The importance of space, time, and stochasticity to the demography and management ofAlliaria petiolata

Abstract

As population modeling is increasingly called upon to guide policy and management, it is important that we understand not only the central tendencies of our study systems, but the consequences of their variation in space and time as well. The invasive plant Alliaria petiolata (garlic mustard) is actively managed in the United States and is the focus of a developing biological control program. Two weevils (Coleoptera: Curculionidae: Ceutorhynchus) that reduce fecundity (C. alliariae) and rosette survival plus fecundity (C. scrobicollis) are under consideration for release pending host specificity testing. We used a demographic modeling approach to (1) quantify variability in A. petiolata growth and vital rates and (2) assess the potential for single-or multiple-agent biocontrol to suppress growth of 12 A. petiolata populations in Illinois and Michigan studied over three plant generations. We used perturbation analyses and simulation models with stochastic environments to estimate stochastic growth rates (k S ) and predict the probability of successful management using either a single biocontrol agent or two agent species together. Not all populations exhibited invasive dynamics. Estimates of k S ranged from 0.78 to 2.21 across sites, while annual, deterministic growth (k) varied up to sevenfold within individual sites. Given our knowledge of the biocontrol agents, this analysis suggests that C. scrobicollis alone may control A. petiolata at up to 63% of our study sites where k S . 1, with the combination of both agents predicted to succeed at 88% of sites. Across sites and years, the elasticity rankings were dependent on k. Reductions of rosette survival, fecundity, or germination of new seeds are predicted to cause the greatest reduction of k in growing populations. In declining populations, transitions affecting seed bank survival have the greatest effect on k. This contrasts with past analyses that varied parameters individually in an otherwise constant matrix, which may yield unrealistic predictions by decoupling natural parameter covariances. Overall, comparisons of stochastic and deterministic growth rates illustrate how analyses of individual populations or years could misguide management or fail to characterize complex traits such as invasiveness that emerge as attributes of populations rather than species.

Understanding the limits to species‐wide demographic generalizations: the ecology and management of Parkinsonia aculeata

“…Our study adds to the growing body of literature that highlights the importance of the demographic variability within a species in relation to environmental context (Oostermeijer et al 1996, Menges and Quintana-Ascencio 2004, Endels et al 2005, Shea et al 2005, 2010, Jongejans et al 2008, Evans et al 2012Sm ıdov a and M€ unzbergov a 2012, Scanga and Leopold 2012, Andrieu et al 2013, Raghu et al 2014. We build on this body of work to develop a novel upscaling method to test whether there are context and upscaling influence ecological inferences and the ability to arrive at demographic generalizations.…”

“…Species-environment interactions can result in very different demographic outcomes depending not just on the species involved, but also on where and when the species occurs (Shea et al 2005, Evans et al 2012. Therefore, in light of HT and the methodological framework of demographic analyses, we sought to understand the limits of demographic generalization about a widespread invader in northern Australia, Parkinsonia aculeata L. (Fabaceae).…”

Soil‐mediated eco‐evolutionary feedbacks in the invasive plant Alliaria petiolata

“…The stochastic population growth rates (k S ) used in our analyses were recalculated from data reported in Evans et al (2012). Readers should review that paper and its online appendices and citations for details on site selection, quantification of vital rates and matrix population model construction and interpretation.…”

“…Despite its significant impacts, A. petiolata stochastic growth rates (k S ) vary significantly among populations from rapid growth (k S > 1) to decline (k S < 1) (Evans et al 2012). Considering the temporal dynamics of A. petiolata's allelochemistry and its relationships with A. petiolata and native plant cover (Lankau et al 2009;Lankau 2012a), we hypothesized that the variation in k S (Evans et al 2012) was likely related to the variation in allelochemistry and thus creates a feedback between evolution (changes in allelochemistry) and ecology (population growth rates). We propose that the gradients in sinigrin result from varying selection on sinigrin that is linked to the population dynamics of the invader; specifically, that selection favours high allelopathic concentrations in newly founded populations, but reduced investment to these chemicals over time as intraspecific competition intensifies and interspecific competition weakens.…”

“…We propose that the gradients in sinigrin result from varying selection on sinigrin that is linked to the population dynamics of the invader; specifically, that selection favours high allelopathic concentrations in newly founded populations, but reduced investment to these chemicals over time as intraspecific competition intensifies and interspecific competition weakens. We assessed this by combining the reanalysed data from ten field sites included in the previous studies of A. petiolata demography (Evans et al 2012) with new data on quantitative genetic variation in allelochemical production to assess the relationship of population growth and vital rates with changes in secondary chemistry. Additionally, we experimentally test whether the variation in the competitive environment alters selection pressures on sinigrin under controlled conditions, in order to confirm the proposed mechanism driving the previously observed patterns in sinigrin concentrations across the invaded range.…”