Interpreting global spatiotemporal patterns in seed dispersal modes under data and methodological constraints

Interpreting global spatiotemporal patterns in seed dispersal modes under data and methodological constraintsA reply to Wasowicz & Green (2026): 'Towards a clearer understanding of evolution of angiosperm dispersal: classical syndromes are subjective and should not be confused with mechanisms'We thank Wasowicz & Green (2026) for their thoughtful commentary on our recent study (Jin et al., 2026) on the evolutionary history and global distribution of seed dispersal modes in angiosperms.Their main criticisms concern the treatment and interpretation of our dispersal mode data, including the heterogeneity of data sources, the use of seed dispersal classifications as proxies for dispersal ability, and the simplification of dispersal categories through the exclusion of polychory.While some of these issues were acknowledged in the discussion of our original paper, we provide here a more detailed clarification of our rationale and the analytical constraints of our approach.A central constraint of our study arises from the availability and completeness of global seed dispersal data.The seed dispersal process is inherently complex, involving multiple potential pathways, agents, and phases (Rubalcava-Castillo et al., 2025), and growing empirical evidence continues to reveal additional layers of this complexity.For example, while diaspore traits are commonly linked to specific dispersal categories (i.e. the dispersal syndrome hypothesis), accumulating evidence suggests that such trait-based inferences may be limited, as these traits are shaped by multiple ecological and evolutionary processes and do not always reflect actual dispersal, particularly in animal-mediated systems (Valenta & Nevo, 2020;Green et al., 2022).In addition, seed dispersal is a context-dependent process, with dominant vectors and dispersal effectiveness potentially shifting with local environmental conditions (Johnson et al., 2019).Therefore, an accurate characterization of seed dispersal modes should ideally integrate trait-based inferences with direct observations and experimental approaches, and fully capture polychory (i.e.plants with multiple dispersal pathways) and diplochory (i.e.plants with sequential dispersal phases) when present (S adlo et al., 2018;Beckman et al., 2026).However, such comprehensive information remains scarce at the global scale.This limitation is particularly acute for rare longdistance dispersal events that, while evolutionarily significant, occur infrequently and unpredictably ( Nogales et al., 2012;