Corals survive severe bleaching event in refuges related to taxa, colony size, and water depth.

Marine heatwaves are increasing in frequency and duration, threatening tropical reef ecosystems through intensified coral bleaching events. We examined a strikingly variable spatial pattern of bleaching in Moorea, French Polynesia following a heatwave that lasted from November 2018 to July 2019. In July 2019, four months after the onset of bleaching, we surveyed > 5000 individual colonies of the two dominant coral genera, Pocillopora and Acropora, at 10 m and 17 m water depths, at six forereef sites around the island where temperature was measured. We found severe bleaching increased with colony size for both coral genera, but Acropora bleached more severely than Pocillopora overall. Acropora bleached more at 10 m than 17 m, likely due to higher light availability at 10 m compared to 17 m, or greater daily temperature fluctuation at depth. Bleaching in Pocillopora corals did not differ with depth but instead varied with the interaction of colony size and Accumulated Heat Stress (AHS), in that larger colonies (> 30 cm) were more sensitive to AHS than mid-size (10-29 cm) or small colonies (5-9 cm). Our findings provide insight into complex interactions among coral taxa, colony size, and water depth that produce high spatial variation in bleaching and related coral mortality.

High-Precision Microscale Particulate Matter Prediction in Diverse Environments Using a Long Short-Term Memory Neural Network and Street View Imagery.

In this study, we propose a novel long short-term memory (LSTM) neural network model that leverages color features (HSV: hue, saturation, value) extracted from street images to estimate air quality with particulate matter (PM) in four typical European environments: urban, suburban, villages, and the harbor. To evaluate its performance, we utilize concentration data for eight parameters of ambient PM (PM1.0, PM2.5, and PM10, particle number concentration, lung-deposited surface area, equivalent mass concentrations of ultraviolet PM, black carbon, and brown carbon) collected from a mobile monitoring platform during the nonheating season in downtown Augsburg, Germany, along with synchronized street view images. Experimental comparisons were conducted between the LSTM model and other deep learning models (recurrent neural network and gated recurrent unit). The results clearly demonstrate a better performance of the LSTM model compared with other statistically based models. The LSTM-HSV model achieved impressive interpretability rates above 80%, for the eight PM metrics mentioned above, indicating the expected performance of the proposed model. Moreover, the successful application of the LSTM-HSV model in other seasons of Augsburg city and various environments (suburbs, villages, and harbor cities) demonstrates its satisfactory generalization capabilities in both temporal and spatial dimensions. The successful application of the LSTM-HSV model underscores its potential as a versatile tool for the estimation of air pollution after presampling of the studied area, with broad implications for urban planning and public health initiatives.

Microbiome ecological memory and responses to repeated marine heatwaves clarify variation in coral bleaching and mortality.

Microbiomes are essential features of holobionts, providing their hosts with key metabolic and functional traits like resistance to environmental disturbances and diseases. In scleractinian corals, questions remain about the microbiome's role in resistance and resilience to factors contributing to the ongoing global coral decline and whether microbes serve as a form of holobiont ecological memory. To test if and how coral microbiomes affect host health outcomes during repeated disturbances, we conducted a large-scale (32 exclosures, 200 colonies, and 3 coral species sampled) and long-term (28 months, 2018-2020) manipulative experiment on the forereef of Mo'orea, French Polynesia. In 2019 and 2020, this reef experienced the two most severe marine heatwaves on record for the site. Our experiment and these events afforded us the opportunity to test microbiome dynamics and roles in the context of coral bleaching and mortality resulting from these successive and severe heatwaves. We report unique microbiome responses to repeated heatwaves in Acropora retusa, Porites lobata, and Pocillopora spp., which included: microbiome acclimatization in A. retusa, and both microbiome resilience to the first marine heatwave and microbiome resistance to the second marine heatwave in Pocillopora spp. Moreover, observed microbiome dynamics significantly correlated with coral species-specific phenotypes. For example, bleaching and mortality in A. retusa both significantly increased with greater microbiome beta dispersion and greater Shannon Diversity, while P. lobata colonies had different microbiomes across mortality prevalence. Compositional microbiome changes, such as changes to proportions of differentially abundant putatively beneficial to putatively detrimental taxa to coral health outcomes during repeated heat stress, also correlated with host mortality, with higher proportions of detrimental taxa yielding higher mortality in A. retusa. This study reveals evidence for coral species-specific microbial responses to repeated heatwaves and, importantly, suggests that host-dependent microbiome dynamics may provide a form of holobiont ecological memory to repeated heat stress.

