Seed production patterns of trees play an important role in plant population dynamics and forest regeneration. Mast seeding occurs in many plant species and across diverse plant communities. The two predominant ultimate hypotheses for mast seeding are predator satiation and pollination efficiency, with climate variation involved as a proximate cause. Studies often investigate single or phylogenetically closely related species, but the underlying mechanisms of mast seeding at the community level, especially considering both reproductive strategy and climate factors, remain scarce and rarely explored. We used eight-year collection of seed rain in 150 seed traps from a 25-ha temperate forest plot in northeast China to characterize the patterns and evaluate potential drivers for mast seeding. We were particularly interested in the relationship between interannual variability of mast seeding and species’ pollination and dispersal vectors, as well as climatic cues.
Results/Conclusions
We found that 16 of 19 tree species underwent mast seeding. Seed production synchrony was evident between species across surveyed years. Wind-pollinated species had higher interannual variation of seed production than insect-pollinated species, while species dispersed by predators and abiotic modes showed little variation. Total seed production at the community level was negatively affected by daily maximum and minimum temperatures during flowering, and positively related to mean minimum temperature of the previous winter. Previous summer temperature and mean wind velocity during the seed dispersal period had weak effects on seed production. Our findings suggest that mast seeding is an adaptive reproductive strategy cued by climatic factors, with pollination efficiency having a larger impact than predator satiation in this forest. We stress the necessity to simultaneously assess both ecological and evolutionary mechanisms of mast seeding and the response to environment at the community level, in order to improve our understanding and future prediction of spatio-temporal seed production pattern and forest dynamics.