Marine and Freshwater Research Marine and Freshwater Research Society
Advances in the aquatic sciences
RESEARCH ARTICLE

Modelling the distribution of fish around an artificial reef

James A. Smith A B D , William K. Cornwell A , Michael B. Lowry C and Iain M. Suthers A B
+ Author Affiliations
- Author Affiliations

A Evolution and Ecology Research Centre, and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia.

B Sydney Institute of Marine Science, Chowder Bay Road, Mosman, NSW 2088, Australia.

C Port Stephens Fisheries Institute, Locked Bag 1, Nelson Bay, NSW 2315, Australia.

D Corresponding author. Email: james.smith@unsw.edu.au

Marine and Freshwater Research 68(10) 1955-1964 https://doi.org/10.1071/MF16019
Submitted: 19 January 2016  Accepted: 29 January 2017   Published: 10 April 2017

Abstract

Artificial reefs are a widely used tool aimed at fishery enhancement, and measuring the scale at which fish assemblages associate with these artificial habitat patches can aid reef design and spatial arrangement. The present study used rapidly deployed underwater video (drop cameras) to determine the magnitude and spatial scale of associations between a fish assemblage and a coastal artificial reef. Count data from drop cameras were combined with distance and bathymetry information to create a suite of explanatory generalised linear mixed models (GLMMs). The GLMMs showed that artificial reefs can influence surrounding fish abundance, but that the magnitude and scale is species specific. Three of the eight taxonomic groups examined showed a positive association with the artificial reef (with model fit poor for the remaining groups); and depth and bottom cover were also influential variables. The spatial scales of these associations with the artificial reef were small, and it was generally the presence of reef (i.e. a reef bottom type) that explained more variation in fish abundance than did distance to reef. The schooling baitfish yellowtail scad was an exception, and had elevated abundance >50 m from the artificial reef. Further distribution modelling of artificial reefs will benefit species-specific design and management of artificial reefs.

Additional keywords: fish abundance, GLM, species distribution model, underwater video.


References

Baine, M. (2001). Artificial reefs: a review of their design, application, management and performance. Ocean and Coastal Management 44, 241–259.
Artificial reefs: a review of their design, application, management and performance.CrossRef |

Beger, M., and Possingham, H. P. (2008). Environmental factors that influence the distribution of coral reef fishes: modeling occurrence data for broad-scale conservation and management. Marine Ecology Progress Series 361, 1–13.
Environmental factors that influence the distribution of coral reef fishes: modeling occurrence data for broad-scale conservation and management.CrossRef |

Belmaker, J., Ziv, Y., and Shashar, N. (2011). The influence of connectivity on richness and temporal variation of reef fishes. Landscape Ecology 26, 587–597.
The influence of connectivity on richness and temporal variation of reef fishes.CrossRef |

Bender, D. J., Contreras, T. A., and Fahrig, L. (1998). Habitat loss and population decline: a meta-analysis of the patch size effect. Ecology 79, 517–533.
Habitat loss and population decline: a meta-analysis of the patch size effect.CrossRef |

Biesinger, Z., Bolker, B. M., and Lindberg, W. J. (2011). Predicting local population distributions around a central shelter based on a predation risk-growth trade-off. Ecological Modelling 222, 1448–1455.
Predicting local population distributions around a central shelter based on a predation risk-growth trade-off.CrossRef |

Bombace, G. (1989). Artificial reefs in the Mediterranean Sea. Bulletin of Marine Science 44, 1023–1032.

Bortone, S. A., Cody, R. P., Turpin, R. K., and Bundrick, C. M. (1998). The impact of artificial‐reef fish assemblages on their potential forage area. Italian Journal of Zoology 65, 265–267.
The impact of artificial‐reef fish assemblages on their potential forage area.CrossRef |

Brandt, J. R., and Jackson, D. C. (2013). Influences of artificial reefs on juvenile red snapper along the Mississippi Gulf coast. Marine and Coastal Fisheries 5, 1–10.
Influences of artificial reefs on juvenile red snapper along the Mississippi Gulf coast.CrossRef |

Buckle, E. C., and Booth, D. J. (2009). Ontogeny of space use and diet of two temperate damselfish species, Parma microlepis and Parma unifasciata. Marine Biology 156, 1497–1505.
Ontogeny of space use and diet of two temperate damselfish species, Parma microlepis and Parma unifasciata.CrossRef |

Burnham, K. P., and Anderson, D. R. (2002). ‘Model Selection and Multimodal Inference: a Practical Information–Theoretic Approach.’ (Springer-Verlag: New York, NY, USA.)

