Justification for Grazing Intensity Experiments: Analysing and Interpreting Grazing Data

Abstract

Grazing trials in which treatments are compared at only 1 gruing intensity greatly outnumber those in which treatments are compared at several grazing intensities. This suggests that, compared to other treatments and the need for replication in grazing trials, researchers consider grazing intensity lower in priority. In this study, a regression modeling approach for analyzing and interpreting data was developed to enhance the vahte of grazing intensity trials. As an example, results from 5 irrigated bermudagrasses (Cynodon dkctylon (L.) Pen) (Caliie, Coastal, Brazes and experimental hybrids S-54 and S-16) which were continuously grazed without field replication by Santa Gertrudis steers at 4 grazing intensities were considered. The relationships between average daily gain (ADG) and stocking rate, ADG and herbage present (ML/ha), and between stocking rate (animals/ha) and herbage present were well described by linear functions for all cultivars, with correlation coefficients(r) mostly above 0.9. CaMcients of determination (R*) for linear regression models derived for ADG vs stocking rate, ADG vs herbage present, and stocking rate VI herbage present were 0.90**, 0.89++, and 0.87**, respectively. Significant cultivar X grazing intensity (as measured by stocking rate or herbage present) interactions (p10.01) were observed. Furthermore, estimated stocking rates which provided maximum gain/ha ranged from 6.6 to 9.4 animals/ha, and the range in herbage present which provided maximum gain/ha was 0.35 to 1.95 Ml/ha. Callie provided an estimated maximum gain/ha of 881 kg/ha/season, while maximum gain/ha for the other cultivars ranged from 613 to 687 kg/ha/season. Comparison between these 5 cuitivars at only 1 grazing intensity would have had very narrow application. The procedure described allowed statistical comparison of cultivars without replication, and inferences about the separate effects of forage quality and quantity on animal performance could be made. Herbage present and cultivu were descriptors of the pasture. Since there was a substantial range of values for herbage present and stocking rate, ail important assumptions underlying linear regression were met and designs utilized in analysis of variance were not needed.

Economic Returns for Purchased or Contract‐Grazed Stockers on Marshall Annual Ryegrass

“…These findings are in disagreement with those of other studies in which the relationship between ADG and stocking rate was linear (Mezzadra et al, 1992; Bransby et al, 1988; Hart, 1972; Bryant et al, 1965; Petersen et al, 1965; Riewe et al, 1963; Riewe, 1961), although Ashley (1993) and Oberholster (1990) also reported a quadratic relationship between ADG and stocking rate for annual ryegrass pastures and also for cereal rye ( Secale cereale L.).…”

Forage Intake and Ingestive Behavior of Cattle Grazing Old World Bluestems

“…Replication of treatments was not attempted initially, because the inevitable differences between replicates would consume resources that could otherwise be allocated to increasing the range of treatments. Bransby et al (1988) described the use of a regression modeling approach for the analysis of unreplicated, multiple treatment grazing trials, based on a proposal by Riewe (1961) . .…”

Livestock grazing regulates ecosystem multifunctionality in semi‐arid grassland

“…This regression approach is more powerful statistically than replicated ANOVAbased designs, and allows for research that is more relevant to both management and predictive ecology, by assessing how the effects of the treatment vary with level of the treatment (Cottingham, Lennon, & Brown, 2005). This regression approach is particularly effective for a broad array of management-scale questions, ranging from effects of grazing to effects of precipitation change (Beier et al, 2012;Bransby, Conrad, Dicks, & Drane, 1988).…”