^{1}

^{*}

Several reports have indicated fertilizer application is not required for increased gum yield in ^{2}) and standard error (SE) were respectively 0.99 and 0.005 for nitrogen,0.79 and 0.024 for calcium, and 0.53 and 0.036 for CEC. Ninety-nine percent, 79%, and 53% of the variation in yield were explained by nitrogen, calcium and CEC, respectively. Under savanna woodland conditions, only nitrogen was positively correlated with yield (r = 0.65), and R^{2 }and SE were respectively 0.70 and 0.014, with 70% of the variation in yield explained by nitrogen. Regression equations were subsequently developed to predict gum yield. Gum yield was correlated with soil chemical properties, and could be predicted based on nitrogen, calcium, and CEC values.

Yield is a function of soil properties, and site index determines productivity. However, a poor site may be highly productive in terms of yield, but it is dependent on the tree species supported on the site, and the interactions between trees and soil. Soil properties, in part, are responsible for plant growth and yield, in conjunction with other climatic factors. Soil chemical and mineral properties affect yield,

This study was conducted at Gummi Forest Reserve in Zamfara State, Nigeria. The area is located between Latitudes 11° 30’ and 25° 15’ North, and Longitudes 40° 50’ and 70° 15’ East. The forest reserve is 300 ha of woodlands within the Gummi Local Government Area of Zamfara State. It is owned and managed for

The region experiences a long dry season from October to May, and a short rainy season from June to September. Two major wind currents coincide with the seasons; the cold easterly occurs during the dry season, and the southwesterly winds during the rainy season. The dry season is characterized by a cold dry period (known as Harmattan) from roughly November to January, followed by a hot dry period from February to April (

The state is located within Northern Guinea Savanna. Tall grasses, shrubs, and short scattered woodland trees characterize the vegetation. Common tree species include

A multistage sampling method was applied to compare

The 900 ha plantation was sectioned into 20 blocks of 45 ha in size. Each block was further divided into 100 x 100 m plots. The plots were finally subdivided into 20 x 20 m sub-plots, resulting in 25 sub-plots per ha. One randomly selected sub-plot from a randomly selected plot within each block, with a total of 10 sub-plots was selected for yield assessment.

The 300 ha natural woodland was sectioned into 10 blocks of 30 ha in size. Each block was further divided into 100 x 100 m plots. The plots were finally subdivided into 50 x 50 m sub-plots. Ten sub-plots were randomly selected from a plot randomly selected within each block for yield data collection. From the randomly selected 10 sub-plots (plots for yield assessment) in the plantation, six sub-plots were randomly chosen for soil sample collection. Six sub-plots were equally chosen from the 10 sub-plots (plots for yield assessment) in the savanna woodland for soil sample collection. In the plantation and savanna woodland, six soil pits were established within the same sub-plots selected for yield assessment.

The yield data collected included the number of trees per sample plot, and gum yield per tree per plot. All standing living trees were recorded. The plantation age at the time of data collection was seven years with a 4 x 4 m space between trees. Based on this spacing, 625 standing trees per ha, or 25 trees per sample plot were expected in the plantation.

Field personnel tapped trees for gum on the same day using short cutlasses, which is a process of cutting holes in the bark to release the exudate. Field personnel were provided a pre-orientation to ensure each individual applied the same tapping skills. Exudates were allowed to dry on the trees, and were hard enough for collection following five weeks. Exudates were weighed (in grams) and yield was recorded on a per tree basis. Code numbers were assigned to each tree in a sampled plot to tally gum yield quantity and respective soil pit as follows:

YA1-25 T = yield quantity tree numbers 1-25, in plot A, pit T

YB1-25 M = yield quantity of tree numbers 1-25, in plot B, pit M

Data were recorded accordingly.

Bulk soil samples were collected at depths of 1-45 cm.

