Disc pasture meter calibration to estimate grass biomass production in the arid dunefield of the south-western Kalahari. Issue 3 (4th October 2019)

• Record Type: Journal Article
• Authors: Harmse, Christiaan J; Dreber, Niels; Trollope, Winston SW
• Is Part Of: African journal of range & forage science. Volume 36:Issue 3(2019)
• Page Start: 161
• Page End: 164
• Publication Date: 2019-10-04
• Subjects: forage production -- grazing -- range management -- savanna -- Stipagrostis spp; Range ecology -- Africa -- Periodicals; Range ecology -- South Africa -- Periodicals; Range management -- Africa -- Periodicals; Range management -- South Africa -- Periodicals; Pasture ecology -- Africa -- Periodicals; Pasture ecology -- South Africa -- Periodicals; Pastures -- Management -- Periodicals; Forage plants -- Africa -- Periodicals; 633.202096
• DOI: 10.2989/10220119.2019.1610905
• Languages: English
• ISSNs: 1022-0119

Abstract

Abstract : The disc pasture meter (DPM) is a tool that is widely used to estimate aboveground standing grass biomass (ASB) in a rapid and non-destructive manner. Depending on the species composition, rangeland condition and local climate, available DPM calibrations may fail in providing precise measurements for a certain area. We calibrated a DPM for the arid dunefield savanna of the south-western Kalahari as found in the Northern Cape province of South Africa and bordering Namibia and Botswana. Assessments were done at 30 sites and restricted to inter-dune areas. The site selection accounted for different grazing conditions to ensure a better representation of the variability in ASB in the region. We determined grass species composition, basal cover and dry matter production in relation to height readings of the DPM. The grass sward was dominated by the species Stipagrostis ciliata, S. obtusa and Schmidtia kalahariensis, with a mean density of 25 cm point-to-tuft distances . Based on 90 paired observations of ASB and disc height ( x ; cm), the equation ӯ (kg ha −1 ) = 213.37( x ) + 103.36 ( r 2 = 0.760) was established. In comparison to other models, the equation avoids an overestimation of ASB in this vegetation type, and thus leads to more accurate estimations.