Spatial distribution of benthic microalgae on coral reefs determined by remote sensing

Understanding the ecological role of benthic microalgae, a highly productive component of coral reef ecosystems, requires information on their spatial distribution. The spatial extent of benthic microalgae on Heron Reef (southern Great Barrier Reef, Australia) was mapped using data from the Landsat 5 Thematic Mapper sensor, integrated with field measurements of sediment chlorophyll concentration and reflectance. Field-measured sediment chlorophyll concentrations, ranging from 23-1,153 mg chl a m^-2, were classified into low, medium, and high concentration classes (1-170, 171-290, and >291 mg chl a m^-2) using a K-means clustering algorithm. The mapping process assumed that areas in the Thematic Mapper image exhibiting similar reflectance levels in red and blue bands would correspond to areas of similar chlorophyll a levels. Regions of homogenous reflectance values corresponding to low, medium, and high chlorophyll levels were identified over the reef sediment zone by applying a standard image classification algorithm to the Thematic Mapper image. The resulting distribution map revealed large-scale (>1 km²) patterns in chlorophyll a levels throughout the sediment zone of Heron Reef. Reef-wide estimates of chlorophyll a distribution indicate that benthic microalgae may constitute up to 20% of the total benthic chlorophyll a at Heron Reef, and thus contribute significantly to total primary productivity on the reef.     

Bathymetry,water optical properties,and benthic classification of coral reefs using hyperspectral remote sensing imagery

The complexity and heterogeneity of shallow coastal waters over small spatial scales provides a challenging environment for mapping and monitoring benthic habitats using remote sensing imagery. Additionally, changes in coral reef community structure are occurring on unprecedented temporal scales that require large-scale synoptic coverage and monitoring of coral reefs. A variety of sensors and analyses have been employed for monitoring coral reefs: this study applied a spectrum-matching and look-up-table methodology to the analysis of hyperspectral imagery of a shallow coral reef in the Bahamas. In unconstrained retrievals the retrieved bathymetry was on average within 5% of that measured acoustically, and 92% of pixels had retrieved depths within 25% of the acoustic depth. Retrieved absorption coefficients had less than 20% errors observed at blue wavelengths. The reef scale benthic classification derived by analysis of the imagery was consistent with the percent cover of specific coral reef habitat classes obtained by conventional line transects over the reef, and the inversions were robust as the results were similar when the benthic classification retrieval was constrained by measurements of bathymetry or water column optical properties. These results support the use of calibrated hyperspectral imagery for the rapid determination of bathymetry, water optical properties, and the classification of important habitat classes common to coral reefs.     

Ecological niche modelling of the distribution of cold-water coral habitat using underwater remote sensing data

Despite a growing appreciation of the need to protect sensitive deep sea ecosystems such as cold-water corals, efforts to map the extent of their distribution are limited by their remoteness. Here we develop ecological niche models to predict the likely distributions of cold-water corals based on occurrence records and data describing environmental parameters (e.g. seafloor terrain attributes and oceanographic conditions). This study has used bathymetric data derived from ship-borne multibeam swath systems, species occurrence data from remotely operated vehicle video surveys and oceanographic parameters from hydrodynamic models to predict coral locations in regions where there is a paucity of direct observations. Predictions of the locations of the scleractinian coral, Lophelia pertusa are based primarily upon ecological niche modelling using a genetic algorithm. Its accuracy has been quantified at local (~ 25 km²) and regional scales (~ 4000 km²) along the Irish continental slope using a variety of error assessment techniques and a comparison with another ecological niche modelling technique. With appropriate choices of parameters and scales of analyses, ecological niche modelling has been effective in predicting the distributions of species at local and regional scales. Refinements of this approach have the potential to be particularly useful for ocean management given the need to manage areas of sensitive habitat where survey data are often limited.     

