Influence of spacing and nutrient regimes on soil physical and chemical properties under Dendrocalamus brandisii (Munro) Kurz. plantation

Introduction

Soil physical and chemical properties serve as fundamental indicators of soil health and play a decisive role in determining the overall productivity, sustainability, and ecological functionality of perennial plantation systems. Key physical parameters, including soil moisture retention capacity and bulk density, directly govern water availability, aeration, root elongation, and soil mechanical resistance (Brady and Weil, 2017) [3] . Simultaneously, soil chemical traits such as soil reaction (pH), electrical conductivity (EC), organic carbon accumulation, and macronutrient/micronutrient pools regulate biochemical reactions, soil microbial activity, and plant nutrient uptake dynamics. Maintaining favorable physical and chemical soil conditions is therefore essential for optimizing biomass accumulation and economic output in intensively managed forest plantations. Bamboo is universally recognized as one of the fastest-growing perennial woody grasses globally, possessing exceptional ecological and socio-economic value. Owing to its extensive subterranean rhizome-root networks, dense canopy cover, and substantial annual litter production, bamboo plays a key role in soil conservation, soil aggregate stabilization, and carbon sequestration (Nath et al., 2015) [10] . Continuous litterfall accumulation and subsequent microbial decomposition add significant organic matter to the upper soil layers, enhancing cation exchange capacity (CEC), improving moisture retention, and promoting efficient biological nutrient cycling (Nair et al., 2010; Kumar and Nair, 2011) [9,7] . Consequently, bamboo-based production systems are widely advocated for land rehabilitation, watershed protection, and sustainable agroforestry development across tropical and subtropical regions. Among silvicultural intervention strategies, planting geometry (spacing) and nutrient management represent two critical operational levers dictating plantation structure and soil quality. Plantation spacing directly dictates spatial stocking density, light interception, microclimatic buffering, canopy closure speed, and root competition volume (Singh et al., 2017) [14] . Optimum planting geometry balances spatial resource utilization while preventing severe inter-clump competition for soil moisture and nutrients. Concurrently, targeted inorganic or organic fertilizer applications fulfill high nutrient demands during early vegetative establishment, supporting rapid culm production and biomass accumulation. However, inadequate or excessive fertilizer inputs can alter soil chemical balances, accelerate soil acidification, or cause nutrient leaching losses under high rainfall regimes (Tripathi and Singh, 2018) [16] . Dendrocalamus brandisii (Munro) Kurz., commonly known as Sweet Bamboo or Velvet Leaf Bamboo, is a highyielding, multipurpose tropical clump-forming species valued for industrial timber, paper pulp, structural construction, and edible shoot production. Given its fast growth rate and high biomass yield, D. brandisii exerts significant nutritional demands on soil reserves. Systematic evaluation of soil physical and chemical parameters under varying management regimes is vital for developing science-based nutrient management protocols (Yadav et al., 2019) [18] . Therefore, the present investigation was undertaken to evaluate the influence of two spacing regimes and three nutrient levels on soil physical and chemical properties under a three-year-old Dendrocalamus brandisii plantation in the humid tropical region of Kodagu, Karnataka, India.

