The Marine chapter of the 2016 State of the Environment (SoE) report incorporates multiple expert templates developed from
streams of marine data. This metadata record describes the Expert Assessment "The state and trends of ecological processes
– primary productivity". The full Expert Assessment, including figures and tables (where provided), is attached to this
record. Where available, the Data Stream(s) used to generate this Expert Assessment are accessible through the "On-line
Resources" section of this record.
DESCRIPTION OF ECOLOGICAL PROCESS FOR EXPERT ASSESSMENT
Satellite data for ocean colour provides the most comprehensive assessment of phytoplankton biomass (PB) and primary production
(PP). The method works very well in oceanic waters but PB and PP can be overestimated in regions where runoff or resuspension
affects water colour (near land, especially near large tropical rivers). In general phytoplankton biomass and primary production
(PP) are low around Australia. Typically both BP and PP are greatest near the coast tending to decline with distance from
shore. Offshore oceanic waters north of ~30°S generally have low rates of PP, < 0.2g C m-3 d-1. From 1997 to 2015 the greatest
rates of PP have been found near shore, in the marginal Arafura Sea and southern Tasman Sea.
The biomass and productivity of the oceans is dependent upon the magnitude and timing of nutrient supply. The more tropical
oceans of northern Australia tend to be strongly stratified restricting nutrient resupply from depth (Chavez et al. 2011).
Australia is one of the driest continents with very low and highly erratic runoff (McMahon, 1982) so nutrient supply from
the land is also low.
DATA STREAM(S) USED IN EXPERT ASSESSMENT
Data used in this assessment are computed from the level 3 (L3) daily global products using one merging method. PP was computed
from merged monthly L3 products using the algorithms developed by Antoine and Morel (1996). Details can be found at http://www.globcolour.info/products_description.html
2016 SOE ASSESSMENT SUMMARY [see attached Expert Assessment for full details]
• 2016 •
Assessment grade: Good
Assessment trend: Improving
Confidence grade: Adequate high quality evidence and high level of consensus
Confidence trend: Adequate high quality evidence and high level of consensus
Comparability: Grade and trend are comparable to the 2011 assessment
• 2011 •
Assessment grade: Very good
Assessment trend: Stable
Confidence grade: Limited evidence or limited consensus
Confidence trend: Limited evidence or limited consensus
CHANGES SINCE 2011 SOE ASSESSMENT
This assessment uses observations from a range of spatial and temporal scales that allows a much better assessment of current
state and trends to be made.
Behrenfeld, M.J., Falkowski, P.G. 1997. Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnology
and Oceanography. 42: 1-20.
Cai, W. 2006. Antarctic ozone depletion causes an intensification of the Southern Ocean supergyre circulation, Geophys. Res.
Lett., 33, L03712, doi:10.1029/2005GL024911.
Carranza, M.M., Gille, S.T. 2015. Southern Ocean wind-driven entrainment enhances satellite chlorophyll-a through the summer,
J. Geophys. Res. Oceans, 120, 304–323, doi:10.1002/2014JC010203.
Chavez, F.P., Messie, M., Pennington, T.J., 2011. Marine primary production in relation to climate variability and change.
Annual Review of Marine Science 3, 227-260.
Condie SA, Dunn JR. Seasonal characteristics of the surface mixed layer in the Australasian region: implications for primary
production regimes and biogeography. Mar Freshw Res. 2006;57(6): 569
Durack, P.J., Wijffels, S.E., 2010. Fifty-year trends in global ocean salinities and their relationship to broad-scale warming.
J. Clim. 23: 4342–4362.
Feng, M., McPhaden, M. J., Xie, S., & Hafner, J. 2013. La Niña forces unprecedented Leeuwin Current warming in 2011. Scientific
Reports 3, 1277; DOI:10.1038/srep01277.
Furnas M.J. 2007. Intra-seasonal and inter-annual variations in phytoplankton biomass, primary production and bacterial production
at North West Cape, Western Australia: Links to the 1997–1998 El Niño event. Cont Shelf Res. 2007;27(7): 958–80.
Furnas M. J., E.J. Carpenter. 2016. Completely over the top: Primary production in the tropical continental shelf seas bordering
northern Australia. (in review). Continental Shelf Research.
Hill, K., S. R. Rintoul, K. R. Ridgway, and P. R. Oke (2011), Decadal changes in the South Pacific western boundary current
system revealed in observations and ocean state estimates, J. Geophys. Res., 116, C01009, doi:10.1029/2009JC005926.
Kelly, P., Clementson, L., Lyne, V. 2015. Decadal and seasonal changes in temperature, salinity, nitrate, and chlorophyll
in inshore and offshore waters along southeast Australia. J. Geophys. Res. Oceans, 120: 4226.
