final fv rr #57 kgw climate change 20120830€¦ · 30/8/2012 · marine biophysical assesment –...

Marine Biophysical Assesment – King George whiting

Fisheries Adaptation to Climate Change ‐ Marine Biophysical Assessment of King George whiting

Greg Jenkins, Neil Hutchinson, Paul Hamer and Jodie Kemp

Fisheries Victoria Research Report Series No. 57

August 2012


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Preferred way to cite this publication:

Jenkins, G. P., Hutchinson, N., Hamer, P. A. and Kemp, J. (2012) Fisheries Adaptation to Climate Change ‐ Marine Biophysical Assessment of King George whiting. Fisheries Victoria Research Report Series No. 57, 41 pp.

ISSN 1448‐7373

ISBN 978‐1‐74326‐060‐9 (Print)

Author Contact Details: Greg Jenkins Fisheries Research Branch, Fisheries Victoria PO Box 114, Queenscliff Vic 3225

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Executive Summary Fisheries Victoria is undertaking a suite of projects under the Future Farming Strategy initiative ʺAdaptation of fisheries, aquaculture and fisheries management to climate changeʺ to prepare fisheries sectors and fisheries managers for change.

Under this initiative, the marine biophysical assessments are aimed at understanding the biophysical implications that may occur in the future due to climate change to better inform decision making. These assessments aim to determine the degree of exposure a species has to climate change to inform assessments on how vulnerable Victoria’s fishing and aquaculture sectors are to these changes.

King George whiting was specifically identified as one of the higher priority species for Victoria as it represents a key recreational and commercial fish species in Victoria that relies on seagrass as a key component to complete its life cycle. The exact extent of this requirement is unknown and requires attention to enable the vulnerability of the species to climate change to be understood.

This project focuses on understanding the key characteristics of seagrass regions within Port Phillip Bay that are important to the production of juvenile King George whiting. This includes the depth of seagrass preferred by different age‐classes of juveniles and the areas of seagrass in Port Phillip Bay that are most important for producing juvenile King George whiting.

The aims of the project were to inform decision makers on the vulnerability of King George whiting to climate change in Port Phillip Bay, informing on opportunities for improving the resilience and adaptation of King George whiting, and informing fishery management arrangements of future whiting population trends.

Sampling with underwater stereo video was done in four areas of Port Phillip Bay: Eastern Beach, Grand Scenic, Mud Islands and Swan Island; in spring 2010 and autumn 2011. Habitats sampled were the sub‐tidal seagrass, Zostera nigricaulis (“seagrass habitat”) and unvegetated sand/mud at the edge of seagrass (“edge habitat”). In each area, habitats were sampled in

two depth zones: “shallow” (0.4 to 1.1 m) and deep (2.2 to 7.7 m).

Stereo video analysis showed distinct patterns in spatial, temporal and depth distribution as well as habitat use in King George whiting. Distinct patterns were also observed in size distributions between sites and depths.

The most common habitat juvenile King George whiting was observed in was shallow seagrass edge habitat. This was consistent with results for small juveniles collected by netting in previous studies. There was, however, a general pattern of larger, older juvenile whiting occurring in deep habitats and also in habitats at Mud Islands.

The smallest King George whiting juveniles recorded in this study were from Grand Scenic (southern Geelong Arm) in autumn, and at a size of 60–120 mm would have been approximately 6 months old. The largest individuals of 2–3 years of age and over 30 cm in length were recorded in deep seagrass habitat at Mud Islands.

Otolith microchemistry was used to investigate the seagrass regions in Port Phillip Bay most important for producing young whiting. Otoliths of newly‐settled post larvae from 10 seagrass sites around Port Phillip Bay were analysed to identify “signatures” for different seagrass sites, and then compared to the signatures formed at the same time in the otoliths of juveniles caught one year later.

There was considerable overlap in otolith chemistry between sites that meant that “signatures” for individual sites could not be identified. However, it was possible to group the sites as ‘north’ and ‘south’ regions to provide a reliable baseline data set with which to determine the origin of 1‐year old King George whiting.

Sufficient 1‐year old whiting could only be collected from three southern sites (Corio Bay, Grassy Point and Swan Bay), and these were all found to have originated from the southern region. Moreover, similarity between signatures in post‐larvae and 1‐year olds from these sites indicated that juveniles had not moved significantly over their first year of juvenile life. These results supported the video observations that smaller juveniles were generally in shallow, nearshore habitat.


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Climate changes impacts on seagrass are likely to depend on depth, as will the flow on impacts to juvenile King George whiting. Although there are significant uncertainties, on balance, the evidence suggests that climate change will have a detrimental effect on seagrass, particularly in shallow habitats. Shallow habitats appear to be the most important for younger juvenile King George whiting. Potential climate change effects on shallow seagrass include increasing sea level, increasing water temperature and desiccation, and increased disturbance due to more frequent and intensive storm events.

In terms of spatial distribution, the youngest juveniles were collected in the Geelong Arm. Seagrass coverage in the Geelong Arm may therefore be particularly significant for young juvenile King George whiting. Decreased runoff under climate change could mean reduced nutrients reaching the southern Geelong Arm and Port Phillip Bay that could cause seagrass decline through nutrient limitation. This would have a similar effect in both shallow and deep seagrass beds.

The resilience of populations of juvenile King George whiting to climate change will largely depend on the resilience of seagrass habitats. Seagrass will be most resilient to climate change where seagrass health is not also compromised by other stressors; particularly those that affect water quality and light availability. In this case, catchment management practices will be crucial to support seagrass health and resilience to climate change.

Predicting the future trend of the King George whiting population has significant uncertainty because of the dependence of fishery recruitment on both larval supply and juvenile survival. However, a significant loss of seagrass would almost inevitably lead to a significant decline in the King George whiting population. As mentioned, reducing other stressors on seagrass health will significantly increase the resilience of seagrass and therefore King George whiting populations to climate change impacts. In this respect, mitigation is mostly the responsibility of catchment and coastal managers rather than fishery managers. However, although fisheries managers are not able to directly manage these areas, they can strongly advocate for this management, either directly between management agencies or through education of industry and the public as to the importance of these areas that will increase pressure for protection.

Management of the King George whiting fishery will need to be adaptive, and ideally would include a harvest strategy that sets limits, targets and decision rules. For King George whiting this strategy could be largely based on monitoring of both post‐larval settlement and seagrass cover to provide an estimate of fishery recruitment in the ensuing years.


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Table of Contents

Executive Summary............................................................................................. iii

Introduction............................................................................................................ 1 Climate change predictions for Victoria................................................................................................................1 Temperature ............................................................................................................................................................1 Rainfall .....................................................................................................................................................................1 Winds........................................................................................................................................................................1 Currents....................................................................................................................................................................2 Seawater Chemistry................................................................................................................................................2 Sea level....................................................................................................................................................................2 Solar radiation .........................................................................................................................................................2

King George whiting biology..................................................................................................................................2 This Report..................................................................................................................................................................3 Objectives....................................................................................................................................................................4

Project Design and Methods ............................................................................... 5 Underwater Stereo Video.........................................................................................................................................5 Study sites ................................................................................................................................................................5 Remote underwater video .....................................................................................................................................5 Experimental design...............................................................................................................................................5 Video analysis .........................................................................................................................................................5 Data analysis............................................................................................................................................................5

Otolith chemistry.......................................................................................................................................................5 Data analysis............................................................................................................................................................7

Results.................................................................................................................... 10 Underwater Stereo Video.......................................................................................................................................10 Time in View .........................................................................................................................................................10 MaxN......................................................................................................................................................................14 Length.....................................................................................................................................................................18

Otolith chemistry.....................................................................................................................................................25 Individual element:Ca ratios ...............................................................................................................................25 Multi‐variate elemental signatures and maximum likelihood analyses .......................................................25

Discussion............................................................................................................. 31 Underwater Stereo Video.......................................................................................................................................31


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Otolith chemistry .................................................................................................................................................... 32 Vulnerability of juvenile King George whiting to climate change............................................................... 33 Future Research ....................................................................................................................................................... 34

Conclusions .......................................................................................................... 35 Improving the resilience and adaptation of King George whiting to climate change............................... 35 Informing fishery management arrangements of future King George whiting population trends........ 36

Acknowledgements ............................................................................................ 37

References ............................................................................................................. 38


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List of Tables Table 1. Depth ranges of shallow and deep sampling zones in each sampling area........................................ 8 Table 2. Results of analysis of variance and Tukey’s post‐hoc comparisons of individual element:Ca ratios

in otolith margins of post‐larval King George whiting sampled from 10 seagrass beds in Port Phillip Bay. .................................................................................................................................................................... 27

Table 3. Results of maximum likelihood simulation analysis of baseline (post–larval) otolith chemistry data (log Mn, Sr, log Ba) from 10 seagrass beds in Port Phillip Bay grouped according to north, south and Bellarine/Corio Bay regions. ................................................................................................................... 30

Table 4. Results of: a) maximum likelihood simulation analysis of baseline (post‐larval) otolith chemistry data (log Mn, Sr, log Ba) from 10 seagrass beds in Port Phillip Bay grouped according to north and south regions, and b) mixed sample composition analyses of 1 year old fish. ....................................... 30

List of Figures Figure 1. Map of Port Phillip Bay showing underwater stereo video sampling areas (blue circles) and

microchemistry sampling sites (black dots). .................................................................................................. 8 Figure 2. Average Time in View for King George whiting recorded by underwater stereo video at Eastern

Beach.................................................................................................................................................................. 11 Figure 3. Average Time in View for King George whiting recorded by underwater stereo video at Grand

Scenic. ................................................................................................................................................................ 11 Figure 4. Average Time in View for King George whiting recorded by underwater stereo video at Mud

Islands................................................................................................................................................................ 12 Figure 5. Average Time in View for King George whiting recorded by baited underwater stereo video at

Mud Islands. ..................................................................................................................................................... 12 Figure 6. Average Time in View for King George whiting recorded by underwater stereo video at Swan

Island. ................................................................................................................................................................ 13 Figure 7. Average MaxN for King George whiting recorded by underwater stereo video at Eastern Beach.

