Monitoring rare flora species using quantitative methods


Astron recently collaborated with a mining client to improve a monitoring program focused on a Declared Rare Flora species adjacent to a mine. The purpose of the program is to detect potential indirect impacts on the health of the plant from mining; for example, dust deposition. Methods in the original program were largely reliant on subjective visual assessments of health. The program was improved by incorporating an efficient and quantitative measure of plant health using a Plant Efficiency Analyser or PEA.

The PEA is a small portable instrument which senses and analyses chlorophyll fluorescence to determine the level of photoinhibition within a leaf: a reliable indicator of leaf physiological health. Photoinhibition can be affected by a range of stressors and is often quantified by the parameter: variable fluorescence divided by maximum fluorescence (Fv/Fm) The Fv/Fm metric has long been recognised as an indicator of plant physiological health and is also favourable as it is a quantitative measure of plant health, rather than a scoring system. Another advantage of Fv/Fm is that it is a leading indicator of plant health; Fv/Fm data may indicate changes in the physiological health of plants that are yet to manifest in ways that can be observed by the human eye.

The trial took place at sites both near and far from the mine pit. At each site several plants were measured for Fv/Fm and scores assigned for health and dust deposition.

Results indicated that Fv/Fm readings were correlated with other measures of plant health and distance from the mine pit had no relationship with plant health readings. There was no significant relationship between dust deposition and Fv/Fm readings.

The PEA was demonstrated to be a practical and quantitative method for monitoring the health. Astron’s plant physiologists and statisticians have a solid track record in improving flora and vegetation monitoring programs by incorporating scientific methods and rigorous sampling designs. We have found that this twin approach not only improves monitoring programs, it also improves cost efficiency.

Monitoring rare flora species using quantitative methods
Monitoring rare flora species using quantitative methods : Image 1