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Prediction vs. reality: Can a PVA model predict population persistence 13 years later?

Publication at Faculty of Science |
2010

Abstract

The challenge of conservation biology is to make models that predict population dynamics and have a high probability of accurately tracking population change (increase, decrease, constancy). In this study we tested whether the transition model is accurate enough to predict population persistence and size 13 years down and whether after 13 years populations had achieved a stable stage distribution.

We modeled 6 small populations of an epiphytic orchid using a Lefkovitch type analysis to predict population growth pattern based on monthly surveys for approximately 1.5 years. In addition, sensitivity and elasticity analyses were used to identify life stages with high sensitivity or elasticity that have the largest influence on population growth rate.

We re-censused the populations 13 years after the first study and compared the structure of the populations to predictions based on the earlier census data. Effective population growth rates were similar to those expected except for one where the population went extinct.

The prediction slightly (but not significantly) overestimated the actual population growth rates of some populations. Elasticity analysis revealed that the adult stage is critical in the life cycle.

The observed stage distributions of the populations were not stable at the beginning of the survey and neither were they after 13 years. We suggest that this might be caused by external perturbations that result in unequal mortality between life stages and stochastic recruitment events.

The ability of the matrices to predict population size approximately eight generations in the future is encouraging and warrants the continued use of these approaches for PVA.