IMOS 2012
IMOS and the Tassie Node 2013
Node Plans for 2010 - 2013
Leadership from:Smith, Buxton, Thompson, Swadling, Sainsbury, Schiller
Tasmania has a large marine research community with diverse interests….
IMOS 2013
IMOS and the Tassie Node philosophy• Its underlying scientific rationale is to link
the physics to the fish, really….
• New in 2012• 2nd IMOS glider arrived • IMOS AUV transects completed• 2nd IMOS acoustic curtain deployed to monitor
movements of key species• Stronger links to Victoria and northern Bass Strait
• Tas IMOS ‘Facility’ Leaders– Benthic: Neville Barrett– Gliders: Peter Thompson– Maria Island NRS: Tim Lynch– Acoustic curtains: Jayson Semmens– Other moorings: Christopher Watson– SOOP: Rudy Kloser……(physics to fish)
– Remote sensing: Edward King– Bass Strait:
IMOS 2013
Rudy Kloser CSIRO [email protected]
Special thanks to:
Sealord Australian Longline Marine National Facility
IMOS CSIRO Wealth from Oceans flagship
CSIRO CPR Anthony Richardson, Marine Instrumentation Matt Sherlock, Jeff Cordell and Andreas Marouchos
SOOP by Rudy Kloser, phytoplankton, zooplankton,midtrophic level fish, commercially caught fish
Basin scale monitoring
Samples from 600-800 m
Net and Acoustic depth stratified (200 m day night strata) sampling along Trans Tasman transect in June
2008
Ocean basin studies using fishing vessels
Australia
New Zealand
0 m
1500 m
17th June
21st June
Integrated Marine Observing System 38 kHz vessel of opportunity acoustic data
Validation experiments• Midwater nets with attached acoustic-optical system
MIDOC net AOS 38 kHz
AOS DSLR
Density, biodiversity and biogeography of micronekton at the scale of an ocean basin with nets, acoustics and optics
Profile of net deployment
IMOS 2012
IMOS• AATAMS sub facility led by Jayson Semmens at UTas
– 2 curtains– 1 at Maria Island
» Just recovered!– 2nd at Cape Barren Island
Significant co-investment in infrastructure from:
CSIRO (David Smith)UTas (Colin Buxton)Ocean Tagging Network
Deployed in January 2012
IMOS 2013(Photos: Darren Moore)
Storm Bay
(Photo: Tony Sprent)
GPS Buoy
Bass Strait
Sub-Facility 11e:
Satellite Altimetry CAL/VAL:• First sea surface height bias data stream was
provided to the mission team in late October 2010 – the data has been highly valued.
• CSIRO co-invests in additional instruments for validation of Storm Bay model
• This stream gets enhanced and updated as new mooring and altimeter data comes online.
• Enquiries: Christopher Watson ([email protected])
National Reference Stations NUTRIENTS!
Key* - long term site# - infrastructure deployed+ - Telemetry^ BGC sampling
Declining silicate but not nitrate?
IMOS 2012
time (year)
1940 1960 1980 2000
nitra
te (µ
M)
0
2
4
6
8
10
Mean
silic
ate
(µM
)
0
1
2
3
4
5NO3
Si
Supply ≠ mixing
[Si] ↓ rise in
other taxa
Toxic dino blooms?
Annual mean values (n = 60)Maria Island
Long-term changes in temperate Australian coastal waters: implications for phytoplankton. Thompson, Baird, Ingleton, Doblin. Marine Ecology Progress Series 394: 1-19 2009.
Modelling 101
• Predicting ecosystem responses from basic data
IMOS 2013
nutrients
phytoplankton
zooplankton
Nutrients: vertical mixing and silicate as a limiting nutrient
• Grant (1971) ‘Variation in silicate concentration atPort Hacking station, Sydney, in relation to phytoplankton growth’ in the Aust J Mar Freshw Res 22:49–54
IMOS 2012
NRSLa Niña of 2011
IMOS 2012
Time (months and years)
Jun/09 Oct/09 Feb/10 Jun/10 Oct/10 Feb/11 Jun/11 Oct/11
mon
thly
sout
hern
osc
illatio
n in
dex
-20
-10
0
10
20
30
El Niño
La Niña
Austral year
Nutrients at Maria IslandSmall
differences between El Nino and La Nina
BUT there was something odd in 2012
High SILICATE
IMOS 2013
El Niño
La Niña
Nitrate ~ 3x silicate
Nutrients at Port Hacking
IMOS 2012
High SILICATE
El NiñoLa Niña
Nutrients at North Stradbroke Island
IMOS 2012
High SILICATE
El Niño La Niña
Surface nutrients at Yongala
IMOS 2012
High SILICATE ~ 10x Maria Is.
El Niño La Niña
El Nino versus La Nina• Behrenfeld et al.
estimated the 1997-98 La Nina caused a 5 petagram C increase in oceanographic PP relative to the following El Nino…– A challenge for us is to
substantiate ΔPP as well and the sequestration of that carbon
IMOS 2012
Austral summer La Nina
Austral summer El Nino
IMOS 2013
NRS nutrient
datastrong shifts between
years (from el nino to la nina)
sampling was adequate to resolve inter-annual variability
Spatial-temporal patterns…..