Review of coral reef ecosystem remote sensing

Coral reef communities face unprecedented pressures at local, regional and global scales as a consequence of climate change and anthropogenic disturbance. Remote sensing, from satellites or aircraft, is possibly the only means to measure the effects of such stresses at appropriately large spatial scales. In the past 30 years, remote sensing of coral reefs has made rapid progress. However, the current technology is still not mature enough to monitor complicated coral reef ecosystems. Compared with foreign research in this field, our work lags far behind. There are still deficiencies in many aspects, such as basic data collection, theoretical research and platform construction. In our nation, it is even unclear how coral reefs disperse and where they may be unhealthy. In this paper, general characteristics of coral reef ecosystems and spectral features of different reef benthos have been summarized, based initially on a review of relevant literature in recent years. Based on the spectral separability of different reef types or benthos, remote sensing can be used to monitor two aspects of coral reefs: (1) Measurement of the ecological properties of reefs. (2) Health assessment of the coral reef ecosystem. In the first part, optical remote sensing methods are widely used to map reef geomorphology and habitats or biotopes. The investigation of geomorphologic zonation has proven to be one of the most successful applications, as different geomorphologic zones are associated with characteristic benthic community structures and occur at spatial scales of tens to hundreds of meters, they are amenable to remote detection by moderate to high resolution sensors. With more and more attention on the ecological problems of coral reefs, a number of studies have used high resolution sensors to map reef communities. The number of classes distinguishable depends on many factors, including the platforms, resolution (spectral, spatial and temporal resolution) and environmental conditions (water depth, water clarity, surface roughness, etc.). Compared with deep water color remote sensing, or terrestrial remote sensing, three techniques for the measurement of reef ecological properties are examined in this paper: (1) Coral reef classification system using remote sensing. (2) Techniques of sea surface correction and water column correction. (3) Techniques of coral reef information extraction from images. In terms of the complexity of coral reef ecosystems, the current techniques still need further improvement or optimization. In the health assessment of coral reef ecosystems, there are two ways to carry out the monitoring using remote sensing: (1) Monitoring the pigment or symbiotic zooxanthellae contents in corals. (2) Measuring the environmental properties of reefs. The first way is theoretically feasible, but difficult to achieve in practice. Currently, most reef health assessments are carried out by measuring environmental parameters, including sea surface temperature, solar radiation, ultraviolet radiation, water color, wind speed and direction, rainfall, ocean acidification, sea level, etc., of which sea surface temperature has been routinely measured by NOAA to monitor coral bleaching. In addition to the contents above, this article puts forward five main prospects for development in the future: (1) Establishment of a coral reef classification system using remote sensing. (2) Satellite launch for monitoring coral reefs. (3) Theoretical and methodological development. (4) Establishment of a spectral database for different reef benthos. (5) Integrated application of multi-source remote sensing data. It is hoped that the information provided here will be a reference for subsequent similar studies.     

Neritic carbonate for six submerged coral reefs from northern Australia: Implications for Holocene global carbon dioxide

Total contribution of six recently discovered submerged coral reefs in northern Australia to Holocene neritic CaCO₃ and CO₂ is assessed to address a gap in global budgets. CaCO₃ production for the reef framework and inter-reefal deposits is 0.26–0.28 Mt. Holocene CO₂ production is 0.14–0.16 Mt. Coral and coralline algae are the dominant sources of Holocene CaCO₃ although foraminifers and molluscs are the dominant constituents of inter-reefal deposits. The total amount of Holocene neritic CaCO₃ produced by the six submerged coral reefs is several orders of magnitude smaller than that calculated using accepted CaCO₃ production values because of very low production, a ‘give-up’ growth history, and presumed significant dissolution and exports. The contribution of submerged coral reefs to global Holocene neritic CaCO₃ is estimated to be 0.26–0.62 Gt, which yields 0.15–0.37 Gt of CO₂. This amount of CO₂ is 0.02–0.05% of the 780 Gt added to the atmosphere since 18 kyr BP. Contributions from Australian submerged coral reefs are estimated to be 0.05 Gt CaCO₃ and 0.03 Gt CO₂ for an emergent reef area of 47.9 × 10³ km². Based on the growth history of the submerged coral reefs in the Gulf of Carpentaria, maximum global Holocene CaCO₃ fluxes could have attained 0.3 Gt yr^− 1 between 11 and 7 ka BP. This additional CaCO₃ would have culminated in a maximum CaCO₃ production from all (emergent and submerged) coral reefs of 1.2 Gt yr^− 1 and neritic CaCO₃ production of 2.75 Gt yr^− 1. The dilemma remains that the global area and CaCO₃ mass of submerged coral reefs are currently unknown. It is inevitable that many more submerged coral reefs will be found. Our findings imply that submerged coral reefs are a small but fundamental source of Holocene neritic CaCO₃ and CO₂.     

