Contrasting Distribution and Foraging Patterns of Herbivorous and Detritivorous Fshes Across Multiple Habitats in a Tropical Seascape

Marine Biology (2019) 166:51 https://doi.org/10.1007/s00227-019-3498-0

ORIGINAL PAPER

Contrasting distribution and foraging patterns of herbivorous and detritivorous fshes across multiple habitats in a tropical seascape

M. Eggertsen1 · D. H. Chacin2 · C. Åkerlund1 · C. Halling1 · C. Berkström1,3

Received: 21 September 2018 / Accepted: 8 March 2019 / Published online: 16 March 2019 © The Author(s) 2019

Abstract Understanding drivers behind patterns of functionally important groups of fshes is crucial for successful management and conservation of tropical seascapes. Herbivorous fshes are the most prominent consumers of marine primary production which can have profound efects on reef resilience. We explored environmental variables afecting distribution and foraging patterns of herbivorous and detritivorous fsh assemblages (siganids, acanthurids and parrotfsh) across distinct shallow-water habitats (coral reefs, macroalgae beds and seagrass meadows) during September–November 2016 at Mafa Island, Tanzania (8°00′S, 39°41′E). We performed underwater visual census to quantify fsh assemblages, measured habitat features, deployed macroalgal assays and conducted inventories of grazing scars. Multi-dimensional scaling and mixed-efects linear models were used to evaluate diferences in fsh assemblages and environmental variables infuencing abundance and foraging patterns of fshes. Fish communities of focal functional groups difered among habitats. Abundance of herbivores and detritivores as well as relative browsing and scraping was highest on coral reefs compared to macroalgae and seagrass meadows. Adult fsh were more abundant on coral reefs while juveniles were abundant in macroalgal beds. Coral cover and crustose coralline algal cover had a positive efect on the abundance of fsh in coral reef areas, while macroalgal cover had a negative efect. Contrastingly, in macroalgae habitats, macroalgal cover had a positive efect on the abundance of parrotfsh. These results highlight the importance of considering connectivity between macroalgal beds and coral reefs through ontogenetic shifts in habitat use by primarily microphagous parrotfsh and of incorporating a range of habitats within coastal management plans.

Introduction

Disentangling which habitat characteristics are critical in shaping abundance, distribution, and ecological processes within the available range of coastal habitats will improve our understanding of marine community patterns and con- Responsible Editor: K.D. Clements. nectivity in shallow coastal seascapes. Benthic habitats provide marine organisms with food and shelter from abiotic or Reviewed by Undisclosed experts. biotic stressors, or a combination of these (Friedlander and Electronic supplementary material The online version of this Parrish 1998), which can further infuence competition and article (https://doi.org/10.1007/s00227-019-3498-0) contains predation risk (Almany 2004). supplementary material, which is available to authorized users. In tropical reef environments, spatial heterogeneity is a strong driver of distribution and diversity patterns of reef * M. Eggertsen [email protected] fsh (Chabanet et al. 1997; Sabater and Tofaeono 2007; Messmer et al. 2011; Samoilys et al. 2018), where char- 1 Department of Ecology, Environment and Plant Sciences, acteristics such as structural complexity and rugosity are Stockholm University, 10691 Stockholm, Sweden important predictors of fsh assemblage structure and abun- 2 College of Marine Sciences, University of South Florida, dance (Bell and Galzin 1984; Gratwicke and Speight 2005; St. Petersburg, FL 33701, USA Graham and Nash 2013). In submerged macrophyte habitats, 3 Department of Aquatic Resources, Institute of Coastal canopy height and cover have been shown to structure fsh Research, Swedish University of Agricultural Sciences, assemblages in both tropical seagrass meadows (Gullström 74242 Öregrund, Sweden

Vol.:(0123456789)1 3 51 Page 2 of 16 Marine Biology (2019) 166:51 et al. 2008; Alonso Aller et al. 2014) and macroalgal beds et al. 2017; Fulton et al. 2019), highlighting the importance (Wenger et al. 2018; van Lier et al. 2018). However, envi- of investigating habitat-specifc ecological functions and ronmental factors as such may impact coral fsh communities linkages to other habitats. on multiple spatial and temporal scales as some fsh spe- A prevailing perspective is that nominally herbivorous cies might have shifting habitat preferences during diferent fshes are driving benthic structure and habitat diferentia- ontogenetic stages and hence utilize alternative habitats like tion through strong top–down control (Mumby 2006; Jack- seagrass meadows, mangroves and/or macroalgal beds dur- son et al. 2014; Bonaldo et al. 2014; Adam et al. 2015). As ing their juvenile life stage (Nagelkerken et al. 2000; Wilson a large part of the studies that propose top–down control et al. 2010; Berkström et al. 2012). For example, trade-ofs on the benthos by herbivorous and detritivorous fshes are between foraging success and predation risk depending on performed in the Caribbean, similar mechanisms might or body size have been shown to explain habitat choice of juve- might not be applicable to the same extent in other geograph- nile groupers (Dahlgren and Eggleston 2000). Microhabitat ical locations (Rof and Mumby 2012). Instead, bottom-up preferences might therefore not be consistent across habitats, efects such as benthic characteristics might be more impor- and environmental predictors might change depending on tant in other places, considering the strong efects benthos habitat identity. can have on reef fsh communities as a whole (Friedlander Certain functional groups of reef fsh have been identifed and Parrish 1998; Friedlander et al. 2003; Messmer et al. as having a major role in maintaining reef resilience and 2011). Long-term studies from the Philippines have shown reef health such as nominally herbivorous and detritivorous strong bottom–up efects on distribution and abundances of fshes (Bellwood et al. 2004; Mumby 2006; Hughes et al. detritivorous fsh (Russ et al. 2018) and parrotfsh assem- 2007; Goatley and Bellwood 2010). The former group can blages (Russ et al. 2015), and similar patterns have been be further classifed into three groups: algivores (i.e., fsh observed in the Pacifc (Tootell and Steele 2016) and the that target eukaryotic macroalgae and turfng algae), sea- Indian Ocean (Samoilys et al. 2018). Due to the inconsisten- grass-feeders, and microphages (fsh feeding on microscopic cies of responses observed, which might be system-specifc, phototrophs that can be both epilithic and endolithic) (Choat further studies are needed. et al. 2002; Clements et al. 2017; Clements and Choat 2018). In the Western Indian Ocean (WIO) region, fshing has Drivers predicting and infuencing abundance, distribution been identifed as the strongest factor infuencing coral reef and feeding patterns of these groups are considered impera- fsh abundance, although benthic variables also had some tive within the management of tropical shallow seascapes. efects (McClanahan and Arthur 2001), indicating a mix of Through feeding activities, these groups are acknowledged top–down and bottom–up factors. The majority of herbivore- to be important and infuential forces in shaping and struc- macroalgae-coral studies have been performed in Kenya turing ecosystems through top–down control, especially by (see, e.g., McClanahan et al. 1999, 2001; McClanahan and balancing algal and coral communities in favour of corals. Arthur 2001), where top–down control in the form of her- Although distribution patterns of herbivorous fsh and bivory has been identifed as an important predictor for mac- herbivory have been studied extensively in coral reef habi- roalgae abundance on coral reefs (McClanahan et al. 2001; tats (see, e.g., Hay 1981; Bellwood et al. 2014; Adam et al. Mörk et al. 2009). Likewise, a study in seagrass meadows 2015; Russ et al. 2015; Steneck et al. 2017), fsh herbivory from Zanzibar has shown that both top–down (fshing) and can also have consequences in other habitats. In seagrass bottom–up (seagrass density) control explained fsh assem- systems, removal of epiphytes through grazing is hypoth- blage structure (Alonso Aller et al. 2014). However, patterns esized to enhance seagrass production by decreasing com- as such might vary across the WIO region, in diferent habi- petition for light (van Montfrans et al. 1984), and seagrass tat types and with diferent fshing pressure. browsing species have a major role in trophodynamics as The present study therefore sets out to explore distribu- they incorporate carbon and nutrients in the food chain tion and foraging patterns of herbivorous and detritivorous (Unsworth et al. 2007). In temperate macroalgal habitats, fshes across multiple habitats within a shallow tropical sea- spatial patterns of algal distribution have been shown to be scape in a marine protected area (MPA) in Tanzania. Addi- structured by top–down control induced by fsh (Vergés et al. tionally, the extent these patterns are driven by benthic char- 2009; Taylor and Schiel 2010). However, foraging patterns acteristics (bottom–up controlled) is studied. In doing so, of nominally herbivorous fsh in naturally occurring tropical we also identify habitat variables which might be important macroalgal beds have been largely understudied (but see Lim in structuring juvenile communities in nursery/recruitment et al. 2016). Canopy-forming tropical macroalgal beds can habitats. This is done by (1) quantifying detritivorous and harbour large numbers of herbivores and have only recently functional groups of herbivorous fsh assemblages in distinct been acknowledged as important nursery grounds for coral and common shallow-water habitats (coral reefs, macroalgal reef fshes, including juvenile acanthurids, parrotfsh and beds and seagrass meadows), (2) identifying environmental rabbitfsh (Evans et al. 2014; Tano et al. 2017; Eggertsen variables structuring these fsh assemblages and foraging