Conceptual model for nitrogen supply to WA Coast
Adapted from Thompson, P.A., Wild-Allen, K., Lourey, M., Rousseaux, C., Waite A.M., Feng, M.,Beckley L.E. 2011. Nutrients in an oligotrophic boundary current: Evidence of a new role for theLeeuwin Current. Progress in Oceanography. (in press, accept 21/02/2011)
• Thin layer of high nitrate, low DO, colder, fresher water at ~ 24 and 25°S
• Captured by LC, dragged south at base of LC
• Where LC cools it intrudes into this layer and mixes to surface
• 3 modes south of 28°S– Eddy– Vertically mixed LC– Stratified LC
Picoplankton around Australia• For most Australian
waters the dominant biomass is < 2µm.
• Can characterize these by pigment and flow cytometry– Synechococcus– Prochlorococcus, the
world’s most abundant species (~1027
individuals) discovered in 1986 by Penny Chisholm. Picture courtesy of Paul Thomson (UWA)
SCOR WG 137 2012
Picoscell counts
increase at mid latitudes on both coastProchloro-coccus
Percentage increase in 2011 (La Nina) relative to 2010 (El Nino).
Samples analysed by Paul Thomson (UWA)
IMOS 2012
Interannual variability 2010 vs 2011
YON
NSI
PHB
MAI KA
IES
PR
OT
NIN
DAR
mea
n ch
la (µ
g L-1
)
0.0
0.2
0.4
0.6
0.8
Rottnest Island
0
100
200
300
400
* * *
KangarooIsland
0
100
200
300
400
500
chlaperidinin (dinos)19-but (pelago)Fuco (diatoms)Neo (greens)Prasino (greens)19-hex (coccos)allo (cryptos)zea (cyanos)DVchla (prochloro)chlb (greens)
* * **
Port Hacking
0
50
100
150
200
*
666%
4781%
North Stradbroke Island
0100200300400500600
Yongala
0
100
200
300
* * **
* * *
Esperance
0
50
100
150
200
250
300
* * * * *
Maria Island
0
50
100
150
200
250
* * *
Merry Christmas 2011
ND
All marker pigments normalized to chlorophyll aand as % of 2010.
2010 to 2011 represented a strong shift from el nino to la nina
Pigment sampling was adequate to resolve inter-annual variability at the Class level for phytoplankton
dinos
Conclusions
• La Nina impacts:Mid latitudes
= more tropical
East coast = more coastal
SW more active STF
SCOR WG 137 2012
More Prochlorococcus= more tropical
More greensAndPrasinophytes
More phytoplankton(chlorophyll a)
Longer termPhytoplanktonSpatial patterns
Sydney’s redtides of the 1990s(Noctiluca scinitillans)
Photos courtesy of Iain Suthers
Noctiluca• A recent
(2002) arrival in SE Tasmania*– Climate
change?– Temperature
tolerance?
• New toxic species: Alexandriumtamarense
Courtesy of Iain Suthers UNSW*Thompson, P.A., P. I. Bonham and K.M. Swadling. 2008. Phytoplankton blooms in the HuonEstuary, Tasmania: top down or bottom up control? Journal of Plankton Research. 30:735-753.
Toxic Algal Bloom!
• Closed east coast commercial and recreational harvest of:– Rock lobster– Shellfish
• Scallops, crabs, mussels, abalone, periwinkles etc
– Fish (scale fish) IMOS 2013
Alexandrium tamarense
Magro, K.L., Arnott, G.H., and Hill, D.R.A., (1997). Algal Blooms in Port Phillip Bay from March 1990 to February 1995: Temporal and Spatial Distribution and Dominant Species, Port Phillip Bay Environmental Study Technical Report No.27
Alexandrium tamarense
Speculative Conclusions
WEALTH FROM OCEANS
La Nina conditions inject Si into coastal waters in northern Australia
Transport of this south in the EAC determines the [Si] along the east coast of Tasmania in the following year
The structure of the La Nina water column also seems to favour dinos
picture by frank olsen
Glider Track
25 days operation6 cross-shelf transects~450 km travelled2345 profiles from surface to 10m above bottomMaximum depth 155m
Courtesy of Emlyn Jones (CSIRO)
Model: Glider Data
Data Assimilating Coastal Model: Comparison with GHRSST
Jones, E. M., Oke, P. R., Rizwi, F. R. and Murray, L. Assimilation of glider and mooring data into a coastal ocean model. Submitted to Ocean Modelling, (in revision).