Mapping migratory bird prevalence using remote sensing data fusion

Background

Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA.

Methodology and Principal Findings

A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy (“fusion”) models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species.

Conclusion and Significance

Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.     

Choosing the appropriate spatial resolution for monitoring coral bleaching events using remote sensing

Bleached corals provide a strong optical signal that suggests that remote sensing investigations of major bleaching events are feasible using airborne or satellite sensors. However, patchy coral cover, varying intensities of bleaching, and water depths are likely to limit the application of remote sensing techniques in monitoring and mapping coral bleaching. Today, satellite multispectral sensors routinely provide images of reefs from 4 m (Ikonos) to 30 m resolution (Landsat); however, the adequacy of these sensors for monitoring and mapping bleaching events remains unclear. To clarify these issues, scanned aerial photographs acquired during the 1998 bleaching event over the Great Barrier Reef (Australia) were analyzed at various spatial resolutions, from 10 cm to 5 m. We found that the accuracy of mapping bleaching is highly sensitive to spatial resolution. Highest accuracy was obtained at 10 cm resolution for detection of totally bleached colonies. At 1 m resolution, as much as 50% of the 10-cm resolution signal is lost, though the spatial patterns remain correctly described. Partially bleached (pale) corals are difficult to detect even in aerial surveys, leading to an underestimation of overall bleaching levels (total and partial bleaching) in aerial photos compared to in-situ surveys. If data volume and processing time are limiting factors, local variance analysis suggests that the optimal resolution necessary to capture spatial patterns of bleaching is in the range 40-80 cm.     

Mapping an invasive bryophyte species using hyperspectral remote sensing data

Reliable distribution maps are crucial for the management of invasive plant species. An alternative to traditional field surveys is the use of remote sensing data, which allows coverage of large areas. However, most remote sensing studies on invasive plant species focus on mapping large stands of easily detectable study species. In this study, we used hyperspectral remote sensing data in combination with field data to derive a distribution map of an invasive bryophyte species, Campylopus introflexus, on the island of Sylt in Northern Germany. We collected plant cover data on 57 plots to calibrate the model and presence/absence data of C. introflexus on another 150 plots for independent validation. We simultaneously acquired airborne hyperspectral (APEX) images during summer 2014, providing 285 spectral bands. We used a Maxent modelling approach to map the distribution of C. introflexus. Although C. introflexus is a small and inconspicuous species, we were able to map its distribution with an overall accuracy of 75 %. Reducing the sampling effort from 57 to 7 plots, our models performed fairly well until sampling effort dropped below 12 plots. The model predicts that C. introflexus is present in about one quarter of the pixels in our study area. The highest percentage of C. introflexus is predicted in the dune grassland. Our findings suggest that hyperspectral remote sensing data have the potential to provide reliable information about the degree of bryophyte invasion, and thus provide an alternative to traditional field mapping approaches over large areas.     