1 3 Marine Biology (2019) 166:51 Page 3 of 16 51 patterns within the seascape and (3) quantifying browsing fshing methods and coral mining practices are forbidden and scraping of algae in these habitats. We hypothesized that (Berkström et al. 2013; Gaspare et al. 2015). the observed fsh assemblages (abundances and species com- The archipelagic environment is infuenced by the East position) and foraging patterns would difer across habitats African Coastal Current (EACC), flowing northwards on a broad spatial scale and will be related to diferences in along the East African coast, and the northeast and south- habitat characteristics, resource availability, and predatory east monsoon winds with one drier and sunnier period assemblages at fne spatial scales (1–25 m). (October–March) and one rainier and more cloudy period (March–October) (Berkström et al. 2013). Tides are semi- diurnal with a mean amplitude of 3.3 m and causing strong Methods and complex currents with velocities reaching up to 6 knots (Horrill et al. 1996). The eastern coastline of the Mafa Description of study area Island is exposed to the open Indian Ocean, but protected by fringing reefs towards the southern part of the archipel- The present study was conducted within the boundaries of ago (Garpe and Öhman 2003; Gaspare et al. 2015). A large the Mafa Island Marine Park (MIMP), in Mafa Island, Tan- and relatively shallow bay (< 15 m deep), fringed by man- zania (8°00′S, 39°41′E) (Fig. 1). The Mafa Island area is grove forests is located on the eastern side of the main island composed of a small archipelago located 20 km from the (Chole Bay), and shallow areas are also located around and Tanzanian mainland and 120 km south of Unguja Island towards the islands of Jibondo, Juani and Chole (Berkström (Zanzibar) and has a high degree of marine biodiversity et al. 2013). Shallow areas are characterized by a mosaic of (Horrill et al. 1996; McClanahan et al. 2008). The MIMP macroalgae-dominated areas, sand fats, seagrass meadows was established in 1995 and is located on the southeastern and coral patch reefs (Berkström et al. 2013). part of the main island, covering a total area of 822 km2, of which 75% is below the high water mark (Gaspare et al. 2015). The protected area is a multi-use park, divided into Field study zones subjected to diferent degrees of protection, from allowance of subsistence/artisanal fshing in some areas to The feld survey was conducted during September–Novem- complete closure in other areas. However, all destructive ber, 2016. The study coincided with the cooler season in

Fig. 1 Small squares indicate where Mafa Island is located on the East African coast and large image the Southeastern side of Mafa Island where the study was conducted. Study sites are indicated with black symbols, and the Mafa Island Marine Park (MIMP) border with a black line. Tc, Thalassodendron ciliatum (Map modifed from Google Earth and MIMP)

