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The Environment Institute
                       Where ideas grow




   Assoc. Prof. Bronwyn Gillanders
   Giant Australian cuttlefish: a globally unique species
   under threat?
Bronwyn Gillanders
   Population structure
     Melita de Vries
     Steve Donnellan
     Mike Gardner

   PhD/Hons students
     Jackie Dupavillon
     Nick Payne
     Leanne Trott
   Giant Australian cuttlefish & the issues

   Population structure

   Potential impacts of desalination brine
Weighs up to 13 kg
                              Grows up to 1 m
                              Lives 1-2 years




Photo: Kaufmann Productions
Ningaloo Reef
                Moreton Bay
Adelaide
8 km of coastline
Winter – May to August
Rocky reef




                         Habitat map: SA DEH


8 km of coastline
Winter – May to August
Males larger than
females
High
male:female sex
ratio
Males ‘battle’ for
females
Females may or
may not mate
with a male
Small males have
other strategies
(e.g. sneakers)
Shear numbers
impressive


Photos: Fred Bavendam
   Skewed towards males (4:1) based on counts
    of each sex
   Assumes individuals on breeding aggregation
    similar amounts of time
   Population sex ratio may be 1:1 with sexes
    spending different amounts of time on the
    breeding aggregation
   Predict males spend more time than females
Males   n = 13
                     Females n = 6




Payne, PhD project
Residence time                                                           Residence period
                                     35                                                                         60
   Mean Residence Time (days ± SE)




                                                                            Mean Residence Period (days ± SE)
                                     30                                                                         50

                                     25
                                                       *                                                                         *
                                                                                                                40
                                     20
                                                                                                                30
                                     15
                                                                                                                20
                                     10

                                      5                                                                         10

                                      0                                                                         0

                                              Males         Females                                                      Males       Females


                                          Male:Female = 3.7 : 1                                                      Male:Female = 4.6 : 1
                                             Population composed of equal numbers of males & females
Payne, PhD project
300

                 270
                         Renewable moratorium on
                 240     fishing introduced in 1998

                 210     Now permanently closed to
                         taking of cuttlefish
Catch (tonnes)




                 180
                         Need to establish long-term
                 150     scientific based management
                         plan
                 120

                  90

                  60

                  30

                   0
                       1984
                       1985
                       1986
                       1987
                       1988
                       1989
                       1990
                       1991
                       1992
                       1993
                       1994
                       1995
                       1996
                       1997
                       1998
                       1999
                       2000
                       2001
                       2002
                       2003
                       2004
                       2005
                       2006
                       2007
                                   From: SARDI Catch Data
   BHP Olympic Dam expansion
     Preferred option: coastal desalination plant in USG
     Point Lowly preferred location (18 ha site)

   Bulk commodities export facility
     Feasibility study by Spencer Gulf Port Link Consortium
      (SGPLC), led by Flinders Ports
     7-13 million tonnes of ore could be exported through new
      facility
   Need to understand
    population structure for
    appropriate spatial
    management
   Demographic processes
    & population dynamics
    may vary



                               From: Keough & Swearer (2007)
   Strongest inferences use a suite of
    techniques
   Genetic & phenotypic approaches

   Might not necessarily expect concordance
    among approaches
     Evolutionary history vs. environmental variation
     Spatial resolution varies by technique
     Genetic approaches may be more conservative
   Marine populations
     Genetic homogeneity over large distances
     High dispersal life history characteristics
   Squid
     High levels of gene flow among populations
   Cuttlefish
     Sepia officinalis – extensive population structuring
   Determine population structure of giant
    Australian cuttlefish using a multidisciplinary
    approach
     Molecular (microsatellite DNA markers)
     Morphometrics
     Statolith chemistry


   Investigate spatial & temporal variation in
    population structure
   Microsatellite genotyping

