Reproduction is a key component of plant life cycles and is crucial for dispersal, however it has a surprisingly poorly understood relationship to environmental drivers. This is particularly true for plant species with highly variable reproduction over time, known as ‘mast seeding’. While mast-seeding patterns have been linked to weather (temperature, precipitation), describing past patterns and predicting future reproduction of plant populations is particularly challenging because high temporal variability in reproduction (with 3-7 or more years between large reproductive events) requires large long-term datasets for analysis, particularly if patterns are changing over time. Using data across Long Term Ecological Research (LTER) sites, and bringing together experts in mast-seeding, forest ecology, population dynamics, synthesis, and statistical and mathematical modeling, the synthesis group plans to:

  1. assess how generalizable temporal patterns of mast seeding are across species and disparate locations;
  2. test how environmental drivers and past performance influence mast seeding along a continuum from non-masting (i.e., low temporal variability) to strongly masting (i.e., high temporal variability) species; and
  3. compare statistical approaches for finding environmental drivers for plant reproduction.

Products from this working group will include: an R-workflow for calculating mast seeding metrics, incorporation of LTER plant reproduction data into i) an existing R-package for LTER population-level synthesis (Popler) and ii) global mast-seeding databases, multiple publications, and a workshop on spatio-temporal patterns and environmental drivers of plant reproduction. April 20, 2022 Webinar