24
Investigation of the trends and variability of terrestrial carbon for the South Asian region

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Monday, 3 February 2014
Hall C3 (The Georgia World Congress Center )
Ananya S. Rao, Indian Institute of Science, Bangalore, Karnataka, India; and G. Bala

Terrestrial ecological systems play an important role in the global carbon cycle as carbon is retained in live biomass, decomposing organic matter and soil; and it is exchanged naturally between these systems and the atmosphere through photosynthesis, respiration, decomposition, and combustion. Carbon in the form of inorganic and organic compounds, notably CO2, is also cycled between the atmosphere, oceans, and terrestrial biosphere and the largest natural exchanges occur between the atmosphere and terrestrial biota. Also, The storage of carbon in the terrestrial biosphere(2100 PgC) is about 3 times larger than the pool of carbon as CO2 in the atmosphere(750 PgC). If all sources of the terrestrial carbon are equal to all the sinks, the carbon cycle can be said to be in equilibrium (or in balance). However, because fossil fuel combustion and deforestation have increased CO2 inputs to the atmosphere without matching increases in the natural sinks (oceans, forests, etc.), these activities have caused the size of the atmospheric carbon pool to increase and is believed to cause the observed trend of increasing global temperatures. Thus, the carbon balance can be changed considerably by various factors, in turn affecting the climate of the world. Here, in this study, we investigate four main drivers of the trends and variability in the land carbon stocks: CO2 Concentration, Nitrogen Deposition, Climate warming and Land use/cover change. Increased atmospheric CO2 has the potential to increase plant growth. This is known as CO2 fertilization effect. This leads to removal of more CO2 from the atmosphere. However, the rate of photosynthesis would increase with higher CO2 concentrations only up to a saturation point. Plant and microbial respiration tend to increase with increasing temperatures. As a consequence, global warming may result in a net release of carbon from the land to the atmosphere. The productivity of many temperate ecosystems is nitrogen limited. Adding N via deposition as well thus has the potential to increase growth, and therefore to sequester CO2 from the atmosphere, until a certain level. Land-use/cover changes are also major contributors to the net emission of CO2. Globally, the long-term flux of carbon from changes in land use (1850–2000) released 156 PgC to the atmosphere. Variability in terrestrial carbon stocks are also driven by other climatic variability which include El Niño and La Niña events, volcanic eruptions etc., which are also assessed as a part of this study. Since all global budgets are an aggregate of various regional budgets, we concentrate on the South Asian region to understand better the processes that cause the trends and variability in the terrestrial carbon of the region. The South Asian region, which has the coordinates 7-38 ° N and 68-98 ° E, is the area of study. It covers all of India, Nepal, Bhutan, Tibet, Bangladesh Eastern part of Pakistan and Western part of Myanmar. The region is home to around 1.6 billion people and covers an area of 5.5X106 Km2. The objective of this study is to quantify the relative contribution of various environmental drivers (Land use change, N-deposition etc.) to the trends and variability in the carbon stocks and fluxes for the South Asian region. A a general circulation model is used for this purpose. Developed by the National Centre for Atmospheric Research (NCAR), the Community Land Model is the land model for the Community Earth System Model (CESM) and the Community Atmosphere Model (CAM). Here we use the Community Land Model version 4, for our study. The model formalizes and quantifies concepts of ecological climatology. It is prognostic in carbon and nitrogen (CN) and also transient land cover change and wood harvest are implemented. A prognostic fire model simulates wildfire. A prognostic fire model simulates wildfire. The contributions of each of the four factors mentioned earlier are quantified for the region.