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Journal Article

Prediction of future grassland vegetation cover fluctuation under climate change scenarios


Zarei,  Azin
Potsdam Institute for Climate Impact Research;

Asadi,  Esmaeil
External Organizations;

Ebrahimi,  Ataollah
External Organizations;

Jafari,  Mohammad
External Organizations;

Malekianc,  Arash
External Organizations;

Nasrabadi,  Hamid Mohammadi
External Organizations;


Chemura,  Abel
Potsdam Institute for Climate Impact Research;


Maskell,  Gina Marie
Potsdam Institute for Climate Impact Research;

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Zarei, A., Asadi, E., Ebrahimi, A., Jafari, M., Malekianc, A., Nasrabadi, H. M., Chemura, A., Maskell, G. M. (2020): Prediction of future grassland vegetation cover fluctuation under climate change scenarios. - Ecological Indicators, 119, 106858.

Cite as: https://publications.pik-potsdam.de/pubman/item/item_24449
Grasslands are subject to degradation in arid and semi-arid areas as the result of various pressures, including climate change. Therefore, spatial and temporal monitoring of vegetation cover fluctuation is needed for better understanding and management of natural resources to sustain livelihoods that depend on these grasslands. In this study, changes in vegetation cover were monitored over 1985-2015, using vegetation indices derived from the Landsat images in Chaharmahal-va-Bakhtiyari province, Iran. The percentage of vegetation cover was recorded from sampling plots in the study areas and vegetation indices were calculated from Landsat data over the study period. The relationship between vegetation cover and climate parameters (temperature (T) and precipitation (P)) was determined from precipitation maps, produced from spatial interpolation of weather stations data and temperature maps, produced by regression equation established between DEM-derived elevation and temperature. Then, a regression equation between climate variables and vegetation cover over a period of 30 years’ period was developed and applied on projected climatic variables for the 2050 under RCP2.6 and RCP8.5 scenarios. The Green Vegetation Index (GVI) was found to be the best index for estimation of vegetation cover from the correlation coefficient (r=0.79) and model RMSE (1.98). The GVI fluctuation was associated with the fluctuation in climate variables, and this was especially evident in especially dry years (1999, 2001 and 2012). From the difference between current and future vegetation cover maps, future vegetation cover change maps were produced and vulnerable areas most likely to be impacted by climate change were identified. The results predict that vegetation cover will be reduced under both scenarios, mostly in the eastern parts of the study region, while 5-25% of vegetation cover increases are projected for some areas in the western parts of the region. Further analysis showed that currently, oak forest covers large swaths of the western parts adjacent to grasslands, but forest degradation will lead to increase of grassland areas at the expense of oak forests. Overall, substantial loss of vegetation cover is predicted in the central parts and extends to the southern parts of the province. Loss of vegetation cover would pave the way to conversion of grassland to other non-productive cover types for pastoral systems. Appropriate management programs and adaptation strategies should be designed and implemented to reduce climate change impacts on grasslands in the identified vulnerable areas.