A novel approach for sampling plant mass-density relationships.

In plant ecology, traditional quadrat-based methods are widely employed to investigate plant mass-density relationships. However, this approach has limitations when applied to irregularly distributed plant populations and communities. To address this challenge, we developed a novel sampling method based on Voronoi diagrams, designed to improve field investigations of mass-density relationships. The Voronoi diagram-based sampling approach defines irregular polygonal plots by merging the Voronoi cells of multiple individuals around a sampling point, enabling more precise delineation of the area and boundaries occupied by plants. To demonstrate the effectiveness and advantages of the Voronoi diagram-based method, we compare it with the traditional quadrat-based method in accessing the classic plant mass-density relationship, which has been suggested to follow a general scaling law. Here the novel approach demonstrated superior performance, providing a more precise and reliable analysis of the plant mass-density relationship. Moreover, our results reveal that the scaling exponent of average plant biomass to population density increases rapidly and then stabilizes near -4/3 as the number of individuals per plot (NI) exceeds 50, driven by declining variability in both average plant biomass and density. This generalizable approach, independent of individual spatial patterns, facilitates efficient empirical data collection with relatively fewer individuals, offering practical advantages for field-based studies. This approach provides a robust and precise tool for investigating and analyzing complex ecosystems, with broad applications in forest biomass estimation, plant interaction modeling, and even large-scale ecological analysis using remote sensing data. It thus holds significant potential for advancing ecological research and guiding ecosystem monitoring and management.