Linking spatial metrics and fish catch reveals the importance of coastal wetland connectivity to inshore fisheries in Queensland, Australia

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Abstract

Many commercially important fish species use coastal marine environments such as mangroves, tidal flats and seagrass beds as nurseries or breeding grounds. The ecological importance of spatially connected habitats to conservation is well established for terrestrial environments. However, few studies have applied spatial metrics, including measures of structural connectivity to marine environments. We examined the relationship between catch-per-unit-effort for commercially caught species and the spatial patterning of mapped benthic habitat types along the coast of Queensland, Australia in their dominant fisheries (trawl, line, net or pot fisheries). We quantified the composition and spatial configuration of seascapes and calculated coastline length, number of estuaries, river length and geographical latitude using 12 metrics within ninety 30-nautical-mile grid cells, which supported inshore fish catch data from 21 species groups. Multiple regression analysis and non-metric multidimensional scaling plots indicated that ecological linkages may exist between geomorphic coastal features and nearshore fisheries production for a number of species groups. Connectivity indices for mangroves, salt marsh and channels explained the largest proportion (30–70%), suggesting the importance of connected tidal wetlands for fisheries. Barramundi (Lates calcarifer) catch-per-unit-effort was best explained by the number of wetland patches, mangrove connectivity and wetland connectivity (r2 = 0.38, n = 28). Catch-per-unit-effort for the Gulf of Carpentaria was highly correlated with wetland connectivity, the number of estuaries and seagrass patch density (r = 0.57, n = 29). The findings could guide the spatial design of marine protected area networks to maintain ecosystem services and avoid potential disruption to connectivity caused by habitat removal or modification. Application of the same approach to analyses of finer spatial scales would enable catch information to be related to particular estuarine habitats and provide better understanding of the importance of habitat connectivity for fisheries.

Introduction

Estuarine dependent or opportunistic fish species are the main target of inshore fisheries that sustain many coastal communities (Feierabend and Zelazny, 1987). Of the about 11,300 extant fish species, the largest proportion (46%) are coastal, ranging from estuaries, lagoons, and deltas to the outer continental shelf (Nelson, 1994), providing >90% of the global fish catch (Pernetta and Milliman, 1995). These fish species have different resource requirements depending on their life cycle (Pittman and McAlpine, 2003, Pittman et al., 2007). However, increased fishing pressure and the alteration of coastal habitats cast doubts on the future of nearshore fisheries. More than 50% of the world’s human population live within 50 km of the coast (Hinrichsen, 1998), impacting on important nursery habitats for fish. Understanding of the value of these nursery habitats for estuarine fish species is vital for their effective protection. In order to establish functional marine protected areas to prevent fisheries habitat destruction and overfishing, an appraisal of the most effective spatial combination of habitats is necessary (Lenanton and Potter, 1987).

There has been extensive search for estuarine habitat values in the past few decades for fish species (Odum, 1968, Blaber et al., 1995, Gillanders et al., 2003) to define the most effective marine protected area design. Many studies have shown linkages between estuarine habitats and nearshore fisheries (Pauly and Ingles, 1986, Manson et al., 2005a, Meynecke et al., 2007). Analyses of estuaries and fish catch data have demonstrated the potential of data sets already available for Australia (Pease, 1999, Saintilan, 2004; Duffy et al., in litt.). Several studies have found correlations between the area of mangroves and the catch in nearby fisheries (Staples et al., 1985, Manson et al., 2005b).

However, little is known about the relative influence of coastal geomorphic characteristics, in particular, the importance of habitat connectivity, on the spatial distribution and abundance of commercial estuary-dependent fish species. Studies have suggested that the ‘edge’ of tidal wetlands provide the greatest attraction to aquatic organisms such as crustaceans and fish (Minello et al., 1994, Vance et al., 2002, Haas et al., 2004). Any change in edge to area ratio due to alteration of the habitat edge will therefore affect the abundance of aquatic organisms. For example, Browder et al. (1989) showed that salt marsh fragmentation was related to prawn abundance, and on smaller scales of a few meters, predation rates of shellfish in seagrass beds were dependent on the patch size to perimeter ratio (Irlandi et al., 1999). Non-species-specific connectivity measures have previously been used in terrestrial reserve design (e.g., buffer measure: Araújo et al., 2002; distance-dependent connectivity measures: Briers, 2002) but currently there are no examples of work on spatial metrics addressing coastal benthic habitat connectivity at appropriately broad spatial scales to support resource management decision making.

