Introduction

Diet and feeding behaviour are primarily important to the ecology, biology and evolution of organisms, as they are essential traits that affect species distribution and population structure (Brown 1984; Cole and Pratchett 2014). In this sense, the feeding behaviour and diet plasticity of a given species are usually shaped by the relationship between species morphology, physiology and the quality and availability of resources in the environment (Brown 1984; Lawton et al. 2012; Cole and Pratchett 2014). This relationship ultimately influences species distribution and density in a given location (Gerking 1994; Lawton et al. 2012). As such, some species may achieve high local abundance and wide geographical distributions by utilizing multiple resources at different sites throughout their ranges (Lawton et al. 2012).

The butterflyfishes (Chaetodontidae) include about 130 reef fish species that live closely associated to the substratum, and most of them consume a variety of benthic prey items, such as anthozoans, polychaetes and crustaceans (Randall 1967; Birkeland and Neudecker 1981; Sazima and Sazima 2001; Pratchett 2005). Butterflyfishes are generally classified into three major guilds according to their diet and feeding selectivity: obligate corallivores, facultative corallivores and non-coral generalist feeders. Most studies on butterflyfish feeding have been focused on Indo-Pacific corallivores, which usually have wide longitudinal and, in some cases, latitudinal distributions on tropical coral reefs (e.g. Hobson 1974; Irons 1989; Tricas 1989; Pratchett 2005; Gregson et al. 2008). Generalist corallivorous butterflyfishes with wide distributions in the Indo-Pacific may change their diet and foraging preferences over large spatial scales, in response to food availability (Berumen et al. 2005; Cole and Pratchett 2014) and intraspecific/interspecific competition (Cox 1994; Pratchett 2005). On the other hand, this variation is less noticeable in highly specialized corallivorous butterflyfishes in the Indo-Pacific, which are more sensitive to differences in the availability of their preferred prey species (Devictor et al. 2010; Cole and Pratchett 2014).

In contrast to corallivorous butterflyfishes, very few studies assessed feeding habits and dietary composition of non-coral feeder species (e.g. Randall 1967; Birkeland and Neudecker 1981; Bonaldo et al. 2005). Non-coral feeders differ from other butterflyfishes in their geographical distribution (Lawton and Pratchett 2012; Cole and Pratchett 2014), as their range is not only associated with coral reef habitats and may include temperate environments (Lawton and Pratchett 2012; Cole and Pratchett 2014). Non-coral feeder butterflyfishes also differ from other butterflyfishes in their morphology, as their gut length/body size ratio is usually intermediate to that of corallivores and planktivores (Berumen et al. 2011). However, little is known on the feeding ecology of non-coral feeder butterflyfishes and how their abundance and feeding habits respond to environmental differences within their distribution.

In the western Atlantic, the banded butterflyfish, Chaetodon striatus, is classified as a non-coral generalist feeder (also known as benthic invertebrate feeder sensu Cole and Pratchett 2014), as it feeds on a wide variety of prey items, with only a small fraction of its diet, if any, represented by scleractinian corals (e.g. Randall 1967; Pitts 1991; Sazima and Sazima 2001; Bonaldo et al. 2005). Chaetodon striatus is the butterflyfish with the widest distribution range in the western Atlantic, which encompasses two biogeographic provinces (Caribbean and Brazil) and a diversity of environmental conditions, such as temperature (17–30 °C), habitat type (e.g. coral and rocky reefs), and food items/availability (Floeter et al. 2001). This diversity of environmental and biotic conditions may ultimately affect the abundance (e.g. via recruitment rates; Pratchett and Berumen 2008), diet, foraging selectivity (e.g. by changes in resource availability) and nutritional condition of C. striatus along its distribution range. However, given the apparent high feeding versatility and generalist habits of this species, it is possible that differences in prey availability do not exert a strong influence on local abundance of C. striatus along its distribution, especially in comparison with highly specialized corallivorous butterflyfishes.

