Correction for bias in visual transect censuses of coral reef fishes

Sale, Peter F.; Sharp, Bill

doi:10.1007/bf00304730

Cited by 129 publications

(101 citation statements)

References 8 publications

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“…This feature alone may imply that the Transect technique is to be preferred. Sale and Sharp (1983) demonstrated that transect-type visual surveys results are dependent on the width of the transect.…”

Section: Methods Comparisonmentioning

confidence: 99%

A Comparison of Three Methods for Visually Assessing Reef Fish Communities: Time and Area Compensated

Bortone

Kimmel

Bundrick

1989

negs

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Reef fish assemblage survey results using Transect, Point, and Random in situ visual assessment techniques were evaluated and compared on a coral reef biotope off the southwestern coast of Puerto Rico. Parameters compared were: number of species, number of individuals, and species diversity (H'). No significant effect attributable to the time-of-day when the surveys were conducted was noted to occur. Variability in observations between divers was not noted for any of the dependent variables while conducting the Transect method. Divers using the Random technique recorded the highest number of species per survey, while the assemblage parameters recorded using Transect and Point methods were statistically similar for most dependent variables. Point surveys, however, had a higher and less variable species diversity. When the data were adjusted for amount of survey time and area it was determined that divers were more efficient in sampling numbers of individuals when using the Transect method.Recently, an interest has developed in the underwater visual assessment of reef fishes (e.g., Barans and Bartone 1983;Harmelin-Vivien et a/. 1985). This interest is due to several reasons as natural reefs serve as important biotopes for testing evolutionary/ecological hypotheses (see Bartone eta/. 1986 for a partial review). Additionally, to assess the relative "health" of natural reefs in terms of productivity, accurate community data are required. Furthermore, advances in the technology of artificial reef design (Buckley et a/. 1985) depend on the development of accurate, quantitative data on fish community abundance and biomass (Bohnsack and Sutherland 1985).Visually gathered reef fish abundance data avoids the substrate disrupting effects of traditional, surface tended collecting devices such as trawling (Bardach 1959 , Brock 1982, DeMartini and Roberts 1982, Kimmel 1985, Sanderson and Solonsky 1986. These studies have used various visual methods to assess fish abundance and employed several analytical techniques to clarify some problems but there remains no clear consensus as to what method is the "best" for all or any specific set of conditions.To help answer this methodological question, two observers compared six different methods under a variety of reef conditions (Bartone eta/. 1986). The conclusion of that study was that all of the compared methods are roughly equivalent in their ability to qualitatively describe a fish assemblage. Methods that produce the most information (i.e., number of species and number of individuals) tend to have less variance and more accurately associate environmental parameters with a particular assemblage. Also, the amount of sample time (and perhaps area) appears to be the most significant variable affecting the similarity of assemblage assessments, regardless of method. This suggests that, of the methods tested, those which produce the greatest amount of information in the least amount of time (or area surveyed) would be the most effective. Given that conventional scientific di...

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Section: Methods Comparisonmentioning

confidence: 99%

A Comparison of Three Methods for Visually Assessing Reef Fish Communities: Time and Area Compensated

Bortone

Kimmel

Bundrick

1989

negs

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“…Our survey protocol may have systematically underestimated their abundance as transect methods have been found to underreport the density of fish species with wide ranges or low abundances (Thresher and Gum, 1986). Furthermore, the size and number of transects can also greatly influence density estimates (Sale and Sharp, 1983). Significantly fewer fish were recorded in nearly all families (including serranids) in the 1997 surveys compared to the 1998 surveys which is thought to be a direct result of the low number of transects employed at each site.…”

Section: T ---mentioning

confidence: 99%

Bahamas. Assessment of the Andros Island Reef System, Bahamas (Part 2: Fishes)

