Towards reliable and explainable models for anticipating ecological change (2021–2024)
- Abstract:
- This project aims to develop a quantitative framework for multivariate ecological prediction. This will allow us to better anticipate how ecosystems respond to environmental change. Recent modelling advances now make it possible to use the complexity of community ecology data to deliver better predictions. The project intends to use long-term ecological datasets to build and test novel multivariate prediction models, using tick paralysis rates in Australian dogs as a case study. Expected outcomes are better tools for studying ecosystem change and new hypotheses about how ecological communities are shaped. Application of these models should provide significant benefits, such as prediction of paralysis tick burdens to improve risk mitigation.
- Grant type:
- ARC Discovery Early Career Researcher Award
- Researchers:
-
-
- Funded by:
- Australian Research Council
