Fisheries Adaptation to Climate Change ‐ Marine Biophysical Assessment of King George whiting
Greg Jenkins, Neil Hutchinson, Paul Hamer and Jodie Kemp
August 2012
Fisheries Victoria Research Report Series No. 57
Marine Biophysical Assesment – King George whiting
If you would like to receive this Author Contact Details: Greg Jenkins information/publication in an Fisheries Research Branch, Fisheries Victoria accessible format (such as large PO Box 114, Queenscliff Vic 3225 print or audio) please call the Authorised by the Victorian Government, Customer Service Centre on: 1 Spring Street, Melbourne 136 186, TTY: 1800 122 969, Printed by DPI Queenscliff, Victoria or email Published by the Department of Primary [email protected] Industries. © The State of Victoria, Department of Primary Copies are available from the website: Industries, 2012. www.dpi.vic.gov.au/fishing This publication is copyright. No part may be General disclaimer reproduced by any process except in accordance This publication may be of assistance to you but with the provisions of the Copyright Act 1968. the State of Victoria and its employees do not guarantee that the publication is without flaw of Preferred way to cite this publication: any kind or is wholly appropriate for your Jenkins, G. P., Hutchinson, N., Hamer, P. A. and particular purposes and therefore disclaims all Kemp, J. (2012) Fisheries Adaptation to Climate liability for any error, loss or other consequence Change ‐ Marine Biophysical Assessment of King which may arise from you relying on any George whiting. Fisheries Victoria Research information in this publication. Report Series No. 57, 41 pp. ISSN 1448‐7373 ISBN 978‐1‐74326‐060‐9 (Print)
Marine Biophysical Assesment – King George whiting ii Executive Summary
Fisheries Victoria is undertaking a suite of two depth zones: “shallow” (0.4 to 1.1 m) and projects under the Future Farming Strategy deep (2.2 to 7.7 m). initiative ʺAdaptation of fisheries, aquaculture Stereo video analysis showed distinct patterns in and fisheries management to climate changeʺ to spatial, temporal and depth distribution as well prepare fisheries sectors and fisheries managers as habitat use in King George whiting. Distinct for change. patterns were also observed in size distributions Under this initiative, the marine biophysical between sites and depths. assessments are aimed at understanding the The most common habitat juvenile King George biophysical implications that may occur in the whiting was observed in was shallow seagrass future due to climate change to better inform edge habitat. This was consistent with results for decision making. These assessments aim to small juveniles collected by netting in previous determine the degree of exposure a species has to studies. There was, however, a general pattern of climate change to inform assessments on how larger, older juvenile whiting occurring in deep vulnerable Victoria’s fishing and aquaculture habitats and also in habitats at Mud Islands. sectors are to these changes. The smallest King George whiting juveniles King George whiting was specifically identified recorded in this study were from Grand Scenic as one of the higher priority species for Victoria (southern Geelong Arm) in autumn, and at a size as it represents a key recreational and of 60–120 mm would have been approximately 6 commercial fish species in Victoria that relies on months old. The largest individuals of 2–3 years seagrass as a key component to complete its life of age and over 30 cm in length were recorded in cycle. The exact extent of this requirement is deep seagrass habitat at Mud Islands. unknown and requires attention to enable the vulnerability of the species to climate change to Otolith microchemistry was used to investigate be understood. the seagrass regions in Port Phillip Bay most important for producing young whiting. Otoliths This project focuses on understanding the key of newly‐settled post larvae from 10 seagrass characteristics of seagrass regions within Port sites around Port Phillip Bay were analysed to Phillip Bay that are important to the production identify “signatures” for different seagrass sites, of juvenile King George whiting. This includes and then compared to the signatures formed at the depth of seagrass preferred by different age‐ the same time in the otoliths of juveniles caught classes of juveniles and the areas of seagrass in one year later. Port Phillip Bay that are most important for producing juvenile King George whiting. There was considerable overlap in otolith chemistry between sites that meant that The aims of the project were to inform decision “signatures” for individual sites could not be makers on the vulnerability of King George identified. However, it was possible to group the whiting to climate change in Port Phillip Bay, sites as ‘north’ and ‘south’ regions to provide a informing on opportunities for improving the reliable baseline data set with which to determine resilience and adaptation of King George the origin of 1‐year old King George whiting. whiting, and informing fishery management arrangements of future whiting population Sufficient 1‐year old whiting could only be trends. collected from three southern sites (Corio Bay, Grassy Point and Swan Bay), and these were all Sampling with underwater stereo video was found to have originated from the southern done in four areas of Port Phillip Bay: Eastern region. Moreover, similarity between signatures Beach, Grand Scenic, Mud Islands and Swan in post‐larvae and 1‐year olds from these sites Island; in spring 2010 and autumn 2011. Habitats indicated that juveniles had not moved sampled were the sub‐tidal seagrass, Zostera significantly over their first year of juvenile life. nigricaulis (“seagrass habitat”) and unvegetated These results supported the video observations sand/mud at the edge of seagrass (“edge that smaller juveniles were generally in shallow, habitat”). In each area, habitats were sampled in nearshore habitat.
Marine Biophysical Assesment – King George whiting iii Climate changes impacts on seagrass are likely to Predicting the future trend of the King George depend on depth, as will the flow on impacts to whiting population has significant uncertainty juvenile King George whiting. Although there because of the dependence of fishery recruitment are significant uncertainties, on balance, the on both larval supply and juvenile survival. evidence suggests that climate change will have a However, a significant loss of seagrass would detrimental effect on seagrass, particularly in almost inevitably lead to a significant decline in shallow habitats. Shallow habitats appear to be the King George whiting population. As the most important for younger juvenile King mentioned, reducing other stressors on seagrass George whiting. Potential climate change effects health will significantly increase the resilience of on shallow seagrass include increasing sea level, seagrass and therefore King George whiting increasing water temperature and desiccation, populations to climate change impacts. In this and increased disturbance due to more frequent respect, mitigation is mostly the responsibility of and intensive storm events. catchment and coastal managers rather than fishery managers. However, although fisheries In terms of spatial distribution, the youngest managers are not able to directly manage these juveniles were collected in the Geelong Arm. areas, they can strongly advocate for this Seagrass coverage in the Geelong Arm may management, either directly between therefore be particularly significant for young management agencies or through education of juvenile King George whiting. Decreased runoff industry and the public as to the importance of under climate change could mean reduced these areas that will increase pressure for nutrients reaching the southern Geelong Arm protection. and Port Phillip Bay that could cause seagrass decline through nutrient limitation. This would Management of the King George whiting fishery have a similar effect in both shallow and deep will need to be adaptive, and ideally would seagrass beds. include a harvest strategy that sets limits, targets and decision rules. For King George whiting this The resilience of populations of juvenile King strategy could be largely based on monitoring of George whiting to climate change will largely both post‐larval settlement and seagrass cover to depend on the resilience of seagrass habitats. provide an estimate of fishery recruitment in the Seagrass will be most resilient to climate change ensuing years. 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.
