Predators facilitate herbivory in nutrient-limited marine ecosystems

Predators facilitate herbivory in nutrient-limited marine ecosystems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Predators facilitate herbivory in nutrient-limited marine ecosystems Anish Paul, Harshul Thareja, Rohan Arthur, Teresa Alcoverro, Sandeep Pulla, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7365908/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract Apex predators influence ecosystem functioning through consumptive and non-consumptive effects. Recent studies suggest that predators can also be an essential source of limiting nutrients in ecosystems such as coral reefs, potentially influencing prey ecology from the bottom up. With rising commercial fishery, predatory fishes are being selectively harvested from reefs. Yet, there is incomplete knowledge of the consequences of this extraction on essential ecosystem processes. Using field experiments and observations, we examined how predatory fishes influence herbivory along a fishing-induced predatory fish biomass gradient in the Lakshadweep Archipelago. We found that mesopredatory fish excreta have greater proportion of phosphorus than nitrogen. Along the gradient, primary and secondary productivity increased, after accounting for pelagic nutrient subsidies. Further, herbivory rates increased with increasing predator biomass, while prey anti-predator response remained unchanged. Our results suggest that predator-induced alterations of nutrient stoichiometry stimulate primary and secondary productivity and enhance herbivory in coral reefs, particularly in systems experiencing mesopredator release following selective fishing of apex predators. Our study shifts focus from the traditional top-down role of predators, highlighting an overlooked bottom-up pathway by which predators can influence ecosystem functioning. Global decline of predators could modify ecosystem processes in ways that are yet unknown, leaving them increasingly vulnerable to future disturbances. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Ocean sciences Ecosystem functions nutrient stoichiometry bottom-up processes predator-prey interactions mesopredator release coral reefs Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Predator-prey interactions are a major governing process in natural ecosystems 1 , 2 . Predators can directly influence the size, demography, and population structure of prey, as well as influence the community composition of an ecosystem 1 – 4 . Apart from directly influencing the prey population through predation, predators also generate a ‘landscape of fear’ 5 , where prey species must remain vigilant not only in the presence of predators but even in their absence, constantly apprehensive about the potential of an imminent attack 6 , 7 . However, the consumptive and non-consumptive top-down effects of predators are not prominent across all ecosystems 8 , 9 , and predator-mediated trophic cascades are considered to be ‘exceptions rather than rule’ in ecosystems with complex trophic structures 10 . Besides exerting top-down effects, predators can also influence bottom-up processes by nutrient input from external sources or by altering the stoichiometry of nutrients available to primary producers 11 – 14 . These effects may be particularly evident in oligotrophic and mesotrophic ecosystems where nutrient availability limits productivity. In such systems, consumer-derived nutrients could modulate primary productivity and, subsequently, consumption, i.e., herbivory 11 , 12 , 15 – 18 . However, much of our current understanding of top predators' influence on ecosystem processes comes from terrestrial and pelagic ecosystems, where their lower abundance and biomass relative to lower trophic levels may limit their nutrient-mediated effects 6 , 7 , 19 – 25 . In contrast, in ecosystems where predators constitute a high proportion of total biomass, they can potentially influence the rates of ecosystem processes through nutrient-mediated pathways 26 – 29 . This potential facilitation of productivity through predatory fish-derived limiting nutrients has rarely been explored, with only a few examples from seagrass ecosystems and low-diversity coral reefs in the Caribbean 11 , 28 . Additionally, while the role of predators in structuring herbivory through top-down effects on herbivore populations has been well documented across ecosystems 23 , 30 – 33 , how predator-derived nutrients could influence herbivory, through their effects on primary productivity, remains underexplored 34 , 35 . Predatory fishes constitute a significant proportion of the standing biomass in undisturbed reefs, often much greater than any terrestrial system, and frequently form permanent or temporary aggregations to feed and/or reproduce 26 – 29 , 36 , 37 . However, the complexities of food webs in coral reefs, associated with uncertainties in their trophic position and diet inconsistencies, have made the role of predators in generating trophic cascades in coral reefs ambiguous and highly context-specific 10 , 38 – 43 . While predator removal has been reported to promote benthic recovery 43 , studies have also reported the co-occurrence of high coral cover and high predator biomass in reefs 44 , 45 . Additionally, owing to their diet, excretory inputs from predatory fish are a major source of phosphorus, a limiting nutrient in coral reef ecosystems that can determine algal productivity 11 , 18 . Thus, in the absence of strong consumptive and non-consumptive effects of predation, predators can potentially mediate herbivory levels in coral reefs by increasing algal production, thereby increasing the algal-removal potential of herbivores through nutrient-mediated pathways 11 , 13 , 26 , 46 . In coral reefs, herbivory is a key process in maintaining the stability and health of the ecosystem 47 – 49 , as it confers resilience to reefs by removing algae that compete with coral recruits for substrate, nutrients, growth, reproduction, and survivorship 49 – 52 . Unpacking these nuanced trophic relationships becomes particularly important in the light of increasing fishing impacts on reefs. As true apex predators, such as sharks, decline due to overfishing, mesopredatory species, like groupers, snappers, and emperors, are attaining the role of top predator and are also increasingly becoming fisheries targets. We lack the understanding of how their removal will impact essential ecosystem processes in coral reefs 53 , 54 . It is therefore crucial to investigate the influence of predatory fishes on algal production and herbivory levels in reefs, especially where mesopredators can play essential bottom-up roles as nutrient providers in nutrient-limited systems. The islands of the Lakshadweep Archipelago are ideally suited to test the role of mesopredators in influencing bottom-up and top-down processes in nutrient-limited ecosystems. Some reefs of Lakshadweep have been relatively unfished until recently 55 , 56 . Nutrient-limited waters and the relatively lightly fished fish community of some of the Lakshadweep’s coral atolls make it a suitable system to study the effect that mesopredatory fishes may have on herbivory levels by altering the bottom-up pathways through nutrient input. We employed a combination of experimental and observational methods to quantify herbivore and piscivore biomass, the stoichiometry of nutrient contributions by herbivores and predators (based on biomass and species-specific nutrient input rates), algal growth rates, herbivore productivity, herbivory rates and prey anti-predatory behaviour along a fishing-induced mesopredatory reef fish biomass gradient to evaluate support for bottom-up vs top-down processes in the coral reefs of Lakshadweep. The specific questions we addressed were: a) Does primary and secondary productivity increase with increasing predator biomass in a nutrient-limited coral reef ecosystem? b) Does herbivory rate vary in response to variations in predator biomass? c) Is there evidence for top-down non-consumptive effects in the form increasing vigilance with increasing predator biomass? Results a) Does productivity increase with increasing predator biomass in a nutrient-limited coral reef ecosystem? Consumer-derived nutrients The mean molar ratio of nitrogen to phosphorus across sites was 52.3:1 (± 8.1, SE) for herbivore excreta, whereas it was considerably lower, at 17.5:1 (± 0.47, SE) for piscivore excreta (Fig. 1 Figure ) . Primary productivity Primary productivity was measured as the monthly proportional growth rate (change in turf height per month/initial height of turf) of turf algae inside herbivore exclosures. Proportional algal growth rate increased by 0.41 month − 1 (95% CI 0.18 to 0.63, p = 0.001 ) per unit standard deviation increase in log-transformed values of predator biomass ( Fig. 2 a, Supplementary Material 1) . In contrast, proportional algal growth rate was not significantly influenced by herbivore biomass (Supplementary Material 1) . Aspect also significantly influenced algal growth rate, with the exposed western aspect showing a reduction in proportional growth rate by 0.61 month − 1 (95% CI 0.24 to 0.99, P = 0.002 ) (Supplementary Material 1, 2) . Secondary productivity Herbivorous fish productivity, i.e., secondary productivity, increased by a factor of 1.41 (95% CI 1.07 to 1.85, p = 0.013 ) per unit standard deviation increase in log-transformed values of predator biomass ( Fig. 2 b, Supplementary Material 3) . Secondary productivity also increased by a factor of 1.40 (95% CI 1.08 to 1.81, p = 0.010) with an unit standard deviation increase in structural complexity of the site (Supplementary Material 3) . Resource availability and aspect of the site had no statistically significant relationship with herbivore productivity (Supplementary Material 3) . b) Does herbivory rate vary in response to variations in predator biomass? Reef-wide herbivory rate Reef-wide herbivory rate was calculated as millimeters of algal frond lost per month from 20 cm × 20 cm plots. Predator biomass had a positive influence on herbivory rate, with a unit standard deviation increase in the log of predator biomass associated with a 0.64 mm/month increase in algal frond loss (95% CI 0.12 to 1.16, P = 0.017 ) within a 20 cm × 20 cm plot ( Fig. 3 a, Supplementary Material 4) . Herbivore biomass, percentage algal cover, and aspect had no statistically significant influence on herbivory rates (Supplementary Material 4) . Community-level herbivory rate The community-level herbivory rate, calculated using the underwater visual census data, increased by a factor of 1.51 (CI 1.18 to 1.93, p = 0.001) per unit standard deviation increase in log-transformed predator biomass ( Fig. 3 b, Supplementary Material 5) . Herbivory rates also increased by a factor of 1.30 (CI 1.03 to 1.65, p = 0.028) per unit standard deviation increase in structural complexity of the site (Supplementary Material 5) . Percentage algal cover and aspect of the site had no statistically significant relationship with community-level herbivory rates (Supplementary Material 5) . c) Is there evidence for top-down non-consumptive effects in the form increasing vigilance with increasing predator biomass? None of the predictors, including predator biomass, had any statistically significant relationship with the proportion of time spent in vigilance by C. striatus individuals ( Fig. 4 b, Supplementary Material 6) . Discussion Predators input key nutrients into reefs 13 , 17 , 28 , 57 , which can enhance algal productivity 34 . Our results indicate that predators can also indirectly enhance reef-scale herbivory via nutrient-mediated pathways and may play a key role in the functioning of coral reef ecosystems. Our results suggest that predatory fishes supply nutrients in reefs at an N:P molar ratio closer to the classical Redfield Ratio of 16:1 and much lower than that of herbivorous fishes 58 . This suggests that there is greater proportional phosphorus than nitrogen in predator excreta, which can thus influence primary productivity in a phosphorus-limited system 58 . This conforms with studies from other parts of the world, establishing predator excreta as a critical source of phosphorus in nutrient-limited tropical marine systems 11 , 59 . Consistent with the previous studies from Lakshadweep, site aspect had the greatest effect on algal growth rates, with the more exposed west having a relatively lower growth rate than the sheltered east 60 . However, our results also indicate a significant positive relationship between primary productivity and predator biomass after statistically controlling for pelagic nutrient subsidies through aspect. Our results thus suggest that, aside from their traditional role in mediating top-down processes, predatory fishes can potentially enhance algal growth rate, i.e., primary productivity, in nutrient-limited atoll systems. This highlights the role of predator-derived nutrients and thus, predators, in influencing bottom-up pathways 11 . Consistent with our expectations, herbivore productivity increased with predator biomass in the reefs of Lakshadweep 34 , 35 . In our estimation of herbivore productivity, we only included herbivorous reef fishes with body sizes greater than 10cm. This body size far exceeds the average size of prey (1.75 cm, 95% CI 0.8 to 3.65) in coral reefs 61 . Therefore, the threat of predation on the sampled herbivorous fish is likely to be insignificant, indicating that the observed herbivore productivity is unlikely to drive the observed predator biomass in our study. Additionally, the targeted fishing pressure towards mesopredatory reef fishes in the atolls of Lakshadweep leaves the herbivorous fish community relatively undisturbed 62 , which in turn reduces the possibility of fishing pressure confounding the relationship between herbivore productivity and predator biomass. Thus, we