Counts of coral reef fishes by an experienced observer are not biased by the number of target species

Fishes are commercially, recreationally and functionally important inhabitants of coral reefs. Accordingly, accurate assessments of fish abundance and diversity are necessary for effective reef management. While some reef fish monitoring programmes target all fishes, many survey a subset of common and visually obvious species. Changing to counts of all species, while desirable, risks new and unwelcome biases from altered observer swimming speeds and search patterns. Here we test whether substantially increasing the number of target species in an established fish monitoring programme biases counts of the original subset, so precluding ongoing comparisons with historical data. A subset of 141 fish species have been visually surveyed along 50 × 5 m transects over 27 years throughout Australia's Great Barrier Reef. We experimentally compared counts of the subset from standard subset-only surveys and from surveys of all species (excluding small site-attached fishes that are surveyed separately) at three diverse reefs. Subset species richness and abundance, in total and of major families, and assemblage structure did not differ due to survey method. The high-level experience of the one observer appeared to overcome new biases from counting more species and the extra 2 min/transect was not logistically excessive. Surveys of all fishes recorded almost 80% more species than subset-only surveys and >130% higher total abundance on average from >150% more genera that included abundant and functionally important taxa. Overall, fish counts by an experienced observer were not biased by the number of species surveyed and counts of all species markedly improved assessments of reef fish diversity and function.     

A multispecies dependent double‐observer model: A new method for estimating multispecies abundance

Conservation of biological communities requires accurate estimates of abundance for multiple species. Recent advances in estimating abundance of multiple species, such as Bayesian multispecies N‐mixture models, account for multiple sources of variation, including detection error. However, false‐positive errors (misidentification or double counts), which are prevalent in multispecies data sets, remain largely unaddressed. The dependent‐double observer (DDO) method is an emerging method that both accounts for detection error and is suggested to reduce the occurrence of false positives because it relies on two observers working collaboratively to identify individuals. To date, the DDO method has not been combined with advantages of multispecies N‐mixture models. Here, we derive an extension of a multispecies N‐mixture model using the DDO survey method to create a multispecies dependent double‐observer abundance model (MDAM). The MDAM uses a hierarchical framework to account for biological and observational processes in a statistically consistent framework while using the accurate observation data from the DDO survey method. We demonstrate that the MDAM accurately estimates abundance of multiple species with simulated and real multispecies data sets. Simulations showed that the model provides both precise and accurate abundance estimates, with average credible interval coverage across 100 repeated simulations of 94.5% for abundance estimates and 92.5% for detection estimates. In addition, 92.2% of abundance estimates had a mean absolute percent error between 0% and 20%, with a mean of 7.7%. We present the MDAM as an important step forward in expanding the applicability of the DDO method to a multispecies setting. Previous implementation of the DDO method suggests the MDAM can be applied to a broad array of biological communities. We suggest that researchers interested in assessing biological communities consider the MDAM as a tool for deriving accurate, multispecies abundance estimates.     

It counts who counts: an experimental evaluation of the importance of observer effects on spotlight count estimates

Spotlight surveys conducted by volunteers is a promising method to assess the abundance of nocturnally active mammals, but estimates are subject to bias if different observer groups differ in their ability to detect animals in the dark. We quantified the variation amongst volunteer spotlight observers with respect to their ability to detect and estimate distance to realistic animal silhouettes at different distances. Detection probabilities were higher for observers experienced in spotlighting mammals than for inexperienced observers, higher for observers with a hunting background compared with non-hunters and decreased as function of age but were independent of sex or educational background. If observer-specific detection probabilities were applied to real counting routes, point count estimates from inexperienced observers without a hunting background would only be 43 % (95 % CI, 39–48) of what inexperienced hunters with a hunting background would obtain and 29 % (25–33) of what experienced spotlight observers would detect. Mean estimated distances to objects did not deviate from true distances (no bias) but were highly imprecise. Female non-hunters estimated distances less precisely than other observers and precision increased with age. The study shows that observer effects may influence abundance estimates and underlines the importance of testing and accounting for observer effects when designing citizen science-based population survey programmes.     

