Volume Backscatter Coefficient Research Articles

Canopy active fuel loads estimation with C-band PolSAR by combining polarization decomposition and vegetation scattering model: a case study in Southwestern China

ABSTRACT The forest canopy active fuel load (CAFL) is easily flammable that is usually consumed in the flaming front, and is a critical factor in crown fire early prediction, suppression and response. Previous studies universally relied on optical remote sensing data, whose effectiveness is extremely limited in regions with cloud cover and haze, such as the southwest of Sichuan, China. Synthetic aperture radar (SAR) can work 24 h and is not affected by weather conditions. This study aims to evaluate the potential of volume backscattering coefficients extracted through decomposition of polarimetric SAR (PolSAR, Radarsat-2 C band) for CAFL estimation. The polarimetric decomposition method used in this study was based on Freeman-Durden decomposition. The separated volume backscattering coefficients were used to estimate CAFL based on the variant of the extended water cloud model (VEWCM). For comparison, the SAR raw observations and extended water cloud model (EWCM) were also used to estimate CAFL. The performance of these two models was validated through quantitative assessment, utilizing CAFL measurements obtained from southwest Sichuan and the leave-one-out cross-validation method. Results show that the VEWCM (R2 = 0.69, RMSE = 0.87 tons/ha) performed better than EWCM (R2 = 0.60, RMSE = 1.48 tons/ha) especially in HV polarization. We concluded that PolSAR has the potential to improve CAFL estimation and further assist with pre-fire risk warnings, fire suppression responses, and post-fire effects assessment.

A Backscatter Model Combing Wind and Rain Effect at Low Incidence Angles

As the Wind blows over the ocean surface, the generated waves are the primary factor affecting the microwave backscatter of the remote sensing radar. In addition, there are also some influencing factors, such as rainfall, which is the best-known atmospheric phenomenon. This paper proposes a wind and rain backscatter model whose angle of incidence is from 1 to 6 deg. The model is developed by considering the influence of ocean surface wind, atmospheric rain attenuation, rain volume backscatter and interactions between raindrops and ocean surface. The wind-induced component of the model adopted a quasi-specular theoretical model for the isotropic rough surface of Gaussian statistics. Rain attenuation is expressed as a coefficient of the model, and rain volume backscatter is expressed as a function of the rain volume backscattering coefficient, the thickness of precipitation layer and the incidence angle. Interactions between raindrops and ocean surface are complicated and deduced from the collocated dataset from the Precipitation Radar onboard the Tropical Rainfall Measuring Mission satellite and the European Centre for Medium-Range Weather Forecasts. Based on the collocated dataset, the result shows the proposed model can estimate reasonably accurate estimates surface backscatter within wind speeds range from 8 to 18 m s−1.

Echo grid integration: A novel method for preprocessing multibeam water column data to quantify underwater gas bubble emissions

AbstractWater column imaging multibeam echo sounder systems (MBESs) are a promising technology for quantitative estimates of the gas bubble volume flow within large gas seepage areas. Considerable progress has been made in recent years toward applicable calibration methods for MBESs as well as developing inversion models to convert acoustically measured backscattering cross sections to gas bubble volume flow. However, MBESs are still not commonly used for quantitative gas flow assessments. A reason for this is the absence of published processing methods that demonstrate how MBES data can be processed to quantitatively represent bubble streams. Here, we present a novel method (echo grid integration) that allows for assessing the aggregated backscattering cross section of targets within horizontal water layers. This derived value enables quantifying bubble stream gas flow rates using existing acoustic inversion methods. The presented method is based on averaging geo‐referenced volume backscattering coefficients onto a high‐resolution 3D voxel‐grid. The results are multiplied with the voxel volume to represent measurements of the total backscattering cross‐section within each voxel cell. Individual gridded values cannot be trusted because the beam pattern effects cause the values of individual targets to “smear” over multiple grid‐cells. The true aggregated backscattering cross‐section is thus estimated as the integral over the grid‐cells affected by this smearing. Numerical simulation of MBES data acquisition over known targets assesses the method's validity and quantify it's uncertainty for different, realistic scenarios. The found low measurement bias (< 1%), and dispersion (< 5%) are promising for application in gas flow quantification methods.

