Assessment of light history indicators for predicting seagrass biomass

Adams, M. P., Ferguson, A. J. P., Collier, C. J., Baird, M. E., Gruber, R. K. and O'Brien, K. R. (2015). Assessment of light history indicators for predicting seagrass biomass. In: T. Weber, M. J. McPhee and R. S. Anderssen, MODSIM2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand. International Congress on Modelling and Simulation, Gold Coast, QLD, Australia, (1303-1309). 29 November - 4 December 2015.

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Name Description MIMEType Size Downloads
Author Adams, M. P.
Ferguson, A. J. P.
Collier, C. J.
Baird, M. E.
Gruber, R. K.
O'Brien, K. R.
Title of paper Assessment of light history indicators for predicting seagrass biomass
Conference name International Congress on Modelling and Simulation
Conference location Gold Coast, QLD, Australia
Conference dates 29 November - 4 December 2015
Proceedings title MODSIM2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand
Publisher The Modelling and Simulation Society of Australia and New Zealand (MSSANZ)
Publication Year 2015
Sub-type Fully published paper
Open Access Status Not Open Access
ISBN 9780987214355
Editor T. Weber
M. J. McPhee
R. S. Anderssen
Start page 1303
End page 1309
Total pages 7
Collection year 2016
Language eng
Formatted Abstract/Summary
Seagrasses are rapidly declining worldwide due to anthropogenic impacts on coastal environments. One major contributor to seagrass loss is the degradation of water quality which reduces light availability.

In this paper we use a data-driven approach to compare several indicators of light history for their ability to predict seagrass biomass. Data sets for daily light and seasonal biomass of seagrass (Zostera muelleri) meadows from two lakes (Lake Macquarie and Tuggerah Lake) in New South Wales, Australia, were analysed. The light history indicators were compared to seagrass biomass, for different periods of light history. Three indicators were tested: (1) an unweighted mean of the light history, (2) a weighted mean of the light history that places greater emphasis on the more recent light doses, and (3) a modified rolling average of light history.

For the time periods that maximised the correlation between seagrass biomass and light history (hereafter called the optimised light history periods), the relationships between seagrass biomass and the three measures of light history always showed high significance (p<0.05) but low predictive power (R2<0.5). Our results consistently demonstrated that there was a significant and positive relationship between light history and biomass at the optimised light history periods. However, light availability was clearly not the only factor influencing seagrass biomass in the two lakes studied. The best correlations were identified for total and below-ground biomass in Lake Macquarie (R2=0.47-0.49, p<0.0001); this was attributed to the high below-ground to aboveground biomass ratio and lesser influence of sediment and nutrient conditions in Lake Macquarie compared to Tuggerah Lake.

All three light history indicators yielded similar correlations between biomass and light history (maximum variation in R2 was 0.05). Indicator 1 was slightly better than the other two because it produced higher R2 values and lower p-values. Indicator 1 was also easier to calculate than indicator 2 and requires a shorter time period of daily light data to optimise than indicator 2. Indicator 3 is ideally suited for use as a tracer in large-scale modelling simulations, and thus may be used in these simulations if indicator 1 cannot be easily calculated. Hence we generally recommend indicator 1, although indicator 3 may also be suitable in some circumstances. For these two indicators, 1.5-8 months of daily light data was required to optimise the correlation between biomass and light history for the seagrass Z. muelleri in Lake Macquarie and Tuggerah Lake. These time periods provide an upper limit on the time that this seagrass species should be subjected to light deprivation before management actions are triggered.
Keyword Light history
Biomass
Management
Monitoring
Seagrass
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes http://www.mssanz.org.au/modsim2015/F8/adams.pdf

Document type: Conference Paper
Collections: School of Chemical Engineering Publications
Official 2016 Collection
 
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Created: Mon, 07 Dec 2015, 09:05:40 EST by Matthew Adams on behalf of School of Chemical Engineering