Which species? A decision-support tool to guide plant selection in stormwater biofilters. (March 2018) - Payne, Emily G.I.; Pham, Tracey; Deletic, Ana; Hatt, Belinda E.; Cook, Perran L.M.; Fletcher, Tim D.
Highlights: Extensive roots, high biomass and growth are critical to effective nitrogen removal Plant nitrogen assimilation is a key driver, occurring alongside high water uptake High root length is a key driver trait in both wet and dry conditions Very low water loss also beneficial in dry Decision-support tool developed to facilitate species selection Abstract: Plant species are diverse in form, function and environmental response. This provides enormous potential for designing nature-based stormwater treatment technologies, such as biofiltration systems. However, species can vary dramatically in their pollutant-removal performance, particularly for nitrogen removal. Currently, there is a lack of information on how to efficiently select from the vast palette of species. This study aimed to identify plant traits beneficial to performance and create a decision-support tool to screen species for further testing. A laboratory experiment using 220 biofilter columns paired plant morphological characteristics with nitrogen removal and water loss for 20 Australian native species and two lawn grasses. Testing was undertaken during wet and dry conditions, for two biofilter designs (saturated zone and free-draining). An extensive root system and high total biomass were critical to the effective removal of total nitrogen (TN) and nitrate (NO3 − ), driven by high nitrogen assimilation. The same characteristics were key to performance under dry conditions, and were associated with high water use for Australian native plants; linking assimilation and transpiration. The decision-support tool uses these scientific relationships and readily-available information to identify the morphology, natural distribution and stress tolerances likely to be good predictors of plant nitrogen and water uptake. Graphical abstract: Image, graphical abstract