UC Riverside

Species extinction is increasing due to anthropogenic threats such as climate change and land-use change. Thus, there is increasing interest in predicting the future fate of species and implementing effective management strategies. In this study, we used spatially-explicit stochastic population models to simulate future projections of three Monkeyflower species, Erythranthe cardinalis, Erythranthe lewisii, and Erythranthe guttata, under climate and land-use change in their regional habitat range in the California Floristic Province. We compared future population projections of two of the three Monkeyflower species, sub-divided into lower and higher elevation ranges, to examine the role of elevational differences in life history parameters in the persistence of the species under projected habitat changes. Lastly, due to the appearance of oscillations and declines in population trajectories of one Monkeyflower species, we explored the role of small, colonized patches on population trajectories. The modeling framework linked species distribution models (SDMs) with population models and dispersal modes parametrized with a combination of multi-year population census data, information from the literature, and publicly available environmental data, including temperature and precipitation projections under two climate scenarios and two climate models. Due to high population growth rates, all three species were limited by changes in habitat due to climate and land-use change. However, subpopulations of E. cardinalis had a low population growth rate at lower elevational ranges leading to extirpation in that region. Conversely, E. lewisii had a high population growth rate but experienced substantial declines in suitable habitat. In the population trajectories of E. lewisii, damped oscillations were observed stemming from a combination of high growth rates and colonization of new small patches which paradoxically reduced the overall population size across the metapopulation. This study highlights the importance of examining small-scale local spatial and demographic characteristics and dynamics, as opposed to large-scale regional habitat and population projections, in understanding the drivers of declines and extinction.