Matear, R.J., Chamberlain, M.A., Sun, C., Feng, M. 2013. Climate change projection of the Tasman Sea from an eddy-resolving
ocean model. J. Geophys. Res. 118: 2961–2976. http://dx.doi.org/10.1002/jgrc.20202, doi:10.1002/jgrc.20202
McGillicuddy, D. J., Robinson, A.R., Siegel, D.A., Jannasch, H.W., Johnson, R., Dickeys, T., McNeil, J., Michaels, A.F.,
Knap, A.H. 1998. Influence of mesoscale eddies on new production in the Sargasso Sea, Nature, 394(6690), 263–266.
McMahon, T.A. (1982): World hydrology: does Australia fit? Hydrology and Water Resources Symp, Institution of Engineers,
Australia, Nat Conf Publ No. 82/3, 1-7.
Mongin, M., Baird, M.E., Tilbrook, B., Matear, R.J., Lenton, A., Herzfeld, M., Wild-Allen, K.A., Skerratt, J., Margvelashvili,
N., Robson, B.J., Duarte, C.M., Gustafsson, M.S.M., Ralph, P.J., Steven, A.D.L. 2016. The exposure of the Great Barrier
Reef to ocean Acidification. Nature Communications. In press.
Oliver, E.C.J., Holbrook, N.J. 2014. Extending our understanding of South Pacific gyre “spin-up”: Modeling the East Australian
Current in a future climate, J. Geophys. Res. Oceans, 119, 2788–2805, doi:10.1002/2013JC009591.
Rousseaux CSG, Lowe R, Feng, M, Waite AM and Thompson PA. 2012. The role of the Leeuwin Current and mixed layer depth on
the autumn phytoplankton bloom off Ningaloo Reef, Western Australia. Continental Shelf Research, doi:10.1016/j.csr.2011.10.010
Siegel DA, Behrenfeld MJ, Maritorena S, McClain, C.R., Anoine, D., Bailey, S.W., Botempi, P.S., Boss, E.S., Dierssen, H.M.,
Doney, S.C., Eplee, Jr., R.E., Evens, R.H., Feldman, G.C., Fields, E., Franz, B.A., Kuring, N.A., Mengelt, C., Nelson,
N.B., Patt, F.S., Robinson, W.D., Sarmento, J.L., Swan, C.M., Werdell, P.J., Westbury, T.K., Wilding, J.G., Yoder, J.A. 2013.
Regional to global assessments of phytoplankton dynamics from the SeaWiFS mission. Remote Sensing of Environment, 135, 77–91.
Signorini, S.R., Franz, B.B., McClain, C.R. 2015. Chlorophyll variability in the oligotrophic gyres: mechanisms, seasonality
and trends. Front. Mar. Sci. http://dx.doi.org/10.3386/fmars.2015.0001
Thompson, PA, Bonham, P, Rochester, W, Doblin, MA, Waite, AM, Richardson A, Rousseaux C. 2015. Climate variability drives
plankton community composition changes: an El Niño to La Niña transition around Australia. J. Plankton Res. 37(5): 966–984.
Thompson PA, Bonham P, Waite AM, Clementson LA, Cherukuru N, Doblin MA. 2011. Contrasting oceanographic conditions and phytoplankton
communities on the east and west coasts of Australia. Deep Sea Research II 58: 645-663
Thompson, P.A., O’Brien, T.D., Lorenzoni, L., Richardson, A.J., Chavez, F. 2016. The South Pacific Ocean, in What are Marine
Ecological Time Series telling us about the ocean? A status report. O'Brien, T.D., Isensee, K., Lorenzoni, L., Valdés, J.L.
(eds). IOC-UNESCO, Paris. IOC Technical Series, No. 129. (in review).
van Ruth, P.D., G.G. Ganf, T.M. Ward. 2010a. Hot-spots of primary productivity: an alternative interpretation to conventional
upwelling models. Estuarine, Coastal and Shelf Science 90 (3), 142-158.
van Ruth, P.D., G.G. Ganf, T.M. Ward. 2010b. The influence of mixing on primary productivity: a unique application of classical
critical depth theory. Progress in Oceanography 85 (3), 224-235.
QUALITY OF DATA USED IN THE ASSESSMENT
Spatial and temporal coverage are excellent. Conversion of ocean colour to primary production by a model introduces a source
of potential error. The magnitude of this error has been assessed (e.g. Carr et al., 2006) but further refinement is
possible for Australian waters. The assessment of trends should be quite robust to any model error.
M.E. Carr, M.A.M. Friedrichs, M. Schmeltz, M.N. Aita, D. Antoine, K.R. Arrigo, et al.
A comparison of global estimates of marine primary production from ocean color
Deep-Sea Research Part II-Topical Studies in Oceanography, 53 (2006), pp. 741–770.
CUSTODIAN AND LOCATION OF DATA
METHOD USED TO DETERMINE STATE OR RECENT TREND
Linear regression fit to each pixel over the duration from 1997 to 2015.
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