An individual-based process model to simulate landscape-scale forest ecosystem dynamics

Forest ecosystem dynamics emerges from nonlinear interactions between adaptive biotic agents (i.e.,
individual trees) and their relationship with a spatially and temporally heterogeneous abiotic environment.
Understanding and predicting the dynamics resulting from these complex interactions is crucial for
the sustainable stewardship of ecosystems, particularly in the context of rapidly changing environmental
conditions. Here we present iLand (the individual-based forest landscape and disturbance model), a novel
approach to simulating forest dynamics as an emergent property of environmental drivers, ecosystem
processes and dynamic interactions across scales. Our specific objectives were (i) to describe the model, in
particular its novel approach to simulate spatially explicit individual-tree competition for resources over
large scales within a process-based framework of physiological resource use, and (ii) to present a suite of
evaluation experiments assessing iLands ability to simulate tree growth and mortality for a wide range of
forest ecosystems. Adopting an approach rooted in ecological field theory, iLand calculates a continuous
field of light availability over the landscape, with every tree represented by a mechanistically derived,
size- and species-dependent pattern of light interference. Within a hierarchical multi-scale framework
productivity is derived at stand-level by means of a light-use efficiency approach, and downscaled to individuals
via local light availability. Allocation (based on allometric ratios) and mortality (resulting from
carbon starvation) are modeled at the individual-tree level, accounting for adaptive behavior of trees in
response to their environment. To evaluate the model we conducted simulations over the extended environmental
gradient of a longitudinal transect in Oregon, USA, and successfully compared results against
independently observed productivity estimates (63.4% of variation explained) and mortality patterns in
even-aged stands. This transect experiment was furthermore replicated for a different set of species and
ecosystems in the Austrian Alps, documenting the robustness and generality of our approach. Model
performance was also successfully evaluated for structurally and compositionally complex old-growth
forests in the western Cascades of Oregon. Finally, the ability of our approach to address forest ecosystem
dynamics at landscape scales was demonstrated by a computational scaling experiment. In simulating
the emergence of ecosystem patterns and dynamics as a result of complex process interactions across
scales our approach has the potential to contribute crucial capacities to understanding and fostering
forest ecosystem resilience under changing climatic conditions.

Keywords: Forest ecosystem dynamics, Complex adaptive systems, Individual-based modeling, Ecological field theory, Hierarchical multi-scale modeling, Forest structure and functioning