Description: In recent years, there has been a widespread deployment of submersible fluorescence sensors by water utilities. They are used to measure diagnostic pigments and estimate algae and cyanobacteria abundance in near real-time. Despite being useful and promising tools, operators and decision-makers often rely on the data provided by these probes without a full understanding of their limitations. As a result, this may lead to wrong and misleading estimations which, in turn, means that researchers and technicians distrust these sensors. In this review paper, we list and discuss the main limitations of such probes, as well as identifying the effect of environmental factors on pigment production, and in turn, the conversion to cyanobacteria abundance estimation. We argue that a comprehensive calibration approach to obtain reliable readings goes well beyond manufacturers’ recommendations, and should involve several context-specific experiments. We also believe that if such a comprehensive set of experiments is conducted, the data collected from fluorescence sensors could be used in artificial intelligence modelling approaches to reliably predict, in near real-time, the presence and abundance of different cyanobacteria species. This would have significant benefits for both drinking and recreational water management, given that cyanobacterial toxicity, and taste and odour compounds production, are species-dependent.

Description: Wetting of leaf litter accumulated in riparian zones during rainfall events provides pulses of dissolved organic matter (DOM) to rivers. Restoring riparian vegetation aims to reduce sediment and nutrient transport into rivers, however DOM from leaf litter can stimulate phytoplankton growth and interfere with water treatment processes. Improved understanding of the loads and chemical composition of DOM leached from leaf litter of different plant species, and how subsequent leaching through soils affects DOM retention or transformation, is needed to predict the outcomes of riparian revegetation. To investigate this, we simulated rapid leaching of rainfall through the leaf litter of two riparian tree species with and without subsequent leaching through soil, comparing dissolved organic carbon (DOC) and nitrogen (DON) loads, and DOM chemical composition (via spectroscopic and novel NMR-fingerprinting techniques). Plant source affected the load and composition of DOM leaching, with Eucalyptus tereticornis leaching more DOC than Casuarina cunninghamiana. Additionally, E. tereticornis DOM had a higher sugar, myo-inositol, benzoic acid, flavonoid and oxygenated aromatic content. More than 90% of leaf litter DOM was retained in the soil under simulated repeated heavy rainfall. The DOM chemistry of these species determined the total loads and changes in DOM composition leaching through soil. Less E. tereticornis DOM was retained by the soil than C. cunninghamiana DOM, with sugars, myo-inositol and amino acids being poorly retained compared to fatty acids and aromatic compounds. It also appears that DOM from E. tereticornis litter primed the soil, resulting in more DON being leached compared with bare soil. In comparison, C. cunninghamiana litter resulted in greater retention of DON, oxygenated aromatic compounds and the amino acid tryptophan. This study provides new information on how a range of DOM sources and transformations affect the DOM ultimately leached into waterways, key to developing improved models of DOM transformations in catchments.

Description: Previous studies have shown that under laboratory conditions, dissolved organic matter (DOM) leached from plants can be differentially more phytotoxic to cyanobacteria, compared to green algae. This study examined how DOM source and transformation processes (microbial and photochemical) affect its chemical composition and phytotoxicity towards a cultured species of cyanobacteria (Raphidiopsis raciborskii) using a factorial experimental design. To complement cyanobacterial bioassays, the chemical composition and associated changes in DOM were determined using spectroscopic (nuclear magnetic resonance (NMR) and absorbance) and elemental analyses. Sunlight exposed DOM from leaves of the terrestrial plants, Casuarina cunninghamiana and Eucalyptus tereticornis had the most phytotoxic effect compared to DOM not exposed to sunlight. This phytotoxic DOM was characterised by relatively low nitrogen content, containing highly coloured and relatively high molecular mass constituents. Both mixed effect model and PCA approaches to predict inhibition of photosynthetic yield indicated phytotoxicity could be predicted (P 〈 0.001) based upon the following parameters: C: N ratio; gilvin, and lignin-derived phenol content of DOM. Parallel proton-detected 1D and 2D NMR techniques showed that glucose anomers were the major constituents of fresh leachate. With ageing, glucose anomers disappeared and products of microbial transformation appeared, but there was no indication of the appearance of additional phytotoxic compounds. This suggests that reactive oxygen species may be responsible, at least partially, for DOM phytotoxicity. This study provides important new information highlighting the characteristics of DOM that link with phytotoxic effects.