Kramer¹,

Marks²,

Turnbull³

2003

Atoll Research Bulletin

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Coral reef fish assemblages mere surveycd at 38 reef-crest and fore-reef habitats along approximate13 200 km of reefs on the eastern side of Andros Island in August of 1997 and 1998. A total of 164 species were recorded in roving diver suivc s. averaging 7'55 species per site. Select species density averaged 37.4 individuals/100m-in belt tranwcts and was significantly more abundant in reef crests than fore reefs. The select fish asseinblages were dominated by scarids, haemulids, and acanthurids, while serranids were ubiquitous but present in low densities (<0.5/100m~. Small differences in the community structure of four geographic areas (north, central, bights, south) are indicative of well-mixed populations. Species richness and abundance were comparatively low, particularly in fore-reef habitats, although mean size and biomass were relatively high. The Andros reef fish assemblages may be naturally limited by low recruitment, lack of nurseiy habitat, or possibly by high levels of predation. The entire reef system may be at high risk to even modest increases in fishing.Intact fish assemblages are integral to the functioning of coral reefs and patterns in their diversity, abundance, and size can be used to understand underlying ecological processes such as recruitment, predation, and herbivory. These patterns vary at different spatial and temporal scales and are likely to be influenced by habitat variables such as topographic complexity (e

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“…Recognized sources of error common to most underwater visual survey techniques include the following: environmental disparities among surveys affecting the detectability of fishes, such as differences in water clarity and habitat characteristics (Thresher & Gunn 1986); the number and variety of target groups counted simultaneously (Lincoln Smith 1989); observer swimming speed (Lincoln Smith 1988, De Girolamo & Mazzoldi 2001; survey area dimensions (Sale & Sharp 1983, Cheal & Thompson 1997, Kulbicki & Sarramegna 1999; acquired behavioral characteristics of target fishes (Kulbicki 1998); and the survey methodology utilized (Thresher & Gunn 1986, Samoilys & Carlos 2000. There are also substantial differences among distinct taxonomic or functional groups of fishes; large, conspicuous, non-schooling fishes tend to be easier to count than small, schooling, highly mobile, or cryptic fishes (Lincoln Smith 1989, Samoilys & Carlos 2000, Stewart & Beukers 2000.…”

Section: Introductionmentioning

confidence: 99%

Impact of observers experience level on counts of fishes in underwater visual surveys

Williams¹,

Walsh²,

Tissot³

et al. 2006

Mar. Ecol. Prog. Ser.

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Underwater visual surveys are widely used to estimate reef fish abundance. Using data from repeated surveys of coral reef sites on West Hawai'i, we assessed one possible factor driving variation among and within observers' counts, namely the level of observers' previous survey experience. Increasing experience was associated with higher estimates of species richness and of abundance for some but not all taxa, but no systematic change in intra-observer variability. Least experienced observers counted 66 to 71% as many Acanthuridae, Labridae, and benthic Pomacentridae as the most experienced observers, and only 44% as many Holocentridae, those taxa being numerically dominated by small, mobile, or cryptic fishes. In contrast, there was no effect of experience level on counts of more conspicuous or slow-moving taxa: Chaetodontidae, Chromis, and Cirrhitidae. Experience bias is unlikely to be a major problem for survey programs that pool data from multiple observers with broadly similar levels of experience, other than that all sources of difference among observers contribute to increased data variability and consequently lowered statistical power and precision. However, experience bias clearly could be a serious issue for survey or monitoring programs that begin with largely inexperienced survey divers who gain experience and, consequently, tend to count more fish as the program matures. While experience level is not the only factor causing differences among observers, it is relatively easy to recognize and therefore to mitigate. KEY WORDS: Underwater visual survey · Bias · Monitoring · Fish countsResale or republication not permitted without written consent of the publisher

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Correction for bias in visual transect censuses of coral reef fishes

Cited by 129 publications

References 8 publications

A Comparison of Three Methods for Visually Assessing Reef Fish Communities: Time and Area Compensated

A Comparison of Three Methods for Visually Assessing Reef Fish Communities: Time and Area Compensated

Bahamas. Assessment of the Andros Island Reef System, Bahamas (Part 2: Fishes)

Impact of observers experience level on counts of fishes in underwater visual surveys

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Correction for bias in visual transect censuses of coral reef fishes

Cited by 129 publications

References 8 publications

A Comparison of Three Methods for Visually Assessing Reef Fish Communities: Time and Area Compensated

A Comparison of Three Methods for Visually Assessing Reef Fish Communities: Time and Area Compensated

Bahamas. Assessment of the Andros Island Reef System, Bahamas (Part 2: Fishes)

Impact of observers experience level on counts of fishes in underwater visual surveys

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Product

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Impact of observers experience level on counts of fishes in underwater visual surveys