Unexpected global biodiversity responses to climate change arise from complex adaptation, seascape, and dispersal dynamics
Abstract
Abstract Global marine biodiversity peaks in the tropics and is widely projected to shift polewards under climate warming as species track thermal optima. These projections rely largely on phenomenological models that treat species responses as shifts in climate suitability and neglect fundamental eco-evolutionary dynamics. The consequences of these dynamics in fluctuating populations for global biodiversity patterns therefore remain unresolved. We addressed this deficit by integrating local adaptation, dispersal, and gene flow – mediated trait homogenisation into spatially explicit global simulations of >1,400 tropical reef fishes under climate change. Biodiversity responses departed systematically from simple poleward redistribution. Depending on the interaction between dispersal and adaptive capacity, latitudinal richness peaks widened or narrowed, shifted equatorward or poleward, or collapsed entirely. These alternative regimes emerged from threshold-dependent interactions between seascape connectivity, metapopulation trait homogenisation, and accumulating thermal stress. Critically, greater dispersal enhanced persistence only below seascape-driven connectivity thresholds; beyond which homogenisation of traits across thermally heterogeneous populations disrupted local adaptation – particularly at metapopulation peripheries – and increased extinction risk. Continuous demographic feedback further generated cumulative stress and extinction tipping dynamics absent from snapshot suitability models. Our results show that eco-evolutionary dynamics can invert or destabilise expected climate-driven redistribution patterns, indicating that projections excluding these mechanisms may systematically misestimate the magnitude and direction of global biodiversity change in a rapidly warming ocean.
Fields of Study & Subjects
Coral and Marine Ecosystems Studies
Species Distribution and Climate Change
Fish Ecology and Management Studies
Publication details
- Journal / source
- bioRxiv (Cold Spring Harbor Laboratory)
- Publication date
- 5 March 2026
- Language
- EN
- Document type
- Preprint