Soil sampling in oil palm plantations: a practical design that accounts for lateral variability at the tree scale Paul N. Nelson, Murom Banabas, Iain Goodrick, Michael J. Webb, Neil I. Huth & Damien O’Grady Plant and Soil An International Journal on Plant-Soil Relationships ISSN 0032-079X Volume 394 Combined 1-2 Plant Soil (2015) 394:421-429 DOI 10.1007/s11104-015-2490-9
1 23
Your article is protected by copyright and all rights are held exclusively by Springer International Publishing Switzerland. This eoffprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”.
1 23
Author's personal copy Plant Soil (2015) 394:421–429 DOI 10.1007/s11104-015-2490-9
METHODS PAPER
Soil sampling in oil palm plantations: a practical design that accounts for lateral variability at the tree scale Paul N. Nelson & Murom Banabas & Iain Goodrick & Michael J. Webb & Neil I. Huth & Damien O’Grady
Received: 17 February 2015 / Accepted: 21 April 2015 / Published online: 30 April 2015 # Springer International Publishing Switzerland 2015
Abstract Aims The aim was to devise a practical soil sampling design for oil palm plantations that takes into account tree-scale variability, thus facilitating detection of trends in soil properties over time. Methods We geometrically evaluated the ability of linear sampling transects to represent the distribution of typical management zones and radial patterns known to influence soil properties. The effect of sampling point density was tested using interpolated surfaces of soil biological, chemical and physical properties derived from values measured on a 35-point sampling grid covering the repeating tree unit in plantations with 15– 25-year old palms. Results The ability of sampling transects to represent the proportion of the plantation in various zones improved with increasing transect length and sampling density. Increasing the number of sampling points from 10 to 50 (using an acceptably long transect with length 5.57×palm spacing) decreased the maximum deviation between the overall mean and the transect-derived mean Responsible Editor: Zucong Cai. P. N. Nelson (*) : I. Goodrick : D. O’Grady College of Science, Technology and Engineering, James Cook University, Cairns, Australia e-mail:
[email protected] M. Banabas PNG Oil Palm Research Association, Kimbe, Papua New Guinea M. J. Webb : N. I. Huth Agriculture Flagship, CSIRO, Townsville, Australia
from 15.9 to 5.6 % for the most variable parameter, respiration, and 3.2 to 0.6 % for the least variable parameter, bulk density. Conclusions Transect sampling provides an efficient means of obtaining a composite soil sample that accounts for tree-scale variability in oil palm plantations. The method is readily adaptable for other tree crops. Keywords Elaeis guineensis (Jacq.) . Sampling design . Soil analysis . Soil carbon . Spatial variability . Tree crop
Introduction For the results of soil analyses to be useful, samples must be taken in a way that accounts for spatial variability. Whatever the purpose of the sampling, sampling design must consider spatial variability at various scales, imposed by the nature of the landscape, vegetation and management (Brown 1999; Mulla and McBratney 2000; McKenzie et al. 2002; de Gruijter et al. 2006; Metcalfe et al. 2008; Pennock et al. 2008; Arrouays et al. 2012). At larger scales, landscape characteristics such as topographic position and soil type are important determinants of variability. Variability at smaller scales can also be important. In forests, orchards, vineyards and plantations, where perennials grow, spatial variability at the scale of rows or trees can be very high, so particular sampling designs are necessary to account for it (Birkeland 1984; Brown 1999). In oil palm (Elaeis guineensis Jacq.) plantations, which as a rule are planted in an equilateral triangular
Author's personal copy 422
pattern, with spacing of 8.50–10.25 m (Corley and Tinker 2003), there is large variability in soil properties at the scale of individual palms, induced by plant characteristics and management practices (Tinker 1960; Rankine and Fairhurst 1998; Corley and Tinker 2003; Nelson et al. 2014b, Fig. 1). Oil palm is becoming an increasingly important crop throughout the tropics (Cramb and Curry 2012; Sayer et al. 2012), and accurate assessment of soil properties under oil palm is critical for ensuring productivity and sustainability of the industry. Accounting for tree-scale variability is necessary when monitoring soil condition, making fertiliser recommendations and when calculating stocks and fluxes of water, carbon and nutrients (Rankine and Fairhurst 1998; Nelson et al. 2014b; Huth et al. 2014). The most common approach used by scientists and plantation managers to account for tree-scale spatial variability is to take separate soil samples from each visible management zone, for example in the weeded circle and under the frond pile (Fig. 1). Samples may also be taken at a particular point in relation to the palm, for example, in the row, halfway between palms (Fig. 1). Composite samples are usually made for each management unit (which has uniform soil type and palm age) using samples from several palms. Provided the sampling points remain consistent with respect to palm and management zone, those methods can be used to compare different fields or to monitor changes over time, within a plantation cycle, which is about 25 years.
