Under the auspices of Global Observation Research Initiative in Alpine Environments (GLORIA), ITFC has established high altitude plots to monitor vegetation changes on selected summits of Mountain Elgon and Rwenzori (famously known as the Mountains of the Moon). GLORIA seeks to establish a long-term observation network to obtain standardized data on alpine biodiversity and vegetation patterns on a global scale. Its purpose is to assess risks of biodiversity losses and the vulnerability of high mountain ecosystems under climate change.
High altitude vegetation monitoring
Mountain regions are hot spots for climate research across the globe because of their similar climatic conditions. Mountains host a high diversity of plants and animals, many of which can only survive at high altitudes characterized by low temperatures. Low-temperature limits of plant life on high mountains are considered to be particularly sensitive to climate change. Numerous changes in plant phenology and in the distribution of plants and animals have been documented to be related to climate change.
What do we hope to achieve?
Overall, this study will contribute to the global data base in comparisons of climate change impacts on mountain biodiversity across continents. More specifically, it will:
- Provide standardised, quantitative data on the altitudinal differences in species richness, species composition, vegetation cover, on the soil temperature and on the snow cover period in mountain systems.
- Assess the potential risks for biodiversity losses due to climate change by comparing the current distribution patterns of species, vegetation, and environmental factors along vertical and horizontal (biogeographical) gradients.
- Provide a baseline for the long-term monitoring and observation of species and vegetation to detect climate-induced changes of vegetation cover, species composition and species migration (at observation intervals of 5 to 10 years or even longer, if appropriate).
- Quantify the temporal changes of biodiversity and vegetation patterns for providing a substantial input to data-based scenarios on risks for biodiversity losses and on risks for ecosystem instability.