Golf Course Management

JAN 2014

Golf Course Management magazine is dedicated to advancing the golf course superintendent profession and helping GCSAA members achieve career success.

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Page 146 of 196

High-performance turf at Keya GC near Fukuoka, Japan, is maintained in soils with sulfur and magnesium near the MLSN guideline and potassium below conventional guidelines. Adding data from sites like this helps to improve the accuracy of the guidelines as they are updated. With MLSN, we take a different approach, taking the data from thousands of sites with good performance, assuming that there must be enough nutrients available to produce good turf because the sites are already performing well, and then selecting a conservative value at the 0.1 level at the lower end. Because we have already omitted the sites with bad performance from our data set, we can have some confdence that these apparently low levels are suffcient to meet the requirements of the grass. Four advantages of this approach 1. The guidelines are based on real data from actual turfgrass sites. We worked only with a data set from sites with good performance, omitting soil test results from problem areas and nutrient-defcient soils. The modeled distribution is a mathematical representation of the soil nutrient levels as they are distributed on actual turfgrass sites. Because the data are carefully selected from soils that are already producing good turf, there is a layer of safety 136 GOLF COURSE MANAGEMENT 01.14 in the model. That is, any clearly defcient soils were not included in the model, so the results are not skewed lower by nutrient-defcient soils. 2. Once the model has been ft to the actual data, we can select a base level we wish to stay above. Again, this model and the associated level are based on the actual nutrient levels in the soil at sites where turfgrass performs well. We chose the nutrient level coinciding with the 10th percentile to defne the MLSN guideline for each element. At this level, 10% of the samples in the data set would have a lower soil nutrient level than the selected MLSN guideline. 3. We can calculate a sustainability index for each element, based on a comparison of the concentration of that element on a soil test with the modeled MLSN distribution for that element. The sustainability index is the proportion of the modeled distribution that reports values greater than the sample soil test value. This is a metric that assists turf managers in the evaluation of soil nutrient levels over time. It also provides a guide for the development of nutrient management programs. Perhaps most important, the sustainability index identifes and rewards the restriction of nutrient inputs when they are not necessary to meet turf performance goals. 4. The MLSN guidelines are easily updated as we add new data from turfgrass sites with good performance (see the sidebar on page 138).These guidelines are self-correcting. Using this method and continuously adding to the reference data set with soil test data from turfgrass sites that perform well, we will see the guidelines move up if they are too low or down if they are too high. In short, these guidelines are designed to be updated as the core data set grows, and the MLSN guidelines will adjust based on samples added to the data set from turfgrass that performs well on various soils and across a wide geographic range. Additional Information For more about these guidelines, videos explaining the guidelines, and a link to the most current version of the guidelines, see: www.

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