Demographic responses of Pinguicula ionantha to prescribed fire: a regression-design LTRE approach

Abstract

This study describes the use of periodic matrix analysis and regression-design life table response experiments (LTRE) to investigate the effects of prescribed fire on demographic responses of Pinguicula ionantha, a federally listed plant endemic to the herb bog/savanna community in north Florida. Multi-state mark-recapture models with dead recoveries were used to estimate survival and transition probabilities for over 2,300 individuals in 12 populations of P. ionantha. These estimates were applied to parameterize matrix models used in further analyses. P. ionantha demographics were found to be strongly dependent on prescribed fire events. Periodic matrix models were used to evaluate season of burn (either growing or dormant season) for fire return intervals ranging from 1 to 20 years. Annual growing and biannual dormant season fires maximized population growth rates for this species. A regression design LTRE was used to evaluate the effect of number of days since last fire on population growth. Maximum population growth rates calculated using standard asymptotic analysis were realized shortly following a burn event (<2 years), and a regression design LTRE showed that short-term fire-mediated changes in vital rates translated into observed increases in population growth. The LTRE identified fecundity and individual growth as contributing most to increases in post-fire population growth. Our analyses found that the current four-year prescribed fire return intervals used at the study sites can be significantly shortened to increase the population growth rates of this rare species. Understanding the role of fire frequency and season in creating and maintaining appropriate habitat for this species may aid in the conservation of this and other rare herb bog/savanna inhabitants.

Reproductive ecology of three rare North American Pinguicula species

“…Already some of this work has been conducted (Kesler et al . and Zaya et al . for P. ionantha ), but additional research is needed to further elucidate and mitigate previously mentioned factors that could lead to and/or increase the decline of these species.…”

“…), prey capture size (Gibson ), odd flower morphologies (Ross ), propagation (Carroll ) and demographics (Kesler et al . ). The research presented in this paper is among the most comprehensive studies associated with the reproductive ecology of North American Pinguicula species.…”

Canopy cover and groundlayer vegetation dynamics in a fire managed eastern sand savanna

“…The comparatively low correlation coefficients between percent change in canopy cover and change in species richness or functional groups suggest that other unmeasured factors also affect these changes. These factors probably include species-level demographic responses to fire, which can increase population growth rates of grassland plants through greater rates of flowering, fecundity and seedling survivorship (Menges and Dolan 1998;Kaye et al, 2001;Kesler et al, 2008). Fire may facilitate this process through seed scarification, removal of litter that would shade light-dependent germinating seeds and seedlings, and release of compounds in smoke that induce germination (Baskin and Baskin 1998;Dixon et al, 1995).…”

Life table response experiment analysis of the stochastic growth rate

“…2004; Van der Voort & McGraw 2006; Zuidema, de Kroon & Werger 2007), invasive species (Burns 2008), pathogens (Davelos & Jarosz 2004), floods (Smith, Caswell & Mettler‐Cherry 2005; Elderd & Doak 2006), disturbance (Endels et al. 2007), fire (Kesler et al. 2008), rainfall (Smith, Caswell & Mettler‐Cherry 2005; Lucas, Forseth & Casper 2008), herbivory (Knight, Caswell & Kalisz 2009), interspecific interactions (Miriti, Wright & Howe 2001; Freville & Silvertown 2005; Griffith & Forseth 2005) and effects on spread speed (Jacquemyn, Brys & Neubert 2005; Jongejans et al.…”

“…Because of their particular interest in comparative studies, plant demographers have applied LTRE analysis in many contexts. To cite just a selection of recent studies, it has been applied to effects of management (Davis, Dixon & Liebman 2003;Brys et al 2004;Van der Voort & McGraw 2006;Zuidema, de Kroon & Werger 2007), invasive species (Burns 2008), pathogens (Davelos & Jarosz 2004), floods (Smith, Caswell & Mettler-Cherry 2005;Elderd & Doak 2006), disturbance (Endels et al 2007), fire (Kesler et al 2008), rainfall (Smith, Caswell & Mettler-Cherry 2005;Lucas, Forseth & Casper 2008), herbivory (Knight, Caswell & Kalisz 2009), interspecific interactions (Miriti, Wright & Howe 2001;Freville & Silvertown 2005;Griffith & Forseth 2005) and effects on spread speed (Jacquemyn, Brys & Neubert 2005;Jongejans et al 2008). Two of the papers in this Special Feature use LTRE calculations as one of their tools for comparative analysis (Jongejans et al 2010;Davison et al 2010).…”