suggest that the positive correlation between predatory fish biomass and herbivorous fish productivity can potentially be caused by indirect facilitation of herbivorous by piscivorous fishes, where the nutrient-enriched seascape generated by predator-derived nutrients (primarily increased phosphorus availability in a phosphorus-limited ecosystem) leads to greater primary productivity, and thus enhances secondary productivity 35 , 63 . Similar patterns have been observed in the reefs of Australia, where novel fish communities, resulting from tropicalization, increased the availability of turf algae, which in turn increased herbivore productivity 63 . Studies from similar oceanic atolls in the Seychelles support a similar hypothesis, where enhanced nutrient availability from seabird excreta has increased secondary productivity via increased turf growth rates (primary productivity) 34 . While nutrient input from reef fishes is expected to be much less compared to that of seabirds 14 , 15 , 26 , studies on grunts (Haemulidae) and damselfishes (Pomacentridae) have shown that fish-derived nutrients can increase algal and coral growth rates on a smaller spatial scale 28 , 64 , 65 . However, further studies examining isotopic signatures in algae and fish tissues, fine-scale oceanographic patterns, and experimentally manipulating consumer biomass, nutrient availability and stoichiometry are required to definitively validate the potential indirect effects of predators on herbivore productivity in coral reefs. Herbivory is considered to be a critical ecosystem function in the coral reefs 66 , 67 . Spatial patterns of herbivory are known to have dramatic influences on the structure, composition and distribution of plant and algal communities in both terrestrial and marine environments 68 – 73 . Our results indicate a statistically significant positive correlation between predator biomass and herbivory rates. Although mesopredators strongly dictate herbivorous fish demography through direct predation during their juvenile state 74 , 75 , predation threat on herbivores reduces significantly with increasing body size 61 , 76 , 77 . This suggests a negligible direct consumptive effect of piscivores on observed herbivores (body size ≥ 10cm) in our study. However, the non-consumptive effects of predation threat can alter feeding behaviour of prey, even in the absence of an imminent predation event 7 , 31 , 78 . Increased perceived predation threat increases rates of feeding by individuals 31 , thus potentially leading to greater herbivory at the level of the reef. However, presence of non-consumptive effects on fishes of lower trophic groups is known to be weak 8 , 9 . Our focal fish observations of a hyperabundant primary consumer species in Lakshadweep, Ctenochaetus striatus , further evidenced this. Along the mesopredatory fish biomass gradient, the adult C. striatus individuals exhibited no change in anti-predatory behaviour, suggesting the absence of a strong non-consumptive effect of predation on adult individuals of prey species. Thus, we argue that observed patterns in herbivory rates along the predator gradient are less likely to be driven by faster consumption of algae as a response to perceived predation threat 31 , 32 . Studies suggest that herbivore biomass in coral reefs strongly correlates with turf algal productivity rather than the total available biomass of turf algae 34 , 63 , 79 , 80 . Hence, we argue that the observed pattern is likely due to enhanced primary productivity resulting from predator-derived nutrients, which increases resource availability and consumption in reefs with greater predator biomass 81 . Thus, our results indicate that in the absence of strong consumptive and non-consumptive effects on herbivores, predators can potentially facilitate herbivory in nutrient-limited systems. Establishing the causal effects of predator-derived nutrients on community-wide herbivory and disentangling the effects of other factors, such as resource availability, nutrient composition of the benthos, structural complexity, sedimentation rates, local hydrodynamics and spatial configuration of sites, requires further investigation using transplant experiments of algal mats and bulk or compound-specific stable isotope tracers across trophic levels 34 , 82 – 84 . However, our study draws attention to a vastly understated role of predators in a system where their top-down role is often debated. It highlights the nuances of trophic interactions and ecosystem functions, aiming to improve the understanding of trophic pathways in complex ecosystems such as coral reefs. Recently, an extensive body of work has established another top trophic group of the near-shore ecosystems, the seabirds, as an integral part of nutrient dynamics in coral reefs 15 – 17 , 34 , 35 , 83 . While mesopredatory fishes can have much less quantity of nutrient input and spatial coverage than nesting seabirds and do not bring in new nutrients from external sources, we argue that they can also play an important role in coral reef nutrient dynamics due to greater proportion of phosphorus in their excreta, especially in atolls where other sources of nutrients are often limiting. Although more work is required to understand the nuances of nutrient fluxes and patterns of productivity and herbivory under varying physicochemical and ecological conditions, our results indicate that predatory fishes, specifically mesopredators, that may not exert a strong top-down influence on the adult life stages of lower trophic levels, may potentially impact the functions performed by these groups by affecting nutrient dynamics and productivity in nutrient-limited systems. Conclusion Pervasive targeted fishing activities have led to a trophic downgrading in coral reefs; with apex predators like sharks being replaced by mesopredators like groupers, snappers, and emperors, which may lack similar strength of non-consumptive effects on lower trophic groups 8 , 9 , 85 – 87 . However, our study highlights a possible role of mesopredatory reef fishes in regulating primary productivity through nutrient input and stoichiometric alteration, and thereby, the overall herbivory rates at the level of the reef. Despite the prevailing narrative of predators influencing ecosystem processes by exerting top-down controls 31 , 32 , 78 , 88 – 90 , our result highlights an equally significant bottom-up influence of predators, where they supply the limiting nutrients and maintain levels of primary and secondary productivity in nutrient-limited systems such as coral reefs 11 , 13 . It also emphasizes the importance of conservation efforts targeting predatory fish populations and underscores the need for sustainable fisheries management practices. Unsustainable targeted extraction of commercially important mesopredatory reef fishes can disrupt nutrient cycling and compromise primary productivity in coral reefs. This, in turn, could trigger cascading effects across trophic levels, but rather than following the traditionally known top-down pathway, these effects might originate from bottom-up processes. Methods • Study Site and Study Design The Lakshadweep Archipelago is a chain of coral atolls situated in the northern Indian Ocean off the west coast of mainland India ( Fig. 5 a ) . Lakshadweep comprises 12 coral islands and submerged banks ( Fig. 5 b ) . The coral atolls of Lakshadweep have shallow lagoons and are surrounded by barrier reefs 91 . The southwest monsoon and north-south orientation of most atolls have given rise to distinct windward and leeward aspects, which strongly influence the ecology and geography of Lakshadweep islands 50 , 60 . Although fishing has been the mainstay of the people of Lakshadweep, commercial fisheries have primarily been centered around the targeted fishing of pelagic skipjack tuna ( Katsuwonus pelamis ), leading to relatively undisturbed fish communities in the coral reefs 55 . However, commercial reef fishery is on rise in the archipelago, with different atolls of Lakshadweep experiencing various degrees of fishing pressure 62 . We sampled three atolls of the Lakshadweep Archipelago: Bitra, Kadmat, and Kavaratti ( Fig. 5 c, 5 d, 5 e ) . The islands represent a gradient of piscivorous fish density, with Bitra at the higher and Kavaratti at the lower end of the spectrum. Previous work from Lakshadweep suggests this gradient to be fishing-induced rather than natural 62 . This shift is most prominent in the atoll of Kavaratti, which had the highest fish biomass before reef fisheries became a mainstay on the island 92 . The island fishery is mainly carried out using the traditional hook and line method, which selectively harvests mesopredatory fishes from the reef, leaving the other functional groups, such as herbivores, relatively undisturbed 55 , 62 . In addition to the fishing-induced biomass gradient, in Bitra, we were able to sample a spawning aggregation site of Plectropomus areolatus (squaretail grouper) during spawning events. Spawning aggregations represent very high densities of fish biomass and can have long-lasting effects on nutrient dynamics and primary productivity in the aggregating reef, even after the aggregation is over 11 , 26 . The aggregation in Bitra is known to occur every new moon from November to April, potentially creating a hotspot of nutrient enrichment in these reefs throughout this period. Thus, we included the site in our predator biomass gradient. We sampled 11 sites across the three islands: two in Bitra, four in Kadmat, and four in Kavaratti ( Fig. 5 c, 5 d, 5 e ) . In Bitra, the sites were located on the eastern (sheltered) aspect of the lagoon; in Kadmat, three sites were located on the east (sheltered), and two were on the west (exposed); and in Kavaratti, two sites were located on the east (sheltered), and two were on the west (exposed). We collected all data for the current study between January 2024 and May 2024. • Field Assessments Piscivore and herbivore fish community We characterized the piscivorous and herbivorous fish community in each reef using underwater visual census (UVC). Three 50m × 10m (500 m 2 area per transect) belt transects were sampled at 12–14 meters depth. A minimum distance of 10m was maintained between two consecutive transects to ensure independence. Two observers conducted the UVCs. The observers swam parallel to each other along the transects. One observer noted the piscivorous fishes belonging to the families Serranidae, Haemulidae, Lethrinidae, Lutjanidae, Cirrhitidae, Malacanthidae, Aulostomidae, Fistularidae and Labridae. The other observer noted herbivorous fish species belonging to the families Scaridae, Kyphosidae, Acanthuridae and Siganidae. Only individuals with body sizes greater than 10 cm were noted during UVCs. We identified all the individuals on the transect to the species level and noted their abundance and size to the nearest centimeter. Algal cover and structural complexity Reef substrates were photographed every 10 meters on each belt transect (n = 6 in each transect) with a standard reference object in the frame. The images were analyzed using the software ImageJ to estimate the percentage of turf algal cover within a 1 m × 1 m area 93 . We averaged the estimates from the three transects to obtain the percentage algal cover of the reef. We measured structural complexity as the average vertical height of the reef on the belt transects. We took measurements at every 5m distance (n = 10 in each transect). Estimates from the three transects were averaged to obtain the structural complexity of the reef. Algal growth rates through herbivore exclusion We established herbivore exclusion cages (20cm × 20cm × 20cm) to quantify algal growth. Box-shaped cages were constructed using plastic mesh (mesh size 2cm diameter) and cable ties. We selected areas of rigid substrate at a depth of 12-14m on the reef that were covered with algal turfs while avoiding farming damselfish territories and heavily sediment-laden substrates. The cages were operational for only 14–21 days and, therefore, did not accumulate significant amounts of fouling algae over the experimental period. We set up four cages in each site and maintained a minimum distance of 10 meters between two adjacent exclosures (n = 44). The exclosures were attached to the reef substrate directly using cable ties. The cages ensured that herbivorous reef fishes were excluded from feeding within the enclosed area. However, the mesh size allowed smaller-sized herbivorous fishes (< 2cm width) to enter the cages and ensured that light and water flow were not impeded. To quantify algal growth rates, the height of 10 fronds of turf algae was measured underwater using the depth probe of a vernier calliper on the day of cage installation. The depth probe yields the exact distance between the tips of the calliper. This distance between the tips was recorded by imprinting it on a saltwater-resistant pressure-sensitive poster adhesive (blue tac) attached to an acrylic board. The imprint was later measured on the surface using a digital vernier calliper, and the values up to one decimal point were noted down in millimeters 94 . The process was repeated the day the cages were removed from the reefs. The average algal height difference between the first and final days was divided by the number of days the exclosure was operational in the reef to obtain daily algal growth rate. As initial turf length is known to affect turf growth 95 , we calculated proportional turf growth (change in turf height per month/initial height of turf) for each exclosure. The value was multiplied by 30 to obtain proportional algal growth rate for a month. Herbivory rates through in-situ exclosures A 20 cm × 20 cm area was marked using a fishing buoy adjacent to the herbivore exclusion cages and served as an open herbivory plot (n = 44). A minimum distance of 1 meter was maintained