Contrasting effects of spatial heterogeneity and environmental stochasticity on population dynamics of a perennial wildflower. (22nd February 2016)

• Record Type: Journal Article
• Authors: Crone, Elizabeth E.
• Editors: Griffith, Alden
• Is Part Of: Journal of ecology. Volume 104:Number 2(2016:Mar.)
• Page Start: 281
• Page End: 291
• Publication Date: 2016-02-22
• Subjects: dispersal -- environmental stochasticity -- generalized linear model -- integral projection model -- plant population and community dynamics -- source–sink dynamics -- spatial heterogeneity; Plant ecology -- Periodicals; 577.05
• DOI: 10.1111/1365-2745.12500
• Languages: English
• ISSNs: 0022-0477

Abstract

Summary: Understanding how variation in growth, survival and reproduction affect population dynamics is a fundamental question in ecology. Although the effects of among‐year variation (environmental stochasticity) are well understood, the effects of among‐site variation (spatial heterogeneity) are less clearly defined. I evaluated the effects of spatial and temporal variation on the population dynamics of Pulsatilla patens, pasqueflower, a perennial prairie forb. I conducted a 10‐year demographic monitoring study, and quantified vital rate variation among sites and years using generalized linear models. I incorporated vital rate functions using this variation into integral projection models for stochastic and spatially heterogeneous environments. I also explored the effects of temporal and spatial autocorrelation, by exploring model predictions over the range of possible values for temporal autocorrelation and local seed dispersal. Vital rates varied more among years than among sites. However, environmental stochasticity and spatial heterogeneity had similar magnitude effects on population dynamics. These effects were also qualitatively different: environmental stochasticity reduced population growth rates relative to the average, whereas spatial heterogeneity increased population growth rates. Spatial autocorrelation and negative temporal autocorrelation led to higher population growth rates, although environmental stochasticity still reduced growth rates for all autocorrelation values, and spatial heterogeneity increased growth rates for all autocorrelation values. Some form of autocorrelation would be necessary for model projections to match observed population trends. Synthesis . Spatial heterogeneity is as important as environmental stochasticity for population dynamics, but it is much less often incorporated into population projection models. This study points to a number of interesting avenues for future research into the roles of spatial heterogeneity and spatiotemporal variation for long‐term population dynamics. Abstract : Spatial heterogeneity is as important as environmental stochasticity for population dynamics, but it is much less often incorporated into population projection models. This study points to a number of interesting avenues for future research into the roles of spatial heterogeneity and spatiotemporal variation for long‐term population dynamics.