Campbell, M. D., Rose, K., Boswell, K., and Cowan, J. (2011). Individual-based modeling of an artificial reef fish community: effects of habitat quantity and degree of refuge. Ecological Modelling 222, 3895–3909.
Individual-based modeling of an artificial reef fish community: effects of habitat quantity and degree of refuge.CrossRef |

Cappo, M., Speare, P., and De’ath, G. (2004). Comparison of baited remote underwater video stations (BRUVS) and prawn (shrimp) trawls for assessments of fish biodiversity in inter-reefal areas of the Great Barrier Reef Marine Park. Journal of Experimental Marine Biology and Ecology 302, 123–152.
Comparison of baited remote underwater video stations (BRUVS) and prawn (shrimp) trawls for assessments of fish biodiversity in inter-reefal areas of the Great Barrier Reef Marine Park.CrossRef |

Carrasco, J. L. (2010). A generalized concordance correlation coefficient based on the variance components generalized linear mixed models for overdispersed count data. Biometrics 66, 897–904.
A generalized concordance correlation coefficient based on the variance components generalized linear mixed models for overdispersed count data.CrossRef |

Champion, C., Suthers, I. M., and Smith, J. A. (2015). Zooplanktivory is a key process for fish production on a coastal artificial reef. Marine Ecology Progress Series 541, 1–14.
Zooplanktivory is a key process for fish production on a coastal artificial reef.CrossRef | 1:CAS:528:DC%2BC28XhtFalsLzI&md5=e6e9f64d812adc2333e4517c50f9bf60CAS |

Clynick, B. G., Chapman, M. G., and Underwood, A. J. (2008). Fish assemblages associated with urban structures and natural reefs in Sydney, Australia. Austral Ecology 33, 140–150.
Fish assemblages associated with urban structures and natural reefs in Sydney, Australia.CrossRef |

dos Santos, L. N., Brotto, D. S., and Zalmon, I. R. (2010). Fish responses to increasing distance from artificial reefs on the southeastern Brazilian Coast. Journal of Experimental Marine Biology and Ecology 386, 54–60.
Fish responses to increasing distance from artificial reefs on the southeastern Brazilian Coast.CrossRef |

Easton, R. R., Heppell, S. S., and Hannah, R. W. (2015). Quantification of habitat and community relationships among nearshore temperate fishes through analysis of drop camera video. Marine and Coastal Fisheries 7, 87–102.
Quantification of habitat and community relationships among nearshore temperate fishes through analysis of drop camera video.CrossRef |

Edgar, G. J. (2008) ‘Australian Marine Life.’ (New Holland Publishers: Sydney, NSW, Australia.)

Elith, J., and Leathwick, J. R. (2009). Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology Evolution and Systematics 40, 677–697.
Species distribution models: ecological explanation and prediction across space and time.CrossRef |

Fabi, G., and Sala, A. (2002). An assessment of biomass and diel activity of fish at an artificial reef (Adriatic Sea) using a stationary hydroacoustic technique. ICES Journal of Marine Science 59, 411–420.
An assessment of biomass and diel activity of fish at an artificial reef (Adriatic Sea) using a stationary hydroacoustic technique.CrossRef |

Folpp, H., Lowry, M., Gregson, M., and Suthers, I. M. (2011). Colonization and community development of fish assemblages associated with estuarine artificial reefs. Brazilian Journal of Oceanography 59, 55–67.
Colonization and community development of fish assemblages associated with estuarine artificial reefs.CrossRef |

Folpp, H., Lowry, M., Gregson, M., and Suthers, I. M. (2013). Fish assemblages on estuarine artificial reefs: natural rocky-reef mimics or discrete assemblages? PLoS One 8, e63505.
Fish assemblages on estuarine artificial reefs: natural rocky-reef mimics or discrete assemblages?CrossRef | 1:CAS:528:DC%2BC3sXpvVKhtL4%3D&md5=6e6bbca93c3ffe70a1e01a1a73e4e7ebCAS |