............................................................................................................................................................................ 15 Figure 8. Average MaxN for King George whiting recorded by underwater stereo video at Grand Scenic.

............................................................................................................................................................................ 15 Figure 9. Average MaxN for King George whiting recorded by underwater stereo video at Mud Islands.

............................................................................................................................................................................ 16 Figure 10. Average MaxN for King George whiting recorded by baited underwater stereo video at Mud

Islands................................................................................................................................................................ 16 Figure 11. Average MaxN for King George whiting recorded by underwater stereo video at Swan Island.

............................................................................................................................................................................ 17 Figure 12. Length frequency distribution for King George whiting recorded by underwater stereo video

at Grand Scenic in shallow seagrass habitat in spring................................................................................ 19 Figure 13. Length frequency distribution for King George whiting recorded by underwater stereo video

at Grand Scenic in shallow edge habitat in spring. ..................................................................................... 19 Figure 14. Length frequency distribution for King George whiting recorded by underwater stereo video

at Grand Scenic in shallow edge habitat in autumn. .................................................................................. 20 Figure 15. Length frequency distribution for King George whiting recorded by underwater stereo video

at Grand Scenic in shallow seagrass habitat in autumn. ............................................................................ 20 Figure 16. Length frequency distribution for King George whiting recorded by underwater stereo video

at Mud Islands in deep seagrass habitat in autumn. .................................................................................. 21


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Figure 17. Length frequency distribution for King George whiting recorded by underwater stereo video at Mud Islands in shallow edge habitat in autumn..................................................................................... 21

Figure 18. Length frequency distribution for King George whiting recorded by baited underwater stereo video at Mud Islands in shallow edge habitat in spring............................................................................. 22

Figure 19. Length frequency distribution for King George whiting recorded by baited underwater stereo video at Mud Islands in shallow edge habitat in autumn. ......................................................................... 22

Figure 20. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in shallow edge habitat in spring. ....................................................................................... 23

Figure 21. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in deep edge habitat in spring. ............................................................................................ 23

Figure 22. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in shallow edge habitat in autumn. .................................................................................... 24

Figure 23. Element:Ca ratios (± SE) of margins of post‐larval King George whiting otoliths sampled from 10 seagrass beds in Port Phillip Bay. ............................................................................................................. 26

Figure 24. Comparison of element:Ca ratios (±SE) in post‐larval otolith margins and the post‐larval otolith regions of 1‐year‐olds from the same cohort sampled at three seagrass beds in Port Phillip Bay........ 28

Figure 25. Canonical variate plot of multi‐element (log Mn:Ca, Sr:Ca, log Ba:Ca) chemistry of post‐larval King George whiting otoliths from three regions of Port Phillip Bay (refer to Figure 23). Ellipses represent 95% confidence intervals around the data. ................................................................................. 29

Figure 26. Canonical variate plot of multi‐element (log Mn:Ca, Sr:Ca, log Ba:Ca) chemistry of post‐larval King George whiting otoliths from north and south regions of Port Phillip Bay (refer to Figure 23).. 29

List of Plates Plate 1. Shallow seagrass habitat at Grand Scenic ................................................................................................. 9 Plate 2. Shallow edge habitat at Mud Islands ........................................................................................................ 9


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Introduction It is predicted that climate change will result in changes to ocean circulation patterns, water temperature and sea level (Poloczanska et al. 2007). Climate change is also predicted to cause changes in weather patterns across south eastern Australia, leading to reduced seasonal rainfall and infrequent high intensity rainfall events resulting in increased turbidity, more variable salinity levels and disturbance of seagrass.

These physical changes and effects on seagrass will have implications for the biomass and range of marine and estuarine fish and the ecosystems that support them. In some cases these changes will manifest in declines in abundance and distribution, and for other species increased abundance and distribution. These changes in abundance and distribution mean that management arrangements will need to be responsive to change.

An understanding of the likely implications to the key Victorian fisheries is necessary to adequately prepare for responding to these challenges and to better target management efforts.

Fisheries Victoria is undertaking a suite of projects under the Future Farming Strategy initiative ʺAdaptation of fisheries, aquaculture and fisheries management to climate changeʺ to prepare fisheries sectors and fisheries managers for change.

Under this initiative, the marine biophysical assessments are aimed at understanding the biophysical implications that may occur in the future due to climate change to better inform decision making. These assessments aim to determine the degree of exposure a species has to climate change to inform assessments on how vulnerable Victoria’s fishing and aquaculture sectors are to these changes.

This project builds on and is informed by a risk assessment undertaken in 2008/09 (Hutchinson et al. 2010) and a desktop review of literature in 2009/10 (Jenkins 2010). These previous projects assisted in establishing a prioritisation framework for focusing research regarding climate change implications for fish in Victoria.

King George whiting was specifically identified as one of the higher priority species for Victoria as it represents a key recreational and

commercial fish species in Victoria that relies on seagrass as a key component to complete its life cycle. The exact extent of this requirement is unknown and requires attention to enable the vulnerability of the species to climate change to be understood.

Climate change predictions for Victoria Temperature Air temperature Air temperature is often strongly related to water temperature in estuaries, bays and inlets. CSIRO climate modelling suggests that under medium emissions the best estimate is for a temperature increase of 0.6–1 oC by 2030, rising to 1.5–2 oC by 2070, with the greatest increase occurring in summer; 2–2.5 oC by 2070 (Anon. 2007). Under high emissions an increase of 2.5–3 oC could occur in the eastern half of Victoria by 2070 (Anon. 2007).

Sea surface temperature Sea surface temperature (SST) off the coast of Victoria under medium emissions is predicted to increase by 0.3–1 oC by 2030, rising to 0.6–2 oC by 2070, with rises greatest in the eastern part of the State (Anon. 2007). Under a high emissions scenario the SST increase in the far east of the State could be 2–2.5 oC (Anon. 2007).

Rainfall The best estimate of rainfall change based on climate modelling under a medium emissions scenario is a deficit of 2–5% by 2030, increasing to a deficit of 5–10% by 2070 (Anon. 2007). This change is highly seasonal, with a spring deficit of 20–30% compared to an autumn deficit of 2–5% by 2070 (Anon. 2007). As well as a reduction in overall rainfall, rain will tend to occur in more intense events, interspersed with an increasing proportion of dry days, signifying more extreme weather fluctuations (Anon. 2007). In terms of rainfall effects on runoff and salinity, reduced runoff and increasing salinity due to decreasing rainfall will be exacerbated by increased solar radiation and decreased humidity leading to increased evaporation rates (Anon. 2007).

Winds While wind speed is not expected to change on a seasonal basis, by 2070, wind speed under a


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medium emissions scenario is expected to decrease by 5–10% in central Victoria in autumn and increase by 2–5% (5–10% off the east coast) in winter (Anon. 2007).

The Victorian climate is dominated by westerly winds associated with the southern annular mode (SAM). In recent decades there has been a poleward shift in the circumpolar westerly winds associated with an upward trend in SAM. This trend is expected to continue under climate change (Cai et al. 2005; Ridgway and Hill 2009). This will lead to a weakening trend for westerly wind strengths over Victoria (Poloczanska et al. 2007).

Currents The East Australian Current (EAC) has strengthened over recent decades so that warmer, saltier water is now found 350 km further south compared to 60 years ago (Ridgway and Hill 2009). It is likely that the EAC will strengthen by a further 20% by 2100 under future climate change (Ridgway and Hill 2009). The main factor driving these changes is the southward migration of the high latitude westerly wind belt mentioned previously (Poloczanska et al. 2007).

The Leeuwin Current (LC) has shown a weakening trend in recent decades due to more frequent El Nino events (Feng et al. 2009). Predictions under future climate change are for no significant change to the LC volume flux by 2030, and a slight further weakening by 2100 (Feng et al. 2009). There is low confidence in these predictions (Feng et al. 2009).

