Higher temperatures associated with global climate change are predicted to cause an increase in soil nutrients such as nitrogen. This will have pronounced effects on plants at northern latitudes that are adapted to low nutrient conditions. We used long-term experimental plots near Kluane, Yukon, to investigate why some species are more successful than others in plots that have been annually fertilized for 22 years. Previous research in this area has shown that success in fertilized conditions varies widely between species: some species increase in abundance when fertilized (e.g. Mertensia paniculata and Epilobium angustifolium), others decline (e.g. Festuca altaica), and others show little change in abundance (e.g. Achillea millefolium). We asked a) whether functional traits such as plant height, specific leaf area (SLA) and growth rates can predict abundance in fertilized conditions and b) whether successful species are phenotypically plastic and are able to increase biomass allocation to leaves in fertilized conditions. We measured morphological traits, growth rates, and biomass allocation for four target species in fertilized and control plots during the 2011 growing season.
Results/Conclusions
Results indicate that a combination of factors has likely contributed to the success of Mertensia paniculata and Epilobium angustifolium in nutrient-enriched conditions. Mertensia paniculata had a higher SLA than any other species, and fertilized plants of this species had rapid growth rates earliest in the season. Epilobium angustifolium was the tallest species and demonstrated phenotypic plasticity by investing more biomass into leaves when fertilized. In contrast, loser and neutral species tended to be shorter with lower SLAs and later growth spurt date. This research reveals that rather than one strategy prevailing as the most successful under fertilized conditions, success in a nitrogen-enriched boreal forest understory may be determined by a combination of traits and strategies. This study highlights the important contribution of long-term experiments in assessing how vegetation may respond under predicted climate change trajectories.