   12 microsatellite loci screened per individual
     Kassahn et al. (2006) Marine Biology
     Wheaton et al. (2007) Molecular Ecology Notes
   Temporal variation
     South Australia
     Five yrs between 1998 & 2006
   Spatial variation
     18 sites across Australia
Ningaloo                                           Moreton
                                                                                           Bay
   Breeding
                               1998                                            QLD
   aggregation                 2000
                               2004
                                                           WA
        Whyalla                2005                              SA
                               2006                                                            18
                                                1                                   NSW
                                                                4 5                          17
                                                                                            16
                                                            3         6                    15
                                      2004             2                      VIC
                          Wallaroo    2005
                                                                                      14
                                                                                13
       Spencer
       Gulf                                                           Bass Strait
                            GSV
                                      Glenelg   1998
                                                1998
Edithburg                             Aldinga   2005
                 Cape
2005
                 Jervis       2005
                              2006
-20500
                                                   Bayesian clustering approach

                                                   Triplicate runs for 1 (panmixia) to 6
               -21500                              populations
Ln Pr(X | K)




                                                   Used admixture model
               -22500
                                                   Assumed correlated alleles across
                                                   populations
               -23500
                                                   Examined each of K populations
                                                   further to detect sub-population
               -24500                              structure
                        1   2   3    4   5    6
                        K, number of populations   STRUCTURE
Q
                             Estimated membership coefficients




                                               0.00
                                                      0.20
                                                             0.40
                                                                    0.60
                                                                           0.80
                                                                                  1.00
                               Whyalla 1998




                               Whyalla 2000




Whyalla
                               Whyalla 2004



                               Whyalla 2005




Breeding aggregation
                                Whyalla 2006



                              Wallaroo 1998


                              Wallaroo 2005




Wallaroo
Spencer Gulf
                             Edithburg 2005



                            Cape Jervis 2005




                            Cape Jervis 2006
                                                                                         Shows overall population structure & individual assignment




                            Aldinga/Myponga
                                  1998
          Gulf St Vincent




                            Aldinga/Myponga
                                  2005
                                                                                         Length of each line proportional to estimated membership in each group




                               Glenelg 1998

                                western AUS
                                 1998-2006
Vic
WA




                                   VIC 2002

                                     NSW
                                   2002/2003
          NSW
Q
                                            Estimated membership coefficients




                                                             0.00
                                                                    0.20
                                                                           0.40
                                                                                  0.60
                                                                                         0.80
                                                                                                1.00




                         Bay
                                                Jervis Bay




                         Jervis
                                                Jervis Bay

                                               Wollongong

                                               Wollongong

                                               Wollongong

                                               Wollongong
                                               Wollongong

                                               Wollongong

                                               Wollongong
                                               Wollongong
                                               Wollongong




                            Wollongong
                                               Wollongong
                                               Wollongong

                                               Wollongong




Central & Southern NSW
                                               Wollongong

                                               Wollongong

                                               Wollongong
                                               Wollongong

                                                Newcastle

                                                Newcastle

                                                Newcastle

                                                Newcastle
                            Newcastle




                                             Coffs Harbour
                                             Coffs Harbour

                                             Coffs Harbour

                                             Coffs Harbour

                                             Coffs Harbour
                                             Coffs Harbour

                                             Coffs Harbour
                                             Coffs Harbour
                            Coffs Harbour



Northern NSW




                                             Coffs Harbour
                                             Coffs Harbour

                                             Coffs Harbour
   Spatial information – sampling location
   1 to 10 populations (n=5 replicate runs)

 Fixed K at modal value to estimate assignment of
  individuals to populations (n=10)
 Continued hierarchical analyses to detect
  subpopulation structure
 GENELAND
Population 3
                       Population 5




Population 1   Population 4            Population 2
South Australia

    Breeding aggregation
                           Population 5



                                     Contact zone




Population 4

               100 km
 28 measurements per individual

 Removed allometric effects of body
size

 Sexually dimorphic  sexes analysed
separately (n= 173 females & 342 males)

 No difference in size among years 
pooled years
5                                         Breeding aggregation
                                                                    GSV & Southern SG
                          3                                         Western SA
Discriminant function 2




                          1                                       90% correctly classified

                                                                  3 variables used for classification
                          1
                                                                  3 variables important: cuttlebone
                                                                  width & 2 beak parameters
                          3

                          5
                           -5    -3       -1       1      3   5
                                Discriminant function 1
                                                                        LRL                     UHL
7                                               Breeding aggregation
                                                                          GSV & Southern SG
                                                                          Western SA
Discriminant function 2