Seawater Chemistry Carbon dioxide dissolving in the sea has lowered pH by 0.1 units since 1750, representing a 30% increase in hydrogen ion (acid) concentration (Havenhand et al. 2009). It is expected that seawater pH will decrease by a further 0.2–0.3 units by 2100 (Havenhand et al. 2009). Increasing seawater acidity will affect organisms with calcium carbonate structures, and there is already evidence of effects on corals and Southern Ocean zooplankton (Havenhand et al. 2009). Conversely, increasing concentration of CO2 in seawater may benefit growth of marine plants such as seagrasses (Connolly 2009).

Sea level Global sea levels have risen by 20 cm over the period 1870 to 2004 (Church et al. 2009). Sea levels will continue to rise by 5–15 cm by 2030 and 18–82 cm by 2100 (Church et al. 2009). The

greatest effect of sea level rise will occur during extreme weather events such as storms with associated storm surges (Church et al. 2009). Such events may become more frequent under climate change (Poloczanska et al. 2007).

Solar radiation Ultraviolet radiation associated with solar radiation is known to have deleterious effects on marine life (Poloczanska et al. 2007). The best estimate of solar radiation change based on climate modelling under a medium emissions scenario is little change by 2030, but a 1–2% increase by 2070, with a “hotspot” of 2–5 % increase over central Victoria including Port Phillip and Western Port (Anon. 2007). Most of this increase will occur in the winter and spring (Anon. 2007).

King George whiting biology King George whiting (Sillaginodes punctatus) are native to Australian coastal waters and inhabit near‐shore shallow waters off the continental shelf as well as bays and inlets from Port Jackson (NSW), to northern Tasmania and Jurien Bay in Western Australia (Gomon et al. 2008). Juvenile fish are restricted to bays and inlets while adults are found in open coastal waters (Kailola et al. 1993).

King George whiting have a life expectancy of 17 years and are thought to reach sexual maturity as early as three years of age and at a length of 32 cm (Jones et al. 1990; Fowler et al. 2000). The size and age at maturity can vary with locality (Fowler et al. 2000). Localities where spawning occurred had the broadest age and size distributions and were in deep water that experienced medium to high wave energy (Fowler et al. 2000).

King George whiting found in Victorian waters spawn between May and July (Jenkins and May 1994) in coastal waters outside bays or inlets (Jenkins et al. 2000). Adults in spawning condition or life history stages less than 100 days old are rarely found in near‐shore central Victorian waters, which suggest that there is little or no spawning activity in the vicinity (Hamer et al. 2004). Recent research suggests that spawning may take place in coastal waters to the west of Victoria’s major bays and inlets, and that some of the Victorian King George whiting population may be derived from spawning in South Australian waters (Jenkins et al. 2000; Hamer et al. 2004). Until the spawning stock(s) for Victorian King George whiting is identified, it will not be


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possible to determine the potential role of varying stock size on recruitment variation.

King George whiting eggs are buoyant, and eggs hatch after a few days at a size of 2 –3 mm (Bruce 1995). Larvae are then transported by water currents and may drift for 3 to 5 months before entering sheltered marine habitats in Victorian bays and inlets in spring when they reach around 15–20 mm length (Jenkins and May 1994). These larvae then settle in or near shallow‐water seagrass beds, mainly in Port Phillip Bay and Western Port (Jenkins et al. 2000).

In the case of Port Phillip Bay, ingress of larvae occurs when strong westerly winds and low barometric pressure cause the sea level on the coast and in the Bay to rise (Jenkins et al. 1997a). Larvae are concentrated in the surface layers during daylight but are distributed throughout the water column at night (Jenkins et al. 1998b). Research shows that the seagrass beds where King George whiting larvae settle most often are those in the areas where currents deliver larvae, rather than being related to the “quality” of the seagrass (Jenkins et al. 1998a). The suitability of seagrass beds is further influenced by wave exposure, with exposed beds carrying fewer post‐larvae than protected ones (Jenkins et al. 1997a). Seagrass is probably crucial to newly‐settled larvae through the provision of food (Jenkins and Hamer 2001) or protection from predators (Hindell et al. 2000b; a).

Although settlement is primarily associated with shallow seagrass and reef‐algal beds (Jenkins and Wheatley 1998), at some sites, newly‐settled individuals have been found in bare unvegetated mud patches within seagrass beds (Jenkins et al. 1997b; Jenkins and Hamer 2001). The importance of a particular habitat may depend on the amount of food available (Jenkins and Hamer 2001) as well as the local current patterns that deliver the larvae to the habitat (Jenkins et al. 1998a).

King George whiting show a change in habitat preference with growth. Post‐larvae initially settle near seagrass and reef‐algae at depths between 0–2 m (Jenkins et al. 1996; Jenkins and Wheatley 1998). From five to six months, most fish are found on unvegetated sand amongst vegetated habitats (Jenkins and Wheatley 1998). Older juveniles may venture into deeper water, where they are more common in areas of patchy seagrass and algae (G. Jenkins personal observation). Quantitative information on habitat use by older juveniles, however, is lacking.

After settlement, juvenile development occurs over the next 3 to 4 years before the onset of sexual maturity. The mature fish then migrate offshore to join other adult stock in oceanic waters (Jones et al. 1990; Hamer et al. 2004). The rate of growth varies depending on the water temperature, with very little growth occurring during the winter and rapid growth from December to March (Coutin 2000).

This Report In Victoria, we assume that King George Whiting rely on seagrass as a critical habitat. We also understand that climate change will cause changes that are likely to affect seagrass (Connolly 2009). More storm events will lead to pulses of turbidity that will reduce light for seagrass growth, as well as directly affecting seagrass through wave disturbance (Connolly 2009). Increased sea level will also mean less light for seagrass growth. Seagrass may be able to migrate shoreward to compensate, however this cannot occur where the shoreline has been ‘hardened’ (i.e. through construction of sea‐walls, breakwaters etc) (Connolly 2009). An overall reduction in freshwater flows with climate change may lead to a limitation on nutrients reaching seagrass, leading to declines (Bulthuis et al. 1992).

Although some aspects of the life history of King George whiting are known, information on the relationship between juvenile whiting in Victorian bays and seagrass habitats is limited to very young post‐settlement stages, reducing our ability to predict future population trends of King George whiting under climate change scenarios. Our greatest opportunity to improve our understanding of King George whiting vulnerability to climate change is to determine the linkages between juvenile King George whiting and seagrass habitats.

This project focuses on understanding the key characteristics of seagrass regions within Port Phillip Bay that are important to the production of juvenile King George whiting. This includes the depth of seagrass preferred by different age‐classes of juveniles and the areas of seagrass in Port Phillip Bay that are most important for producing juvenile King George whiting. The work was conducted in Port Phillip Bay; however the fundamental principles learnt would be transferable to other Victorian bays and inlets. This knowledge will enable us to predict the consequences of seagrass loss to King George whiting populations under climate change. The


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results will also allow for adaptation in terms of focussing efforts on maintaining seagrass habitat in the critical areas, depths etc that are crucial to King George whiting populations. This would mean management is focussed on limiting disturbance through human activities that would exacerbate the effects of climate change in key areas. Guidance on these measures will help enhance the resilience of the King George whiting in Port Phillip Bay, and more broadly across Victoria, under climate change.

Objectives • To inform decision makers on the

vulnerability of King George whiting to climate change in Port Phillip Bay

• To inform opportunities for improving the resilience and adaptation of King George whiting and for informing fishery management arrangements of future population trends.


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Project Design and Methods

Underwater Stereo Video Study sites Sampling was done in four areas of Port Phillip Bay: Eastern Beach, Grand Scenic, Mud Islands and Swan Island (Fig. 1); between October 2010 and March 2011. Habitats sampled were the sub‐tidal seagrass, Zostera nigricaulis (“seagrass habitat”) (Plate 1) and unvegetated sand/mud at the edge of seagrass (“edge habitat”) (Plate 2). In each area, habitats were sampled in two depth zones: “shallow” (0.4 to 1.1 m) and deep (2.2 to 7.7 m) (Table 1).

Remote underwater video Fish were sampled using remotely deployed stereo video systems (SeaGIS Pty. Ltd., Australia). Stereo systems consisted of a frame with two Canon HV20 cameras with wide angle lenses (7 mm focal length) in housings angled inward at 8 degrees, on bars 65 cm apart and 40 cm above the sea floor, and a diode arm for synchronisation of cameras. Video was unbaited to prevent attraction of fish from nearby positions. Disturbance effects that may affect fish behaviour were restricted by only beginning video analysis after 1 min. Videos were retrieved 1 h after deployment. A trial of baited video was also conducted at Mud Islands. A bait bag was suspended on a cane rod approximately 1.5 m in front of the cameras. Bait consisted of smashed mussels and squid pieces.

Experimental design Each area was sampled in spring and autumn. An area was sampled over two days, and three frame drops were allocated randomly to each habitat by depth combination (six drops per day). Thus, a total of 12 h of video footage was taken by the stereo cameras over two days in each area. The same procedure was used for baited video at Mud Islands in December 2010 and for shallow habitat only in May 2011.

