COS 83-10 - Demographic analysis of a dioecious threatened plant and the consequences of not having complete data

Wednesday, August 9, 2017: 11:10 AM
B110-111, Oregon Convention Center
Natali Ramirez-Bullon1, Vivian Negron-Ortiz2 and Alice A. Winn1, (1)Biological Science, Florida State University, Tallahassee, FL, (2)U.S. Fish and Wildlife Service, Panama City, FL
Background/Question/Methods

The number of studies that use structured demographic models to answer conservation questions has increased in the past four decades yet few assess endangered or threatened plant species. One reason may be that there are not clear guidelines available to conservation managers to collect appropriate demographic data, particularly for plants with complex life cycles. Consequently, managers often collect or only have access to data from mature individuals, which are easier to identify and detect than other stages (e.g. seedlings and juveniles). Assessing population dynamics without data on all life cycle stages may be especially difficult for species with longer or complicated life cycles. We quantified the consequences of assessing population dynamics with incomplete demographic data for three populations of a threatened dioecious perennial herb, Euphorbia telephioides. Previous counts of reproductive individuals suggested that these populations were stable. We constructed and analyzed stage structured demographic models for three populations, we estimated population growth rates using data from randomly marked plants representing the whole life cycle and compared them to population growth rates projected from a subset of the data that excluded juvenile plants.

Results/Conclusions

Population growth rate estimates using data for all stages of the life cycle indicate that these populations are projected to decline (all population growth rates significantly less than 1). Deterministic Lambda estimates excluding juvenile individuals were significantly greater by 3 % to 8% than estimates that based on a random sample of marked individuals that included all life cycle stages. Moreover, at one population, using data generally available for managers (adults only) resulted in λ >1, meaning the population was projected to grow, which can be misleading when compared to the assessment using complete data. For these populations, excluding juvenile plants overestimated survival probabilities, which resulted in greater estimates of population growth rates. This case illustrates the importance of incorporating data from all stages of the life cycle when assessing population growth rates of endangered and threatened long-lived plants.