand the response of the birds to environmental pollution in the study area. Therefore, we reinforce that studies using birds as bioindicators should focus on one or a few species which have well-known specific characteristics, such as foraging area and feeding preferences.
Author contribution JT was responsible for conceptualizing the project, data analysis, acquisition of financial support, methodology (capture of birds, data and biological samples collection, slide analysis, and processing of feathers), and writing the manuscript. GZPR helped with the methodology (MN and NA analysis and feather processing), data analysis, and manuscript writing. DF helped with the methodology (capture of birds), data analysis, and manuscript writing. MSdeS helped with the methodology (capture of birds and collection of biological samples) and revised the language and grammar of the manuscript. JP helped with the methodology (capture of birds and collection of biological samples). JHB did part of data analysis and helped with the methodology (capture of birds and collection of biological samples). JMK helped with the methodology (processing of feathers). MRL helped with the methodology (collection of biological samples). AS helped with the methodology (analysis and detection of metals in the samples). RL helped with the methodology (analysis and detection of metals in the samples). GG helped with the conceptualization of the project, was responsible for the supervision and validation of the project and acquisition of financial support, and helped with manuscript writing.
Funding This work was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brasil (CAPES).

Declarations
Ethics approval All procedures performed in this study were approved by the Ethics Committee on the Use of Animals of the Feevale University (Comitê de Ética no Uso de Animais, CEUA-FEEVALE), project 02.19.075, and by Brazilian environmental agencies (SISBIO authorization 70856-1 and CEMAVE authorization 159/2019).

Consent to participate "Not applicable"
Consent for publication "Not applicable" Competing interests The authors declare no competing interests.