Marine Biophysical Assesment – King George whiting iv 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
Marine Biophysical Assesment – King George whiting v 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
Marine Biophysical Assesment – King George whiting vi 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
Marine Biophysical Assesment – King George whiting vii 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
Marine Biophysical Assesment – King George whiting viii Introduction
It is predicted that climate change will result in commercial fish species in Victoria that relies on changes to ocean circulation patterns, water seagrass as a key component to complete its life temperature and sea level (Poloczanska et al. cycle. The exact extent of this requirement is 2007). Climate change is also predicted to cause unknown and requires attention to enable the changes in weather patterns across south eastern vulnerability of the species to climate change to Australia, leading to reduced seasonal rainfall be understood. and infrequent high intensity rainfall events resulting in increased turbidity, more variable Climate change predictions for salinity levels and disturbance of seagrass. Victoria These physical changes and effects on seagrass Temperature will have implications for the biomass and range Air temperature of marine and estuarine fish and the ecosystems Air temperature is often strongly related to water that support them. In some cases these changes temperature in estuaries, bays and inlets. CSIRO will manifest in declines in abundance and climate modelling suggests that under medium distribution, and for other species increased emissions the best estimate is for a temperature abundance and distribution. These changes in increase of 0.6–1 oC by 2030, rising to 1.5–2 oC by abundance and distribution mean that 2070, with the greatest increase occurring in management arrangements will need to be summer; 2–2.5 oC by 2070 (Anon. 2007). Under responsive to change. high emissions an increase of 2.5–3 oC could An understanding of the likely implications to occur in the eastern half of Victoria by 2070 the key Victorian fisheries is necessary to (Anon. 2007). adequately prepare for responding to these Sea surface temperature challenges and to better target management Sea surface temperature (SST) off the coast of efforts. Victoria under medium emissions is predicted to Fisheries Victoria is undertaking a suite of increase by 0.3–1 oC by 2030, rising to 0.6–2 oC by projects under the Future Farming Strategy 2070, with rises greatest in the eastern part of the initiative ʺAdaptation of fisheries, aquaculture State (Anon. 2007). Under a high emissions and fisheries management to climate changeʺ to scenario the SST increase in the far east of the prepare fisheries sectors and fisheries managers State could be 2–2.5 oC (Anon. 2007). for change. Rainfall Under this initiative, the marine biophysical The best estimate of rainfall change based on assessments are aimed at understanding the climate modelling under a medium emissions biophysical implications that may occur in the scenario is a deficit of 2–5% by 2030, increasing to future due to climate change to better inform a deficit of 5–10% by 2070 (Anon. 2007). This decision making. These assessments aim to change is highly seasonal, with a spring deficit of determine the degree of exposure a species has to 20–30% compared to an autumn deficit of 2–5% climate change to inform assessments on how by 2070 (Anon. 2007). As well as a reduction in vulnerable Victoria’s fishing and aquaculture overall rainfall, rain will tend to occur in more sectors are to these changes. intense events, interspersed with an increasing proportion of dry days, signifying more extreme This project builds on and is informed by a risk weather fluctuations (Anon. 2007). In terms of assessment undertaken in 2008/09 (Hutchinson et rainfall effects on runoff and salinity, reduced al. 2010) and a desktop review of literature in runoff and increasing salinity due to decreasing 2009/10 (Jenkins 2010). These previous projects rainfall will be exacerbated by increased solar assisted in establishing a prioritisation radiation and decreased humidity leading to framework for focusing research regarding increased evaporation rates (Anon. 2007). climate change implications for fish in Victoria. King George whiting was specifically identified Winds as one of the higher priority species for Victoria While wind speed is not expected to change on a as it represents a key recreational and seasonal basis, by 2070, wind speed under a
Marine Biophysical Assesment – King George whiting 1 medium emissions scenario is expected to greatest effect of sea level rise will occur during decrease by 5–10% in central Victoria in autumn extreme weather events such as storms with and increase by 2–5% (5–10% off the east coast) in associated storm surges (Church et al. 2009). Such winter (Anon. 2007). events may become more frequent under climate change (Poloczanska et al. 2007). The Victorian climate is dominated by westerly winds associated with the southern annular Solar radiation mode (SAM). In recent decades there has been a Ultraviolet radiation associated with solar poleward shift in the circumpolar westerly winds radiation is known to have deleterious effects on associated with an upward trend in SAM. This marine life (Poloczanska et al. 2007). The best trend is expected to continue under climate estimate of solar radiation change based on change (Cai et al. 2005; Ridgway and Hill 2009). climate modelling under a medium emissions This will lead to a weakening trend for westerly scenario is little change by 2030, but a 1–2% wind strengths over Victoria (Poloczanska et al. increase by 2070, with a “hotspot” of 2–5 % 2007). increase over central Victoria including Port Currents Phillip and Western Port (Anon. 2007). Most of this increase will occur in the winter and spring The East Australian Current (EAC) has (Anon. 2007). strengthened over recent decades so that warmer, saltier water is now found 350 km further south compared to 60 years ago King George whiting biology (Ridgway and Hill 2009). It is likely that the EAC King George whiting (Sillaginodes punctatus) are will strengthen by a further 20% by 2100 under native to Australian coastal waters and inhabit future climate change (Ridgway and Hill 2009). near‐shore shallow waters off the continental The main factor driving these changes is the shelf as well as bays and inlets from Port Jackson southward migration of the high latitude (NSW), to northern Tasmania and Jurien Bay in westerly wind belt mentioned previously Western Australia (Gomon et al. 2008). Juvenile (Poloczanska et al. 2007). fish are restricted to bays and inlets while adults are found in open coastal waters (Kailola et al. The Leeuwin Current (LC) has shown a 1993). weakening trend in recent decades due to more frequent El Nino events (Feng et al. 2009). King George whiting have a life expectancy of 17 Predictions under future climate change are for years and are thought to reach sexual maturity as no significant change to the LC volume flux by early as three years of age and at a length of 32 2030, and a slight further weakening by 2100 cm (Jones et al. 1990; Fowler et al. 2000). The size (Feng et al. 2009). There is low confidence in these and age at maturity can vary with locality predictions (Feng et al. 2009). (Fowler et al. 2000). Localities where spawning occurred had the broadest age and size Seawater Chemistry distributions and were in deep water that Carbon dioxide dissolving in the sea has lowered experienced medium to high wave energy pH by 0.1 units since 1750, representing a 30% (Fowler et al. 2000). increase in hydrogen ion (acid) concentration King George whiting found in Victorian waters (Havenhand et al. 2009). It is expected that spawn between May and July (Jenkins and May seawater pH will decrease by a further 0.2–0.3 1994) in coastal waters outside bays or inlets units by 2100 (Havenhand et al. 2009). Increasing (Jenkins et al. 2000). Adults in spawning seawater acidity will affect organisms with condition or life history stages less than 100 days calcium carbonate structures, and there is already old are rarely found in near‐shore central evidence of effects on corals and Southern Ocean Victorian waters, which suggest that there is little zooplankton (Havenhand et al. 2009). Conversely, or no spawning activity in the vicinity (Hamer et increasing concentration of CO2 in seawater may al. 2004). Recent research suggests that spawning benefit growth of marine plants such as may take place in coastal waters to the west of seagrasses (Connolly 2009). Victoria’s major bays and inlets, and that some of Sea level the Victorian King George whiting population Global sea levels have risen by 20 cm over the may be derived from spawning in South period 1870 to 2004 (Church et al. 2009). Sea Australian waters (Jenkins et al. 2000; Hamer et al. levels will continue to rise by 5–15 cm by 2030 2004). Until the spawning stock(s) for Victorian and 18–82 cm by 2100 (Church et al. 2009). The King George whiting is identified, it will not be
Marine Biophysical Assesment – King George whiting 2 possible to determine the potential role of After settlement, juvenile development occurs varying stock size on recruitment variation. over the next 3 to 4 years before the onset of sexual maturity. The mature fish then migrate King George whiting eggs are buoyant, and eggs offshore to join other adult stock in oceanic hatch after a few days at a size of 2 –3 mm (Bruce waters (Jones et al. 1990; Hamer et al. 2004). The 1995). Larvae are then transported by water rate of growth varies depending on the water currents and may drift for 3 to 5 months before temperature, with very little growth occurring entering sheltered marine habitats in Victorian during the winter and rapid growth from bays and inlets in spring when they reach around December to March (Coutin 2000). 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 This Report Western Port (Jenkins et al. 2000). In Victoria, we assume that King George Whiting rely on seagrass as a critical habitat. We also In the case of Port Phillip Bay, ingress of larvae understand that climate change will cause occurs when strong westerly winds and low changes that are likely to affect seagrass barometric pressure cause the sea level on the (Connolly 2009). More storm events will lead to coast and in the Bay to rise (Jenkins et al. 1997a). pulses of turbidity that will reduce light for Larvae are concentrated in the surface layers seagrass growth, as well as directly affecting during daylight but are distributed throughout seagrass through wave disturbance (Connolly the water column at night (Jenkins et al. 1998b). 2009). Increased sea level will also mean less light Research shows that the seagrass beds where for seagrass growth. Seagrass may be able to King George whiting larvae settle most often are migrate shoreward to compensate, however this those in the areas where currents deliver larvae, cannot occur where the shoreline has been rather than being related to the “quality” of the ‘hardened’ (i.e. through construction of sea‐walls, seagrass (Jenkins et al. 1998a). The suitability of breakwaters etc) (Connolly 2009). An overall seagrass beds is further influenced by wave reduction in freshwater flows with climate exposure, with exposed beds carrying fewer change may lead to a limitation on nutrients post‐larvae than protected ones (Jenkins et al. reaching seagrass, leading to declines (Bulthuis et 1997a). Seagrass is probably crucial to newly‐ al. 1992). settled larvae through the provision of food (Jenkins and Hamer 2001) or protection from Although some aspects of the life history of King predators (Hindell et al. 2000b; a). George whiting are known, information on the relationship between juvenile whiting in Although settlement is primarily associated with Victorian bays and seagrass habitats is limited to shallow seagrass and reef‐algal beds (Jenkins and very young post‐settlement stages, reducing our Wheatley 1998), at some sites, newly‐settled ability to predict future population trends of individuals have been found in bare unvegetated King George whiting under climate change mud patches within seagrass beds (Jenkins et al. scenarios. Our greatest opportunity to improve 1997b; Jenkins and Hamer 2001). The importance our understanding of King George whiting of a particular habitat may depend on the vulnerability to climate change is to determine amount of food available (Jenkins and Hamer the linkages between juvenile King George 2001) as well as the local current patterns that whiting and seagrass habitats. deliver the larvae to the habitat (Jenkins et al. 1998a). This project focuses on understanding the key characteristics of seagrass regions within Port King George whiting show a change in habitat Phillip Bay that are important to the production preference with growth. Post‐larvae initially of juvenile King George whiting. This includes settle near seagrass and reef‐algae at depths the depth of seagrass preferred by different age‐ between 0–2 m (Jenkins et al. 1996; Jenkins and classes of juveniles and the areas of seagrass in Wheatley 1998). From five to six months, most Port Phillip Bay that are most important for fish are found on unvegetated sand amongst producing juvenile King George whiting. The vegetated habitats (Jenkins and Wheatley 1998). work was conducted in Port Phillip Bay; Older juveniles may venture into deeper water, however the fundamental principles learnt where they are more common in areas of patchy would be transferable to other Victorian bays and seagrass and algae (G. Jenkins personal inlets. This knowledge will enable us to predict observation). Quantitative information on habitat the consequences of seagrass loss to King George use by older juveniles, however, is lacking. whiting populations under climate change. The
Marine Biophysical Assesment – King George whiting 3 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.
