Are Ecosystem Services Replaceable by Technology Yet? Bio-Inspired Technologies for Ecosystem Services: Challenges and Opportunities
Bibliographic record
Abstract
As ecological collapse accelerates under the pressures of anthropogenic climate change, adaptation strategies increasingly include technological proxies for nature's functions. But can ecosystem services (ES) be meaningfully replaced by technology? Revisiting this urgent question first posed by Fitter (2013), we assess the extent to which bio-inspired design-particularly biomimetics-has advanced the capacity to support, enhance, or replace natural ES. We convened an interdisciplinary team to synthesize and refine a comprehensive list of 22 ecosystem services, integrating often-overlooked cultural and relational dimensions. Using this framework, we conducted a large-scale analysis of over 68,000 peer-reviewed publications from the biomimetics and bio-inspired design literature between 2004 and 2025, applying AI-assisted classification to evaluate whether, and how, these technologies map onto specific ES functions and benefits. Our findings reveal both promise and profound limitations. Bio-inspired research engages with 20 of the 22 ES, but over 78% of this work concentrates on five technologically tractable functions-biochemicals, disease regulation, waste treatment, fibre/hide/wood, and fuel. Foundational supporting and regulating services such as pollination, soil formation, and nutrient cycling are almost entirely absent. Moreover, only 3% of technologies described in the academic literature aim to support existing systems; the overwhelming emphasis on enhancement (39%) and replacement (58%) suggests a design paradigm skewed toward substitution rather than coexistence. Intangible, co-produced services-particularly those related to culture, identity, and meaning-remain outside the current reach of biomimetic design. This skew reveals a dangerous imbalance: while certain ES can be technologically approximated, the relational, emergent, and systemic qualities of ecosystems elude replication. Technological replacement must not become a substitute for preservation. Instead, bio-inspired design should be mobilized as a tool for adaptation that amplifies and protects the living systems on which human and more-than-human futures depend.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.013 | 0.028 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".