Estimating population density from indirect sign: track counts and the Formozov–Malyshev–Pereleshin formula

For many purposes it is often desirable to estimate animal population densities over large areas. Where total counts are not possible and sightings are relatively rare, a range of methods exists to estimate densities from indirect sign. Such methods are frequently unreliable and usually require independent calibration or confirmation. We present an analytical method for estimating population density from track counts. The method, widely known in the Russian Federation but not in the English language scientific literature, requires counts of tracks of known age, together with estimates of animal daily travel distances. We use simulations to verify the theoretical basis of the approach and to indicate potential precision that may be achieved. We illustrate application of the approach using a large data set on ungulate track counts in the Russian Far East. We suggest that under most circumstances, nonparametric bootstrapping will be the most appropriate method for deriving estimates of confidence intervals about density estimates. As with other approaches to estimating density from indirect sign, the method that we discuss is vulnerable to violations of an array of underlying assumptions. However, it is easily applied and could represent an important method by which the relationship between indices of abundance and absolute density can be understood.     

Toward reliable population density estimates of partially marked populations using spatially explicit mark–resight methods

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Evaluating Methods for Counting Cryptic Carnivores

ABSTRACT Numerous techniques have been proposed to estimate carnivore abundance and density, but few have been validated against populations of known size. We used a density estimate established by intensive monitoring of a population of radiotagged leopards (Panthera pardus) with a detection probability of 1.0 to evaluate efficacy of track counts and camera-trap surveys as population estimators. We calculated densities from track counts using 2 methods and compared performance of 10 methods for calculating the effectively sampled area for camera-trapping data. Compared to our reference density (7.33 ± 0.44 leopards/100 km²), camera-trapping generally produced more accurate but less precise estimates than did track counts. The most accurate result (6.97 ± 1.88 leopards/100 km²) came from camera-trap data with a sampled area buffered by a boundary strip representing the mean maximum distance moved by leopards outside the survey area (MMDMOSA) established by telemetry. However, contrary to recent suggestions, the traditional method of using half the mean maximum distance moved from photographic recaptures did not result in gross overestimates of population density (6.56 ± 1.92 leopards/100 km²) but rather displayed the next best performance after MMDMOSA. The only track-count method comparable to reference density employed a capture-recapture framework applied to data when individuals were identified from their tracks (6.45 ± 1.43 leopards/100 km²) but the underlying assumptions of this technique limit more widespread application. Our results demonstrate that if applied correctly, camera-trap surveys represent the best balance of rigor and cost-effectiveness for estimating abundance and density of cryptic carnivore species that can be identified individually.     

Nest and breeding population abundance of Least Terns: assessing bias and variation in survey timing and methods

Methods commonly used to estimate the number of nests and size of the breeding population at colonies of Least Terns (Sternula antillarum) and other waterbirds include walk‐through counts of nests (ground‐nest counts) and counts of incubating adults from the colony perimeter (incubating‐adult counts). The bias and variance of different methods and the comparability of repeated surveys versus once‐annual censuses are poorly understood. Our objectives were to assess (1) the potential bias and variation of the more rapid incubating‐adult counts compared to the time‐intensive, and presumably more accurate, ground‐nest counts, and (2) how accurately a once‐annual census captured peak nesting abundance. We studied nine Least Tern colonies at Cape Lookout National Seashore (CALO), North Carolina, from April to August 2010–2012. We analyzed observer and survey method agreement with concordance correlation coefficients (ρ_c). We deployed time‐lapse cameras at 156 nests and used repeated‐measures logistic regression to determine if the proportion of time spent incubating varied with colony, time of day, or time of season. We found substantial agreement in abundance estimates of Least Tern nests and incubating adults between observers and survey methods, and among different times of day and seasons (all comparisons ρ_c > 0.97). Least Terns incubated eggs 94% of the time on average during daylight hours, irrespective of colony, nesting stage, or month. Although the nesting peak at CALO occurred during the recommended census period for Least Terns, abundance estimates for surveys conducted at different times during that period varied by as much as 39%. We recommend conducting incubating‐adult counts to estimate nest and breeding population abundance of Least Terns or other waterbirds when vegetation or dunes do not obstruct views of nesting colonies. In addition, given the variation in abundance estimates for surveys conducted at different times during the recommended survey period, incubating‐adult counts should be performed at least twice during the census period, with the maximum count reported as peak nest abundance.     