Marine Biophysical Assesment – King George whiting 4 Project Design and Methods
Underwater Stereo Video Video analysis Video was assessed using two different methods, Study sites MaxN and time in view (TiV) (Smith et al. 2011). Sampling was done in four areas of Port Phillip MaxN was the greatest number of a given fish Bay: Eastern Beach, Grand Scenic, Mud Islands species in a single video frame from the hour and Swan Island (Fig. 1); between October 2010 long video (an index of abundance), while TiV and March 2011. Habitats sampled were the sub‐ was recorded as the total time in seconds that at tidal seagrass, Zostera nigricaulis (“seagrass least one King George whiting was in view of the habitat”) (Plate 1) and unvegetated sand/mud at left camera. If a fish was lost from view (i.e. the edge of seagrass (“edge habitat”) (Plate 2). In hidden in seagrass or swam out of the field of each area, habitats were sampled in two depth view) and did not reappear within 10 sec, it was zones: “shallow” (0.4 to 1.1 m) and deep (2.2 to deemed to have left the sampling area (Smith et 7.7 m) (Table 1). al. 2011). The computer software packages EVENTMEASURE and PHOTOMEASURE were Remote underwater video used to get species MaxN and TiV data and Fish were sampled using remotely deployed estimate fish lengths (SeaGIS Pty. Ltd., stereo video systems (SeaGIS Pty. Ltd., Australia). Orientation and location within the Australia). Stereo systems consisted of a frame camera field of view could affect the with two Canon HV20 cameras with wide angle measurement of fish; therefore, only the lengths lenses (7 mm focal length) in housings angled of fish that were measured with less than 10% inward at 8 degrees, on bars 65 cm apart and 40 error were recorded. Lengths were measured for cm above the sea floor, and a diode arm for fish from a single video frame, with consecutive synchronisation of cameras. Video was unbaited measurements at least 5 minutes apart to avoid to prevent attraction of fish from nearby the possibility of measuring the same fish more positions. Disturbance effects that may affect fish than once. behaviour were restricted by only beginning video analysis after 1 min. Videos were retrieved Data analysis 1 h after deployment. A trial of baited video was Graphs were plotted of MaxN and TiV of King also conducted at Mud Islands. A bait bag was George whiting in terms of average and standard suspended on a cane rod approximately 1.5 m in error of the three drops in each habitat by depth front of the cameras. Bait consisted of smashed combination for each area and season. mussels and squid pieces. Kolmogorov‐Smirnov two‐sample test was used to assess length frequency data and determine Experimental design any difference amongst areas, seasons and depth Each area was sampled in spring and autumn. by habitat combinations. An area was sampled over two days, and three frame drops were allocated randomly to each habitat by depth combination (six drops per day). Otolith chemistry Thus, a total of 12 h of video footage was taken Sampling of post‐larval King George whiting by the stereo cameras over two days in each area. To develop area specific ‘baseline’ otolith The same procedure was used for baited video at chemistry signatures, recently settled (post‐ Mud Islands in December 2010 and for shallow larval, approximately 20–50 mm length) King habitat only in May 2011. 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
Marine Biophysical Assesment – King George whiting 5 were extracted from the net, rinsed in distilled glass slides and then sonicated in Milli‐Q water water and then frozen. for three minutes. Sonicated samples were again liberally rinsed (x3) in Milli‐Q water and stored We restricted analyses of post‐larval otolith in sealed plastic containers for analysis. chemistry to fish ≥ 25 mm standard length, SL (tip of snout to tip of caudle peduncle). This Trace element analyses were undertaken using a minimum size was chosen due to the time lag New Wave Research UP‐213 Nd:YAG ultraviolet between when a larva enters Port Phillip Bay and laser microprobe operated in Q‐switched mode settles into a seagrass area, and when the otolith coupled to a ThermoFinnigan Element 2 high composition becomes representative of the resolution inductively coupled plasma mass settlement location. Previous studies indicate that spectrometer (HR‐ICP‐MS) situated at Fisheries a 25 mm SL post‐larval King George whiting is Research Branch, Queenscliff. Data were likely to be between 50 and 60 days post‐entry to collected for the following isotopes: 25Mg, 55Mn, Port Phillip Bay (Jenkins and May 1994; Hamer 65Cu, 66Zn, 88Sr, 85Rb, 138Ba, and 208Pb, along with and Jenkins 1996). Based on daily otolith 43Ca which was used as the internal standard. increment widths for post‐larval King George Calibration was achieved with the National whiting presented in Jenkins and May (1994) an Institute of Standards (NIST) 612 glass wafer ablation diameter of 80 μm would be equivalent using methods described in (Lahaye et al. 1997; to 25‐35 days of otolith growth post‐entry to Port Hamer et al. 2003). Resolved concentrations were Phillip Bay. Sampling otoliths from post‐larvae < expressed as ratios to calcium for graphical 25 mm SL would have risked measuring a presentations and statistical analyses. A laser chemical composition that was more indicative of spot diameter of 80 μm, repetition rate of 6 Hz the planktonic/oceanic than the post‐settlement and fluence of ~10 J cm‐2, was used. Otolith environment in Port Phillip Bay. surfaces were pre‐ablated prior to actual data acquisition to remove any residual surface Sampling of 1 year old King George whiting contamination from cutting and polishing. Each In November–December 2011 samples of 1 year laser ablation spot sample consisted of 15 blank old King George whiting that had survived from scans of the carrier gases, followed by an ablation the previous year’s settlement (i.e. the same period of 25 scans, of which the first 5 scans were cohort as sampled for the baseline otolith excluded from data integration to allow for chemistry signatures) were collected from signal stabilisation. The sample data was blank seagrass habitats in Port Phillip Bay. Sampling subtracted before it was integrated to provide the was conducted using a combination of the seine actual counts used for the calculation of net used previously for post‐larval sampling and elemental concentrations. Detection limits (LOD) a similar net of 30 m length. Despite efforts to were calculated for each sample based on three sample 1 year olds at 9 sites around Port Phillip standard deviations of blank gas samples and Bay (Swan Bay, Mud Islands, Blairgowrie, adjusted for ablation yield (Lahaye et al. 1997). Rosebud, Ricketts Point, Altona, Kirks Point, The LOD values were as follows (μmol/mol Ca): Corio Bay, Grassy Point, Fig. 1), they could only Mg=1.691; Mn=0.404; Cu=0.116; Zn=0.117; be captured in sufficient numbers at Corio Bay, Rb=0.105; Sr=1.817; Ba=0.0849; Pb=0.065. Grassy Point and Swan Bay. A total of 70 x 1 year For the post‐larval otoliths (i.e. baseline chemical old whiting (Corio Bay 27, Grassy Point 16, Swan signatures), two ablations were made adjacent to Bay 27) were processed for chemical analysis. the margins of each otolith, one ablation at the Otolith preparation and chemical analysis dorsal tip and the other sightly ventral of the sulcus. Otolith margins were focused on for Thawed King George whiting samples were chemical analysis of post‐larval otoliths as it was measured for SL to the nearest 0.5 mm under a expected that the chemistry near the otolith stereo microscope with an ocular micrometer. margin will reflect the general area where a fish Otoliths were then extracted with fine stainless is collected and will therefore provide steel needles, rinsed in Milli Q water, air dried representative ‘baseline’ or location specific and stored in plastic vials. Otoliths were chemical signatures. embedded in epoxy resin (AKA‐Resin and AKA‐ Cure, Pacific Laboratory Supplies), and polished For the age 1 year otolith samples the post‐larval with lapping film (Ultralap 30, 12 μm) in the region within the otolith sections of these older transverse plane to expose the core region. fish was similarly targeted by sampling within Polished otoliths were triple rinsed in Milli‐Q specified windows at set distances both ventral water, air dried, mounted onto petrographic and dorsal of the core region. This sampling