Materials and Methods

The investigation was conducted during 2022-2023 in an established Dendrocalamus brandisii plantation at the experimental field station of the College of Forestry, Ponnampet, Kodagu, Karnataka (12°08′ N latitude, 75°53′ E longitude, and 840 m above mean sea level). The experimental site is located in the Western Ghats region of southern India and experiences a humid tropical climate with heavy southwest monsoonal rainfall averaging 2,500-3,000 mm annually. The soils of the site are deep, well-drained red latosols (Alfisols/Ultisols) with an acidic reaction and moderate organic matter content. The experiment was laid out in a Split Plot Design with three replications, comprising two main plot treatments and three sub-plot treatments. The main plot factor consisted of two spacing regimes: M₁ (4.0 × 5.0 m; 500 plants ha⁻¹) and M₂ (5.0 × 5.0 m; 400 plants ha⁻¹). The sub-plot factor consisted of three nutrient regimes: S₁ (recommended dose of 25 g N, 9 g P₂O₅, and 25 g K₂O plant⁻¹ year⁻¹), S₂ (25% higher than the recommended dose, i.e., 31.25 g N, 11.25 g P₂O₅, and 31.25 g K₂O plant⁻¹ year⁻¹), and S₃ (50% higher than the recommended dose, i.e., 37.50 g N, 13.50 g P₂O₅, and 37.50 g K₂O plant⁻¹ year⁻¹). Soil samples were collected after completion of the 2022-2023 annual growth cycle from two standardized depths, namely surface soil (D₁: 0-15 cm) and subsurface soil (D₂: 15-30 cm). Composite samples were prepared by thoroughly mixing sub-samples collected from five random locations within the active rooting zone of each experimental plot using a stainless-steel auger. For chemical analysis, the samples were air-dried under shade, gently crushed using a wooden mallet, passed through a 2-mm stainless-steel sieve, and stored in polyethylene bags, while separate undisturbed soil cores were collected using calibrated cylindrical steel core samplers for bulk density estimation. Soil moisture content was determined by the gravimetric method, wherein fresh soil samples were weighed immediately after collection, oven-dried at 105 ± 2 °C for 24 hours to constant weight, and moisture percentage was calculated as [(Fresh Weight -Oven Dry Weight)/Oven Dry Weight] × 100. Soil bulk density was estimated using the core method by dividing the oven-dry mass of soil by the known volume of the sampling core and expressed in g cm⁻³. Soil pH and electrical conductivity (EC) were measured in a 1:2.5 soil-towater suspension using a digital pH meter and conductivity meter, respectively, following the procedure described by Richards (1954) [13] , with EC expressed in dS m⁻¹ at 25 °C. Soil organic carbon was estimated using the Walkley and Black wet oxidation method involving potassium dichromate and concentrated sulphuric acid followed by back titration with ferrous ammonium sulphate (Walkley and Black, 1934; Nelson and Sommers, 1996) [17,11] , and expressed in g kg⁻¹. Available nitrogen was determined by the alkaline potassium permanganate distillation method (Subbiah and Asija, 1956) [15] , wherein the liberated ammonia was absorbed in boric acid and titrated against standard sulphuric acid, and results were expressed in kg ha⁻¹. Available phosphorus was extracted using Bray's No. 1 extractant (0.03 N NH₄F + 0.025 N HCl), appropriate for acidic soils, and quantified spectrophotometrically at 882 nm using the ascorbic acid blue colour method (Bray and Kurtz, 1945) [4] , while available potassium was extracted with neutral 1 N ammonium acetate (pH 7.0) and measured using a flame photometer (Jackson, 1973) [6] . Available sulphur was extracted with 0.15% calcium chloride solution and estimated turbidimetrically using barium chloride at 420 nm (Jackson, 1973) [6] , whereas exchangeable calcium and magnesium were extracted with neutral 1 N ammonium acetate and determined by complexometric EDTA titration using Calcon and Eriochrome Black T indicators (Jackson, 1973) [6] , with values expressed in cmol(+) kg⁻¹. The experimental data on all soil physical and chemical properties were subjected to analysis of variance (ANOVA) appropriate for the Factorial Split Plot Design, and treatment means were compared using the Critical Difference (CD) test at the 5% level of significance (P = 0.05). Nonsignificant treatment effects were denoted as "NS". Gravimetric soil moisture data were subjected to arcsine transformation before statistical analysis, although the original untransformed means are presented in the tables along with the transformed values.

Results and Discussion

Soil Physical Properties

Statistical analysis revealed that spacing, nutrient regimes, and their interaction had no significant effect (P > 0.05) on soil moisture content or bulk density at either soil depth. M₂ (5.0 × 5.0 m) recorded slightly higher surface soil moisture (20.79%), while M₁ showed higher moisture at 15-30 cm (19.84%). Among nutrient regimes, S₂ recorded the highest surface moisture (20.93%) and S₃ the highest subsurface moisture (19.87%), with M₂S₂ and M₁S₃ producing the maximum surface (21.85%) and subsurface (20.53%) moisture, respectively. Bulk density ranged from 1.19-1.46 g cm⁻³ (0-15 cm) and 1.28-1.38 g cm⁻³ (15-30 cm), with the highest value under S₃ (1.43 g cm⁻³), though differences were non-significant. The results indicate that soil physical properties change slowly in young bamboo plantations, consistent with the findings of Singh et al. (2017) [14] , Nath et al. (2015) [10] , and Yadav et al. (2019) [18] .

Soil pH and Electrical Conductivity (EC)

Spacing had no significant effect (P > 0.05) on soil pH, whereas nutrient regimes significantly influenced pH at both 0-15 cm (P = 0.0166) and 15-30 cm (P = 0.0243). Treatment S₁ recorded the highest pH (6.28), while S₂ and S₃ caused slight acidification (6.18-6.20), likely due to H⁺ ion release during nitrification of applied nitrogen fertilizers. Electrical conductivity (EC) also varied significantly among nutrient regimes (p < 0.05), ranging from 0.98 to 1.00 dS m⁻¹, with slightly higher values under S₂ and S₃ because of increased soluble fertilizer salts. However, all EC values remained below the critical salinity threshold (<2.0 dS m⁻¹), indicating suitable conditions for bamboo growth. The interaction between spacing and nutrient regimes was nonsignificant for both pH and EC. Similar results were reported by Tripathi et al. (2018) [16] , Banik et al. (2020) [2] , and Nath et al. (2015) [10] .