COUNTING STELLER SEA LION PUPS IN ALASKA: AN EVALUATION OF MEDIUMFORMAT, COLOR AERIAL PHOTOGRAPHY

Estimates of Steller sea lion ( Eumetopias jubatus ) pup production are valuable for estimating population trend and size. Currently in Alaska, pups are counted by visiting rookeries, driving older animals into the water, then walking through the rookeries and counting the pups, a highly disruptive procedure. At smaller rookeries, with good vantage points, pups are occasionally counted from the periphery of rookeries without disturbing the sea lions. We evaluated counts made from medium-format, color, aerial photographs as an alternative to drive counts and peripheral counts. Neither the peripheral counts nor the aerial photographic counts disturbed animals on the rokeries. There were strong 1:1 linear relationships between photographic counts and drive counts ( r ²= 0.966, P < 0.001) and between photographic counts and peripheral counts ( r ²= 0.999, P < 0.001). Precision was similar for all three methods of counting. We suggest that medium-format, color, aerial photographs is appropriate for routine surveys of Steller sea lion pups in Alaska because it is not disruptive to the hauled-out sea lions and provides comparable estimates with similar precision to drive and peripheral counts. Large areas canbe rapidly surveyed during periods of good weather with a minimum of manpower.     

Distance models as a tool for modelling detection probability and density of native bumblebees

Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombus spp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp. and other pollinators.     

Census and distribution of large carnivores in the Tsavo national parks,a critical east African wildlife corridor

Kenya's Tsavo National Parks are a critical conservation area and the only wilderness corridor through densely populated human-dominated landscapes stretching from the East African coast to Lake Victoria, separating extensive undeveloped grasslands south of the equator from the undeveloped semiarid bushlands to the north. At nearly 21,000 km², Tsavo is one of four lion strongholds in East Africa and part of Africa's most important populations of all other large African carnivores. To provide baseline data on the status of large carnivores, a track survey was undertaken in 2013. Lions and both hyaena species were widely distributed across both parks, while cheetahs and wild dogs were more patchily distributed. Spotted hyaenas were the most abundant, with an estimated population of 3,903 ± 514 (95% CI), followed by lion (706 ± 201), striped hyaena (679 ± 144), leopard (452 ± 98), cheetah (154 ± 74) and wild dog (111 ± 92). Tsavo's carnivores suffer from bushmeat poaching, illegal grazing and retaliatory killing, and increasing human numbers on its periphery. Given Tsavo's importance as a stronghold for lions and an ecological corridor, increased investment in effective protection is strongly recommended. Evaluating trends will require complementary techniques in light of intensive monitoring requirements.     

An integrated modeling approach to estimating Gunnison sage‐grouse population dynamics: combining index and demographic data

Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large‐scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short‐term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage‐grouse (Centrocercus minimus). The long‐term population index data available for Gunnison sage‐grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage‐grouse to be variable and slightly declining over the past 16 years.     

Statistical power of replicated helicopter surveys in southern African conservation areas

