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