Australian Acacia species, commonly known as wattles, have been widely introduced outside Australia, with some species now amongst the most widespread and damaging invasive trees globally. Early warning and monitoring systems that can track the distribution and dispersion of novel introduced species or monitor the establishment and spread of those that have been introduced are required to aid scientists, policymakers, land managers and other stakeholders in the prevention of further wattle introductions.
This chapter provides an overview of the commonly used modelling techniques in the study of wattles, and specifically modelling aimed at predicting invasiveness useful for the early warning, assessment, and monitoring of wattles. A systematic review of published literature is first conducted to understand the spatial-temporal extent of modelling applications across different wattle species, and to provide an overview on the main modelling techniques and types of data adopted in wattle research. Then, applications of such modelling techniques and data are illustrated by a set of case studies, specifically focused on the use of (1) remote sensing data, (2) citizen science data and (3) the application of dynamic models to address wattles.
The chapter integrates ideas and examples that can be useful for guiding prediction of future wattle introductions, establishment, and invasions. Even though modelling tools have their limitations, they allow to study real-world challenges through testing hypothesis and analysing potential scenarios, which is useful to address topics like the adaptive management of ever-shifting social-ecological systems