1 3 51 Page 4 of 16 Marine Biology (2019) 166:51 coastal Tanzania, with mean sea surface temperatures scale, where 1 denoted no rugosity (fat) and 5 the highest, a of ~ 26 °C (McClanahan et al. 2007). method suggested by Gratwicke and Speight (2005). A total of 3 diferent habitats types were surveyed at 9 Depth was measured for each transect with a dive com- sites scattered throughout the shallow seascape (< 4 m of puter (Suunto Vyper Novo) and each transect was georefer- depth) (Fig. 1). Seagrass meadows were monospecifc and enced by marking start and end point with a GPS kept at the consisted mainly of Thalassodendron ciliatum and mac- surface and placed inside a waterproof bag. For all variables roalgal areas were dominated by the canopy-forming brown measured, a mean value per transect was calculated. algae Sargassum aquifolium and Turbinaria conoides. While seagrass densities and cover can fuctuate with season (Rob- Browser assays bins and Bell 2000), they generally do not undergo such dramatic changes as some Sargassum spp. (Fulton et al. For estimating relative browsing pressure in diferent habi- 2014). Many Sargassum species from the southern Western tats, standardized browsing assays were used. Even though Indian Ocean have slower growth rates during this time of browsing assays only provide a relative estimation of the the year, with cover and biomass in algal patches becom- surrounding grazing pressure, it has been widely used within ing less dense (Gillespie and Critchley 1999a). There is an ecological studies for quantifying grazing pressure across increase in biomass and cover during the warmer season areas and for identifying important browsing species (Fox (December–March) (Gillespie and Critchley 1999b). Coral and Bellwood 2008a, b; Ganesan et al. 2006). However, reef sites were comprised of a heterogenous mosaic of scle- results have to be interpreted with care, as there is a pro- ractinian corals. Habitat types were chosen on the premises found risk that opportunistic fsh might feed on assays out where they were commonly occurring, located at approxi- of curiosity, an efect which will be impossible to disentan- mately the same depths (1–4 m) and present in large and gle from data on biomass loss only (Wulf 2017). To cir- consistent patches (> 100 m2). cumvent this issue to some degree, 6 of the bioassays were documented by remote underwater video cameras (RUVs) Fish and habitat surveys (GoPro Hero Session) for ~ 1 h during each experimental setup (ntotal = 54), to identify which species of herbivores Fish assemblages were surveyed by performing underwater targeted the tethered algae. Assays were constructed by −1 visual census (UVCs), (n ≈ 5 habitat and site , ntotal = 48; tethering thalli of Eucheuma denticulatum and Sargassum ncoral = 15, nmacroalgae = 20, nseagrass = 13) along 25 × 2 m belt aquifolium to PVC pipes and placing them in three diferent transects by snorkeling. All fshes were identifed to lowest habitat types (Thalassodendron ciliatum-dominated seagrass taxonomical level and total length (TL) was noted to closest meadows, macroalgal beds, and coral reefs) during a full cm, according to the method described in Tano et al. (2017). tidal cycle (~ 24 h). The macroalgal species were chosen All surveys were performed between 09:30 and 16:00 and because they are a common feature of the macroalgal assem- between the low and high tide peak. A snorkeler swam along blages in coastal Tanzania (Tano et al. 2016, 2017), and the transect line ~ 0.1 m s−1, documenting all mobile fsh have been found in relatively large quantities in stomachs of species and then returning along the line examining substrate main herbivorous fshes such as Siganus sutor (Eggertsen and plant/algae cover more thoroughly for small, cryptic spe- et al. unpublished), a common browser in Tanzanian coastal cies. Each snorkeler was equipped with a camera (Canon waters (Lugendo et al. 2007; Kimirei et al. 2011). Powershot G7x Mark II and Canon WP-DC54 underwa- Fronds of E. denticulatum and S. aquifolium were col- ter housing), for later identifcation, if necessary. To avoid lected from the feld and kept in tanks with aerated seawater potential bias of length estimations, trial estimations were over night. Suitable sizes of thalli were chosen (< 5 g), dead/ performed prior to the study until snorkelers were calibrated necrotic tissue and epiphytes were removed, and algae were with each other and any possible bias consistent. All UVCs spun in a salad spinner for 10 s to remove excess water. were performed by the same observers (M. Eggertsen and Thalli were then weighed and put into marked zip lock bags D.H. Chacin). for transportation to the site. Two thalli of each species were Every 5th meter of the transect, a 0.5 × 0.5 m square was tethered to a PVC pipe. Every browsing assay constituted −1 placed and photographed from above, where benthic com- a total of 4 pieces of thallus (nbrowsing assays = 18 habitat , −1 position (percent cover of calcareous rubble, soft substrate, nthallus = 72 habitat , ntotal = 648) (Fig. 2). Care was taken live coral cover, macroalgal cover, seagrass cover, number to place the browsing assays in continuous habitats and at a of macrophyte species, epilithic algal matrix (EAM) cover distance away from habitat edges. and crustose coralline algal (CCA) cover and rugosity) was Fishes removing biomass from the browsing assays were estimated and the height of the 3 tallest macrophytes was identifed from the videos and herbivorous fshes within the measured to the closest cm using a ruler (n = 6 transect−1). video frame that were not feeding were also noted. RUVs Rugosity was visually estimated according to a 1–5 grade have in some cases been shown to reveal more information

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Fig. 2 a Browsing assay and b caged control than UVCs regarding observations of herbivorous species Quadrats of 0.15 × 0.15 m were randomly placed on hard, (Fox and Bellwood 2008a) whereas in some cases results calcareous (dead) surfaces, where all clean grazing scars have been equal (Longo and Floeter 2012). Both methods were counted and measured to the nearest centimeter (n ~ 20 were included in the current study as RUVs have not been habitat type −1) (Fig. 3). Due to lack of suitable substrate for used within the study area before for monitoring herbivores. scrapers to feed on in seagrass habitats, this study was only Browsing assays were retrieved after ~ 24 h, demounted from performed in hard substrate habitats, i.e., coral and mac- the PVC pipes and put in marked zip lock bags for transpor- roalgal habitats. tation to land. Prior to weighing, algae samples were spun in a salad spinner for 10 s to remove excess water. To control Statistical analyses for handling and daily growth rates of tethered macroalgae, a caged control (nthallus = 4) was placed in the experimental Fishes were classifed into the following functional groups; area at each sampling occasion. seagrass and algivores (species feeding on seagrass, eukaryotic macroalgae, and turfng algae), detritivores, micro- Grazing scar inventories phages (species feeding on endo- and epilithic microscopic phototrophs) and territorial grazers according to literature To quantify grazing activity in diferent habitats by exca- and FishBase (Montgomery et al.1989; Choat et al. 2002; vating and scraping parrotfsh, an inventory of feeding scar Clements et al. 2017; Clements and Choat 2018; Tebbett densities was conducted. As feeding by excavating and et al. 2017; Froese and Pauly 2017; Russ et al. 2018). scraping parrotfsh resulted in conspicuous grazing scars Distribution of focal functional groups of fsh in difer- in the substratum it is possible to visually quantify these ent habitats (coral, macroalgae and seagrass) was explored (Bonaldo and Bellwood 2008, 2009; Bonaldo et al. 2011). with non-metrical multidimensional scaling (nMDS) with

Fig. 3 a Coral reef covered in grazing scars from parrotfsh and b close up of grazing scars

