Estimating Rangeland Production in Current and Future Conditions Using SSM-iCrop2 Model in Iran

• Published in: Agricultural research (India : Online) Vol. 12; no. 3; pp. 346 - 355
• Main Authors: Nehbandani, Alireza, Barani, Hossein, Soltani, Afshin, Torabi, Benjamin, Sharifian Bahraman, Abolfazl
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.09.2023; Springer Nature B.V
• Subjects: Biodiversity; Biomedical and Life Sciences; Carbon dioxide; Carbon dioxide concentration; Cell Biology; Climate change; Climate effects; Coefficient of variation; Correlation coefficient; Correlation coefficients; Dry matter; Full-Length Research Article; Life Sciences; Parameterization; Plant Biochemistry; Plant Ecology; Plant Genetics and Genomics; Plant Sciences; Rangelands; Spring (season); Steppes; Iran; GYGA-ED; Climate change; Rangeland production; SSM-iCrop2; HadGEM
• ISSN: 2249-720X; 2249-7218
• DOI: 10.1007/s40003-023-00652-z

The effect of climate change on rangelands production in Iran is an important issue. This study aimed at parameterization and evaluation of SSM-iCrop2 and predicting spring re-growth and production of rangelands in current and future (under RCP4.5 and RCP8.5 climate change scenarios in 2050) conditions in Iran. The dry matter production data of 46 sites and the initiation date for spring growth of 34 sites in five rangeland types (Sahara-Sindian, semi-desert, steppe, semi-steppe, and high-mountainous) and three rangeland conditions (good, fair and poor) were used for parameterization and evaluation of the model. The results demonstrated that the model performed well and could predict rangeland production with a coefficient of variation of 18% and a correlation coefficient of 0.96. Simulation runs showed that climate change will affect growth and production of rangelands. In a way that the current 10.86 million ton average rangeland production of the country was estimated 6.9 and 4.8 percent less in RCP4.5 and RCP8.5, respectively. Furthermore, the average spring re-growth decreased from 73 days after first of January in the current condition to 66 and 61 days after January in RCP4.5 and RCP8.5 scenarios, respectively. Growth and production were closely linked to temperature and precipitation changes. Also, the increase in CO 2 concentration modulated the negative effects of climate change. Ultimately, it can be concluded that SSM-iCrop2 model has the ability to simulate large-scale rangeland production with a relatively simple approach.