Pa ge 1 Pa ge 1 American Journal of Geospatial Technology (AJGT) Forms and Distribution of Phosphorus along A Toposequence at the University of Benin, Nigeria Godspower Oke Omokaro1*, Kolawole Agoro Abiola2, Anthonia Bakare2, Edmond Osemwengie Airueghian2, Ikioukenigha Michael3 Volume 3 Issue 1, Year 2024 ISSN: 2833-8006 (Online) DOI: https://doi.org/10.54536/ajgt.v3i1.2591 https://journals.e-palli.com/home/index.php/ajgt Article Information ABSTRACT Received: February 27, 2024 Accepted: March 30, 2024 Published: April 02, 2024 The experiment was conducted at University of Benin, Nigeria, involving soil samples from four toposequence sites (Crest, Middle, Lower, and Bottom) at different depths (0-15 cm, 15-30 cm, and 30-45 cm). A total of 36 samples were collected and analyzed for various pa- rameters using standard procedures. The parameters included particle size distribution, pH, total organic carbon (TOC), total nitrogen (N), available phosphorus (P), Carbon (C), Hy- drogen (H), Magnesium (Mg), Potassium (K), Sodium (Na), ECEC, and Aluminum (Al). Re- sults indicated that pH was lowest in the Crest area (pH 4.10 at 30-45 cm depth) and highest in the Bottom area (pH 5.80 at 0-15 cm to 30-45 cm depth). Different soil properties showed varying highest values across the toposequence depths. These properties included Total or- ganic C, Total N, Available P, Ca, K, Mg, H, Na, ECEC, sand content, and the various forms of phosphorus. The correlation table revealed significant positive and negative relationships between different forms of phosphorus and various soil physical and chemical properties. The experiment demonstrated distinct variations in soil properties along the toposequence sites and depths. The findings contribute to a better understanding of soil characteristics in the studied region, aiding in informed agricultural practices and land management decisions. Keywords Slope Gradient, Soil Variability, Soil Nutrient, Soil Properties, Toposequence 1 Institute of Ecology, Faculty of Environmental Engineering, Peoples Friendship University of Russia named after Patrice Lumumba, Moscow, Russia 2 Department of Soil Science and Land Management, Faculty of Agriculture, University of Benin, Nigeria 3 Department of Geography and Regional Planning, Igbinedion University, Okada, Mission Road, Edo State, Nigeria * Corresponding author’s e-mail: omokaro.kelly@gmail.com INTRODUCTION One of the naturally occurring soil forming factors that affect soil properties and controlling soil forming factors that affect soil properties and control soil erosion processes through the redistribution of soil particles and soil organic matter is topography (Ziadat & Taimeh, 2013). Slope gradient is one of the important topographic factors that influence the process of drainage; runoff and soil erosion thereby affects physicochemical properties (Farmanullah, 2013). Soil loss would normally be expected to increase with the increase in slope gradient because of the respective increase in velocity of surface runoff and decrease in infiltration rate (Zhang & Hosoyamada, 1996). Soils vary in their characteristics primarily because of topography (Amhakhian & Achimugu, 2011) which modifies soil water relationships and large extent influences on rainfall, drainage, soil erosion, textural composition and other soil properties that affect plant growth within a field (Atofarati et al., 2012). Topographic variability associated with crop production is an integrated reflection on soil properties and factors affecting agricultural productivity (Dinaburga et al., 2010). The topography of agricultural fields can influence soil physicochemical properties (soil depth, texture, and mineral contents), biomass production, incoming solar radiation, and precipitation and affect crop production. As increased topography/elevation significantly increased soil moisture, precipitation, soil organic matter and labile carbon, whereas bulk density, pH and soil temperature were significantly lower at the higher elevations (Griffiths et al., 2009). The scale of soil variation depends