We compared the abundance, diet and foraging rates and selectivity of C. striatus among eight distinct sites, spanning 44° of latitude, testing whether local variation in the availability of prey exerted an important influence on this seemingly generalist species. We particularly investigated whether fish density, foraging rates, foraging selectivity and nutritional condition varied along the studied gradient. We verified key dietary resources of C. striatus by validating in situ feeding observations using dietary analyses. We also assessed C. striatus gut length relative to body size, to verify whether this metric supported the food habit found for this species. As we show below, we found no differences in C. striatus density and foraging rates among sites. Also, our results suggest that C. striatus has high feeding plasticity, as it forages on a wide variety of food items and substrata along the studied sites, without clear differences in nutritional condition. Therefore, the present study reveals how wide-ranging species can be better understood using a plethora of complementary approaches.

Materials and methods

Study sites

The present study was conducted in eight sites distributed along the western Atlantic. These sites included three types of reefs: tropical biogenic reefs (one in Puerto Rico and three in Brazil: Tamandaré, Salvador and Abrolhos), volcanic rocky reefs (Trindade Island) and subtropical rocky reefs (Guarapari, Arraial do Cabo and Florianópolis; all situated in Brazil) (Fig. 1; Table 1). These eight sites were chosen because of their different reef formations and because they encompass a wide latitudinal range along Chaetodon striatus distribution in the western Atlantic. In fact, one of our sites, Florianópolis, is located on the Brazilian State that encloses the southernmost distribution limit of the species (Anderson et al. 2015).

Fig. 1
figure 1

Study sites along Chaetodon striatus distribution range (left); Barplots represent the feeding index based on stomach contents analysis of the most consumed items: Cnidarians and Polychaetes

Full size image
Table 1 Chaetodon striatus body size (cm, mean ± SE) and information on the study sites: temperature range (minimum and maximum mean temperature between 2003 and 2013; Selig et al. 2010), mean dive temperature (our data), geographic coordinates, coral species richness (Scleractinia/Octocorallia), main reef formation and cover, and the number of observed fishes in each site, number of transects and number of photographs analysed for each site
Full size table

Fieldwork was conducted between January 2010 and March 2012 on SCUBA. Underwater observations were done during daytime, between 9:00 and 16:00 h, in a total of 140 h of sampling, in depths ranging 2–16 m, which correspond to the range where rocky reefs were found at the study sites in Brazil. In Puerto Rico, however, the studied reefs were 18–22 m deep because we found no C. striatus individuals in shallow reefs. In each site, we sampled at least two different locations. We also compiled the yearly mean and minimum average water temperature for each site between 2003 and 2013 (Table 1; Selig et al. 2010). Sampling in Brazil was done during the austral summer and in Puerto Rico during boreal winter. Although data collection in Puerto Rico occurred during winter, water temperature was similarly warm across all study sites (Table 1).

Fish density

The density of C. striatus was assessed with a minimum of 30 belt transects per site (20 m long × 2 m wide = 40 m2; details in Floeter et al. 2007), except for Puerto Rico, where data were obtained from online published sources (data collected in 100 m2 belt transects at La Parguera; NOAA 2014). Samples of 13 additional sites along its distribution range were included for comparison (using the same transect size; 40 m2).

Foraging behaviour and benthic cover

We quantified the foraging behaviour of C. striatus by following haphazardly chosen individuals for 3-min periods (following Pratchett 2005; Cole and Pratchett 2011; Lawton and Pratchett 2012; Lawton et al. 2012). During each period, the observer counted the number of bites taken on each substratum type (see details below), keeping a distance of 1–3 m from the fish (Birkeland and Neudecker 1981). We observed a minimum of 49 individuals per site (Table 1) and, to minimize the risk of resampling the same fish individual, observers swam through the sampling site to search for individuals further away (following Birkeland and Neudecker 1981). Before each count, the observer waited a few minutes to minimize observer’s effect on individual behaviour (Birkeland and Neudecker 1981). Only adult individuals were followed (total length generally >10 cm) to reduce variance attributable to ontogeny.