Signatures of gravity wave-induced instabilities in balloon lidar soundings of polar mesospheric clouds

Abstract. The Balloon Lidar Experiment (BOLIDE), which was part of the Polar Mesospheric Cloud Turbulence (PMC Turbo) Balloon Mission has captured vertical profiles of PMCs during a 6 d flight along the Arctic circle in July 2018. The high-resolution soundings (20 m vertical and 10 s temporal resolution) reveal highly structured layers with large gradients in the volume backscatter coefficient. We systematically screen the BOLIDE dataset for small-scale variability by assessing these gradients at high resolution. We find longer tails of the probability density distributions of these gradients compared to a normal distribution, indicating intermittent behaviour. The high occurrence rate of large gradients is assessed in relation to the 15 min averaged layer brightness and the spectral power of short-period (5–62 min) gravity waves based on PMC layer altitude variations. We find that variability on small scales occurs during weak, moderate, and strong gravity wave activity. Layers with below-average brightness are less likely to show small-scale variability in conditions of strong gravity wave activity. We present and discuss the signatures of this small-scale variability, and possibly related dynamical processes, and identify potential cases for future case studies and modelling efforts.

The polar mesospheric cloud dataset of the Balloon Lidar Experiment (BOLIDE)

Abstract. The Balloon Lidar Experiment (BOLIDE) observed polar mesospheric clouds (PMCs) along the Arctic circle between Sweden and Canada during the balloon flight of PMC Turbo in July 2018. The purpose of the mission was to study small-scale dynamical processes induced by the breaking of atmospheric gravity waves by high-resolution imaging and profiling of the PMC layer. The primary parameter of the lidar soundings is the time- and range-resolved volume backscatter coefficient β. These data are available at high resolutions of 20 m and 10 s (Kaifler, 2021, https://doi.org/10.5281/zenodo.5722385). This document describes how we calculate β from the BOLIDE photon count data and balloon floating altitude. We compile information relevant for the scientific exploration of this dataset, including statistics, mean values, and temporal evolution of parameters like PMC brightness, altitude, and occurrence rate. Special emphasis is given to the stability of the gondola pointing and the effect of resolution on the signal-to-noise ratio and thus the detection threshold of PMC. PMC layers were detected during 49.7 h in total, accounting for 36.8 % of the 5.7 d flight duration and a total of 178 924 PMC profiles at 10 s resolution. Up to the present, published results from subsets of this dataset include the evolution of small-scale vortex rings, distinct Kelvin–Helmholtz instabilities, and mesospheric bores. The lidar soundings reveal a wide range of responses of the PMC layer to larger-scale gravity waves and breaking gravity waves, including the accompanying instabilities, that await scientific analysis.

Evaluation of echosounder data preparation strategies for modern machine learning models

Fish stock assessment and management requires accurate estimates of fish abundance, which are typically derived from echosounder observations using acoustic target classification (ATC). Skilled operators are regularly assisted in classifying acoustic targets by software and there has been an increasing interest toward using machine learning to create improved tools. Recent studies have applied deep learning approaches to acoustic data, however, algorithm data-preparation strategies (influencing model output) are presently poorly understood and standardization is needed to enable collaborative research and management. For example, a common pre-processing technique is to resample backscatter data coming from echosounder measurements from the original resolution to a coarser resolution in the horizontal (time) and vertical (range) directions. Using data values derived from the volume backscattering coefficient obtained during the Norwegian sandeel survey, we investigate which resampling resolutions are suitable for ATC using a convolutional neural network trained to classify single values of backscatter data. This process is known as pixel-level semantic segmentation. Our results indicate that it is possible to downsample the data if important information related to acoustic characteristics is not smoothed out. We also show that the classification performance is improved when providing the network with contextual information relating to range. These findings will provide input to fisheries acoustic data standards and contribute to the on-going development of automated ATC methods.