The following soil properties were analyzed: Acidity (pH), Electrical Conductivity (EC), Nitrogen (N), Phosphorus (P), Potassium (K), Sodium (Na), Calcium (Ca), Magnesium (Mg), Hydrogen (H), Aluminum (Al), Cation Exchange Capacity (CEC), Organic Carbon (OC), Sand, Silt, and Clay.

The laboratory analyses were conducted at the General Science Laboratory, Usmanu Danfodiyo University Sokoto, Nigeria. The soil samples were air-dried, gently crushed in a mortar and pestle, and passed through a 2 mm sieve. The laboratory experiments performed on fine fractions (< 2 mm) are described below. Separates with sizes > 2 mm were generally not encountered in view of the fine texture of the soils in the study area.

Particle size analysis was conducted by the hydrometer method (

Correlation and simple linear regression were employed for statistical analyses using the Statistical Package for Social Scientists (SPSS). The regression equation was determined as follows (

where _{0} is the regression constant, _{1} is the regression slope, _{ij} is the error.

Maximum gum yield per tree for the ten plots was 115.72 g; the lowest yield figure per tree was 72.55 g, and the mean yield per tree from all samples was 85.09 g. Nitrogen and CEC exhibited a significant (

The relationship between gum yield and nitrogen under plantation conditions was further explained by regression analysis results (^{2} = 0.99) represents a measure of the degree of reliability in predicting gum yield from nitrogen. Increased gum yield was related to decreased calcium levels in the plantation (

Calcium accounted for 79% of the varia-tion in gum yield. CEC in plantation soil increased as gum yield increased (

Sandy soils with low organic matter (OM) have a corresponding low CEC, but clay soils with high OM, have a much greater capacity to hold cations. The relationship between OM and cations under plantation conditions indicated that with a higher clay value (r = 0.44,

The savanna woodland showed a significant positive correlation between N and gum yield (r = 0.65, ^{2} = 0.07) represents a measure of the degree of reliability in predicting gum yield from N. The low clay content r-value in the natural savanna woodland resulted in the absence of a correlation between CEC and yield. This N observation can be used to predict gum yield under natural stand conditions using

Plant population dynamics are important factors to consider when assessing organic matter deposition. The species composition comprising different plant populations and the interplay of plant communities will have an affect on the amount and composition of organic matter. Soil litter amounts under plantation conditions were higher than under the natural woodlands of

The dry land species

Result of correlation analysis between gum yield and soil properties under plantation. (*): significant correlation coefficient at α = 0.05. Maximum gum yield value was 115.72 g; minimum yield was 72.55 g, while the mean yield was 85.09 g.

Soil properties | Max | Min | Mean | Correlation Coefficient (r) |
---|---|---|---|---|