Comparison of removal‐based methods for estimating abundance of five species of prairie songbirds

Estimating species abundance is important for land managers, especially for monitoring conservation efforts. The two main survey methods for estimating avian abundance are point counts and transects. Previous comparisons of these two methods have either been limited to a single species or have not included detection probability. During the 2012 breeding season, we compared and assessed the efficiency (precision for amount of effort) of point count time of detection (PCTD) and dependent double‐observer transect (TRMO) methods based on detection probabilities and abundance estimates of five species of songbirds that use a range of habitats in a prairie system in Montana dominated by sagebrush and grassland vegetation. Our focal species included Vesper Sparrows (Pooecetes gramineus), a generalist species found in both shrub and grassland habitat, shrub‐obligate Brewer's Sparrows (Spizella breweri), and McCown's Longspurs (Rhynchophanes mccownii), Horned Larks (Eremophila alpestris), and Western Meadowlarks (Sturnella neglecta), three species of grassland obligates that prefer different grass heights. Detection probabilities were significantly higher for TRMO surveys, with less variation for all five species and differences most pronounced for Brewer's Sparrows and Horned Larks. PCTD surveys required less field effort (~8–20 fewer people minutes per plot) than TRMO surveys because the TRMO surveys required two people. However, time spent on TRMO surveys provided between 0.38 and 87 times more precision per people minute than PCTD surveys. Our results suggest that TRMO surveys provide a more efficient (measured as time spent per unit of standard error) field‐based technique in sagebrush prairie systems for the species we investigated, resulting in more precise detection and abundance estimates.     

Determining Methods of Underwater Visual Census for Estimating the Abundance of Coral Reef Fishes

We aimed to determine optimal methods of underwater visual census (UVC) for estimating the abundance of coral reef fishes exploited by fisheries in the tropical Pacific. Two main methods were tested using SCUBA: strip transect and stationary point counts. We assessed their relative accuracy, precision, power and efficiency (cost), and compared different census area dimensions, observer swimming speeds, and number of replicates. Twenty-five comparisons of the two UVC methods were conducted for 73 species from five families of coral reef fishes, on reefs in Australia and Fiji. Species were grouped within families based on their mobility. Few significant differences were found, either among or between strip transects and stationary point counts. The data were characterised by high variability, low precision and low power. A trend for greater accuracy in density estimates of small sedentary species with smaller census area was apparent, which probably reflects searching efficiency. Only one species group, the sedentary Acanthuridae showed differences between transects and point counts. Higher, hence presumably more accurate, density estimates were obtained with 50m×5m transects. Notably, point counts could be deployed in 70% of the time of transects. A bootstrapping procedure demonstrated a consistent improvement in precision of density estimates with increasing number of replicates, but no appreciable change in precision was found beyond 10 to 15 replicates, in all species groups and for both transects and point counts. Consequently, and because of the high variability inherent in fish density estimates, we recommend that at least 10 replicates be used to quantify the species considered here. The power calculations showed that only large differences in density will be detected with the replication levels typical of UVC surveys. Power was greatest for the roving serranids, with a decrease in density of about 50% detectable for this species group. We discuss the importance of carefully defining the behavioural attributes of species prior to selecting a UVC method. A method of temporal stratification in a count is described for censusing a range of species of varying mobilities. We suggest that fish mobility and search efficiency are key factors in optimising UVC methods.     

Abundance estimates to inform butterfly management: double-observer versus distance sampling