Finite-amplitude sound propagation effects in volume backscattering measurements for fish abundance estimation

Scientific advice for governmental management of marine resources relies on acoustical observation methods. Quantification and identification of fish and plankton species are often achieved using multi-frequency acoustic data. Accurate measurements of backscattering cross-sections and volume backscattering coefficients are essential. Systematic errors from finite-amplitude sound propagation are demonstrated in experimental survey measurements on Atlantic mackerel using 120 kHz and 200 kHz echosounders and high power settings. Finite-amplitude signal distortion causes excess transmission loss that is not accounted for in fisheries acoustics today, other than by fixed limits on the maximum transmitted power. The demonstrated errors are of a magnitude that can seriously bias abundance estimation and species identification. It is shown how the finite-amplitude effects can be modelled and predicted quantitatively, within a framework of electroacoustic power budget equations. A method is provided to calculate related errors in echosounder calibration and oceanic measurement of acoustic volume backscattering. When accounting for finite-amplitude effects in echosounder signal processing, higher transmit powers can be used when needed to improve signal-to-noise ratio or extend measurement range. The results indicate that historical survey data can be adjusted for such errors using numerical simulations. The echosounder characteristics relevant to finite-amplitude effects can be determined by laboratory measurements.

Spectrally Resolved Raman Lidar to Measure Backscatter Spectra of Atmospheric Three-Phase Water and Fluorescent Aerosols Simultaneously: Instrument, Methodology, and Preliminary Results

This work presents a spectrally resolved Raman lidar (SRRL) for simultaneous measurement of volume backscattering coefficient spectra (backscatter spectra for short) of atmospheric three-phase water and fluorescent aerosols. The SRRL emits 354.8-nm laser light and records both N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Raman echoes around 386.7 nm and spectral signals in a specially modified spectral range of ~393–424 nm. By defining normalized spectra, a unique spectra decomposition approach is developed for successive retrieval of normalized spectra components of fluorescent aerosols, water vapor, ice water, and liquid water. Furthermore, the backscatter spectra of each component are obtained by referencing the N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Raman signals. Three typical measurement cases are provided. For the clear-day case, the lidar-measured normalized water vapor Raman spectra are found to be nearly invariant in shape and can serve as background spectra reference for decomposition of mixed-phase water Raman spectra. Besides, fluorescence backscatter intensities are usually weak enough to be neglected in clear areas. For the fluorescence case, the fluorescence backscatter intensities become much stronger to prevent accurate measurements of water vapor. For the mixed-phase water virga case, the decomposed backscatter spectra of condensed ice and liquid water indicate the coexistence of ice water and less amount of liquid water in the falling water virga. In conclusion, this kind of SRRL is believed to have provided the potential for simultaneous and accurate profiling of atmospheric water vapor and cloud liquid/ice water and opened up new perspectives for studies of cloud–aerosol interaction.

An Improved Backscattering Theoretical Model for Snow Area

Remote sensing has been studied for a long time to monitor the earth terrain. Remote sensing technology has been used globally in many different fields and one of the most popular area of study that uses remote sensing technology is snow monitoring. In previous researches, remote sensing has been modelled on snow area to study the scattering mechanisms of various scattering processes. In this paper, surface volume second order term that was dropped in previous study is derived, included and studied to observe the improvement in the surface volume backscattering coefficient. This new model is applied on snow layer above ground and the snow layer is modelled as a volume of ice particles as the Mie scatterers that are closely packed and bounded by irregular boundaries. Various parameters are used to investigate the improvement of adding the new term. Results show improvement in cross-polarized return, for all the range of parameters studied. Comparison is made with the field measurement result from U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) in 1990. Close agreement is shown between developed model and data field backscattering coefficient result.

Investigation of Aerosol Inhomogeneities Parameters in Planetary Boundary Layer in UV-A Spectral Region

For today necessity of atmosphere wind remote sensing for wide pool of applications require development of new measurement methods and improvement of already existing.Currently doppler methods for wind speed measuring have largest sensing range. Correlation-based methods are provide lower sensing range for wind speed measurement. However, doppler-based lidar are expensive in opposite to simply designed correlation lidars that additionally allows to measure wind profile along sensing direction.Development of wind correlation lidars required knowledge of atmosphere aerosol inhomogeneities parameters.The most experimental research till now in this area are related to visible spectral range.One of the perspective eye-safety spectral range for wind lidar is UV spectral region. There not so much experimental research works of aerosol inhomogeneities parameters in UV.This paper is related to field experiments of aerosol inhomogeneities parameters in planetary boundary layer on 0.355 um operating wavelength.Block diagram and parameters of lidar with 0.355 operating wavelength is shown. Process of experiments is described. Typical atmosphere backscattering echo-signal for single laser pulse is demonstrated.Procedures if lidar signals processing are described, example of two-dimensional field of relative fluctuations of volume backscattering coefficient for different atmosphere conditions is shown.Results of measurement data processing shown that in planetary boundary layer average contrast of aerosol inhomogeneities in most cases has values in range 0,4% – 10 % (in case of snow up to 25%), and size in range 1,5 – 20 m. Dependency of observation number of aerosol inhomogeneities by range z from lidar to backscattering volume is descending with 1/z manner that the same for dependency for signal-noise ratio SNR(z).

