Lead: Susie Wood
Our ability to monitor and predict the onset of water quality problems such as cyanobacterial blooms and bottom-water anoxia is limited by the availability near real-time physicochemical and biological data. A network of over 20 real-time observation platforms is now operational in New Zealand lakes providing observations of variables such as temperature and dissolved oxygen through the water column. While these data are invaluable for our understanding of these systems and for hydrodynamic models, they do not yet provide enough biological and chemical information to predict water quality at critical time scales, nor do they provide any data on biological communities.
The aim of this critical step is to test and validate sampling and analysis methods, and sensors which address these shortcomings. We are focusing on:
Assessing the feasibility of using phycocyanin (a pigment specific to cyanobacteria) sensors to determine cyanobacterial biomass in-situ.
Exploring the potential of deploying nitrate sensors on observation platforms.
Investigating the potential of environmental DNA techniques to complement traditional methodologies and allow biodiversity assessments at unparalleled spatial and temporal scales.
Linking with CS 1.2.2 to assess the potential of deploying hyperspectral sensors on observational platforms.
CS1.2.2 - assessment of hyperspectral sensors
Bay of Plenty Regional Council
Department of Conservation (Ashburton lakes)
Lake Rotorua (Kaikoura)
Hodges CM, Wood SA, Puddick J, Hamilton DP. 2018. Sensor manufacturer, temperature, and cyanobacteria morphology affect in situ phycocyanin fluorescence measurements. Environmental Science and Pollution Research 25: 1079-1088.
Wood S, Kelly D, Waters S,
Cotterill V, Wood S, Hamilton D. 2016. Highlighting the challenges of using phycocyanin sensors for routine monitoring of cyanobacteria. Oral Paper presented at the New Zealand Freshwater Sciences Society Annual Meeting, Invercargill, 5-8 December 2016.
Cotterill V, Wood S, McBride C, Kelly D, Breitbarth E, Lehmann M, Hamilton D. 2016. Enhancing real-time lake monitoring technologies. Poster presented at the New Zealand Freshwater Sciences Society Annual Meeting, Invercargill, 5-8 December 2016.
Cotterill V. 2017. Evaluation of a phycocyanin sensor for use in cyanobacteria monitoring and examining the effects of nutrients and light on phycocyanin quotas. Unpublished Master of Science Thesis. Submitted July 2017. Supervisors: Hamilton D, Wood S.
Hodges CM. 2016. A validation study of phycocyanin sensors for monitoring cyanobacteria in cultures and field samples. Unpublished Master of Science Thesis.Supervisors: Hamilton D, Wood S.