Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

354-2 Space-for-Time Substitution and Paired Plot Design: Alternatives to Convectional Experimental Design.

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Beyond RCBD:Experimental Design for Spatial Variability

Wednesday, October 25, 2017: 10:00 AM
Marriott Tampa Waterside, Florida Salon I-III

Bing Cheng Si, Dept Soil Science, University of Saskatchewan, Saskatoon, SK, Canada and Asim Biswas, 50 Stone Road East, University of Guelph, Guelph, ON, CANADA
Abstract:
Replicated experiments are well-suited for annual crops, but have many challenges when perennials and woody species are involved. One common question is how woody species (or forest or orchard) affect soil properties and which, in turn, affect the plantations. Here we adopt the space for time substitution and paired plot design to tackle the question. On the Chinese loess plateau, there has been massive ecorestoration efforts since 1999. Different tree species have since been planted for soil and water conservation, and for economical return. However, there are increasing concerns on the sustainability of these ecorestoration efforts. In order to answer the sustainability question in a rapid fashion, a proper experimental design is needed for sampling and monitoring, from the existing farm field, soil and vegetation properties. Using the space-for-time substitutions and paired plot design, we selected orchards that have a stand age of 9, 13, 15,18, and 22. Soil water contents and organic carbon contents were measured. The long-term trend in soil water and carbon contents were analyzed and the effect of deep-rooted vegetation on deep soil water storage, groundwater recharge and carbon storage with increasing stand age were quantified. The results obtained from these experiment designs provide much needed information that is otherwise hard to obtain from a conventional experimental design for sustainability assessment.

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Beyond RCBD:Experimental Design for Spatial Variability