Automated SEM/EDX imaging for the in-depth characterization of non-exhaust traffic emissions from the Munich subway system.

A SEM/EDX based automated measurement and classification algorithm was tested as a method for the in-depth analysis of micro-environments in the Munich subway using a custom build mobile measurements system. Sampling was conducted at platform stations, to investigate the personal exposure of commuters to subway particulate matter during platform stays. EDX spectra and morphological features of all analyzed particles were automatically obtained and particles were automatically classified based on pre-defined chemical and morphological boundaries. Source apportionment for individual particles, such as abrasion processes at the wheel-brake interface, was partially possible based on the established particle classes. An average of 98.87 ± 1.06 % of over 200,000 analyzed particles were automatically assigned to the pre-defined classes, with 84.68 ± 16.45 % of particles classified as highly ferruginous. Manual EDX analysis further revealed, that heavy metal rich particles were also present in the ultrafine size range well below 100 nm.

Humic-like Substances (HULIS) in Ship Engine Emissions: Molecular Composition Effected by Fuel Type, Engine Mode, and Wet Scrubber Usage.

Humic-like substances (HULIS), known for their substantial impact on the atmosphere, are identified in marine diesel engine emissions obtained from five different fuels at two engine loads simulating real world scenarios as well as the application of wet sulfur scrubbers. The HULIS chemical composition is characterized by electrospray ionization (ESI) ultrahigh resolution mass spectrometry and shown to contain partially oxidized alkylated polycyclic aromatic compounds as well as partially oxidized aliphatic compounds, both including abundant nitrogen- and sulfur-containing species, and clearly different to HULIS emitted from biomass burning. Fuel properties such as sulfur content and aromaticity as well as the fuel combustion efficiency and engine mode are reflected in the observed HULIS composition. When the marine diesel engine is operated below the optimum engine settings, e.g., during maneuvering in harbors, HULIS-C emission factors are increased (262-893 mg kg-1), and a higher number of HULIS with a shift toward lower degree of oxidation and higher aromaticity is detected. Additionally, more aromatic and aliphatic CHOS compounds in HULIS were detected, especially for high-sulfur fuel combustion. The application of wet sulfur scrubbers decreased the HULIS-C emission factors by 4-49% but also led to the formation of new HULIS compounds. Overall, our results suggest the consideration of marine diesel engines as a relevant regional source of HULIS emissions.

Effectiveness assessment of repetitive transcranial alternating current stimulation with concurrent EEG and fNIRS measurement.

Transcranial alternating current stimulation (tACS) exhibits the capability to interact with endogenous brain oscillations using an external low-intensity sinusoidal current and influences cerebral function. Despite its potential benefits, the physiological mechanisms and effectiveness of tACS are currently a subject of debate and disagreement. The aims of our study are to (i) evaluate the neurological and behavioral impact of tACS by conducting repetitive sham-controlled experiments and (ii) propose criteria to evaluate effectiveness, which can serve as a benchmark to determine optimal individual-based tACS protocols. In this study, 15 healthy adults participated in the experiment over two visiting: sham and tACS (i.e., 5 Hz, 1 mA). During each visit, we used multimodal recordings of the participants' brain, including simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), along with a working memory (WM) score to quantify neurological effects and cognitive changes immediately after each repetitive sham/tACS session. Our results indicate increased WM scores, hemodynamic response strength, and EEG power in theta and delta bands both during and after the tACS period. Additionally, the observed effects do not increase with prolonged stimulation time, as the effects plateau towards the end of the experiment. In conclusion, our proposed closed-loop scheme offers a promising advance for evaluating the effectiveness of tACS during the stimulation session. Specifically, the assessment criteria use participant-specific brain-based signals along with a behavioral output. Moreover, we propose a feedback efficacy score that can aid in determining the optimal stimulation duration based on a participant-specific brain state, thereby preventing the risk of overstimulation.

Readiness to Practice in Health Care: An Empirical Definition Based on a Content Analysis of the Literature.

