Journal of Resources and Ecology >
Sampling Size Requirements to Delineate Spatial Variability of Soil Properties for Site-Specific Nutrient Management in Rubber Tree Plantations
First author: LIN Qinghuo, E-mail: qinghuol@163.com
Received date: 2018-11-07
Accepted date: 2019-01-30
Online published: 2019-07-30
Supported by
Foundation: National Key Research and Development Program of China (2018YFD0201100)
Foundation for China Agriculture Research System (CARS-34)
Fundamental Scientific Research Funds for Chinese Academy of Tropical Agricultural Sciences (1630022017007).
Copyright
Site-specific nutrient management is an important strategy to promote sustainable production of rubber trees in order to obtain high yields of natural rubber. Making effective nutrient management decisions for rubber trees depend on knowing the spatial variations of soil fertility properties in advance. In this study the Kriging geostatistical method was used to examine the spatial variability of soil total nitrogen (TN), organic matter (OM), available phosphorus (AP) and available potassium (AK) in a typical hilly rubber tree plantation in Hainan, China. The spatial variability of the soils was small for the TN and OM and had medium variability for the AP and AK variables. Anisotropic semivariograms of all soil properties revealed that elevation and building contour ledge can profoundly affect the spatial variability of soil properties in the plantation, except for the AK variable. Soil samples had to be collected in alignment with the direction of elevation and perpendicular to the direction of building contour ledges, which was needed to obtain more reliable information within the study area in the rubber tree plantation. In formulating a sample scheme for AK, the distribution features of the soil’s parent material should be considered as the influence factor in the study field. The Kriging method used to guide the soil sampling for spatial variability dertermination of soil properties was about 2-5 times more efficient than the classic statistical method.
LIN Qinghuo , LI Hong , LI Baoguo , LUO Wei , LIN Zhaomu , CHA Zhengzao , GUO Pengtao . Sampling Size Requirements to Delineate Spatial Variability of Soil Properties for Site-Specific Nutrient Management in Rubber Tree Plantations[J]. Journal of Resources and Ecology, 2019 , 10(4) : 441 -450 . DOI: 10.5814/j.issn.1674-764X.2019.04.011
Fig. 1 Sampling sites (100 sites) in the rubber tree plantation (4200 m2) |
Fig. 2 Sampling points of different sampling strategies |
Table 1 Statistical parameters for selected chemical properties of soil in a rubber plantation (100 samples in total) |
Soil properties | Mean | Range | SD | CV(%) | Skew | Kurt | PK-S* |
---|---|---|---|---|---|---|---|
TN(g kg-1) | 0.79 | 0.48-1.13 | 0.12 | 14.64 | 0.35 | 0.58 | 0.43 |
OM(g kg-1) | 14.29 | 8.44-19.64 | 1.99 | 13.95 | 0.20 | 0.93 | 0.67 |
AP(mg kg-1) | 5.20 | 2.52-9.46 | 1.49 | 28.68 | 0.58 | -0.08 | 0.54 |
AK(mg kg-1) | 34.68 | 20.01-62.39 | 10.67 | 30.77 | 0.93 | 0.17 | 0.10 |
Table 2 Classes of soil properties in a rubber plantation on Hainan Island (Lu, 1983) |
Class | TN(g kg-1) | OM(g kg-1) | AP(mg kg-1) | AK(mg kg-1) |
---|---|---|---|---|
Abundant* | >1.4 | >25 | >8 | >60 |
Normal | 0.8-1.4 | 20-25 | 5-8 | 40-60 |
Lack | <0.8 | <20 | <5 | <40 |
Note: * Abundant indicates high yield latex will be attained, with no additional application of fertilizers; Normal indicates median yield late will be attained, with a small amount of fertilizers needed; Lack indicates low yield latex will be attained, with the application of fertilizers having significant effects. |