pH (1:1) H2O | 7.40 | 6.00 | 6.20 | 0.47 |

EC (mS m^{-1}) |
1738.40 | 1340.80 | 1533.20 | 0.47 |

N (Cmol kg^{-1}) |
2.36 | 0.30 | 1.45 | 0.72* |

P (Cmol kg^{-1}) |
2.84 | 2.51 | 2.63 | 0.11 |

K (Cmol kg^{-1}) |
2.45 | 1.75 | 2.11 | 0.47 |

Na (Cmol kg^{-1}) |
0.85 | 0.64 | 0.68 | 0.63 |

Ca(Cmol kg^{-1}) |
7.30 | 3.20 | 3.95 | -0.73* |

Mg(Cmol kg^{-1}) |
7.40 | 2.53 | 4.30 | 0.62 |

H (Cmol kg^{-1}) |
3.72 | 2.35 | 2.75 | 0.03 |

Al (Cmol kg^{-1}) |
1.84 | 1.20 | 1.45 | 0.34 |

CEC (Cmol kg^{-1}) |
16.10 | 10.20 | 14.30 | 0.67* |

OC (g kg^{-1}) |
5.90 | 4.90 | 4.96 | 0.09 |

Sand (g kg^{-1}) |
540.40 | 305.20 | 439.15 | 0.37 |

Silt (g kg^{-1}) |
420.45 | 200.10 | 300.60 | 0.04 |

Clay (g kg^{-1}) |
368.80 | 114.60 | 256.80 | 0.44 |

Results of simple linear regression analysis of gum yield as influenced by Nitrogen, Calcium and CEC in plantations. The following regression equation was obtained for the prediction of gum yield from Nitrogen, Calcium and CEC under plantation: Log (g) = + Log (Cmol kg^{-1}), where is the yield as influenced by , A is the regression constant, is the regression slope, is any of the significantly correlated soil properties (N, Ca or CEC). (**): highly significant

Ni =10 | B | Standard error of B | t-value | P-level Nitrogen |
---|---|---|---|---|

Intercept | 3.360130 | 0.0044423 | 759.7802 | 0.0001** |

LogNt (P) | -0.751777 | 0.023291 | 32.2782 | 0.0001 |

Calcium Intercept | 3.369138 | 0.02727 | 123.7549 | 0.0001** |

LogCa (P) | -0.254914 | 0.046416 | -5.4920 | 0.000479 |

CEC Intercept | 3.467869 | 0.081027 | 42.7988 | 0.0001** |

LogCEC (P) | 0.230209 | 0.076174 | 3.0221 | 0.016505 |

Result of correlation analysis between gum yield and soil properties under natural forests. Maximum gum yield was 125.28 g, minimum yield was 62.95 g, while the mean yield was 87.67 g. (*): significant correlation coefficient at α = 0.05.

Soil properties | Max | Min | Mean | CorrelationCoefficient (r) |
---|---|---|---|---|

pH (1:1) H_{2}O |
7.05 | 6.45 | 6.70 | 0.05 |

EC (Ms m^{-1}) |
812.00 | 684.10 | 791.00 | 0.09 |

N (Cmol kg^{-1}) |
1.60 | 0.49 | 0.73 | 0.65* |

P (Cmol kg^{-1}) |
2.60 | 2.50 | 2.54 | 0.32 |

K (Cmol kg^{-1}) |
0.95 | 0.49 | 0.91 | 0.19 |

Na (Cmol kg^{-1}) |
1.64 | 1.08 | 1.44 | 0.32 |

Ca (Cmol kg^{-1}) |
4.12 | 1.85 | 2.05 | 0.06 |

Mg (Cmol kg^{-1}) |
3.81 | 0.94 | 1.17 | 0.05 |

H (Cmol kg^{-1}) |
3.60 | 2.10 | 2.67 | 0.36 |

Al (Cmol kg^{-1}) |
0.70 | 0.14 | 0.28 | 0.05 |

CEC (Cmol kg^{-1}) |
12.30 | 7.11 | 10.00 | 0.03 |

OC (g kg^{-1}) |
4.82 | 3.51 | 3.80 | 0.17 |

Sand (g kg^{-1}) |
500.10 | 312.40 | 441.70 | 0.43 |

Silt (g kg^{-1}) |
482.40 | 211.30 | 334.30 | 0.03 |

Clay (g kg^{-1}) |
364.60 | 185.20 | 215.00 | 0.02 |

Result of simple linear regression analysis of gum yield as influenced by Nitrogen in natural forest. The following regression equation was obtained for the prediction of gum yield from nitrogen under the natural stand: Log Y(g)= 3.954 + 0.248 LogNt(Cmol kg^{-1}) [R^{2} = 0.70, SE =0.014, n=10]. (**): highly significant at α = 0.01; Ni: number of sample; Nt: nitrogen; N: natural stands.

Ni =10 | B | Standard error of B | P-level | |
---|---|---|---|---|

Intercept | 3.953590 | 0.19251 | 205.3705 | 0.0001** |

LogNt(N) | 0.247526 | 0.057572 | -4.2994 | 0.0062618 |