METHODS

Ecological simulation in computational design

Rhino.Ecologic enables designers to explore how plant communities develop in response to spatial design decisions. By combining environmental analysis with ecological simulation, the framework links geometry, environmental conditions, and plant dynamics within Rhino and Grasshopper. Rather than treating vegetation as a static layer applied after form generation, the system models plant communities as dynamic systems that evolve in response to spatial configuration and environmental conditions.

This approach reframes ecological performance as an emergent property of design decisions. Geometry, environmental parameters, and biological processes are coupled within a computational framework, allowing ecological outcomes to be explored during the design process rather than assessed retrospectively.

From geometry to ecological domain

Similar to pixels in a two-dimensional image, voxels subdivide three-dimensional space into discrete volumetric units. At the core of the system lies the transformation of three-dimensional design geometry into a discretized spatial domain. Voxelization provides a common spatial representation for geometry, environmental analysis, and ecological simulation. By operating within the same discretized domain, environmental conditions and plant interactions can be evaluated consistently across complex three-dimensional designs.

Project geometry is converted into a structured voxel grid, where each voxel represents a volumetric unit of space and serves as the fundamental carrier of environmental and ecological information. The voxelization process establishes spatial resolution, adjacency relationships, boundary conditions, and environmental sampling points within the model.

This discretized representation defines the topology within which ecological processes unfold. It enables localized interaction between plants and their immediate environment while maintaining a direct correspondence to the original design geometry.

Environmental mapping

Before plant communities can be simulated, the system must determine the environmental conditions at every location within the model. Environmental conditions are derived directly from geometry and geographic context and are computed at voxel resolution. These include solar exposure, soil depth and volume, and precipitation distribution, forming a spatially explicit representation of environmental heterogeneity.

Solar exposure is determined through geometric shading and radiation analysis. Soil depth and volume define the available rooting space within the voxel domain, while precipitation distribution represents spatial water input across the system. Together, these parameters define the environmental constraints under which plant communities develop.

Environmental conditions are not approximated globally but resolved locally, enabling differentiated ecological responses across surfaces, volumes, and orientations.

Ecological simulation

Ecological dynamics are simulated using an individual-based community model, the Joschinski Model (Joschinski et al., 2024).

Within this framework, each plant is represented as an individual entity defined by functional traits. Growth, reproduction, and mortality occur at the level of individual organisms, and ecological processes emerge from interaction between plants and their environment.

Simulation proceeds in discrete annual time steps and includes germination, growth and biomass accumulation, resource allocation, shading and competition, reproduction and dispersal, and mortality. Solar energy intercepted by plant crowns is converted into biomass according to species-specific efficiencies, while maintenance costs and environmental limitations influence survival.

Competition emerges from spatial overlap and light availability rather than imposed hierarchy. Community structure is not predefined but develops from local interaction under environmental constraints.

Emergence and temporal dynamics

Every design iteration becomes an ecological scenario. Changes in geometry produce different environmental conditions, leading to different trajectories of plant community development.

Ecological outcomes in Rhino.Ecologic are emergent. Species distribution, biomass & plant volume development, and biodiversity patterns arise from the interaction of spatial configuration, environmental conditions, species traits, and stochastic variation.

Because the model operates over time, ecological performance is inherently temporal. Outputs represent trajectories rather than static states, enabling the evaluation of succession processes, long-term biomass development, species turnover, and ecological stability.

Design scenarios can therefore be assessed not only for immediate performance, but for their long-term ecological behavior.

Integration into the design workflow

Rhino.Ecologic is embedded within the Rhino and Grasshopper environment, allowing ecological simulation to operate directly within parametric design workflows.

Each modification to geometry such as changes in massing, soil configuration, or exposure alters the environmental conditions of the voxel domain. These changes propagate through the ecological simulation, producing different trajectories of plant community development.

Each design iteration can therefore be understood as an ecological scenario in which biodiversity, biomass, and spatial patterns emerge from the interaction between form and environment.

Data and interpretation

Simulation results are accessible at multiple levels, including voxel-level environmental data, plant-level ecological data, and aggregated statistical outputs. These data can be visualized, extracted, and integrated into further analysis or optimization workflows.

Rhino.Ecologic does not predict exact species occurrence. Instead, it simulates potential ecological dynamics under defined conditions. Outputs should be interpreted as scenario-based projections, relative performance indicators, and comparative design metrics rather than deterministic predictions.

Scope and limitations

Rhino.Ecologic is designed for early-stage and intermediate design exploration at architectural and urban scales. The model operates on simplified representations of environmental processes, uses generalized plant trait data, and assumes a discretized spatial resolution.

It does not replace detailed ecological field analysis or site-specific ecological expertise. Instead, it provides a computational framework for integrating ecological reasoning into design workflows.

Summary

Rhino.Ecologic establishes a method in which ecological processes are treated as integral components of spatial design. By coupling voxel-based environmental mapping with individual-based ecological simulation, the system enables the representation of environmental heterogeneity, the simulation of plant community dynamics, and the evaluation of long-term ecological performance within a unified computational environment. Individual-based simulation allows competition, succession, and community structure to emerge from local interactions rather than being prescribed in advance.

Ecology, in this framework, is not an external constraint but an active system operating within design space.

Rhino.Ecologic is a free Grasshopper plugin for Rhino 8 and Rhino BETA for Windows.

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Further explore Rhino.Ecologic!

METHODS → Understand the ecological & environmental models behind the simulation.
DOCUMENTATION → Everything you need to run your first simulation.
RESEARCH → Explore the science behind the scene.