Estimating individual fish school biomass using digital omnidirectional sonars, applied to mackerel and herring

Abstract Economic profitability and responsible fisheries are objectives of fishermen and fisheries managers. In purse seine fisheries, an accurate biomass estimate of the targeted school is crucial to accomplish this. For this study, omnidirectional fisheries sonar was used to estimate individual school biomass of Norwegian spring spawning herring (Clupea harengus) and Atlantic mackerel (Scomber scombrus). A sonar sampling design based on professional skipper’s experience provided detailed information on school dimensions and acoustic backscattering. Using calibrated digital sonar data, school volume and fish densities were obtained, and school biomass computed. A positive linear relation was found between the estimated sonar school biomass and purse seine catches for both species (r2 = 0.92; residual standard error, RSE = 4.7 t). Large variability in volume backscattering coefficient and uncertainty in side-aspect target strength (TS) are the main sources of discrepancy between the estimates and the catch. Using a 4 dB (39%) weaker mean TS for mean side-aspect TS than the normal mean dorsal aspect TS was needed for optimizing the 1:1 relationship between sonar biomass estimate and catch. Accurate estimation of single school biomass can reduce the catch of unexpectedly large schools, leading to improvements in economic efficiency and reduced release of dead or dying fish.

Ground-based lidar processing and simulator framework for comparing models and observations (ALCF 1.0)

Abstract. Automatic lidars and ceilometers (ALCs) provide valuable information on cloud and aerosols but have not been systematically used in the evaluation of general circulation models (GCMs) and numerical weather prediction (NWP) models. Obstacles associated with the diversity of instruments, a lack of standardisation of data products and open processing tools mean that the value of large ALC networks worldwide is not being realised. We discuss a tool, called the Automatic Lidar and Ceilometer Framework (ALCF), that overcomes these problems and also includes a ground-based lidar simulator, which calculates the radiative transfer of laser radiation and allows one-to-one comparison with models. Our ground-based lidar simulator is based on the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP), which has been extensively used for spaceborne lidar intercomparisons. The ALCF implements all steps needed to transform and calibrate raw ALC data and create simulated attenuated volume backscattering coefficient profiles for one-to-one comparison and complete statistical analysis of clouds. The framework supports multiple common commercial ALCs (Vaisala CL31, CL51, Lufft CHM 15k and Droplet Measurement Technologies MiniMPL), reanalyses (JRA-55, ERA5 and MERRA-2) and models (the Unified Model and AMPS – the Antarctic Mesoscale Prediction System). To demonstrate its capabilities, we present case studies evaluating cloud in the supported reanalyses and models using CL31, CL51, CHM 15k and MiniMPL observations at three sites in New Zealand. We show that the reanalyses and models generally underestimate cloud fraction. If sufficiently high-temporal-resolution model output is available (better than 6-hourly), a direct comparison of individual clouds is also possible. We demonstrate that the ALCF can be used as a generic evaluation tool to examine cloud occurrence and cloud properties in reanalyses, NWP models, and GCMs, potentially utilising the large amounts of ALC data already available. This tool is likely to be particularly useful for the analysis and improvement of low-level cloud simulations which are not well monitored from space. This has previously been identified as a critical deficiency in contemporary models, limiting the accuracy of weather forecasts and future climate projections. While the current focus of the framework is on clouds, support for aerosol in the lidar simulator is planned in the future.