A landscape approach to the ecological study of marine animals is still in its infancy (Kneib and Wagner, 1994, Robbins and Bell, 1994), with few studies quantifying marine landscape structure at spatial scales appropriate to the fisheries management (Pittman and McAlpine, 2003, Pittman et al., 2007). Investigations have been dominated by studies in single habitat types, predominantly mangroves (Faunce and Serafy, 2006) or seagrass (Pittman et al., 2004). For highly mobile species, particularly those that use more than one habitat type through daily home range movements or ontogenetic shifts, a broader scale approach that incorporates multiple habitat types is appropriate (Irlandi and Crawford, 1997, Mumby et al., 2004, Meynecke et al., 2007). Landscape connectivity is thus an important concept that has rarely been explored for marine environments but is now subject to increasing attention (Kneib, 2000, Guest and Connolly, 2006, Sheaves, 2006). A seascape connectivity index for estuarine habitats could be a useful instrument for the implementation of an ecosystem approach to fisheries management.

We use ‘structural connectivity’ in this study to investigate the spatial proximity of fish habitat types and develop indicators for spatially characterising coastal ecosystems of Queensland, Australia. The study is exploratory and focuses on spatial associations between faunal patterns and environmental patterns. The coastline of Queensland is covered with an estimated 32,000 km2 of mangroves, salt marsh and seagrass (Bucher and Saenger, 1994) extending from Moreton Bay (27°S 153°E) in south-east Queensland with a subtropical climate and average rainfall of 1100 mm y−1, to the Gulf of Carpentaria (14°S 139°E) in the north-west of Queensland with a tropical climate and an average rainfall ranging from 600 mm y−1 in the south to 1600 mm y−1 in the north (Bureau of Meteorology, 2003). This stretch of coastline provides a large variety of different habitat types varying in spatial configuration along the coast (Fig. 1).

We investigated the linkages between seascape structure and the spatial distributions and abundance of estuary-dependent fish species based on fisheries species catch records using landscape ecology concepts and methods. The analysis has the following objectives: (1) evaluate the relative importance of connectivity in comparison to other habitat metrics in determining coastal fish catch in Queensland, Australia; and (2) identify geographical regions in coastal Queensland with high fish habitat connectivity. The results will help generate testable hypotheses concerning the value of habitat connectivity to nearshore secondary production, and assist prioritisation of estuaries for future ecosystem-based fishery management.

Section snippets

Fishery and tidal wetland data collection

Data on catch, effort (number of days and boats) and gross value of production for estuary dependent species or species groups were provided by the Department of Primary Industries and Fisheries Assessment and Monitoring Unit (Table 1). This dataset is based on daily logbook records reported by commercial fishers providing details of their catch and effort, covering the years 1988–2004, and recorded in 30-nautical-mile grids (half-degree) for the entire coast of Queensland. Prawns were only

Habitat distribution, spatial characteristics and overall results

The habitat analyses reflected large areas of tidal wetlands in south-east Queensland and the Gulf of Carpentaria where saltpans are dominating. Wetland edge to area ratio was highest in the south-east (V35W35), north of Queensland (G14) and the Gulf of Carpentaria (AG18, AD18); wetland connectivity index (100 m) (Table 3) was highest in south-east Queensland, near Cairns (H17, I17) and in some grids in the Gulf of Carpentaria (AC10, AG18, AC18). We found that high connectivity of landscape was

Connectivity – indicator for estuarine habitat conservation

This study applied an exploratory landscape approach to identify the major environmental variables influencing the observed spatial patterns in fish and prawn catches in Queensland, Australia. We were able to demonstrate an association between broad-scale landscape connectivity and fish catch. The study supports the paradigm that heterogeneity and connectivity of coastal marine habitats at a broad spatial scale appears to explain a significant proportion of the spatial variability in fish catch

Acknowledgements

We thank Jan Warnken for technical support in geographic information systems (Griffith University) and, Malcolm Dunning, Leonard Olyott, Karen Danaher (Department of Primary Industries and Fisheries) and Michael Arthur (Griffith University) for useful discussions during this study. Ronald Baker (National Oceanic and Atmospheric Administration), Julie Robins, Lew Williams (Department of Primary Industries and Fisheries) and two anonymous reviewers provided constructive comments on earlier drafts

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