We used photoquadrats to estimate the relative abundance of each substratum type in each study site. Five photographs (covering an area of 40 cm × 60 cm; Krajewski and Floeter 2011) were taken in an area of approximately 2 m × 2.5 m (5 m2) around the place where the last bite was taken by the observed individual (i.e. at the end of each 3-min observation period). However, because of logistical problems, we were not able to take photographs of all sampled individuals, but of about 60–98 % of them at each study site. Photographs were analysed with the software Coral Point Count with Excel Extension (CPCe v3.5—Kohler and Gill 2006), in which 20 points were randomly placed on each photograph. The benthic component immediately under each point was identified and placed into 11 categories, including six algae-dominated types (epilithic algal matrix, crustose, foliose, leathery, corticated and articulated calcareous), three Anthozoa (Octocorallia, Zoantharia and Scleractinia) and two others (Porifera and sand). Non-representative substratum types (<5 %) were excluded for RSF analyses (see “Materials and methods” section below). We analysed 154–491 photographs for each study site (Table 1).

Diet and relative gut length

For the analyses of diet, C. striatus adult individuals were collected with hand spear and had their stomach contents immediately stored in tubes with formaldehyde. We collected 17–30 fish individuals at each sampling site (total = 169 individuals). For each collected individual, we also assessed the relative gut length, by measuring the total length (TL) of each fish individual and the full non-stretched gut length, from the pyloric duct to the rectum. This measure can provide important information regarding the main type of diet in chaetodontids (Berumen et al. 2011).

The food items of each stomach were identified under a stereomicroscope to the most precise taxonomic category possible. The volume of each item was measured using a Petri dish, with a graph paper (each cell comprising 1 mm2 of area) attached to the opposite side of the dish to serve as a counting grid (Hellawell and Abel 1970; Albrecht and Caramaschi 2003). Each food item was placed on the Petri dish and compressed to 1 mm of height with a histological glass. This limit was set with the help of two small glass slides 1 mm thick adjacent to the food item. The volume (mm3) of each item was measured by counting the number of grid cells occupied by the item. The relative importance of each item in the diet of a given individual was analysed through the feeding index (IAi), which combines frequency of occurrence and volume of each item (following Kawakami and Vazzoler 1980; Lima et al. 2012).

Masses of organic material that seemed unidentifiable were analysed under a microscope to search for clue elements, such as spicules and nematocysts. Contents were classified as “digested organic matter” when these elements were found mixed within organic matter. If nematocysts were recorded in high abundance within the organic matter, the item was placed into Cnidaria Hexacorallia Actiniaria or Cnidaria Hexacorallia Zoantharia category, according to the type of nematocyst found. As it was not possible to distinguish the nematocysts from Cnidaria Hexacorallia Corallimorpharia and Scleractinia, items with these nematocysts were thus classified as Cnidaria Hexacorallia Corallim/Scle. When nematocysts belonging to multiple orders were present, items were classified as Cnidaria Hexacorallia “other”. When no identifiable elements were found, the material was classified as unidentifiable. Marine invertebrate taxonomists were consulted to confirm or identify dubious items.

Nutritional condition

Nutritional condition, which may be considered as a fitness measure, can be quantified through RNA:DNA ratio analyses (Behrens and Lafferty 2007). This index has been broadly employed as a fitness measure, since RNA protein synthesis varies with metabolic demand, i.e. fluctuates in response to food availability (quality), while DNA content per cell is fixed (Chícharo and Chícharo 2008). To determine RNA/DNA ratios, samples containing C. striatus white muscle from Puerto Rico, Salvador, Guarapari and Florianópolis (n = 20, 19, 19 and 20, respectively) were immediately stored in RNALater solution (Qiagen) after sampling and kept in a −20 °C freezer. Samples were thawed, and RNA and DNA concentrations of each sample were first assessed using ethidium bromide fluorescence (Dahlhoff and Menge 1996). We then weighted samples to 100 mg and homogenized them in replicates with 10 volumes of 2 mol NaCl. Samples were centrifuged for 1 min, and 5 µL of each sample was transferred into a microplate by adding 0.14 µL of solution containing 0.005 mg ethidium bromide and 0.15 mg proteinase K at 37 °C for 60 min. Following this initial incubation, we added 100 µL of buffer (80 mm Tris–HCl, pH 8.0 at 20 °C) and measured fluorescence at 365-nm excitation and 590-nm emission using a SpectraMax M5 spectrofluorometer. We assessed fluorescence attributable to RNA and DNA by sequential digestion of each nucleic acid using first 5 µL RNAse I (SIGMA), followed by 60-min incubation and then 5 µL DNAse I (SIGMA) and then by 30-min incubation. Finally, we estimated RNA and DNA concentrations based on standard curves of fluorescence, in which quantities of these nucleic acids are known.

