Understanding and predicting the response of species to climate change is crucial to develop effective long-term conservation strategies. Species distribution models (SDMs) are the most applied tool to predict species distributions in a changing climate and are based on current correlations between species occurrences and climatic factors. Classic SDMs do not consider the demographic mechanisms underlying species responses to climate variation. Further, they assume that all populations respond in the same way to climate change because they do not account for population genetic differentiation (e.g. local adaptation). To produce more accurate predictions of species distribution and abundance we need to identify climatic factors driving population performance and to investigate how populations differ in their response to climate change due to local adaptation. We assessed the importance of microclimate and local adaptation on population growth rates (λ) of the moss Hylocomiastrum umbratum, based on a 3-yr transplantation experiment. Since the frequency and abundance of H. umbratum increases towards north in Sweden, we expected higher population growth rates of all populations in colder and more humid sites, and that northern populations perform better than southern populations in these northern-like conditions. We transplanted moss mats at 30 forest sites with contrasting microclimate in central Sweden. The moss transplants were collected from six populations at the species’ northern and southern range margins in Sweden. We estimated the effects of microclimate and population origin on the vital rates and used integral projection models (IPMs) to assess these effects on the population growth rate.
Results/Conclusions
Population origin affected all vital rates in all years, whereas microclimatic variables (summer temperature and snow-melting day) influenced growth and survival only in the first year. In agreement with our hypothesis, population growth rates of southern populations were lower in cold, northern-like microclimates, than in warm southern-like conditions (Δ λ = 0.138), while northern populations performed better in northern-like conditions (Δ λ = 0.030). Different photosynthesis optima and development rates probably underlie such different populations response. These patterns suggest local adaptation, however, they emerged only in the first study years. In the second year, which was more humid, survival rate was higher (95%) than in the first year (81%), likely explaining the differences in the observed patterns. Our study highlights that population genetic differentiation can be important and that accounting for local population adaptation is essential to achieve more realistic predictions of species abundance and distribution changes in response to climate change.