Video analysis Video was assessed using two different methods, MaxN and time in view (TiV) (Smith et al. 2011). MaxN was the greatest number of a given fish species in a single video frame from the hour long video (an index of abundance), while TiV was recorded as the total time in seconds that at least one King George whiting was in view of the left camera. If a fish was lost from view (i.e. hidden in seagrass or swam out of the field of view) and did not reappear within 10 sec, it was deemed to have left the sampling area (Smith et al. 2011). The computer software packages EVENTMEASURE and PHOTOMEASURE were used to get species MaxN and TiV data and estimate fish lengths (SeaGIS Pty. Ltd., Australia). Orientation and location within the camera field of view could affect the measurement of fish; therefore, only the lengths of fish that were measured with less than 10% error were recorded. Lengths were measured for fish from a single video frame, with consecutive measurements at least 5 minutes apart to avoid the possibility of measuring the same fish more than once.

Data analysis Graphs were plotted of MaxN and TiV of King George whiting in terms of average and standard error of the three drops in each habitat by depth combination for each area and season. Kolmogorov‐Smirnov two‐sample test was used to assess length frequency data and determine any difference amongst areas, seasons and depth by habitat combinations.

Otolith chemistry Sampling of post‐larval King George whiting

To develop area specific ‘baseline’ otolith chemistry signatures, recently settled (post‐larval, approximately 20–50 mm length) King George whiting were sampled from seagrass habitats at 10 locations around Port Phillip Bay (Swan Bay, Mud Islands, Blairgowrie, Rosebud, Ricketts Point, Altona, Kirks Point, Corio Bay, Grand Scenic, Grassy Point , Fig. 1). Samples were collected in 1–1.5 m water depth from October to December 2010 using a 10 m x 2 m seine with a 2 mm mesh and 10 m hauling ropes. Samples were obtained from multiple dates and net hauls at each site. The King George whiting


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were extracted from the net, rinsed in distilled water and then frozen.

We restricted analyses of post‐larval otolith chemistry to fish ≥ 25 mm standard length, SL (tip of snout to tip of caudle peduncle). This minimum size was chosen due to the time lag between when a larva enters Port Phillip Bay and settles into a seagrass area, and when the otolith composition becomes representative of the settlement location. Previous studies indicate that a 25 mm SL post‐larval King George whiting is likely to be between 50 and 60 days post‐entry to Port Phillip Bay (Jenkins and May 1994; Hamer and Jenkins 1996). Based on daily otolith increment widths for post‐larval King George whiting presented in Jenkins and May (1994) an ablation diameter of 80 μm would be equivalent to 25‐35 days of otolith growth post‐entry to Port Phillip Bay. Sampling otoliths from post‐larvae < 25 mm SL would have risked measuring a chemical composition that was more indicative of the planktonic/oceanic than the post‐settlement environment in Port Phillip Bay.

Sampling of 1 year old King George whiting

In November–December 2011 samples of 1 year old King George whiting that had survived from the previous year’s settlement (i.e. the same cohort as sampled for the baseline otolith chemistry signatures) were collected from seagrass habitats in Port Phillip Bay. Sampling was conducted using a combination of the seine net used previously for post‐larval sampling and a similar net of 30 m length. Despite efforts to sample 1 year olds at 9 sites around Port Phillip Bay (Swan Bay, Mud Islands, Blairgowrie, Rosebud, Ricketts Point, Altona, Kirks Point, Corio Bay, Grassy Point, Fig. 1), they could only be captured in sufficient numbers at Corio Bay, Grassy Point and Swan Bay. A total of 70 x 1 year old whiting (Corio Bay 27, Grassy Point 16, Swan Bay 27) were processed for chemical analysis.

Otolith preparation and chemical analysis

Thawed King George whiting samples were measured for SL to the nearest 0.5 mm under a stereo microscope with an ocular micrometer. Otoliths were then extracted with fine stainless steel needles, rinsed in Milli Q water, air dried and stored in plastic vials. Otoliths were embedded in epoxy resin (AKA‐Resin and AKA‐Cure, Pacific Laboratory Supplies), and polished with lapping film (Ultralap 30, 12 μm) in the transverse plane to expose the core region. Polished otoliths were triple rinsed in Milli‐Q water, air dried, mounted onto petrographic

glass slides and then sonicated in Milli‐Q water for three minutes. Sonicated samples were again liberally rinsed (x3) in Milli‐Q water and stored in sealed plastic containers for analysis.

Trace element analyses were undertaken using a New Wave Research UP‐213 Nd:YAG ultraviolet laser microprobe operated in Q‐switched mode coupled to a ThermoFinnigan Element 2 high resolution inductively coupled plasma mass spectrometer (HR‐ICP‐MS) situated at Fisheries Research Branch, Queenscliff. Data were collected for the following isotopes: 25Mg, 55Mn, 65Cu, 66Zn, 88Sr, 85Rb, 138Ba, and 208Pb, along with 43Ca which was used as the internal standard. Calibration was achieved with the National Institute of Standards (NIST) 612 glass wafer using methods described in (Lahaye et al. 1997; Hamer et al. 2003). Resolved concentrations were expressed as ratios to calcium for graphical presentations and statistical analyses. A laser spot diameter of 80 μm, repetition rate of 6 Hz and fluence of ~10 J cm‐2, was used. Otolith surfaces were pre‐ablated prior to actual data acquisition to remove any residual surface contamination from cutting and polishing. Each laser ablation spot sample consisted of 15 blank scans of the carrier gases, followed by an ablation period of 25 scans, of which the first 5 scans were excluded from data integration to allow for signal stabilisation. The sample data was blank subtracted before it was integrated to provide the actual counts used for the calculation of elemental concentrations. Detection limits (LOD) were calculated for each sample based on three standard deviations of blank gas samples and adjusted for ablation yield (Lahaye et al. 1997). The LOD values were as follows (μmol/mol Ca): Mg=1.691; Mn=0.404; Cu=0.116; Zn=0.117; Rb=0.105; Sr=1.817; Ba=0.0849; Pb=0.065.

For the post‐larval otoliths (i.e. baseline chemical signatures), two ablations were made adjacent to the margins of each otolith, one ablation at the dorsal tip and the other sightly ventral of the sulcus. Otolith margins were focused on for chemical analysis of post‐larval otoliths as it was expected that the chemistry near the otolith margin will reflect the general area where a fish is collected and will therefore provide representative ‘baseline’ or location specific chemical signatures.

For the age 1 year otolith samples the post‐larval region within the otolith sections of these older fish was similarly targeted by sampling within specified windows at set distances both ventral and dorsal of the core region. This sampling


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window was determined from measurements of the distance from core to the ablation centres of 95 post‐larval otoliths.

Data analysis Data were initially screened for extreme outliers (defined as data that were >3 interquartile ranges either above the 75th percentile or below the 25th percentile (Wilkinson et al. 1996)) and number of samples below the limits of detection. Rb, Pb and Cu were excluded from further analyses due to >40% of data falling below the LOD. For Mg, Mn, Sr, and Ba all data were above LOD, and for Zn approximately 98% of data were above LOD. Prior to further analysis the data were averaged across both sample points on each otolith.

Statistical analysis of post‐larval and 1 year old otoliths involved univariate analysis of variance followed by post‐hoc Tukey’s pairwise comparison tests to determine significant differences in individual element:Ca ratios between sites. Only element:Ca ratios that varied significantly (P < 0.05) among sites for the post larvae were used to further develop the otolith chemistry baseline signatures.

Discrimination of otolith chemistry signatures among sampling sites was assessed using canonical variate plots and quadratic discriminant function analysis with a cross validation leave‐one‐out jackknife classification procedure. These analyses, however, revealed significant overlap of samples among all sites and generally poor discriminatory power at the site level (average correct classification of 43%) and are not presented in detail herein. To remain consistent with a regional approach to our assessment of potential climate change impacts, we chose to group sites into two logical regional groupings for constructing baseline datasets. The first grouping involved 3 regions: South (Rosebud, Blairgowrie, Mud Islands), Bellarine/Corio Bay (Swan Bay, Grassy Point, Grand Scenic, Eastern Beach,) and North (Kirk Point, Altona, Ricketts Point). The second broader baseline grouping involved a north‐south separation of seagrass areas; North (Kirks Point, Altona, Ricketts Point), and South (Grand Scenic, Corio Bay, Grassy Point, Swan Bay, Mud Islands, Blairgowrie, Rosebud).

Using the above groups we conducted a maximum likelihood simulation analysis (Millar 1987; 1990a) of the post‐larval otolith chemistry data to assess the degree and precision of

discrimination between the baseline groups. Maximum likelihood estimation (MLA) (Millar 1987; 1990a) was then used to determine the contributions of the different baseline groups (i.e. sources) to the samples of 1 year old fish. The HISEA programme described in (Millar 1990b) (http://www.stat.auckland.ac.nz/~millar/) was used to conduct the MLA analyses. Data for all elements were transformed to ln (x + 1) to meet univariate normality (Millar 1990a). For each cohort the simulation mode with 1000 simulations was initially used to estimate the variability of the estimator (i.e. baseline data). Bootstrapping (1000 re‐samplings of sample sizes the same as the original sample sizes) (Quinn and Keough 2002) of the baseline (post‐larvae) and mixed sample (1 year old fish) data was used to estimate the mean and standard deviation of the proportions of 1 year old fish originating from the different baseline/source areas.