BACKGROUND: Health care services require practitioners to be ready to practice (R2P), but evidence shows new graduates vary in R2P. Unfortunately, there is a lack of clarity about what R2P entails. METHOD: A content analysis of the empirical literature (Gaur & Kumar, 2018) was used to quantify the elements and higher-order categories of R2P. RESULTS: Across 108 articles, professional development activities, communication, previous experience, confidence, clinical skills, patient-centered care, integration of knowledge, teamwork, competency, management, and interpersonal skills were used to define R2P at least 25% of the time. We identified seven domains of R2P: clinical experience, social experiences, professional development experiences, personal attributes, cognitive aspects, onboarding experiences, and educational experiences. CONCLUSION: Our study empirically defined what is associated with health professionals who were perceived as or perceived themselves as R2P in health care. Our results inform training, preparation, research, and the transition from medical training to the workplace. [J Contin Educ Nurs. 2023;54(7):302-312.].

Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference.

Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs - designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [-4.1, -0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones.

The climate adaptive characteristics of urban inside/outside water bodies based on their cooling effect in Poyang and Dongting lake regions, China.

Most publications have focused on the cooling effect of urban inside water bodies. However, the climate adaptive characteristics of urban inside/outside water bodies is seldom studied. In this paper, three types of water bodies, i.e., urban inside water bodies, urban outside discrete water bodies and large water bodies are identified according to their relative spatial relationships with built-up areas. The climate adaptive landscape characteristics of water bodies are analyzed based on water bodies' cooling effect (WCE) inside and outside cities in the Poyang Lake and Dongting Lake regions. Seventy-three Landsat TM/OLI/TIRS images acquired from 1989 to 2019 are employed. Landscape scale characteristics of urban inside/outside water bodies are described by area, water depth, perimeter to area ratio (PARA) and distance-weighted area index (DWAI). Three temperature-related parameters are calculated to estimate the WCE in different conditions. Climate adaptive characteristics of water bodies inside/outside cities are determined by correlation and regression analysis. Results show that: 1) The long river shape, depth, orientation and fluidity of urban inside water bodies are benefit to enhance their cooling effect; 2) the distance of urban outside water bodies from built-up areas are positive correlated with their cooling effect; 3) the optimal acreage of large water bodies are >2500 km2 and 1111-1287.5 km2 for climate adaption of Poyang Lake and Dongting Lake, respectively. Simultaneously, the WCE of urban outside large water bodies is related with human activities and climate conditions. The results of our study provide a significant contribution to blue-space planning in cities, and provide insights into actionable climate adaption planning in inland large lake areas.

Reduced soil multifunctionality and microbial network complexity in degraded and revegetated alpine meadows.

Understanding how microbial processes develop and change in alpine meadow soils is key to global initiatives toward environmental sustainability and local land management. Yet, how microbial interactions mediate soil multifunctionality in disturbed and managed alpine meadows remains understudied. Here, we investigated multiple community metrics, particularly microbial network properties and assembly processes, of soil bacterial and fungal communities and their links to certain soil functions along a degradation-restoration sequence of alpine meadows in the Qinghai-Tibetan Plateau. Meadow degradation caused significant declines in soil hydraulic conductivity (e.g., higher bulk density, reduced soil porosity and water content) and nitrogen availability, leading to lowered soil multifunctionality. Meadow degradation only caused weak changes in microbial abundance, alpha diversity, and community composition, but remarkably reduced bacterial network complexity, to a less extent for fungal network properties. Short-term artificial restoration with productive grass monocultures did not restore soil multifunctionality, in turn even destabilized bacterial network and favored pathogenic over mutualistic fungi. Soil fungi community are more stable than bacteria in disturbed alpine meadows, and they evolved with distinct assembly strategies (stochastic-dominant versus deterministic-driven processes, respectively). Further, microbial network complexity, positively and better predicts soil multifunctionality than alpha diversity. Our work shows how microbial interaction complexity may enhance soil multifunctionality in degraded alpine meadow ecosystems, noting that meadow restoration with low plant species diversity may failed in restoring multiple ecosystem functions. These findings would help predict the outcomes of global environmental changes and inform management strategies in regional grassland conservation and restoration.

Widespread perturbation of ETS factor binding sites in cancer.