Table 3 Semivariogram model of soil properties and their parameter in a rubber plantation |
Variable | Best model | A1 (m) | A2 (m) | κ | φ (°) | C0 | C1 | C0/(C0+C1) | Cross-validation indices | ||
---|---|---|---|---|---|---|---|---|---|---|---|
ME | RMSE | RMSSE | |||||||||
TN | Spherical | 52.93 | 16.93 | 3.13 | 20.5 | 4.18E-03 | 0.010 | 0.29 | 2.84E-03 | 0.087 | 0.975 |
OM | Spherical | 46.19 | 16.57 | 2.79 | 8.8 | 1.579 | 2.694 | 0.37 | 2.41E-02 | 1.737 | 1.06 |
AP | Spherical | 62.23 | 36.10 | 1.72 | 44.6 | 1.655 | 0.730 | 0.69 | 8.20E-04 | 1.439 | 1.028 |
AK | Spherical | 52.86 | 23.98 | 2.20 | 286.2 | 72.663 | 47.192 | 0.61 | -3.47E-02 | 9.528 | 0.985 |
Note: A1, the range parameter for the major axis of soil properties; A2, the range parameter for the minor axis of soil properties; κ, the anisotropic ratio, A1/A2; φ, azimuth angle of the major axis, measured in degrees clockwise from the positive north direction; ME, mean error, should be near zero for a good prediction; RMSE, root-mean-square error, should be small for a good prediction; RMSSE, root-mean-square standardized error, should be close to 1 for a good prediction. |
Fig. 3 Anisotropic semivariogram models for the selected soil properties in a rubber plantation. Chemical properties of soil included total nitrogen (TN); organic matter (OM); available phosphorous (AP); and available potassium (AK). |
Fig. 4 Anisotropic semivariogram models for the selected soil properties in a rubber plantation. Soil chemical properties included total nitrogen (TN); organic matter (OM); available phosphorous (AP); and available potassium (AK). |
Table 4 Estimated sample sizes (numbers) to obtain mean values within ±5% and ±10% of classic and Kriging methods |
Variable | ±5%* | ±10% | ||||
---|---|---|---|---|---|---|
SD | Classic | Kriging | SD | Classic | Kriging | |
TN | 0.04 | 27 | 9 | 0.08 | 10 | 2 |
OM | 0.72 | 25 | 9 | 1.44 | 10 | 2 |
AP | 0.26 | 57 | 29 | 0.52 | 26 | 8 |
AK | 1.73 | 60 | 32 | 3.47 | 29 | 9 |
Note: * Within the certain error of the true population means. |
Fig. 5 Kriging and classic statistical standard errors in relation to sample sizes for estimating chemical properties of soil at a rubber plantation. Soil chemical properties included: (a) TN, total nitrogen; (b) OM, organic matter; (c) AP, available phosphorous; (d) AK, available potassium. |
Table 5 Test results of soil properties for various sampling strategies |
Samplestrategy * | Sample number | TN | OM | AP | AK | ||||
---|---|---|---|---|---|---|---|---|---|
RMSE | G | RMSE | G | RMSE | G | RMSE | G | ||
A | 50 | 0.07 | 61.09 | 1.27 | 58.78 | 1.08 | 46.71 | 6.75 | 59.58 |
B | 50 | 0.07 | 64.61 | 1.19 | 63.98 | 1.03 | 52.30 | 7.57 | 49.19 |
C | 40 | 0.08 | 47.51 | 1.47 | 44.80 | 1.18 | 36.47 | 7.98 | 43.57 |
D | 40 | 0.08 | 48.37 | 1.44 | 47.09 | 1.21 | 33.58 | 9.30 | 23.27 |
* A: sampling spacing of 6 m × 14 m, sampling number of 50; |
[1] |
|
[2] |
|
[3] |
|
[4] |
|
[5] |
|
[6] |
Da Silva B M C G,
|
[7] |
|
[8] |
|
[9] |
|
[10] |
|
[11] |
FAO.1998. World reference base for soil resources. World Soil Resources Report No. 84, FAO, Rome.
|
[12] |
|
[13] |
|
[14] |
|
[15] |
|
[16] |
|
[17] |
|
[18] |
Irsg.2013. Rubber Statistical Bulletin. International rubber study group,Singapore, 55.
|
[19] |
|
[20] |
|
[21] |
|
[22] |
|
[23] |
|
[24] |
|
[25] |
|
[26] |
|
[27] |
|
[28] |
|
[29] |
|
[30] |
|
[31] |
|
[32] |
|
[33] |
|
[34] |
|
[35] |
|
[36] |
|
[37] |
|
[38] |
|
/
〈 |
|
〉 |