Grey Coupland

Learn how to turn degraded land on school grounds into a thriving biodiverse Bush Classroom for two-way learning. Bush Classrooms are culturally responsive, outdoor learning areas that privilege the first cultures of this country and celebrate Aboriginal ways of knowing, being and doing. Bush Classrooms provide opportunities to deliver components of the Western Australian Curriculum while supporting student and community engagement and wellbeing. 

Miyawaki forests are becoming increasingly popular for greening and enhancing biodiversity in our urban landscapes. These forests offer an alternative to traditional methods of urban greening and have the capacity to provide the multifaceted benefits associated with urban forests at a more rapid rate. As part of a Miyawaki Forest Program at Murdoch University, 15 Miyawaki forests have been planted in the south-west of Australia, a Mediterranean climate. Forests planted as part of this program are restoring small pockets of the endangered woodlands plant community. Plantings are based on research adapting the methodology to suit the region’s unique plant species and environment. The survivorship and growth rate of plants is recorded in these forests and compared with adjacent plantings using traditional methods for reforestation. Biodiversity and abundance of soil organisms in these forests and in nearby bushland are assessed using eDNA and soil respiration rates. Citizen scientist data are also gathered by school children involved in the outreach aspects of the program. Results to date indicate rapid growth of Miyawaki forests in the Australian context, and that these forests can be biodiversity havens and a valuable tool for bringing biodiversity into our cities.

Globally, biodiversity is increasingly under threat, with action required at the national level to mitigate the crisis. However, at the local level, citizens often feel powerless to act. This is where planting of Miyawaki forests has become an increasingly popular choice for non-government organisations, community groups and local councils. The Miyawaki methodology is attractive because these forests are perceived to be small scale projects that can be carried out by citizen scientists, and have considerable environmental benefits. This rationale stems from reports of Miyawaki forests exhibiting high growth rates and biodiversity: forests have been reported to grow up to ten times faster and contain up to 100 times the biodiversity of forests planted using traditional reforesting techniques. As such, these tiny forests punch above their tiny size in terms of their ability to become the hero for engaging the community in environmental action, as well as creation of biodiversity hotspots and more liveable urban environments. To test how well these forests can be planted and monitored by citizen scientists, a Miyawaki forest has been planted by children at a local Perth primary school under the guidance of a researcher. Children will monitor the forest as citizen scientists over the next ten years, gathering data on plant growth, animal and plant biodiversity and forest temperature regimes. The researcher will investigate soil biodiversity using eDNA, microbial activity and soil nutrients. There is a paucity of data available on the biological performance of Miyawaki forests. As such, the project will provide valuable information to decision makers, enabling more informed decisions on whether the more prescriptive Miyawaki method is the most suitable use of resources relative to environmental outcomes for urban revegetation programmes, and help us determine if these tiny forests really can be a big hero for community led environmental action.

The development of inspection protocols and mitigation strategies are critical components of plant and animal biosecurity measures. The inclusion of available detection data can greatly enhance the evidence base for these types of decisions. However, a key step in analysing these data is the choice of an appropriate statistical model. This paper focuses on determining an appropriate model for biosecurity border and post-border detection of non-indigenous species for Barrow Island, Australia under stringent biosecurity controls. This is a flagship biosecurity project that is under close national and international scrutiny. A range of standard models were compared, including standard and zero-inflated Poisson, negative binomial and log-normal alternatives. These models failed to adequately describe the key characteristics of the data, namely an excess of zero and single organism detections, a range of detections between two and a hundred organisms, and a few extreme values, ranging between 250 and 1000 organisms. Alternative models were explored, including: (i) modelling the censored data ignoring the zero and extremely large detections, (ii) a component where detections were modelled ignoring the zero detections and including outliers and finally, (iii) zero-inflated model with the complete data set inclusive of zero detections. The negative binomial based models consistently gave the best outcomes under different degrees of inflation or over-dispersion, but are limited in that they cannot provide information about the mechanisms underlying zero-inflation. A three component log normal mixture model was found to be the best fit as it addressed these issues. This study demonstrates the importance of model choice in analysing biosecurity data, and suggests that mixture models may be more appropriate than more standard distributions. The data set gathered at Barrow Island is, however, unique for biosecurity border and post-border detection biosurveillance. Given this, general inferences about the underlying phenomena made based on the model should be made with caution. Comparable datasets should be obtained and tested to validate the choice of model for this type of data.