ICES Journal of Marine Science, 63: 1590e1603 (2006) doi:10.1016/j.icesjms.2006.06.008 Habitat suitability modelling of economically important fish species with commercial fisheries data Liz Morris and David Ball Morris, L., and Ball, D. 2006. Habitat suitability modelling of economically important fish species with commercial fisheries data. e ICES Journal of Marine Science, 63: 1590e1603. Downloaded from https://academic.oup.com/icesjms/article/63/9/1590/696978 by guest on 01 October 2021 In this study we used catch and effort data from a commercial fishery to generate habitat suitability models for Port Phillip Bay, Victoria, Australia. Species modelled were King George whiting (Sillaginodes punctata), greenback flounder (Rhombosolea tapirina), Aus- tralian salmon (Arripis trutta and A. truttaceus), and snapper (Pagrus auratus). Locations of commercial catches were reported through a grid system of fishing blocks. Spatial analyses in a Geographic Information System (GIS) were applied to describe each fishing block by its habitat area. A multivariate approach was adopted to group each fishing block by its dominant habitats. Standardized catch per unit effort values were overlaid on these groups to identify those that returned high or low catches for each species. A simple set of rules was then devised to predict the habitat suitability for each habitat combination in a fishing block. The spatial distribution of these habitats was presented in a GIS. These habitat suit- ability models were consistent with existing anecdotal information and expert opinion. While the models require testing, we have shown that in the absence of adequate fishery-independent data, commercial catch and effort data can be used to produce habitat suitability models at a bay-wide scale. Ó 2006 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved. Keywords: catch and effort, fisheries habitat, Geographic Information Systems, multivariate analysis, Port Phillip Bay. Received 25 May 2005; accepted 26 June 2006. L. Morris and D. Ball: Primary Industries Research Victoria e Marine and Freshwater Systems, PO Box 114, Queenscliff, Victoria 3225, Australia. Correspondence to L. Morris: tel: þ61 3 5258 0111; fax: þ61 3 5258 0270; e-mail: [email protected]. Introduction problems when used as a surrogate for fishery-independent data, relating to the scale of information, sampling bias, The protection of fishery habitat is a vital part of ecosystem- reporting issues, and confidentiality (Mace, 1997; Starr and based approaches to fisheries management, and acknowl- Fox, 1997; Zheng et al., 2001; Gallaway et al., 2003a, b). edges that fish populations should not be considered Most commercial fisheries data do not have precise geo- independently of their environment (Sharp, 1997; Parsons graphic coordinates to define spatial location; more often and Harrison, 2000). Despite this, we often lack detailed they use a system of coarse-scale grids for fishers to record information about the importance of different habitat types catch locations. Further, associated environmental data are to fish species, so may be failing to provide adequate pro- not typically recorded with the catch information (Rubec, tection for important habitats. Where fish-habitat associa- 1996). Despite these problems, fisheries scientists and man- tion data exist, it is possible to combine them with habitat agers are increasingly interested in accessing the large data in a Geographic Information System (GIS) to provide amount of information that exists within the fishing com- a spatially explicit model of habitat suitability (Gallaway munity (Bowen, 1997; Maurstad, 2002). et al., 1999; Rubec et al., 1999, 2001, 2003; Brown In areas where characteristics of the fishery are well et al., 2000; Guisan and Zimmermann, 2000; Stoner et al., known, one way of sourcing fisher knowledge is to use 2001). commercial catch and effort data. An implicit assumption Commercial fisheries’ catch and effort data from vessel in using these data is that the regions in which fishers are monitoring systems and logbooks are routinely collected operating have the highest densities of the targeted species. for stock assessment and fishery management purposes in Several recent studies have used logbook data and vessel Australia and internationally. Such data have intrinsic monitoring systems to investigate the spatial distributions 1054-3139/$32.00 Ó 2006 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved. Habitat suitability modelling of fish species with commercial fisheries data 1591 of fish, and have attempted to link this information with In this study we analysed catch and effort data for King environmental data (Denis and Robin, 2001; Zheng et al., George whiting (Sillaginodes punctata), greenback floun- 2001; Denis et al., 2002; Kemp and Meaden, 2002; Marrs der (Rhombosolea tapirina), Australian salmon (Arripis et al., 2002; Reynolds, 2003). In this study, we extend spp.), and snapper (Pagrus auratus) to