Abundance estimates are used to establish baselines, set recovery targets, and assess management actions, all of which are essential aspects of evidence-based natural resource management. For many rare butterflies, these estimates do not exist, and conservation decisions rely instead on expert opinion. Using Bartram’s scrub-hairstreak (Strymon acis bartrami, US Endangered) as a case study, we present a novel comparison of two methods that permit the incorporation of detection probabilities into abundance estimates, distance sampling and double-observer surveys. Additionally we provide a framework for establishing a systematic sampling scheme for monitoring very rare butterflies. We surveyed butterflies monthly in 2013, increasing intensity to weekly when butterflies were detected. We conducted 19 complete, island-wide surveys on Big Pine Key in the Florida Keys, detecting a total of 59 Bartram’s scrub-hairstreaks across all surveys. Peak daily abundances were similar as estimated with distance sampling, 156 butterflies (95 % CI 65–247), and double-observer, 169 butterflies (95 % CI 65–269). Selecting a method for estimating abundance of rare species involves evaluating trade-offs between methods. Distance sampling requires at least 40 detections, but only one observer, while double-observer requires only 10 detections, but two observers. Double-observer abundance estimates agreed with distance sampling estimates, which suggests that double-observer is a reasonable alternative method to use for estimating detection probability and abundance for rare species that cannot be surveyed with other, more commonly used methods.     

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.     

Pooling robustness in distance sampling: Avoiding bias when there is unmodelled heterogeneity

The pooling robustness property of distance sampling results in unbiased abundance estimation even when sources of variation in detection probability are not modeled. However, this property cannot be relied upon to produce unbiased subpopulation abundance estimates when using a single pooled detection function that ignores subpopulations. We investigate by simulation the effect of differences in subpopulation detectability upon bias in subpopulation abundance estimates. We contrast subpopulation abundance estimates using a pooled detection function with estimates derived using a detection function model employing a subpopulation covariate. Using point transect survey data from a multispecies songbird study, species-specific abundance estimates are compared using pooled detection functions with and without a small number of adjustment terms, and a detection function with species as a covariate. With simulation, we demonstrate the bias of subpopulation abundance estimates when a pooled detection function is employed. The magnitude of the bias is positively related to the magnitude of disparity between the subpopulation detection functions. However, the abundance estimate for the entire population remains unbiased except when there is extreme heterogeneity in detection functions. Inclusion of a detection function model with a subpopulation covariate essentially removes the bias of the subpopulation abundance estimates. The analysis of the songbird point count surveys shows some bias in species-specific abundance estimates when a pooled detection function is used. Pooling robustness is a unique property of distance sampling, producing unbiased abundance estimates at the level of the study area even in the presence of large differences in detectability between subpopulations. In situations where subpopulation abundance estimates are required for data-poor subpopulations and where the subpopulations can be identified, we recommend the use of subpopulation as a covariate to reduce bias induced in subpopulation abundance estimates.     

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.     

Aerial Surveys for Estimating Wild Turkey Abundance in the Texas Rolling Plains

Abstract: Aerial surveys have been used to estimate abundance of several wild bird species including wild turkeys (Meleagris gallopavo). We used inflatable turkey decoys at 3 study sites in the Texas Rolling Plains to simulate Rio Grande wild turkey (M. g. intermedia) flocks. We evaluated detectability of flocks and errors in counting flock size during fixed-wing (Cessna 172) aerial surveys using logistic and linear regression models. Flock detectability was primarily influenced by flock size and vegetative cover, and errors in counting flock size were primarily influenced by size of flocks. We conducted computer simulations to evaluate the accuracy and precision of fixed-wing aerial surveys and examined power to detect trends in population change. Our simulations suggested abundance estimates from fixed-wing aerial surveys may be underestimated by 10-15% (2.0-4.8% CV). Power analyses suggested that fixed-wing aerial surveys can provide sufficient power (>0.80) to detect a population change of 10-25% over a 4-5-year period. We concluded fixed-wing aerial surveys are feasible on ecoregion scales.     

Estimation and Correction of Visibility Bias in Aerial Surveys of Wintering Ducks

Abstract: Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1–100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36–42%, and associated standard errors increased 38–55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):808–813; 2008)     

