Population viability with fire in Eryngium cuneifolium: deciphering a decade of demographic data

• Published in: Ecological monographs 2004-02, Vol.74 (1), p.79-99
• Main Authors: Menges, Eric S., Quintana-Ascencio, Pedro F.
• Format: Article
• Language: English
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; Biological and medical sciences; Conservation biology; Demecology; Demography; disturbance; Ecology; elasticity; Eryngium cuneifolium; fire; Florida rosemary scrub; Fundamental and applied biological sciences. Psychology; Lake Wales Ridge; matrix models; Plants; Plants and fungi; Population; Population ecology; Population size; Rosemary; Seed banks; Seedlings; Statistical analysis; Viability; Yearlings
• ISSN: 0012-9615; 1557-7015
• DOI: 10.1890/03-4029

We analyzed and modeled the demography of Eryngium cuneifolium, an herbaceous species endemic to the fire-prone Florida scrub, using 10 annual censuses (1990-1999) of 11 populations at Archbold Biological Station. Nearly every aspect of the demography of this plant is affected by time since fire. Year, time since fire, life history stage, and plant age affected survival, growth, and fecundity of E. cuneifolium, but time since fire and life history stage had the most consistent effects. Survival, flowering stem production, and early seedling survival were highest in recently burned sites. Long-term survival, growth, and fecundity were highest for yearling cohorts recruiting recently after fire, with the largest contrast between plants recruiting two years postfire and those recruiting more than a decade postfire. Prior (historical) stage also affected individual plant fates. For example, plants with prior stasis or regression in stage subsequently died in greater numbers than plants with prior advancement in stage. Historical analyses did not suggest any cost associated with the initiation of flowering. We used a matrix selection approach to explicitly model Eryngium cuneifolium population viability in relation to fire. This simulation strategy included preserving observed data and variances within projection matrices formed for individual combinations of population and year. We built 54 of these matrices, each with six stages (seed bank, yearlings, vegetative plants, and three reproductive stages). Each of these matrices also represented a specific time since fire. In building matrices, we minimized the use of pooled data while retaining specific matrices whenever possible. In this way, we preserved both the correlation structure within individual matrices (populations, years) and protected patterns among matrices across the time-since-fire gradient. To deal with less-detailed data on recruitment processes, we evaluated 13 fertility and seed bank scenarios that bracketed a range of outcomes. All scenarios were similar in showing the positive effects of fire on the demography of E. cuneifolium. The scenario with high seed bank survival (0.5) and low germination rates (0-0.005) was the best predictor of observed postfire years of peak aboveground population size (~8 yr) and aboveground population disappearance (30-34 yr), and also did a good job of reproducing observed population trajectories. Finite rates of increase (λ) were >1 only during the first decade