Marine pollution and coral reefs

Coral reefs are exposed to many anthropogenic stresses increasing in impact and range, both on local and regional scales. The main ones discussed here are nutrient enrichment, sewage disposal, sedimentation, oil-related pollution, metals and thermal pollution. The stress comprising the main topic of this article, eutrophication, is examined from the point of view of its physiological and ecological mechanisms of action, on a number of levels. Nutrient enrichment can introduce an imbalance in the exchange of nutrients between the zooxanthellae and the host coral, it reduces light penetration to the reef due to nutrient- stimulated phytoplankton growth, and, most harmful of all, may bring about proliferation of seaweeds. The latter rapidly outgrow, smother and eventually replace, the slow-growing coral reef, adapted to cope with the low nutrient concentrations typical in tropical seas.
Eutrophication seldom takes place by itself. Sewage disposal invariably results in nutrient enrichment, but it also enriches the water with organic matter which stimulates proliferation of oxygen-consuming microbes. These may kill corals and other reef organisms, either directly by anoxia, or by related hydrogen sulfide production. Increased sediment deposition is in many cases associated with other human activities leading to eutrophication, such as deforestation and topsoil erosion.
Realistically achievable goals to ensure conservation, and in some instances, rehabilitation of coral reefs are listed.     

珊瑚共生体碳代谢特征研究进展

珊瑚礁作为一种典型的海洋生态系统,具有巨大的固碳和储碳潜力。然而,目前对于珊瑚礁的净碳能力(碳释放与碳吸收)仍存在争议,主要归因于珊瑚共生体碳代谢的多样性和复杂性。珊瑚礁在生物钙化、呼吸过程中向大气释放二氧化碳(CO₂);但在生物合成和沉积过程中却可以将碳进行固定与埋藏;为此,珊瑚礁的碳源碳汇身份还有待明确。现有部分研究表明,共生体通过碳代谢可以促进珊瑚礁吸收大气中的CO₂。此外,珊瑚礁和海岸带蓝碳生态系统通常表现出很强的连通性,珊瑚共生体碳代谢能有效提高海岸带盐沼植被、海草床、海洋浮游植物等生物的碳汇功能。为了加深对珊瑚礁碳源-碳汇功能的理解,综述了珊瑚共生体的碳代谢特征,梳理了共生体中碳的关键生态过程(有机碳的迁移、无机碳的转化、两者的赋存状态),总结了细菌-虫黄藻-病毒在共生体碳代谢中的作用,评述了珊瑚礁碳源-碳汇特征及影响因子。旨在阐明珊瑚共生体碳代谢的关键过程,并基于此寻求有效的珊瑚礁碳增汇技术,形成以碳增量为主的珊瑚保护与修复技术,提升珊瑚礁在蓝碳生态系统中的贡献。     

Sea urchin bioerosion on coral reefs: place in the carbonate budget and relevant variables

Two aspects of erosion by sea urchins (Echinoidea) in coral reef habitats are: the direct passage of reef framework material through the gut and the indirect effects through the weakening of the reef structure. Urchin bioerosion can equal or exceed reef carbonate production. The impact of urchins on reefs depends on three variables: species type, test size and population density. Large differences in bioerosion by urchins of the same test size occur between different species. Size differences between species in a sea urchin community, as well as size differences within a species along a reef, can be significant. Bioerosion per urchin increases enormously with size. Changes in population density, through time and space, result in significant changes in bioerosion. It is demonstrated how the interaction of these variables determines in-situ sea urchin bioerosion.     

Improved retrieval of Secchi depth for optically-complex waters using remote sensing data

Water transparency is one of the ecological indicators for describing water quality and the underwater light field which determines its productivity. In the European Water Framework Directive (WFD) as well as in the European Marine Strategy Framework Directive (MSFD) water transparency is used for ecological status classification of inland, coastal and open sea waters and it is regarded as an indicator for eutrophication in Baltic Sea management (HELCOM, 2007). We developed and compared different empirical and semi-analytical algorithms for lakes and coastal Nordic waters to retrieve Secchi depth (Z_SD) from remote sensing data (MERIS, 300 m resolution). The algorithms were developed in water bodies with high coloured dissolved organic matter absorption (a_CDOM(442) ranging 1.7–4.0 m⁻¹), Chl a concentration (0.5–73 mg m⁻³) and total suspended matter (0.7–37.5 g m⁻³) and validated against an independent data set over inland and coastal waters (0.6 m < Z_SD < 14.8 m). The results indicate that for empirical algorithms, using longer wavelengths in the visible spectrum as a reference band decreases the RMSE and increases the coefficient of determination (R²). The accuracy increased (R² = 0.75, RMSE = 1.33 m, n = 134) when Z_SD was retrieved via an empirical relationship between Z_SD and K_d(490). The best agreement with in situ data was attained when Z_SD was calculated via both the diffuse and the beam attenuation coefficient (R² = 0.89, RMSE = 0.77 m, n = 89). The results demonstrate that transparency can be retrieved with high accuracy over various optical water types by the means of ocean color remote sensing, improving both the spatial and temporal coverage. The satellite derived Z_SD product could be therefore used as an additional source of information for WFD and MSFD reporting purposes.     

