Estimating Spatio-temporal Responses of Net Primary Productivity to Climate Change Scenarios in the Seyhan Watershed by Integrating Biogeochemical Modelling and Remote Sensing
Climate change will have a significant impact on ecosystem functions, particularly in the Mediterranean. The aim of this study is to estimate responses of terrestrial net primary productivity (NPP) to four scenarios of regional climate change in the Seyhan watershed of the Eastern Mediterranean, integrating biogeochemical modelling and remote sensing. The CASA model was utilised to predict annual fluxes of regional NPP for baseline (present) (2000–2010) and future (2070–2080) climate conditions. A comprehensive data set including percentage of tree cover, land cover map, soil texture, normalised difference vegetation index, and climate variables was used to constitute the model. The multi-temporal metrics were produced using sixteen-day MODIS composites at a 250-m spatial resolution. The future climate projections were based on the following four Representative Concentration Pathways (RCPs) scenarios defined in the 5th Assessment Report of The Intergovernmental Panel on Climate Change: RCP 26, RCP 4.5, RCP 6.0 and RCP 8.5. The future NPP modelling was performed under CO2 concentrations ranging from 421 to 936 ppm and temperature increases from 1.1 to 2.6 ℃. Model results indicated that the mean regional NPP was approximately 1185 g C m−2 yr−1. Monthly NPP ranged from 10 to 260 g C m−2 for the baseline period. The total annual NPP was, on average, estimated at 3.19 Mt C yr−1 for the baseline period and 3.08 Mt C yr−1 for the future period. NPP in the Seyhan watershed appears to be sensitive to changes in temperature and precipitation. The CASA provide promising results for a better understanding and quantification of ecological and economic implications of regional impacts of climate change on biological productivity across the complex and heterogeneous watersheds of Turkey.
KeywordsClimate change IPCC Modelling MODIS NPP RCPs Turkey
We would like to acknowledge the research project grants (project no: 110Y338) from the Scientific and Technological Research Council (TÜBITAK) of Turkey.
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