A technical description of the Balloon Lidar Experiment (BOLIDE)

Abstract. The Balloon Lidar Experiment (BOLIDE) was the first high-power lidar flown and operated successfully on board a balloon platform. As part of the PMC Turbo payload, the instrument acquired high-resolution backscatter profiles of polar mesospheric clouds (PMCs) from an altitude of ∼ 38 km during its maiden ∼ 6 d flight from Esrange, Sweden, to northern Canada in July 2018. We describe the BOLIDE instrument and its development and report on the predicted and actual in-flight performance. Although the instrument suffered from excessively high background noise, we were able to detect PMCs with a volume backscatter coefficient as low as 0.6×10-10 m−1 sr−1 at a vertical resolution of 100 m and a time resolution of 30 s.

Bloom-forming toxic cyanobacterium Microcystis: Quantification and monitoring with a high-frequency echosounder

Harmful cyanobacterial blooms pose a serious environmental threat to freshwater lakes and reservoirs. Investigating the dynamics of toxic bloom-forming cyanobacterial genus Microcystis is a challenging task due to its huge spatiotemporal heterogeneity. The hydroacoustic technology allows for rapid scanning of the water column synoptically and has a significant potential for rapid, non-invasive in situ quantification of aquatic organisms. The aim of this work is to develop a reliable cost-effective method for the accurate quantification of the biomass (B) of gas-bearing cyanobacterium Microcystis in water bodies using a high-frequency scientific echosounder. First, we showed that gas-bearing Microcystis colonies are much stronger backscatterers than gas-free phytoplanktonic algae. Then, in the tank experiments, we found a strong logarithmic relationship between the volume backscattering coefficient (sv) and Microcystis B proxies, such as Microcystis-bound chlorophyll a (Chl aMicro) and particle volume concentration. The sv/B ratio remained unchanged over a wide range of B concentrations when the same source of Microcystis material was used. Our measurements in Lake Dianchi (China) also revealed strong logarithmic relationship between sv and Chl aMicro. The biomass-calibrated echosounder was used to study the diurnal variability of Microcystis B in the lake. We found a sharp increase in the cyanobacterium B and sv/Chl aMicro ratio near the water surface during the daytime and more uniform distribution of these parameters during the nighttime. We argue that the variations in B and sv/Chl aMicro ratio could be associated with temporal changes in thermal stratification and turbulent mixing. Our data suggest that the sv/Chl aMicro ratio positively correlates with (i) the percentage of larger colonies in population and/or (ii) the content of free gas in cells. The last properties allow Microcystis colonies to attain rapid floating, which enables them to concentrate at the water surface at conducive ambient conditions. The sv/Chl aMicro ratio can be a new important variable reflecting the ability of Microcystis colonies to migrate vertically. Monitoring of this ratio may help to determine the early warning threshold for Microcystis scum formation. The proposed acoustic technology for in situ quantification of Microcystis biomass can be a powerful tool for accurate monitoring and assessment of this cyanobacterium at high spatiotemporal resolution in water bodies.

FiniteAmplitude Power Budget Equations for Acoustic Fish Abundance Estimation

Finiteamplitude (nonlinear) sound propagation effects in seawater may cause measurement errors in fish and zooplankton abundance estimation and species identification for accessible echo sounder transmit electrical power levels and operating frequencies of about 100 kHz and higher. A sufficiently validated framework to quantify, control, and compensate for such errors in these applications is not available. The conventional power budget equations in fisheries acoustics are valid for smallamplitude signals only. The study aims to fill this “gap”. The conventional theory is generalized to account for finiteamplitude incident sound propagation, arbitrary electrical termination, and the range of electrical and acoustical echo sounder parameters. Equations for use in calibration and oceanic surveying are derived in terms of the backscattering cross section,, and the volume backscattering coefficient,. The “finiteamplitude terms” in these expressions can—for relevant transmit electrical power levels of relevant echo sounders—be measured in controlled tank experiments. Alternatively, they can be calculated using numerical models. The resulting equations enable estimation of finiteamplitude measurement errors in these applications; development of recommended upper limits for echo sounder power levels; controlled reduction of finiteamplitude errors in calibration and surveying; and development of correction factors for survey data already subjected to such measurement errors.