                          3
                                                                        90% correctly classified

                                                                        8 variables used for classification

                          -1                                            3 beak parameters contribute to
                                                                        differences




                          -5
                           -5.0     -2.8    -0.6     1.6    3.8   6.0
                                  Discriminant function 1
Dissolved trace    Uptake by      Statolith
   elements       cephalopod   incorporation
Prehatchling                                                                                   Hatchling
Sr:Ca statolith (mmol mol-1)




                                                                                                           Sr:Ca statolith (mmol mol-1)
                                              35                                                                                                       35
   Sr:Ca prehatchling statolith (mmol mol )




                                                                                                                                                       30
                                         -1




                                              30




                                                                                                               Sr:Ca hatchling statolith (mmol mol )
                                                                                                                    -1
                                              25                                                                                                       25


                                              20                                                                                                       20


                                              15                                                                                                       15


                                              10                                                                                                       10


                                               5                                                                                                        5


                                               0                                                                                                        0
                                                   0    5      10      15      20      25        30   35                                                    0    5      10     15    20     25       30   35
                                                                                            -1
                                                       Sr:Ca seawater (mmol mol-1)
                                                           Sr:Ca prehatchling seawater (mmol mol )
                                                                                                                                                            Sr:Ca seawater (mmolmol- ) -1)       1
                                                                                                                                                                   Sr:Ca hatchling seawater (mmol mol


  Trott, Hons thesis
5                                    Breeding aggregation
                                                               GSV & Southern SG
                                                               Western SA
Discriminant function 2




                          3

                          1                                    Mg:Ca, Sr:Ca & Ba:Ca

                                                               Discriminant Function Analysis
                          -1                                   All years – 77% correctly classified
                                                               2004 – 78% correct
                                                               2005 – 79% correct
                          -3                                   2006 – 83% correct

                          -5
                            -7        -3          1        5
                                 Discriminant function 1
   Not one panmictic population
   Evidence for 5 populations across species range
   Breeding aggregation differs from elsewhere

   Evolutionary & ecological implications
     Possibly incipient species
     Adaptive divergence along an environmental
      gradient
     Recent & rapid differentiation
Ocean again at ~ 7KYA




                        From: Andrew Hugall
 Mating behaviour differs
 Physiological tolerance & condition in relation to
  temperature & salinity
  ▪ Two populations may be prevented from significant overlap due to
    differing tolerances
 Are individuals from two populations able to mate, are
  eggs viable, are offspring fertile
  ▪ Testing degree of reproductive isolation
 Determine degree of genetic isolation – genome wide
  screening
 Ecological implications of morphological differences
Intake pipe



                                               Proposed locations

           Breeding area

                                           Out take pipe
  320 ML SW/day            120 ML FW/day via
       from USG;           320 km pipeline
  Salinity >40 ppt


   200 ML SW/day
  returned in more
concentrated form;
     Salinity 78 ppt

                                  From: Olympic Dam EIS website
   Discharge of large volumes of highly concentrated brine back to
    ocean
     Elevated salt concentration & contaminants
     Elevated temperature & turbidity levels
     Decreased oxygen levels


   Brine high specific density  sinks to bottom

   Could impact adult mating behaviours, & benthic life history
    stages
   Salinity effects embryonic development
   Resources diffuse across membrane
   Solubility of gases (e.g. O2) decreased in
    hyper-saline water
   Increased salinity causes a diffusion limitation
n =12




          Control                                   Brine
           39ppt            40ppt   45ppt   50ppt   55ppt



Dupavillon, Hons thesis
Mean field concentration




                              Brine: Increased Sr, Ca, K & Mg

                              High Mg causes mortality and
                              reduced mobility

                              High concentrations
                              found in 45, 50 and 55‰.


