Designing an experiment with quantitative treatment factors to study the effects of climate change |
| |
Authors: | H.‐P. Piepho M. Herndl E. M. Pötsch M. Bahn |
| |
Affiliation: | 1. Biostatistics Unit, Institute of Crop Science, Universit?t Hohenheim, Stuttgart, Germany;2. Institute of Plant Production and Cultural Landscape, Agricultural Research and Education Centre, Raumberg‐Gumpenstein, Austria;3. Institute of Ecology, University of Innsbruck, Innsbruck, Austria |
| |
Abstract: | Experiments for studying the effects of climatic change on ecosystems often involve manipulation of one or several quantitative treatment factors of interest. Response surface regression is the method of choice for these types of experiment. Here, we describe the development of a design of a free air CO2 enrichment experiment with two quantitative treatment factors, that is, elevated temperature and CO2 enrichment. The design strategy takes account of budget constraints imposing limitations on the number of plots with elevated temperature and CO2 levels. The approach is based on polynomial regression models and is focussed on an efficient estimation of interaction between the two treatment factors. Extension to more than two factors is straightforward. An analysis of soil moisture data demonstrates the overall suitability of the proposed design to analyse non‐linear interactions of two (or more) global change factors. |
| |
Keywords: | experimental design field experiment free air CO2 enrichment multifactorial experiment polynomial regression response surface regression |
|
|