between the exclosure and the control plot to avoid cage effects. The height of 10 turf algal fronds was measured using the same method as inside the cages. Daily herbivory rate was estimated as the difference between daily algal growth inside the exclosures and the paired open herbivory plot present next to it at the end of the period. The value was multiplied by 30 to get the herbivory rate in mm/month. Anti-predatory behaviour through focal observations Across the predator biomass gradient, we carried out focal observations on a candidate fish species of lower trophic level, Ctenochaetus striatus , to test the presence of non-consumptive effects of predators on prey fish species. We chose C. striatus as the candidate species because it is one of the most ubiquitous and abundant species in Lakshadweep, and the juveniles are known to be predated upon by mesopredatory reef fishes 60 , 75 . Sampling was conducted during the day between 0900 and 1200 when fishes are known to be active, and all the sampled individuals were chosen opportunistically. We followed 10 C. striatus individuals at each sampling site (n = 110). C. striatus individuals with body sizes greater than 18 cm were sampled to avoid behavioural variations due to body size dissimilarity. This body size is also speculated to be out of direct predation threat by coral reef mesopredators and is much greater than the average prey size of coral reef fishes 61 , 77 . Thus, they are deemed suitable for examining the non-consumptive effects of predators on herbivore behaviour. The focal individuals were filmed for 4 minutes. Consecutive observations were separated spatially by at least 10 meters to avoid sampling the same individuals. We swam in one direction between two successive focal follows to avoid repeated observations of the same individual. All the observations were conducted within a narrow depth range of 10–13 meters. The videos were analyzed later to observe the proportion of time spent in vigilance by the individual. Our observations indicated that individuals resumed feeding within 30 seconds of video recording, and did not show any signs of diver-induced disturbance like accelerating away from the observer or repeated hiding. Hence, we excluded the first 30 seconds of the video. If the fish could not be seen because it had moved behind a big boulder after 30 seconds, we waited until it could be seen again in the video and restarted analyzing the video. The videos were analyzed for a total of 3-minutes. Time spent in vigilance is widely considered to be a reliable metric of understanding anti-predatory response of prey to predation threat, with increasing predation threat being associated with an increased amount of time spent in vigilance by prey individuals 96 , 97 . Thus, we noted down time spent in vigilance by the C. striatus individuals during the 3-minute. Vigilance was defined as the behavioural state in which the focal individual swam with its face pointed towards the water column or at a positive angle to the reef substrate ( Fig. 4 a ) 98 . • Quantification and Statistical Analysis Quantifying predatory and herbivorous fish biomass We used fish identity, body size and abundance data obtained from UVCs to estimate the biomass using the formula W = a × L b , where W = estimated biomass, L = observed length of the fish, and a and b values are standard fish values obtained for each species from Fishbase 99 . Total biomass at the level of the transect was divided by the area of each transect to obtain fish biomass per unit area. A mean of the transect-level values was estimated to obtain site-level fish biomass per unit area. Previous studies suggest the existence of a fishing-induced predatory fish biomass gradient in the atolls of Lakshadweep 62 . Our underwater visual census data also suggested the presence of a mesopredator biomass gradient across the 11 sampled sites in Lakshadweep. We also found a strong positive correlation between predator biomass and herbivore biomass ( r = 0.9 ). Predator and herbivore biomass were thus log-transformed to account for the parametric correlation between the two variables and avoid multicollinearity issues in subsequent models ( r = 0.65 ). Controlling for pelagic nutrient subsidies The oceanic coral reefs typically thrive in phosphorus-limited seascapes, and pelagic nutrients vectored by planktivorous fishes and piscivorous fish excretion are considered to be the two major sources of phosphorus in such systems 11 , 59 , 100 – 103 . Numerous studies have established planktivore-mediated pelagic phosphorus input as a ubiquitous and salient source of nutrients in offshore coral reef ecosystems 100 , 104 . In this study, we were unable to estimate pelagic phosphorus input in the reefs of Lakshadweep. However, studies on plankton biomass and hydrodynamics suggest that pelagic plankton transport to coral reefs through subsurface waters is mediated by wind and wave exposure 101 . The north-south orientation of Lakshadweep’s atolls gives rise to two distinct wave exposure regimes: the calmer and sheltered east, or the leeward aspect, and the turbulent and exposed west, or the windward aspect 50 , 60 . On average, the windward western aspect of Lakshadweep atolls experiences about three times greater wave power across the season compared to the leeward eastern aspect, with the contrast being highest during the Indian summer monsoon 105 . These contrasting exposure regimes likely translate to differences in pelagic nutrient subsidies. Thus, to statistically control for pelagic nutrient subsidies, we included the physical aspects of the sites in our regression models. Productivity along predator biomass gradient Estimating consumer-derived nutrient inputs We used data obtained from UVCs to estimate consumer-derived nutrient input in the water. We used a global consumer-derived nutrient input dataset to calculate size-specific nitrogen and phosphorus input in the system for each species of herbivore and piscivore fish 106 . If the nutrient input value for any observed body size for a species was unavailable, the nearest available body size (difference of ≤ 2cm) in the dataset was considered to calculate the nutrient input. If the values were not present for any particular species, the values available for a congeneric species were considered for the calculation 107 . We converted the absolute mass of nitrogen and phosphorus input to moles by dividing each by the atomic mass of the respective element. The N:P molar ratio (ratio between the amounts of elements in moles) was calculated for all the sampled sites. We estimated the mean N:P molar ratio and calculated the standard error using a non-parametric bootstrapping method with 2000 iterations to infer the relative role of herbivores and piscivores in supplying nutrients in the system. Estimating algal growth rates We employed linear mixed-effects models to investigate the impact of herbivore and piscivore biomass on algal growth rates. Proportional algal growth rate was modelled against log-transformed predator and herbivore biomass. Aspect was added as a fixed effect in the model. Site identity was included as a random intercept to account for any other factors at the site level that influence algal growth rates. Both continuous predictors were scaled before being included in the model. Quantifying herbivore productivity Recent modeling advancements have enabled the calculation of productivity of reef fish assemblages by combining underwater census data with predicted growth and size-based mortality rates 82 , 108 . Thus, we calculated herbivorous fish productivity using fish species identity, size and abundance obtained from the underwater visual census 108 , 109 . The census data was filtered only to include grazers, scrapers and excavators - the herbivore functional groups that feed on turf algae. We estimated the standardized growth parameter, K max , for all individuals using observed body size, diet and a mean sea surface temperature of 28°C 108 . Using the estimated species and size-specific K max values, we estimated the age of the individuals using the individual age framework and estimated biomass gain through somatic growth over a day for all the individuals 108 , 110 . Finally, by subtracting a per-capita loss due to natural mortality, we calculated productivity as the biomass gained per day by all surviving individuals at the level of the transect. We converted the value per transect to productivity per unit hectare of area per day. Productivity was modelled as a function of predator biomass, resource availability, structural complexity and aspect of the site using a generalized linear mixed-effects model with gamma error distribution and log-link. Resource availability was quantified as the product of site-level percentage algal cover and average daily absolute algal growth rate obtained from the exclosures. We used site identity as a random intercept to account for any inherent variability in productivity within a site. Predator biomass was log-transformed and all the continuous predictors were scaled before being used in the model. Herbivory rate along predator biomass gradient Estimating reef-wide herbivory rates Herbivory rates obtained from the in-situ exclosures were modelled as a function of log-transformed predator and herbivore biomass using a linear mixed-effects model. Herbivore biomass comprised the total biomass of grazers, scrapers and excavators, as they are known to feed on turf algae, thus contributing to herbivory. Aspect was included as a fixed effect in the model, as herbivory rates are known to be influenced by wave exposure regimes 60 . Site-level percentage cover of turf algae was added as a fixed effect, as the availability of algal resources can determine the levels of herbivory in any unit area of the reef. We used site identity as a random intercept in the model. Both continuous predictors were scaled before being used in the model. Quantifying community-level herbivory We estimated monthly community-level herbivory on turf algae in terms of grams of carbon ingested per unit area by the herbivorous fish community present at the site. Herbivory rates were estimated by combining underwater visual census data of herbivores with a global carbon ingestion dataset 106 . We calculated size- and species-specific daily carbon ingestion by herbivorous reef fishes belonging to the functional groups: grazer, scraper and excavator. If the ingestion value for any observed size of a species was missing from the dataset, the value for the nearest body size (with a difference of ≤ 2 cm) was used to calculate herbivory rates. If a species from our study area was absent from the dataset, we used data from a congeneric species that was present in the dataset. We calculated the mean herbivory rate at the level of each transect and converted it to grams of carbon ingested per unit square meter of the reef per day. We modelled community-level herbivory rates as a function of log-transformed predator biomass, percentage algal cover, structural complexity and aspect of the site using a generalized linear mixed-effects model with gamma error distribution and log-link. We used site identity as a random intercept and scaled all the continuous predictor variables before using them in the model. Assessing anti-predatory behaviour Time spent in vigilance was divided by the total observable time to obtain the proportion of time spent in vigilance. We used generalized linear mixed-effects models with a beta error distribution and logit link function to model proportion of time spent in vigilance. Log-transformed predator and herbivore biomass were added as predictor variables. Resource availability was quantified as the product of site-level proportion of algal cover and mean daily absolute algal growth rate (mm) obtained from the exclosures and was added as a fixed effect. Aspect was added as a fixed effect to account for wave exposure regime. Structural complexity was added as a predictor. Site was added as a random intercept to account for any inter-site variability. All continuous predictors were scaled before being used in the model. Validity and Diagnostics of Models Models were fitted based on the distribution of the data as revealed by the preliminary analyses. The model fit for linear mixed-effects models was visually examined using a plot of model residuals against the fitted values to check for homoskedasticity, a Q-Q plot of residuals to check normality and a histogram of the model residuals to check for normality. The Shapiro-Wilk test for normality was used on the residuals of the datasets that were difficult to assess visually for normality. The Variance Inflation Factor (VIF) was calculated for each fitted model, ensuring the absence of multicollinearity between predictors. Model fit for generalized linear mixed-effects models with gamma error distribution and log-link was assessed using plots of raw residuals, Pearson's residuals and deviance residuals, a plot of simulated residuals against the model residuals and a Q-Q plot of residuals. All models were checked for the presence of overdispersion. All analyses were performed using R version 4.4.2 111 . Package “lme4” was used to run linear mixed-effects models 112 . Package “glmmTMB” was used to run generalized linear mixed-effects models with beta and gamma error distributions 113 . Package “car” was used to check for the variance inflation factor 114 . Package “DHARMa” was used to check the model fit of the generalized linear mixed-effects models with gamma error distribution 115 . Package “visreg” was used to extract data from models 116 , and the package “tidyverse” was used for data cleaning and visualization 117 . Package “performance” was used to check for overdispersion 118 . Herbivore productivity was estimated using the package “rfishprod” 108 . Declarations Funding Funding