Comparing diversity data collected using a protocol designed for volunteers with results from a professional alternative

In light of the continuing biodiversity crisis, the need for high‐resolution, broad‐scale ecological data is particularly acute. The expansive scale of volunteer data collection programmes provides an opportunity to address this challenge, however, protocols used to collect such data are typically less standardized than those used by professional scientists. Although previous studies have established that different protocols can lead to different results, it remains unclear how relevant these differences are to specific study goals, such as biodiversity assessment. This study uses both null model and Bayesian occupancy approaches to examine the capacity of a widely used volunteer survey protocol, the roving diver transect, to detect patterns of marine fish diversity. Richness estimates are compared with those obtained using the conventional belt transects favoured in many peer reviewed studies, examining the power of both protocols to detect statistically significant differences between survey sites and quantifying differences in detectability. Pairwise site comparisons of α‐diversity (i.e. within site diversity) were consistent between protocols, particularly for species totals. The roving diver transect protocol detected a substantially larger number of species than the belt transect protocol, due to notably higher detectability, even after controlling for confounding factors. Both protocols detected the same species pool, although the species richness among observations was higher for the belt protocol at certain sites. The significance of pairwise site β‐diversity (i.e. differentiation between sites) comparisons differed between the protocols and care should be exercised, when using either protocol, when studying variation in species composition. These results provide vital information for managers and researchers considering the use of volunteer data or protocols for the purpose of biodiversity assessment in aquatic systems, helping to quantify the value of thousands of existing survey records. The larger number of species detected by the volunteer protocol suggests this protocol may be advantageous with regards to the completion of taxonomic lists.

[1]  C. Kremen,et al.  Evaluating the Quality of Citizen‐Scientist Data on Pollinator Communities , 2011, Conservation biology : the journal of the Society for Conservation Biology.

[2]  J. Andrew Royle,et al.  Modelling community dynamics based on species‐level abundance models from detection/nondetection data , 2011 .

[3]  O. Defeo,et al.  Taxonomic relatedness and spatial structure of a shelf benthic gastropod assemblage , 2011 .

[4]  Antonio Orlandi,et al.  Unite research with what citizens do for fun: "recreational monitoring" of marine biodiversity. , 2010, Ecological applications : a publication of the Ecological Society of America.

[5]  John K Kruschke,et al.  Bayesian data analysis. , 2010, Wiley interdisciplinary reviews. Cognitive science.

[6]  David Huard,et al.  PyMC: Bayesian Stochastic Modelling in Python. , 2010, Journal of statistical software.

[7]  Laurent Wantiez,et al.  Counting coral reef fishes: Interaction between fish life-history traits and transect design , 2010 .

[8]  J. David Allan,et al.  Managing for ocean biodiversity to sustain marine ecosystem services , 2009 .

[9]  Rob Slotow,et al.  An assessment of the use of volunteers for terrestrial invertebrate biodiversity surveys , 2009, Biodiversity and Conservation.

[10]  J. Clobert,et al.  Advantages of Volunteer‐Based Biodiversity Monitoring in Europe , 2009, Conservation biology : the journal of the Society for Conservation Biology.

[11]  M. Conroy,et al.  Detection heterogeneity in underwater visual‐census data , 2008 .

[12]  M. Conroy,et al.  Accounting for detectability in reef-fish biodiversity estimates , 2008 .

[13]  B. Halpern,et al.  Functional diversity responses to changing species richness in reef fish communities , 2008 .

[14]  J. Andrew Royle,et al.  Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys , 2008 .

[15]  J. Andrew Royle,et al.  Estimating species richness and accumulation by modeling species occurrence and detectability. , 2006, Ecology.

[16]  J. Andrew Royle,et al.  Estimating Size and Composition of Biological Communities by Modeling the Occurrence of Species , 2005 .

[17]  David W. Macdonald,et al.  Validating mammal monitoring methods and assessing the performance of volunteers in wildlife conservation—“Sed quis custodiet ipsos custodies ?” , 2003 .

[18]  R. Sluka,et al.  Evaluating the use of roving diver and transect surveys to assess the coral reef fish assemblage off southeastern Hispaniola , 2002, Coral Reefs.

[19]  S. Lek,et al.  Is scuba sampling a relevant method to study fish microhabitat in lakes? Examples and comparisons for three European species , 2001 .

[20]  Robert K. Colwell,et al.  Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness , 2001 .

[21]  R. Ambrose,et al.  Sampling patchy distributions:comparison of sampling designs in rocky intertidal habitats , 2000 .

[22]  C. S. Robbins,et al.  Population declines in North American birds that migrate to the neotropics. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[23]  R. Thresher,et al.  Comparative analysis of visual census techniques for highly mobile, reef-associated piscivores (Carangidae) , 1986, Environmental Biology of Fishes.

[24]  W. Patefield,et al.  An Efficient Method of Generating Random R × C Tables with Given Row and Column Totals , 1981 .

[25]  R. Whittaker Vegetation of the Siskiyou Mountains, Oregon and California , 1960 .

[26]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[27]  Hugh Sweatman,et al.  Spatial variation in the functional characteristics of herbivorous fish communities and the resilience of coral reefs. , 2013, Ecological applications : a publication of the Ecological Society of America.

[28]  S. Stanley An Analysis of the History of Marine Animal Diversity , 2007 .

[29]  P. Legendre,et al.  vegan : Community Ecology Package. R package version 1.8-5 , 2007 .

[30]  L. Rocha,et al.  Relevance of cryptic fishes in biodiversity assessments: A case study at Buck Island Reef National Monument, St. Croix , 2006 .

[31]  D. Roy,et al.  The Butterfly Monitoring Scheme Report to Recorders 2003 , 2004 .

[32]  János Podani,et al.  RANDOMIZATION OF PRESENCE–ABSENCE MATRICES: COMMENTS AND NEW ALGORITHMS , 2004 .

[33]  Brice X Semmens,et al.  Conservation and management applications of the REEF volunteer fish monitoring program. , 2003, Environmental monitoring and assessment.

[34]  M. Chiappone,et al.  A comparison of belt quadrat and species presence/absence sampling of stony coral (Scleractinia and Milleporina) and sponges for evaluating species patterning on patch reefs of the central Bahamas , 1992 .

[35]  W. Gladstone,et al.  Accuracy and bias of visual estimates of numbers, size structure and biomass of a coral reef fish , 1990 .