Marine Biophysical Assesment – King George whiting 6 window was determined from measurements of discrimination between the baseline groups. the distance from core to the ablation centres of Maximum likelihood estimation (MLA) (Millar 95 post‐larval otoliths. 1987; 1990a) was then used to determine the contributions of the different baseline groups (i.e. Data analysis sources) to the samples of 1 year old fish. The Data were initially screened for extreme outliers HISEA programme described in (Millar 1990b) (defined as data that were >3 interquartile ranges (http://www.stat.auckland.ac.nz/~millar/) was either above the 75th percentile or below the 25th used to conduct the MLA analyses. Data for all percentile (Wilkinson et al. 1996)) and number of elements were transformed to ln (x + 1) to meet samples below the limits of detection. Rb, Pb and univariate normality (Millar 1990a). For each Cu were excluded from further analyses due to cohort the simulation mode with 1000 >40% of data falling below the LOD. For Mg, Mn, simulations was initially used to estimate the Sr, and Ba all data were above LOD, and for Zn variability of the estimator (i.e. baseline data). approximately 98% of data were above LOD. Bootstrapping (1000 re‐samplings of sample sizes Prior to further analysis the data were averaged the same as the original sample sizes) (Quinn and across both sample points on each otolith. Keough 2002) of the baseline (post‐larvae) and Statistical analysis of post‐larval and 1 year old mixed sample (1 year old fish) data was used to otoliths involved univariate analysis of variance estimate the mean and standard deviation of the followed by post‐hoc Tukey’s pairwise proportions of 1 year old fish originating from comparison tests to determine significant the different baseline/source areas. 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
Marine Biophysical Assesment – King George whiting 7
o 145 E Altona
Kirk Ricketts Pt Pt o 38 S
Corio Bay Grassy Pt
Grand Scenic Mud Swan Bay Is
Swan Island
Bass Strait Blairgowrie 0 510Kms Rosebud
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
Marine Biophysical Assesment – King George whiting 8
Plate 1. Shallow seagrass habitat at Grand Scenic
Plate 2. Shallow edge habitat at Mud Islands
Marine Biophysical Assesment – King George whiting 9
Results
Underwater Stereo Video
Time in View At Eastern Beach, King George whiting (KGW) KGW were also in view for an average of a few were in view in shallow edge habitat for an minutes in deep seagrass and deep edge habitat average of 2–3 min in both spring and autumn in autumn only (Fig. 4). For baited video at Mud (Fig. 2). KGW were also in view for an average of Islands, time in view of KGW in shallow edge less than one minute in deep seagrass in spring habitat increased from spring to autumn (Fig. 5). (Fig. 2). However, the TiV in this habitat in autumn was less than half that recorded with the unbaited At Grand Scenic, KGW were in view in shallow video in the same habitat (Figs 4, 5). edge habitat for an average of 35 to 40 minutes in both spring and autumn (Fig. 3). KGW were also At Swan Bay, KGW were in view in shallow edge in view for an average of a few minutes in habitat for an average of approximately 17 shallow seagrass in spring and for less than a minutes in spring and 6 minutes in autumn (Fig. minute in autumn (Fig. 3). 6). KGW were also in view in deep edge habitat for an average of a few minutes in spring and an At Mud Islands, KGW were in view in shallow average of less than a minute in autumn (Fig. 6). edge habitat for an average of approximately 12 minutes in autumn only (Fig. 4).
Marine Biophysical Assesment – King George whiting 10 7
6
5
4
3
2
(Mins) View Time in Seagrass, Shallow Seagrass, Deep 1 Edge, Shallow
Edge, Deep 0 Spring Autumn Season
Figure 2. Average Time in View for King George whiting recorded by underwater stereo video at Eastern Beach.
60
50
40
30
20
(Mins) View Time in Seagrass, Shallow Seagrass, Deep 10 Edge, Shallow Edge, Deep
0 Spring Autumn
Season Figure 3. Average Time in View for King George whiting recorded by underwater stereo video at Grand Scenic.
Marine Biophysical Assesment – King George whiting 11 20
15
10
5 Seagrass, Shallow Time in (Mins) View Seagrass, Deep Edge, Shallow Edge, Deep 0 Spring Autumn
Season
Figure 4. Average Time in View for King George whiting recorded by underwater stereo video at Mud Islands.
9
8
7
6
5
4
3
Seagrass, Shallow (Mins) View Time in 2 Seagrass, Deep
1 Edge, Shallow
Edge, Deep 0 Spring Autumn
Season
Figure 5. Average Time in View for King George whiting recorded by baited underwater stereo video at Mud Islands.
Marine Biophysical Assesment – King George whiting 12 40
30
20
Seagrass, Shallow 10
(Mins) View in Time Seagrass, Deep Edge, Shallow Edge, Deep 0 Spring Autumn
Season
Figure 6. Average Time in View for King George whiting recorded by underwater stereo video at Swan Island.
Marine Biophysical Assesment – King George whiting 13 MaxN At Eastern Beach, KGW in shallow edge habitat For baited video at Mud Islands, KGW in had a similar average MaxN of approximately shallow edge habitat had an average MaxN that two in spring and autumn (Fig. 7). KGW had an approximately doubled from spring to autumn average MaxN in deep seagrass in spring that (Fig. 10). Average MaxN of KGW for shallow was lower than that for shallow edge habitat (Fig. edge habitat in autumn was similar for baited 7). and unbaited video (Figs 9, 10). At Grand Scenic, KGW in shallow edge habitat At Swan Island, KGW in shallow edge habitat had a similar average MaxN of approximately 10 had an average MaxN of approximately six in in both spring and autumn (Fig. 8). KGW also spring and three in autumn (Fig. 11). KGW had a had a similar average MaxN in shallow seagrass MaxN in deep edge habitat that was about half of in spring (due to a MaxN of 29 in one video the level in shallow edge habitat in both spring replicate), but MaxN in this habitat was lower in and autumn (Fig. 11). 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).
Marine Biophysical Assesment – King George whiting 14 7
6
5
4
Max N Max 3
2 Seagrass, Shallow
Seagrass, Deep
1 Edge, Shallow
Edge, Deep
0 Spring Autumn Season
Figure 7. Average MaxN for King George whiting recorded by underwater stereo video at Eastern Beach.
30
20
N Max 10 Seagrass, Shallow Seagrass, Deep Edge, Shallow
Edge, Deep
0 Spring Autumn Season
Figure 8. Average MaxN for King George whiting recorded by underwater stereo video at Grand Scenic.
Marine Biophysical Assesment – King George whiting 15 12
10
8
6
N Max
4 Seagrass, Shallow Seagrass, Deep 2 Edge, Shallow
Edge, Deep
0 Spring Autumn Season Figure 9. Average MaxN for King George whiting recorded by underwater stereo video at Mud Islands.
15
10
Max N Max
5
Seagrass, Shallow Seagrass, Deep Edge, Shallow Edge, Deep 0 Spring Autumn Season
Figure 10. Average MaxN for King George whiting recorded by baited underwater stereo video at Mud Islands.
Marine Biophysical Assesment – King George whiting 16 15
10
N Max
5 Seagrass, Shallow Seagrass, Deep Edge, Shallow Edge, Deep 0
Spring Autumn
Season
Figure 11. Average MaxN for King George whiting recorded by underwater stereo video at Swan Island.
