From pixels to length: Body length estimation of aquatic macroinvertebrates from digital images for ecological applications

Accurate measurement of macroinvertebrate body length is a key component of ecological research, providing essential data for estimating biomass, evaluating growth rates, and understanding trophic interactions in aquatic ecosystems. Yet, comprehensive datasets remain scarce, largely due to the labor-intensive and error-prone nature of traditional manual measurements - especially when processing bulk, mixed-species samples, where body sizes of individual specimens may range over orders of magnitude. This study presents a streamlined, non-destructive approach using Fiji, a free open-source image processing software, in combination with the Labkit plugin to extract body length information from digital images. Its novelty lies in enabling high-density bulk sample processing, interactive segmentation to overcome computational limitations, and taxon-specific area-length regression within a reproducible and transparent end-to-end protocol. In this workflow, body length is manually measured for a representative subset of specimens, while body area is extracted from segmented images for all. A linear regression of body length (Y) on image-derived area (X) allows reliable length estimation for specimens not measured manually. This approach improves throughput, offering an accessible and scalable solution for large-scale ecological assessment. • Semi-automated workflow using Fiji and Labkit. • Regression-based estimation of body length from image-derived area. • Fast, reproducible alternative to traditional manual measurements.