on the specific soil characteristic that is being studied. Some soil properties, such as texture, pH, and porosity, are considered to be rather spatially static, while other features such as soil nitrogen N, soil available forms of P and K, and biological properties are highly spatially variable (Piotrowska & Długosz 2012). Soil spatial variability can occur across multiple spatial scales, ranging from the micro level (millimeters) to the plot level (meters) and up to the landscape level (kilometers) (Cobo et al., 2010). The aim of the study was to determine the physical and chemical properties of soils found on Toposequence along University of Benin. The specific objectives were to determine the: physical and chemical properties of the soils and Phosphorus forms and distribution in the soil of the study area. MATERIALS AND METHODS This study will be carried out at the Ugbowo campus of The University of Benin, Benin City in Edo state, Nigeria. The area lies between latitude 6º23ʹ 37ʺ and 6º24ʹ 26ʺ North and longitude 5° 36ʹ 25ʺ and 5° 38ʹ 09ʺ East. It is a segment of the coastal plain sand, commonly called acid sand of Nigeria. The natural climate is humid tropics. The natural vegetation is rain forest. The rainy season is bimodal with peak in July and September. Average rainfall is between 1500-2500mm annually. Mean maximum and minimum temperature are 31 and 22oC. The soil has been mapped as ultisol with Rhodicpaleudult as the modal profile (Ogeh and Ogwurike 2006). Pa ge 2 https://journals.e-palli.com/home/index.php/ajgt Am. J. Geo Spat. Technol. 3(1) 1-8, 2024 Geography of Study Site Point 1: latitude 6.3981630 and longitude 5.6313240 Point 2: latitude 6.3986950 and longitude 5.6352700 Point 3: latitude 6.4021850 and longitude 5.6352700 Point 4: latitude 6.4048320 and longitude 5.6384720 Sample Collection Soil samples were collected from toposequence site at capitol in the University of Benin, Benin City, Edo State. Three different sites were selected for each toposequence and samples were collected in each selected site at different depths (0-15 cm, 15-30 cm and 30-45 cm) using an auger. Soil samples from same depth were bulked to make a composite sample. One composite soil sample was then prepared from the three sub samples for each soil depth. The composite soil samples were then air-dried, mixed well and passed through a 2 mm sieve for the analysis of selected soil physical and chemical properties. Soil Laboratory Analysis The particle size distribution of the soil was assessed using the hydrometer method by Gee and Or (2002). The clay content was determined after 2 hours using the method described by Ibitoye (2008). The pH level of the air-dried soil was measured using a glass electrode pH meter with a 1:1 ratio, following the procedure outlined by Mclean (1982). Prior to the pH measurement, calibration of the pH meter was performed using buffer pH 4.0 and 9.0. The electrode was immersed in the liquid portion of the mixture to obtain the reading, which was then recorded. Soil organic carbon was determined by the Walkley-Black method procedure by wet oxidation using chromic acid digestion (Nelson & Sommer, 1996). Exchangeable K, Ca Na, and Mg were extracted with a 1 M NH4OAc, pH 7 solution. Thereafter, K was analyzed with a flame photometer and Ca and Mg were determined with an atomic absorption spectrophotometer (Okelabo et al., 2002). Exchangeable acidity procedures and results were reported in Cmolkg-1 according to the method described by Black (1965). Total N was determined using micro- Kjeldahl digestion and distillation techniques (Bremner, 1996); Available P was determined by Bray-1 extraction followed by molybdenum blue colorimetry (Frank et al., 1998), Total phosphorus in the soils was determined by perchloric acid digestion and Inorganic P was fractionated by method. Determination of Phosphorus as Aluminum Phosphate (Al-P) One gram of air-dried soil (2 mm sieve) was weighed out placed in 250 ml plastic container. 