Data analysis

Density data (i.e. discrete counts) are, by definition, better characterized by distributions such as Poisson and negative binomial. Therefore, an analysis of variance among multiple sites could be performed with generalized linear models (GLMs) assuming, for example, a Poisson distribution for the model error (Zuur et al. 2009). However, our density data presented a significant inflation of zeros (i.e. transects where no individuals were recorded), such that a GLM presented substantial overdispersion regardless of the choice of error distribution, hence hindering model interpretation. Therefore, to reduce the zero inflation, we adopted a bootstrap approach that entails the following three steps: (1) at each iteration (n = 10,000), for each site, 15 larger transects were drawn by pooling smaller original transects at random (with replacement) until a total area of 200 m2 was achieved (i.e. 5 × 40 m2 or 2 × 100 m2); (2) at each iteration, a Bayesian Poisson GLM (using a log link; see Electronic Supplementary Material for details) was then fitted to estimate the average density/200 m2 for each site; (3) these estimates of model averages (1002 MCMC steps per model fitting) were stored at each iteration to obtain a joint posterior distribution of random averages estimated from all the GLMs (total of 1000 iterations × 1002 MCMC steps per iteration = 1,002,000 estimates). Statistical significance between sites was assessed by the overlap (or lack thereof) between the 95 % confidence intervals of joint posterior distributions for average density/200 m2.

Foraging rates among sites were compared using a GLM assuming a negative binomial distribution for the model error. An earlier model exploration indicated that the model was better fitted with a negative binomial distribution rather than Poisson (particularly, the gamma shape parameter θ ≈ 1).

Resource selection function (RSF) was used to evaluate foraging substratum selectivity, i.e. selection for preferred benthic substrata, at each of the seven study sites (Trindade was not included in this analysis, due to lack of data; see Table 1). Because our data consisted of direct observations of foraging substratum in which different individuals forage on (bitten substratum scored as 1), within a variety of available substrata (1000 random samples of unbitten substrata following observed availability proportion scored as 0), we applied a RSF using the logistic regression approach proposed by Manly (1993). The following log-linear form of the logistic regression represented our model:

$$\ln w = \beta_{1} \times {\text{Food}} + \beta_{2} \times {\text{Site}} + \beta_{3} \times {\text{Food}} \times {\text{Site}} + \varepsilon ,$$

where w depicts the selection strength based on the use/availability ratio, β 1–3 represent model coefficients that indicate the effects of each variable, and ɛ is the model error. Sites and food (=foraging substratum) were entered as categorical variables in the model. The significance of each parameter was assessed using type-III analysis of variance through partial likelihood ratio tests (Cox and Oakes 1984). We then refitted the significant model with observations of each fish individual being clustered to avoid pseudoreplication, which allowed estimating robust standard errors. RSF was conducted using the survival package version 2.8 (Therneau 2015) in R Software version 3.2.1 (R Core Team 2015).

One-way ANOVA was used to compare nutritional condition of C. striatus (measured as the natural logarithm of RNA/DNA) among sites. Tukey HSD was used to investigate pairwise differences among sites. Data met the assumptions for normality of residuals and homogeneity of variances for parametric tests (Underwood 1997; Zar 1999).

Data manipulation, statistical analyses and figures were coded in the R Software version 3.2.1 (R Core Team 2015) and can be fully reproduced assessing a free repository on GitHub (https://github.com/dbarneche/chaStri).

Results

Overall, density of C. striatus was not significantly different among most sites. However, density in Guarapari was significantly higher than in Puerto Rico (i.e. the 95 % confidence intervals from the posterior distributions do not overlap; Fig. 2a). Additional density data from other 13 sites support that C. striatus density in the Caribbean is generally lower than in the Brazilian coast (Fig. 2b).