Marine Biophysical Assesment – King George whiting 17 Length At Eastern Beach, one individual of 238 mm was At Swan Island in spring, KGW in shallow edge measured in deep seagrass habitat. habitat were smaller than in deep edge habitat, KGW length at Grand Scenic ranged from 110 to ranging from 90 to 150 mm in length (Fig. 20), 160 mm in shallow seagrass in spring (Fig. 12). compared with 150 to 240 mm in length in deep A similar distribution occurred in shallow edge habitat (Fig. 21). This difference in length habitat with the addition of some smaller distributions was highly significant (KS test, individuals between 80 and 100 mm (Fig. 13). D=1, P<0.001) with no overlap in length ranges The difference in length frequency distributions (Figs 20, 21). The length range of KGW on between the two shallow habitats in spring was shallow edge habitat in autumn was 150 to 220 not significant (KS test, D=0.4, P=0.16). In mm (Fig. 22). autumn, KGW on shallow edge habitat ranged Length distributions amongst sites were from 60 to 120 mm together with a larger group compared for KGW on shallow edge habitat in ranging from 150 to 200 mm (Fig. 14). Only two autumn. KGW at Mud Islands (Fig. 17) were individuals were measured in shallow seagrass significantly larger than at Swan Island (Fig. 22) in autumn (Fig. 15), with one falling into each of (KS test, D=0.6, P=0.003), that in turn were the length groups identified for shallow edge significantly larger than at Grand Scenic (Fig. 14) habitat (Fig. 14). (KS test, D=0.906, P<0.001). 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).
Marine Biophysical Assesment – King George whiting 18 7
6
5
4
Number 3
2
1
0 0 0 0 0 0 0 0 50 60 70 80 90 00 30 40 50 10 60 20 30 4 1 11 12 1 1 1 160 170 18 190 200 2 220 230 240 250 2 270 280 29 30 310 3 3 3 35 Length (mm)
Figure 12. Length frequency distribution for King George whiting recorded by underwater stereo video at Grand Scenic in shallow seagrass habitat in spring.
6
5
4
3
Number
2
1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 60 7 8 9 00 3 70 80 9 0 3 40 70 9 1 20 50 1 11 12 1 14 150 160 1 1 1 2 21 22 2 2 250 260 2 280 2 300 3 3 330 340 350
Length (mm)
Figure 13. Length frequency distribution for King George whiting recorded by underwater stereo video at Grand Scenic in shallow edge habitat in spring.
Marine Biophysical Assesment – King George whiting 19 30
20
Number
10
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 60 7 80 90 0 10 2 4 7 0 2 3 5 70 8 3 1 1 1 130 1 150 160 1 180 19 2 210 2 2 240 2 260 2 2 290 300 310 320 3 340 35 Length (mm) Figure 14. Length frequency distribution for King George whiting recorded by underwater stereo video at Grand Scenic in shallow edge habitat in autumn.
1
Number
0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 60 7 80 9 0 10 2 30 4 6 8 00 20 40 5 60 7 80 9 1 3 50 1 1 1 1 1 150 1 170 1 190 2 210 2 230 2 2 2 2 2 2 300 3 320 3 340 3
Length (mm)
Figure 15. Length frequency distribution for King George whiting recorded by underwater stereo video at Grand Scenic in shallow seagrass habitat in autumn.
Marine Biophysical Assesment – King George whiting 20 3
2
Number 1
0 0 0 0 0 0 0 0 0 0 0 0 0 50 6 7 8 90 10 2 3 5 60 7 8 0 1 40 50 60 9 00 3 100 1 1 1 140 1 1 1 1 190 2 2 220 230 2 2 2 270 280 2 3 310 320 3 340 350 Length (mm)
Figure 16. Length frequency distribution for King George whiting recorded by underwater stereo video at Mud Islands in deep seagrass habitat in autumn.
6
5
4
3
Number 2
1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 50 60 8 90 2 30 4 70 80 9 0 1 3 5 6 7 8 0 1 2 30 4 50 70 100 110 1 1 1 150 160 1 1 1 2 2 220 2 240 2 2 2 2 290 3 3 3 3 3 3
Length (mm)
Figure 17. Length frequency distribution for King George whiting recorded by underwater stereo video at Mud Islands in shallow edge habitat in autumn.
Marine Biophysical Assesment – King George whiting 21 4
3
2
Number
1
0 0 0 0 5 60 70 80 90 50 20 100 110 120 130 140 150 16 170 180 190 200 210 220 23 240 2 260 270 280 290 300 310 3 330 340 350 Length (mm)
Figure 18. Length frequency distribution for King George whiting recorded by baited underwater stereo video at Mud Islands in shallow edge habitat in spring.
1.0
Number
0.0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 50 6 70 8 90 3 5 7 9 2 4 1 1 22 8 0 33 3 35 100 11 120 140 1 160 18 1 20 210 230 24 250 26 270 2 290 3 310 3 Length (mm)
Figure 19. Length frequency distribution for King George whiting recorded by baited underwater stereo video at Mud Islands in shallow edge habitat in autumn.
Marine Biophysical Assesment – King George whiting 22 4
3
2
Number
1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 50 6 7 80 90 30 6 7 8 10 10 11 12 1 14 150 1 1 1 190 20 21 22 23 24 250 260 270 280 290 300 3 32 33 34 35 Length (mm)
Figure 20. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in shallow edge habitat in spring.
3
2
Number 1
0 0 0 5 6 70 80 90 00 100 110 120 130 140 150 160 170 180 190 2 210 220 230 240 250 260 270 280 290 300 310 320 330 340 350
Length (mm)
Figure 21. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in deep edge habitat in spring.
Marine Biophysical Assesment – King George whiting 23 6
5
4
3
Number
2
1
0 0 0 0 0 0 0 0 0 0 0 0 00 1 2 30 60 7 80 9 00 10 3 4 50 60 70 80 10 20 40 5 5 6 7 8 90 1 1 1 1 140 150 1 1 1 1 2 2 220 2 2 2 2 2 2 290 300 3 3 330 3 3
Length (mm)
Figure 22. Length frequency distribution for King George whiting recorded by underwater stereo video at Swan Island in shallow edge habitat in autumn.
Marine Biophysical Assesment – King George whiting 24 Bellarine/Corio Bay = Swan Bay, Grassy Point, Otolith chemistry Grand Scenic, Eastern Beach; North = Kirks Point, Altona, Ricketts Point. Grouping 2: North = Kirks Point, Altona, Ricketts Point; South = Individual element:Ca ratios Grand Scenic, Corio Bay, Grassy Point, Swan Bay, Mud Islands, Blairgowrie, Rosebud) Post‐larval otoliths indicated for grouping 1 that there was a Variation in the element:Ca ratios of post‐larval significant overlap of otolith multi‐element otolith margins was significant among seagrass chemistry among the sampling regions, areas in Port Phillip Bay for Ba:Ca, Sr:Ca and particularly for the south and Bellarine/Corio Mn:Ca, but not for Mg:Ca and Zn:Ca (Fig. 23, regions (Fig. 25). For grouping 2, however, the Table 2). Ba:Ca was highest at Rosebud and overlap of multi‐element otolith chemistry Swan Bay and lowest at Grassy Point and between the north and south regions was less Ricketts Point (Fig. 23). Mn:Ca was highest at pronounced (Fig. 26). Kirk Point and Altona and lowest at Swan Bay Maximum likelihood simulations of the baseline and Blairgowrie (Fig. 23). Sr:Ca was highest at multi‐element otolith chemistry data for Swan Bay, Grassy Point and Rosebud, and grouping 1 indicated that the estimated generally similar across the other sites (Fig. 23). contribution from simulations was the same as There were no clear regional (i.e. north, south, the actual contribution for the north region with Bellarine/Corio) trends in variation of individual a reasonable precision (SD = 11%) (Table 3). otolith element:Ca ratios, with most of the However, for the south and Bellarine/Corio variation occurring at the smaller scale, i.e. regions, the estimated contributions from between adjacent sites (Fig. 23). simulations were 6% lower and higher 1‐year‐old otoliths respectively for these two regions, and precision was poor (SD = 15 and 21% respectively) (Table Samples of one year old fish could only be 3). obtained from three areas in southern Port Phillip Bay (Swan Bay, Corio Bay and Grassy Maximum likelihood simulations of the baseline Point). Variation of Mn:Ca, Ba:Ca, and Sr:Ca in multi‐element otolith chemistry data for the post‐larval regions of the 1 year old otoliths grouping 2 (north v south) indicated that the was significant among the three sites (ANOVA, estimated contributions from simulations were Mn:Ca, Sr:Ca p<0.001, Ba:Ca p<0.05). Further, for close to the actual contributions for the north these element:Ca ratios, the patterns of variation and south regions (estimated 2% higher and among sites were similar to those observed in lower than actual for north and south regions the post‐larval otolith margins sampled from respectively) with a reasonable precision (SD = these sites 1 year prior (Fig. 24). Similar to the 9% for both regions) (Table 4). post‐larval stages, variation among sites was not Based on the above results we conducted the significant for Zn:Ca (ANOVA, p>0.1), but was maximum likelihood mixed sample composition significant for Mg:Ca (ANOVA, p<0.05). Mg:Ca analyses of 1 year old otoliths using baseline ratios measured in the post‐larval otoliths were grouping 2 only (north and south) to achieve the generally higher than in the post‐larval regions most accurate and precise estimates. The mixed of the 1 year old otoliths (Fig. 24), possibly sample bootstrap analysis indicated with a very indicative that sampling positions in the 1 year high precision (< 1% SD) that the 1 year old old otoliths were not perfectly matched with the samples from Corio Bay, Grassy Point and Swan post‐larval sizes sampled the previous year (e.g. Bay were 100% derived from post‐larvae that Hamer et al. 2003). had settled in seagrass beds of southern Port Phillip Bay (Table 4). 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;
Marine Biophysical Assesment – King George whiting 25
150 2,000
) -1 ) -1 100
1,000
50
Magnesium:Ca (µmol.mol Strontium:Ca (µmol.mol
0 0 10 3
)
-1 ) -1 2
5
1
Barium:Ca (µmol.mol Manganese:Ca (µmol.mol
0 0
3 Altona Altona Rosebud Rosebud Kirk Point Kirk Kirk Point Kirk Corio Bay Corio Bay Swan Bay Swan Swan Bay Swan Mud Island Mud Island Blairgowrie Blairgowrie ) Grassy Point Grassy Point Grassy -1 Grand Scenic Grand Scenic Ricketts Point Ricketts Point 2 Bellarine/Corio Bay South North
1 South
Zinc:Ca (µmol.mol Site / region groups
0
Altona Rosebud Kirk Point Kirk Corio Bay Swan Bay Swan Mud Island Blairgowrie Grassy Point Grand Scenic Ricketts Point
Bellarine/Corio Bay South North
South
Site / region groups
Figure 23. Element:Ca ratios (± SE) of margins of post‐larval King George whiting otoliths sampled from 10 seagrass beds in Port Phillip Bay.
