Evaluating Multi-Method Insect Monitoring on a Green Roof in Amsterdam
Complementary, Not Competing
M. Gupta (TU Delft - Architecture and the Built Environment)
Titus Venverloo – Mentor (Massachusetts Institute of Technology)
Eveline van Leeuwen – Mentor (Amsterdam Institute for Advanced Metropolitan Solutions (AMS))
Antoine Cribellier – Mentor (Wageningen University & Research)
J.W.F. Wamelink – Graduation committee member (TU Delft - Design & Construction Management)
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Abstract
Insect populations across Europe are in measurable decline, yet monitoring methods remain predominantly manual, episodic, and limited in temporal resolution. Researchers describe the future of insect monitoring as a combination of manual and digital sampling and processing methods. This study addresses that gap through a staggered, multi-method monitoring campaign on an urban green rooftop in Amsterdam. Different combinations of manual (pitfall traps, light traps, sweep netting, transect walks) and technological (computer vision, eDNA) methods are compared based on their resulting richness, relative abundance, and activity to test how method choice affects biodiversity estimates.
The study was conducted in close collaboration with ecologists, urban planners, and rooftop maintenance workers to understand the complementarity of methods not only quantitatively but also in terms of the different objectives the practitioners seek to achieve through insect monitoring. The quantitative study reveals that activity data from novel methods, although imperfect and inherently different from relative abundance data captured by manual methods, still provide partially overlapping yet complementary information. Discussion with practitioners echoed the view that the trustworthiness of novel methods must be assessed at the species and measurement-type levels, rather than assumed for the technology as a whole. It also revealed that complementarity can operate at the data level or the pipeline level, where continuous, imperfect, and low-cost monitoring is used to direct scarce expert time and resources toward relevant moments and locations.