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Figure 1. Map of Port Phillip Bay showing underwater stereo video sampling areas (blue circles) and microchemistry sampling sites (black dots).

Table 1. Depth ranges of shallow and deep sampling zones in each sampling area

Sampling Area “Shallow” depth range (m) “Deep” depth range (m) Eastern Beach 0.7 – 1.0 3.4 ‐ 6.1 Grand Scenic 0.8 – 1.1 3.2 – 5.6 Mud Islands 0.6 – 1.0 4.1 – 7.7 Swan Island 0.4 – 1.0 2.1 – 2.8

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Plate 1. Shallow seagrass habitat at Grand Scenic

Plate 2. Shallow edge habitat at Mud Islands


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Results

Underwater Stereo Video Time in View At Eastern Beach, King George whiting (KGW) were in view in shallow edge habitat for an average of 2–3 min in both spring and autumn (Fig. 2). KGW were also in view for an average of less than one minute in deep seagrass in spring (Fig. 2).

At Grand Scenic, KGW were in view in shallow edge habitat for an average of 35 to 40 minutes in both spring and autumn (Fig. 3). KGW were also in view for an average of a few minutes in shallow seagrass in spring and for less than a minute in autumn (Fig. 3).

At Mud Islands, KGW were in view in shallow edge habitat for an average of approximately 12 minutes in autumn only (Fig. 4).

KGW were also in view for an average of a few minutes in deep seagrass and deep edge habitat in autumn only (Fig. 4). For baited video at Mud Islands, time in view of KGW in shallow edge habitat increased from spring to autumn (Fig. 5). However, the TiV in this habitat in autumn was less than half that recorded with the unbaited video in the same habitat (Figs 4, 5).

At Swan Bay, KGW were in view in shallow edge habitat for an average of approximately 17 minutes in spring and 6 minutes in autumn (Fig. 6). KGW were also in view in deep edge habitat for an average of a few minutes in spring and an average of less than a minute in autumn (Fig. 6).


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Figure 2. Average Time in View for King George whiting recorded by underwater stereo video at Eastern Beach.

Figure 3. Average Time in View for King George whiting recorded by underwater stereo video at Grand Scenic.

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Figure 4. Average Time in View for King George whiting recorded by underwater stereo video at Mud Islands.

Figure 5. Average Time in View for King George whiting recorded by baited underwater stereo video at Mud Islands.

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Figure 6. Average Time in View for King George whiting recorded by underwater stereo video at Swan Island.

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MaxN At Eastern Beach, KGW in shallow edge habitat had a similar average MaxN of approximately two in spring and autumn (Fig. 7). KGW had an average MaxN in deep seagrass in spring that was lower than that for shallow edge habitat (Fig. 7).

At Grand Scenic, KGW in shallow edge habitat had a similar average MaxN of approximately 10 in both spring and autumn (Fig. 8). KGW also had a similar average MaxN in shallow seagrass in spring (due to a MaxN of 29 in one video replicate), but MaxN in this habitat was lower in autumn (Fig. 8).

At Mud Islands in autumn, MaxN was highest in shallow edge habitat, intermediate in deep seagrass and lowest in deep edge habitat (Fig. 9).

For baited video at Mud Islands, KGW in shallow edge habitat had an average MaxN that approximately doubled from spring to autumn (Fig. 10). Average MaxN of KGW for shallow edge habitat in autumn was similar for baited and unbaited video (Figs 9, 10).

At Swan Island, KGW in shallow edge habitat had an average MaxN of approximately six in spring and three in autumn (Fig. 11). KGW had a MaxN in deep edge habitat that was about half of the level in shallow edge habitat in both spring and autumn (Fig. 11).


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Figure 7. Average MaxN for King George whiting recorded by underwater stereo video at Eastern Beach.

Figure 8. Average MaxN for King George whiting recorded by underwater stereo video at Grand Scenic.

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Figure 9. Average MaxN for King George whiting recorded by underwater stereo video at Mud Islands.

Figure 10. Average MaxN for King George whiting recorded by baited underwater stereo video at Mud Islands.

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Figure 11. Average MaxN for King George whiting recorded by underwater stereo video at Swan Island.

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Length At Eastern Beach, one individual of 238 mm was measured in deep seagrass habitat.

KGW length at Grand Scenic ranged from 110 to 160 mm in shallow seagrass in spring (Fig. 12). A similar distribution occurred in shallow edge habitat with the addition of some smaller individuals between 80 and 100 mm (Fig. 13). The difference in length frequency distributions between the two shallow habitats in spring was not significant (KS test, D=0.4, P=0.16). In autumn, KGW on shallow edge habitat ranged from 60 to 120 mm together with a larger group ranging from 150 to 200 mm (Fig. 14). Only two individuals were measured in shallow seagrass in autumn (Fig. 15), with one falling into each of the length groups identified for shallow edge habitat (Fig. 14).

At Mud Islands in autumn, KGW in deep seagrass ranged from 210 to 310 mm (Fig. 16), while the size distribution in shallow edge habitat was similar but included smaller individuals between 170 and 200 mm in length (Fig. 17). The difference in length frequency distributions between the deep seagrass and the shallow edge shallow habitats in autumn was significant (KS test, D=0.707, P=0.005). For baited underwater stereo video at Mud Islands, the length range in shallow edge habitat in spring was 140 to 220 mm (Fig. 18), while for the same habitat in autumn the range was 210 to 280 mm (Fig. 19).

At Swan Island in spring, KGW in shallow edge habitat were smaller than in deep edge habitat, ranging from 90 to 150 mm in length (Fig. 20), compared with 150 to 240 mm in length in deep habitat (Fig. 21). This difference in length distributions was highly significant (KS test, D=1, P<0.001) with no overlap in length ranges (Figs 20, 21). The length range of KGW on shallow edge habitat in autumn was 150 to 220 mm (Fig. 22).

Length distributions amongst sites were compared for KGW on shallow edge habitat in autumn. KGW at Mud Islands (Fig. 17) were significantly larger than at Swan Island (Fig. 22) (KS test, D=0.6, P=0.003), that in turn were significantly larger than at Grand Scenic (Fig. 14) (KS test, D=0.906, P<0.001).


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Figure 12. Length frequency distribution for King George whiting recorded by underwater stereo video at Grand Scenic in shallow seagrass habitat in spring.

Figure 13. Length frequency distribution for King George whiting recorded by underwater stereo video at Grand Scenic in shallow edge habitat in spring.

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Figure 14. Length frequency distribution for King George whiting recorded by underwater stereo video at Grand Scenic in shallow edge habitat in autumn.

Figure 15. Length frequency distribution for King George whiting recorded by underwater stereo video at Grand Scenic in shallow seagrass habitat in autumn.

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Figure 16. Length frequency distribution for King George whiting recorded by underwater stereo video at Mud Islands in deep seagrass habitat in autumn.

Figure 17. Length frequency distribution for King George whiting recorded by underwater stereo video at Mud Islands in shallow edge habitat in autumn.

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Figure 18. Length frequency distribution for King George whiting recorded by baited underwater stereo video at Mud Islands in shallow edge habitat in spring.

Figure 19. Length frequency distribution for King George whiting recorded by baited underwater stereo video at Mud Islands in shallow edge habitat in autumn.

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Figure 20. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in shallow edge habitat in spring.

Figure 21. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in deep edge habitat in spring.

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Figure 22. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in shallow edge habitat in autumn.

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Otolith chemistry

Individual element:Ca ratios Post‐larval otoliths

Variation in the element:Ca ratios of post‐larval otolith margins was significant among seagrass areas in Port Phillip Bay for Ba:Ca, Sr:Ca and Mn:Ca, but not for Mg:Ca and Zn:Ca (Fig. 23, Table 2). Ba:Ca was highest at Rosebud and Swan Bay and lowest at Grassy Point and Ricketts Point (Fig. 23). Mn:Ca was highest at Kirk Point and Altona and lowest at Swan Bay and Blairgowrie (Fig. 23). Sr:Ca was highest at Swan Bay, Grassy Point and Rosebud, and generally similar across the other sites (Fig. 23). There were no clear regional (i.e. north, south, Bellarine/Corio) trends in variation of individual otolith element:Ca ratios, with most of the variation occurring at the smaller scale, i.e. between adjacent sites (Fig. 23).

1‐year‐old otoliths

Samples of one year old fish could only be obtained from three areas in southern Port Phillip Bay (Swan Bay, Corio Bay and Grassy Point). Variation of Mn:Ca, Ba:Ca, and Sr:Ca in the post‐larval regions of the 1 year old otoliths was significant among the three sites (ANOVA, Mn:Ca, Sr:Ca p<0.001, Ba:Ca p<0.05). Further, for these element:Ca ratios, the patterns of variation among sites were similar to those observed in the post‐larval otolith margins sampled from these sites 1 year prior (Fig. 24). Similar to the post‐larval stages, variation among sites was not significant for Zn:Ca (ANOVA, p>0.1), but was significant for Mg:Ca (ANOVA, p<0.05). Mg:Ca ratios measured in the post‐larval otoliths were generally higher than in the post‐larval regions of the 1 year old otoliths (Fig. 24), possibly indicative that sampling positions in the 1 year old otoliths were not perfectly matched with the post‐larval sizes sampled the previous year (e.g. Hamer et al. 2003).