Understanding the ecology of large ungulates in southern Africa requires accurate and precise measures of population size. Recovery or exploitation of ungulates in reserves is currently instigated when population size changes exceed 15% per annum, but monitoring is usually undertaken with single counts from helicopters, for which precision and the power to detect change are untested. In essence, power being the strength of a monitoring result in showing change over time. Retrospective power analysis is a useful technique to investigate the variability of single‐count aerial surveys. Using replicated helicopter‐based counts of southern African ungulates and post hoc analysis, we investigated the power of currently used single‐count surveys across five common ungulate species and 11 wildlife reserves. We expected high variability in count data and set α = 0.1 and 0.2 (α being the type I error rate), and asked two questions: ‘How much does power vary in replicated aerial counts of southern African wildlife across reserves and species?’ and ‘Can current single‐count aerial surveys detect population changes in response to management actions or are the statistical errors intractable?’ Single counts were mostly unreliable; only one of 42 had sufficient power to detect meaningful changes in population size or their trends at α = 0.1, and only three had sufficient power at α = 0.2. Power varied widely according to species (e.g. warthog, median power at α = 0.1; 0.12–0.37: blue wildebeest, median power at α = 0.1; 0.23–0.74), and, within species, between replicates and reserves. Our retrospective calculations demonstrated insensitivity and ineffectiveness in most currently applied single counts from helicopters. Consequently, it is impossible to interpret the effects of ungulate conservation actions on many southern African reserves. Retrospective power analyses enables determination of which previous aerial surveys were useful for population assessment and adaptive management, and which should be discarded. We recommend that prospective power analyses are undertaken to determine future helicopter survey sample size and replication requirements, especially in small reserves.     

Evaluation of three methods to estimate density and detectability from roadside point counts

Roadside point counts are often used to estimate trends of bird populations. The use of aural counts of birds without adjustment for detection probability, however, can lead to incorrect population trend estimates. We compared precision of estimates of density and detectability of whistling northern bobwhites (Colinus virginianus) using distance sampling, independent double-observer, and removal methods from roadside surveys. Two observers independently recorded each whistling bird heard, distance from the observer, and time of first detection at 362 call-count stops in Ohio. We examined models that included covariates for year and observer effects for each method and distance from observer effects for the double-observer and removal methods using Akaike's Information Criterion (AIC). The best model of detectability from distance sampling included observer and year effects. The best models from the removal and double-observer techniques included observer and distance effects. All 3 methods provided precise estimates of detection probability (CV = 2.4–4.4%) with a range of detectability of 0.44–0.95 for a 6-min survey. Density estimates from double-observer surveys had the lowest coefficient of variation (2005 = 3.2%, 2006 = 1.7%), but the removal method also provided precise estimates of density (2005 CV = 3.4%, 2006 CV = 4.8%), and density estimates from distance sampling were less precise (2005 CV = 9.6%, 2006 CV = 7.9%). Assumptions of distance sampling were violated in our study because probability of detecting bobwhites near the observer was <1 or the roadside survey points were not randomly distributed with respect to the birds. Distances also were not consistently recorded by individual members of observer pairs. Although double-observer surveys provided more precise estimates, we recommend using the removal method to estimate detectability and abundance of bobwhites. The removal method provided precise estimates of density and detection probability and requires half the personnel time as double-observer surveys. Furthermore, the likelihood of meeting model assumptions is higher for the removal survey than with independent double-observers. © 2011 The Wildlife Society.     

Scent Lure Effect on Camera-Trap Based Leopard Density Estimates

Density estimates for large carnivores derived from camera surveys often have wide confidence intervals due to low detection rates. Such estimates are of limited value to authorities, which require precise population estimates to inform conservation strategies. Using lures can potentially increase detection, improving the precision of estimates. However, by altering the spatio-temporal patterning of individuals across the camera array, lures may violate closure, a fundamental assumption of capture-recapture. Here, we test the effect of scent lures on the precision and veracity of density estimates derived from camera-trap surveys of a protected African leopard population. We undertook two surveys (a ‘control’ and ‘treatment’ survey) on Phinda Game Reserve, South Africa. Survey design remained consistent except a scent lure was applied at camera-trap stations during the treatment survey. Lures did not affect the maximum movement distances (p = 0.96) or temporal activity of female (p = 0.12) or male leopards (p = 0.79), and the assumption of geographic closure was met for both surveys (p >0.05). The numbers of photographic captures were also similar for control and treatment surveys (p = 0.90). Accordingly, density estimates were comparable between surveys (although estimates derived using non-spatial methods (7.28–9.28 leopards/100km²) were considerably higher than estimates from spatially-explicit methods (3.40–3.65 leopards/100km²). The precision of estimates from the control and treatment surveys, were also comparable and this applied to both non-spatial and spatial methods of estimation. Our findings suggest that at least in the context of leopard research in productive habitats, the use of lures is not warranted.     

