Forest Dynamics and Tree Mortality Modeling

Forest dynamics models seek to represent the processes governing the structure, composition and function of forest ecosystems over time. Central to these models are the demographic processes of regeneration, growth, competition and mortality, which collectively determine patterns of biomass accumulation, species turnover and carbon cycling. Approaches range from individual‐based and gap models that resolve tree-by-tree interactions to cohort-based and dynamic vegetation models operating at landscape or regional scales. Mortality modelling encompasses empirical formulations derived from long-term inventories, process-based representations of hydraulic failure and carbon starvation, and theoretical constructs grounded in plant physiology. Recent advances emphasise the role of species-specific traits, community composition and disturbance regimes in driving tree death, while methodological innovations have improved parameter estimation through data assimilation, imputation of missing trait values and calibration against historical observations. Robust mortality submodels are now recognised as one of the greatest sources of uncertainty in long-term projections, particularly under novel climate conditions. Improved understanding of indirect effects—such as shifts in recruitment and diversity–productivity relationships—and direct physiological responses to heat and drought has significant implications for forest management, carbon sequestration planning and biodiversity conservation at global to regional scales.

Research from Nature Portfolio

Recent studies have disentangled the direct physiological impacts of climate change from the indirect effects mediated by shifts in species composition. Simulations across temperate forests demonstrate that compositional turnover often amplifies or mitigates productivity responses to warmer and drier conditions, chiefly by altering complementarity in resource use. Warmer climates have been shown to modify diversity–productivity relationships by favouring drought-tolerant or fast-growing species, underlining the pivotal role of recruitment dynamics in long-term ecosystem resilience. These findings highlight that accurate projections of productivity and carbon storage hinge on models that capture both physiological stress responses and community-scale compositional change.

Research from all publishers

Trait-enabled, cohort-based models now integrate high-resolution functional trait databases and phylogenetic information to simulate Mediterranean forest dynamics. By defining over 200 taxonomic entities and employing meta-modelling and imputation workflows, these models improve representation of species-level growth and mortality, yielding regional-scale projections of basal area that align closely with empirical inventories.

A comparative assessment of 15 dynamic vegetation models revealed that the choice of mortality submodel can drive differences of up to 170 percent in basal area trajectories under future climate scenarios. Sensitivity to mortality formulation often exceeds that to climate forcing, emphasising mortality as a critical uncertainty in long-term projections.

In unmanaged old-growth stands, adding empirically derived equations for seed production and seedling survival into gap models markedly enhances simulation of species composition and recruitment processes. This work demonstrates that seedling-to-sapling transition times and early-life mortality critically shape community turnover, particularly under changing climatic regimes.

Forest Dynamics and Tree Mortality Modeling publication trend

The graph below shows the total number of articles in forest dynamics and tree mortality modeling across all publications each year (not limited to Nature Index journals).

Technical terms

Dynamic vegetation model: A simulation framework representing forest processes (growth, competition, mortality, regeneration) across spatial scales.

Mortality submodel: The component of a vegetation model that quantifies tree death probabilities based on size, competition, climate or physiology.

Trait-enabled model: A model parameterised using species functional traits (leaf area, wood density) rather than broad plant functional types.

Cohort: A group of trees sharing the same species, size class or age, treated collectively to reduce computational complexity.

Basal area: The cross-sectional area of all tree stems per unit land area, commonly used as a proxy for stand density and competition.

Species recruitment: The process by which new individuals establish, survive and enter the sapling cohort, influencing future stand composition.

References

1. MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales. Geoscientific Model Development (2023).
2. Tree mortality submodels drive simulated long‐term forest dynamics: assessing 15 models from the stand to global scale. Ecosphere (2019).
3. The importance of regeneration processes on forest biodiversity in old-growth forests in the Pacific Northwest. Philosophical Transactions of the Royal Society B Biological Sciences (2024).
4. Long-term response of forest productivity to climate change is mostly driven by change in tree species composition. Scientific Reports (2018).
5. The evolution, complexity and diversity of models of long‐term forest dynamics. Journal of Ecology (2022).