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Bray–Curtis dissimilarity index from the “vegan” package habitat types (coral, macroalgae and seagrass) were investi- (Oksanen et al. 2017). Main and interactive efects of habitat gated using mixed linear models, and ANOVA models were and sites for species composition of focal fsh communities performed with abundant juveniles/adults of microphagous were tested using PERMANOVA, Bray–Curtis dissimilari- fshes as “site” did not add any variation. ties (999 permutations) using “adonis” function from the Predictor variables were checked for multicollinearity “vegan” package (Oksanen et al. 2017). Species which by pairwise comparison using the Spearman rank test and occurred ≤ 3 in the UVCs were removed from the nMDS by evaluating variation infation factor (VIF) values (Zuur analysis. A similarity of percentage (SIMPER) analysis et al. 2010). Predictor variables with VIF-values ≥ 2 were (Clarke 1993) from the “vegan” package was performed to removed from the same model. Prior to model ftting, nor- identify which fsh species contributed the most to dissimi- mal distributions of predictor variables were visually exam- larities among the three habitat types. Abundance of func- ined by basic diagnostic plots and if needed, transformation tional groups (herbivores, detritivores, and microphages) log(x + 1) and rescaling to size range was performed. All was analyzed with mixed linear models, “lme4” package, statistical analyses were performed in R version 3.3.1. (R with “site” as random factor and habitat as a fxed factor Core Team 2017). (Bates et al. 2015). Functional group “territorial grazers” was removed from the analyses as roving herbivorous and detritivorous fshes were the main focus of the present study. Results Habitat variables afecting total abundances of all focal functional groups were analyzed separately for each habitat Fish assemblages of focal functional groups using mixed linear models (multiple regressions) with “site” as a random factor and additional predictor variables as fxed A total of 3,672 fshes from 34 families, 97 genera and factors (percent cover of calcareous rubble, soft substrate, 165 species were recorded in the UVCs during the study, live coral cover, macroalgal cover, seagrass cover, number of which 1141 were identifed as seagrass and algivores, of macrophyte species, EAM cover, CCA cover, rugosity detritivores or microphages. Of these, 645 individuals were and predatory fsh abundance). Macroalgal habitats were identifed to species level (27 species), the majority of fsh analyzed with multiple linear regression models, as there identifed only to family level being juvenile labrid scarids. was no diference on site level. Model selection was per- The three habitat types held distinct herbivorous fsh assem- formed by stepwise removal of predictor variables, start- blages and there was also a signifcant diference depending ing with a model containing all predictor variables allowed. on site (PERMANOVA, Fig. 4, Table 1). The algivorous Non-signifcant variables were then removed one by one acanthurid Naso brevirostris was one of the most infuential and using function ‘step’ from “lme4” package, based on species in dissimilarities among habitats as it was abundant Aikaike information criterion (AIC) values. If ΔAIC ≥ 2, in coral reef sites but absent from macroalgal and seagrass the model with the lowest AIC value was considered as the habitats (SIMPER, Table 2). most parsimonious one. Detritivores were most abundant on coral reef sites and Browsing assays (biomass loss for the 2 species of mac- absent from seagrass habitats, while seagrass and algivores roalgae) were analyzed with ANOVA, and mixed linear and microphages were more evenly distributed across the models (total biomass loss in diferent habitats) with “site” seascape (Fig. 5). as a random factor and “habitat” as a fxed factor. Mean Overall, seagrass and algivores and microphages were the values of biomass loss for each macroalgal species were most abundant functional groups (Fig. 5a), the former con- calculated per bioassay and the two species of algae were sisting of acanthurids (mainly subadult Naso brevirostris), analyzed separately. To identify which habitats difered one Chaetodontid (Chaetodon klenii), one Pomacanthid from each other, Tukey’s contrast test was used from pack- (Centropyge multispinis) the scarid labrids Calotomus car- age ‘multcomp’ (Hothorn et al. 2008). Total biomass loss in olinus and Leptoscarus vaigiensis, and the siganid Siganus relation to environmental variables (macroalgal cover, mac- sutor, while the latter group exclusively consisted of juvenile rophyte cover, rugosity, seagrass and algivorous fsh abun- and initial phases of scarid labrids (Scarus spp. and Chloru- dances, EAM cover, live coral cover) was tested using mixed rus sordidus). linear regression models with “site” and “tethered species No diference was found in the total abundance of sea- ID” as random factors and additional predictor variables as grass and algivores among habitat types (Mixed linear “fxed”. Where there was no variance added due to “site” or model, F (2,40) = 16.756, P = 0.160, Fig. 5b) or for micro- “tethered species ID”, linear regression models were used. phages (Mixed linear model, F (2,40) = 0.256, P = 0.775, All fsh of the focal functional groups < 5 cm were clas- Fig. 5d). Detritivores were absent from seagrass habitats sifed as juveniles and larger individuals as adults. Size and signifcantly more abundant in coral reef habitats than in classes of pooled functional groups of fshes in diferent macroalgal habitats, (Mixed linear model, F (1,29)=16.756,

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in seagrass meadows). Coral reefs harbored higher abun- 1.0 dances of adult fshes than macroalgal (Mixed linear model, F (2,40) = 6.76, P = 0.0025) and seagrass habitats (Mixed 0.5 F P LeptVaig linear model, (2,40) = 6,76, = 0.0034). Further, mac- ChloSor ChryUni roalgal habitats held higher abundances of microphagous ChryBio ChaeKle SigaSut F 0.0 AcanTri juveniles than seagrass habitats (ANOVA, (2,45) = 3.248,

