Agroforestry compound planting and breeding can substantially contribute to the green and sustainable advancement of agriculture. However, the effects of the bayberry-tea-chicken compound cultivation model on tea quality and the underlying mechanisms remain unclear. This study compared the effects of tea monocropping (TM), tea-bayberry intercropping (TB), and the tea-bayberry-chicken compound model (TBC) on tea 100‑bud weight and quality, soil physicochemical properties, key enzymatic activities, and microbial community structure, and analyzed the relationships among these factors. Relative to the TM treatment, TB and TBC treatments were associated with 10.1
Long-term nitrogen (N) addition alters soil N cycling and plant N acquisition, but it remains poorly resolved which soil indicators can statistically explain differences in short-term plant ¹⁵N responses between independently established forest platforms receiving matched N inputs. We compared short-term plant ¹⁵N responses and prespecified soil indicators between two long-term forest experimental platforms receiving a common N-addition treatment. At Changbai Mountain and Wuying, we compared control and matched 50 kg N ha⁻¹ yr⁻¹ treatments, with three independent plots per treatment at each platform. Separate microplots received ¹⁵NH₄⁺ or ¹⁵NO₃⁻ pulse tracers, and 24-h plant-tissue ¹⁵N recovery responses were quantified. We evaluated soil NH₄⁺–N, soil NO₃⁻–N, pH, soil moisture, microbial biomass nitrogen (MBN), and potential β-1,4-N-acetylglucosaminidase (NAG) activity as prespecified soil indicators using models adjusted for the platform × treatment structure. The N-addition effects on short-term plant ¹⁵NH₄⁺ and ¹⁵NO₃⁻ responses were significantly larger at Wuying than at Changbai Mountain. The between-platform difference was greater for ¹⁵NH₄⁺ than ¹⁵NO₃⁻ responses (Site × Treatment × N form: F₁,₄ = 8.52, P = 0.043). NAG activity was negatively associated with both responses (β = −5.32 for ¹⁵NH₄⁺ and − 4.62 for ¹⁵NO₃⁻; Benjamini–Hochberg-adjusted q = 0.026 for both) and was the only candidate whose inclusion improved model support. With NAG included, the between-platform contrasts were attenuated by 61.1
Nitrogen (N) leaching is a major pathway of N loss in upland cropping systems, directly reducing fertilizer N recovery efficiency (FNRE). However, the interactions between N leaching, soil N transformation, and crop N uptake across contrasting soil types remain poorly understood. A 15N-labeled column leaching experiment with and without maize cultivation was conducted using eight pedologically distinct soils representing the major maize-growing regions of China. Nitrogen leaching dynamics, fertilizer N fate, and the relationships among soil properties, maize growth, and FNRE were comprehensively evaluated. Nitrogen leaching showed consistent temporal dynamics across all eight soils regardless of maize cultivation, with peak losses occurring during the first three leaching events after fertilization. The NO3−-N dominated cumulative N leaching (16.0
Gully erosion is a major contributor to soil loss, but the applicability of GeoWEPP in gully-dominated catchments remains uncertain. This study evaluated the performance and parameter transferability of GeoWEPP in simulating event-scale runoff and soil loss in two gully-dominated catchments. Runoff and sediment were monitored at the gully head and catchment outlet during the rainfall seasons of 2022 and 2023. The key partition parameters in the model (critical source area and minimum source channel length) were optimized to obtain a drainage network consistent with the observed gully configuration. Hillslope cropland, gully, and woodland were represented as distinct model units, and cropland tillage orientation and gully vegetation cover were further considered in the parameterization. Parameters were calibrated in F1 and transferred to F2 without further adjustment. Model performance was evaluated using R2 and NSE. While event runoff depth changed only slightly, sediment concentration and sediment yield modulus increased markedly from the gully head to the catchment outlet. At the outlet, sediment concentration and sediment yield modulus were 5.5 and 11.3 times their corresponding gully head value in F1 and 9.6 and 18.0 times those in F2. The calibrated erosion-related parameters differed markedly among model units. Nearly bare gully surfaces had the highest rill erodibility and the lowest critical shear stress. GeoWEPP performed well in simulating runoff, with R2 and NSE values of 0.90 and 0.82 in F1 and 0.91 and 0.87 in F2. Soil loss simulations achieved R2 and NSE values of 0.83 and 0.64 in F1 and 0.85 and 0.63 in F2. GeoWEPP reproduced event-scale runoff and the overall variation in soil loss in the studied gully-dominated catchments, although soil loss during high-erosion events was often underestimated.
Coastal vegetated soils store large amounts of soil organic matter (SOM), yet composition is mainly inferred from bulk stocks. We tested whether the filter-press mid-infrared attenuated total reflectance (MIR-ATR) method can resolve SOM functional-group chemistry across three coastal vegetation zones, and with depth. Soil samples (n = 150) were obtained from 10 cores (five 10 cm depth intervals to 50 cm) in vegetation zones (mangrove, MG; saltmarsh, SM; and paperbark, PB) at Wilsons Promontory National Park, Victoria, Australia. MG and SM zones are tidally inundated, PB is supratidal. Multivariate curve resolution (MCR) and constrained peak fitting were used to separate OM, water and mineral contributions and to track functional groups from litter into the profile. Plant tissues were dominated by carbohydrates, amide, carboxylate, and phenolic bands. Spectra revealed similar major organic components for MG and SM in the soil, but more complexity for PB. Litter spectral signatures were evident in the surface (0–10 cm) soil layer. Most change in functional-group intensity was in the surface soil. Aliphatic C–H: carbohydrate peak-area ratios changed little with depth, consistent with mineral dilution and continuing root input rather than proof of selective carbohydrate loss. The filter-press ATR method can track functional-group patterns in wet coastal soils. Aliphatic C–H, carbonyl, phenolic and carbohydrate-related bands differed among vegetation communities and with depth. Vegetation and hydrology co-vary on this transect, so the PB contrast with MG and SM is a combined plant–environment effect.
