Contrasting tree growth and soil organic carbon across stand densities in a Picea crassifolia plantation: associations with soil nitrogen

Abstract

Introduction Stand density can influence both tree growth and belowground carbon storage in plantations, but density conditions favorable for these two functions may not necessarily coincide. Methods We investigated a Picea crassifolia plantation in the Qilian Mountains under five stand-density conditions with nominal initial densities of approximately 4,444, 2,500, 2,000, 3,333, and 2,667 stems ha⁻¹. Each treatment comprised three spatially independent replicate stands, with three 50 × 50 m quadrats established within each stand, resulting in nine quadrat-level observations per treatment. Tree growth, leaf and root C, N, and P concentrations, soil physical properties, and soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) contents and densities were evaluated across the 0–80 cm soil profile. Correlation analysis, redundancy analysis (RDA), and exploratory structural equation modeling (SEM) were further used to examine statistical associations among the measured variables. Results Tree height, ground diameter, and crown development were greater under the nominal 2,000 and 2,667 stems ha⁻¹ treatments, whereas these conditions did not consistently correspond to greater soil C and nutrient storage. In contrast, the nominal 3,333 and 2,500 stems ha⁻¹ treatments generally showed higher SOC, TN, and TP densities in several soil layers. RDA indicated that TP contributed most strongly to the multivariate differentiation among the measured traits, whereas exploratory SEM identified TN as the strongest statistical correlate of SOC among the measured soil variables. Discussion These findings demonstrate contrasting density-associated patterns between aboveground tree growth and belowground carbon and nutrient storage. Under the conditions examined here, density management should therefore consider the balance between tree growth and soil carbon and nutrient functions rather than assume a single universally optimal stand density.