35 ml of I N NH4Cl was added, and the mixture shaken on a mechanical shaker for 30 minutes. To remove water soluble and loosely bound P and exchangeable Ca, the suspension was filtered (Whatman filter paper No. 42) and the filtrate discarded, leaving the soil residues. To the residues in the plastic bottle were added 35 ml of 0.5 N NH4F, covered tightly and shaken for 1hr on a mechanical shaker. The mixture was filtered, and the clear filtrates were used for Al-P determination. The soils residues in the plastic bottle were reserved for Fe-P extraction. For Al-P determination, aliquots (10 ml) of the extract were pipetted out into 50 ml volumetric flask and 15 ml boric acid added (0.8 M). Blue colour was developed using 4 ml of reagent B solution and made up to mark with distilled water. Absorbance readings were recorded at 660 nm wavelength using the UV/VIS Unicam spectro- colorimeter Phosphorus Determination as Iron Phosphate (Fe- P) The soil residue saved after Al-P extraction was washed twice with 25 ml saturated NaCl and filtered each time and the filtrate discarded. Thereafter, 35 ml 0.1 N NaOH was added to the plastic bottles, covered tightly and shaken for 17 hours. The suspensions were filtered, and clear extract collected for Fe-P determination. The soil residues in the plastic bottle were reserved for Ca- P extraction. For Fe –P determination, 5 ml aliquot of the clear solution was pipetted into 50 ml volumetric flask, 4 ml of reagent B was added for the blue colour development and made up to mark with distilled water. Absorbance readings were recorded at 660 nm wavelength using a UV/VIS Unicam spectro-colorimeter. Phophorus Determination as Calcium Phosphate (Ca-P) The soil residues saved after the Fe-P extraction was washed twice with 25 ml saturated NaCl solution (10%), filtered each time and discarded, 35 ml of 0.5 N H2SO4 was added to the soil in the plastic bottles, covered tightly and shaken on the mechanical shaker for I hour. The suspensions were filtered, and clear solution obtained. 30 ml aliquot of the clear solution was pipetted into 50 ml of volumetric flask, 4 ml of the reagent B was added for colour development, and the volume made up to mark with distilled water. Absorbance readings were recorded at 660 nm wavelength using a UV/VIS Unicam spectro- colorimete. Determination of Total Phosphorus and Occluded Phosphorus One gram of finely ground (0.5 mm scene) soil was weighed out each into 250 ml conical flasks and 25 ml of HNO3, 4 ml of perchloric acid and 2 ml of H2SO4 added respectively and mixed thoroughly. It was digested on a heater inside a fume cupboard until the colour due to organic matter disappeared. Then additional 20 minutes heating was allowed to dry completely. At this stage heavily white fumes due to HNO3, HClO4 and H2SO4 appeared, and the insoluble materials looked like white sand. The flask was shaken occasionally during digestion. The digest was allowed to cool, and 70 ml of distilled water was added to the digest and heated to warm. The suspension was filtered into 250 ml volumetric flask and made up to mark with distilled water. Then, 10 ml aliquot was pipetted into 50 ml volumetric flask, 4 ml of the Pa ge 3 https://journals.e-palli.com/home/index.php/ajgt Am. J. Geo Spat. Technol. 3(1) 1-8, 2024 reagent B was added and made up to mark with distilled water. The absorbance reading was recorded at 660 nm wavelength using a UV/VIS Unicam spectro-colorimeter. The occluded phosphorus (inactive P) was calculated as the difference between the total phosphorus and the active phosphorus (Al-P, Fe-P, Ca-P). Statistical Analysis Plant parameters measured were subjected to analysis of Variance (ANOVA) using GENSTAT 8th Edition while Duncan’s New Multiple Range Test was used to separate the means at 5% level of probability. RESULTS AND DISCUSSION Effect of Toposequence on Soil Properties Table 1 displays the physical and chemical properties of soil across different toposequence depths at the University of Benin, Benin City. The pH values were acidic in all Crest depths (0-15 cm: 4.60, 15-30 cm: 4.90, 30-45 cm: 4.10) and Middle depths, remaining consistently acidic. Lower depths showed a