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Forests cover approximately 70% of the area contaminated by the Fukushima Daiichi Nuclear Power Plant accident in 2011. Following this severe contamination event, radiocaesium (¹³⁷Cs) is anticipated to circulate within these forest ecosystems for several decades. Since the accident, a number of models have been constructed to evaluate the past and future dynamics of ¹³⁷Cs in these forests. To explore the performance and uncertainties of these models we conducted a model inter-comparison exercise using Fukushima data. The main scenario addressed an evergreen needleleaf forest (cedar/cypress), which is the most common and commercially important forest type in Japan. We also tested the models with two forest management scenarios (decontamination by removal of soil surface litter and forest regeneration) and, furthermore, a deciduous broadleaf forest (konara oak) scenario as a preliminary modelling study of this type of forest. After appropriate calibration, the models reproduced the observed data reliably and the ranges of calculated trajectories were narrow in the early phase after the fallout. Successful model performances in the early phase were probably attributable to the availability of comprehensive data characterizing radiocaesium partitioning in the early phase. However, the envelope of the calculated model end points enlarged in long-term simulations over 50 years after the fallout. It is essential to continue repetitive verification/validation processes using decadal data for various forest types to improve the models and to update the forecasting capacity of the models.

The pattern of soil carbon stock is atypical along the slope position in a seasonally dry tropical forest; the mean stock values increase from the lower, middle, to upper slopes, at 11.5, 13.2, and 15.5 kg m⁻², respectively. In sloping landscapes, soil organic carbon tends to accumulate in lower slopes, but our previous soil respiration study suggested that soil carbon stock distribution along the slope position in seasonally dry tropical forests is atypical. The aims of this study were: (i) to examine whether the atypical pattern occurs widely in the watershed; and (ii) to examine the pattern of root development in the soil profile as a source of soil carbon. The density and stock of soil carbon in three soil layers (0–10, 10–30, and 30–100 cm) of 13 soil profiles were compared in different positions on the slope (upper, middle, and lower). Root biomass at each slope position was also determined. Soil carbon density in each layer increased significantly with an increase in the relative position of the slopes, particularly in the 10–30 cm soil layer. The density of medium root (3–10 mm in diameter) in the upper slopes was significantly higher than that in the middle and lower slopes, especially for 15–60 cm soil layers. The atypical pattern of soil carbon accumulation along the slope position occurred widely in the studied watershed and appeared to be caused by the development of root systems in deeply weathered soil under xeric soil conditions in the upper slopes. Roots of bamboo undergrowth may also contribute to soil carbon stabilization by reducing soil erosion in the surface soil.

Nutrient recycling is one of the most important services that supports other processes in ecosystems. Changing litterfall patterns induced by climate change can cause imbalances in nutrient availability. In this study, we reported the long-term (28-year) interplay between environmental factors and variability among litterfall fractions (leaves, flowers, and fruit) in a tropical dry forest located in Kanchanaburi, Thailand. A long-term litter trap dataset was collected and analyzed by lagged generalized additive models. Strong seasonality was observed among the litter fractions. The greatest leaf and flower litterfall accumulated mostly during the cool, dry season, while fruit litterfall occurred mostly during the rainy season. For leaf litter, significant deviations in maximum temperature (Tmax), volumetric soil moisture content (SM), and evapotranspiration (ET) during the months prior to the current litterfall month were the most plausible factors affecting leaf litter production. Vapor pressure deficit (VPD) and ET were isolated as the most significant factors affecting flower litterfall. Interestingly, light, mean temperature (Tmean), and the southern oscillation index (SOI) were the most significant factors affecting fruit litterfall, and wetter years proved to be highly correlated with elevated fruit litterfall. Such environmental variability affects both the triggering of litterfall and its quantity. Shifting environmental conditions can therefore alter nutrient recycling rates through the changing characteristics and quantity of litter.

Forest soils support tree productivity and resilience. However, long-term manipulations of drought and substrate inputs are rare. This resource reports 16S rRNA gene, ITS2, and long-amplicon (SSU–ITS–LSU) sequencing datasets of bacterial, fungal, and arbuscular mycorrhizal fungal communities from Japanese forest soil following 8 years of throughfall exclusion.