Although >90% of somatic mutations reside in non-coding regions, few have been reported as cancer drivers. To predict driver non-coding variants (NCVs), we present a transcription factor (TF)-aware burden test based on a model of coherent TF function in promoters. We apply this test to NCVs from the Pan-Cancer Analysis of Whole Genomes cohort and predict 2555 driver NCVs in the promoters of 813 genes across 20 cancer types. These genes are enriched in cancer-related gene ontologies, essential genes, and genes associated with cancer prognosis. We find that 765 candidate driver NCVs alter transcriptional activity, 510 lead to differential binding of TF-cofactor regulatory complexes, and that they primarily impact the binding of ETS factors. Finally, we show that different NCVs within a promoter often affect transcriptional activity through shared mechanisms. Our integrated computational and experimental approach shows that cancer NCVs are widespread and that ETS factors are commonly disrupted.

Presbyopic LASIK using the Supracor algorithm and micromonovision in presbyopic myopic patients: 12-month visual and refractive outcomes.

PURPOSE: To evaluate the visual and refractive outcomes for presbyopia and myopia treatment using the Teneo 317 M2 platform and the myopic Supracor algorithm. SETTING: Percy Military Hospital and Private Laser Victor Hugo Center, Paris, France. DESIGN: Observational retrospective nonrandomized study. METHODS: 50 eyes (25 patients) treated with bilateral myopic Supracor and micromonovision using the Teneo 317 M2 platform and followed up for 12 months. Study outcomes included binocular and monocular visual acuities (without correction for distance and near vision), the spherical equivalent, predictability, stability, safety, optical aberrations, and complications. RESULTS: The mean age was 50.6 ± 2.7 years, and the mean preoperative spherical equivalent was -2.6 ± 1.4 diopters. At 12 months postoperatively, the mean binocular uncorrected distance visual acuity was 0.02 ± 0.03 logMAR, and 24 patients (96%) achieved an acuity of 20/25 or better. The binocular uncorrected near visual acuity was equal to Jaeger 1 in 18 patients (72%) and Jaeger 2 or better in 23 patients (92%). 12 eyes (24%) had lost 1 Snellen line, and 1 eye (2%) had lost 2 Snellen lines of monocular corrected distance visual acuity. No cases required retreatment; however, 1 eye (2%) underwent revision surgery because of diffuse lamellar keratitis. CONCLUSIONS: This study suggests that Supracor using the Teneo 317 M2 platform is a safe and effective technique for myopia and presbyopia treatment. Supracor is therefore a viable alternative to monovision for presbyopia and myopia. However, a careful patient selection is essential to satisfy realistic expectations.

Levels and drivers of urban black carbon and health risk assessment during pre- and COVID19 lockdown in Augsburg, Germany.

This study aimed to evaluate the levels and phenomenology of equivalent black carbon (eBC) at the city center of Augsburg, Germany (01/2018 to 12/2020). Furthermore, the potential health risk of eBC based on equivalent numbers of passively smoked cigarettes (PSC) was also evaluated, with special emphasis on the impact caused by the COVID19 lockdown restriction measures. As it could be expected, peak concentrations of eBC were commonly recorded in morning (06:00-8:00 LT) and night (19:00-22:00 LT) in all seasons, coinciding with traffic rush hours and atmospheric stagnation. The variability of eBC was highly influenced by diurnal variations in traffic and meteorology (air temperature (T), mixing-layer height (MLH), wind speed (WS)) across days and seasons. Furthermore, a marked "weekend effect" was evidenced, with an average eBC decrease of ∼35% due to lower traffic flow. During the COVID19 lockdown period, an average ∼60% reduction of the traffic flow resulted in ∼30% eBC decrease, as the health risks of eBC exposure was markedly reduced during this period. The implementation of a multilinear regression analysis allowed to explain for 53% of the variability in measured eBC, indicating that the several factors (e.g., traffic and meteorology) may contribute simultaneously to this proportion. Overall, this study will provide valuable input to the policy makers to mitigate eBC pollutant and its adverse effect on environment and human health.

Aerosol emissions from a marine diesel engine running on different fuels and effects of exhaust gas cleaning measures.