Fig. 2
figure 2

a Average density of individuals in seven study sites and b density in additional sites along the distributional range of C. striatus. In (a), the curves represent the posterior density distribution of parameters (average densities of individuals in each site) summed across all MCMC chains (n = 1,002,000) as estimated using Bayesian methods in JAGS. In (b), circles represent the number of individuals per m2

Full size image

Mean foraging rates of C. striatus differed among some sites, without a clear trend (Table 2; Fig. 3). Chaetodon striatus showed preferences for some substratum types over others [substratum effect (β 1): L.R. χ 2 = 161.08, df = 10, p < 0.0001], but patterns of substratum selection and rejection were not consistent across sites [site effect (β 2): L.R. χ 2 = 706.57, df = 6, p < 0.0001; Fig. 4]. Foraging substrata selected in some sites were avoided or used according to their availability in other sites [interaction term effect site–substratum (β 3): LR χ 2 = 1896.27, df = 60, p < 0.0001]. No substrata were totally preferred or rejected across the seven sites, and C. striatus selected all substrata considered in at least one study site (Fig. 4). Articulated calcareous algae, for example, were positively selected in four out of seven study sites. In fact, in Florianópolis, this item was not recorded on the photographs (Fig. S1 in Electronic Supplementary Material). Anthozoa Octocorallia was selected in two study sites in Brazil. Moreover, in tropical sites in Brazil, such as Abrolhos and Tamandaré, C. striatus selected Anthozoa Scleractinia, differently from what was found in Puerto Rico, where hard coral was neither selected nor rejected. Epilithic algae matrix was slightly to substantially preferred in five out of seven sites (Fig. 4).

Table 2 Average deviations in foraging rates (bites/3 min−1) among sites
Full size table
Fig. 3
figure 3

Foraging rates (3 min−1) of C. striatus at each studied site. Blue circles represent the average foraging rates as estimated by the negative binomial GLM, and interval bars (too small to be seen) represent model estimated average 95 % CI

Full size image
Fig. 4
figure 4

Strength selection estimation for different food items consumed by C. striatus in each of the eight study sites. Food items with values crossing dashed lines were used according to their availability (use/availability = 1). Food items strength selection values above 1 were selected (use > availability), while values below 1 indicate avoidance (use < availability). Food acronyms are as follows: ALGAE: EAM epilithic algal matrix, MCRU, crustose; MFOL, foliose; MCOR, leathery; MCT, corticated; MCA, articulated calcareous; CORALS: Anthozoans: ANT OCT, Octocorallia; ANT ZOA, Zoantharia; ANT SCL, Scleractinia; OTHERS: POR, Porifera; SAND, Sand. Numbers depict data points above the maximum y axis value (i.e. 6)

Full size image

Cnidaria and Polychaeta composed most of C. striatus diet in all sites (Table 3; Fig. 1). The number of items in all individuals combined per site ranged from 12 to 23 (the lowest diversity of items in Salvador and Tamandaré, the highest in Puerto Rico). Mollusca and/or Crustacean eggs were found in stomach contents in all sites, but in different proportions (Table 3). In terms of feeding index (IAi), sessile Polychaeta (mainly Sabellidae and Serpulidae) and Cnidaria Hexacorallia (0–58.2 and 2.8–94 %, respectively) were the dominant diet items across all sites, representing 4.5–94 % of the feeding index per site when combined (Table 3). Octocorallia was only found in stomach contents from Trindade (10 % frequency of occurrence—FO) and Puerto Rico (6.7 % FO), in both cases with IAi < 0.1 %.

Table 3 Frequency of occurrence (%, FO), volume (%, V) in the diet and feeding index (%, IAi) of dietary items (“other” counting as one item) of Chaetodon striatus from populations in the eight study sites along the western Atlantic
Full size table

Stomach length varied between 37.5 and 106 cm, with gut length relative to total length ranging 2.9–7.3 (mean 4.6 ± 0.26 SE; Fig. 5). Chaetodon striatus RNA/DNA ratio was similar among Puerto Rico, Guarapari and Florianópolis, but lower in Salvador (ANOVA: p < 0.01; Fig. 6).

