Final Project: Landscape Practice for Biodiversity in Vertical Greenery

Empirical Mapping Biodiversity Assessment of 3D Ecological Performance

By Ren Junyao

Assignment 5 link: Please open the link, download and view.

Research Context

Background:

In landscape architecture, data-integrated modeling of three-dimensional ecological performance is increasingly important. However, there is often a gap between the expected ecological benefits of vertical landscape designs and the actual outcomes observed in reality. Recognizing and understanding this discrepancy is a crucial first step for improving modeling accuracy and guiding future optimizations.

Research Question:

Does incorporating a vertical dimension in landscape design truly enhance biodiversity at the neighborhood scale? This project specifically asks whether existing vertical greenery installations are effectively improving local biodiversity.

Case Study Site:

The Wilmar Headquarters building at one-north was selected as the case study. This site features extensive vertical greenery, making it ideal for examining how 3D landscape design affects biodiversity.

Node Definition and Predicted Biodiversity Scores

Node Identification: Using the building’s landscape design plans, delineated every planted patch as a separate node. In practice, this means each green wall segment, rooftop garden, or ground-level planting area was marked out as an individual unit for analysis. These nodes form the basis of biodiversity assessment, as each is considered a distinct habitat area.

Habitat Value Scoring: For each identified node, a predicted biodiversity score was calculated from the plants design data. The scoring method accounts for the composition of plant species in that node – nodes with a higher proportion of wildlife-attracting plants (species that provide food or habitat for birds, insects, etc.) receive higher scores.

Expected Biodiversity Index: The result is a predicted biodiversity index for every node. This index represents the expected ecological performance of that node before observing the actual fauna. Essentially, it is a hypothesis of how well each patch should support biodiversity based on its vegetation characteristics.

Table: Node Attributes and Predicted Scores: Full table link here.

On-Site Survey and Results

Biodiversity Field Survey: An on-site survey was carried out to collect observed biodiversity data for each node. Surveyors followed predefined transect routes through and around the building, systematically recording all plant and animal species present at each node and counting the number of individual organisms observed.

Empirical Biodiversity Index: From the survey data, actual biodiversity indices for each node were calculated. These empirical indices quantify the real biodiversity performance of each node. The collected data not only provide a basis for spatial mapping of biodiversity across the site, but also serve as ground truth for validating the predicted scores statistically.

Table: Survey Recording and Biodiversity Indices: Full table link here.

Interactive 2.5D Biodiversity Visualization & Statistical Analysis

2.5D Interactive Spatial Map:

Right side present a semi-3D (2.5D) map of the building’s green infrastructure to visualize biodiversity data in context. This map displays each node’s predicted biodiversity score alongside its observed biodiversity index at the corresponding location (e.g. along different facade levels and site areas). The spatial visualization highlights where the design anticipated biodiversity “hotspots” and whether those areas actually exhibited high biodiversity on site, making any spatial discrepancies between expectation and reality immediately apparent.

Scatter Plot (Prediction vs. Observation):

A scatter chart plot the predicted biodiversity score of each node against its observed biodiversity index. This visualization directly shows the correlation between design expectations and real outcomes. Notably, the data points cluster along a downward-sloping trend line – a clear negative correlation. In other words, nodes that were predicted to have higher biodiversity often turned out to have lower biodiversity in reality, and vice versa. This negative trend indicates that the vertical greenery design underperformed relative to expectations: the intended biodiversity benefits were not realized to the extent predicted. The scatter plot thus serves as a crucial reality check, revealing the gap between the model’s predictions and the actual ecological performance measured on site.

Implications and Future Strategies:

• Validating Assumptions: The finding of a negative correlation underscores the importance of empirically validating design assumptions. In this case, the design’s predicted biodiversity gains did not materialize as anticipated, revealing a significant gap between expectation and reality. Rather than a successful improvement, the vertical greenery provided less biodiversity benefit than hoped, which is an important outcome to acknowledge.
• Learning Opportunity: This discrepancy is not just a critique of the current design – it is a valuable learning opportunity for future 3D ecological design strategies. The mismatch between expected and observed performance highlights where our predictive model or design approach may need refinement. By analyzing why high predicted scores corresponded to low actual biodiversity (for example, perhaps the plant species selection or habitat provisions were not as effective as assumed, intervention of human activities, terrestrial animal not reachable), designers can identify specific shortcomings in the design strategy.
• Improving Future Designs: Going forward, these insights can inform the refinement of vertical greenery systems. We can adjust predictive models to be more accurate and update design guidelines to better support actual biodiversity (e.g. selecting plant species with proven wildlife value, providing additional habitat features, improving wildlife corridors, find some ways for human wildlife coexistence). In essence, the underperformance of this project’s design highlights clear opportunities to improve future vertical green designs so that predicted ecological benefits are more faithfully realized in practice.