The emissions of marine diesel engines have gained both global and regional attentions because of their impact on human health and climate change. To reduce ship emissions, the International Maritime Organization capped the fuel sulfur content of marine fuels. Consequently, either low-sulfur fuels or additional exhaust gas cleaning devices for the reduction in sulfur dioxide (SO2) emissions became mandatory. Although a wet scrubber reduces the amount of SO2 significantly, there is still a need to consider the reduction in particle emissions directly. We present data on the particle removal efficiency of a scrubber regarding particle number and mass concentration with different marine fuel types, marine gas oil, and two heavy fuel oils (HFOs). An open-loop sulfur scrubber was installed in the exhaust line of a marine diesel test engine. Fine particulate matter was comprehensively characterized in terms of its physical and chemical properties. The wet scrubber led up to a 40% reduction in particle number, whereas a reduction in particle mass emissions was not generally determined. We observed a shift in the size distribution by the scrubber to larger particle diameters when the engine was operated on conventional HFOs. The reduction in particle number concentrations and shift in particle size were caused by the coagulation of soot particles and formation/growing of sulfur-containing particles. Combining the scrubber with a wet electrostatic precipitator as an additional abatement system showed a reduction in particle number and mass emission factors by >98%. Therefore, the application of a wet scrubber for the after-treatment of marine fuel oil combustion will reduce SO2 emissions, but it does not substantially affect the number and mass concentration of respirable particulate matters. To reduce particle emission, the scrubber should be combined with additional abatement systems.

Differences in initial abundances reveal divergent dynamic structures in Gause's predator-prey experiments.

Improved understanding of complex dynamics has revealed insights across many facets of ecology, and has enabled improved forecasts and management of future ecosystem states. However, an enduring challenge in forecasting complex dynamics remains the differentiation between complexity and stochasticity, that is, to determine whether declines in predictability are caused by stochasticity, nonlinearity, or chaos. Here, we show how to quantify the relative contributions of these factors to prediction error using Georgii Gause's iconic predator-prey microcosm experiments, which, critically, include experimental replicates that differ from one another only in initial abundances. We show that these differences in initial abundances interact with stochasticity, nonlinearity, and chaos in unique ways, allowing us to identify the impacts of these factors on prediction error. Our results suggest that jointly analyzing replicate time series across multiple, distinct starting points may be necessary for understanding and predicting the wide range of potential dynamic types in complex ecological systems.

Real-Time Investigation of Primary Ship Engine Emissions by Vacuum Resonance-Enhanced Multiphoton Ionization High-Resolution Orbitrap Mass Spectrometry.

The comprehensive chemical description of air pollution is a prerequisite for understanding atmospheric transformation processes and effects on climate and environmental health. In this study, a prototype vacuum photoionization Orbitrap mass spectrometer was evaluated for field-suitability by an online on-site investigation of emissions from a ship diesel engine. Despite remote measurements in a challenging environment, the mass spectrometric performance could fully be exploited. Due to the high resolution and mass accuracy in combination with resonance-enhanced multiphoton ionization, the aromatic hydrocarbon profile could selectively and sensitively be analyzed. Limitations from commonly deployed time-of-flight platforms could be overcome, allowing to unraveling the oxygen- and sulfur-containing compounds. Scan-by-scan evaluation of the online data revealed no shift in exact m/z, assignment statistics with root mean square error (RMSE) below 0.2 ppm, continuous high-resolution capabilities, and good isotopic profile matches. Emissions from three different feed fuels were investigated, namely, diesel, heavy fuel oil (HFO), and very low sulfur fuel oil (VLSFO). Regulations mainly concern the fuel sulfur content, and thus, exhaust gas treatment or new emerging fuels, such as the cycle-oil-based VLSFO, can legally be applied. Unfortunately, despite lower CHS-class emissions, a substantial amount of PAHs is emitted by the VLSFO with higher aromaticity compared to the HFO. Hence, legislative measures might need to take further chemical criteria into account.

Detection of Polycyclic Aromatic Hydrocarbons in High Organic Carbon Ultrafine Particle Extracts by Electrospray Ionization Ultrahigh-Resolution Mass Spectrometry.