for this work was provided by the Department of Atomic Energy, Government of India to National Centre for Biological Sciences (Project Identification No: RTI 4006); Shri AMM Murugappa Chettiar Research Centre (MCRC), Ashraya Hasta Trust and Rohini Nilekani Philanthropies to RA; and National Geographic Society (Grant No: NGS 96905R-22) to RK. The Fisheries Society of the British Isles supported AP through a Travel Grant during his tenure at Lancaster University. AP was awarded the Infosys Travel Award by National Centre for Biological Sciences to attend and present the results of this study at the International Conference for Young Marine Researchers 2024, Bremen, Germany. The Spanish National Research Council supported TA through the Memorandum of Understanding between Centre D’Estudis Avançats de Blanes (CEAB, CSIC) and Nature Conservation Foundation (NCF). Permission statement I confirm that the required permissions to conduct field work in the atolls of Lakshadweep Archipelago were obtained from the Department of Environment and Forests, Union Territory of Lakshadweep (F. No. 1/5/2023-E&F/1045). Should you need any further documentation or information, please feel free to contact me. Competing interests The authors declare no competing interests. Author Contribution AP, RK, RA and TA conceptualized and designed the study. AP, HT, RK, RA and TA collected data. AP and SP analyzed and summarized the data for the manuscript. AP curated and visualized the data and wrote the first draft. All authors contributed equally towards reviewing and approving the final draft. Acknowledgement We thank the Department of Environment and Forests, Union Territory of Lakshadweep, for the timely permit and support to conduct this study (F. No. 1/5/2023-E&F/1045). We thank the NCBS–TIFR, Nature Conservation Foundation, and Wildlife Conservation Society–India for their institutional, administrative, and logistical support. We thank all our funders for the generous funding that made this work possible. We thank Siya Bhagat, Wenzel Pinto, and Abdul Rauf for their assistance with data collection and Sidharth Sankaran for transcribing the benthic photoquadrats. We thank Anwar Hussain, M.K. Ibrahim (Ummini), and everyone at ESMUC and LakScuba for their logistical support during the fieldwork. We are deeply grateful to the people of Bitra, Kadmat and Kavaratti for their unwavering support. We thank James Robinson and Renato Morais for their advice on the fish productivity analysis. We are grateful to Nick Graham, Casey Benkwitt, Jennifer Appoo, Mayank Kohli, Pritha Dey, Kulbhushansingh Suryawanshi and Mayuresh Gangal for their critical input and feedback on different aspects and stages of the study. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7365908","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":505835243,"identity":"dac02655-9afb-44a5-960f-c050f5561cdc","order_by":0,"name":"Anish Paul","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYFACxgZmEMXH39j44AOQwcZOrBY2icOHDWeAGMxE2APRwpCWJs0D5+IB/LObmz8X7rBLbGM4YyZt82ubPB8zA+OHjzm4tUjcOdgmPfNMcmIbc4+xdW7fbcM2ZgZmyZnb8FhzA6iYt40ZZIvh7dye24xALWzMvHi0yN9IbP7M21YP1JJjIG3Zc9ueoBaDG4kN0rxth4Fa0pKkGX7cTiSoxRDoMGneM8eN20CB3NtwO7mNmbEZr1/kbqQ//sy7o1q2HxSVP/7ctp3f3nzww0d83gcBxgYYow2FS4wWhj+EFY+CUTAKRsHIAwAlwFKlPSgfEAAAAABJRU5ErkJggg==","orcid":"","institution":"National Centre for Biological Sciences","correspondingAuthor":true,"prefix":"","firstName":"Anish","middleName":"","lastName":"Paul","suffix":""},{"id":505835244,"identity":"56533f2a-7b1c-4fab-a0f0-ee4d2d61f037","order_by":1,"name":"Harshul Thareja","email":"","orcid":"","institution":"National Centre for Biological Sciences","correspondingAuthor":false,"prefix":"","firstName":"Harshul","middleName":"","lastName":"Thareja","suffix":""},{"id":505835245,"identity":"15e77101-172d-46e3-8955-300d63757711","order_by":2,"name":"Rohan Arthur","email":"","orcid":"","institution":"Nature Conservation Foundation","correspondingAuthor":false,"prefix":"","firstName":"Rohan","middleName":"","lastName":"Arthur","suffix":""},{"id":505835246,"identity":"9bae73ae-c74c-4b44-be4e-c3179d930011","order_by":3,"name":"Teresa Alcoverro","email":"","orcid":"","institution":"Centre D’Estudis Avançats de Blanes (CEAB – CSIC)","correspondingAuthor":false,"prefix":"","firstName":"Teresa","middleName":"","lastName":"Alcoverro","suffix":""},{"id":505835247,"identity":"d08633fb-167e-4bd1-ac07-9b694eb62b45","order_by":4,"name":"Sandeep Pulla","email":"","orcid":"","institution":"National Centre for Biological Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sandeep","middleName":"","lastName":"Pulla","suffix":""},{"id":505835249,"identity":"3638340e-a33f-490b-b680-812cbaed53a8","order_by":5,"name":"Rucha Karkarey","email":"","orcid":"","institution":"Lancaster University","correspondingAuthor":false,"prefix":"","firstName":"Rucha","middleName":"","lastName":"Karkarey","suffix":""}],"badges":[],"createdAt":"2025-08-13 14:23:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7365908/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7365908/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-34145-6","type":"published","date":"2025-12-30T15:57:37+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90067806,"identity":"cfbe8a7c-9ee9-4549-839a-bbc4f6f71eb8","added_by":"auto","created_at":"2025-08-28 05:55:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29076,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eNitrogen to Phosphorus molar ratio comparison between herbivore and piscivore excreta across sites. Error bars represent bootstrapped standard error around the mean. The dotted line represents the classical Redfield Ratio (16:1).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7365908/v1/0960ffbd7499842d47990801.png"},{"id":90068028,"identity":"40d04e7d-544b-456b-b186-6f674a1d250f","added_by":"auto","created_at":"2025-08-28 06:03:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77560,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePrimary and secondary productivity increases with predator biomass. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Algal growth rate was measured as the monthly average increase in algal frond heights in the absence of herbivory. Algal growth rate increases with increasing log-transformed predator biomass. Points represent observed data (n = 44), and lines represent the partial predicted values from the linear mixed-effects model, with all other predictors set at their mean. The shaded regions represent the 95% confidence intervals. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eb.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Herbivorous fish productivity was estimated using species identity, size and abundance of grazers, scrapers and excavators obtained from the underwater visual census. Herbivorous fish productivity shows a positive correlation with log-transformed predator biomass. Points represent observed data (n = 33), and lines represent the partial predicted values from the generalized linear mixed-effects model with gamma error distribution and log-link, with all other predictors set at their mean. The shaded regions represent the 95% confidence intervals.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7365908/v1/c7ec912ff24388aa5839b004.png"},{"id":90067807,"identity":"b081d28e-fe1a-4dc2-a4ab-5c8d8d1eb174","added_by":"auto","created_at":"2025-08-28 05:55:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":72889,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eHerbivory rates increase along the predator biomass gradient, suggesting that, in the absence of strong consumptive and non-consumptive effects of predation, predators can facilitate herbivory. We employed two complementary approaches to estimate herbivory: \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Site-level Herbivory rates were measured as the difference between monthly algal growth inside the exclosures and that of the paired open herbivory plot located next to it. Site-level herbivory rate positively correlates with log-transformed predator biomass. Points represent observed data (n = 44), and the line represents the partial predicted values from the linear mixed-effects model, with all other predictors set at their mean. The shaded region represents the 95% confidence interval. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eb.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003eCommunity-wide herbivory rates, measured in terms of grams of carbon ingested per unit area by the herbivorous fish community, shows a positive correlation with log-transformed predator biomass. Points represent observed data (n = 33), and the line represents the partial predicted values from the generalized linear mixed-effects model with gamma error distribution and log-link, with all other predictors set at their mean. The shaded region represents the 95% confidence interval.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7365908/v1/f9044d278def8f34cf5dccf8.png"},{"id":90068029,"identity":"32ca274a-a635-42fe-8be9-88ac34afbf90","added_by":"auto","created_at":"2025-08-28 06:03:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":227736,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTime spent in vigilance by individuals of a hyperabundant prey species remains unchanged along the predator biomass gradient. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea. \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eAn adult Ctenochaetus striatus showing vigilance behaviour during our observation. The face of the individual is directed toward the water column at a positive angle to the reef substrate. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eb.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Proportion of time spent in vigilance by C. striatus individuals shows no statistically significant relationship with increasing log-transformed predator biomass. Points are observed data and lines represent the partial predicted values from the generalized linear mixed-effects model with all other predictors set at their mean. The shaded regions represent the 95% confidence intervals.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7365908/v1/96c3d6f4575f21f0d2ad180a.png"},{"id":90067809,"identity":"eae2f017-0883-4220-9667-fa898f0e0e08","added_by":"auto","created_at":"2025-08-28 05:55:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":105747,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eWe conducted the study along a mesopredatory reef fish biomass gradient in the Lakshadweep Archipelago. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003eLakshadweep Archipelago is situated in the northern Indian Ocean and is part of the Chagos-Laccadive Oceanic Ridge. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eb.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Lakshadweep comprises 12 coral atolls. We sampled 11 sites (red dots) across three atolls: \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ec.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Bitra, \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ed.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003eKadmat and \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ee.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Kavaratti, in two exposure regimes: sheltered (East, “E”) and exposed (West, “W”). Red dots represent sampling sites within each atoll.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7365908/v1/72736be36aa5421e380c6ef8.png"},{"id":99545391,"identity":"d6e02d1c-4d72-4a9b-8a92-311ada19404f","added_by":"auto","created_at":"2026-01-05 16:07:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2035167,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7365908/v1/736e2a98-f2ff-4107-b100-4cef8e9bd4cd.pdf"},{"id":90067810,"identity":"5bc09e4c-94a3-47b6-849b-82760bf23485","added_by":"auto","created_at":"2025-08-28 05:55:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":225851,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7365908/v1/f994ac1b47196eccece92e85.