Quantitative evaluations of biomass accumulation after disturbances in forests are crucially important for elucidating and predicting forest carbon dynamics in order to understand the carbon sink/source activities. During early secondary succession, understory vegetation often affects sapling growth. However, reports on biomass recovery in naturally-regenerating sites are limited in Japan. Therefore, we traced annual or biennial changes in plant species, biomass, and net primary production (NPP) in a naturally regenerating site in Japan after windthrow and salvage-logging plantation for nine years. The catastrophic disturbance depleted the aboveground biomass (AGB) from 90.6 to 2.7 Mg·ha⁻¹, changing understory dominant species from Dryopteris spp. to Rubus idaeus. The mean understory AGB recovered to 4.7 Mg·ha⁻¹ in seven years with the dominant species changing to invasive Solidago gigantea. Subsequently, patches of deciduous trees (mainly Betula spp.) recovered whereas the understory AGB decreased. Mean understory NPP increased to 272 g·C·m⁻²·year⁻¹ within seven years after the disturbance, but decreased thereafter to 189 g·C·m⁻²·year⁻¹. Total NPP stagnated despite increasing overstory NPP. The biomass accumulation is similar to that of naturally regenerating sites without increase of trees in boreal and temperate regions. Dense ground vegetation and low water and nutrient availability of the soil in the study site restrict the recovery of canopy-forming trees and eventually influence the biomass accumulation.

A laboratory incubation experiment is conducted for 90 days under controlled conditions where either pruning residue or its biochar is applied to determine which application generates the lowest amount of greenhouse gas from tea plantation soil. To study the effect of incorporation depth on soil N₂O and CO₂ emissions, experiment 1 is performed with three treatments: (1) control; (2) tea pruning residue; and (3) residue biochar mixed with soil from two different depths (0–5 cm and 0–10 cm layers). In experiment 2, only the 0–10 cm soil layer is used to study the effect of surface application of tea pruning residue or its biochar on soil N₂O and CO₂ emissions compared with the control. The results show that biochar significantly increases soil pH, total C and C/N ratio in both experiments. The addition of pruning residue significantly increases soil total C content, cumulative N₂O and CO₂ emissions after 90 days of incubation. Converting pruning residue to biochar and its application significantly decreases cumulative N₂O emission by 17.7% and 74.2% from the 0–5 cm and 0–10 cm soil layers, respectively, compared to their respective controls. However, biochar addition increases soil CO₂ emissions for both the soil layers in experiment 1. Surface application of biochar to soil significantly reduces both N₂O and CO₂ emissions compared to residue treatment and the control in experiment 2. Our results suggest that converting pruning residue to biochar and its addition to soil has the potential to mitigate soil N₂O emissions from tea plantation.

To investigate the effect of paddy-upland (PU) rotation system on greenhouse gas emissions, methane (CH₄) and nitrous oxide (N₂O) emissions were monitored for three years for a PU rotation field (four cultivations (wheat-soybean-rice-rice) over three years) and continuous paddy (CP) field on alluvial soil in western Japan. Soil carbon storage was also calculated using an improved Rothamsted Carbon (RothC) model. The net greenhouse gas balance was finally evaluated as the sum of CO₂eq of the CH₄, N₂O and changes in soil carbon storage. The average CH₄ emissions were significantly lower and the average N₂O emissions were significantly higher in the PU field than those in the CP field (p < 0.01). On CO₂ equivalent basis, CH₄ emissions were much higher than N₂O emission. In total, the average CO₂eq emissions of CH₄ plus N₂O in the PU field (1.81 Mg CO₂ ha⁻¹ year⁻¹) were significantly lower than those in the CP field (7.42 Mg CO₂ ha⁻¹ year⁻¹) (p < 0.01). The RothC model revealed that the changes in soil carbon storage corresponded to CO₂eq emissions of 0.57 and 0.09 Mg CO₂ ha⁻¹ year⁻¹ in the both fields, respectively. Consequently, the net greenhouse gas balance in the PU and CP fields were estimated to be 2.38 and 7.51 Mg CO₂ ha⁻¹ year⁻¹, respectively, suggesting a 68% reduction in the PU system. In conclusion, PU rotation system can be regarded as one type of the climate-smart soil management.

Appearance, aroma and taste are important factors for assessing the quality of tea (Camellia sinensis) and then shading of tea is performed to increase chlorophyll content, which is an important factor for evaluating the appearance and good taste. Although some traditional approaches that require tremendous efforts for the collection of samples and laboratory chemical analyses have been applied, they are not feasible for long-term monitoring. In contrast, hyperspectral remote sensing is proven to be an efficient way for chlorophyll content monitoring. In this study, the three different approaches of kernel-based extreme learning machine (KELM), random forests (RF), and deep belief nets (DBN) were compared to assess the potential for estimating leaf chlorophyll contents from hyperspectral data with existing supervised learning models. Overall, regression models based on KELM yielded the highest performance, achieving a Root Mean Square (RMS) error of 0.20-0.56μg/cm².