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Evaluating the variability of ANPP in central Iranian arid and semi-arid rangelands using CASA model and its relationship with climatic factors

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Abstract

Aboveground Net Primary Production (ANPP) plays an important role in regulating ecological processes and carbon cycle in arid and semi-arid rangelands. Hence, this study aimed to investigate the spatio-temporal variability of rangeland ANPP in seven bioclimatic zones in Isfahan Province using the Carnegie-Ames-Stanford Approach (CASA) ecosystem model fitted with MODIS-NDVI and climatic data during 2000–2016. The model evaluation indicated a good agreement between the estimated and observed ANPP (R2 = 0.917). In concomitant with the precipitation gradient, the mean annual ANPP increased from east towards west and southwest of the region from zero to 160 g C m–2 yr–1. The maximum and minimum ANPP values occurred in humid and cold as well as hyper-arid and warm zone, respectively. The annual temporal variability of ANPP was analyzed in response to climatic factors (precipitation and temperature), Temperature Vegetation Dryness Index (TVDI) and Standard Precipitation Index (SPI) drought indices. The drought was found as the most important factor affecting ANPP. The minimum and maximum ANPP values were observed in 2000 (23.23 g C m–2 yr–1) and 2014 (41.73 g C m–2 yr–1). The maximum ANPP occurred in May and June during which temperature, as an important factor in plant growth, reached its optimum and precipitation affected with a time lag. The annual rangeland ANPP was positively associated with precipitation and negatively with temperature.

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Authors and Affiliations

  1. Department of Natural Resources, Isfahan University of Technology, Isfahan, 8415683111, Iran

    Marjan Saki, Saeid Soltani, Mostafa Tarkesh Esfahani & Reza Jafari

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  1. Marjan Saki
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  2. Saeid Soltani
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  3. Mostafa Tarkesh Esfahani
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  4. Reza Jafari
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Correspondence to Marjan Saki.

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Saki, M., Soltani, S., Esfahani, M.T. et al. Evaluating the variability of ANPP in central Iranian arid and semi-arid rangelands using CASA model and its relationship with climatic factors. Geosci J 23, 531–545 (2019). https://doi.org/10.1007/s12303-018-0040-1

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