Conservation & ecosystem management

Conservation & ecosystem managements

We develop data-driven solutions to tackle biodiversity loss caused by habitat destruction, invasive species, overpopulation, and climate change. We use stochastic models to optimize species management,

A core focus of our work is assessing the ecological and economic impacts of invasive species, providing actionable strategies to mitigate their effects. By leveraging long-term ecological data, we design proactive conservation approaches that enhance ecosystem resilience. We also develop cost-effective management strategies for species like koalas, feral cats, pigs and rabbits, ensuring practical applications for conservation efforts.

Through collaboration with citizen scientists, conservation organisations, and policymakers, we aim to bridge the gap between science and action.

Main contributions

Saltré, F., et al, (2025). Balancing overpopulation and conservation targets to optimize koala management strategies. Ecology & Evolution, 15 (1): 4364.

Hamnett, P., et al, (2024). Stochastic population models to identify optimal and cost-effective harvest strategies for feral pig eradication. Ecosphere, 15 (1): 4364.

Mathwin, R., et al, (2024). Stochastic metapopulation dynamics of a threatened amphibian to improve water delivery. Proceedings of the National Academy of Sciences, 121 (1) e2311280120.

Bradshaw, CJA., et al., (2024). Damage costs from invasive species exceed management expenditure in nations experiencing lower economic activity. Quaternary Geochronology, 79: 101489.

Mathwin, R., et al, (2024). Modeling the effects of water regulation on the population viability of a threatened amphibian. Nature Communications, 10:5311.

Venning, KWR., et al, (2021). Predicting targets and costs for feral-cat reduction on large islands using stochastic population models. Ecography 42: 1587-1599.

Roy-Dufresne, E., et al, (2019). Modelling the distribution of a wide-ranging invasive species using the sampling efforts of expert and citizen scientists. Global Change Biology, 24: 1371-1381.

Roy-Dufresne, E., et al, (2019). The Australian National Rabbit Database. Nature Communications, 7(1): 10511.

Fordham, D., et al, (2016). Predicting and mitigating future biodiversity loss using long-term ecological proxies. Method in Ecology & Evolution, 6(3): 247-256.

Saltré, F., et al, (2015). How climate, migration ability, and habitat fragmentation affect the projected future distribution of European beech. Global Change Biology, 21(2): 897-910.