Marine Biophysical Assesment – King George whiting 26 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.
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*
KP = Kirk Point, SB = Swan bay, CB = Corio Bay, RP = Ricketts Point, A = Altona, B = Blairgowrie, RB = Rosebud
Marine Biophysical Assesment – King George whiting 27
2,500 5 10 ) Post-larvae ) -1 ) -1 4 -1 1 year old 2,000 mol.mol 3 µ µmol.mol ( ( 5 2 1,500
Barium:Ca (µmol.mol
Strontium:Ca 1
Manganese:Ca
0 1,000 0
Corio Bay 1+ Corio Bay 0+ Corio Bay 1+ Corio Bay 0+ Corio Bay 0+ Corio Bay 1+ Swan Bay 1+ Bay Swan Swan Bay 0+ Bay Swan 1+ Bay Swan Swan Bay 0+ Bay Swan Swan Bay 0+ Bay Swan 1+ Bay Swan Grassy Point 0+ Grassy Point 1+ Grassy Point 1+ Point Grassy Grassy Point 0+ Point Grassy Grassy Point 0+ Grassy Point 1+ 150 3
) -1
) -1 100 2
50 1
Zinc:Ca (µmol.mol
Magnesium:Ca (µmol.mol 0 0
Corio Bay 0+ Corio Bay 1+ Swan Bay 1+ Bay Swan Swan Bay 0+ Bay Swan Corio Bay 0+ Corio Bay 1+ Swan Bay 1+ Bay Swan 0+ Bay Swan Grassy Point 0+ Point Grassy 1+ Point Grassy Grassy Point 0+ Grassy Point 1+
Site / age group
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.
Marine Biophysical Assesment – King George whiting 28
5 Mn:Ca Ba:Ca Sr:Ca
3
1
Canonical variate 2 variate Canonical
-1
Ba:Ca North Mn:Ca Sr:Ca South -3 Bellarine/Corio -3 -1 1 3 5 Bay Canonical variate 1
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.
North South
-3 -2 -1 0 1 2 Canonical variate 1 Ba:Ca Sr:Ca
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).
Marine Biophysical Assesment – King George whiting 29 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.
Baseline (0‐age post Actual MLA estimated Standard deviation larvae) group contribution to contribution to of estimation (%) simulated mixture simulated (%) mixture (%)
North (n=47) 31 31 11 (Altona, Kirk Point, Ricketts Point) South (n=45) 30 24 15 (Blairgowrie, Mud Islands, Rosebud)
Bellarine/Corio bay 39 45 21 (n=59)
(Corio Bay, Grand Scenic, Grassy Point, Swan Bay)
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.
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 Actual MLA Standard MLA composition of Standard deviation post‐larvae) group contributi estimated deviation 1‐year olds (%) of estimation (%) on to contribution of simulated to simulated estimation mixture mixture (%) (%) (%)
North (n=47) 31 33 9 0 <1 (Altona, Kirk Point, Ricketts Point)
South (n=104) 69 67 9 100 <1 (Blairgowrie, Corio Bay, Grand Scenic, Grassy Point, Mud Islands, Rosebud, Sway Bay)
Marine Biophysical Assesment – King George whiting 30 Discussion
KGW of about 1 year age, and length of 80–160 Underwater Stereo Video mm in length, were common both within shallow Stereo video analysis showed distinct patterns in seagrass beds and edge habitat at the Grand spatial, temporal and depth distribution as well Scenic site and also shallow seagrass edge habitat as habitat use in KGW. Distinct patterns were at Swan Island. also observed in size distributions between sites and depths. There was a general pattern of larger, older juvenile KGW occurring in deep habitats and The most common habitat juvenile KGW were also in habitats at Mud Islands. KGW observed in was shallow seagrass edge habitat. approximately 18 months old and 150–220 mm in This is consistent with previous studies on young length were recorded in shallow edge habitat at juvenile KGW using fine mesh seine nets in Port Swan Island and Grand Scenic, but were also Phillip Bay. Post‐larvae (approx 20 mm in length) common at Mud Islands in this habitat. Larger settled in shallow (<1 m deep) seagrass habitat in juvenile KGW, 2 to 3 years of age and ranging in the spring (Jenkins and Black 1994; Jenkins and length to 30 cm, were recorded in deep edge Wheatley 1998; Hutchinson et al. 2011), however, habitat at Swan Island, as well as shallow edge after 4–5 months there was a shift to unvegetated habitat at Mud Islands. The largest individuals of habitat within the vicinity of seagrass or reef‐ over 30 cm in length were recorded in deep algae (Jenkins and Wheatley 1998). In some areas seagrass habitat at Mud Islands. such as Swan Bay, small post‐larvae are found on unvegetated mud habitat when nearby seagrass A preliminary stereo underwater video study on is very dense (Jenkins et al. 1997b; Jenkins and KGW at Mud Islands (Jenkins 2010) recorded Hamer 2001). In general, the dependence of juveniles in shallow edge and seagrass habitat. KGW on seagrass appears mainly related to food, Like the present study, TiV was highest in either through feeding directly on epifauna shallow edge habitat; however, MaxN in the within seagrass beds or taking advantage of earlier study was highest in shallow seagrass elevated food levels on unvegetated habitat that (Jenkins 2010). The size range of juvenile KGW is enriched with seagrass detritus from nearby was greater in the earlier study, ranging from beds (Jenkins and Hamer 2001). Robertson (1977) less than 100 mm to over 350 mm (Jenkins 2010). also found a shift in KGW from seagrass habitat This indicates that young juveniles had settled to mudflat after 4–5 months post‐settlement in directly into seagrass at Mud Islands and/or that Western Port. This corresponded with a shift in young juveniles had migrated from coastal areas the diet to include benthic infauna such as at < 1 year of age. Presence of newly‐settled KGW polychaete worms and ghost shrimp (Robertson has been recorded in shallow seagrass at Mud 1977). Studies using stable isotopes have shown Island (Hutchinson et al. 2011). A key finding of that KGW have a very strong dependence on the preliminary study was that while juvenile seagrass through the food chain, even though KGW were common on unvegetated habitat at this could be an indirect relationship where the edge of seagrass, they were never recorded seagrass detritus provides the plant food base in from unvegetated habitat distant (> 200 m) from unvegetated habitat (Longmore et al. 2002; seagrass (Jenkins 2010), presumably because of a Hindell et al. 2004). lack of enrichment of the sediment by seagrass detritus and therefore reduced benthic Our study shows that shallow seagrass edge productivity. habitat continues to be important for juvenile KGW over the first few years of growth. The Our results were also broadly consistent with a smallest KGW recorded in this study were from previous underwater video study in shallow Grand Scenic in autumn, and at a size of 60–120 seagrass habitat at Blairgowrie (Smith et al. 2011). mm would have been approximately 6 months This study also found older juvenile KGW were old. Jenkins and Wheatley (1998) found a high most abundant in seagrass edge habitat. abundance of a similar size range of KGW in Interestingly, 0+ age whiting, observed between autumn from a nearby site at Clifton Springs, December and February, were most abundant on suggesting this area of the Geelong Arm may be seagrass, supporting observations from seine important for these young fish. In the spring, netting that KGW are closely related to seagrass
Marine Biophysical Assesment – King George whiting 31 for the first few months after entering the bay in influenced by local terrestrial point source the spring but move onto unvegetated edge inputs, water depth/temperature, tidal habitat after four to five months in the late flows/flushing rates and potentially sediment summer/autumn (Smith et al. 2011). chemistry (Forrester and Swearer 2002; Elsdon and Gillanders 2004; Hamer and Jenkins 2007; Like many sampling methods, there are inherent Elsdon et al. 2008). biases in underwater video sampling that can affect results. TiV and MaxN suggested that While post‐larval otolith chemistry varied juvenile KGW were most abundant at Grand significantly between some seagrass beds, across Scenic and least abundant at the Corio Bay site the 10 sample sites there was considerable (Eastern Beach). The video from the Corio Bay overlap of the element:Ca ratio data. This limited site, however, had generally poorer visibility our ability to construct clear baseline elemental than other sites and this may have biased the signatures or “tags” for individual seagrass beds. results. Another factor affecting results was that Broad regional groupings of sites, however, some video recordings in deep seagrass at Swan resulted in more powerful discrimination of Island could not be analysed due to long seagrass otolith elemental chemistry baseline signatures. stems blocking the view, leading to relative In particular, grouping the sites as ‘north’ and under‐sampling of this habitat. ‘south’ regions provided a reliable baseline data set with which to determine the composition of We tested baited video as a possible way to older KGW. increase sample sizes, particularly for estimating size composition of juvenile KGW in video Despite the inability to develop baseline otolith recordings, however there was no discernable elemental signature at smaller scales, seagrass effect of bait on number of KGW detected. The beds in northern and southern Port Phillip Bay bait was successful in attracting some other fish are subject to different climate related risks and groups to the field of view, most notably anthropogenic impacts. Seagrass beds in leatherjackets. The use of baited video in studies northern Port Phillip Bay, such as Kirk Point, comparing habitat use is problematical in any Altona and Ricketts Point are relatively small in case as individuals may be attracted from area, generally restricted