Multi‐variate elemental signatures and maximum likelihood analyses Canonical variate plots (Mn:Ca, Sr:Ca, Ba:Ca) of the regional baseline groupings (Grouping 1: South = Rosebud, Blairgowrie, Mud Islands;

Bellarine/Corio Bay = Swan Bay, Grassy Point, Grand Scenic, Eastern Beach; North = Kirks Point, Altona, Ricketts Point. Grouping 2: North = Kirks Point, Altona, Ricketts Point; South = Grand Scenic, Corio Bay, Grassy Point, Swan Bay, Mud Islands, Blairgowrie, Rosebud) indicated for grouping 1 that there was a significant overlap of otolith multi‐element chemistry among the sampling regions, particularly for the south and Bellarine/Corio regions (Fig. 25). For grouping 2, however, the overlap of multi‐element otolith chemistry between the north and south regions was less pronounced (Fig. 26).

Maximum likelihood simulations of the baseline multi‐element otolith chemistry data for grouping 1 indicated that the estimated contribution from simulations was the same as the actual contribution for the north region with a reasonable precision (SD = 11%) (Table 3). However, for the south and Bellarine/Corio regions, the estimated contributions from simulations were 6% lower and higher respectively for these two regions, and precision was poor (SD = 15 and 21% respectively) (Table 3).

Maximum likelihood simulations of the baseline multi‐element otolith chemistry data for grouping 2 (north v south) indicated that the estimated contributions from simulations were close to the actual contributions for the north and south regions (estimated 2% higher and lower than actual for north and south regions respectively) with a reasonable precision (SD = 9% for both regions) (Table 4).

Based on the above results we conducted the maximum likelihood mixed sample composition analyses of 1 year old otoliths using baseline grouping 2 only (north and south) to achieve the most accurate and precise estimates. The mixed sample bootstrap analysis indicated with a very high precision (< 1% SD) that the 1 year old samples from Corio Bay, Grassy Point and Swan Bay were 100% derived from post‐larvae that had settled in seagrass beds of southern Port Phillip Bay (Table 4).


26

Figure 23. Element:Ca ratios (± SE) of margins of post‐larval King George whiting otoliths sampled from 10 seagrass beds in Port Phillip Bay.

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nd S

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Bla

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South




27

Table 2. Results of analysis of variance and Tukey’s post‐hoc comparisons of individual element:Ca ratios in otolith margins of post‐larval King George whiting sampled from 10 seagrass beds in Port Phillip Bay.

KP = Kirk Point, SB = Swan bay, CB = Corio Bay, RP = Ricketts Point, A = Altona, B = Blairgowrie, RB = Rosebud

Independent variable = site (df = 9) Dependent Variables: F‐ratio MS p Tukey’s significant differences

between sites (* p < 0.05, ** p< 0.01, *** p< 0.001)

Magnesium:Ca 1.551 873.351 0.136 NS Manganese:Ca (log) 4.973 0.719 <0.001 KP > SB**, RB*, B *

A > SB***,RB***,B** Zinc:Ca (log) 1.471 0.107 0.164 NS Strontium:Ca 6.254 204367.914 <0.001 SB > CB***,RP***,A*

GP > CB***,RP** RB > CB***, RP**

Barium:Ca (log) 8.787 0.402 <0.001 SB > RP***,GP***,A* RB > RP***,GP***,A***,B**,CB* CB > RP*


28

Figure 24. Comparison of element:Ca ratios (±SE) in post‐larval otolith margins and the post‐larval otolith regions of 1‐year‐olds from the same cohort sampled at three seagrass beds in Port Phillip Bay.

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29

Figure 25. Canonical variate plot of multi‐element (log Mn:Ca, Sr:Ca, log Ba:Ca) chemistry of post‐larval King George whiting otoliths from three regions of Port Phillip Bay (refer to Figure 23). Ellipses represent 95% confidence intervals around the data.

Figure 26. Canonical variate plot of multi‐element (log Mn:Ca, Sr:Ca, log Ba:Ca) chemistry of post‐larval King George whiting otoliths from north and south regions of Port Phillip Bay (refer to Figure 23).

Canonical variate 1

South North

Bellarine/Corio Bay -3 -1 1 3 5

-3

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Mn:Ca Ba:Ca Sr:Ca

-3 -2 -1 0 1 2Canonical variate 1

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Ba:Ca Sr:Ca


30

Table 3. Results of maximum likelihood simulation analysis of baseline (post–larval) otolith chemistry data (log Mn, Sr, log Ba) from 10 seagrass beds in Port Phillip Bay grouped according to north, south and Bellarine/Corio Bay regions.

Table 4. Results of: a) maximum likelihood simulation analysis of baseline (post‐larval) otolith chemistry data (log Mn, Sr, log Ba) from 10 seagrass beds in Port Phillip Bay grouped according to north and south regions, and b) mixed sample composition analyses of 1 year old fish.

Baseline (0‐age post larvae) group

Actual contribution to simulated mixture

(%)

MLA estimated contribution to simulated mixture (%)

Standard deviation of estimation (%)

North (n=47) (Altona, Kirk Point, Ricketts Point)

31

31

11

South (n=45) (Blairgowrie, Mud Islands, Rosebud)

30

24

15

Bellarine/Corio bay (n=59) (Corio Bay, Grand Scenic, Grassy Point, Swan Bay)

39 45 21

a) Simulation of baselines

b) Composition (origin) of 1 year olds (Corio Bay n=27; Grassy Point n=16; Swan

Bay n=26) Baseline (0‐age post‐larvae) group

Actual contribution to

simulated mixture (%)

MLA estimated

contribution to simulated mixture (%)

Standard deviation

of estimation

(%)

MLA composition of 1‐year olds (%)

Standard deviation of estimation (%)

North (n=47) (Altona, Kirk Point, Ricketts Point)

31

33

9 0

<1

South (n=104) (Blairgowrie, Corio Bay, Grand Scenic, Grassy Point, Mud Islands, Rosebud, Sway Bay)

69

67

9

100

<1


31

Discussion

Underwater Stereo Video Stereo video analysis showed distinct patterns in spatial, temporal and depth distribution as well as habitat use in KGW. Distinct patterns were also observed in size distributions between sites and depths.

The most common habitat juvenile KGW were observed in was shallow seagrass edge habitat. This is consistent with previous studies on young juvenile KGW using fine mesh seine nets in Port Phillip Bay. Post‐larvae (approx 20 mm in length) settled in shallow (<1 m deep) seagrass habitat in the spring (Jenkins and Black 1994; Jenkins and Wheatley 1998; Hutchinson et al. 2011), however, after 4–5 months there was a shift to unvegetated habitat within the vicinity of seagrass or reef‐algae (Jenkins and Wheatley 1998). In some areas such as Swan Bay, small post‐larvae are found on unvegetated mud habitat when nearby seagrass is very dense (Jenkins et al. 1997b; Jenkins and Hamer 2001). In general, the dependence of KGW on seagrass appears mainly related to food, either through feeding directly on epifauna within seagrass beds or taking advantage of elevated food levels on unvegetated habitat that is enriched with seagrass detritus from nearby beds (Jenkins and Hamer 2001). Robertson (1977) also found a shift in KGW from seagrass habitat to mudflat after 4–5 months post‐settlement in Western Port. This corresponded with a shift in the diet to include benthic infauna such as polychaete worms and ghost shrimp (Robertson 1977). Studies using stable isotopes have shown that KGW have a very strong dependence on seagrass through the food chain, even though this could be an indirect relationship where seagrass detritus provides the plant food base in unvegetated habitat (Longmore et al. 2002; Hindell et al. 2004).

Our study shows that shallow seagrass edge habitat continues to be important for juvenile KGW over the first few years of growth. The smallest KGW recorded in this study were from Grand Scenic in autumn, and at a size of 60–120 mm would have been approximately 6 months old. Jenkins and Wheatley (1998) found a high abundance of a similar size range of KGW in autumn from a nearby site at Clifton Springs, suggesting this area of the Geelong Arm may be important for these young fish. In the spring,

KGW of about 1 year age, and length of 80–160 mm in length, were common both within shallow seagrass beds and edge habitat at the Grand Scenic site and also shallow seagrass edge habitat at Swan Island.

There was a general pattern of larger, older juvenile KGW occurring in deep habitats and also in habitats at Mud Islands. KGW approximately 18 months old and 150–220 mm in length were recorded in shallow edge habitat at Swan Island and Grand Scenic, but were also common at Mud Islands in this habitat. Larger juvenile KGW, 2 to 3 years of age and ranging in length to 30 cm, were recorded in deep edge habitat at Swan Island, as well as shallow edge habitat at Mud Islands. The largest individuals of over 30 cm in length were recorded in deep seagrass habitat at Mud Islands.