Treatment - salinity
                  Treatment      Dupavillon & Gillanders (2009)
Increase 1‰ = ~7%
              decrease in survival




                        Total mortality



Treatment - salinity
                            Dupavillon & Gillanders (2009)
Smaller size at higher salinity
Smaller individuals  less well developed for feeding & swimming




                     Treatment - salinity

                                               Dupavillon & Gillanders (2009)
   If brine disperses & background salinity levels
    reached close to discharge outfall
     May be little impact on eggs
   But
     USG already hypersaline environment
     Strong tidal currents, but are USG waters flushed
      & mixed with ocean waters given bathymetry?
     Also, dodge tides
     Potential for major impact on GAC
   Mating behaviour highly visual
   Inbound migratory routes of cuttlefish
     Will adults move up and over high salinity, benthic
      plumes?
     Will adults migrate around benthic plume to reach
      breeding sites?
   Only known breeding aggregation of cuttlefish in world!
   Population at Point Lowly likely a different species
   Little if any input from SSG population


   Potential for brine to impact early life history stage
   Unsure about impacts on adult behaviour & migration
   Species can’t move elsewhere to lay eggs
   Cephalopods short lived (1-2 years)
   No storage effect in population
    Need to be more cautious cf. managing finfish
Photos: Fred Bavendam, Sean Connell, Jackie Dupavillon,
Kaufman Productions, Nick Payne, Tim Rogers




Recent ABC Catalyst story:
http://www.abc.net.au/catalyst/stories/2695601.htm
The Environment Institute
                         Where ideas grow




   Next Seminar: 23 October

   Assoc. Prof. Veronica Soebarto
   Environmentally-sensitive design

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Giant Australian cuttlefish: a globally unique species under threat.

