But where are the numbers? Building the evidence bridge for ecological design
Buildings are already being designed with nature in mind. But without a shared knowledge infrastructure connecting design decisions to ecological outcomes, ambition and reality keep drifting apart.
During my PhD, I ran workshops at Utrecht University with building professionals, including architects, project managers, financial controllers, facility managers. Those professionals make real decisions about real buildings. I’d walk them through the concept of ecologically functional buildings facing them with questions like how design choices shape ecosystem services, how a building can support or suppress ecosystem services, such as biodiversity, and how we as humans are far more embedded in ecological systems than most of us were ever taught to appreciate.
The conversations were always engaging. And they almost always arrived at the same point: this makes sense, but where are the numbers? Where is the evidence that this green roof actually supports pollination in this urban context? What is the measurable difference between a biodiverse planted façade and a monoculture one? Can I show my finance director an environmental return, in terms they’ll recognise?
I often couldn’t give them those numbers in the room. Not because the knowledge doesn’t exist. Some of it actually does exist, but its scattered across thousands of ecological studies, monitoring reports, and design evaluations from across the world. However, no one had connected it into something a non-ecologist could use. I noticed something else in those workshops: the gap wasn’t only about data. It was also about a whole mode of thinking. Most building professionals had never been taught to see a building as part of an ecosystem. That kind of systems thinking, where understanding is needed on how organisms interact, how services flow, how giving and taking needs to be balanced, simply isn’t part of architectural or building development education. It’s barely part of most people’s education at all.
The data gap and the literacy gap feed each other. No numbers means no incentive to learn the ecology. No ecological literacy means no one paying to gather more numbers.
What made my frustration sharper was watching what mostly happens after buildings are completed. Many of the supposedly sustainable building I encountered during my research had genuine ambitions with their designs, such as green walls, integrated water systems, and pollinator gardens. But once a building is handed over to its users, responsibilities shift. The original design team moves on, they might have earned a sustainable building certificate, for instance from BREEAM or LEED. Maintenance teams, trained in technical systems rather than ecological ones, take over and monitoring almost never happens. However, this is where the actual collection of data happens to analyze whether the green roof is doing what it was meant to do.
The reasons are structural, not accidental. Ecological monitoring takes time and often requires contracting a specialist who knows the measurement methods. The project is officially complete. There’s no budget line for it and no one formally responsible. Another disincentive is that an owner can market a sustainable building, but if real measurement produces numbers lower than expected, that becomes a liability rather than an asset. Measuring generates a communal benefit where the whole field can learn from, but the cost falls entirely on the individual who commissions it. So the rational financial choice is not to measure. Some of the most sophisticated tools for predicting ecosystem service potential, like the Ecological Intelligence tool, have been built into consultancy models precisely because the data they generate has commercial value. It doesn’t flow back into a shared knowledge commons. Every situation is cited as unique, every dataset kept proprietary, and the field keeps starting from scratch.
High ambitions, low outcomes, and no evidence trail to learn from result in a system that keeps reinventing the wheel or keeps installing green walls based on assumption rather than proof.
This is what made me turn to the scientific literature. Some data is there, however, not in abundance, and then also unevenly distributed depending on which ecosystem service you’re looking for. Empirical measurements from real buildings in real urban contexts, published in journals across ecology, urban planning, building science, and environmental engineering. The problem is that finding it is itself a research task. It requires knowing how to search across disciplines, how to translate between terminologies, how to read dense academic prose and extract the few numbers that would actually matter to a building developer. Industry professionals normally don’t read scientific publications, not because they don’t care, but because the format wasn’t designed for them. The field-specific language, the methodological detail, the lengthy discussion sections are all necessary for scientific rigour, however represent obstacles to practical use. The conclusions and the specific measured values would be exactly what a developer needs, however there is no common database, no structured extraction, no bridge.
EcoBUILD seeks to become that bridge. It is a knowledge graph platform that systematically connects building design strategies to the ecosystem services they generate, drawing on the ‘Designing for Urban Ecosystem Services’ diagram from Pedersen Zari and Hecht (2020). EcoBUILD started with linking 146 design archetypes to 57 ecosystem services. The underlying work to extract, structure data and make them navigable is the painstaking literature synthesis that building professionals don’t have time for. The more data that can be overlaid from different contexts and climates, the stronger the patterns become and the better we can predict outcomes for new projects. Ecological variability is real and every site is different, but that is an argument for more shared data rather than less.
At its core, EcoBUILD offers architects and building development teams identify the best-evidenced strategies for a given context and sustainability ambition.
There is a clear connection here to what NATURESCAPES is examining at the landscape scale. The fragmentation of NbS evidence that makes landscape-level synergies and trade-offs so hard to assess is the same fragmentation that makes building-scale ecological performance so hard to demonstrate. Buildings are not usually framed as nature-based solutions but if they are designed well, they can function as that. EcoBUILD is trying to make that visible, measurable, and actionable. Therefore, we conclude saying that evidence exists. It’s just been waiting for someone to connect the dots.