SPATIO -TEMPORAL DYNAMICS OF GREENHOUSE GAS EMISSIONS FROM SOIL IN FOREST ECOSYSTEMS OF PAKISTAN

Intergovernmental Panel on Climate Change (IPCC) in its sixth assessment report (AR -6) has documented that the atmosphere, ocean, and land have been warmed at an unprecedented rate as per history of last 2000 years. Greenhouse gas (GHG) emissions from agriculture and forest soils account for 24% of the total global emissions. Soil processes directly contribute to climate change through the production and consumption of carbon dioxide (CO2), methane (CH4) and nitrous Oxide (N2O). Because of huge spatial and temporal variability in the soil -atmosphere exchange of GHGs, the measurement of prevailing concentrations and prediction are still difficult. Under different forest types, soil responds in a dissimilar fashion under varying climatic conditions. This research endeavor was pursued to estimate GHG accumulations from soil under scrub, subtropical pine and moist temperate forests. This study is of unique scientific efforts and features in which empirical data of the soil GHG emissions was gathered based on field observations. The present study apprehended forest diversity and temporal variations using a static chamber and photoacoustic spectroscopy to estimate GHG accumulations from soil. Seasonal variations strongly influenced CO2 emissions in three forest types, while N2O accumulation was not influenced by seasonal variations. In the winter season, the GHG accumulation decreased due to reduced microbial and root respiration. Methane was not detected in any of the forest types investigated in this study. Our results showed that soil under moist temperate forests produced more CO2 in summer as compared to that in the other forest types. The subtropical chir pine forest has the highest N2O accumulation in both summer and winter seasons. The outcomes of the research will be useful for developing national GHG inventory as well as Forest Reference Emission Levels (FREL) for REDD+ implementation under the Paris Agreement. Further, the data produced in this study may be helpful in carbon trading under Kyoto Protocol. The present approximations of GHGs will aid in predicting the future climate trends.