Pace and parity predict short-term persistence of small plant populations

Life history traits are used to predict asymptotic odds of extinction from dynamic conditions. Less is known about how life history traits interact with stochasticity and population structure of finite populations to predict near-term odds of extinction. Through empirically parameterized matrix population models, we study the impact of life history (reproduction, pace), stochasticity (environmental, demographic), and population history (existing, novel) on the transient population dynamics of finite populations of plant species. Among fast and slow pace and either uniform or increasing reproductive intensity or short or long reproductive lifespan, slow, semelparous species are at the greatest risk of extinction. Long reproductive lifespans buffer existing populations from extinction while the odds of extinction of novel populations decreases when reproductive effort is uniformly spread across the reproductive lifespan. Our study highlights the importance of population structure, pace, and two distinct aspects of parity for predicting near-term odds of extinction. 

Methods
We gathered empirically derived stage-based population models from the COMPADRE Plant Matrix Database v6.22.5.0 (created 2022-05-11; Salguero-Gomez et al. 2015) that (1) were ergodic and irreducible, (2) were modelled on an annual time step (Iles et al. 2016), and (3) did not explicitly parse clonal growth into a separate matrix. This subset resulted in 1,606 matrices representing multiple years and/or populations of 317 plant species.