A preliminary stereo underwater video study on KGW at Mud Islands (Jenkins 2010) recorded juveniles in shallow edge and seagrass habitat. Like the present study, TiV was highest in shallow edge habitat; however, MaxN in the earlier study was highest in shallow seagrass (Jenkins 2010). The size range of juvenile KGW was greater in the earlier study, ranging from less than 100 mm to over 350 mm (Jenkins 2010). This indicates that young juveniles had settled directly into seagrass at Mud Islands and/or that young juveniles had migrated from coastal areas at < 1 year of age. Presence of newly‐settled KGW has been recorded in shallow seagrass at Mud Island (Hutchinson et al. 2011). A key finding of the preliminary study was that while juvenile KGW were common on unvegetated habitat at the edge of seagrass, they were never recorded from unvegetated habitat distant (> 200 m) from seagrass (Jenkins 2010), presumably because of a lack of enrichment of the sediment by seagrass detritus and therefore reduced benthic productivity.

Our results were also broadly consistent with a previous underwater video study in shallow seagrass habitat at Blairgowrie (Smith et al. 2011). This study also found older juvenile KGW were most abundant in seagrass edge habitat. Interestingly, 0+ age whiting, observed between December and February, were most abundant on seagrass, supporting observations from seine netting that KGW are closely related to seagrass


32

for the first few months after entering the bay in the spring but move onto unvegetated edge habitat after four to five months in the late summer/autumn (Smith et al. 2011).

Like many sampling methods, there are inherent biases in underwater video sampling that can affect results. TiV and MaxN suggested that juvenile KGW were most abundant at Grand Scenic and least abundant at the Corio Bay site (Eastern Beach). The video from the Corio Bay site, however, had generally poorer visibility than other sites and this may have biased the results. Another factor affecting results was that some video recordings in deep seagrass at Swan Island could not be analysed due to long seagrass stems blocking the view, leading to relative under‐sampling of this habitat.

We tested baited video as a possible way to increase sample sizes, particularly for estimating size composition of juvenile KGW in video recordings, however there was no discernable effect of bait on number of KGW detected. The bait was successful in attracting some other fish groups to the field of view, most notably leatherjackets. The use of baited video in studies comparing habitat use is problematical in any case as individuals may be attracted from habitats a considerable distance away. In general we would not recommend the use of baited video for studying juvenile KGW.

Otolith chemistry There was significant spatial variation in otolith chemistry of post‐larval KGW sampled in seagrass beds around Port Phillip Bay. Variation was most notable for barium, manganese and strontium. These elements have been found to commonly show spatial variation in otoliths of a variety of species and geographic locations, and are regularly used as natural tags in studies aimed at determining nursery origins and connectivity among fish populations (Campana 1999; Thorrold et al. 2001; Gillanders 2002; Elsdon et al. 2008; Hamer et al. 2011).

Spatial variation of individual element:Ca ratios occurred at the local scale of seagrass beds and did not show clear regional (i.e. north, south, Bellarine) trends. Ba:Ca and Mn:Ca in particular showed highly significant local‐scale variation. For example, Ba:Ca levels for post‐larval otoliths from Rosebud and Swan Bay were elevated relative to other sites, and Mn:Ca was elevated at Altona and Kirk Point relative to other sites. These local‐scale effects likely related to variation of local water physico‐chemical properties

influenced by local terrestrial point source inputs, water depth/temperature, tidal flows/flushing rates and potentially sediment chemistry (Forrester and Swearer 2002; Elsdon and Gillanders 2004; Hamer and Jenkins 2007; Elsdon et al. 2008).

While post‐larval otolith chemistry varied significantly between some seagrass beds, across the 10 sample sites there was considerable overlap of the element:Ca ratio data. This limited our ability to construct clear baseline elemental signatures or “tags” for individual seagrass beds. Broad regional groupings of sites, however, resulted in more powerful discrimination of otolith elemental chemistry baseline signatures. In particular, grouping the sites as ‘north’ and ‘south’ regions provided a reliable baseline data set with which to determine the composition of older KGW.

Despite the inability to develop baseline otolith elemental signature at smaller scales, seagrass beds in northern and southern Port Phillip Bay are subject to different climate related risks and anthropogenic impacts. Seagrass beds in northern Port Phillip Bay, such as Kirk Point, Altona and Ricketts Point are relatively small in area, generally restricted to shallower waters and subject to greater levels of anthropogenic disturbance, including freshwater inputs and chemical pollutants, than beds in the southern bay. As such, determining the relative importance of the northern seagrass beds to supporting recruitment of KGW in Port Phillip Bay is important.

Sampling of older KGW of the same cohort as the post‐larvae was necessarily restricted to 1 year old fish due to the time scale of the project. Sampling of 1 year old fish was made difficult due to the timing of this project, corresponding with a year of poor recruitment of juvenile KGW to Port Phillip Bay. This meant that it was difficult to collect enough fish from a range of sites around the bay to do a full bay‐wide population analysis. Future sampling/analyses of this cohort at older ages when recruited to the fishery (i.e. 2–3 year age) is recommended, and this could involve recreational and commercial fishers, allowing much greater and cost‐effective sampling effort.

Maximum likelihood composition analysis of the 1 year old samples from the three sites in southern Port Phillip Bay (Corio Bay, Grassy Point, Swan Bay) clearly indicated no contribution from northern bay seagrass beds to populations at these southern seagrass areas.


33

Furthermore, comparisons of the individual element:Ca ratios between the post‐larval stages and the post‐larval otolith regions of the 1 year olds (particularly for Ba:Ca) for these three sites indicated close similarity of both the values of the ratios and the patterns of variation among the sites. This suggests that the 1 year old fish had remained resident in the local area of capture for their first year of life, and supports the observations from the video sampling that shallow areas of seagrass beds are preferred habitat for KGW for their first 1–2 years of life.

Vulnerability of juvenile King George whiting to climate change The most likely impact of climate change on juvenile KGW will be mediated through effects on seagrass. The preferred habitat of juvenile KGW appears to be a mosaic of patchy seagrass and unvegetated habitat, with seagrass detritus providing enriched feeding on the sand/mud at the seagrass edge. Unvegetated habitat some distance away from seagrass does not appear to support juvenile KGW.

The importance of seagrass to juvenile KGW was clearly demonstrated in Western Port in the mid 1970s when a major loss of 70% of seagrass cover occurred. The commercial catch of KGW up until this point had shown an increasing trend in parallel with the catch in Port Phillip, but after the loss the catch declined while the Port Phillip catch continued to increase (Jenkins 2010).

Climate changes impacts on seagrass are likely to depend on depth, as will the flow‐on impacts to juvenile KGW. Shallow habitats appear to be the most important for younger juvenile KGW. Older juveniles occur in deeper habitat but can also utilise shallow habitat, such as at Mud Islands.

In terms of spatial distribution, the youngest juveniles were collected in the Geelong Arm, which is also known to be a primary area for settlement of post‐larvae. Seagrass coverage in the Geelong Arm may therefore be particularly significant for young juvenile KGW.

The key seagrass species forming habitat for KGW in PPB is the sub‐tidal seagrass Zostera nigricaulis. Seagrass distribution and abundance is driven primarily by light and nutrients. Seagrasses have relatively high light requirements compared to other aquatic plants such as algae. This is why the deepest seagrass beds in PPB occur towards the entrance, where waters are clearest. Seagrasses also tend to have defined nutrient requirements. Seagrass growth

can be limited by nutrients, particularly nitrogen, in PPB (Bulthuis et al. 1992). Conversely, it is well known that excessive nutrients can cause seagrass dieback due to smothering by fast growing algal epiphytes (Bjork et al. 2008).

High temperatures and exposure are also detrimental to seagrasses. In Western Port, a combination of smothering of Zostera leaves by sediment from the catchment blocking light, together with hot weather and low tides associated with an intense El Nino event is thought to have initiated the seagrass die‐off. This mechanism is less likely in PPB where shallow mud banks are not nearly as extensive as in Western Port; but potentially could happen in Swan Bay and Corner Inlet, where extensive mud banks do occur.

Historical seagrass mapping has shown that seagrass beds in southern PPB and the southern Geelong Arm increased in area over 50 years until the late 1990s, however the decadal drought that began at this time was associated with a decline in seagrass in these areas. The primary hypothesis for the mechanism behind this decline is that reduced freshwater flows during the drought resulted in nutrient limitation of seagrass. This hypothesis is supported by increased seagrass cover recorded over the past two years of La Nina above average rainfall. Different historical patterns are apparent for Swan Bay and the northern Geelong Arm where seagrass beds are more directly affected by catchment inputs (freshwater and nutrients) and are less likely to be nutrient limited.

Climate change will have a number of potential impacts on seagrass (Connolly 2009). Increasing sea level will lead to a reduction in shallow seagrass beds unless there is corresponding colonisation shorewards. In some cases, however, shoreward colonisation will not be possible due to man made barriers (break walls etc.) or to unsuitability of the substrate (Short and Neckles 1999; Connolly 2009).

Climate change will also lead to more intense storm and runoff events, causing direct effects on seagrass through physical disturbance and also reduced light through increased turbidity (Connolly 2009). Areas of seagrass most susceptible to these effects will be those near catchment inputs such as Swan Bay, and northern Port Phillip Bay, Western Port and Corner Inlet. Shallow seagrass beds will be the most affected by direct disturbance while deeper beds will be more affected by reduced light.