Biological destruction of coral reefs

The major agents of biological destruction of coral reefs can be divided into grazers, etchers and borers. Each of these groups is reviewed on a world wide basis, together with the mechanisms by which they destroy the coral substrate. Rates of bioerosion attributed to major agents of grazers, etchers and borers are given, together with limitations of some of the measurements. Recent work is highlighting the variability in rates of bioerosion both over time and space. Factors which may be responsible for this variability are discussed. Bioerosion is a major factor influencing reef morphology and the ways in which this is achieved is discussed in some detail. Although the review concentrates mainly on present day reefs, some attempt is made to consider the impact of bioerosion on older reefs.     

Ground-level spectroscopy analyses and classification of coral reefs using a hyperspectral camera

With the general aim of classification and mapping of coral reefs, remote sensing has traditionally been more difficult to implement in comparison with terrestrial equivalents. Images used for the marine environment suffer from environmental limitation (water absorption, scattering, and glint); sensor-related limitations (spectral and spatial resolution); and habitat limitation (substrate spectral similarity). Presented here is an advanced approach for ground-level surveying of a coral reef using a hyperspectral camera (400–1,000 nm) that is able to address all of these limitations. Used from the surface, the image includes a white reference plate that offers a solution for correcting the water column effect. The imaging system produces millimeter size pixels and 80 relevant bands. The data collected have the advantages of both a field point spectrometer (hyperspectral resolution) and a digital camera (spatial resolution). Finally, the availability of pure pixel imagery significantly improves the potential for substrate recognition in comparison with traditionally used remote sensing mixed pixels. In this study, an image of a coral reef table in the Gulf of Aqaba, Red Sea, was classified, demonstrating the benefits of this technology for the first time. Preprocessing includes testing of two normalization approaches, three spectral resolutions, and two spectral ranges. Trained classification was performed using support vector machine that was manually trained and tested against a digital image that provided empirical verification. For the classification of 5 core classes, the best results were achieved using a combination of a 450–660 nm spectral range, 5 nm wide bands, and the employment of red-band normalization. Overall classification accuracy was improved from 86 % for the original image to 99 % for the normalized image. Spectral resolution and spectral ranges seemed to have a limited effect on the classification accuracy. The proposed methodology and the use of automatic classification procedures can be successfully applied for reef survey and monitoring and even upscaled for a large survey.     

Predicting species distributions across the Amazonian and Andean regions using remote sensing data

Aim We explore the utility of newly available optical and microwave remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and QuikSCAT (QSCAT) instruments for species distribution modelling at regional to continental scales. Using eight Neotropical species from three taxonomic groups, we assess the extent to which remote sensing data can improve predictions of their geographic distributions. For two bird species, we investigate the specific contributions of different types of remote sensing variables to the predictions and model accuracy at the regional scale, where the benefits of the MODIS and QSCAT satellite data are expected to be most significant. Location South America, with a focus on the tropical and subtropical Andes and the Amazon Basin. Methods Potential geographic distributions of eight species, namely two birds, two mammals and four trees, were modelled with the maxent algorithm at 1‐km resolution over the South American continent using climatic and remote sensing data separately and combined. For each species and model scenario, we assess model performance by testing the agreement between observed and simulated distributions across all thresholds and, in the case of the two focal bird species, at selected thresholds. Results Quantitative performance tests showed that models built with remote sensing and climatic layers in isolation performed well in predicting species distributions, suggesting that each of these data sets contains useful information. However, predictions created with a combination of remote sensing and climatic layers generally resulted in the best model performance across the three taxonomic groups. In Ecuador, the inclusion of remote sensing data was critical in resolving the known geographically isolated populations of the two focal bird species along the steep Amazonian–Andean elevational gradients. Within remote sensing subsets, microwave‐based data were more important than optical data in the predictions of the two bird species. Main conclusions Our results suggest that the newly available remote sensing data (MODIS and QSCAT) have considerable utility in modelling the contemporary geographical distributions of species at both regional and continental scales and in predicting range shifts as a result of large‐scale land‐use change.     

