Modeling Potential Distribution and Carbon Dynamics of Natural Terrestrial Ecosystems: A Case Study of Turkey

• Main Authors: Can Ertekin, Onder Gulbeyaz, Suha Berberoglu, Fatih Evrendilek
• Format: Article
• Language: English
• Published: MDPI AG 2007-10-01
• Series: Sensors
• Subjects: Biogeoclimate zones; Land cover; Spatio-temporal modeling; Net primary productivity; Soil organic carbon; Turkey.
• Online Access: http://www.mdpi.com/1424-8220/7/10/2273/

We derived a simple model that relates the classification of biogeoclimatezones, (co)existence and fractional coverage of plant functional types (PFTs), and patternsof ecosystem carbon (C) stocks to long-term average values of biogeoclimatic indices in atime- and space-varying fashion from climate–vegetation equilibrium models. ProposedDynamic Ecosystem Classification and Productivity (DECP) model is based on the spatialinterpolation of annual biogeoclimatic variables through multiple linear regression (MLR)models and inverse distance weighting (IDW) and was applied to the entire Turkey of780,595 km2 on a 500 m x 500 m grid resolution. Estimated total net primary production(TNPP) values of mutually exclusive PFTs ranged from 108 26 to 891 207 Tg C yr-1under the optimal conditions and from 16 7 to 58 23 Tg C yr-1 under the growth-limiting conditions for all the natural ecosystems in Turkey. Total NPP values ofcoexisting PFTs ranged from 178 36 to 1231 253 Tg C yr-1 under the optimalconditions and from 23 8 to 92 31 Tg C yr-1 under the growth-limiting conditions. Thenational steady state soil organic carbon (SOC) storage in the surface one meter of soil wasestimated to range from 7.5 1.8 to 36.7 7.8 Pg C yr-1 under the optimal conditions andfrom 1.3 0.7 to 5.8 2.6 Pg C yr-1 under the limiting conditions, with the national range of 1.3 to 36.7 Pg C elucidating 0.1% and 2.8% of the global SOC value (1272.4 Pg C), respectively. Our comparisons with literature compilations indicate that estimated patterns of biogeoclimate zones, PFTs, TNPP and SOC storage by the DECP model agree reasonably well with measurements from field and remotely sensed data.