An improved survey method for monitoring population trends of Golden‐winged Warblers and other patchily distributed birds

Conventional surveys designed to monitor common and widespread species may fail to adequately track population changes of rare or patchily distributed species that are often of high conservation concern. We evaluated the performance of a new monitoring approach that employs both a spatially balanced sampling design and a targeted survey protocol designed to estimate population trends of one such patchily distributed species, the Golden‐winged Warbler (Vermivora chrysoptera), in the Appalachian Mountains Bird Conservation Region (BCR 28), USA. Our spatially balanced survey consisted of 105 sample quads (one‐quarter Delorme Atlas pages) across the current range of Golden‐winged Warblers within BCR 28, each with five sample points located in early successional habitat. From 2009 to 2013, collaborators visited each sample point once per year during the peak breeding season and conducted a 17‐min survey consisting of passive observation and playback of conspecific songs and mobbing vocalizations. We used multi‐season, single‐species occupancy models to estimate probability of quad occupancy, detection probability, and occupancy dynamics for Golden‐winged Warblers and closely related Blue‐winged Warblers (Vermivora cyanoptera). Our survey protocol resulted in high estimates of detection probability for Golden‐winged (92%) and Blue‐winged (79%) warblers, with 47% and 56% of quads estimated to be initially occupied, respectively. Derived population trend estimates (λ) indicated an average decline in population of 6% for Golden‐winged Warblers and 7% for Blue‐winged Warblers, resulting in estimated 21% and 22% declines, respectively, in quad occupancy after 5 yr. Our results demonstrate that coupling a spatially balanced survey design in appropriate habitat with a playback protocol to increase detection rates is a viable strategy for tracking populations of Golden‐winged Warblers in the Appalachian Mountains BCR. Similar survey methods should be considered for other rare, declining, or patchily distributed bird species that require targeted monitoring.     

Laboratory sources of error for algal community attributes during sample preparation and counting

Applied algal studies typically require enumeration of preserved cells. As applications of algal assessments proliferate, understanding sources of variability inherent in the methods by which abundance and species composition data are obtained becomes even more important for precision of measurements. We performed replicate counts of diatoms on permanently fixed coverglasses and all algae in Palmer–Maloney chambers to assess precision and accuracy of measurements derived from common counting methods. We counted diatoms and all algae with transects and random fields. Variability estimates (precision) of diatom density, species diversity, and species composition on permanent coverglasses were low between replicate subsamples and between replicate transects. However, average density estimates of diatoms settled on coverglasses determined with transect methods were 42–52% greater than density estimates made with random fields. This bias was due to a predictable, nonrandom distribution of diatoms on the coverglass with few diatoms near edges. Despite bias in density when counting diatoms along coverglass transects, no bias was observed in estimates of species composition. Estimates of density and taxa richness of all-algae in Palmer–Maloney chambers also had low variability among multiple transects and high similarity in species composition between transects. In addition, counting method in Palmer–Maloney chambers did not affect estimates of algal cell density, taxa richness, and species composition, which suggested that counting units were distributed randomly in the chambers. Thus, most sources of variability in sample preparation and analysis are small; however, transect counts should not be used to estimate cell density, and sufficient numbers of random fields must be counted to account for edge effects on cell distribution with material settled on permanently fixed coverglasses.     