produce habitat suit- this approach to predict the distribution of suitable habitats, ability models. These species are all major components of and by extension, fish distributions, based on commercial the Port Phillip Bay fishery and include demersal species catch and effort data in Port Phillip Bay, Victoria, Australia (King George whiting, greenback flounder, snapper) and (Figure 1). a pelagic predator (Australian salmon). We assumed that Port Phillip Bay is a large and relatively shallow marine models for the demersal species would be more reliable be- embayment. It is characterized by predominantly bare sand, cause of the closer association of these species with the silt, and clay sediments, with extensive shallow seagrass types of habitat parameters investigated in the study. Downloaded from https://academic.oup.com/icesjms/article/63/9/1590/696978 by guest on 01 October 2021 beds bordering the southern and western shores (Figure 2). The fishery for King George whiting and Australian The bay is linked to the oceanic waters of Bass Strait salmon targets sub-adults, with minimum catch sizes of through a narrow entrance called The Rip, and the tidal 27 and 21 cm, respectively. The snapper fishery can be di- range in most of the bay is <1 m. Its fishery is managed vided into a longline fishery that targets primarily adult fish, through a licencing system with restrictions on fishing and a haul-seine/mesh-net fishery that primarily targets sub- gear types, minimum allowable fish sizes, fishing seasons, adults, colloquially known as ‘‘pinkies’’. Sub-adult snapper and spatial closures (e.g. marine national parks). There have a minimum legal catch size of 27 cm, whereas adults are 59 licenced commercial fishers operating in the Bay, may reach lengths >80 cm. The greenback flounder fishery who primarily fish from small vessels with seine-nets targets adults with a minimum catch size of 23 cm. (haul, purse, and beach), mesh-nets (also known as gill- Haul-seining is restricted to the shallower areas of the nets), and longlines (Anon., 2001). bay. Mesh-nets are used throughout the bay, but most of Figure 1. Port Phillip Bay location maps, and fishery catch and effort block boundaries. 1592 L. Morris and D. Ball Longlines consist of a monofilament main line weighted at each end with a maximum of 200 hooks typically attached at 10-m intervals by 1-m snoods (Coutin, 2000). Fishers are only permitted to deploy one longline at a time, and these are typically used in the deeper areas of the bay away from possible seabed snags, interference from recreational fishers and boating, and where the by- catch of low value species is likely to be minimized. Methods Downloaded from https://academic.oup.com/icesjms/article/63/9/1590/696978 by guest on 01 October 2021 Habitat data GIS polygon layers for depth, sediment type, and substra- tum type/biota provided the habitat information to charac- terize each fishing block (Figure 2). The depth layer was produced by digitizing depth contours from 1:25 000 hydro- graphic charts sourced from the Port of Melbourne Corpo- ration. The sediment type layer was digitized from a 1:100 000 seabed sediment map presented in a study of grain-size distribution throughout the bay (PMA, 1987). A substratum type/biota polygon layer at a scale of 1:25 000 was available from mapping of seagrass distribu- tion, through interpretation of high-resolution colour aerial photography combined with extensive ground-truthing (Blake and Ball, 2001). Because Port Phillip Bay is pre- dominantly a marine system, salinity and water temperature were not considered to be significant influences on the dis- tribution of the fish species investigated in the study. All spatial analyses and development of habitat suitabil- ity maps were undertaken with the GIS software ARCINFO and ArcView. To determine the habitat characteristics of each fishing block, we combined all habitat layers into a sin- gle layer in the GIS. The Identity command in ARCINFO was used to overlay the fishing block layer with substratum type/biota, depth, and sediment polygon layers, and to cal- culate the geometric intersection of each layer (Figure 3). Two layers were intersected at a time with the Identity command, and the output of the process formed one of the input layers to intersect with the next layer (i.e. a geo- metric intersection was calculated on the fishing block and substratum type/biota layers first, then the output from this was intersected with the depth layer, and so on until all layers had been intersected). The final output of this process was a single combined layer that retained the spatial fea- tures and attributes for each of the input layers (Figure 3). A composite habitat code for each feature in the output layer was then calculated by combining the habitat codes Figure 2. Port Phillip Bay depths, substratum type/biota (after from each input layer. The attributes of the GIS habitat Blake and Ball, 2001), and sediments (after PMA, 1987).