Forest Dynamics and Climate Change Modeling

Forest dynamics encompass the processes of growth, mortality, regeneration and succession that shape forest structure and composition over time. In the context of a changing climate, these processes are increasingly driven by alterations in temperature, precipitation patterns, CO₂ concentrations and extreme weather events. Dynamic vegetation models and forest landscape models integrate ecophysiological principles, demographic rates and disturbance regimes to simulate how forests respond to these drivers across spatial and temporal scales. Such models are calibrated with field inventory data, remote sensing observations and experimental results to project shifts in species ranges, biomass accumulation and carbon cycling. By linking fine‐scale processes (for example, competition for light and water) with landscape‐level phenomena (such as fire, pest outbreaks and land use change), researchers can explore feedbacks between forests and the climate system, assess vulnerability hotspots and inform adaptive management strategies. This modelling framework underpins assessments of carbon sequestration potential, biodiversity conservation and ecosystem service delivery under scenarios of moderate to high greenhouse gas emissions.

Research from Nature Portfolio

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Research from all publishers

Recent work in northeastern China has used a process‐based ecosystem model to simulate aboveground biomass trajectories for mixed Korean pine–hardwood and larch–hardwood assemblages under multiple RCP scenarios. Results indicate that coniferous species generally exhibit an initial rise in biomass under moderate warming, followed by declines under high‐emission pathways, while temperate hardwoods tend to gain competitive advantage and shift their distributions northwards. Such projections offer guidance for adjusting species selection in afforestation and conservation planning.

In the Southern Carpathians, a coupled landscape succession and ecophysiological model applied across an altitudinal gradient reveals that, although total biomass may increase in the near term, medium‐ to long‐term shifts in species composition are likely. Beech and spruce show sensitivity to extreme warming scenarios, whereas silver fir and other montane species may expand. These findings underscore the need to adapt silvicultural practices—such as selective thinning and assisted migration—to maintain forest resilience and sustain productivity in mountain landscapes.

Forest Dynamics and Climate Change Modeling publication trend

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

Technical terms

Forest landscape model: A simulation tool that represents interactions among tree growth, disturbances (fire, pests, harvesting) and spatial processes (seed dispersal, connectivity) across large areas.

Representative Concentration Pathway (RCP): A greenhouse gas concentration trajectory used in climate modelling to describe potential future radiative forcing levels.

Aboveground biomass: The total mass of living plant material (stems, branches, foliage) per unit area, often expressed in tonnes of dry matter per hectare.

Carbon sequestration: The process by which forests accumulate and store carbon in biomass and soils, mitigating atmospheric CO₂ increases.

References

1. Assessing the impact of climate warming on tree species composition and distribution in the forest region of Northeast China. Frontiers in Plant Science (2024).
2. A large‐scale forest landscape model incorporating multi‐scale processes and utilizing forest inventory data. Ecosphere (2013).
3. Shifts in Forest Species Composition and Abundance under Climate Change Scenarios in Southern Carpathian Romanian Temperate Forests. Forests (2021).