Short Oral Presentation 12th Australian Streams Management Conference 2026

Tried, true and new: An ever-evolving vegetation monitoring program (138726)

Trish Grant 1 , Jo Slijkerman 1 , Sacha Jellinek 2 , Jonathan Wilson 2 , Al Danger 2
  1. Water Technology P/L, Notting Hill, VIC, Australia
  2. Melbourne Water, Melbourne, Vic, Australia

Context and Rationale

Understanding the condition and trajectory of streamside vegetation across the Melbourne Water region is critical for setting strategic priorities and identifying drivers of change, including climate impacts and threats such as deer. The Streamside Vegetation Assessment (SVA) program, first implemented in 2021, is designed to track long-term change and is repeated every five years to build a robust evidence base.

Method and Approach

The second round of monitoring has recently been completed. Multiple teams undertook rapid condition assessments at 506 sites across the region, stratified by sub-catchment and selected to represent a diversity of land uses and tenures. Detailed assessments were conducted at 80 sites to capture finer-scale information. Wherever possible, junior botanists were paired with experienced practitioners to support professional development, knowledge transfer, and industry networking.

Results and Outputs

Site-based condition scores have been spatially linked to stream reaches to generate reach-averages that interestingly correlate well with expert elicitation data collected in 2018. Summary statistics comparing 2021 and 2025 results are presented; however, additional rounds will be required before trends in condition change can be determined with confidence.

Outcomes and Impact

Beyond its long-term monitoring objectives, the dataset is already supporting additional applications. The SVA data can be used to train and refine remote sensing algorithms, enabling extrapolation of botanist-collected detail across larger spatial extents. The 2025 survey also captured enhanced in-stream species data to inform future habitat suitability modelling. Mentoring and collaboration emerged as one of the most immediate and valued outcomes of the program.