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predators facilitate herbivory in nutrient-limited marine ecosystems","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePredator-prey interactions are a major governing process in natural ecosystems \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Predators can directly influence the size, demography, and population structure of prey, as well as influence the community composition of an ecosystem \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Apart from directly influencing the prey population through predation, predators also generate a \u0026lsquo;landscape of fear\u0026rsquo; \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, where prey species must remain vigilant not only in the presence of predators but even in their absence, constantly apprehensive about the potential of an imminent attack \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, the consumptive and non-consumptive top-down effects of predators are not prominent across all ecosystems \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, and predator-mediated trophic cascades are considered to be \u0026lsquo;exceptions rather than rule\u0026rsquo; in ecosystems with complex trophic structures \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eBesides exerting top-down effects, predators can also influence bottom-up processes by nutrient input from external sources or by altering the stoichiometry of nutrients available to primary producers \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. These effects may be particularly evident in oligotrophic and mesotrophic ecosystems where nutrient availability limits productivity. In such systems, consumer-derived nutrients could modulate primary productivity and, subsequently, consumption, i.e., herbivory \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. However, much of our current understanding of top predators\u0026apos; influence on ecosystem processes comes from terrestrial and pelagic ecosystems, where their lower abundance and biomass relative to lower trophic levels may limit their nutrient-mediated effects \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In contrast, in ecosystems where predators constitute a high proportion of total biomass, they can potentially influence the rates of ecosystem processes through nutrient-mediated pathways \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. This potential facilitation of productivity through predatory fish-derived limiting nutrients has rarely been explored, with only a few examples from seagrass ecosystems and low-diversity coral reefs in the Caribbean \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Additionally, while the role of predators in structuring herbivory through top-down effects on herbivore populations has been well documented across ecosystems \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, how predator-derived nutrients could influence herbivory, through their effects on primary productivity, remains underexplored \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003ePredatory fishes constitute a significant proportion of the standing biomass in undisturbed reefs, often much greater than any terrestrial system, and frequently form permanent or temporary aggregations to feed and/or reproduce \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, the complexities of food webs in coral reefs, associated with uncertainties in their trophic position and diet inconsistencies, have made the role of predators in generating trophic cascades in coral reefs ambiguous and highly context-specific \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. While predator removal has been reported to promote benthic recovery \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, studies have also reported the co-occurrence of high coral cover and high predator biomass in reefs \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Additionally, owing to their diet, excretory inputs from predatory fish are a major source of phosphorus, a limiting nutrient in coral reef ecosystems that can determine algal productivity \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Thus, in the absence of strong consumptive and non-consumptive effects of predation, predators can potentially mediate herbivory levels in coral reefs by increasing algal production, thereby increasing the algal-removal potential of herbivores through nutrient-mediated pathways \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. In coral reefs, herbivory is a key process in maintaining the stability and health of the ecosystem \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, as it confers resilience to reefs by removing algae that compete with coral recruits for substrate, nutrients, growth, reproduction, and survivorship \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eUnpacking these nuanced trophic relationships becomes particularly important in the light of increasing fishing impacts on reefs. As true apex predators, such as sharks, decline due to overfishing, mesopredatory species, like groupers, snappers, and emperors, are attaining the role of top predator and are also increasingly becoming fisheries targets. We lack the understanding of how their removal will impact essential ecosystem processes in coral reefs \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. It is therefore crucial to investigate the influence of predatory fishes on algal production and herbivory levels in reefs, especially where mesopredators can play essential bottom-up roles as nutrient providers in nutrient-limited systems.\u003c/p\u003e\n\u003cp\u003eThe islands of the Lakshadweep Archipelago are ideally suited to test the role of mesopredators in influencing bottom-up and top-down processes in nutrient-limited ecosystems. Some reefs of Lakshadweep have been relatively unfished until recently \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Nutrient-limited waters and the relatively lightly fished fish community of some of the Lakshadweep\u0026rsquo;s coral atolls make it a suitable system to study the effect that mesopredatory fishes may have on herbivory levels by altering the bottom-up pathways through nutrient input. We employed a combination of experimental and observational methods to quantify herbivore and piscivore biomass, the stoichiometry of nutrient contributions by herbivores and predators (based on biomass and species-specific nutrient input rates), algal growth rates, herbivore productivity, herbivory rates and prey anti-predatory behaviour along a fishing-induced mesopredatory reef fish biomass gradient to evaluate support for bottom-up vs top-down processes in the coral reefs of Lakshadweep. The specific questions we addressed were:\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003ea) Does primary and secondary productivity increase with increasing predator biomass in a nutrient-limited coral reef ecosystem?\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003eb) Does herbivory rate vary in response to variations in predator biomass?\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003ec) Is there evidence for top-down non-consumptive effects in the form increasing vigilance with increasing predator biomass?\u003c/p\u003e\n\u003c/span\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003ea) Does productivity increase with increasing predator biomass in a nutrient-limited coral reef ecosystem?\u003c/h2\u003e\n \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\n \u003ch2\u003eConsumer-derived nutrients\u003c/h2\u003e\n \u003cp\u003eThe mean molar ratio of nitrogen to phosphorus across sites was 52.3:1 (\u0026plusmn;\u0026thinsp;8.1, SE) for herbivore excreta, whereas it was considerably lower, at 17.5:1 (\u0026plusmn;\u0026thinsp;0.47, SE) for piscivore excreta \u003cstrong\u003e(Fig.\u0026nbsp;1\u003c/strong\u003e\u003cstrong\u003eFigure\u003c/strong\u003e \u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003ePrimary productivity\u003c/h3\u003e\n\u003cp\u003ePrimary productivity was measured as the monthly proportional growth rate (change in turf height per month/initial height of turf) of turf algae inside herbivore exclosures. Proportional algal growth rate increased by 0.41 month\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (95% CI 0.18 to 0.63, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.001\u003c/em\u003e) per unit standard deviation increase in log-transformed values of predator biomass \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea, \u003cstrong\u003eSupplementary Material 1)\u003c/strong\u003e. In contrast, proportional algal growth rate was not significantly influenced by herbivore biomass \u003cstrong\u003e(Supplementary Material 1)\u003c/strong\u003e. Aspect also significantly influenced algal growth rate, with the exposed western aspect showing a reduction in proportional growth rate by 0.61 month\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (95% CI 0.24 to 0.99, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.002\u003c/em\u003e) \u003cstrong\u003e(Supplementary Material 1, 2)\u003c/strong\u003e.\u003c/p\u003e\n\u003ch3\u003eSecondary productivity\u003c/h3\u003e\n\u003cp\u003eHerbivorous fish productivity, i.e., secondary productivity, increased by a factor of 1.41 (95% CI 1.07 to 1.85, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.013\u003c/em\u003e) per unit standard deviation increase in log-transformed values of predator biomass \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb, \u003cstrong\u003eSupplementary Material 3)\u003c/strong\u003e. Secondary productivity also increased by a factor of 1.40 (95% CI 1.08 to 1.81, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) with an unit standard deviation increase in structural complexity of the site \u003cstrong\u003e(Supplementary Material 3)\u003c/strong\u003e. Resource availability and aspect of the site had no statistically significant relationship with herbivore productivity \u003cstrong\u003e(Supplementary Material 3)\u003c/strong\u003e.\u003c/p\u003e\n\u003ch3\u003eb) Does herbivory rate vary in response to variations in predator biomass?\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eReef-wide herbivory rate\u003c/h2\u003e\n \u003cp\u003eReef-wide herbivory rate was calculated as millimeters of algal frond lost per month from 20 cm \u0026times; 20 cm plots. Predator biomass had a positive influence on herbivory rate, with a unit standard deviation increase in the log of predator biomass associated with a 0.64 mm/month increase in algal frond loss (95% CI 0.12 to 1.16, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.017\u003c/em\u003e) within a 20 cm \u0026times; 20 cm plot \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea, \u003cstrong\u003eSupplementary Material 4)\u003c/strong\u003e. Herbivore biomass, percentage algal cover, and aspect had no statistically significant influence on herbivory rates \u003cstrong\u003e(Supplementary Material 4)\u003c/strong\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eCommunity-level herbivory rate\u003c/h3\u003e\n\u003cp\u003eThe community-level herbivory rate, calculated using the underwater visual census data, increased by a factor of 1.51 (CI 1.18 to 1.93, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) per unit standard deviation increase in log-transformed predator biomass \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb, \u003cstrong\u003eSupplementary Material 5)\u003c/strong\u003e. Herbivory rates also increased by a factor of 1.30 (CI 1.03 to 1.65, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.028) per unit standard deviation increase in structural complexity of the site \u003cstrong\u003e(Supplementary Material 5)\u003c/strong\u003e. Percentage algal cover and aspect of the site had no statistically significant relationship with community-level herbivory rates \u003cstrong\u003e(Supplementary Material 5)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec) Is there evidence for top-down non-consumptive effects in the form increasing vigilance with increasing predator biomass?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eNone of the predictors, including predator biomass, had any statistically significant relationship with the proportion of time spent in vigilance by \u003cem\u003eC. striatus\u003c/em\u003e individuals \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb, \u003cstrong\u003eSupplementary Material 6)\u003c/strong\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePredators input key nutrients into reefs \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, which can enhance algal productivity \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Our results indicate that predators can also indirectly enhance reef-scale herbivory via nutrient-mediated pathways and may play a key role in the functioning of coral reef ecosystems.\u003c/p\u003e\u003cp\u003eOur results suggest that predatory fishes supply nutrients in reefs at an N:P molar ratio closer to the classical Redfield Ratio of 16:1 and much lower than that of herbivorous fishes \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. This suggests that there is greater proportional phosphorus than nitrogen in predator excreta, which can thus influence primary productivity in a phosphorus-limited system \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. This conforms with studies from other parts of the world, establishing predator excreta as a critical source of phosphorus in nutrient-limited tropical marine systems \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eConsistent with the previous studies from Lakshadweep, site aspect had the greatest effect on algal growth rates, with the more exposed west having a relatively lower growth rate than the sheltered east \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. However, our results also indicate a significant positive relationship between primary productivity and predator biomass after statistically controlling for pelagic nutrient subsidies through aspect. Our results thus suggest that, aside from their traditional role in mediating top-down processes, predatory fishes can potentially enhance algal growth rate, i.e., primary productivity, in nutrient-limited atoll systems. This highlights the role of predator-derived nutrients and thus, predators, in influencing bottom-up pathways \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eConsistent with our expectations, herbivore productivity increased with predator biomass in the reefs of Lakshadweep \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. In our estimation of herbivore productivity, we only included herbivorous reef fishes with body sizes greater than 10cm. This body size far exceeds the average size of prey (1.75 cm, 95% CI 0.8 to 3.65) in coral reefs \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Therefore, the threat of predation on the sampled herbivorous fish is likely to be insignificant, indicating that the observed herbivore productivity is unlikely to drive the observed predator biomass in our study. Additionally, the targeted fishing pressure towards mesopredatory reef fishes in the atolls of Lakshadweep leaves the herbivorous fish community relatively undisturbed \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e, which in turn reduces the possibility of fishing pressure confounding the relationship between herbivore productivity and predator biomass. Thus, we suggest that the positive correlation between predatory fish biomass and herbivorous fish productivity can potentially be caused by indirect facilitation of herbivorous by piscivorous fishes, where the nutrient-enriched seascape generated by predator-derived nutrients (primarily increased phosphorus availability in a phosphorus-limited ecosystem) leads to greater primary productivity, and thus enhances secondary productivity \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Similar patterns have been observed in the reefs of Australia, where novel fish communities, resulting from tropicalization, increased the availability of turf algae, which in turn increased herbivore productivity \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Studies from similar oceanic atolls in the Seychelles support a similar hypothesis, where enhanced nutrient availability from seabird excreta has increased secondary productivity via increased turf growth rates (primary productivity) \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. While nutrient input from reef fishes is expected to be much less compared to that of seabirds \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, studies on grunts (Haemulidae) and damselfishes (Pomacentridae) have shown that fish-derived nutrients can increase algal and coral growth rates on a smaller spatial scale \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e,\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. However, further studies examining isotopic signatures in algae and fish tissues, fine-scale oceanographic patterns, and experimentally manipulating consumer biomass, nutrient availability and stoichiometry are required to definitively validate the potential indirect effects of predators on herbivore productivity in coral reefs.