High‐resolution photo‐mosaic time‐series imagery for monitoring human use of an artificial reef

Successful marine management relies on understanding patterns of human use. However, obtaining data can be difficult and expensive given the widespread and variable nature of activities conducted. Remote camera systems are increasingly used to overcome cost limitations of conventional labour‐intensive methods. Still, most systems face trade‐offs between the spatial extent and resolution over which data are obtained, limiting their application. We trialed a novel methodology, CSIRO Ruggedized Autonomous Gigapixel System (CRAGS), for time series of high‐resolution photo‐mosaic (HRPM) imagery to estimate fine‐scale metrics of human activity at an artificial reef located 1.3 km from shore. We compared estimates obtained using the novel system to those produced with a web camera that concurrently monitored the site. We evaluated the effect of day type (weekday/weekend) and time of day on each of the systems and compared to estimates obtained from binocular observations. In general, both systems delivered similar estimates for the number of boats observed and to those obtained by binocular counts; these results were also unaffected by the type of day (weekend vs. weekday). CRAGS was able to determine additional information about the user type and party size that was not possible with the lower resolution webcam system. However, there was an effect of time of day as CRAGS suffered from poor image quality in early morning conditions as a result of fixed camera settings. Our field study provides proof of concept of use of this new cost‐effective monitoring tool for the remote collection of high‐resolution large‐extent data on patterns of human use at high temporal frequency.     

Demographic consequences of habitat loss and crowding in large carnivores: A natural experiment

Habitat loss is one of largest threats to the persistence of large carnivore populations. However, because most large carnivores are long‐lived, cryptic and wide‐ranging, few studies examine the demographic consequences of habitat loss, and the resultant crowding that ensues, on these species. We used long‐term data to examine the demographic responses of an African lion (Panthera leo) population to flooding‐induced habitat loss in a seasonal wetland, the Okavango Delta, during a transition from low to high annual flooding patterns. We found that intraspecific competition reduced cub survival and that this effect was exacerbated by habitat loss and consequent crowding. The proportion of cubs recorded in the population also declined as crowding increased, and both the survival of cubs and proportion of cubs recorded declined as prey abundance decreased. Apparent sub‐adult survival declined with increasing pride size, but this likely reflects emigration rather than mortality. Adult survival remained relatively constant throughout the study period, a population response which is important in buffering populations against short‐term fluctuations in ecological conditions. As many large carnivore populations face future habitat loss, it is important that we understand the demographic consequences of habitat loss in order to better mitigate its effects in the future.     

Using the Formozov–Malyshev–Pereleshin formula to convert mammal spoor counts into density estimates for long‐term community‐level monitoring

Finding an appropriate method to monitor a wide range of mammal species simultaneously is notoriously difficult, as each method has its limitations. Here, we examine a formula, known as the Formozov–Malyshev–Pereleshin (FMP), which uses mean daily travel distances (day ranges) to convert spoor counts into density estimates. Availability of accurate estimates of day ranges is a limitation of the FMP formula. Here, we used allometry to estimate day ranges for those species that lacked empirical movement data and general additive models (GAM) to assess trends in density estimates. With this approach, we derived density estimates for 10 mammal species, regardless of whether they were abundant, or rare and elusive (e.g. carnivores). General additive models suggest that six species are stable or increasing, and four declining, although all nonsignificantly. Use of allometric estimates in lieu of empirical estimates led to falsely increased precision in density estimates, highlighting the need to fill the knowledge gap in movement ecology for certain species. Simulations were used to examine error introduced into trend estimates by this bias. We conclude that the FMP formula, when properly employed, can be an efficient method for simultaneous monitoring of multispecies in different functional groups.     