NMDS 2 Coral reef P = 0.039), and slightly higher than in the coral reef sites, AcanNig CentMul NasoBre Macroalgae .CtenBin ScarFre although this was not signifcant. −0.5 ZebrSco AcanLeu Seagrass RUVs revealed a higher diversity of seagrass and algivo- CtenTruAcanXan CtenStri rous species than the UVCs in all habitat types. For example, −1.0 N. elegans which were observed feeding on macroalgae in the tethering videos were never observed in the UVCs. Fur- −1.5 −1 012 thermore, few Siganus sutor were observed in UVCs but NMDS1 were common in RUVs (Electronic Supplementary Mate- rial; Table 6S). Fig. 4 NMDS ordination displaying assemblages of seagrass and algivores, detritivores and microphages in each habitat type, stress Environmental variables 0.19. Each symbol corresponds to a sample (1 UVC, 50 m2), and the more similar a UVC is regarding species composition, the closer they are positioned together. Fish species which are infuential in clus- Environmental variables identifed as food resources tar- tering of habitats are displayed in the graph and named as follow- geted by the focal functional groups of fshes (macroalgae, ing: AcanLeu, Acanthurus leucosternon; AcanNig, A. nigrofuscus; AcanTri, A. triostegus; AcanXan, A. xanthopterus; CentMul, Centro- seagrass, EAM, and calcareous rubble) were unevenly dis- pyge multispinis; ChaeKle, Chaetodon kleinii; ChloSor, Chlorurus tributed between the habitat types (Electronic Supplemen- sordidus; ChryBio, Chrysiptera biocellata; ChryUni, Chrysiptera tary Materials; Table 7S). Calcareous rubble was the most unimaculata; CtenBin, Ctenochaetus binotatus; CtenStri, C. stria- abundant food resource in both coral and macroalgal areas tus; CtenTru, C. truncatus; LeptVaig, Leptoscarus vaigiensis; Naso- Bre, Naso brevirostris; ScarFre, Scarus frenatus; SigaSut, Siganus (50.1 ± 5.0 and 52.8 ± 4.6%, respectively). Seagrass habi- sutor; ZebrSco, Zebrasoma scopas. Ellipses are 95% confdence inter- tats had low cover of all food resources except for seagrass val (94.1%). Environmental variables explaining fsh abundances dif- fered among the diferent habitat types (Table 3, Fig. 7, Elec- Table 1 Permutational analysis of variances (PERMANOVA) for tronic Supplementary Materials; Fig. 10S). In the coral reef species composition of seagrass and algivores, detritivores and micro- sites, live coral cover and CCA cover had a positive infu- phagous fsh assemblages using Bray–Curtis dissimilarities in diferent habitat types (coral reefs, macroalgae, and seagrass) ence on the abundance of all fsh (herbivores, detritivores, and microphages pooled) (Table 3, Fig. 7, Electronic Sup- df F R2 P MS value plementary materials; Fig. 10S). Likewise, EAM cover had Habitat 2 1.261 6.345 0.16 0.001 a positive infuence on fsh abundance in coral reef habitats, Site 5 1.062 5.343 0.33 0.001 both independently and in combination with CCA cover. Habitat × site 1 0.689 3.463 0.04 0.004 Within the macroalgal beds, there were signifcant posi- Residuals 37 0.46 tive relationships between fsh abundances and macroalgal Total 45 1.00 height, macroalgal cover and rugosity (Table 3, Electronic Supplementary Materials; Fig. 10S). There was also a sig- p Numbers in bold denote signifcant -values nifcant interaction between macroalgal height and rugosity (Linear regression, r2 = 0.43, F (3,16)=5.703, P = 0.019). P = 0.0003), and were composed of acanthurids; a few Acan- In seagrass habitats, there were no signifcant relationships thurus xanthopterus and dominated by several Ctenochaetus between fsh abundances and any of the measured environ- species (Electronic Supplementary Material, Table 6S). mental variables. Abundances of focal functional groups of fshes of difer- When separating fsh into functional groups, slightly ent size classes difered between habitats (Fig. 6). Seagrass diferent linear models explained abundances in diferent habitats held lower abundance of juveniles (> 5 cm) than habitat types (Table 4, Electronic Supplementary Materi- the 2 other habitats (Mixed linear model, F (2,26)= 7.744, als; Fig. 11S). In coral reef habitats, no model was found P = 0.0008), but there was no signifcant diference between for seagrass and algivores and detritivores, and for micro- coral reefs and macroalgal habitats (mean value 5.13 ± 1.50 phages the best model included macroalgal cover, live coral ind. transect −1 in coral reef habitats, 6.60 ± 1.64 ind. cover, predatory fsh abundance and CCA cover (Table 4). transect−1 in macroalgal areas and 3.0 ± 1.39 ind. transect−1 In the macroalgal areas, the most parsimonious model for

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Table 2 SIMPER analysis Macroalgae Seagrass table displaying the 10 most infuential fsh species Coral reef Scarinae spp. (M) + 17.03 Naso brevirostris (SA) − 15.61 contributing to observed Naso brevirostris (SA) − 14.48 Chlorurus sordidus (M) + 15.11 dissimilarities in species composition among the diferent Chrysiptera unimaculata (SA) + 8.09 Scarinae spp. (M) − 7.45 habitats (all sites pooled) Chlorurus sordidus (M) − 5.83 Zebrasoma scopas (SA) − 6.45 Scarus frenatus (M) + 5.80 Chaetodon kleinii (SA) + 6.38 Zebrasoma scopas (SA) − 5.42 Ctenochaetus truncatus (SA) − 5.49 Centropyge multispinis (SA) − 5.30 Centropyge multispinis (SA) − 5.341 Scarus ghobban (M) + 5.0 Siganus sutor (SA) + 4.31 Ctenochaetus truncatus (D) − 4.33 Acanthurus nigrofuscus (SA) − 4.30 Acanthurus nigrofuscus (SA) − 3.78 Leptoscarus vaigiensis (SA) + 3.39 Seagrass Scarinae spp. (M) + 21.16 Chlorurus sordidus (M) − 15.12 Chrysiptera unimaculata (SA) + 11.48 Scarus ghobban (M) + 8.89 Chaetodon kleinii (SA) − 6.76 Scarus frenatus (M) + 5.13 Siganus sutor (SA) − 5.0 Centropyge multispinis (SA) + 4.91 Chrysiptera biocellata (SA) + 4.37 Leptoscarus vaigiensis (SA) − 4.04

Values correspond to average % dissimilarity explained by that particular species. Letters in brackets denote functional group; D, detritivore; SA, seagrass/algivore; M, microphage and “+” or “−” denote higher or lower abundances compared with the habitat in the left column

explaining abundance of seagrass and algivores was preda- were recorded on Sargassum aquifolium at the termination tory fsh abundance and for microphages, macroalgal cover of the experiment. and macrophyte height (Table 4). In the seagrass habitats, there were no signifcant models. Grazing scar inventory studies

Coral reef sites had signifcantly higher number and sizes Browser assays of grazing scars compared to what was found in macroalgal habitats (Mixed linear model, F (1,110) = 16.397, P = 0.0001 Biomass loss of tethered algae was signifcantly higher in and F (1,110) = 21.710, P < 0.0001, respectively) (Fig. 9). the coral reef habitats than in the two macrophyte habitats (mixed linear model, F = 25.454, P < 0.0001, Table 5), with biomass loss being slightly higher in the macroalgal habitats Discussion compared to the seagrass meadows. There was no diference in biomass loss between the two macroalgal species. To our knowledge, this is the frst study examining habitat Macrophyte cover (both seagrass and feshy macroalgae) associations, distribution, and foraging patterns of seagrass in the surrounding habitat was the single signifcant fac- and algivorous, detritivorous, and microphagous fshes from tor explaining biomass loss of tethered macroalgae (linear varying life stages across several shallow-water habitat types regression, r2 = 0.436, F (1,16)=12.371, P =0.0028) (Fig. 8). (coral reefs, macroalgae beds, and seagrass meadows) within Very few fsh were observed feeding on the tethered a tropical seascape. As hypothesized, densities of focal func- macroalgae in the RUVs, and all observations were from tional groups of fshes and foraging patterns were not equally the coral reef sites (Chawe Kubwa, Kitutia and Milimani). distributed within the seascape, but varied with habitats. Acanthurids were the most common fsh observed; small Likewise, species composition of nominally herbivorous and (~ 25 cm) Naso brevirostris (n = 4), adult N. elegans (n = 2), detritivorous fshes also changed signifcantly with habitat, N. vlamingii (n = 1) and one siganid species; Siganus sutor suggesting that fsh communities in this study are subjected (n = 1). All observed fsh targeted E. denticulatum, but bites to, and to a certain extent, driven by bottom-up processes, which was most obvious for the microphagous parrotfsh.