strong acidic trend (pH 5.5 to 5.0), while Bottom depths were moderately acidic (pH 5.80). Total nitrogen (N) varied with depths, ranging from low (Crest 0-15 cm: 1.0) to moderately low (Crest 30-45 cm: 1.30). Bottom 30-45 cm had the highest N (1.95 g/ kg), and Lower 30-45 cm had the lowest (0.90 g/kg). Total organic carbon (C) increased with soil depths across all toposequence. Crest 30-45 cm had the highest C (17.00 g/kg - High), while Middle 30-45 cm had the lowest (7.10 g/kg - moderate), and the findings align with Chude et al., (2011). Cation exchange capacity (CEC) varied among toposequence and decreased with depth. Middle had the highest CEC values at various depths (11.04 cmolkg-1, 11.56 cmolkg-1), indicative of soil productivity and useful for phosphorus, potassium, and magnesium recommendations. High CEC values relate to organic matter and clay content, offering more negative electrostatic sites for positive cation attraction. These results support Vogelmann et al. (2010) findings on CEC correlation with organic matter and pH levels. Table 1: Physical and Chemical Properties of Soils under various Toposequence To po se q. D ep th (c m ) pH T O C T. N PO 4 H A l K C a N a M g E C E C Sa nd Si lt C la y T C ⭢g/kg⭠ mg/kg ⭢ cmol/kg ⭠ ⭢ g/kg ⭠ C re st 0- 15 4. 60 15 .4 0 1. 9 3. 91 0. 50 0. 00 0. 08 0. 96 0. 10 0. 65 2. 29 67 7. 20 80 .0 0 24 2. 80 SL 15 -3 0 4. 90 9. 50 1. 1 1. 35 0. 60 0. 00 0. 21 0. 80 0. 10 0. 65 2. 36 80 1. 20 20 .0 0 17 8. 80 SL 30 -4 5 4. 10 17 .0 0 1. 95 2. 38 0. 40 0. 00 0. 04 0. 64 0. 10 0. 97 2. 15 79 1. 20 20 .0 0 18 8. 80 SL M id dl e 0- 15 4. 60 11 .2 0 1. 15 7. 67 0. 50 0. 00 0. 19 0. 96 0. 10 0. 97 2. 72 87 7. 20 30 .0 0 92 .8 0 SC L 15 -3 0 4. 30 9. 00 1. 08 2. 61 0. 50 0. 00 0. 04 0. 96 0. 10 0. 97 2. 57 79 7. 20 50 .0 0 15 2. 80 SC L 30 -4 5 4. 40 7. 10 0. 9 6. 61 0. 40 0. 00 0. 14 0. 80 0. 09 0. 97 2. 4 73 7. 20 30 .0 0 23 2. 80 SC L L ow er 0- 15 5. 50 11 .8 0 1. 2 42 .3 5 0. 40 0. 00 0. 10 8. 50 0. 10 1. 94 11 .0 4 76 8. 20 25 .0 0 20 6. 80 SC L 15 -3 0 5. 20 11 .0 0 1. 11 21 .2 3 0. 40 0. 00 0. 14 9. 30 0. 10 1. 62 11 .5 6 75 8. 20 75 .0 0 16 6. 80 SL 30 -4 5 5. 00 12 .8 0 1. 3 19 .9 4 0. 50 0. 00 0. 10 5. 61 0. 10 0. 65 6. 96 77 8. 20 69 .0 0 15 2. 80 SL B ot to m 0- 15 5. 80 8. 80 1 9. 25 0. 40 0. 00 0. 15 5. 29 0. 12 0. 65 6. 61 66 8. 20 55 .0 0 27 6. 80 SL 15 -3 0 5. 80 11 .8 0 1. 2 6. 06 0. 30 0. 00 0. 21 6. 09 0. 09 0. 97 7. 66 64 8. 20 35 .0 0 31 6. 80 LS Pa ge 4 https://journals.e-palli.com/home/index.php/ajgt Am. J. Geo Spat. Technol. 3(1) 1-8, 2024 30 -4 5 5. 80 10 .6 0 1. 16 5. 11 0. 40 0. 00 0. 16 4. 33 0. 11 0. 97 5. 97 66 8. 20 55 .0 0 27 6. 80 SL Where: TC = Textural Class, SL = Sandy loam, SCL = Sandy clay loam, LS = Loamy sand Table 1 further presents the results of soil separates from different toposequence locations. All land use types predominantly exhibited sandy texture (sand fraction: 877.20-801.20 g/kg, silt fraction: 80-20 g/kg, clay fraction: 318.80-92.80 g/kg). Sand content increased with depth, while clay content decreased. Soil texture remained similar across toposequence, as it is not significantly influenced by soil management or toposequence variation (Oyedele et al., 2009). Hydrogen (H) content ranged from 0.30-0.60 cmol/kg across the toposequence. The highest H value (0.60 cmol/kg) was at Crest, depth 15-30 cm, while the lowest (0.30 cmol/kg) was at Bottom, depth 15-30 cm. Hydrogen content was relatively consistent throughout the toposequence. Aluminium (Al) was not detected at any toposequence depth, indicating its absence throughout the area. Available phosphorus content varied across toposequence. Bottom had moderate (9.25 mg/kg), low (6.06 mg/kg), and low (5.11 mg/kg) P content. Lower had high (42.35 mg/ kg) and moderate (19.94 mg/kg) P content at 30-45 cm depth; Middle had low P content (7.61 mg/kg, 2.61 mg/kg, and 6.61 mg/kg). Crest exhibited low P content (3.91 mg/ kg) at 0-15 cm depth and very low P content (1.35 mg/kg, 2.38 mg/kg) at other depths (Chude et al., 2011). Higher phosphorus content in Lower may be due to its higher organic matter