Suitability Maps Process
Suitability curves were developed for each clover species for three climate variables (average annual precipitation, average July maximum temperature, and average annual extreme low temperature) and three soil variables (drainage class, pH, and salinity). For each variable and for each species, the curves were fitted using estimated yield data across the range of values for the given variable. Climate variables were fitted using Logistic curve, pH was fitted with a Gaussian curve, and salinity was fitted with a critical exponential function. Since soil drainage is defined as categories, no function was fitted; estimated relative yield values were based on suitable ranges of drainage specified in the NRCS Range and Pasture handbook.
The coefficients for the model equations were compiled into a single table as input to a python script written for ESRI's GIS software, ArcGIS. The script uses spatial data for each of the climate and soil variables as inputs, and together with the table of equation coefficients, produces spatial outputs representing percent yield for each of the clover species and each climate and soil variable. This design ensures that the script can easily be re-run with updated equation coefficients as the relationships between the environmental variables and yield are refined.
The percent yield layers are then classified by the script into four suitability classes, as follows:
0-25% - Not suitable
25%-50% - Marginally suitable
50%-75% - Moderately suitable
75%-100% - Suitable
The script produces three "hybrid" suitability layers based on combinations of the three climate variables, the three soil variables, and all six climate and soil variables together. These combined suitability layers were created by selecting for every location the lowest suitability value of the included variables, with overall suitability for a species limited by the most restrictive factor. A map atlas was created in ArcGIS to produce Jpeg maps of each clover species for each soil, climate, and "hybrid" variable.
Species Suitability Maps
Suitability maps were developed for each species using quantitative tolerance functions for climate and soil factors applied to GIS grids for minimum temperature, maximum temperature, annual precipitation, soil pH, soil drainage, and soil salinity. Combinations of factors maps were also produced for all climate, all soil, and all factors; 9 maps for each species.
- Alsike Clover
- Arrowleaf Clover
- Crimson Clover
- Kura (Caucasian) Clover
- Red Clover
- Strawberry Clover
- Subterranean Clover
- White Clover
Alsike Clover Suitability Maps
- Minimum Temperature
- Soil pH
- Combined Climate
- Maximum Temperature
- Soil Drainage
- Combined Soil
- Annual Precipitation
- Soil Salinity
- Combined Climate & Soil