FAMeLeS: A multispecies and fully automated method to measure morphological leaf traits

Abstract

Abstract Leaf shape parameters are of key importance to explain the role of energy balance and water economy in plant species distribution, plant productivity and, more generally, in plant–environment interactions. Yet, leaf shape measurements based on image processing are still challenging due to the high diversity of leaf shapes, colours and sizes leading to the development of time‐consuming methods with a narrow field of applicability, sometimes species‐specific or often limited to a few species. We developed a fully automated method for measuring multiple leaf shape parameters (area, perimeter, length, width, circularity and solidity) based on a large image sampling of leaf diversity (including litter) belonging to 587 species and spread over 232 countries worldwide. To evaluate the accuracy of the method to detect small objects, the sampling particularly targeted Mediterranean ecosystems (32 species and 25,205 leaves), in which small leaves often represent methodological challenges. We compared our approach and found that its mean error in leaf area measurement (+0.46%) was 1.7–148 times lower than four existing methods. It was also the only one capable of detecting and measuring all leaves in the test data set, even variegated and small leaves (less than 1 mm2). Its reliability was extensively checked on the largest and most diversified data set ever used. Our method, accessible to the broader scientific community, was simple, rapid and effective on multiple image file types and on a high diversity of leaf size, shape and colour. As such, our approach allows measurement not only on fresh leaves but also on dry leaves, such as leaf litter or leaves from herbaria. This tolerance to leaf characteristics is crucial to increase large‐scale sampling efforts and paves the way for a standardized multispecies approach to measuring leaf morphological traits for ecological and agricultural studies.