content, while lower phosphorus content in other areas could be attributed to fixation, abundant crop harvest, and erosion impacts (Yeshanch, 2015). Table 2: Phosphorus availability on different toposequence site Slope Depth (cm) Ca-P Al-P Fe-P Occluded-P Total-P ⭢ (mg/kg) ⭠ Crest 0-15 4.73 29.51 15.19 81.41 96.59 15-30 3.73 34.52 16.90 81.74 98.64 30-45 2.58 43.26 15.33 110.74 126.06 Middle 0-15 1.43 74.49 122.63 411.92 534.55 15-30 6.02 33.95 63.32 17.72 81.04 30-45 5.44 33.95 34.95 50.18 85.13 Lower 0-15 7.74 20.63 12.18 150.32 162.49 15-30 7.16 16.62 7.88 151.75 159.63 30-45 3.44 15.04 8.02 118.45 126.47 Bottom 0-15 7.45 73.20 8.45 307.94 316.39 15-30 6.45 16.90 9.17 170.92 180.09 30-45 2.44 9.88 12.61 96.68 109.28 Total Phosphorus As shown in Table 2, the total P content in all the profiles varied from 81.04 to 534.55μg g-1 with a mean of 173.03μg g-1. These values are comparable to the values reported by Adeleye and Omueti (2006) for some soils derived from basement complex parent material. Total P was generally highest in the lower slope and lowest at upper slope. Also, total P was highest in the topsoil of crest apart from that of depth (30-45). This trend could be due to accumulation of litters on the topsoil as also suggested by Osodeke and Osondu (2006). Ca –P varied from 9.88 to 74μg g-1 with a mean of 33.5μg g-1, Al – P varied from 1.43 to 7.74μg g-1 with a mean of 4.88μg g-1, Fe – P varied from 7.88 to 122.63μg g-1 with a mean value of 27.4μg g-1, Occluded – P varied from 17.72 to 411.92μg g-1 with a mean value of 145.8μg g-1. Ca – P had the least value among the active P forms while the Occluded – P had the highest value. This could probably be due to the acidity nature of the soils and the fact that it is the most soluble of the inorganic forms and tends to revert to the less soluble iron and aluminium phosphate in acid soils as suggested by Aghimien et al. (1988). Al – P is the least soluble of the inorganic P fraction and tends to accumulate at the expense of the more soluble Al – P and Ca P and this accounted for the relatively higher content of iron phosphate in the acidic soils (Agbimien et al., 1988). Mokwunye and Bationo (2002) also reported that the main sources of plant available P in soils are generally accepted as active P form rather than inactive P form. And secondary Phosphate as Al-P, Fe – P and Ca – P increase in content with strengthening of weathering and pedogenesis in the soil. Lambers et al. (2008) suggested that relationship exist between P content and forms in soils and stages of soil development. All soil P is in the primary mineral form (mainly Al- P and Ca – P mineral) Pa ge 5 https://journals.e-palli.com/home/index.php/ajgt Am. J. Geo Spat. Technol. 3(1) 1-8, 2024 at the beginning of soil development. With time, these inorganic P weather giving rise to P in various other forms mainly organic P (reservoir) occluded P and available P. Correlation Matrix Correlation coefficient for Crest Table 3 shows the correlation coefficient (r) between forms of P (Al-P, Ca-P, Fe-P, Occluded-P and Total-P) with some soil of physical and chemical properties of toposequence at crest. Iron forms of P were positively and significantly correlated with Clay (r=0.997), K (r=0.997) at (P<0.05) but negatively and significantly correlated with Sand and Silt (r=0.997), (r=0.997) at (P<0.05). Total form of P were negatively and significantly correlated with pH (r=0.998) at (P<0.05) having other forms of P (Al-P, Ca-P, Fe-P and Occluded-P) not positively nor negatively significantly correlated with some soil of physical and chemical properties of toposequence at the Crest Level. Table 3: Crest Correlation Coefficient CREST AL-P Ca-P Fe-P Occluded-P Total-P Av. P -0.897 -0.993 -0.368 -0.685 -0.722 Ca -0.668 0.578 0.796 -0.887 -0.861 Clay -0.155 0.040 0.997* -0.491 -0.445 EC -0.995 0.977 0.182 -0.967 -0.979 ECEC -0.514 0.412 0.897 -0.782 -0.748 H 0.155 -0.040 -0.997 0.491 0.445 K 0.001 -0.116 0.997* -0.350 -0.300 Mg 0.778 -0.845 0.562 0.508 0.533 Na -0.177 0.289 -0.966 0.179 0.127 O.M 0.464 -0.563 0.845 0.124 