Using spatially explicit individual-based models to prioritize conservation strategies: A case study on the little bustard

Steppe birds are among the most threatened terrestrial birds worldwide, requiring urgent, well-planned, and cost-effective conservation strategies to halt population declines. The little bustard (Tetrax tetrax) is one of those species that has experienced sharp population declines across its western range, yet the effectiveness of different management interventions remains poorly understood. Predictive models, such as Individual-Based Models (IBM), provide powerful tools to anticipate and assess the effectiveness of conservation scenarios for endangered species, supporting evidence-based management decisions.

In this study, we developed a spatially explicit demographic IBM to evaluate conservation strategies for the little bustard in Extremadura, Spain, where the species faces a skewed sex ratio towards males, habitat degradation and high anthropogenic mortality. Our model integrates high-resolution habitat suitability data with demographic parameters to simulate individual behaviours and interactions with the environment, forecasting habitat use and population dynamics under different management strategies.

The model calibration process supported the hypothesis that nest, chick, and adult survival positively correlate with habitat suitability. Notably, our results suggest that the unbalanced sex ratio is partially driven by low female survival rates in less favourable habitats. We simulated conservation strategies focused on habitat improvement and the mitigation of anthropogenic mortality over 50 years (2022–2072). The results indicate that habitat enhancements alone are insufficient to reverse population declines without complementary efforts to reduce anthropogenic mortality. This finding emphasizes the need for an integrated, long-term conservation strategy that combines habitat management with proactive measures to mitigate human-induced mortality, ensuring the sustainable recovery of little bustard populations.

More broadly, this study highlights the value of IBMs as high-resolution, spatially explicit decision-support tools for conservation planning, offering critical insights into prioritizing and implementing cost-effective strategies.