Lidar Observation of Mesospheric Clouds Above Beijing: A Case Study

We report on the first observation of mesospheric cloud (MC) at the altitude range of 50-65 km with lidars at Yanqing (40.5°N, 116°E) and Pingquan (41°N, 118.7°E) on 30 October 2018. The MC occurred at the 51-56 km altitude range during the hours of dawn. It had an obvious double-layer structure, but the cloud layer was sparse. The MC was re-observed at the 56-62 km altitude range in the twilight, and the double-layer structure was still obvious. However, the cloud layer became thicker with a maximum volume backscatter coefficient (BSC) 3.1×10−10m−1sr−1. Atmospheric temperature structure was derived according to the lidar observations, and it was found that, several hours before the MC occurrence, a temperature anomaly with coldest temperature ~185 K was propagating downward at the altitudes of 50-65 km. This MC layer was simultaneously observed with lidar at Pingquan in the twilight. It could be a regional MC event and possibly formed locally by a transient cooling due to small-scale disturbances in the mesosphere.

The Raman LIDAR for the pre-production phase of Cherenkov Telescope Array

The ARCADE Raman lidar has been tested and validated at L'Aquila before the deployment at CTA (Cherenkov Telescope Array) North site. Some modifications have been done on the original ARCADE system to improve its performances, and an extensive programme of measurements has been performed. The Raman lidar (RL) technique is discussed with specific care to the technical constrains of RL systems, and the signal analysis, i.e., the estimation of aerosol optical depth, volume backscatter coefficient, and water vapour profiles and their significance (errors and resolution). Some final comments and conclusions are outlined.

Advances in atmospheric temperature profile measurements using high spectral resolution lidar

This paper reports the atmospheric temperature profile measurements using a University of Wisconsin-Madison High Spectral Resolution Lidar (HSRL) and describes improvements in the instrument performance. HSRL discriminates between Mie and Rayleigh backscattering [1]. Thermal motion of molecules broadens the spectrum of the transmitted laser light due to Doppler effect. The HSRL exploits this property to allow the absolute calibration of the lidar and measurements of the aerosol volume backscatter coefficient. Two iodine absorption filters with different line widths are used to resolve temperature sensitive changes in Rayleigh backscattering for atmospheric temperature profile measurements.

Behaviours of Atlantic herring and mackerel in a purse-seine net, observed using multibeam sonar

To ensure efficient and sustainable purse-seine fisheries, the catch process must be monitored to better understand the reactions of fish to the gear. In this study, we monitored the behaviours of herring (Clupea harengus) and mackerel (Scomber scombrus) schools during purse-seine capture using a multibeam imaging sonar (Simrad MS70, 75–112 kHz) mounted on a research vessel. The fish behaviours differed between species and purse-seine sets. For both species, the acoustic volume backscattering coefficient increased as 0–80% of the seine was hauled aboard, indicating a corresponding increase in fish spatial density. This increase was significantly greater for herring than mackerel. As 0–40% of the seine was hauled aboard the fishing vessel, schools changed their spatial distribution and volume independent of seine hauling, while for some schools, depth and height decreased. The acoustic volume backscattering strength was up to 25 dB higher in the centre of the school than in the edges. The average lateral target strength was estimated for individual fish in the captured herring schools, and the effect of incident angle on the backscattering strength is considered.

Investigating acoustic diversity of fish aggregations in coral reef ecosystems from multifrequency fishery sonar surveys

Remote species classification using fisheries acoustic techniques in coral reef ecosystems remains one of the greatest hurdles in developing informative metrics and indicators required for ecosystem management. We reviewed long-term marine ecosystem acoustic surveys that have been carried out in the US Caribbean covering various coral reef habitat types and evaluated metrics that may be helpful in classifying multifrequency acoustic signatures of fish aggregations to taxonomic groups. We found that the energetic properties across frequencies, in particular the mean and the maximum volume backscattering coefficient, provided the majority of the discriminating power in separating schools and aggregations into distinct groups. To a lesser extent, school shape and geometry helped isolate a distinctive group of reef fishes based on shoaling behaviour. Schools and aggregations were clustered into five distinct groups. The use of underwater video surveys from a Remote Operating Vehicle (ROV) conducted in the proximity of the acoustic observations allowed us to associate the clusters with broad categories of species groups such as large predators, including fishery important species to small forage fishes. The remote classification methods described here are an important step toward improving marine ecosystem acoustics for the study and management of coral reef fish communities.