Estimating Detection Probabilities of Waterfowl Broods From Ground-Based Surveys

ABSTRACT Brood:pair ratios could provide an economical method for assessing spatial or temporal variation in waterfowl productivity, but such estimators are severely biased by incomplete detection of broods. We conducted 3 sequential counts of 1,357 waterfowl broods in northeastern North Dakota, USA, and used closed-population mark-recapture models to estimate total brood abundance while controlling for variation in detection probabilities (p). Blue-winged teal (Anas discors) broods had the lowest average detection probability (p = 0.305), whereas diving-duck broods had the highest average detectability (p = 0.571). Detection was generally highest in morning or evening, but temporal patterns varied among species and there was no survey window that maximized detection probabilities for all species. Detection probabilities averaged 0.108 (SD = 0.056) higher for an experienced observer versus an inexperienced observer. Detection probabilities were 0.044 higher for roadside versus walk-up surveys and increased with increasing brood size, total brood abundance, survey date, wind speed, temperature, cloud cover, and amount of time spent surveying each wetland. Detection probabilities declined with increasing wetland size and amount of tall peripheral vegetation. Our mark-recapture results indicated that a traditional unreplicated brood survey would have missed 67.5% of estimated broods, summed over all species. Use of closed-population mark-recapture techniques provided an effective method for reducing this bias and identifying and quantifying factors that reduce detection probabilities of waterfowl broods. We recommend that future brood surveys incorporate 2 or 3 temporally segregated replicate counts to allow for formal estimation of detection probabilities.     

Aerial survey of waterbirds on wetlands as a measure of river and floodplain health

1. This study highlights the use of waterbird communities as potential measures of river and floodplain health at a landscape scale. 2. The abundance and diversity of a waterbird community (54 species) was measured over 15 trips with four aerial and three ground counts per trip on a 300-ha lake in arid Australia. 3. Aerial survey estimates of individual species were significantly less precise (SE/mean) than ground counts across two (11–100 and > 1000) out of four abundance classes of waterbirds: 0–10, 11–100, 101–1000 and > 1000. Standard error/mean as a percentage decreased with increasing abundance from about 60% for the lowest abundance class to 18% for the largest abundance class. 4. Aerial survey estimates were negatively biased for species in numbers of less than 10 and greater than 5000 but unbiased compared to ground counts for other abundance classes. Aerial surveys underestimated numbers of waterbirds by 50% when there were 40 000 waterbirds. Three ground counts found about seven more waterbird species than four aerial surveys. One ground count took about 150 times longer than two aerial surveys and cost 14 times more. 5. Regression models were derived, comparing aerial survey estimates to ground counts for 31 of 36 species for which there were sufficient data. Aerial survey estimates were unbiased for most of these species (67%), negatively biased for six species and positively biased for one species. Estimates were negatively biased in species that occurred in small numbers or that dived in response to the aircraft. 6. River system health encompasses the state of floodplain wetlands. Waterbirds on an entire wetland or floodplain may be estimated by aerial survey of waterbirds; this is a coarse but effective measure of waterbird abundance. Aerial survey is considerably less costly than ground survey and potentially provides a method for measuring river and floodplain health over long periods of time at the same scale as river management.     

ABUNDANCE OF SOUTHERN CALIFORNIA COASTAL BOTTLENOSE DOLPHINS ESTIMATED FROM TANDEM AERIAL SURVEYS

We describe a tandem aerial survey method for bottlenose dolphins ( Tursiops truncatus ) that uses two aircraft and independent observer teams to conduct consecutive surveys of the same coastal strip one hour apart. Alternatively, one aircraft with one observer team surveys the same coastal strip twice over several hours. Using mark-recapture analysis, we corrected survey counts for visibility bias resulting from missing dolphin groups at the surface and submerged groups. Dolphin groups were considered "recaptured" when we determined that both observer teams had detected the same group. This tandem method is highly useful for estimating abundance (and visibility bias) for species where population closure may be assumed between flights. We assumed population closure between flights and matched groups using geographic location, group size, and expected travel rates. We derive a new variance estimator of population size which incorporates group-size variability commonly encounteted in cetacean surveys. From six tandem surveys conducted from 1991 to 1994, we estimated the abundance of southern California coastal bottlenose dolphins to be between 78 (95% CI 60-102) and 271 (240-306) animals, with an average of 140 (128-154). Variability in abundance estimates is likely due to seasonal and interannual movement of animals along the California and Baja California coast. Abundance estimates from tandem surveys averaged 53% higher than dolphin counts obtained from individual survey flights, demonstrating the importance of correcting for visibility bias.     