Methodology matters when estimating deer abundance: a global systematic review and recommendations for improvements

Deer (Cervidae) are key components of many ecosystems and estimating deer abundance or density is important to understanding these roles. Many field methods have been used to estimate deer abundance and density, but the factors determining where, when, and why a method was used, and its usefulness, have not been investigated. We systematically reviewed journal articles published during 2004–2018 to evaluate spatio-temporal trends in study objectives, methodologies, and deer abundance and density estimates, and determine how they varied with biophysical and anthropogenic attributes. We also reviewed the precision and bias of deer abundance estimation methods. We found 3,870 deer abundance and density estimates. Most estimates (58%) were for white-tailed deer (Odocoileus virginianus), red deer (Cervus elaphus), and roe deer (Capreolus capreolus). The 6 key methods used to estimate abundance and density were pedestrian sign (track or fecal) counts, pedestrian direct counts, vehicular direct counts, aerial direct counts, motion-sensitive cameras, and harvest data. There were regional differences in the use of these methods, but a general pattern was a temporal shift from using harvest data, pedestrian direct counts, and aerial direct counts to using pedestrian sign counts and motion-sensitive cameras. Only 32% of estimates were accompanied by a measure of precision. The most precise estimates were from vehicular spotlight counts and from capture–recapture analysis of images from motion-sensitive cameras. For aerial direct counts, capture–recapture methods provided the most precise estimates. Bias was robustly assessed in only 16 studies. Most abundance estimates were negatively biased, but capture–recapture methods were the least biased. The usefulness of deer abundance and density estimates would be substantially improved by 1) reporting key methodological details, 2) robustly assessing bias, 3) reporting the precision of estimates, 4) using methods that increase and estimate detection probability, and 5) staying up to date on new methods. The automation of image analysis using machine learning should increase the accuracy and precision of abundance estimates from direct aerial counts (visible and thermal infrared, including from unmanned aerial vehicles [drones]) and motion-sensitive cameras, and substantially reduce the time and cost burdens of manual image analysis.     

Use of autonomous audio recordings for the rapid inventory of birds in the white‐sand forests of the Peruvian Amazon

White‐sand forests are patchily distributed ecosystems covering just 5% of Amazonia that host many specialist species of birds not found elsewhere, and these forests are threatened due to their small size and human exploitation of sand for construction projects. As a result, many species of birds that are white‐sand specialists are at risk of extinction, and immediate conservation action is paramount for their survival. Our objective was to evaluate current survey methods and determine the relative effect of the size of patches of these forests on the presence or absence of white‐sand specialists. Using point counts and autonomous recorders, we surveyed avian assemblages occupying patches of white‐sand forest in the Peruvian Amazon in April 2018. Overall, we detected 126 species, including 21 white‐sand forest specialists. We detected significantly more species of birds per survey point with autonomous recorders than point counts. We also found a negative relationship between avian species richness and distance from the edge of patches of white‐sand forest, but a significant, positive relationship when only counting white‐sand specialists. Although we detected more species with autonomous recorders, point counts were more effective for detecting canopy‐dwelling passerines. Therefore, we recommend that investigators conducting surveys for rare and patchily distributed species in the tropics use a mixed‐method approach that incorporates both autonomous recorders and visual observation. Finally, our results suggest that conserving large, continuous patches of white‐sand forest may increase the likelihood of survival of species of birds that are white‐sand specialists.     

Comparative analysis of visual census techniques for highly mobile,reef-associated piscivores (Carangidae)

Synopsis Visual census techniques applicable to coral reef-associated fishes are reviewed and the results of field tests using six (three transect-based and three point-based) to estimate the density of carangids at Carter Reef, Great Barrier Reef, are presented. Data are analyzed with respect to the effects of observers on fishes seen, observer biasses, precision of the estimates and, as far as possible, accuracy of the estimates. Transects generate estimates of population density and structure different from those of point-based estimates. Various point-based census methods, however, generate density estimates consistent with one another and are generally more precise than transect-based methods. The results of the field study obviously cannot be generalized to other quite different types of reef fishes. The problems we encountered and a review of the techniques used to census reef fishes visually in the past, however, suggest that: (1) interval counts, such as Rapid Visual Census techniques, are likely to be inaccurate and difficult to compare; (2) for species with high probabilities of detection, instantaneous area counts appear to be the most effective way to estimate densities, whereas cryptic species are best censused using instantaneous variable distance point counts, and (3) strip transects may often be less efficient than line transects, due to inconstant levels of subject detectability.