Submitted to: Rangeland Ecology and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 9, 2008
Publication Date: November 1, 2008
Repository URL: http://www.bioone.org/doi/pdf/10.2111/07-147.1
Citation: Clark, P., Hardegree, S.P., Moffet, C.A., Pierson Jr, F.B. 2008. Point sampling to stratify biomass variablity in sagebrush steppe vegetation. Rangeland Ecology and Management 61:614-622. Interpretive Summary: Tradition methods for sampling vegetation biomass are time-consuming, expensive, and, because they destructive, prevent repeated measures. We examined cost effectiveness of using a non-destructive, point sampling technique to stratify variability in subsequent biomass sampling on a sagebrush-bunchgrass rangeland site in southern Idaho. Double-sampling strategies where half of the point-sampled plots were also measured for biomass yielded a cost savings of 39% with relatively minor reduction in biomass sample precision (18 ± 4%). Agricultural producers, natural resource managers, and research will greatly benefit from these findings through cost savings and increased availability of biomass information accruing when sampling cost constraints are reduced.
Technical Abstract: Cover and yield are two of the most commonly monitored plant attributes in rangeland vegetation surveys. These variables are usually highly correlated and many previous authors have suggested point-intercept estimates of plant cover could be used as a surrogate for more expensive and destructive methods of estimating plant biomass. When measurement variables are highly correlated, double sampling can be used to pre-stratify variability in the measurement that is more difficult or costly to obtain thus improving sampling efficiency. The objective of this study was to examine the cost effectiveness of using point-intercept data to pre-stratify variability in subsequent clipped-biomass sampling on a sagebrush-bunchgrass rangeland site in southern Idaho. Point-intercept and biomass data were obtained for shrub, grass and forb vegetation in ninety 1-m2 plots. These data were used to develop a synthetic population of 10,000 simulated plots to conduct sensitivity analysis on alternative double-sampling scenarios. Monte Carlo simulation techniques were used to determine the effect of sampling design on cost and variability of biomass estimates as a function of point-intercept sample size (i), number of sample strata (s), and number of biomass samples per stratum (m). Minimization of variability in biomass estimates were always obtained from stratification scenarios in which a single median biomass estimate was obtained for a given stratum. Double-sampling strategies in which half of the point-intercept plots were also measured for biomass yielded a cost savings of 39% with a reduction in biomass-sample precision of only 18 ± 4%. The relative loss of precision in biomass estimates (62 ± 12%) became equal to the relative cost savings of double sampling for scenarios in which the ratio of point-intercept/biomass samples exceeded a value of 5.