Fournier, D. A., Skaug, H. J., Ancheta, J., Ianelli, J., Magnusson, A., Maunder, M. N., Nielsen, A., and Sibert, J. (2012). AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optimization Methods & Software 27, 233–249.
AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models.CrossRef |

French, B., Clarke, K. R., Platell, M. E., and Potter, I. C. (2013). An innovative statistical approach to constructing a readily comprehensible food web for a demersal fish community. Estuarine, Coastal and Shelf Science 125, 43–56.
An innovative statistical approach to constructing a readily comprehensible food web for a demersal fish community.CrossRef |

Gladstone, W., Lindfield, S., Coleman, M., and Kelaher, B. (2012). Optimisation of baited remote underwater video sampling designs for estuarine fish assemblages. Journal of Experimental Marine Biology and Ecology 429, 28–35.
Optimisation of baited remote underwater video sampling designs for estuarine fish assemblages.CrossRef |

Harvey, E. S., Cappo, M., Butler, J. J., Hall, N., and Kendrick, G. A. (2007). Bait attraction affects the performance of remote underwater video stations in assessment of demersal fish community structure. Marine Ecology Progress Series 350, 245–254.
Bait attraction affects the performance of remote underwater video stations in assessment of demersal fish community structure.CrossRef |

Hilbe, J. M. (2011) ‘Negative Binomial Regression.’ (Cambridge University Press: Cambridge, UK.)

Horne, J. K. (2000). Acoustic approaches to remote species identification: a review. Fisheries Oceanography 9, 356–371.
Acoustic approaches to remote species identification: a review.CrossRef |

Jordan, L. K. B., Gilliam, D. S., and Spieler, R. E. (2005). Reef fish assemblage structure affected by small-scale spacing and size variations of artificial patch reefs. Journal of Experimental Marine Biology and Ecology 326, 170–186.
Reef fish assemblage structure affected by small-scale spacing and size variations of artificial patch reefs.CrossRef |

Keller, K., Steffe, A. S., Lowry, M., Murphy, J. J., and Suthers, I. M. (2016). Monitoring boat-based recreational fishing effort at a nearshore artificial reef with a shore-based camera. Fisheries Research 181, 84–92.
Monitoring boat-based recreational fishing effort at a nearshore artificial reef with a shore-based camera.CrossRef |

Lindquist, D. G., Cahoon, L. B., Clavijo, I. E., Posey, M. H., Bolden, S. K., Pike, L. A., Burk, S. W., and Cardullo, P. A. (1994). Reef fish stomach contents and prey abundance on reef and sand substrata associated with adjacent artificial and natural reefs in Onslow Bay, North Carolina. Bulletin of Marine Science 55, 308–318.

Lowry, M., Folpp, H., Gregson, M., and Suthers, I. (2012). Comparison of baited remote underwater video (BRUV) and underwater visual census (UVC) for assessment of artificial reefs in estuaries. Journal of Experimental Marine Biology and Ecology 416-417, 243–253.
Comparison of baited remote underwater video (BRUV) and underwater visual census (UVC) for assessment of artificial reefs in estuaries.CrossRef |

Malcolm, H. A., Gladstone, W., Lindfield, S., Wraith, J., and Lynch, T. P. (2007). Spatial and temporal variation in reef fish assemblages of marine parks in New South Wales, Australia: baited video observations. Marine Ecology Progress Series 350, 277–290.
Spatial and temporal variation in reef fish assemblages of marine parks in New South Wales, Australia: baited video observations.CrossRef |

Mellin, C., Andréfouët, S., and Ponton, D. (2007). Spatial predictability of juvenile fish species richness and abundance in a coral reef environment. Coral Reefs 26, 895–907.
Spatial predictability of juvenile fish species richness and abundance in a coral reef environment.CrossRef |

Mellin, C., Bradshaw, C. J. A., Meekan, M. G., and Caley, M. J. (2010). Environmental and spatial predictors of species richness and abundance in coral reef fishes. Global Ecology and Biogeography 19, 212–222.
Environmental and spatial predictors of species richness and abundance in coral reef fishes.CrossRef |

Miller, M. E. (2007). Key biological parameters and commercial fishery for ocean leatherjackets ‘Nelusetta ayraudi’ (Monacanthidae) off the coast of New South Wales, Australia. M.Env.Sc. Thesis, University of Wollongong, NSW, Australia.

