Predicting the impacts of clearing on vegetation communities: a model-based approach for identifying conservation priorities in Queensland, Australia

ABSTRACT

Predicting outcomes is critical for conservation prioritisation. We predicted the areas that are likely to be impacted using a generalised estimating equation from a logistic regression and intersected our model with vegetation community mapping for Queensland, Australia. Under the assumption that areas with a high probability of clearing would eventually be cleared, we identified vegetation communities at risk of transitioning into a more vulnerable status, addressing a critical knowledge gap. Specifically, we identify: 1) areas within the study region's bioregions face the highest risk of forest cover loss; 2) communities may transition to more vulnerable according to their extent-based vulnerability status. Our analysis determined high-risk areas within the study region and vegetation communities vulnerable to changing status. Three clearing scenarios – low, moderate and high – were evaluated. In the low scenario, 0.3 per cent of vegetation communities experienced clearing, with 26 communities changing their status. The moderate scenario impacted 35 per cent of vegetation communities, with 103 communities at risk. In the high scenario (our most aggressive assumption), 45 per cent of vegetation communities overlapped with areas suitable for clearing, affecting the status of 158 communities. We emphaise the need to protect high-risk communities while implementing effective management strategies in areas where clearing poses minimal threat.

KEYWORDS:

• Habitat loss
• Queensland
• predictive modelling
• risk-based approach
• regional ecosystems
• vegetation

Acknowledgement

The authors would like to acknowledge the valuable contributions of each team member to the design, analysis, and writing of this manuscript. Vanessa Adams and Stephanie Hernandez conceptualised the study. All authors developed the research questions, and designed the methodology. Stephanie Hernandez completed the data collection, data analysis, and interpretation of the results. Nicholas Murray, Stephanie Duce and Vanessa Adams provided expertise in spatial analysis and policy analysis and contributed to the development and implementation of research. Marcus Sheaves provided supervisory support and contributed to the statistical analysis. All authors contributed to the writing of the manuscript. Stephanie Hernandez conducted extensive literature reviews, coordinated discussions with Queensland’s Department of Environment and Science to ensure the accuracy of the interpretation of regional ecosystem identifications. The Authors acknowledge Peter Johnson who provided critical insights and expertise in the field of vegetation management and contributed to the interpretation of the findings. All authors actively participated in the writing and revision process, providing intellectual input, and approving the final version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Queensland State Government: [Grant Number 201600768].