Theme 1-2: Rangeland/Grassland Ecology--Poster Sessions
Description
Change in range condition classes over time are usually the basis for monitoring management effectiveness. Several approaches have been proposed to monitor the range condition classes in relation to a bench mark usually called climax stage. There are some types of range condition classification often included in a range inventory. In this paper, six factors of canopy cover, litter frequency, plant vigour, soil protection percentage, plant composition, and present production as a percentage of indicative state were described for determination range conditions. We have determined range condition classes by using R software. This method was developed by FAO projects in Iran. The relationships between different factors and their scores were determined by linear equations. The vegetation data in field were collected in 20 plots of 25x60 cm by established F-shaped layouts. In each plot, species cover percentages, litters, rocks, and bare soils were estimated. Based on our total scores, we got the fair state of range condition. It is possible to create a package in R software to determine condition classes which will be used by range managers and experts.
Citation
Fakhar, Nafiseh; Mesdaghi, Mansour; and Naseri, Kamal, "Range Condition Classification Based on Quantitative Characteristics of Vegetation" (2022). IGC Proceedings (1993-2023). 27.
https://uknowledge.uky.edu/igc/24/1-2/27
Included in
Range Condition Classification Based on Quantitative Characteristics of Vegetation
Change in range condition classes over time are usually the basis for monitoring management effectiveness. Several approaches have been proposed to monitor the range condition classes in relation to a bench mark usually called climax stage. There are some types of range condition classification often included in a range inventory. In this paper, six factors of canopy cover, litter frequency, plant vigour, soil protection percentage, plant composition, and present production as a percentage of indicative state were described for determination range conditions. We have determined range condition classes by using R software. This method was developed by FAO projects in Iran. The relationships between different factors and their scores were determined by linear equations. The vegetation data in field were collected in 20 plots of 25x60 cm by established F-shaped layouts. In each plot, species cover percentages, litters, rocks, and bare soils were estimated. Based on our total scores, we got the fair state of range condition. It is possible to create a package in R software to determine condition classes which will be used by range managers and experts.
