Climate change and biodiversity loss are increasingly recognised as interdependent processes rather than parallel crises. Shifts in climate reshape species composition, phenology and community structure; biodiversity in turn modulates carbon, water and energy exchange, ecosystem stability and the capacity of ecosystems to buffer climate extremes. Despite this coupling, the two domains are still largely investigated with separate observational systems, model families and scientific communities. Closing that gap is a prerequisite for credible projections of ecosystem functioning and for the ecosystem services that societies depend on.
This session invites contributions that explicitly address the climate–biodiversity nexus and its consequences for ecosystem functioning and service delivery. We welcome work across terrestrial, freshwater and coastal ecosystems, from the plot to the continental scale, and across natural, agricultural, forest and urban systems.
Topics of interest include, but are not limited to:
• Joint effects of climate variability, extremes and biodiversity change on productivity, carbon and water fluxes, and ecosystem stability and resilience;
• Integrated monitoring of climate and biodiversity — flux towers, ecological and biodiversity networks, eDNA, acoustic and camera-based sensing, satellite and airborne remote sensing, and the fusion of these streams;
• Process-based, trait-based and coupled climate–ecosystem models that represent biodiversity explicitly;
• Artificial intelligence and machine learning for detecting biodiversity and functional change, upscaling in-situ observations, emulating and constraining models, and handling sparse or heterogeneous ecological data;
• Quantification, mapping and valuation of ecosystem services under combined climate and biodiversity pressures;
• Evidence supporting nature-based solutions, restoration and adaptation planning, including uncertainty communication and use in policy and climate services.
We particularly encourage submissions that cross disciplinary boundaries — combining ecology, climate science, remote sensing and data science — and contributions from early career scientists.