Estimating biophysical parameters of rice with remote sensing data using support vector machines

Hyperspectral reflectance (350–2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application. Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters, comprising leaf area index (LAI; m² green leaf area m⁻² soil) and green leaf chlorophyll density (GLCD; mg chlorophyll m⁻² soil), using stepwise multiple regression (SMR) models and support vector machines (SVMs). Four transformations of the rice canopy data were made, comprising reflectances (R), first-order derivative reflectances (D1), second-order derivative reflectances (D2), and logarithm transformation of reflectances (LOG). The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI, with a root mean square error (RMSE) of 1.0496 LAI units. The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD, with an RMSE of 523.0741 mg m⁻². The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters, but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.     

Mapping coral reefs using consumer-grade drones and structure from motion photogrammetry techniques

We propose a novel technique to measure the small-scale three-dimensional features of a shallow-water coral reef using a small drone equipped with a consumer-grade camera, a handheld GPS and structure from motion (SfM) algorithms. We used a GoPro HERO4 with a modified lens mounted on a DJI Phantom 2 drone (maximum total take-off weight <2 kg) to perform a 10 min flight and collect 306 aerial images with an overlap equal or greater than 90%. We mapped an area of 8380 m², obtaining as output an ortho-rectified aerial photomosaic and a bathymetric digital elevation model (DEM) with a resolution of 0.78 and 1.56 cm pixel⁻¹, respectively. Through comparison with airborne LiDAR data for the same area, we verified that the location of the ortho-rectified aerial photomosaic is accurate within ~1.4 m. The bathymetric difference between our DEM and the LiDAR dataset is −0.016 ± 0.45 m (1σ). Our results show that it is possible, in conditions of calm waters, low winds and minimal sun glint, to deploy consumer-grade drones as a relatively low-cost and rapid survey technique to produce multispectral and bathymetric data on shallow-water coral reefs. We discuss the utility of such data to monitor temporal changes in topographic complexity of reefs and associated biological processes.

     

Assessing coral reefs on a pacific-wide scale using the microbialization score

The majority of the world's coral reefs are in various stages of decline. While a suite of disturbances (overfishing, eutrophication, and global climate change) have been identified, the mechanism(s) of reef system decline remain elusive. Increased microbial and viral loading with higher percentages of opportunistic and specific microbial pathogens have been identified as potentially unifying features of coral reefs in decline. Due to their relative size and high per cell activity, a small change in microbial biomass may signal a large reallocation of available energy in an ecosystem; that is the microbialization of the coral reef. Our hypothesis was that human activities alter the energy budget of the reef system, specifically by altering the allocation of metabolic energy between microbes and macrobes. To determine if this is occurring on a regional scale, we calculated the basal metabolic rates for the fish and microbial communities at 99 sites on twenty-nine coral islands throughout the Pacific Ocean using previously established scaling relationships. From these metabolic rate predictions, we derived a new metric for assessing and comparing reef health called the microbialization score. The microbialization score represents the percentage of the combined fish and microbial predicted metabolic rate that is microbial. Our results demonstrate a strong positive correlation between reef microbialization scores and human impact. In contrast, microbialization scores did not significantly correlate with ocean net primary production, local chla concentrations, or the combined metabolic rate of the fish and microbial communities. These findings support the hypothesis that human activities are shifting energy to the microbes, at the expense of the macrobes. Regardless of oceanographic context, the microbialization score is a powerful metric for assessing the level of human impact a reef system is experiencing.