Why Are Seed Dispersal Models Rarely Used? Limitations of Scalability and Improvement Measures

Seed dispersal studies have primarily relied on prediction model methods, which limit clarity regarding how variables affect movement direction. Suggestions for improvement are limited to specific domains due to the lack of quantitative evaluation of the comprehensive scope of the basic steps, from explaining seed dispersal to its application in related fields. This study aimed to reconsider the classification of seed movement mechanisms, identify research trends from an integrated perspective, and discuss the current implications and improvement measures. The data included 240 studies related to seed dispersal across the observation, generalization, and application phases. By classifying the mechanisms based on the direction of movement, the main variables affecting movement due to gravity or wind can be clearly distinguished. Although seed dispersal models assume gravity as the core principle, only 12.91% of the studies addressed terminal velocity, and a mere 1.25% measured the diaspore area, both of which are essential for accurate prediction. In addition, attempts to utilize seed dispersal for natural regeneration were relatively frequent (14.58%), but they remained at the empirical model stage, relying on data collected in the field, and thus lacked connection with models developed in previous studies. The requirements for enhancing the field usability of seed dispersal based on the current review include (1) improving the data collection system for securing primary data, (2) collecting sufficient field data, and (3) developing a unified model that can be applied to various conditions and species.