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.     

Comparison and Assessment of Aerial and Ground Estimates of Waterbird Colonies

Abstract: Aerial surveys are often used to quantify sizes of waterbird colonies; however, these surveys would benefit from a better understanding of associated biases. We compared estimates of breeding pairs of waterbirds, in colonies across southern Louisiana, USA, made from the ground, fixed-wing aircraft, and a helicopter. We used a marked-subsample method for ground-counting colonies to obtain estimates of error and visibility bias. We made comparisons over 2 sampling periods: 1) surveys conducted on the same colonies using all 3 methods during 3–11 May 2005 and 2) an expanded fixed-wing and ground-survey comparison conducted over 4 periods (May and Jun, 2004–2005). Estimates from fixed-wing aircraft were approximately 65% higher than those from ground counts for overall estimated number of breeding pairs and for both dark and white-plumaged species. The coefficient of determination between estimates based on ground and fixed-wing aircraft was ≤0.40 for most species, and based on the assumption that estimates from the ground were closer to the true count, fixed-wing aerial surveys appeared to overestimate numbers of nesting birds of some species; this bias often increased with the size of the colony. Unlike estimates from fixed-wing aircraft, numbers of nesting pairs made from ground and helicopter surveys were very similar for all species we observed. Ground counts by one observer resulted in underestimated number of breeding pairs by 20% on average. The marked-subsample method provided an estimate of the number of missed nests as well as an estimate of precision. These estimates represent a major advantage of marked-subsample ground counts over aerial methods; however, ground counts are difficult in large or remote colonies. Helicopter surveys and ground counts provide less biased, more precise estimates of breeding pairs than do surveys made from fixed-wing aircraft. We recommend managers employ ground counts using double observers for surveying waterbird colonies when feasible. Fixed-wing aerial surveys may be suitable to determine colony activity and composition of common waterbird species. The most appropriate combination of survey approaches will be based on the need for precise and unbiased estimates, balanced with financial and logistical constraints. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):697–706; 2008)     

Blind Count Surveys of White-Tailed Deer and Population Estimates Using Bowden's Estimators

Abstract: Conducting surveys from blinds when supplemental feed (bait) has been provided has not been evaluated for estimating parameters of ungulate populations. We conducted blind count surveys of white-tailed deer (Odocoileus virginianus) in a 214-ha enclosure in central Texas, USA, in 2007 and 2008 to address 2 main objectives: 1) to evaluate a blind count survey protocol developed for use on small parcels of land, and 2) to use data collected from blind count surveys to conduct simulations to evaluate the reliability of abundance and sex ratio estimates obtained from Bowden's estimator. In each year population abundance (2007: 60; 2008: 48) and sex ratio (M:F, 2007: 0.58; 2008: 0.71) were known as were sighting frequencies of every animal. The enclosure had 5 blinds and we baited each blind with corn. We encountered many deer during surveys because there were only 2 deer in 2007 and 1 deer in 2008 that we did not view from blinds ≥1 time. To evaluate bias and precision of abundance and sex ratio estimates we conducted 10,000 bootstrap simulations. We evaluated both parameters in relation to the percentage of each population marked, number of surveys conducted from blinds, and whether surveys were conducted in the morning, evening, or both morning and evening. Also, we evaluated abundance in relation to whether we identified animals with unique marks to individual, and we evaluated sex ratio in relation to intersexual distribution of marks. Abundance estimates were less biased and more precise when we uniquely identified all marked animals and 40–70% of the population was marked. Sex ratio estimates were less biased when 40–70% of the population was marked and surveys were conducted in the morning and evening. Sex ratio estimates, however, were less precise than abundance estimates. Unbiased estimates of white-tailed deer population parameters can be obtained from blind count surveys conducted on small parcels of enclosed land and when animals are baited.     