to shallower waters and habitats a considerable distance away. In general subject to greater levels of anthropogenic we would not recommend the use of baited disturbance, including freshwater inputs and video for studying juvenile KGW. chemical pollutants, than beds in the southern bay. As such, determining the relative Otolith chemistry importance of the northern seagrass beds to There was significant spatial variation in otolith supporting recruitment of KGW in Port Phillip chemistry of post‐larval KGW sampled in Bay is important. seagrass beds around Port Phillip Bay. Variation Sampling of older KGW of the same cohort as the was most notable for barium, manganese and post‐larvae was necessarily restricted to 1 year strontium. These elements have been found to old fish due to the time scale of the project. commonly show spatial variation in otoliths of a Sampling of 1 year old fish was made difficult variety of species and geographic locations, and due to the timing of this project, corresponding are regularly used as natural tags in studies with a year of poor recruitment of juvenile KGW aimed at determining nursery origins and to Port Phillip Bay. This meant that it was connectivity among fish populations (Campana difficult to collect enough fish from a range of 1999; Thorrold et al. 2001; Gillanders 2002; Elsdon sites around the bay to do a full bay‐wide et al. 2008; Hamer et al. 2011). population analysis. Future sampling/analyses of Spatial variation of individual element:Ca ratios this cohort at older ages when recruited to the occurred at the local scale of seagrass beds and fishery (i.e. 2–3 year age) is recommended, and this could involve recreational and commercial did not show clear regional (i.e. north, south, Bellarine) trends. Ba:Ca and Mn:Ca in particular fishers, allowing much greater and cost‐effective showed highly significant local‐scale variation. sampling effort. For example, Ba:Ca levels for post‐larval otoliths Maximum likelihood composition analysis of the from Rosebud and Swan Bay were elevated 1 year old samples from the three sites in relative to other sites, and Mn:Ca was elevated at southern Port Phillip Bay (Corio Bay, Grassy Altona and Kirk Point relative to other sites. Point, Swan Bay) clearly indicated no These local‐scale effects likely related to variation contribution from northern bay seagrass beds to of local water physico‐chemical properties populations at these southern seagrass areas.
Marine Biophysical Assesment – King George whiting 32 Furthermore, comparisons of the individual can be limited by nutrients, particularly nitrogen, element:Ca ratios between the post‐larval stages in PPB (Bulthuis et al. 1992). Conversely, it is well and the post‐larval otolith regions of the 1 year known that excessive nutrients can cause olds (particularly for Ba:Ca) for these three sites seagrass dieback due to smothering by fast indicated close similarity of both the values of growing algal epiphytes (Bjork et al. 2008). the ratios and the patterns of variation among the High temperatures and exposure are also sites. This suggests that the 1 year old fish had detrimental to seagrasses. In Western Port, a remained resident in the local area of capture for combination of smothering of Zostera leaves by their first year of life, and supports the sediment from the catchment blocking light, observations from the video sampling that together with hot weather and low tides shallow areas of seagrass beds are preferred associated with an intense El Nino event is habitat for KGW for their first 1–2 years of life. thought to have initiated the seagrass die‐off. This mechanism is less likely in PPB where Vulnerability of juvenile King shallow mud banks are not nearly as extensive as George whiting to climate change in Western Port; but potentially could happen in The most likely impact of climate change on Swan Bay and Corner Inlet, where extensive mud juvenile KGW will be mediated through effects banks do occur. on seagrass. The preferred habitat of juvenile Historical seagrass mapping has shown that KGW appears to be a mosaic of patchy seagrass seagrass beds in southern PPB and the southern and unvegetated habitat, with seagrass detritus Geelong Arm increased in area over 50 years providing enriched feeding on the sand/mud at until the late 1990s, however the decadal drought the seagrass edge. Unvegetated habitat some that began at this time was associated with a distance away from seagrass does not appear to decline in seagrass in these areas. The primary support juvenile KGW. hypothesis for the mechanism behind this decline The importance of seagrass to juvenile KGW was is that reduced freshwater flows during the clearly demonstrated in Western Port in the mid drought resulted in nutrient limitation of 1970s when a major loss of 70% of seagrass cover seagrass. This hypothesis is supported by occurred. The commercial catch of KGW up until increased seagrass cover recorded over the past this point had shown an increasing trend in two years of La Nina above average rainfall. parallel with the catch in Port Phillip, but after Different historical patterns are apparent for the loss the catch declined while the Port Phillip Swan Bay and the northern Geelong Arm where catch continued to increase (Jenkins 2010). seagrass beds are more directly affected by catchment inputs (freshwater and nutrients) and Climate changes impacts on seagrass are likely to are less likely to be nutrient limited. depend on depth, as will the flow‐on impacts to juvenile KGW. Shallow habitats appear to be the Climate change will have a number of potential most important for younger juvenile KGW. Older impacts on seagrass (Connolly 2009). Increasing juveniles occur in deeper habitat but can also sea level will lead to a reduction in shallow utilise shallow habitat, such as at Mud Islands. seagrass beds unless there is corresponding colonisation shorewards. In some cases, however, In terms of spatial distribution, the youngest shoreward colonisation will not be possible due juveniles were collected in the Geelong Arm, to man made barriers (break walls etc.) or to which is also known to be a primary area for unsuitability of the substrate (Short and Neckles settlement of post‐larvae. Seagrass coverage in 1999; Connolly 2009). the Geelong Arm may therefore be particularly significant for young juvenile KGW. Climate change will also lead to more intense storm and runoff events, causing direct effects on The key seagrass species forming habitat for seagrass through physical disturbance and also KGW in PPB is the sub‐tidal seagrass Zostera reduced light through increased turbidity nigricaulis. Seagrass distribution and abundance (Connolly 2009). Areas of seagrass most is driven primarily by light and nutrients. susceptible to these effects will be those near Seagrasses have relatively high light catchment inputs such as Swan Bay, and requirements compared to other aquatic plants northern Port Phillip Bay, Western Port and such as algae. This is why the deepest seagrass Corner Inlet. Shallow seagrass beds will be the beds in PPB occur towards the entrance, where most affected by direct disturbance while deeper waters are clearest. Seagrasses also tend to have beds will be more affected by reduced light. defined nutrient requirements. Seagrass growth
Marine Biophysical Assesment – King George whiting 33 Seagrass in southern Port Phillip Bay may be abundances of prey organisms such as affected by long‐term decreases in freshwater polychaete worms. One pertinent question in runoff under climate change, similar to the relation to climate change impacts is whether decreased runoff and associated increased KGW juveniles are specifically dependent on salinity seen during the extended drought in the seagrass detritus or whether other plant detritus, 2000s. The decreased runoff will mean reduced such as from algae, could compensate for nutrients reaching the Geelong Arm and seagrass loss. southern Port Phillip Bay that could cause Stable isotope ratios of elements such as nitrogen seagrass decline through nutrient limitation. This can be used to identify the plant basis of food would have a similar effect on both shallow and chains because they can provide a unique deep seagrass beds. signature for different plant types supporting the Shallow seagrass beds may also be vulnerable to diet. In theory, this method could be used to increased air and water temperatures under determine the dependency of juvenile KGW on climate change at extreme low tides (Walker seagrass to support their food chain, and 2012). This risk is of greatest concern where therefore their vulnerability to seagrass loss extensive shallow mud banks occur, such as through climate change. Swan Bay, Western Port and Corner Inlet. Seed funding was provided in this project to A potential positive effect of climate change on investigate the potential for using stable isotopes seagrass is the predicted increased in dissolved of seagrass and other plant sources to investigate carbon dioxide that will be available for the diet dependency of juvenile KGW on photosynthesis (Connolly 2009). The extent of seagrass. Samples were collected from around this benefit is highly uncertain as the extent of Port Phillip Bay of seagrass and other plant inorganic carbon limitation of Zostera growth and sources such as algae. Analysis indicated that productivity is relatively unknown for Victorian stable isotopes of