34

Seagrass in southern Port Phillip Bay may be affected by long‐term decreases in freshwater runoff under climate change, similar to the decreased runoff and associated increased salinity seen during the extended drought in the 2000s. The decreased runoff will mean reduced nutrients reaching the Geelong Arm and southern Port Phillip Bay that could cause seagrass decline through nutrient limitation. This would have a similar effect on both shallow and deep seagrass beds.

Shallow seagrass beds may also be vulnerable to increased air and water temperatures under climate change at extreme low tides (Walker 2012). This risk is of greatest concern where extensive shallow mud banks occur, such as Swan Bay, Western Port and Corner Inlet.

A potential positive effect of climate change on seagrass is the predicted increased in dissolved carbon dioxide that will be available for photosynthesis (Connolly 2009). The extent of this benefit is highly uncertain as the extent of inorganic carbon limitation of Zostera growth and productivity is relatively unknown for Victorian seagrass systems.

Although there are significant uncertainties, on balance the evidence suggests that climate change will have a detrimental effect on seagrass, particularly in shallow habitats. This has significant implications for juvenile KGW growth and survival into the future, given the previous research showing that seagrass is a key settlement habitat for post‐larvae (Jenkins and Wheatley 1998), and that results of this study suggest that shallow seagrass edge habitat is critical for young juvenile KGW. Impacts will vary depending on location. For example, the southern Geelong Arm was an important area for young juvenile KGW in this study and under climate change seagrass in this area could be affected by nutrient limitation due to freshwater flows. Alternatively, seagrass in important nursery areas such as Swan Bay, northern Western Port and northern Corner Inlet may be more affected by intense storm and runoff events, as well as more extreme temperatures.

Future Research The importance of seagrass edge habitat to KGW demonstrated in this study indicates that the importance of seagrass to juveniles may be mainly through the enrichment of sediments by seagrass detritus leading to increased

abundances of prey organisms such as polychaete worms. One pertinent question in relation to climate change impacts is whether KGW juveniles are specifically dependent on seagrass detritus or whether other plant detritus, such as from algae, could compensate for seagrass loss.

Stable isotope ratios of elements such as nitrogen can be used to identify the plant basis of food chains because they can provide a unique signature for different plant types supporting the diet. In theory, this method could be used to determine the dependency of juvenile KGW on seagrass to support their food chain, and therefore their vulnerability to seagrass loss through climate change.

Seed funding was provided in this project to investigate the potential for using stable isotopes of seagrass and other plant sources to investigate the diet dependency of juvenile KGW on seagrass. Samples were collected from around Port Phillip Bay of seagrass and other plant sources such as algae. Analysis indicated that stable isotopes of nitrogen, usually used to identify plant sources, varied greatly with locality in Port Phillip Bay. This result complicates the use of stable isotopes in a potential future study on dietary plant sources of juvenile King George whiting, and suggests that stable isotopes of carbon and sulphur may also need to be analysed to provide a reliable discrimination of seagrass based diets from those based on other plant types.

A current major study funded by the Department of Sustainability and Environment on seagrass resilience in Port Phillip Bay will provide further information on the potential changes to seagrass under climate change. The study will use a combination of field experiments, numerical modelling and genetics to investigate the resilience of seagrass to the effects of environmental change, particularly changes to catchment inputs of nutrients and sediments. The results of this study should help refine, and give greater confidence to, our predictions of the trend in seagrass abundance in Port Phillip Bay under climate change. In turn, this will improve confidence in predictions of the effects of climate change on the long‐term trend in KGW abundances in Port Phillip Bay.


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Conclusions

Improving the resilience and adaptation of King George whiting to climate change The population levels of King George whiting in Victorian Bays and inlets result from a combination of larval supply from distant spawning grounds to the west, and juvenile survival largely dependent on adequate cover of seagrass habitats in bays and inlets (Jenkins 2010). Like seagrass cover, larval supply is likely to be affected by climate change, especially in relation to water temperatures in Bass Strait affecting larval growth, and the strength of the Leeuwin Current affecting larval dispersal (Jenkins 2010). Effects of climate change on larval supply are largely beyond the influence of any management actions, however, in the case of juvenile survival and seagrass, there are a number of management actions that can be undertaken to improve the resilience and adaptation of King George whiting to climate change.

The resilience of seagrass to climate change will be improved where seagrass health is not also compromised by anthropogenic stressors; particularly those that affect water quality and light availability (Bjork et al. 2008). In this case, catchment management practices will be crucial to support seagrass health and resilience to climate change.

Catchment management can improve land‐use practices to reduce nutrient and sediment loads in run‐off, as well as reducing where possible the use of pesticides and herbicides (Bjork et al. 2008). This management may be particularly important for Swan Bay, which we have shown is a significant source of juvenile KGW. The use of stormwater sediment traps and the effective treatment of effluent are also key management priorities, as is the provision of buffer zones of undisturbed land along stream edges together with the protection of coastal wetlands that act as natural filtration systems (Bjork et al. 2008).

In cases such as southern Geelong Arm and southern Port Phillip Bay, nutrients may become limiting when run‐off is reduced under climate change. It will be important for catchment management to reduce, where possible, the extraction of water from streams for farming,

dams etc that would otherwise contribute to runoff and nutrient input.

A key to improving seagrass resilience through catchment management is to include these marine assets in catchment management planning. Such planning requires accurate mapping of seagrass beds so that spatial planning can be undertaken and potential impacts considered.

The proper management and control of activities that can cause direct physical disturbance of seagrass beds is another crucial area to improve seagrass resilience (Bjork et al. 2008). Such activities can include the development of coastal infrastructure (breakwalls, marinas etc), channel dredging activities, and physical damage caused by boats (anchoring, propeller scarring) and moorings.

Marine environmental management can assist seagrass resilience to climate change by protecting areas of seagrass that have shown resilience to climate variation in the past and are likely to act as refuge areas in the future. These areas can be identified for Port Phillip Bay based on historical seagrass mapping (Ball et al. 2009). Areas of seagrass that show high production of seeds that would contribute to colonisation of other areas should also be considered for management protection. In the case of resilience of King George whiting to climate change, any protection by marine managers of seagrass habitat in key juvenile distribution areas such as those identified in this study would be of considerable benefit.

Seagrass restoration may be considered as a strategy of final resort, but it is costly and the success is generally low and variable (Orth et al. 2006). In general, if conditions are not suitable for natural seagrass growth, artificial planting will also tend not to be successful. In the few cases where there has been some success, the process is very expensive and the area restored is relatively small and may not be of benefit to King George whiting resilience to climate change.


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Informing fishery management arrangements of future King George whiting population trends Predicting the future trend of the King George whiting population has significant uncertainty because of the dependence of fishery recruitment on both larval supply and juvenile survival. The predictions for larval supply under climate change are uncertain depending on the main factors influencing larval dispersal and survival (Jenkins 2010). Climate change may be positive for larval supply if increased water temperatures in Bass Strait lead to higher larval growth rates and survival (Jenkins and King 2006), or negative for larval supply if the predicted weakening of the Leeuwin current leads to less dispersal of larvae to central Victorian Bays (Jenkins 2010). Even if larval supply is relatively robust, however, climate change is expected to lead to decreased seagrass coverage that will reduce fishery recruitment through decreased juvenile growth and survival. A major loss of seagrass would have very significant consequences for fishery recruitment as has previously been seen in Western Port (Jenkins 2010). Overall, the best estimate would be that there will be a long‐term decline in fishery recruitment for KGW under climate change in central Victorian Bays, albeit with significant uncertainty.

As mentioned, reducing other stressors on seagrass health will significantly increase the resilience of seagrass and therefore KGW populations to climate change impacts. In this respect, mitigation is mostly the responsibility of catchment and coastal managers rather than fishery managers. However, although fisheries managers are not able to directly manage these

areas, they can strongly advocate for this management, either directly between management agencies or through education of industry and the public as to the importance of these areas that will increase pressure for protection.

Management of the King George whiting fishery will need to be adaptive, and ideally would include a harvest strategy that sets limits, targets and decision rules. For KGW, this strategy could be largely based on monitoring of both post‐larval settlement and seagrass cover to provide an estimate of fishery recruitment in the ensuing years.

Monitoring of post‐larval KGW settlement in PPB has now been undertaken for 14 years and provides a reliable index of larval supply for this bay. Into the future this index will give a leading indicator of any effects of climate change on the levels of post‐larval settlement. Monitoring seagrass cover in central Victorian bays has also been undertaken over the past decade, and because shallow seagrass habitat is most critical, monitoring can be relatively straight forward based on aerial imagery. Again this information would provide a leading indicator of possible trends in seagrass cover under climate change that would affect juvenile survival. Information from these monitoring programs would then be fed back into the harvest strategy in relation to pre‐set decision rules.


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Acknowledgements We thank David Hatton and Andrew Brown for assistance with field sampling. We also thank Tim Kenner for assisting with the video analysis.

We wish to acknowledge the funding for this work provided by Future Farming Strategy Initiative on climate change adaptation through Fisheries Victoria.


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