\u003c/p\u003e\u003cp\u003eHerbivory is considered to be a critical ecosystem function in the coral reefs \u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. Spatial patterns of herbivory are known to have dramatic influences on the structure, composition and distribution of plant and algal communities in both terrestrial and marine environments \u003csup\u003e\u003cspan additionalcitationids=\"CR69 CR70 CR71 CR72\" citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. Our results indicate a statistically significant positive correlation between predator biomass and herbivory rates.\u003c/p\u003e\u003cp\u003eAlthough mesopredators strongly dictate herbivorous fish demography through direct predation during their juvenile state \u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e,\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e, predation threat on herbivores reduces significantly with increasing body size \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e,\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e,\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. This suggests a negligible direct consumptive effect of piscivores on observed herbivores (body size\u0026thinsp;\u0026ge;\u0026thinsp;10cm) in our study. However, the non-consumptive effects of predation threat can alter feeding behaviour of prey, even in the absence of an imminent predation event \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. Increased perceived predation threat increases rates of feeding by individuals \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, thus potentially leading to greater herbivory at the level of the reef. However, presence of non-consumptive effects on fishes of lower trophic groups is known to be weak \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Our focal fish observations of a hyperabundant primary consumer species in Lakshadweep, \u003cem\u003eCtenochaetus striatus\u003c/em\u003e, further evidenced this. Along the mesopredatory fish biomass gradient, the adult \u003cem\u003eC. striatus\u003c/em\u003e individuals exhibited no change in anti-predatory behaviour, suggesting the absence of a strong non-consumptive effect of predation on adult individuals of prey species. Thus, we argue that observed patterns in herbivory rates along the predator gradient are less likely to be driven by faster consumption of algae as a response to perceived predation threat \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Studies suggest that herbivore biomass in coral reefs strongly correlates with turf algal productivity rather than the total available biomass of turf algae \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. Hence, we argue that the observed pattern is likely due to enhanced primary productivity resulting from predator-derived nutrients, which increases resource availability and consumption in reefs with greater predator biomass \u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. Thus, our results indicate that in the absence of strong consumptive and non-consumptive effects on herbivores, predators can potentially facilitate herbivory in nutrient-limited systems.\u003c/p\u003e\u003cp\u003eEstablishing the causal effects of predator-derived nutrients on community-wide herbivory and disentangling the effects of other factors, such as resource availability, nutrient composition of the benthos, structural complexity, sedimentation rates, local hydrodynamics and spatial configuration of sites, requires further investigation using transplant experiments of algal mats and bulk or compound-specific stable isotope tracers across trophic levels \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan additionalcitationids=\"CR83\" citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e. However, our study draws attention to a vastly understated role of predators in a system where their top-down role is often debated. It highlights the nuances of trophic interactions and ecosystem functions, aiming to improve the understanding of trophic pathways in complex ecosystems such as coral reefs. Recently, an extensive body of work has established another top trophic group of the near-shore ecosystems, the seabirds, as an integral part of nutrient dynamics in coral reefs \u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. While mesopredatory fishes can have much less quantity of nutrient input and spatial coverage than nesting seabirds and do not bring in new nutrients from external sources, we argue that they can also play an important role in coral reef nutrient dynamics due to greater proportion of phosphorus in their excreta, especially in atolls where other sources of nutrients are often limiting. Although more work is required to understand the nuances of nutrient fluxes and patterns of productivity and herbivory under varying physicochemical and ecological conditions, our results indicate that predatory fishes, specifically mesopredators, that may not exert a strong top-down influence on the adult life stages of lower trophic levels, may potentially impact the functions performed by these groups by affecting nutrient dynamics and productivity in nutrient-limited systems.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePervasive targeted fishing activities have led to a trophic downgrading in coral reefs; with apex predators like sharks being replaced by mesopredators like groupers, snappers, and emperors, which may lack similar strength of non-consumptive effects on lower trophic groups \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan additionalcitationids=\"CR86\" citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e–\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e. However, our study highlights a possible role of mesopredatory reef fishes in regulating primary productivity through nutrient input and stoichiometric alteration, and thereby, the overall herbivory rates at the level of the reef. Despite the prevailing narrative of predators influencing ecosystem processes by exerting top-down controls \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e,\u003cspan additionalcitationids=\"CR89\" citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e–\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e, our result highlights an equally significant bottom-up influence of predators, where they supply the limiting nutrients and maintain levels of primary and secondary productivity in nutrient-limited systems such as coral reefs \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. It also emphasizes the importance of conservation efforts targeting predatory fish populations and underscores the need for sustainable fisheries management practices. Unsustainable targeted extraction of commercially important mesopredatory reef fishes can disrupt nutrient cycling and compromise primary productivity in coral reefs. This, in turn, could trigger cascading effects across trophic levels, but rather than following the traditionally known top-down pathway, these effects might originate from bottom-up processes.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003cdiv id=\"Sec24\" class=\"Section4\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003cdiv id=\"Sec28\" class=\"Section4\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\n\n"},{"header":"Methods","content":"\u003ch2\u003e• Study Site and Study Design\u003c/h2\u003e\u003cp\u003eThe Lakshadweep Archipelago is a chain of coral atolls situated in the northern Indian Ocean off the west coast of mainland India \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. Lakshadweep comprises 12 coral islands and submerged banks \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb\u003cb\u003e)\u003c/b\u003e. The coral atolls of Lakshadweep have shallow lagoons and are surrounded by barrier reefs \u003csup\u003e\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e. The southwest monsoon and north-south orientation of most atolls have given rise to distinct windward and leeward aspects, which strongly influence the ecology and geography of Lakshadweep islands \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Although fishing has been the mainstay of the people of Lakshadweep, commercial fisheries have primarily been centered around the targeted fishing of pelagic skipjack tuna (\u003cem\u003eKatsuwonus pelamis\u003c/em\u003e), leading to relatively undisturbed fish communities in the coral reefs \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. However, commercial reef fishery is on rise in the archipelago, with different atolls of Lakshadweep experiencing various degrees of fishing pressure \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWe sampled three atolls of the Lakshadweep Archipelago: Bitra, Kadmat, and Kavaratti \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee\u003cb\u003e)\u003c/b\u003e. The islands represent a gradient of piscivorous fish density, with Bitra at the higher and Kavaratti at the lower end of the spectrum. Previous work from Lakshadweep suggests this gradient to be fishing-induced rather than natural \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. This shift is most prominent in the atoll of Kavaratti, which had the highest fish biomass before reef fisheries became a mainstay on the island \u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e. The island fishery is mainly carried out using the traditional hook and line method, which selectively harvests mesopredatory fishes from the reef, leaving the other functional groups, such as herbivores, relatively undisturbed \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. In addition to the fishing-induced biomass gradient, in Bitra, we were able to sample a spawning aggregation site of \u003cem\u003ePlectropomus areolatus\u003c/em\u003e (squaretail grouper) during spawning events. Spawning aggregations represent very high densities of fish biomass and can have long-lasting effects on nutrient dynamics and primary productivity in the aggregating reef, even after the aggregation is over \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The aggregation in Bitra is known to occur every new moon from November to April, potentially creating a hotspot of nutrient enrichment in these reefs throughout this period. Thus, we included the site in our predator biomass gradient. We sampled 11 sites across the three islands: two in Bitra, four in Kadmat, and four in Kavaratti \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee\u003cb\u003e)\u003c/b\u003e. In Bitra, the sites were located on the eastern (sheltered) aspect of the lagoon; in Kadmat, three sites were located on the east (sheltered), and two were on the west (exposed); and in Kavaratti, two sites were located on the east (sheltered), and two were on the west (exposed). We collected all data for the current study between January 2024 and May 2024.\u003c/p\u003e\u003ch2\u003e• Field Assessments\u003c/h2\u003e\u003ch2\u003ePiscivore and herbivore fish community\u003c/h2\u003e\u003cp\u003eWe characterized the piscivorous and herbivorous fish community in each reef using underwater visual census (UVC). Three 50m × 10m (500 m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e area per transect) belt transects were sampled at 12–14 meters depth. A minimum distance of 10m was maintained between two consecutive transects to ensure independence. Two observers conducted the UVCs. The observers swam parallel to each other along the transects. One observer noted the piscivorous fishes belonging to the families Serranidae, Haemulidae, Lethrinidae, Lutjanidae, Cirrhitidae, Malacanthidae, Aulostomidae, Fistularidae and Labridae. The other observer noted herbivorous fish species belonging to the families Scaridae, Kyphosidae, Acanthuridae and Siganidae. Only individuals with body sizes greater than 10 cm were noted during UVCs. We identified all the individuals on the transect to the species level and noted their abundance and size to the nearest centimeter.