  • 1. The Environment Institute Where ideas grow Assoc. Prof. Bronwyn Gillanders Giant Australian cuttlefish: a globally unique species under threat?
  • 3. Population structure  Melita de Vries  Steve Donnellan  Mike Gardner  PhD/Hons students  Jackie Dupavillon  Nick Payne  Leanne Trott
  • 4. Giant Australian cuttlefish & the issues  Population structure  Potential impacts of desalination brine
  • 5. Weighs up to 13 kg Grows up to 1 m Lives 1-2 years Photo: Kaufmann Productions
  • 6. Ningaloo Reef Moreton Bay
  • 8. 8 km of coastline Winter – May to August
  • 9. Rocky reef Habitat map: SA DEH 8 km of coastline Winter – May to August
  • 10. Males larger than females High male:female sex ratio Males ‘battle’ for females Females may or may not mate with a male Small males have other strategies (e.g. sneakers) Shear numbers impressive Photos: Fred Bavendam
  • 11. Skewed towards males (4:1) based on counts of each sex  Assumes individuals on breeding aggregation similar amounts of time  Population sex ratio may be 1:1 with sexes spending different amounts of time on the breeding aggregation  Predict males spend more time than females
  • 12. Males n = 13 Females n = 6 Payne, PhD project
  • 13. Residence time Residence period 35 60 Mean Residence Time (days ± SE) Mean Residence Period (days ± SE) 30 50 25 * * 40 20 30 15 20 10 5 10 0 0 Males Females Males Females Male:Female = 3.7 : 1 Male:Female = 4.6 : 1  Population composed of equal numbers of males & females Payne, PhD project
  • 14. 300 270 Renewable moratorium on 240 fishing introduced in 1998 210 Now permanently closed to taking of cuttlefish Catch (tonnes) 180 Need to establish long-term 150 scientific based management plan 120 90 60 30 0 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 From: SARDI Catch Data
  • 15. BHP Olympic Dam expansion  Preferred option: coastal desalination plant in USG  Point Lowly preferred location (18 ha site)  Bulk commodities export facility  Feasibility study by Spencer Gulf Port Link Consortium (SGPLC), led by Flinders Ports  7-13 million tonnes of ore could be exported through new facility
  • 16. Need to understand population structure for appropriate spatial management  Demographic processes & population dynamics may vary From: Keough & Swearer (2007)
  • 17. Strongest inferences use a suite of techniques  Genetic & phenotypic approaches  Might not necessarily expect concordance among approaches  Evolutionary history vs. environmental variation  Spatial resolution varies by technique  Genetic approaches may be more conservative
  • 18. Marine populations  Genetic homogeneity over large distances  High dispersal life history characteristics  Squid  High levels of gene flow among populations  Cuttlefish  Sepia officinalis – extensive population structuring
  • 19.
  • 20. Determine population structure of giant Australian cuttlefish using a multidisciplinary approach  Molecular (microsatellite DNA markers)  Morphometrics  Statolith chemistry  Investigate spatial & temporal variation in population structure
  • 21. Microsatellite genotyping  12 microsatellite loci screened per individual  Kassahn et al. (2006) Marine Biology  Wheaton et al. (2007) Molecular Ecology Notes  Temporal variation  South Australia  Five yrs between 1998 & 2006  Spatial variation  18 sites across Australia
  • 22. Ningaloo Moreton Bay Breeding 1998 QLD aggregation 2000 2004 WA Whyalla 2005 SA 2006 18 1 NSW 4 5 17 16 3 6 15 2004 2 VIC Wallaroo 2005 14 13 Spencer Gulf Bass Strait GSV Glenelg 1998 1998 Edithburg Aldinga 2005 Cape 2005 Jervis 2005 2006
  • 23. -20500 Bayesian clustering approach Triplicate runs for 1 (panmixia) to 6 -21500 populations Ln Pr(X | K) Used admixture model -22500 Assumed correlated alleles across populations -23500 Examined each of K populations further to detect sub-population -24500 structure 1 2 3 4 5 6 K, number of populations STRUCTURE
  • 24. Q Estimated membership coefficients 0.00 0.20 0.40 0.60 0.80 1.00 Whyalla 1998 Whyalla 2000 Whyalla Whyalla 2004 Whyalla 2005 Breeding aggregation Whyalla 2006 Wallaroo 1998 Wallaroo 2005 Wallaroo Spencer Gulf Edithburg 2005 Cape Jervis 2005 Cape Jervis 2006 Shows overall population structure & individual assignment Aldinga/Myponga 1998 Gulf St Vincent Aldinga/Myponga 2005 Length of each line proportional to estimated membership in each group Glenelg 1998 western AUS 1998-2006 Vic WA VIC 2002 NSW 2002/2003 NSW
  • 25. Q Estimated membership coefficients 0.00 0.20 0.40 0.60 0.80 1.00 Bay Jervis Bay Jervis Jervis Bay Wollongong Wollongong Wollongong Wollongong Wollongong Wollongong Wollongong Wollongong Wollongong Wollongong Wollongong Wollongong Wollongong Central & Southern NSW Wollongong Wollongong Wollongong Wollongong Newcastle Newcastle Newcastle Newcastle Newcastle Coffs Harbour Coffs Harbour Coffs Harbour Coffs Harbour Coffs Harbour Coffs Harbour Coffs Harbour Coffs Harbour Coffs Harbour Northern NSW Coffs Harbour Coffs Harbour Coffs Harbour
  • 26. Spatial information – sampling location  1 to 10 populations (n=5 replicate runs)  Fixed K at modal value to estimate assignment of individuals to populations (n=10)  Continued hierarchical analyses to detect subpopulation structure  GENELAND