Morton, J. K., and Gladstone, W. (2011). Spatial, temporal and ontogenetic variation in the association of fishes (family Labridae) with rocky-reef habitats. Marine and Freshwater Research 62, 870–884.
Spatial, temporal and ontogenetic variation in the association of fishes (family Labridae) with rocky-reef habitats.CrossRef |

Murphy, H. M., and Jenkins, G. P. (2010). Observational methods used in marine spatial monitoring of fishes and associated habitats: a review. Marine and Freshwater Research 61, 236–252.
Observational methods used in marine spatial monitoring of fishes and associated habitats: a review.CrossRef | 1:CAS:528:DC%2BC3cXisVagsrw%3D&md5=01436e958075592f160910e16ff0d54fCAS |

Parsons, D. F., Suthers, I. M., Cruz, D. O., and Smith, J. A. (2016). Effects of habitat on fish abundance and species composition on temperate rocky reefs. Marine Ecology Progress Series 561, 155–171.
Effects of habitat on fish abundance and species composition on temperate rocky reefs.CrossRef |

Pita, P., Fernández-Márquez, D., and Freire, J. (2014). Short-term performance of three underwater sampling techniques for assessing differences in the absolute abundances and in the inventories of the coastal fish communities of the northeast Atlantic Ocean. Marine and Freshwater Research 65, 105–113.
Short-term performance of three underwater sampling techniques for assessing differences in the absolute abundances and in the inventories of the coastal fish communities of the northeast Atlantic Ocean.CrossRef |

Pittman, S. J., and Brown, K. A. (2011). Multi-scale approach for predicting fish species distributions across coral reef seascapes. PLoS One 6, e20583.
Multi-scale approach for predicting fish species distributions across coral reef seascapes.CrossRef | 1:CAS:528:DC%2BC3MXntVait7Y%3D&md5=fc6cabdeab3a7e1d358435c76bbac04bCAS |

Poff, N. L., and Allan, J. D. (1995). Functional organization of stream fish assemblages in relation to hydrological variability. Ecology 76, 606–627.
Functional organization of stream fish assemblages in relation to hydrological variability.CrossRef |

Ricketts, T. H. (2001). The matrix matters: effective isolation in fragmented landscapes. American Naturalist 158, 87–99.
The matrix matters: effective isolation in fragmented landscapes.CrossRef | 1:STN:280:DC%2BD1critlynug%3D%3D&md5=b865555692042d14c1812cf1c700275cCAS |

Robinson, L. M., Elith, J., Hobday, A. J., Pearson, R. G., Kendall, B. E., Possingham, H. P., and Richardson, A. J. (2011). Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities. Global Ecology and Biogeography 20, 789–802.
Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities.CrossRef |

Ross, P. M., Thrush, S. F., Montgomery, J. C., Walker, J. W., and Parsons, D. M. (2007). Habitat complexity and predation risk determine juvenile snapper (Pagrus auratus) and goatfish (Upeneichthys lineatus) behaviour and distribution. Marine and Freshwater Research 58, 1144–1151.
Habitat complexity and predation risk determine juvenile snapper (Pagrus auratus) and goatfish (Upeneichthys lineatus) behaviour and distribution.CrossRef |

Sainte-Marie, B., and Hargrave, B. T. (1987). Estimation of scavenger abundance and distance of attraction to bait. Marine Biology 94, 431–443.
Estimation of scavenger abundance and distance of attraction to bait.CrossRef |

Saunders, D. A., Hobbs, R. J., and Margules, C. R. (1991). Biological consequences of ecosystem fragmentation: a review. Conservation Biology 5, 18–32.
Biological consequences of ecosystem fragmentation: a review.CrossRef |

Scott, M. E., Smith, J. A., Lowry, M. B., Taylor, M. D., and Suthers, I. M. (2015). The influence of an offshore artificial reef on the abundance of fish in the surrounding pelagic environment. Marine and Freshwater Research 66, 429–437.
The influence of an offshore artificial reef on the abundance of fish in the surrounding pelagic environment.CrossRef |