Flinders MPA (east of Bass Strait)
Freycinet (off Wineglass Bay)Huon MPATasmanian Fracture MPA
(south of Maatsuyker)
AUV benthic surveys
Neville Barrett Craig Johnson
Superscience Postdoctoral Fellow
Williams et al. ‘Monitoring of benthic reference sites’, IEEE Robotics and Automation Magazine, 19 (1) pp. 73-84. ISSN 1070-9932 (2012)
Johnson et al. ‘Climate change cascades: Shifts in oceanography, species' ranges and subtidal marine community dynamics in eastern Tasmania’, Journal of Experimental Marine Biology and Ecology, 400 (1-2) pp. 17-32. ISSN 0022-0981 (2011)
Edgar and Barrett ‘An assessment of population responses of common inshore fishes and invertebrates following declaration of five Australian marine protected areas’, Environmental Conservation, 39 (3) pp. 271-281.
Leaper et al. Comparing large-scale bioregions and fine-scale community-level biodiversity predictions from subtidal rocky reefs across south-eastern Australia’, Journal of Applied Ecology, 49 (4) pp. 851-860. ISSN 0021-8901 (2012)
IMOS 2013
UPTAKE: ANiMMSThe Australian National Network in Marine Science is collaboration
between James Cook University, The University of Tasmania and The University of Western Australia. ANNIMS has recently funded five synthesis teams to address issues in marine science of national and international importance.
– SYNTHESIS OF BIOPHYSICAL PROCESSES RELATED TO RANGE SHIFTING SPECIES IN SOUTH EAST AND SOUTH WEST AUSTRALIA
– TEAM: Stewart Frusher, Gretta Pecl, Alistair Hobday, Neil Holbrook, Graham Edgar, Beth Fulton, Reg Watson, Peter Thompson, Nicole Hill, Thomas Wernberg, Daniel Smale, Ben Radford, Ming Feng, Jennifer Sunday, Amanda Bates
– Will use CPR and NRS data for phytoplankton and zooplankton
• Other ANiMMs projects– Understanding climate drivers and predicting the future for coastal Australian ecosystems:– The roles of waves, tides, eddies and cross-shelf flows in carbon exchange:– Triangulating climate records from fish, marine invertebrates and trees to understand ocean warming:
ANiMMS
• Understanding the global redistribution of species in a changing climate
• Amanda Bates et al.
• In review: Nature Climate Change
IMOS 2013
IMOS 2013
UPTAKE: INFORMD, NECTAR• INFORMD
new significant FRDC funded project in SE (2012) led by Scott Condie using IMOS data
NECTAR (National eResearch Collaboration Tools and Resources)
new investment in using IMOS data in Tasmania.
Conclusions
WEALTH FROM OCEANS
• First 5 years have been a great success
• Room for improvement in terms of:– Integration– Data availability– Products– Spatial coverage
picture by frank olsen
Declining Spring Bloom?
• Ocean colourdata to assess spring bloom dynamics
IMOS 2012
Long-term changes in temperate Australian coastal waters: implications for phytoplankton. Thompson, Baird, Ingleton, Doblin. Marine Ecology Progress Series 394: 1-19 2009.
Observational Science
Photons
Algal cellgrowth process
acclimationsbiochemical
morphological
Species levelinteractions
with theenvironment
•Processes•Growth•Losses
•sinking•grazing
LocalEcosystem
levelInteractions & Higher tropic
levels
Nutrientsnitrogen
silica
Less phytoplankton?
• Tendency (significant trend) for the growth rate of the spring bloom to decline over the first 10 years of available SeaWifsdata.
IMOS 2012
Long-term changes in temperate Australian coastal waters: implications for phytoplankton. Thompson, Baird, Ingleton, Doblin. Marine Ecology Progress Series 394: 1-19 2009.
CSIRO.
IMOS Observations: pelagic
• ARGOs: vital to the large scale hydrodynamics
Data Assimilating Coastal Model: Summary• The assimilation of data from a relatively sparse coastal observing
network has improved our state estimates.• The EnOI approach is very computationally efficient when compared
with other algorithms (e.g. EnKF, 3D/4D Var)• Current work includes the estimation of model parametersJones, E. M., Oke, P. R., Rizwi, F. R. and Murray, L. Assimilation of glider and mooring data into a
coastal ocean model. Submitted to Ocean Modelling, (Under revision).
Possible Future Work:Generate a 2 year reanalysis similar to BRAN for the SETas region
• Assimilate glider, mooring and remote sensing data• Withhold the SB sampling data for validation
Objective array design (OSE/OSSE’s) using the DA tools?
Data Assimilation: EnOI -Glider Data
43
Australian Coastal Modelling and information systems | Coastal Environmental Modelling Team
Rise in dinoflagellates?• From the Huon
Estuary– Significant rise in
peridinin (found only in dinoflagellates) relative to chorophyll a = more dinos
IMOS 2012
Thompson, P.A., P. I. Bonham and K.M. Swadling. 2008. Phytoplanktonblooms in the Huon Estuary, Tasmania: top down or bottom up control? Journal of Plankton Research. 30:735-753.
IMOS 2012
IMOS 2013
IMOS and the Tassie Node
• Other facilities are crucial to achieving our vision:
– Argo Floats– Ships of Opportunity– Deep water moorings– Ocean Gliders– Satellite Remote Sensing