Fig. 5
figure 5

Relative gut length of C. striatus in comparison with other butterflyfishes, grouped by feeding preferences (mean ± 95 % CI). Information displayed by white bars was extracted from Berumen et al. (2011)

Full size image
Fig. 6
figure 6

RNA/DNA ratio (mean ± 95 % CI) for C. striatus individuals four study sites along the Brazilian coast. A total of 19–20 individuals were analysed per study site

Full size image

Discussion

This study found that the abundance of C. striatus was not significantly different among most studied sites in Brazil, despite spanning 27° of latitude, and marked differences in local habitat structure, benthic composition and environmental conditions. However, densities in the Caribbean were generally lower than in Brazil. Our study shows that C. striatus is versatile and generalist, without strong patterns of selectivity of diet items and foraging substrata across sites. This fact, along with the similar density and nutritional condition of C. striatus within the studied range, indicates that the different reef formations and environmental conditions in the western Atlantic do not represent a major challenge to the maintenance of populations of this species in this area. Indeed, the high feeding plasticity of C. striatus is probably one of the factors explaining the species occurrence in so many markedly different reef ecosystems.

Despite the marked similar abundance and feeding versatility of C. striatus on reefs in the western Atlantic, its distribution terminates abruptly at 27°S in southern Brazil (Floeter et al. 2001; Ferreira et al. 2004; Anderson et al. 2015), the southernmost distribution limit for myriad tropical reef fishes within the Brazilian Province. In this area, there is an almost complete absence of suitable reef habitats, and temperatures stay below 17 °C for extended periods in winter, which constrain the occurrence of tropical reef species (Floeter et al. 2001; Ferreira et al. 2004; Anderson et al. 2015). As a consequence, even versatile species such as C. striatus may have their establishment and survivorship challenged by extreme environmental conditions.

Our diet analyses corroborated the classification of C. striatus as non-coral generalist feeder, as it ingested a large variety of benthic items. Polychaetes and cnidarians were the groups consumed in higher quantity in all study sites, as observed in a previous study in the Caribbean, in which polychaetes and anthozoans represented, respectively, 58.7 and 32.5 % of C. striatus stomach contents (Randall 1967). Similarly, a study in shallow reefs in Brazil found that C. striatus feeds mostly on cnidarians (Bonaldo et al. 2005). Polychaetes are an abundant food resource on reefs, with species associated with algae, sand, corals and sponges (Paiva 2006). This fact probably explains why, in the present study, C. striatus foraged mostly in substrata like algal patches and sand, where these invertebrates may occur in high abundances (Paiva 2006). Also, the great contribution of anthozoans in C. striatus diet was supported by field observations of foraging behaviour, as a high proportion of bites were taken in at least one anthozoan category in almost all sites.

The use of complementary diet and foraging behaviour data allowed us to have a broader view of C. striatus feeding patterns. In Arraial do Cabo and Abrolhos, for example, C. striatus frequently bit on octocorals, which were completely absent in stomach contents in these sites. Polyp sclerites of Phyllogorgia dilatata and Plexaurella spp, the main octocorals in Arraial do Cabo and Abrolhos, are usually fragile or absent (Castro et al. 2010; Medeiros personal communication), what probably explains their absence in stomach contents in these sites. In contrast, stomach contents in Florianópolis had high quantities of anthozoans (75.1 % IAi), which were not recorded as a foraging substratum in this site. Indeed, most bites were taken on algal-dominated substrata (Fig. 4 and Fig. S1 in Electronic Supplementary Material) in Florianópolis, where fish probably search for cryptic anthozoans, such as small anemones. These cases exemplify the importance of combining field observations and stomach content analyses for a better comprehension of the feeding ecology of a species.

Our study revealed a high diversity of food items in C. striatus diet, some with high frequency of occurrence but low volume, which resulted in low feeding index values. Some of these items probably represent important complementary resources, with high energetic value (Fyhn and Govoni 1995; Nagelkerken et al. 2009). This is the case for crustaceans, present in stomach contents from almost all sampling sites, but with low feeding index (<0.5 %), as well as egg mass, also with high frequency but with low volume (except at Tamandaré, which presented a feeding index of 77.7 %).

Some food items of low nutritional value, such as sand and calcareous skeleton, were probably ingested incidentally with invertebrates. Algal ingestion by C. striatus must also be incidental, since the frequency of this item in the diet of butterflyfish species feeding on algae is usually higher than the values recorded in the present study (e.g. Sano 1989).