Smith, J. A., Lowry, M. B., and Suthers, I. M. (2015). Fish attraction to artificial reefs not always harmful: a simulation study. Ecology and Evolution 5, 4590–4602.
Fish attraction to artificial reefs not always harmful: a simulation study.CrossRef |

Smith, J. A., Lowry, M. B., Champion, C., and Suthers, I. M. (2016). A designed artificial reef is among the most productive marine fish habitats: new metrics to address ‘production versus attraction’. Marine Biology 163, 188.
A designed artificial reef is among the most productive marine fish habitats: new metrics to address ‘production versus attraction’.CrossRef |

Stanley, D. R., and Wilson, C. A. (2003) Seasonal and spatial variation in the biomass and size frequency distribution of fish associated with oil and gas platforms in the northern Gulf of Mexico. In ‘Fisheries, Reefs, and Offshore Development, American Fisheries Society Symposium 36’, 24–26 October 2000, New Orleans, LA, USA. (Eds D. R. Stanley, and A. Scarborough-Bull.) pp. 123–153. (American Fisheries Society: Bethesda, MD, USA.)

Strelcheck, A. J., Cowan, J. H., and Shah, A. (2005). Influence of reef location on artificial-reef fish assemblages in the northcentral Gulf of Mexico. Bulletin of Marine Science 77, 425–440.

Taylor, M. D., Baker, J., and Suthers, I. M. (2013). Tidal currents, sampling effort and baited remote underwater video (BRUV) surveys: are we drawing the right conclusions? Fisheries Research 140, 96–104.
Tidal currents, sampling effort and baited remote underwater video (BRUV) surveys: are we drawing the right conclusions?CrossRef |

Thierry, J.-M. (1988). Artificial reefs in Japan: a general outline. Aquacultural Engineering 7, 321–348.
Artificial reefs in Japan: a general outline.CrossRef |

Vega Fernández, T., D’Anna, G., Badalamenti, F., and Perez-Ruzafa, A. (2008). Habitat connectivity as a factor affecting fish assemblages in temperate reefs. Aquatic Biology 1, 239–248.
Habitat connectivity as a factor affecting fish assemblages in temperate reefs.CrossRef |

Villard, M.-A., and Metzger, J. P. (2014). REVIEW: beyond the fragmentation debate: a conceptual model to predict when habitat configuration really matters. Journal of Applied Ecology 51, 309–318.
REVIEW: beyond the fragmentation debate: a conceptual model to predict when habitat configuration really matters.CrossRef |

Walsh, W. J. (1985). Reef fish community dynamics on small artificial reefs: the influence of isolation, habitat structure, and biogeography. Bulletin of Marine Science 36, 357–376.

Williams, A., and Bax, N. J. (2001). Delineating fish–habitat associations for spatially based management: an example from the south-eastern Australian continental shelf. Marine and Freshwater Research 52, 513–536.
Delineating fish–habitat associations for spatially based management: an example from the south-eastern Australian continental shelf.CrossRef |

Willis, T. J., and Babcock, R. C. (2000). A baited underwater video system for the determination of relative density of carnivorous reef fish. Marine and Freshwater Research 51, 755–763.
A baited underwater video system for the determination of relative density of carnivorous reef fish.CrossRef |

Willis, T. J., Millar, R. B., and Babcock, R. C. (2000). Detection of spatial variability in relative density of fishes: comparison of visual census, angling, and baited underwater video. Marine Ecology Progress Series 198, 249–260.
Detection of spatial variability in relative density of fishes: comparison of visual census, angling, and baited underwater video.CrossRef |

Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A., and Smith, G. M. (2009). ‘Mixed Effects Models and Extensions in Ecology with R.’ (Springer: New York.)

Zuur A. F., Saveliev A. A., and Ieno E. N. (2012). ‘Zero Inflated Models and Generalized Linear Mixed Models with R.’ (Highland Statistics: Newburgh, UK.)

Zuur, A. F., Hilbe, J. M., and Ieno, E. N. (2013). ‘A Beginner’s Guide to GLM and GLMM with R.’ (Highland Statistics: Newburgh, UK.)



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