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(a)

1.00

0.75

0.50

0.25

0.00 Proportion of focal groups fish

(b) (c) (d)

20 Abundance 50 m 2 -1 2 m 50 Abundance

CR MA SG CR MA SG CR MA SG

Fig. 5 a Top panel displays proportion of diferent functional groups meadows (Thalassodendron ciliatum), b seagrass and algivores, c in all samples (underwater visual censuses (UVCs), all habitats and detritivores and d microphages. Each dot in fgures represents a sam- all sites). Bottom panels display abundance of fsh from diferent ple (1 UVC), boxes show median (thick line), 25th and 75th percen- functional groups in the three habitat types (all sites pooled) from tile. Error bars are 95% confdence interval. CR, coral reef; MA, mac- the UVCs (50 m2); coral reef sites, macroalgal habitats and seagrass roalgae; SG, seagrass

Fig. 6 Boxplots showing (a)(b) abundance of size classes a fsh > 5 cm and b fsh < 5 cm of 70 (all functional groups pooled) fshes in diferent habitat cat- 60 egories (coral reefs, macroalgal habitats and seagrass meadows) 50 from the UVCs (50 m2). Each dot in fgures represents a 40 sample (1 UVC), boxes show median (thick line), 25th and 75th percentile. Error bars are 30 95% confdence intervals. One outlier (a UVC containing 125 20 adult fsh) was removed from the coral reef habitat in the left 10 fgure 0

coral reef macroalgaeseagrass coral reef macroalgae seagrass

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Table 3 Results of mixed- Predictor variable Habitat efects linear models (fxed efects only, coral reef, and Coral reef Macroalgae Seagrass seagrass meadow habitats) P P P and linear models (macroalgal value Conditional value Adjusted value Condi- R2 R2 R2 areas) displaying environmental value value tional variables predicting fsh value abundances (all functional Live coral Cover 0.59 – – NA NA groups pooled) in diferent 0.013 habitats, signifcant P values Cover CCA 0.008 0.66 – – NA NA indicated in bold Live coral cover × cover CCA 0.036 0.85 – – NA NA Cover EAM – – – – NA NA Cover EAM × cover CCA 0.018 0.85 – – NA NA Cover calcareous rubble – – – – – – Cover seagrass NA NA NA NA – – Cover macroalgae – – 0.044 0.16 – – No of macrophyte species NA NA – – – – Macrophyte height NA NA 0.005 0.43 – – Rugosity – – 0.006 0.43 NA NA Rugosity × macrophyte height NA NA 0.019 0.43 NA NA Depth – – – – – – Predatory fsh abundance – – – – – –

Hyphens denote non-signifcant results and NA denote variables not tested for this particular habitat, usu- ally due to the lack of a predictor variable within the habitat or no variation of the predictor within the habitat

(a)(b)

macrophyte live coral CCA cover height rugosity EAM cover cover (+) macroalgal (+) macroalgal (+) x CCA cover (+) cover cover (+) (-) (+)

Fig. 7 Conceptualized illustration of benthic variables infuencing arrows are variables only afecting a single functional group. Positive abundance of herbivorous fsh in a coral reef habitats and b mac- or negative relationships are indicated with (+) or (–), respectively. roalgal habitats. Black arrows denote variables having an efect on Symbols courtesy partly of IAN library, University of Maryland the total roving herbivorous/detritivorous fsh community and grey

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Table 4 Results of signifcant Model Coefcient SE F value P value R2 R2 mixed-efects linear models marginal conditional (fxed efects only) predicting Coral reef fsh densities of focal functional Seagrass/algivores groups (seagrass/algivores, detritivores, and microphages) No signifcant model in the diferent habitat types Microphages 0.457 0.657 Cover macroalgae − 0.292 5.0527 0.049 Live coral cover 0.013 3.7603 0.083 Cover CCA + 0.362 8.4746 0.019 Predatory fsh abundance 0.524 2.6807 0.134 Detritivores No signifcant model Macroalgae Seagrass/algivores 0.490a 0.4617b Predatory fsh abundance + 0.156 17.294 0.0006 Microphages 0.6663a 0.6271b Cover macroalgae + 0.382 13.445 0.0002 Macrophyte height + 0.042 20.505 0.0003

Coral reef habitats were analyzed with mixed linear models and macroalgal habitats with linear models. Signifcant P values are indicated in bold. Detritivores were absent from macroalgal habitats, which is why they are not included in the table a Denote multiple R-squared b Adjusted R-squared

Table 5 Results of mixed linear Habitat comparison Estimated std. error df z value Adjusted P value models (fxed efects only) of biomass loss of tethered Eucheuma denticulatum macroalgae in diferent habitats Seagrass × coral − 1.563 134 0.243 < 0.00001 Macroalgae × coral − 1.311 134 0.230 < 0.00001 Macroalgae × seagrass 0.253 134 0.238 0.538 Sargassum aquifolium Seagrass × coral − 1.413 134 0.281 < 0.00001 Macroalgae × coral − 1.060 134 0.271 0.0003 Macroalgae × seagrass 0.353 134 0.260 0.362

Signifcant P values are indicated in bold

Life stages of microphagous parrotfsh also varied with Tano et al. (2017) also observed large numbers of juve- habitat; smaller individuals (< 5 cm) were more abundant nile parrotfsh in macroalgal areas in Zanzibar, Tanzania, in macroalgal habitats and larger individuals more com- compared to neighboring habitats, suggesting that shallow mon in coral reef and seagrass habitats. This was mirrored areas in the Western Indian Ocean (WIO) dominated by in the inventory of grazing scars, which were signifcantly canopy-forming macroalgae may serve as nurseries for this smaller in macroalgal habitats compared to coral reef sites, particular group of fshes. likely refecting the distribution patterns of ontogenetic Habitat features benefting certain functional groups of stages of this functional group. Lower numbers of graz- fshes in one habitat might not be the same in another since ing scars in the macroalgal habitats might be the result of diferent environmental variables explained fsh abundances fshes feeding more intensely on epiphytes than on hard in diferent habitat types. “Live coral cover”, “CCA cover” substrate surfaces. However, that would not explain the and “CCA cover” in combination with “EAM cover”, had signifcant diferences in sizes of grazing scars. Whether a positive efect on the abundance of fsh (all functional or not it was the same species using diferent habitats dur- groups pooled) in coral reef habitats, which is similar to ing distinct life stages was impossible to tell, as a majority results from other studies (Friedlander et al. 2003; Osuka of the juveniles were seldom identifed to species level. et al. 2018). In the macroalgal beds, habitat quality variables