Fig. 1 Typical management zones in two inter-rows of a mature oil palm plantation. The pattern is repeated throughout the plantation. Management zones are the ‘frond pile’ (FP), where pruned fronds are placed, the ‘weeded circle’ (WC), which is kept bare to facilitate harvesting, the ‘harvest path’ (HP), upon which fruit is removed from the plantation and workers gain access for other management practices, and the remaining area, here called the ‘avenue’ (AV). In some plantations, pruned fronds are also placed perpendicular to the main frond pile, in the ‘frond tip’ (FT) zone. ‘Rows’ are the lines of palms parallel to the harvest paths. Dashed white lines show equilateral triangular spacing of palms
Plant Soil (2015) 394:421–429
However, they have several disadvantages. Firstly, samples taken in any particular management zone do not tell us anything about processes in other zones, which may be important for the palm. For example, taking samples from the weeded circle and frond pile does not give any information about soil properties in the ‘avenue’ area (Fig. 1), which comprises most of the plantation and is often where fertilisers have been placed. Secondly, soil properties might be expected to vary within the zones, so the position within the zone is important, but is generally not considered or recorded. In cases where quantities per hectare are being calculated, all zones must be sampled representatively and their relative areas measured. Thirdly, important patterns of variation, such as those induced by the distribution of fertiliser, do not necessarily correspond with visible zones. Finally, sampling by visible zones is not suitable for monitoring changes that span more than one crop cycle, as the position of palms and zones changes when palms are replanted. Therefore, results from one crop cycle cannot be compared to results from the previous one. To assess sustainability, monitoring of soil properties should be carried out over more than one crop cycle. In view of these difficulties for monitoring soil properties in oil palm plantations over time, especially over more than one crop cycle, we have been assessing methods for obtaining composite soil samples that take into account tree-scale variability. A tree-unit grid is the best available method for obtaining a sample that accounts for tree-scale variability (Nelson et al. 2014b). However, setting up such a grid is time-consuming, so it is unlikely to be adopted as a routine monitoring procedure by plantation managers. We therefore devised and assessed, and present here, a transect-based method that is much simpler to carry out than the grid-based method. The transect method provides similar coverage of treescale variability to the grid-based method, but traverses a larger area, and is suitable for monitoring changes over more than one crop cycle.
Methods Geometrical approach and testing We designed a sampling approach starting with the premise that it will be most economically and logistically feasible if sampling can be carried out by no more than two people and does not require them to make any
Author's personal copy Plant Soil (2015) 394:421–429
calculations. To meet that specification we assessed linear transects that start at one palm stem and end at another palm stem, visible from the first. Sampling transects must cross an even number of rows so that equal numbers of harvest paths and frond piles are crossed. The angle of possible transects relative to the rows is 30° or 90° for a 2-row transect and approaches 60° as the number of rows crossed increases (Fig. 2). The length of the transects (L) is given by qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi L ¼ ðsin 60 Þ2 þ ðn þ xÞ2 ð1Þ where n is the number of rows crossed, x equals negative 0.5 for transects >60° and positive 0.5 for transects 60°’ transect crosses 6 tree units. When each of these portions of the transect are redrawn onto a single tree unit, the result is 5 equally spaced parallel lines (5 rather than 6 because the first and last portions merge into one line through the centre of the palm). The off-set or distance between the redrawn lines equals 1/n for transects >60° and 1/(n +1) for transects
