Functional diversity in motion: a general theory of eco-evolutionary change in complex ecosystems

Most ecosystems are characterized by a rich and dynamic landscape of functional diversity. Ecological interactions that drive biodiversity and adaptation are profoundly complex — they arise from fine‐scale variation in organismal traits, unfold across ecological and evolutionary timescales, and operate within dynamic ever-changing environments. An individual’s performance, and thus its contribution to community structure and ecosystem functioning, emerges from the following key factors: (1) its physiological state (such as size, age, or energy reserves), (2) its capacity to acclimate to short-term microclimatic changes, (3) trait-mediated trade-offs it faces in growth and survival, (4) the traits and states of other organisms in the community, and (5) the long-term abiotic environment which itself may be co-created by the population. To understand how functional diversity is filtered and reshaped by these processes, we need a theory that can play out long-term eco-evolutionary dynamics of ecosystems while incorporating realistic ecological complexity. 

Here, we introduce a unified trait-based eco-evolutionary framework that meets this challenge by explicitly integrating three core features of real ecosystems: (1) continuous physiological state structure, (2) intraspecific and interspecific trait variation, and (3) frequency-dependent selection driven by population–environment feedbacks. The framework can be coupled to trait-based eco-physiological models of individual performance, allowing short-term acclimation and long-term evolution to be treated within a single, coherent system. This makes it possible to predict the best-adapted trait combinations under different environments, to test whether physiological trade-offs encoded in models are consistent with observed trait distributions along environmental gradients, and to project how those distributions will shift under future short- and long-term environmental change. At the same time, the approach provides a scalable alternative to computationally intensive individual-based models while retaining key sources of ecological and evolutionary complexity.

We apply this framework to predict plant hydraulic strategies across environmental gradients by coupling it with the Plant-FATE model, which accounts for physiological acclimation of individuals and trait-size-structured vegetation demographics of populations. The theory predicts that, all else being equal, plants evolve more negative xylem vulnerability (P50) in drier environments, matching broad empirical patterns across real ecosystems. This agreement provides an evolutionarily grounded validation of the functional trade-offs embedded in plant physiology and enables robust forecasts of how trait distributions — and their biogeochemical implications — are likely to respond to ongoing environmental change.