0.176 Sand 0.155 -0.040 -0.997* 0.491 0.445 Silt 0.155 -0.040 -0.997* 0.491 0.445 Total N 0.646 -0.913 -0.378 0.337 0.386 pH -0.933 0.885 0.435 -1.000 -0.998* Table 4: Middle Correlation Coefficient Middle AL-P Ca-P Fe-P Occluded-P Total-P Av. P 0.999* -0.986 0.963 0.992 0.998* Ca 0.311 -0.198 0.596 0.239 0.303 Clay 0.918 -0.958 0.744 0.945 0.921 EC -0.987 0.999 -0.885 -0.996 -0.998 ECEC 0.408 -0.299 0.676 0.339 0.401 H -0.500 0.396 -0.749 -0.434 -0.493 K -0.500 0.597 -0.200 -0.563 -0.507 Mg 0.692 -0.603 0.885 0.636 0.686 Na -0.500 0.597 -0.200 -0.563 -0.507 O.M -0.063 -0.053 0.376 0.011 -0.055 Sand ____ -0.116 -0.317 0.074 0.008 Silt -0.994 1.000* -0.908 0.999* -0.995 Total N -0.030 -0.686 -0.346 0.044 -0.023 pH 0.918 0.865 0.996 0.998 0.915 Correlation Coefficient for Middle Table 4 shows the correlation coefficient (r) between forms of P (Al-P, Ca-P, Fe-P, Occluded-P and Total-P) with some soil of physical and chemical properties of toposequence at middle. Al-P and Total-P were positively and significantly correlated with Available P (r=0.999) and (r=0.998) at (P<0.05) respectively; Ca-P and Occluded-P were positively and significantly correlated with Silt (r=1.000) and (r=0.999) at (P<0.05) respectively, but Fe-P were not positively nor negatively and significantly correlated with some physical and chemical properties of toposequence at Middle. Pa ge 6 https://journals.e-palli.com/home/index.php/ajgt Am. J. Geo Spat. Technol. 3(1) 1-8, 2024 Correlation Coefficient for Lower Table 5 shows the correlation coefficient (r) between forms of P (Al-P, Ca-P, Fe-P, Occluded-P and Total-P) with some soil of physical and chemical properties of toposequence at lower. Ca-P were negatively and significantly correlated with Total N (r =-0.986) at (P<0.05), Fe-P were positively and significantly correlated with Mg (r = 1.000) at (P<0.05). Occluded-P were positively and significantly correlated with H and Na (r = 0.999), (r = 0.999) at (P<0.05) respectively. Total-P were positively and significantly correlated with Ca and H (r = 0.997), (r = 0.997) at (P<0.05) respectively while Al-P were not positively nor negatively correlated with some soil of physical and chemical properties of toposequence at lower. Table 5: Lower Correlation Coefficient Lower AL-P Ca-P Fe-P Occluded-P Total-P Av. P 0.431 -0.198 0.683 0.354 -0.250 Ca 0.718 0.992 0.475 0.999 0.997* Clay -0.947 -0.950 -0.805 -0.887 -0.932 EC 0.936 0.536 0.999 0.392 0.491 ECEC 0.961 0.935 0.832 0.865 0.915 H 0.718 0.992 0.475 0.999* 0.997* K 0.547 -0.065 0.774 -0.226 -0.118 Mg 0.962 0.604 1.000* 0.467 0.561 Na 0.718 0.992 0.475 0.999* 0.997 O.M 0.979 0.904 0.872 0.824 0.881 Sand 0.987 0.886 0.892 0.800 0.861 Silt -0.243 0.388 -0.525 0.533 0.437 Total N 0.880 -0.986* 0.696 0.951 0.979 pH 0.991 0.871 0.906 0.994 0.843 Correlation Coefficient for Bottom Table 6 show Occluded-P and Total P were positively and significantly correlated with EC (r =0.998), (r = 0.999) at (P<0.05) respectively, while Al-P, Ca-P and Fe-P were not positively nor negatively and significantly correlated with some soil of physical and chemical properties of toposequence at bottom. Table 6: Bottom Correlation Coefficient Bottom AL-P Ca-P Fe-P Occluded-P Total-P Av. P 0.871 0.297 -0.271 0.721 0.729 Ca 0.912 0.945 -0.936 0.986 0.984 Clay 0.971 0.542 -0.519 0.880 0.885 EC 0.981 0.847 -0.832 0.998* 0.999* ECEC 0.287 0.866 -0.879 0.517 0.508 H 0.101 0.756 -0.774 0.346 0.336 K -0.194 0.532 -0.555 0.657 0.046 Mg -0.585 -0.982 0.987 -0.769 -0.762 Na 0.995 0.654 -0.634 0.938 0.942 O.M 0.217 -0.512 0.535 -0.034 -0.023 Sand -0.985 -0.598 0.576 -0.910 -0.915 Silt 0.585 0.982 -0.987 0.769 0.762 Total N 0.361 -0.377 0.402 0.117 1.000 pH 0.996 0.785 -0.768 0.987 0.988 DISCUSSION The study shows a very low positivity, negativity and significantly correlated with soil properties and that can be traceable to; Phosphorus been a major limiting factor in the growth and function of many forest, because P is a mineral nutrient derived from the weathering of rocks and drift where it deficiencies tend to become more acute as landscapes and soils age due to progressive Pa ge 7 https://journals.e-palli.com/home/index.php/ajgt Am. J. Geo Spat. Technol. 