The variation in gut length of C. striatus among individuals of similar total body length in the presented study (up to 30 cm) is expected, as gut morphology can vary among conspecific individuals (Raubenheimer and Bassil 2007). Also, Berumen et al. (2011) compared the gut length, relative to total body length, of 28 species of butterflyfishes, including obligate coral feeders, facultative coral feeders, generalists, non-coral feeders and planktivores. Our results of relative gut length in C. striatus fit within the subset of generalists and non-coral feeders (4–5 of relative gut length, Fig. 5), as proposed by the gut content analyses in the present study.

The similarities of RNA/DNA ratio indicates that most C. striatus populations sampled in the present study have similar nutritional condition. Although we did not analyse tissue samples for all study sites, our geographically extreme sites (Puerto Rico and Florianópolis) were included. In fact, nutritional condition was similar even considering Florianópolis, the southernmost limit of distribution of the studied species, where environmental conditions can be adverse for many tropical reef fish species. Also, although individuals from Salvador showed a lower RNA/DNA ratio, this value was higher than 1, considered as the indicative boundary of physiological stress, such as starvation (Kono et al. 2003; Behrens and Lafferty 2007). These relatively low values from Salvador may be explained by the higher contribution of cnidarians in C. striatus stomach contents (94 % IAi), in the bite rates (62.8 %), as well as in the benthic cover of this site (49.5 %) (Fig. S1 in Electronic Supplementary Material). Cnidarians provide relatively less energetic value and nutritional quality, probably because of chemical and structural defences (Birkeland and Neudecker 1981; Fox and Morrow 1981; Suchanek and Green 1981). Therefore, the relatively higher consumption of cnidarians by C. striatus in Salvador is a likely driver of lower RNA/DNA in this site.

Our results support the usual trophic classification of C. striatus as “sessile invertebrate feeder” (Ferreira et al. 2004), feeding on a wide variety of prey items (e.g. Randall 1967; Pitts 1991; Bonaldo et al. 2005), as in our study sessile invertebrates presented the highest feeding index (83 %) among all food items. Further, mobile invertebrates represented a substantial part of C. striatus diet (14 %) in our sites, which indicates that the species diet is more versatile than previously assumed. This fact is particularly relevant as polychaetes and crustaceans generally have higher caloric value (639 and 817 cal/g wet wt, Cummins and Wuycheck 1971) than anthozoans (494 cal/g, wet wt Cummins and Wuycheck 1971). Therefore, the mobile invertebrates may have a higher contribution in providing energy and nutrients to C. striatus than previously assumed. In terms of feeding behaviour, C. striatus could be considered as a generalist zoobenthivore that forages on multiple substrata in tropical and subtropical reefs. This strategy seems successful along a wide variety of reef environments, temperature range and resource availability in which C. striatus occurs, as indicated by the absence of major differences in density and foraging rates across the studied reefs.

In summary, our study assessed different aspects related to C. striatus feeding, by using a combination of tools to identify potential drivers of the density and distribution of a wide-ranging reef fish species. In assessing different variables related to C. striatus feeding, we obtained a broad understanding of its feeding ecology, specifically by comparing data obtained from in situ observations (abundance, feeding rates, substratum selection) with laboratory analyses (diet composition, gut length relative to body size, nutritional condition). Our results show that C. striatus is evenly distributed along its range, with no major differences in foraging rates across sites encompassing a 44° latitudinal range. Chaetodon striatus also exhibits high feeding plasticity, with use of different diet items and foraging substrata throughout its distribution. This feeding plasticity was not related to major differences in nutritional condition across sites. This uniformity in C. striatus feeding is striking, especially considering the high differences in reef structure (tropical coral reef, temperate rocky reefs), benthic cover and fish community (Ferreira et al. 2004; Floeter et al. 2001, 2004) along the studied gradient. Therefore, the feeding versatility and plasticity of C. striatus seem to explain its wide latitudinal distribution, which encompasses two biogeographic provinces and a wide range of environmental conditions (Floeter et al. 2001). Our results thus highlight the importance of assessing a large geographical gradient within the distribution range of generalist species to better comprehend their feeding ecology.