The detection of polycyclic aromatic hydrocarbons (PAHs) by electrospray ionization (ESI) without additional reagents or targeted setup changes to the ionization source was observed in ultrafine particle (UFP) extracts, with high organic carbon (OC) concentrations, generated by a combustion aerosol standard (CAST) soot generator. Particulate matter (PM) was collected on filters, extracted with methanol, and analyzed by ESI Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Next to oxygen-containing species, pure hydrocarbons were found to be one of the most abundant compound classes, detected as [M + Na]+ or [M + H]+ in ESI+ and mostly as [M - H]- in ESI-. The assigned hydrocarbon elemental compositions are identified as PAHs due to their high aromaticity index (AI > 0.67) and were additionally confirmed by MS/MS experiments as well as laser desorption ionization (LDI). Thus, despite the relatively low polarity, PAHs have to be considered in the molecular attribution of these model aerosols and/or fresh emissions with low salt content investigated by ESI.

Investigation of COVID-19-related lockdowns on the air pollution changes in augsburg in 2020, Germany.

The COVID-19 pandemic in Germany in 2020 brought many regulations to impede its transmission such as lockdown. Hence, in this study, we compared the annual air pollutants (CO, NO, NO2, O3, PM10, PM2.5, and BC) in Augsburg in 2020 to the record data in 2010-2019. The annual air pollutants in 2020 were significantly (p < 0.001) lower than that in 2010-2019 except O3, which was significantly (p = 0.02) higher than that in 2010-2019. In a depth perspective, we explored how lockdown impacted air pollutants in Augsburg. We simulated air pollutants based on the meteorological data, traffic density, and weekday and weekend/holiday by using four different models (i.e. Random Forest, K-nearest Neighbors, Linear Regression, and Lasso Regression). According to the best fitting effects, Random Forest was used to predict air pollutants during two lockdown periods (16/03/2020-19/04/2020, 1st lockdown and 02/11/2020-31/12/2020, 2nd lockdown) to explore how lockdown measures impacted air pollutants. Compared to the predicted values, the measured CO, NO2, and BC significantly reduced 18.21%, 21.75%, and 48.92% in the 1st lockdown as well as 7.67%, 32.28%, and 79.08% in the 2nd lockdown. It could be owing to the reduction of traffic and industrial activities. O3 significantly increased 15.62% in the 1st lockdown but decreased 40.39% in the 2nd lockdown, which may have relations with the fluctuations the NO titration effect and photochemistry effect. PM10 and PM2.5 were significantly increased 18.23% an 10.06% in the 1st lockdown but reduced 34.37% and 30.62% in the 2nd lockdown, which could be owing to their complex generation mechanisms.

Priority effects in coral-macroalgae interactions can drive alternate community paths in the absence of top-down control.

The outcomes of species interactions can vary greatly in time and space with the outcomes of some interactions determined by priority effects. On coral reefs, benthic algae rapidly colonize disturbed substrate. In the absence of top-down control from herbivorous fishes, these algae can inhibit the recruitment of reef-building corals, leading to a persistent phase shift to a macroalgae-dominated state. Yet, corals may also inhibit colonization by macroalgae, and therefore the effects of herbivores on algal communities may be strongest following disturbances that reduce coral cover. Here, we report the results from experiments conducted on the fore reef of Moorea, French Polynesia, where we: (1) tested the ability of macroalgae to invade coral-dominated and coral-depauperate communities under different levels of herbivory, (2) explored the ability of juvenile corals (Pocillopora spp.) to suppress macroalgae, and (3) quantified the direct and indirect effects of fish herbivores and corallivores on juvenile corals. We found that macroalgae proliferated when herbivory was low but only in recently disturbed communities where coral cover was also low. When coral cover was <10%, macroalgae increased 20-fold within 1 year under reduced herbivory conditions relative to high herbivory controls. Yet, when coral cover was high (50%), macroalgae were suppressed irrespective of the level of herbivory despite ample space for algal colonization. Once established in communities with low herbivory and low coral cover, macroalgae suppressed recruitment of coral larvae, reducing the capacity for coral replenishment. However, when we experimentally established small juvenile corals (2 cm diameter) following a disturbance, juvenile corals inhibited macroalgae from invading local neighborhoods, even in the absence of herbivores, indicating a strong priority effect in macroalgae-coral interactions. Surprisingly, fishes that initially facilitated coral recruitment by controlling algae had a net negative effect on juvenile corals via predation. Corallivores reduced the growth rates of corals exposed to fishes by ~30% relative to fish exclosures, despite increased competition with macroalgae within the exclosures. These results highlight that different processes are important for structuring coral reef ecosystems at different successional stages and underscore the need to consider multiple ecological processes and historical contingencies to predict coral community dynamics.