\u003c/p\u003e\u003ch2\u003eAlgal cover and structural complexity\u003c/h2\u003e\u003cp\u003eReef substrates were photographed every 10 meters on each belt transect (n = 6 in each transect) with a standard reference object in the frame. The images were analyzed using the software ImageJ to estimate the percentage of turf algal cover within a 1 m × 1 m area \u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e. We averaged the estimates from the three transects to obtain the percentage algal cover of the reef. We measured structural complexity as the average vertical height of the reef on the belt transects. We took measurements at every 5m distance (n = 10 in each transect). Estimates from the three transects were averaged to obtain the structural complexity of the reef.\u003c/p\u003e\u003ch2\u003eAlgal growth rates through herbivore exclusion\u003c/h2\u003e\u003cp\u003eWe established herbivore exclusion cages (20cm × 20cm × 20cm) to quantify algal growth. Box-shaped cages were constructed using plastic mesh (mesh size 2cm diameter) and cable ties. We selected areas of rigid substrate at a depth of 12-14m on the reef that were covered with algal turfs while avoiding farming damselfish territories and heavily sediment-laden substrates. The cages were operational for only 14–21 days and, therefore, did not accumulate significant amounts of fouling algae over the experimental period. We set up four cages in each site and maintained a minimum distance of 10 meters between two adjacent exclosures (n = 44). The exclosures were attached to the reef substrate directly using cable ties. The cages ensured that herbivorous reef fishes were excluded from feeding within the enclosed area. However, the mesh size allowed smaller-sized herbivorous fishes (\u0026lt; 2cm width) to enter the cages and ensured that light and water flow were not impeded.\u003c/p\u003e\u003cp\u003eTo quantify algal growth rates, the height of 10 fronds of turf algae was measured underwater using the depth probe of a vernier calliper on the day of cage installation. The depth probe yields the exact distance between the tips of the calliper. This distance between the tips was recorded by imprinting it on a saltwater-resistant pressure-sensitive poster adhesive (blue tac) attached to an acrylic board. The imprint was later measured on the surface using a digital vernier calliper, and the values up to one decimal point were noted down in millimeters \u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e. The process was repeated the day the cages were removed from the reefs. The average algal height difference between the first and final days was divided by the number of days the exclosure was operational in the reef to obtain daily algal growth rate. As initial turf length is known to affect turf growth \u003csup\u003e\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e, we calculated proportional turf growth (change in turf height per month/initial height of turf) for each exclosure. The value was multiplied by 30 to obtain proportional algal growth rate for a month.\u003c/p\u003e\u003ch2\u003eHerbivory rates through in-situ exclosures\u003c/h2\u003e\u003cp\u003eA 20 cm × 20 cm area was marked using a fishing buoy adjacent to the herbivore exclusion cages and served as an open herbivory plot (n = 44). A minimum distance of 1 meter was maintained between the exclosure and the control plot to avoid cage effects. The height of 10 turf algal fronds was measured using the same method as inside the cages. Daily herbivory rate was estimated as the difference between daily algal growth inside the exclosures and the paired open herbivory plot present next to it at the end of the period. The value was multiplied by 30 to get the herbivory rate in mm/month.\u003c/p\u003e\u003ch2\u003eAnti-predatory behaviour through focal observations\u003c/h2\u003e\u003cp\u003eAcross the predator biomass gradient, we carried out focal observations on a candidate fish species of lower trophic level, \u003cem\u003eCtenochaetus striatus\u003c/em\u003e, to test the presence of non-consumptive effects of predators on prey fish species. We chose \u003cem\u003eC. striatus\u003c/em\u003e as the candidate species because it is one of the most ubiquitous and abundant species in Lakshadweep, and the juveniles are known to be predated upon by mesopredatory reef fishes \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. Sampling was conducted during the day between 0900 and 1200 when fishes are known to be active, and all the sampled individuals were chosen opportunistically. We followed 10 \u003cem\u003eC. striatus\u003c/em\u003e individuals at each sampling site (n = 110). \u003cem\u003eC. striatus\u003c/em\u003e individuals with body sizes greater than 18 cm were sampled to avoid behavioural variations due to body size dissimilarity. This body size is also speculated to be out of direct predation threat by coral reef mesopredators and is much greater than the average prey size of coral reef fishes \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e,\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. Thus, they are deemed suitable for examining the non-consumptive effects of predators on herbivore behaviour.\u003c/p\u003e\u003cp\u003eThe focal individuals were filmed for 4 minutes. Consecutive observations were separated spatially by at least 10 meters to avoid sampling the same individuals. We swam in one direction between two successive focal follows to avoid repeated observations of the same individual. All the observations were conducted within a narrow depth range of 10–13 meters.\u003c/p\u003e\u003cp\u003eThe videos were analyzed later to observe the proportion of time spent in vigilance by the individual. Our observations indicated that individuals resumed feeding within 30 seconds of video recording, and did not show any signs of diver-induced disturbance like accelerating away from the observer or repeated hiding. Hence, we excluded the first 30 seconds of the video. If the fish could not be seen because it had moved behind a big boulder after 30 seconds, we waited until it could be seen again in the video and restarted analyzing the video. The videos were analyzed for a total of 3-minutes. Time spent in vigilance is widely considered to be a reliable metric of understanding anti-predatory response of prey to predation threat, with increasing predation threat being associated with an increased amount of time spent in vigilance by prey individuals \u003csup\u003e\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e,\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e. Thus, we noted down time spent in vigilance by the \u003cem\u003eC. striatus\u003c/em\u003e individuals during the 3-minute. Vigilance was defined as the behavioural state in which the focal individual swam with its face pointed towards the water column or at a positive angle to the reef substrate \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e \u003csup\u003e\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003ch2\u003e• Quantification and Statistical Analysis\u003c/h2\u003e\u003ch2\u003eQuantifying predatory and herbivorous fish biomass\u003c/h2\u003e\u003cp\u003eWe used fish identity, body size and abundance data obtained from UVCs to estimate the biomass using the formula W = a × L\u003csup\u003eb\u003c/sup\u003e, where W = estimated biomass, L = observed length of the fish, and a and b values are standard fish values obtained for each species from Fishbase \u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e. Total biomass at the level of the transect was divided by the area of each transect to obtain fish biomass per unit area. A mean of the transect-level values was estimated to obtain site-level fish biomass per unit area.\u003c/p\u003e\u003cp\u003ePrevious studies suggest the existence of a fishing-induced predatory fish biomass gradient in the atolls of Lakshadweep \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Our underwater visual census data also suggested the presence of a mesopredator biomass gradient across the 11 sampled sites in Lakshadweep. We also found a strong positive correlation between predator biomass and herbivore biomass (\u003cem\u003er\u003c/em\u003e = \u003cem\u003e0.9\u003c/em\u003e). Predator and herbivore biomass were thus log-transformed to account for the parametric correlation between the two variables and avoid multicollinearity issues in subsequent models (\u003cem\u003er = 0.65\u003c/em\u003e).\u003c/p\u003e\u003ch2\u003eControlling for pelagic nutrient subsidies\u003c/h2\u003e\u003cp\u003eThe oceanic coral reefs typically thrive in phosphorus-limited seascapes, and pelagic nutrients vectored by planktivorous fishes and piscivorous fish excretion are considered to be the two major sources of phosphorus in such systems \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan additionalcitationids=\"CR101 CR102\" citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e–\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u003c/sup\u003e. Numerous studies have established planktivore-mediated pelagic phosphorus input as a ubiquitous and salient source of nutrients in offshore coral reef ecosystems \u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e,\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e. In this study, we were unable to estimate pelagic phosphorus input in the reefs of Lakshadweep. However, studies on plankton biomass and hydrodynamics suggest that pelagic plankton transport to coral reefs through subsurface waters is mediated by wind and wave exposure \u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e. The north-south orientation of Lakshadweep’s atolls gives rise to two distinct wave exposure regimes: the calmer and sheltered east, or the leeward aspect, and the turbulent and exposed west, or the windward aspect \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. On average, the windward western aspect of Lakshadweep atolls experiences about three times greater wave power across the season compared to the leeward eastern aspect, with the contrast being highest during the Indian summer monsoon \u003csup\u003e\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e\u003c/sup\u003e. These contrasting exposure regimes likely translate to differences in pelagic nutrient subsidies. Thus, to statistically control for pelagic nutrient subsidies, we included the physical aspects of the sites in our regression models.\u003c/p\u003e\u003ch2\u003eProductivity along predator biomass gradient\u003c/h2\u003e\u003ch2\u003eEstimating consumer-derived nutrient inputs\u003c/h2\u003e\u003cp\u003eWe used data obtained from UVCs to estimate consumer-derived nutrient input in the water. We used a global consumer-derived nutrient input dataset to calculate size-specific nitrogen and phosphorus input in the system for each species of herbivore and piscivore fish \u003csup\u003e\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e. If the nutrient input value for any observed body size for a species was unavailable, the nearest available body size (difference of ≤ 2cm) in the dataset was considered to calculate the nutrient input. If the values were not present for any particular species, the values available for a congeneric species were considered for the calculation \u003csup\u003e\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e\u003c/sup\u003e. We converted the absolute mass of nitrogen and phosphorus input to moles by dividing each by the atomic mass of the respective element. The N:P molar ratio (ratio between the amounts of elements in moles) was calculated for all the sampled sites. We estimated the mean N:P molar ratio and calculated the standard error using a non-parametric bootstrapping method with 2000 iterations to infer the relative role of herbivores and piscivores in supplying nutrients in the system.\u003c/p\u003e\u003ch2\u003eEstimating algal growth rates\u003c/h2\u003e\u003cp\u003eWe employed linear mixed-effects models to investigate the impact of herbivore and piscivore biomass on algal growth rates. Proportional algal growth rate was modelled against log-transformed predator and herbivore biomass. Aspect was added as a fixed effect in the model. Site identity was included as a random intercept to account for any other factors at the site level that influence algal growth rates. Both continuous predictors were scaled before being included in the model.\u003c/p\u003e\u003ch2\u003eQuantifying herbivore productivity\u003c/h2\u003e\u003cp\u003eRecent modeling advancements have enabled the calculation of productivity of reef fish assemblages by combining underwater census data with predicted growth and size-based mortality rates \u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e,\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e\u003c/sup\u003e. Thus, we calculated herbivorous fish productivity using fish species identity, size and abundance obtained from the underwater visual census \u003csup\u003e\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e,\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e\u003c/sup\u003e. The census data was filtered only to include grazers, scrapers and excavators - the herbivore functional groups that feed on turf algae. We estimated the standardized growth parameter, \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e, for all individuals using observed body size, diet and a mean sea surface temperature of 28°C \u003csup\u003e\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e\u003c/sup\u003e. Using the estimated species and size-specific \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e values, we estimated the age of the individuals using the individual age framework and estimated biomass gain through somatic growth over a day for all the individuals \u003csup\u003e\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e,\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u003c/sup\u003e. Finally, by subtracting a per-capita loss due to natural mortality, we calculated productivity as the biomass gained per day by all surviving individuals at the level of the transect. We converted the value per transect to productivity per unit hectare of area per day. Productivity was modelled as a function of predator biomass, resource availability, structural complexity and aspect of the site using a generalized linear mixed-effects model with gamma error distribution and log-link. Resource availability was quantified as the product of site-level percentage algal cover and average daily absolute algal growth rate obtained from the exclosures. We used site identity as a random intercept to account for any inherent variability in productivity within a site. Predator biomass was log-transformed and all the continuous predictors were scaled before being used in the model.