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) tropical (Lim et al. 2016) and temperate macroalgal areas 3 (Fulton et al. 2016; van Lier et al. 2017). “Calcareous rubble”, which has been shown to have a strong positive efect on abundances of acanthurids and parrotfsh (Russ et al. 2015, 2018), did not have any efects on abundance in the 2 present study. This is probably due to the rather high cover of calcareous rubble in coral and macroalgal habitats (50.3 and 52.8%, respectively), implying that this is currently not 1 a food-limiting resource on Mafa Island. The positive relationship between “live coral cover” and

log(biomass loss tethered algae) (g nominally herbivorous fsh abundances is probably due to 02550 75 100 the numerous feeding surfaces in the form of dead hard sub- macrophyte cover (%) strata this benthic category is associated with. Note that “live coral cover” was almost never the dominating substrate in Fig. 8 Linear regression displaying environmental variables (macro- UVCs (48.465 ± 5.26%), not even in the coral reef habitats, phyte cover in the surrounding habitat) afecting biomass loss (g) of which all had a high degree of calcareous rubble. Although tethered macroalgae during 24 h experiment (both species pooled). not a food source for the majority of the fshes in the study, Each dot represents a mean value from each site and habitat. Shaded areas denote partial residuals CCA cover might indicate areas with low sedimentation, which are more attractive feeding grounds for many herbivorous fshes (Bellwood and Fulton 2008). such as “macrophyte height”, “macrophyte cover” and The lack of signifcant explanatory variables in the sea- “rugosity”, had a positive efect, patterns that are consistent grass habitats is likely a consequence of the limited sam- with studies of microhabitat selection of labrid fshes in both ple size and small value range within measured variables.

(a) (b)

3.0 25

20 2.5

15 2.0

10 1.5

5 size of grazing scars (cm) 1.0 number of grazing scars 0.02 m2 -1 0 0.5

coral reef macroalgae coral reef macroalgae

Fig. 9 a Number of grazing scars in coral reef habitats and macroal- smaller than in the coral reef habitats; ncoral = 78, nmacroalgae = 39. Illus- gal areas, b sizes of grazing scars (cm) in diferent habitats. Due to trations from IAN library, University of Maryland an unforeseen weather event, the sample size in macroalgae areas is

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Factors such as spatial arrangement within the seascape and efect on the abundance of parrotfsh while it was positive distance to other habitats or deeper waters might be more in another habitat type. important for structuring fsh assemblages in these habitats Algal consumption, measured as the removal of macroal- (Gullström et al. 2008; Henderson et al. 2017). gae from assays, was the highest within coral reef sites, fol- Fish likely respond diferently to habitat characteristics lowed by macroalgal beds, and seagrass meadows. However, and environmental variables depending on ontogenetic stage it does not necessarily mean that grazing intensity per se was (Macpherson 1998; Almany 2004). The difering bottom–up the highest in coral reef habitats in the present study. Since variables explaining fsh abundance in diferent habitat types biomass loss of tethered macroalgae was negatively related in the present study are probably refecting shifts in habitat to macroalgal cover in the surrounding habitat, it suggests a preferences for diferent life stages of fshes. Abundance density-dependent process, where grazing pressure might be of microphagous parrotfsh was negatively associated with “smoothed out” in areas with high macrophyte cover. Mac- macroalgal cover in coral reef habitats, while in macroalgal roalgal feeding fsh might therefore not be able to eradicate areas the relationship was reversed and there was instead a dense macroalgal stands or “blooms” on coral reefs, if they positive efect of macroalgal cover and canopy height on par- are already established. Solitary fronds may, however, be rotfsh abundance. This is likely an efect of smaller/younger targeted and limited by browsing fsh since the survival and fsh seeking shelter from predators in the form of structural growth of newly settled Sargassum spp. have been shown to complexity, provided by height and cover of macroalgae, be strongly suppressed by top–down control (Diaz-Pulido and by hard underlying structure (rugosity) (van Lier et al. and McCook 2003). 2018). The negative relationship with macroalgal cover is Understanding how habitats structure fsh assemblages in in line with results from previous studies from the Great spatially heterogeneous environments is imperative because Barrier Reef, Australia, where dense macroalgal stands of it will improve habitat-based approaches of management and Sargassum spp. in coral reef environments were found to conservation. As tropical natural macroalgal habitats have induce avoidance behavior of roving herbivores (Hoey and been shown to host high numbers of juvenile and subadult Bellwood 2011). There is likely a trade-of between food scarine labrids, these linkages between reefs and macroalgal and shelter changing throughout ontogeny in these fshes, beds should be considered in seascape management (Tano but also between diferent types of shelter, provided by live et al. 2017; Eggertsen et al. 2017; Fulton et al. 2019), even coral or by microhabitat topography in the macroalgal areas. though these habitats have only been recently acknowledged. Shelter from predators is an important resource in coral reef Furthermore, the availability of nursery grounds and con- environments (Kerry and Bellwood 2016), and can be size- nectivity to coral reefs by nominally herbivorous fshes have specifc, as inter-structural spaces which are smaller than the been found to enhance herbivory (Adam et al. 2011; Olds potential predator width will act as shelter for a fsh that ft et al. 2012, Harborne et al. 2016). Therefore, the protection within the space provided (Bartholomew et al. 2000; Gull- of important ecological functions urges the preservation of ström et al. 2011). Macroalgal areas with both soft and hard seascapes comprising multiple habitats with a high degree complexity in the form of fronds and coral rubble might of connectedness. This is particularly important in the WIO therefore provide sufcient shelter for smaller individuals, area, where a large part of the population is living within the while it is advantageous for larger fsh to keep to areas with coastal region and is heavily dependent on the local marine larger structures, as provided by live coral. Consequently, resources. macroalgal areas in shallow areas with tall canopies and high macrophyte cover might be advantageous for the survival and recruitment of parrotfsh and hence contribute to the replenishment of important herbivores and microphages on Conclusion coral reefs. This is strengthened by recent studies showing that tropical macroalgal habitats host high numbers of juve- The current study illustrates that multiple habitat types nile and subadult parrotfsh, suggesting that they are impor- within the seascape matrix are needed to host a diverse com- tant nursery grounds for these species and that linkages munity of herbivorous and detritivorous fshes. Further, the between habitats should be highlighted in coral reef man- study suggests that in the absence of overfshing, the her- agement (Tano et al. 2017; Eggertsen et al. 2017). However, bivorous community may be driven by bottom–up mecha- we would like to stress that deteriorated coral reefs with high nisms, with emphasis on microphagous parrotfsh. The study cover of feshy macroalgae is not what we defne as “natural also highlights the importance of habitat quality in terms macroalgal areas”, and that nursery habitat qualities might of cover and complexity for maintaining certain ecological depend on where in the seascape a habitat is located. This functions. These features might vary across habitats, and is, to some extent, illustrated in the present study as high afect life stages of nominally herbivorous fshes diferently. macroalgal cover in the coral reef habitat had a negative A habitat feature (e.g., macroalgal cover on coral reefs) that

