Changes in global climate could cause shifts in species distributions and therefore affect the long-term dynamics of rare and endangered plant populations. Linking climate change models to demographic models may provide useful insights into the potential effects of environmental changes on rare plants, and therefore aid in their current and future conservation. We used demographic models to project population sizes of several rare plant species into future climate scenarios. Population growth rates were calculated from demographic data sets of 7-10 years for five rare, native Oregon plant species populations at multiple sites (Astragalus tyghensis, Pyrrocoma radiata, Horkelia congesta, Lomatium bradshawii and Lomatium cookii). First, we developed models to predict population growth from environmental variables using multiple linear regression with observed data. Climate variables included monthly precipitation, average monthly dew point, minimum, and maximum temperature during specific growing seasons. Second, we simulated future population trajectories based on 1) predicted environments from climate change models (HadCM3 and CSIRO MK3), 2) observed climate variable means and variances, and 3) IID conditions of our data sets without climate predictors.
Results/Conclusions
Linear regression models for the five species had adjusted R2 from 0.20 to 0.74. Models were weakest for L. bradshawii and H. congesta, and strongest for A. tyghensis. Stochastic lambda was 0.98 (SD = 0.33) under climate change forecasts for A. tyghensis (0.90 for observed climate and 0.95 for IID). Stochastic lambda was 0.61 (SD = 0.25) under forecasted climate for P. radiata (0.86 for both observed climate and IID). Under climate change forecasts, extinction probability in 50 years was 10% for A. tyghensis and 100% for P. radiata (13% in 25 years). Environmental factors explained some variation in population growth rates in all five species and may be useful in stochastic demographic models in general. Forecasts of population growth under climate change scenarios are more pessimistic in some plant species (P. radiata) than forecasts based on past conditions or IID, suggesting negative effects of climate change on these rare species. However this method does not explicitly address indirect effects of climate change on plant populations such as herbivory, intra- and inter-specific interactions, pathogens, etc.