\u003c/p\u003e\u003ch2\u003eHerbivory rate along predator biomass gradient\u003c/h2\u003e\u003ch2\u003eEstimating reef-wide herbivory rates\u003c/h2\u003e\u003cp\u003eHerbivory rates obtained from the in-situ exclosures were modelled as a function of log-transformed predator and herbivore biomass using a linear mixed-effects model. Herbivore biomass comprised the total biomass of grazers, scrapers and excavators, as they are known to feed on turf algae, thus contributing to herbivory. Aspect was included as a fixed effect in the model, as herbivory rates are known to be influenced by wave exposure regimes \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Site-level percentage cover of turf algae was added as a fixed effect, as the availability of algal resources can determine the levels of herbivory in any unit area of the reef. We used site identity as a random intercept in the model. Both continuous predictors were scaled before being used in the model.\u003c/p\u003e\u003ch2\u003eQuantifying community-level herbivory\u003c/h2\u003e\u003cp\u003eWe estimated monthly community-level herbivory on turf algae in terms of grams of carbon ingested per unit area by the herbivorous fish community present at the site. Herbivory rates were estimated by combining underwater visual census data of herbivores with a global carbon ingestion dataset \u003csup\u003e\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e. We calculated size- and species-specific daily carbon ingestion by herbivorous reef fishes belonging to the functional groups: grazer, scraper and excavator. If the ingestion value for any observed size of a species was missing from the dataset, the value for the nearest body size (with a difference of ≤ 2 cm) was used to calculate herbivory rates. If a species from our study area was absent from the dataset, we used data from a congeneric species that was present in the dataset. We calculated the mean herbivory rate at the level of each transect and converted it to grams of carbon ingested per unit square meter of the reef per day. We modelled community-level herbivory rates as a function of log-transformed predator biomass, percentage algal cover, structural complexity and aspect of the site using a generalized linear mixed-effects model with gamma error distribution and log-link. We used site identity as a random intercept and scaled all the continuous predictor variables before using them in the model.\u003c/p\u003e\u003ch3\u003eAssessing anti-predatory behaviour\u003c/h3\u003e\u003cp\u003eTime spent in vigilance was divided by the total observable time to obtain the proportion of time spent in vigilance. We used generalized linear mixed-effects models with a beta error distribution and logit link function to model proportion of time spent in vigilance. Log-transformed predator and herbivore biomass were added as predictor variables. Resource availability was quantified as the product of site-level proportion of algal cover and mean daily absolute algal growth rate (mm) obtained from the exclosures and was added as a fixed effect. Aspect was added as a fixed effect to account for wave exposure regime. Structural complexity was added as a predictor. Site was added as a random intercept to account for any inter-site variability. All continuous predictors were scaled before being used in the model.\u003c/p\u003e\u003ch2\u003eValidity and Diagnostics of Models\u003c/h2\u003e\u003cp\u003eModels were fitted based on the distribution of the data as revealed by the preliminary analyses. The model fit for linear mixed-effects models was visually examined using a plot of model residuals against the fitted values to check for homoskedasticity, a Q-Q plot of residuals to check normality and a histogram of the model residuals to check for normality. The Shapiro-Wilk test for normality was used on the residuals of the datasets that were difficult to assess visually for normality. The Variance Inflation Factor (VIF) was calculated for each fitted model, ensuring the absence of multicollinearity between predictors. Model fit for generalized linear mixed-effects models with gamma error distribution and log-link was assessed using plots of raw residuals, Pearson's residuals and deviance residuals, a plot of simulated residuals against the model residuals and a Q-Q plot of residuals. All models were checked for the presence of overdispersion.\u003c/p\u003e\u003cp\u003eAll analyses were performed using R version 4.4.2 \u003csup\u003e111\u003c/sup\u003e. Package \u003cem\u003e“lme4”\u003c/em\u003e was used to run linear mixed-effects models \u003csup\u003e\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u003c/sup\u003e. Package \u003cem\u003e“glmmTMB”\u003c/em\u003e was used to run generalized linear mixed-effects models with beta and gamma error distributions \u003csup\u003e\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e\u003c/sup\u003e. Package \u003cem\u003e“car”\u003c/em\u003e was used to check for the variance inflation factor \u003csup\u003e\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e\u003c/sup\u003e. Package \u003cem\u003e“DHARMa”\u003c/em\u003e was used to check the model fit of the generalized linear mixed-effects models with gamma error distribution \u003csup\u003e\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e\u003c/sup\u003e. Package \u003cem\u003e“visreg”\u003c/em\u003e was used to extract data from models \u003csup\u003e\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e\u003c/sup\u003e, and the package \u003cem\u003e“tidyverse”\u003c/em\u003e was used for data cleaning and visualization \u003csup\u003e\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e\u003c/sup\u003e. Package \u003cem\u003e“performance”\u003c/em\u003e was used to check for overdispersion \u003csup\u003e\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e\u003c/sup\u003e. Herbivore productivity was estimated using the package \u003cem\u003e“rfishprod”\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eFunding for this work was provided by the Department of Atomic Energy, Government of India to National Centre for Biological Sciences (Project Identification No: RTI 4006); Shri AMM Murugappa Chettiar Research Centre (MCRC), Ashraya Hasta Trust and Rohini Nilekani Philanthropies to RA; and National Geographic Society (Grant No: NGS 96905R-22) to RK. The Fisheries Society of the British Isles supported AP through a Travel Grant during his tenure at Lancaster University. AP was awarded the Infosys Travel Award by National Centre for Biological Sciences to attend and present the results of this study at the International Conference for Young Marine Researchers 2024, Bremen, Germany. The Spanish National Research Council supported TA through the Memorandum of Understanding between Centre D\u0026rsquo;Estudis Avan\u0026ccedil;ats de Blanes (CEAB, CSIC) and Nature Conservation Foundation (NCF).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003ePermission statement\u003c/h2\u003e\u003cp\u003e I confirm that the required permissions to conduct field work in the atolls of Lakshadweep Archipelago were obtained from the Department of Environment and Forests, Union Territory of Lakshadweep (F. No. 1/5/2023-E\u0026amp;F/1045). Should you need any further documentation or information, please feel free to contact me.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAP, RK, RA and TA conceptualized and designed the study. AP, HT, RK, RA and TA collected data. AP and SP analyzed and summarized the data for the manuscript. AP curated and visualized the data and wrote the first draft. All authors contributed equally towards reviewing and approving the final draft.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the Department of Environment and Forests, Union Territory of Lakshadweep, for the timely permit and support to conduct this study (F. No. 1/5/2023-E\u0026amp;F/1045). We thank the NCBS\u0026ndash;TIFR, Nature Conservation Foundation, and Wildlife Conservation Society\u0026ndash;India for their institutional, administrative, and logistical support. We thank all our funders for the generous funding that made this work possible. We thank Siya Bhagat, Wenzel Pinto, and Abdul Rauf for their assistance with data collection and Sidharth Sankaran for transcribing the benthic photoquadrats. We thank Anwar Hussain, M.K. Ibrahim (Ummini), and everyone at ESMUC and LakScuba for their logistical support during the fieldwork. We are deeply grateful to the people of Bitra, Kadmat and Kavaratti for their unwavering support. We thank James Robinson and Renato Morais for their advice on the fish productivity analysis. We are grateful to Nick Graham, Casey Benkwitt, Jennifer Appoo, Mayank Kohli, Pritha Dey, Kulbhushansingh Suryawanshi and Mayuresh Gangal for their critical input and feedback on different aspects and stages of the study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThis study did not generate any new or unique codes. All data supporting the findings and conclusions of this article will be made publicly available in the Zenodo data repository upon publication. Any additional information required to analyze the data will be made available by the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSheriff, M. J., Peacor, S. D., Hawlena, D. \u0026amp; Thaker, M. Non-consumptive predator effects on prey population size: A dearth of evidence. \u003cem\u003eJ. Anim. 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Source Softw.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e, 3139 (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Ecosystem functions, nutrient stoichiometry, bottom-up processes, predator-prey interactions, mesopredator release, coral reefs","lastPublishedDoi":"10.21203/rs.3.rs-7365908/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7365908/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eApex predators influence ecosystem functioning through consumptive and non-consumptive effects. Recent studies suggest that predators can also be an essential source of limiting nutrients in ecosystems such as coral reefs, potentially influencing prey ecology from the bottom up. With rising commercial fishery, predatory fishes are being selectively harvested from reefs. Yet, there is incomplete knowledge of the consequences of this extraction on essential ecosystem processes. Using field experiments and observations, we examined how predatory fishes influence herbivory along a fishing-induced predatory fish biomass gradient in the Lakshadweep Archipelago. We found that mesopredatory fish excreta have greater proportion of phosphorus than nitrogen. Along the gradient, primary and secondary productivity increased, after accounting for pelagic nutrient subsidies. Further, herbivory rates increased with increasing predator biomass, while prey anti-predator response remained unchanged. Our results suggest that predator-induced alterations of nutrient stoichiometry stimulate primary and secondary productivity and enhance herbivory in coral reefs, particularly in systems experiencing mesopredator release following selective fishing of apex predators. Our study shifts focus from the traditional top-down role of predators, highlighting an overlooked bottom-up pathway by which predators can influence ecosystem functioning. Global decline of predators could modify ecosystem processes in ways that are yet unknown, leaving them increasingly vulnerable to future disturbances.\u003c/p\u003e","manuscriptTitle":"Predators facilitate herbivory in nutrient-limited marine ecosystems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-28 05:55:26","doi":"10.21203/rs.3.rs-7365908/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-31T11:03:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-30T04:31:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-02T20:22:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255498416331566801016135612350908079311","date":"2025-09-30T22:18:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248575100451534142395999310354640822496","date":"2025-09-11T16:21:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-11T14:00:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-29T10:51:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-21T16:48:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-21T16:44:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b0dc6660-b5ed-4277-b97f-64f6a37ce578","owner":[],"postedDate":"August 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":53728829,"name":"Biological sciences/Ecology"},{"id":53728830,"name":"Earth and environmental sciences/Ecology"},{"id":53728831,"name":"Earth and environmental sciences/Ocean sciences"}],"tags":[],"updatedAt":"2026-01-05T16:02:48+00:00","versionOfRecord":{"articleIdentity":"rs-7365908","link":"https://doi.org/10.1038/s41598-025-34145-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-30 15:57:37","publishedOnDateReadable":"December 30th, 2025"},"versionCreatedAt":"2025-08-28 05:55:26","video":"","vorDoi":"10.1038/s41598-025-34145-6","vorDoiUrl":"https://doi.org/10.1038/s41598-025-34145-6","workflowStages":[]},"version":"v1","identity":"rs-7365908","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7365908","identity":"rs-7365908","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}