nitrogen, usually used to seagrass systems. identify plant sources, varied greatly with locality in Port Phillip Bay. This result Although there are significant uncertainties, on complicates the use of stable isotopes in a balance the evidence suggests that climate potential future study on dietary plant sources of change will have a detrimental effect on seagrass, juvenile King George whiting, and suggests that particularly in shallow habitats. This has stable isotopes of carbon and sulphur may also significant implications for juvenile KGW growth need to be analysed to provide a reliable and survival into the future, given the previous discrimination of seagrass based diets from those research showing that seagrass is a key based on other plant types. settlement habitat for post‐larvae (Jenkins and Wheatley 1998), and that results of this study A current major study funded by the Department suggest that shallow seagrass edge habitat is of Sustainability and Environment on seagrass critical for young juvenile KGW. Impacts will resilience in Port Phillip Bay will provide further vary depending on location. For example, the information on the potential changes to seagrass southern Geelong Arm was an important area for under climate change. The study will use a young juvenile KGW in this study and under combination of field experiments, numerical climate change seagrass in this area could be modelling and genetics to investigate the affected by nutrient limitation due to freshwater resilience of seagrass to the effects of flows. Alternatively, seagrass in important environmental change, particularly changes to nursery areas such as Swan Bay, northern catchment inputs of nutrients and sediments. The Western Port and northern Corner Inlet may be results of this study should help refine, and give more affected by intense storm and runoff greater confidence to, our predictions of the events, as well as more extreme temperatures. trend in seagrass abundance in Port Phillip Bay under climate change. In turn, this will improve Future Research confidence in predictions of the effects of climate The importance of seagrass edge habitat to KGW change on the long‐term trend in KGW abundances in Port Phillip Bay. 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
Marine Biophysical Assesment – King George whiting 34 Conclusions
dams etc that would otherwise contribute to Improving the resilience and runoff and nutrient input. adaptation of King George A key to improving seagrass resilience through whiting to climate change catchment management is to include these The population levels of King George whiting in marine assets in catchment management Victorian Bays and inlets result from a planning. Such planning requires accurate combination of larval supply from distant mapping of seagrass beds so that spatial spawning grounds to the west, and juvenile planning can be undertaken and potential survival largely dependent on adequate cover of impacts considered. seagrass habitats in bays and inlets (Jenkins The proper management and control of activities 2010). Like seagrass cover, larval supply is likely that can cause direct physical disturbance of to be affected by climate change, especially in seagrass beds is another crucial area to improve relation to water temperatures in Bass Strait seagrass resilience (Bjork et al. 2008). Such affecting larval growth, and the strength of the activities can include the development of coastal Leeuwin Current affecting larval dispersal infrastructure (breakwalls, marinas etc), channel (Jenkins 2010). Effects of climate change on larval dredging activities, and physical damage caused supply are largely beyond the influence of any by boats (anchoring, propeller scarring) and management actions, however, in the case of moorings. juvenile survival and seagrass, there are a number of management actions that can be Marine environmental management can assist undertaken to improve the resilience and seagrass resilience to climate change by adaptation of King George whiting to climate protecting areas of seagrass that have shown change. resilience to climate variation in the past and are likely to act as refuge areas in the future. These The resilience of seagrass to climate change will areas can be identified for Port Phillip Bay based be improved where seagrass health is not also on historical seagrass mapping (Ball et al. 2009). compromised by anthropogenic stressors; Areas of seagrass that show high production of particularly those that affect water quality and seeds that would contribute to colonisation of light availability (Bjork et al. 2008). In this case, other areas should also be considered for catchment management practices will be crucial management protection. In the case of resilience to support seagrass health and resilience to of King George whiting to climate change, any climate change. protection by marine managers of seagrass Catchment management can improve land‐use habitat in key juvenile distribution areas such as practices to reduce nutrient and sediment loads those identified in this study would be of in run‐off, as well as reducing where possible the considerable benefit. use of pesticides and herbicides (Bjork et al. 2008). Seagrass restoration may be considered as a This management may be particularly important strategy of final resort, but it is costly and the for Swan Bay, which we have shown is a success is generally low and variable (Orth et al. significant source of juvenile KGW. The use of 2006). In general, if conditions are not suitable for stormwater sediment traps and the effective natural seagrass growth, artificial planting will treatment of effluent are also key management also tend not to be successful. In the few cases priorities, as is the provision of buffer zones of where there has been some success, the process is undisturbed land along stream edges together very expensive and the area restored is relatively with the protection of coastal wetlands that act as small and may not be of benefit to King George natural filtration systems (Bjork et al. 2008). whiting resilience to climate change. 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,
Marine Biophysical Assesment – King George whiting 35 Informing fishery management areas, they can strongly advocate for this management, either directly between arrangements of future King management agencies or through education of George whiting population trends industry and the public as to the importance of Predicting the future trend of the King George these areas that will increase pressure for whiting population has significant uncertainty protection. because of the dependence of fishery recruitment Management of the King George whiting fishery on both larval supply and juvenile survival. The will need to be adaptive, and ideally would predictions for larval supply under climate include a harvest strategy that sets limits, targets change are uncertain depending on the main and decision rules. For KGW, this strategy could factors influencing larval dispersal and survival be largely based on monitoring of both post‐ (Jenkins 2010). Climate change may be positive larval settlement and seagrass cover to provide for larval supply if increased water temperatures an estimate of fishery recruitment in the ensuing in Bass Strait lead to higher larval growth rates years. and survival (Jenkins and King 2006), or negative for larval supply if the predicted weakening of Monitoring of post‐larval KGW settlement in the Leeuwin current leads to less dispersal of PPB has now been undertaken for 14 years and larvae to central Victorian Bays (Jenkins 2010). provides a reliable index of larval supply for this Even if larval supply is relatively robust, bay. Into the future this index will give a leading however, climate change is expected to lead to indicator of any effects of climate change on the decreased seagrass coverage that will reduce levels of post‐larval settlement. Monitoring fishery recruitment through decreased juvenile seagrass cover in central Victorian bays has also growth and survival. A major loss of seagrass been undertaken over the past decade, and would have very significant consequences for because shallow seagrass habitat is most critical, fishery recruitment as has previously been seen monitoring can be relatively straight forward in Western Port (Jenkins 2010). Overall, the best based on aerial imagery. Again this information estimate would be that there will be a long‐term would provide a leading indicator of possible decline in fishery recruitment for KGW under trends in seagrass cover under climate change climate change in central Victorian Bays, albeit that would affect juvenile survival. Information with significant uncertainty. from these monitoring programs would then be fed back into the harvest strategy in relation to As mentioned, reducing other stressors on pre‐set decision rules. 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
Marine Biophysical Assesment – King George whiting 36 Acknowledgements
We thank David Hatton and Andrew Brown for We wish to acknowledge the funding for this assistance with field sampling. We also thank work provided by Future Farming Strategy Tim Kenner for assisting with the video analysis. Initiative on climate change adaptation through Fisheries Victoria.
Marine Biophysical Assesment – King George whiting 37 References
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