Alpine plant communities are some of the most visibly impacted by climate change. A number of studies have documented longer growing seasons, changes in precipitation, and upward range shifts of component species. Changes in temperature and precipitation may drive ecosystem change via direct and indirect effects on plant community structure. While experimental studies are crucial to understanding the mechanisms of climate change effects on ecosystems, they are limited by their small scales, often examining only one climate variable at a time, and also by their relatively short durations, but early changes in plant communities have been shown to be a poor predictor of long term ones. Natural gradient studies are a good complement to explore the long-term effects of climate as they reflect gradual, long-term ecosystem processes. I examined how aspects of plant community structure, biomass and C:N ratios, and soil N availability are affected over natural gradients of temperature and precipitation using an existing grid of 12 grassland sites in southwestern Norway in 2010. The grid’s unique design allowed me to examine the separate and interacting effects of the climate variables.
Results/Conclusions
Soil N availability was strongly negatively correlated with temperature, but not correlated with precipitation. This could be due to slower rates of plant uptake at colder, alpine sites relative to warmer sites. There was a positive effect of both temperature and precipitation on aboveground plant community biomass, with biomass peaking at intermediate precipitation
levels. There were also positive correlations between precipitation, graminoid dominance, and plant community C:N. This suggests changes in plant community C:N are mediated through graminoid dominance. Previous field and lab warming experiments, mostly in the arctic tundra, have reported increases in N mineralization or availability with increased temperature: My results appear to contradict these studies and stress the need to compare experimental results to natural gradient studies. Natural gradients can give vital clues about how particular relationships between variables may change in the context of other variables not accounted for in short-term, small-scale experiments. This is particularly relevant in the face of climate change where multiple ecosystem variables are changing at once, potentially causing a deviation from the predicted trajectory of a community.