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A spatially explicit forest gap model was developed for the Sierra Nevada, California, and is the first of its kind because it integrates climate, fire and forest pattern. The model simulates a forest stand as a grid of 15×15 m forest plots and simulates the growth of individual trees within each plot. Fuel inputs are generated from each individual tree according to tree size and species. Fuel moisture varies both temporally and spatially with the local site water balance and forest condition, thus linking climate with the fire regime. Fires occur as a function of the simulated fuel loads and fuel moisture, and the burnable area is simulated as a result of the spatially heterogeneous fuel bed conditions. We demonstrate the model’s ability to couple the fire regime to both climate and forest pattern. In addition, we use the model to investigate the importance of climate and forest pattern as controls on the fire regime. Comparison of model results with independent data indicate that the model performs well in several areas. Patterns of fuel accumulation, climatic control of fire frequency and the influence of fuel loads on the spatial extent of fires in the model are particularly well-supported by data. This model can be used to examine the complex interactions among climate, fire and forest pattern across a wide range of environmental conditions and vegetation types. Our results suggest that, in the Sierra Nevada, fuel moisture can exert an important control on fire frequency and this control is especially pronounced at sites where most of the annual precipitation is in the form of snow. Fuel loads, on the other hand, may limit the spatial extent of fire, especially at elevations below 1500 m. Above this elevation, fuel moisture may play an increasingly important role in limiting the area burned.

A linkage between the two major modeling approaches to forest dynamics, transition Markovian models and jabowa-foret type simulators, is generated by developing a compact model of forest dynamics. This patch transition model utilizes functional roles instead of species. The roles or types are based on the regeneration and mortality characteristics of tree species; specifically, the requirements of canopy gaps for regeneration and the capacity to create canopy gaps upon death. A gap-size plot can be assigned to each of a set of states defined according to dominance of one of the roles. Transition probabilities among these states and mean holding times in each transition lead to semi-Markovian analytical calculations of the stationary state probabilities. Forest dynamics, as the proportions of total canopy space occupied by each role in a collection of gap-size plots, can be analyzed and simulated using a chain of first-order differential equations to emulate the distributed time-delays. Additional fixed time-delays in the transition of every pair of states is also included to account for long latencies. In addition to simplifying the simulations, the resulting model can also utilize available results of the theory of semi-Markov processes; and therefore, can provide analytical guidance to the simulations, the feasibility of direct exploration of hypothesis and the possibility of fast computation from closed-form solutions and formulae. These advantages can especially be useful in the simulation of landscape dynamics and species-rich tropical forests.

The importance of life-history traits to vegetation pattern and system-level behavior was evaluated for two North American ecosystems, a semiarid grassland and an eastern deciduous forest. Responses of the systems to spatial and temporal variability in environmental conditions were compared using a common modeling framework, a class of individual-based simulators known as ‘gap models’ that incorporate life-history mechanisms to simulate mixed-species, mixed-lifeform and mixed-age communities. A grassland (STEPPE) and a forest model (ZELIG) of similar structure were used to provide a comparative analysis between the two ecosystem types. Life-history traits were important in distinguishing dynamics between the simulated grassland and forest. Responses of the two systems to spatial extent and temporal variability were not simply scaled by the size or rate of processes associated with individual grasses or trees. Two important characteristics of a system were the form of growth by the dominant species (clonal or incremental) and the mode of competition (symmetric, asymmetric). Perennial grasses with clonal growth were responsive to a broader range of environmental conditions relative to the more restrictive response of individual trees with incremental growth. The endogenous rhythm associated with the lifecycle of individual trees was important to forest dynamics, but was not important for systems dominated by clonal grasses with an indefinite lifespan. Asymmetric competition for light by individual trees resulted in different system-level dynamics than for a grassland, where symmetric competition for belowground resources by individual grassland plants is the primary mode of competition.

We describe an approach to investigating and understanding the interactions between vegetation structure and ecosystem processes that uses simulation models as a framework for comparison and synthesis across ecosystems arrayed along environmental gradients. The models are individual-based vegetation simulators and compartment models of nutrient cycling and soil water relations. Applications focus on interactions and feedbacks between vegetation structure (species composition, size structure) and ecosystem processes (water balance, nutrient cycling), and how these relationships vary across environmental gradients. Preliminary results indicate that life-history traits of plants have a profound influence on system-level behaviors, and that differences between grasslands and forests can be attributed largely to contrasting traits of grasses and trees. Experiments with linked vegetation-ecosystem process models diverge from simulations with either model run independently, suggesting the importance of feedbacks between details of vegetation pattern and ecosystem processes. The development of a fully coupled vegetation-ecosystem process model that is sufficiently general to simulate systems dominated by multiple lifeforms presents several conceptual, logistical, and scaling challenges, but also provides for new opportunities in ecosystem theory.

The Forest Ecosystem Dynamics (FED) project involves the development of an integrated mathematical model which links individual submodels of soil processes, forest growth and succession, and radiative transfer. The model will accommodate spatial scales from local to regional, and temporal scales from physiological to long term ecological processes. In its integrated form, the model is designed to simulate a forest ecosystem operating in a “process-response” manner whereby natural or anthropogenically induced changes in the environment will elicit responses within the soil, vegetation, and radiation regime of a forest that will impact and modify each other. In order to insure maximum flexibility for both the modeler and the user, an “object-oriented” structure will be implemented. In this way, the model will provide a tool with which patterns and processes within northern forests resulting from global change can be predicted.