Contingent factors explain average divergence in functional composition over 88 years of old field succession. (1st October 2018)

• Record Type: Journal Article
• Authors: Clark, Adam Thomas; Knops, Johannes M. H.; Tilman, Dave
• Editors: Bardgett, Richard
• Is Part Of: Journal of ecology. Volume 107:Number 2(2019:Mar.)
• Page Start: 545
• Page End: 558
• Publication Date: 2018-10-01
• Subjects: environmental driver -- grassland -- interspecific competition -- metacommunity -- old field succession -- plant community assembly -- plant population and community dynamics; Plant ecology -- Periodicals; 577.05
• DOI: 10.1111/1365-2745.13070
• Languages: English
• ISSNs: 0022-0477

Abstract

Abstract: "Old fields" are ecosystems that have been previously managed and subsequently abandoned, usually from agricultural use. These systems are classic testing grounds for hypotheses about community assembly. However, old field succession can be difficult to predict: seemingly similar fields often diverge in terms of species composition and environmental conditions. Here, we test the relative roles of contingency and stochasticity in driving vegetative successional dynamics. We draw on three decades of surveys in 24 old fields at the Cedar Creek Ecosystem Science Reserve (Minnesota, USA), and focus on five drivers that are known to shape local plant communities: soil fertility, fire, climate, competition, and demography. These drivers can contribute to contingency when they act consistently across fields and years (e.g., soil nitrogen accumulation, experimental fire regimes, or average climate), or to stochasticity when their effects are variable (e.g., annual variations in weather, or colonization and mortality events). We proceed in two steps. First, we fit regressions estimating abundance, colonization, and mortality for eight major functional groups in relation to these five drivers. We then use these regressions to parameterize a series of metacommunity simulation models, and test whether observed levels of stochasticity and variation in the drivers are sufficient to explain successional divergence. All drivers were significantly associated with plant species abundances, colonization, and mortality. Contingent factors strongly altered predicted successional trajectories. However, replicate simulations with similar conditions followed similar successional trajectories, suggesting that stochastic processes did not lead to divergence. This robustness of successional dynamics may be explained by compensatory trade‐offs. For example, species that were abundant late in succession typically suffered from low colonization rates and high mortality rates early in succession. Synthesis. Average successional dynamics among old fields at Cedar Creek follow largely consistent trends. Though dynamics of individual fields vary, much of this variation can be explained by contingent factors. Stochastic processes appear not to be sufficiently strong to create divergent successional trajectories among fields with similar sets of drivers. Our results therefore suggest that divergence among successional trajectories in chronosequences may be the result of predictable contingent factors, rather than unpredictable stochastic fluctuations. Abstract : Average successional dynamics among old fields at Cedar Creek follow largely consistent trends. Though dynamics of individual fields vary, much of this variation can be explained by contingent factors. For example, regular burning (left half of picture) can lead to reduced leaf litter and changes in plant species abundances relative to unburned fields (right half of picture). In contrast, stochastic processes appear not to be sufficiently strong to create divergent successional trajectories among fields with similar sets of drivers. Our results suggest that divergence among successional trajectories in chronosequences may be the result of predictable contingent factors, rather than unpredictable stochastic fluctuations. Photo credit: Adam Clark, April 2017. Field 5 at Cedar Creek.