3(1) 1-8, 2024 leaching and sequestration (Vitousek, 2004). P deficiency is particularly widespread in rain-fed upland farming systems throughout the tropics and remains a major plant nutrient constraint. It is also attributed to some combination of soil parent material, soil age, topography, climate, and biological activity, high weathering intensity and loss by soil erosion (Fairhurst et al., 1999). Paulos (1996) indicated that the concentrations of active P forms were related to the degree of chemical weathering. Hence, all the forms of P can exist in all soils, but P bound by Al and Fe is abundant in highly weathered acidic soils and such is the case of the study area. CONCLUSION Phosphorus is an essential nutrient that is utilized for energy transport and growth by all organisms, where it is involved in many critical biological processes, such as energy metabolism, the synthesis of nucleic acid, and photosynthesis, and is highly needed in this study location as to help increase its availability for plant growth and metabolism. Acknowledgment The work is that of Bachelor of Agriculture project registered at the Department of Soil Science and Land Management, Faculty of Agriculture, University of Benin, Nigeria. Special thanks to Dr. Mrs. Anthonia Bakare for guidance. REFERENCES Adeleye, E. O. & Omueti, J. A. I. (2006). Profile distribution of phosphorus fractions in soils derived from basement complex rocks in southwestern Nigeria. Nigeria Journal Soil Science, 16(1), 52–58. Aghimien, E. A., Udo, E. J., & Ataga, O. (1988). Profile distribution of forms of Iron and Aluminium in the hydromorphic soils of southeastern Nigeria. Journal West African Science Association, 31(1), 57–70. Amhakhian, S. O., & Achimugu, S. (2011). Characteristics of soil on toposequence in Egume, Dekina Local Government Area of Kogi State. Production Agriculture and Technology, 7(2), 29–36. Atofarati, S. O., Ewulo, B. S., & Ojeniyi, S. O. (2012). Characterization and classification of soils on two toposequences at Ile-Oluji, Ondo State, Nigeria. International Journal of Agricultural Science, 2(7), 642–650. Black, C. A. (1965). Methods of Soil Analysis. American Society of Agronomy. p. 1572. Bouyoucos, C. J. (1951). Hydrometer method improved for making particle size analysis. Agronomy Journal, 43, 434–438. Bremner, J. M. (1996). Nitrogen-total. In: Sparks, D. L. (Ed.), Methods of soil analysis. Part 3. Chemical methods (2nd ed.). SSSA Book Series No. 5. Madison, WI: ASA and SSSA, pp. 1085–1121. Chude, V. O., Olayintola, S. O., Osho, A. O., & Dauda, C.K. (2011). Fertilizer use and management practices for crops in Nigeria (4th ed.). Federal Fertilizer department, Federal Ministry of Agriculture and Rural Development Abuja, pp. 42–43. Cobo, J. G., Dercon, G., Yekeye, T., Chapungu, L., Kadzere, C., Murwira, A., Delve, R., & Cadisch, G. (2010). Integration of mid-infrared spectroscopy and geostatistics in the assessment of soil spatial variability at the landscape level. Geoderma, 158, 398–411. Dinaburga, G., Lapins, D., & Kopmanis, J. (2010). Differences of soil agrochemical properties in connection with altitude in Winter Wheat. Engineering for Rural Development, 79–84. Fairhurst, T. R., Lefroy, R., Mutert, E., & Batijes, N. (1999). The importance, distribution, and causes of phosphorus deficiency as a constraint to crop production in the tropics. Agroforestry Forum, 9, 2–8. Farmanullah Khan, Z. Hayat, W. Ahmad, M. Ramzan, Z. Shah, M. Sharif, I. Ahmad Mian, & M. Hanif. (2013). Effect of slope position on physicochemical properties of eroded soil. Soil Environment, 32(1), 22– 28. Frank, K., Beegle, D., & Denning, J. (1998). Phosphorus. In: Brown, J. R. (Ed.), Recommended chemical soil test procedures for the North Central Region (North Central Regional Research Publication No. 221, revised). Columbia, MO: Missouri Agricultural Experiment Station, pp. 21–26. Gee, G. W., & Or, D. (2002). Particle size distribution. In: Dane, J. H., & Topp, G. C. (Eds.), Methods