Seasonal variation in soil bulk density, organic nitrogen, available phosphorus, and pH

Authors: Wuest, Stewart

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/10/2015
Publication Date: 7/24/2015
Publication URL: http://handle.nal.usda.gov/10113/5922788
Citation: Wuest, S.B. 2015. Seasonal variation in soil bulk density, organic nitrogen, available phosphorus, and pH. Soil Science Society of America Journal. 79:1188-1197.

Interpretive Summary: Soil scientists most commonly evaluate levels of soil carbon, nitrogen, pH, and other soil factors by sampling at one point in time. This study sampled soil every month for 39 months to learn how much sampling error might be caused by the yearly cycle of soil temperature, moisture, plant growth, and other seasonal factors. It was found that the seasonal cycle is substantial for soil organic nitrogen, available phosphorus, and pH, with a minimum of 10% and maximums above 30% variation. It is recommended that scientists sample at many points during a year in order to get more accurate evaluations of the differences between soil management options and more accurate estimates of long-term changes.

Technical Abstract: Scientists are being called upon to measure and predict the effects of soil management and climate change on organic matter and other soil properties. The estimates and predictions generated from current conditions and short-term experiments will only be accurate if our measurement techniques produce the data that we assume it does. Perhaps the least studied aspect of soil sampling is the possibility that the timing of samples might introduce large non-random errors. This study sampled replicated plots every month for 39 months. Even after removing the measurement variation caused by surface soil bulk density fluctuations, variation in organic N, available P, and pH was always greater than 10%. Much of the variation appeared to be temporally correlated in a seasonal cycle. In this experiment, with a one-year crop rotation, averaging 12 monthly samples allowed differences between soil treatments to be detected that were 2 to 4% of the mean. When highly accurate estimates are desired, researchers need to consider multiple sample timings to overcome temporal variability.