1 3 51 Page 14 of 16 Marine Biology (2019) 166:51 is detrimental for a certain age class of a functional group of regional- and local-scale variables on tropical seagrass fsh of fshes (e.g., adult microphages) might simultaneously be assemblages. Mar Biol 161:2395–2405. https://doi.org/10.1007/ s00227-014-2514-7 important in an adjacent habitat (e.g., natural macroalgal Bartholomew A, Diaz R, Cicchetti G (2000) New dimensionless indi- beds) for a diferent life stage of a fsh (juvenile) of the same ces of structural habitat complexity: predicted and actual efects functional group. This highlights the need of a holistic view on a predator’s foraging success. Mar Ecol Prog Ser 206:45–58. of the shallow tropical seascape for efcient management https://doi.org/10.3354/meps206045 Bates D, Maechler M, Bolker B, Walker S (2015) Fitting linear mixed- and conservation. efects models using lme4. J Stat Softw 67(1):1–48. https://doi. org/10.18637/jss.v067.i01 Acknowledgements We wish to thank the two anonymous reviewers Bell J, Galzin R (1984) Infuence of live coral cover on coral-reef who contributed with valuable and constructive input to the manu- fsh communities. Mar Ecol Prog Ser 15:265–274. https://doi. script. We also wish to thank Dr. Amelia Buriyo at the University of org/10.3354/meps015265 Dar es Salaam, Karlina See Kee, Yessenia Rojas, the staf at the Mafa Bellwood DR, Fulton CJ (2008) Sediment-mediated suppression of Island Marine Park (MIMP), Big Blu Mafa Island Dive Centre and herbivory on coral reefs: decreasing resilience to rising sea-levels Mafa Island Diving for their support during feld work in Mafa Island. and climate change? Limnol Oceanogr 53:2695–2701 Last but not least, we want to thank our Tanzanian boat captain, Mr. Bellwood DR, Hughes TP, Folke C, Nystrom M (2004) Confronting Nahoda Salamala for his invaluable help and local knowledge. The the coral reef crisis. Nature 429:827 study in Mafa was supported by the Swedish Research Council (Grant Bellwood DR, Goatley CHR, Brandl SJ, Bellwood O (2014) Fifty mil- nos. 2015-05848, 2015-01257, E0344801) and the National Science lion years of herbivory on coral reefs: fossils, fsh and functional Foundation Graduate Research Fellowship and the Graduate Research innovations. Proc R Soc B Biol Sci 281:20133046–20133046. Opportunities Worldwide (Grant no. 1144244). https://doi.org/10.1098/rspb.2013.3046 Berkström C, Gullström M, Lindborg R, Mwandya AW, Yahya Compliance with ethical standards SAS, Kautsky N, Nyström M (2012) Exploring ‘knowns’ and ‘unknowns’ in tropical seascape connectivity with insights from Conflict of interest The authors declare that they have no confict of East African coral reefs. Estuar Coast Shelf Sci 107:1–21. https interest. Funding was provided by the Swedish Research Council, the ://doi.org/10.1016/j.ecss.2012.03.020 National Science Foundation Graduate Research Fellowship and the Berkström C, Jörgensen T, Hellström M (2013) Ecological connectivity Graduate Research Opportunities Worldwide. and niche diferentiation between two closely related fsh species in the mangrove-seagrass-coral reef continuum. Mar Ecol Prog Ethical approval All applicable international, national, and/or institu- Ser 477:201–215. https://doi.org/10.3354/meps10171 tional guidelines for the care and use of animals and sampling were fol- Bonaldo R, Bellwood D (2008) Size-dependent variation in the func- Scarus rivulatus lowed in the current study. All necessary approvals have been obtained. tional role of the parrotfsh on the Great Bar- Field sampling in Tanzania was performed with permission from Tan- rier Reef, Australia. Mar Ecol Prog Ser 360:237–244. https://doi. zania Commission for Science and Technology (COSTECH), research org/10.3354/meps07413 permits no 2016-291-NA-2016-217 (M. Eggertsen), no 2016-294-NA- Bonaldo RM, Bellwood DR (2009) Dynamics of parrotfsh grazing 2016-217 (D. Chacin) and no 2016-293-NA-2016-217 (C. Åkerlund). scars. Mar Biol 156:771–777. https://doi.org/10.1007/s0022 7-009-1129-x Bonaldo R, Krajewski J, Bellwood D (2011) Relative impact of par- Open Access This article is distributed under the terms of the Crea- rotfsh grazing scars on massive Porites corals at Lizard Island, tive Commons Attribution 4.0 International License (http://creativeco Great Barrier Reef. Mar Ecol Prog Ser 423:223–233. https://doi. mmons.org/licen ses/by/4.0/ ), which permits unrestricted use, distribu- org/10.3354/meps08946 tion, and reproduction in any medium, provided you give appropriate Bonaldo R, Hoey A, Bellwood D (2014) The Ecosystem roles of par- credit to the original author(s) and the source, provide a link to the rotfshes on tropical reefs. In: Hughes R, Hughes D, Smith I (eds) Creative Commons license, and indicate if changes were made. Oceanography and marine biology. CRC Press, Boca Raton, pp 81–132 Chabanet P, Ralambondrainy H, Amanieu M, Faure G, Galzin R (1997) Relationships between coral reef substrata and fsh. Coral Reefs 16:93–102. https://doi.org/10.1007/s003380050063 References Choat JH, Clements K, Robbins W (2002) The trophic status of herbivorous fshes on coral reefs. Mar Biol 140:613–623. https://doi. 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