Variation in soil data within a small site
Recently, I undertook a soil investigation at the National Arboretum Canberra as part of an environmental measurement and monitoring course at the Australian National University. Soils were sampled from nine locations within one forest plot containing Eucalyptus tricarpa (red ironbark) and Corymbia maculata (spotted gum) tree species. Using field methods, we tested for profile depth, texture, structure, Emerson, gravimetric moisture content, bulk density, hydraulic conductivity, total porosity, pH and colour. The variation in soil physical and chemical properties between the nine sampling locations was surprising considering the proximity of each sampling location. Our results showed that structure grade ranged between massive to strong, total porosity between 0.49- 0.61, hydraulic conductivity (Ksat) from 1.57- 402.63 mm/hr, Emerson from stable to dispersive and profile depth from 25cm- 205cm. Textures also varied with soils of sandy loams, sandy clays, light clays, medium clays and silty clay loams.
Why do we have significant data variation in soil samples collected from the same site? Is it because the person doing the fieldwork did something wrong? The truth is, variation can be contributed by a number of different factors and is not necessarily due to sampler’s error.
The main factor is the varying soil properties at the site. Soil properties are effected by differences in slope, topography, management (e.g. fertiliser and irrigation regime), ground cover and geology. Soil recovered from a steeper slope or on top of a hill is generally different from soil at the bottom of the hill (low lying area), with the main distinction being the depth of soil available and formed on different topography. Soil from areas with dense vegetation could also be different to areas with bare ground; such as the case shown in the soil cores below taken 70m from each other.
However it must be noted that differences in the data can be caused by human activity or disturbance, as well as sampler’s error. For example, areas of high human traffic on site will have more compacted soils which can alter the soil properties, whilst some areas of the site may have been filled with imported soils due to former landuse activity, altering the soil type on-site
Variation can also stem from differences in observation between the samplers. This doesn’t necessarily mean either of the samplers are wrong. Subjectivity in field testing is common and can introduce bias into data. A great example of this is soil field texturing which requires a subjective classification of soil texture based on how to soil ‘feels’ to the sampler. To overcome subjectivity, we can compare field results with laboratory results and use standardised field guides, such as a soil munsell chart to determine colour (shown below).
Why is it important to understand the varying factors that can affect the soil data? In order to characterise a soil resource accurately, it is vital to consider the features and history of the site, and possible variations of soil type to gain an accurate representation of the soils on-site. A quick guide is to ask the following questions prior to sampling:
- What are the site properties? (topography, location, climate)
- What are the known soil properties on site? (geology, soil landscape)
- What are the current and former landuse of the site?
- What did you observe from site? (compaction? Slope? Disturbed soil? Earthwork?)
- Are all samplers trained to use the same sampling method? Including quality controls?
- Are all laboratory tests conducted using the same methods? What were the quality controls?
Article written by SESL Australia intern Samantha Hovar