  • 27. Population 3 Population 5 Population 1 Population 4 Population 2
  • 28. South Australia Breeding aggregation Population 5 Contact zone Population 4 100 km
  • 29.  28 measurements per individual  Removed allometric effects of body size  Sexually dimorphic  sexes analysed separately (n= 173 females & 342 males)  No difference in size among years  pooled years
  • 30. 5 Breeding aggregation GSV & Southern SG 3 Western SA Discriminant function 2 1 90% correctly classified 3 variables used for classification 1 3 variables important: cuttlebone width & 2 beak parameters 3 5 -5 -3 -1 1 3 5 Discriminant function 1 LRL UHL
  • 31. 7 Breeding aggregation GSV & Southern SG Western SA Discriminant function 2 3 90% correctly classified 8 variables used for classification -1 3 beak parameters contribute to differences -5 -5.0 -2.8 -0.6 1.6 3.8 6.0 Discriminant function 1
  • 32. Dissolved trace Uptake by Statolith elements cephalopod incorporation
  • 33. Prehatchling Hatchling Sr:Ca statolith (mmol mol-1) Sr:Ca statolith (mmol mol-1) 35 35 Sr:Ca prehatchling statolith (mmol mol ) 30 -1 30 Sr:Ca hatchling statolith (mmol mol ) -1 25 25 20 20 15 15 10 10 5 5 0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 -1 Sr:Ca seawater (mmol mol-1) Sr:Ca prehatchling seawater (mmol mol ) Sr:Ca seawater (mmolmol- ) -1) 1 Sr:Ca hatchling seawater (mmol mol Trott, Hons thesis
  • 34. 5 Breeding aggregation GSV & Southern SG Western SA Discriminant function 2 3 1 Mg:Ca, Sr:Ca & Ba:Ca Discriminant Function Analysis -1 All years – 77% correctly classified 2004 – 78% correct 2005 – 79% correct -3 2006 – 83% correct -5 -7 -3 1 5 Discriminant function 1
  • 35. Not one panmictic population  Evidence for 5 populations across species range  Breeding aggregation differs from elsewhere  Evolutionary & ecological implications  Possibly incipient species  Adaptive divergence along an environmental gradient  Recent & rapid differentiation
  • 36. Ocean again at ~ 7KYA From: Andrew Hugall
  • 37.  Mating behaviour differs  Physiological tolerance & condition in relation to temperature & salinity ▪ Two populations may be prevented from significant overlap due to differing tolerances  Are individuals from two populations able to mate, are eggs viable, are offspring fertile ▪ Testing degree of reproductive isolation  Determine degree of genetic isolation – genome wide screening  Ecological implications of morphological differences
  • 38. Intake pipe Proposed locations Breeding area Out take pipe 320 ML SW/day 120 ML FW/day via from USG; 320 km pipeline Salinity >40 ppt 200 ML SW/day returned in more concentrated form; Salinity 78 ppt From: Olympic Dam EIS website
  • 39. Discharge of large volumes of highly concentrated brine back to ocean  Elevated salt concentration & contaminants  Elevated temperature & turbidity levels  Decreased oxygen levels  Brine high specific density  sinks to bottom  Could impact adult mating behaviours, & benthic life history stages
  • 40. Salinity effects embryonic development  Resources diffuse across membrane  Solubility of gases (e.g. O2) decreased in hyper-saline water  Increased salinity causes a diffusion limitation
  • 41. n =12 Control Brine 39ppt 40ppt 45ppt 50ppt 55ppt Dupavillon, Hons thesis
  • 42. Mean field concentration Brine: Increased Sr, Ca, K & Mg High Mg causes mortality and reduced mobility High concentrations found in 45, 50 and 55‰. Treatment - salinity Treatment Dupavillon & Gillanders (2009)
  • 43. Increase 1‰ = ~7% decrease in survival Total mortality Treatment - salinity Dupavillon & Gillanders (2009)
  • 44. Smaller size at higher salinity Smaller individuals  less well developed for feeding & swimming Treatment - salinity Dupavillon & Gillanders (2009)
  • 45. If brine disperses & background salinity levels reached close to discharge outfall  May be little impact on eggs  But  USG already hypersaline environment  Strong tidal currents, but are USG waters flushed & mixed with ocean waters given bathymetry?  Also, dodge tides  Potential for major impact on GAC
  • 46. Mating behaviour highly visual  Inbound migratory routes of cuttlefish  Will adults move up and over high salinity, benthic plumes?  Will adults migrate around benthic plume to reach breeding sites?
  • 47. Only known breeding aggregation of cuttlefish in world!  Population at Point Lowly likely a different species  Little if any input from SSG population  Potential for brine to impact early life history stage  Unsure about impacts on adult behaviour & migration  Species can’t move elsewhere to lay eggs  Cephalopods short lived (1-2 years)  No storage effect in population   Need to be more cautious cf. managing finfish
  • 48. Photos: Fred Bavendam, Sean Connell, Jackie Dupavillon, Kaufman Productions, Nick Payne, Tim Rogers Recent ABC Catalyst story: http://www.abc.net.au/catalyst/stories/2695601.htm
  • 49. The Environment Institute Where ideas grow Next Seminar: 23 October Assoc. Prof. Veronica Soebarto Environmentally-sensitive design