Soil Chemical Properties

Statistical analysis showed that spacing, nutrient regimes, and their interaction had no significant effect (P > 0.05) on soil organic carbon (OC), primary macronutrients (N, P₂O₅, K₂O), or secondary nutrients (S, Ca, Mg). Surface OC ranged from 10.58-14.10 g kg⁻¹ and subsurface OC from 11.36-20.56 g kg⁻¹, with wider spacing (M₂) recording higher subsurface OC (17.19 g kg⁻¹), and the maximum value under M₂S₁ (20.56 g kg⁻¹).

Available N ranged from 167.49-194.07 kg ha⁻¹, P₂O₅ from 13.75-16.75 kg ha⁻¹, and K₂O from 248.22-287.79 kg ha⁻¹, with M₂ generally maintaining higher nutrient levels. Available S ranged from 2.30-4.17 mg kg⁻¹, while exchangeable Ca and Mg varied from 2.47-4.27 and 2.42-3.88 cmol(+) kg⁻¹, respectively. The non-significant response indicates that soil nutrient dynamics change gradually in young bamboo plantations and become more evident with stand maturation, consistent with Nath et al. (2015) [10] , Singh et al. (2017) [14] , and Kumar et al. (2021) [8] .

Conclusion

The study revealed that spacing and nutrient regimes had limited influence on the soil physical and chemical properties of a threeyear-old Dendrocalamus brandisii plantation. Soil bulk density, moisture content, organic carbon, and available nutrients (N, P, K, S, Ca, and Mg) did not differ significantly among treatments, indicating stable soil conditions under managed bamboo cultivation. Significant effects were observed only for soil pH and electrical conductivity, with higher fertilizer levels causing slight acidification and increased EC, although both remained within the optimum range for bamboo growth. Wider spacing (5.0 × 5.0 m) generally maintained higher soil moisture and nutrient availability due to reduced plant competition. The limited treatment effects are mainly attributed to the young age of the plantation, as improvements in soil properties under bamboo develop gradually through litter decomposition and root turnover. Overall, Dendrocalamus brandisii shows strong potential for sustaining soil health and fertility under appropriate silvicultural management.

References

1. Banik RL. Silviculture and field guide to priority bamboos of Bangladesh and South Asia. Chittagong: Bangladesh Forest Research Institute; 2015.
2. Banik RL, Nath AJ, Das AK. Nutrient dynamics and soil fertility alterations in managed tropical bamboo plantations. Journal of Forest Research. 2020;31(4):1205-1214.
3. Brady NC, Weil RR. The Nature and Properties of Soils. 15th ed. New York: Pearson Education Inc.; 2017.
4. Bray RH, Kurtz LT. Determination of total, organic and available forms of phosphorus in soils. Soil Science. 1945;59(1):39-45.
5. Bremner JM, Mulvaney CS. Nitrogen-total. In: Page AL, Miller RH, Keeney DR, editors. Methods of Soil Analysis, Part 2: Chemical and Microbiological Properties. Madison (WI): American Society of Agronomy and Soil Science Society of America; 1982. p. 595-624.
6. Jackson ML. Soil Chemical Analysis. New Delhi: Prentice Hall of India Pvt. Ltd.; 1973.
7. Kumar BM, Nair PKR. Carbon Sequestration Potential of Agroforestry Systems: Opportunities and Challenges. Dordrecht: Springer Science & Business Media; 2011.
8. Kumar D, Sharma G, Yadav RP. Soil organic carbon pools and nutrient availability under long-term bamboo plantations in humid tropics. Agroforestry Systems. 2021;95(3):511522.
9. Nair PKR, Nair VD, Kumar BM, Showalter JM. Carbon sequestration in agroforestry systems. Advances in Agronomy. 2010;108:237-307.
10. Nath AJ, Das G, Das AK. Bamboo-based agroforestry systems improve soil quality and carbon storage in humid tropical ecosystems of northeast India. Agroforestry Systems. 2015;89(6):1013-1024.
11. Madison (WI): Soil Science Society of America and American Society of Agronomy; 1996. p. 961-1010.
12. Olsen SR, Cole CV, Watanabe FS, Dean LA. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate. USDA Circular No. 939. Washington, DC: United States Department of Agriculture; 1954.
13. Richards LA. Diagnosis and Improvement of Saline and Alkali Soils. Agriculture Handbook No. 60. Washington, DC: United States Department of Agriculture; 1954.
14. Singh AK, Singh KA, Singh R. Effect of bamboo plantation on soil properties and nutrient dynamics under subtropical conditions. Indian Forester. 2017;143(6):567-573.
15. Subbiah BV, Asija GL. A rapid procedure for the estimation of available nitrogen in soils. Current Science. 1956;25(8):259-260.
16. Tripathi SK, Singh KP. Influence of bamboo plantations on soil fertility and nutrient dynamics in tropical ecosystems. Journal of Tropical Forest Science. 2018;30(4):473-482.
17. Walkley A, Black IA. An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Science. 1934;37(1):29-38.
18. Yadav RP, Sharma G, Kumar D. Effect of nutrient management on soil fertility and productivity in bamboo plantations. Indian Journal of Agroforestry. 2019;21(2):4551.