Fish assemblages on artificial and natural reefs in the Flower Garden Banks National Marine Sanctuary, USA

 Visual censusing was used to characterize fish assemblages on artificial and natural reefs located within the boundaries of the Flower Garden Banks National Marine Sanctuary (FGBNMS) in the northwestern Gulf of Mexico. Emphasis was placed on determining spatial and temporal patterns in habitat utilization by fishes on an offshore artificial reef (Mobil Platform HI-A389A). Overall, 43 species were observed during diurnal surveys in the upper 24 m of the artificial reef. Midwater pelagic fishes (i.e., carangids and scombrids) accounted for over 50% of all taxa enumerated on the artificial reef; however, these taxa were transient members of the assemblage and were observed infrequently. Labrids, pomacentrids, and serranids were the dominant reef-dependent taxa. Distinct trends in vertical, diel, and seasonal abundances were observed for juvenile and adult fishes. Of the three designated depth zones (upper 1.5–9.0, middle 9.0–16.5; lower 16.5–24.0 m), abundance and species diversity were lowest in the upper zone. Nocturnal counts were characterized by a marked reduction or complete absence of most species, due in part to twilight cover-seeking and movement activities. Seasonal variation in community composition and species abundance (May versus September) was primarily due to recruitment of juveniles (0-age fishes) to the artificial reef in late summer. Increases in total fish abundance (all taxa combined) coincided with both increasing habitat rugosity and degree of fouling. Species richness on natural coral reefs in the FGBNMS was higher than on the artificial reef. Unlike the artificial reef, fish assemblages on the natural reefs were dominated by a single family (Pomacentridae) which accounted for over 50% of all individuals observed. Accepted: 1 August 1996     

Observer error in vegetation surveys: a review

Aims Vegetation sampling employing observers is prone to both inter-observer and intra-observer error. Three types of errors are common: (i) overlooking error (i.e. not observing species actually present), (ii) misidentification error (i.e. not correctly identifying species) and (iii) estimation error (i.e. not accurately estimating abundance). I conducted a literature review of 59 articles that provided quantitative estimates or statistical inferences regarding observer error in vegetation studies.Important findings Almost all studies (92%) that tested for a statistically significant effect of observer error found at least one significant comparison. In surveys of species composition, mean pseudoturnover (the percentage of species overlooked by one observer but not another) was 10–30%. Species misidentification rates were on the order of 5–10%. The mean coefficient of variation (CV) among observers in surveys of vegetation cover was often several hundred % for species with low cover, although CVs of 25–50% were more representative of species with mean covers of>50%. A variety of metrics and indices (including commonly used diversity indices) and multivariate data analysis techniques (including ordinations and classifications) were found to be sensitive to observer error. Sources of error commonly include both characteristics of the vegetation (e.g. small size of populations, rarity, morphology, phenology) and attributes of the observers (e.g. mental fatigue, personal biases, differences in experience, physical stress). The use of multiple observers, additional training including active feedback approaches, and continual evaluation and calibration among observers are recommended as strategies to reduce observer error in vegetation surveys.     

You are what you eat, whenever or wherever you eat it: an integrative analysis of fish food habits in Canadian and U.S.A. waters

The degree to which fish diet differs by season and area, particularly over broad scales, was examined for the first time in temperate, contiguous north-west Atlantic Ocean waters by comparing food habit data for 10 species of fishes collected concurrently during the spring and autumn surveys in the U.S.A. (Gulf of Maine proper and Georges Bank) and in the summer survey in Canada (western Scotian Shelf and Bay of Fundy). For most species, there was a general concurrence among the three seasons and four areas: summer diets had the same dominant prey items as spring and autumn diets. Although a suite of multivariate analyses did elucidate some differences in specific proportions of the diet for these species across seasons and areas, the main prey did not substantially change for most of these species. These results suggest that there are (1) minimal differences in diet across season for these species at these taxonomic resolutions, (2) there are minimal differences in diet geographically for these species and (3) differences across species, as expected, are important. Many fisheries ecosystem and multispecies models are dependent on food habit data, where resolving seasonal and spatial differences in diet remains an important consideration; however, the present work implies that amalgamated estimates of diet from seasonal surveys may be a reasonable approach when no finer seasonal resolution exists, as long as due diligence is exercised.