of Soil Analysis. Part 4, Physical methods. Soil Science. Am Book Series No.5, ASA and SSSA, Madison, WI, pp. 255–293. Griffiths, R. P., Madritch, M. D., & Swanson, A. K. (2009). The effects of topography on forest soil characteristics in the Oregon Cascade Mountains (USA): Implications for the effects of climate change on soil properties. Forest Ecology and Management, 257, 1–7. Ibitoye, A. A. (2008). Laboratory Manual on Basic Soil Analysis. Foladore Nig. Ltd, Akure, Nigeria, pp. 23– 47. Lambers, H., Raven, J. A., Shaver, G. R., & Smith, S. E. (2008). Plant nutrient-acquisition strategies change with soil age. Trends in Ecology Evolution, 23(2), 95–103. McLean, E. O. (1982). Soil pH and lime requirement. In: Page, A. L., Miller, R. H., & Keen, D. R. (Eds.), Methods of Soil Analysis, Part II. ASA Monograph No. 9. Madison, WI: ASA, pp. 199–223. Mokwunye, U., & Bationo, A. (2002). Meeting the phosphorus needs of the soils and crops of West Africa: the role of ingenious phosphate rocks. In: Vandalauwe et al. (Eds.), Integrated Plant Nutrient Management in Sub-Saharan Africa. CABI Publishing, USA, pp. 352. Nelson, D. W., & Sommer, L. E. (1996). Total carbon, Organic Carbon and Organic Matter. In: Sparks, D. L. (Ed.), Methods of Soil Analysis. Part 3. SSSA Book Series No. 5 SSSA Madison, WI, pp. 960–1010. Ogeh, J. S., & Ogwurike, P. C. (2006). Influence of Pa ge 8 https://journals.e-palli.com/home/index.php/ajgt Am. J. Geo Spat. Technol. 3(1) 1-8, 2024 Agricultural Land Use Types on some Soil Properties in Midwestern Nigeria. Journal of Agronomy, 5(3), 387– 390. Ogunkunle, A. O. (1993). Variation of some soil properties along two top sequences on Quartile schist and banded gnesis in southern Nigeria. Geoderma, 30(4), 397–402. Okalebo, J. R., Gathua, K. W., & Woomer, P. L. (2002). Laboratory methods of soil and plant analysis. A working manual (2nd ed.). Nairobi, Kenya: TSBF- CIAT, SACRED Africa, KARI, SSEA, 128 pp. Osodeke, V. E., & Osondu, N. E. (2006). Phosphorus distribution along a toposequence of a coastal sand parent material in southeastern Nigeria. Agricultural Journal, 3, 167–171. Oyedele, D. J., Awotoye, O. O., & Popoola, S. E. (2009). Soil Physical and Chemical properties under continuous maize cultivation as influenced by hedgerow tree species on Alfisols in Southwestern Nigeria. African Journal of Agricultural Research, 4(8), 736–739. Paulos, D. (1996). Availability of phosphorus in the coffee soil of Southwest Ethiopia. In: Soil the Resource Base for Survival: Proceedings of the 2nd Conference of Ethiopian Society of Soil Science (ESSS ’93), Addis Ababa, Ethiopia, 23–24 September 1993, M. Tekalign and H. Mitiku, Eds., pp. 119–129. Piotrowska, A., & Długosz, J. (2012). Spatio–temporal variability of microbial biomass content and activities related to some physicochemical properties of Luvisols. Geoderma, 173–174, 199–208. Porder, S., Payton, A., & Vitousek, P. M. (2005). Erosion landscape development affects plant nutrient status in the Hawaiian Islands. Oecologia, 142, 440–449. Vitousek, P. M., Porder, S., Houlton, B. Z., & Chadwick, O. A. (2010). Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen–phosphorus interactions. Ecological Application, 20(1), 5–15. Vogelmann, E. S., Reinert, D. J., Mentges, M. I., Vieira, D. A., de Barros, P. C. A., & Fasinmirin, J. T. (2010). Repellence in soils of humid subtropic climates of Rio Grande do sul, Brazil. Soil and Tillage Research Institute, pp. 126–133. Yeshanch, G. T. (2015). Assessment of soil fertility variation in different land uses and management practice. Watershed South Walo zone, Northern Ethiopia. International Journal of Environmental Bioremediation and Biodegradation, 3(1), 15–22. Zhang, K. L., & Hosoyamada, K. (1996). Influence of slope gradient on interrail erosion of Shirasu soil. Soil Physical Condition and Plant Growth in Japan, 73, 37–44. Ziadat, F. M., & Taimeh, A. Y. (2013). Effect of rainfall intensity, slope, and land use and antecedent soil moisture on soil erosion in an arid environment. Land Degradation and Development, 24, 582–590.