E

cosystem stability—the capacity of ecological communities to maintain their functions and resist disturbances—is essential for sustaining the ecosystem services upon which human wellbeing relies. Biodiversity loss, driven by global change, represents one of the most pressing threats to ecosystem stability. Despite significant advancements, the mechanisms underlying the temporal stability of ecosystems remain insufficiently understood due to their inherent complexity and current methodological limitations. This challenge is further exacerbated by the increasing intensity of anthropogenic disturbances, highlighting the urgent need to develop more precise predictive tools to inform effective conservation strategies.

In this context, the present project aims to address these knowledge gaps through the integration of advanced theoretical frameworks, extensive ecological databases, and cutting-edge computational tools, such as deep learning and machine learning. Specifically, the project seeks to: (1) analyze the effects of dominant species on ecosystem stability and evaluate the consequences of the loss of subordinate species; (2) examine the functional traits of species that underpin their ecological responses to environmental fluctuations; (3) develop a conceptual framework that integrates species-level information within a community-level perspective to establish robust metrics for assessing temporal stability; and (4) build a predictive model incorporating environmental variables and climate change scenarios to forecast the temporal stability of ecosystems over time.

The proposed methodology will combine multiscale approaches—spanning species, community, and landscape levels—and will rely on data from established environmental monitoring networks at a global scale and in a specific region of Spain. This approach will enable the application of predictive models in real-world contexts, aiming to generate results that not only contribute to theoretical knowledge but also help provide practical tools for decision-making, fostering informed, sustainable, and evidence-based conservation strategies.