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Fungi in soil play pivotal roles in nutrient cycling, pest controls, and plant community succession in terrestrial ecosystems. Despite the ecosystem functions provided by soil fungi, our knowledge of the assembly processes of belowground fungi has been limited. In particular, we still have limited knowledge of how diverse functional groups of fungi interact with each other in facilitative and competitive ways in soil. Based on the high-throughput sequencing data of fungi in a cool-temperate forest in northern Japan, we analyzed how taxonomically and functionally diverse fungi showed correlated fine-scale distributions in soil. By uncovering pairs of fungi that frequently co-occurred in the same soil samples, networks depicting fine-scale co-occurrences of fungi were inferred at the O (organic matter) and A (surface soil) horizons. The results then led to the working hypothesis that mycorrhizal, endophytic, saprotrophic, and pathogenic fungi could form compartmentalized (modular) networks of facilitative, antagonistic, and/or competitive interactions in belowground ecosystems. Overall, this study provides a research basis for further understanding how interspecific interactions, along with sharing of niches among fungi, drive the dynamics of poorly explored biospheres in soil.

Ionic polymer–metal composite (IPMC) sensors generate voltages or currents when subjected to deformation. The magnitude and time constant of the electrical response vary significantly with ambient humidity and water content. However, most conventional physical models focus solely on cation dynamics and do not consider water dynamics. In addition to cation dynamics, Zhu’s model explicitly incorporates the dynamics of water. Consequently, Zhu’s model is considered one of the most promising approaches for physical modeling of IPMC sensors. This paper presents exact analytical solutions to Zhu’s model of IPMC sensors for the first time. The derivation method transforms Zhu’s model into the frequency domain using Laplace transform-based analysis together with linear approximation, and subsequently solves it as a boundary value problem of a set of linear ordinary differential equations. The resulting solution is expressed as a transfer function. The input variable is the applied bending deformation, and the output variables include the open-circuit voltage or short-circuit current at the sensor terminals, as well as the distributions of cations, water molecules, and electric potential within the polymer. The obtained transfer functions are represented by irrational functions, which typically arise as solutions to a system of partial differential equations. Furthermore, this paper presents analytical approximations of the step response of the sensor voltage or current by approximating the obtained transfer functions. The steady-state and maximum values of the time response are derived from these analytical approximations. Additionally, the relaxation behavior of the sensor voltage is characterized by a key parameter newly derived from the analytical approximation presented in this paper.

Climate change is accelerating, and the monitoring of plant phenology is becoming increasingly important. In response to this need, many vegetation indices (VIs) and analytical methods have been developed. However, many VIs are vulnerable to uncertainties caused by snowmelt, making them potentially unsuitable for monitoring spring phenology in forested regions where leaf flush (start of season, SOS) begins simultaneously with snowmelt. Although several VIs for snowy regions have been proposed, most of them were designed for tundra vegetation, such as grasslands. Currently, no VI or analytical method specifically suited for snowy forested regions has been firmly established. Similarly, there is still no well-established method for continuously monitoring autumn coloration. In this study, we propose the use of hue, one of the components of the HSV model, for remote sensing of plant phenology. Hue quantifies differences in object color and is expected to facilitate clearer distinction of snow influence. It may also enable accurate detection of canopy color transitions, such as autumn coloration. We evaluate the applicability of hue to remote sensing using in situ spectroradiometer observations collected from five sites of the Phenological Eyes Network (PEN), which represent a range of ecosystems—including forests, grasslands, and paddy fields—as well as the relative spectral response (RSR) of the Second-generation Global Imager (SGLI) onboard the GCOM-C satellite operated by JAXA (Japan Aerospace Exploration Agency). The results suggest that hue is more robust to snow-related uncertainties than traditional VIs (NDVI, EVI, CCI, NDGI) and may also be effective for quantifying autumn coloration. Hue is calculated solely from blue, green, and red reflectance, without relying on near-infrared (NIR) or shortwave infrared (SWIR) channels. Since blue, green and red channels are available on almost all optical satellite sensors, hue may offer broader applicability than many traditional VIs.

Understanding the regeneration and succession of belowground communities, particularly in forests, is vital for maintaining ecosystem health. Despite its importance, there is limited knowledge regarding how fungal communities change over time during ecosystem development, especially under different forest restoration strategies. In this study, we focused on two restoration methods used in northern Japan: monoculture planting and natural regeneration. We examined the responses of the fungal community to monoculture plantations (active tree planting) and naturally regenerated (passive regeneration) forests over a 50-year chronosequence, using natural forests as a reference. Based on DNA metabarcoding, we assessed the richness of fungal Operational Taxonomic Units (OTUs) and their dissimilarity. Our findings revealed that soil fungal richness remained stable after natural regeneration but declined in monoculture plantations, from 354 to 247 OTUs. While the compositional dissimilarity of fungal assemblages between monoculture plantations and natural forests remained consistent regardless of the time since tree planting, it significantly decreased after natural regeneration, suggesting recovery to a state close to the reference level. Notably, the composition of key functional fungal groups—saprotrophic and ectomycorrhizal— has increasingly mirrored that of natural forests over time following passive natural regeneration. In summary, our study suggests that monoculture plantations may not be effective for long-term ecosystem function and service recovery because of their limited support for soil fungal diversity. These results underscore the importance of natural regeneration in forest restoration and management strategies.

The photochemical reflectance index (PRI) and the chlorophyll carotenoid index (CCI) are carotenoid-sensitive vegetation indices, which can monitor vegetation’s photosynthetic activities. One unique satellite named “Global Change Observation Mission-Climate (GCOM-C)” is equipped with a sensor, “Second Generation Global Imager (SGLI)”, which has the potential to frequently and simultaneously observe PRI and CCI over a wide swath. However, the observation accuracy of PRI and CCI derived from GCOM-C/SGLI remains unclear in forests. Thus, we demonstrated their accuracy assessment by comparing them with in situ data. We collected in situ spectral irradiance data at four forest sites in Japan for three years. We statistically compared satellite PRI with in situ PRI, and satellite CCI with in situ CCI. From the obtained results, the satellite PRI showed poor agreement (the best: r=0.294 (p<0.05)) and the satellite CCI showed good agreement (the best: r=0.911 (p<0.001)). The greater agreement of satellite CCI is possibly because satellite CCI contained fewer outliers and satellite CCI was more resistant to small noise, compared to satellite PRI. Our results suggest that the satellite CCI is more suitable for practical use than the satellite PRI with the latest version (version 3) of GCOM-C/SGLI’s products.

Accurate evaluation of forest biomass distribution and its long-term change over wide areas is required for effective forest carbon management and prediction of landscape-scale forest dynamics. We evaluated a landscape-scale (225 km 2 ) decadal forest carbon budget at a 1 ha spatial resolution in a cool-temperate forest, by repeating airborne laser observations 10 years apart and partitioning net forest biomass change (FBC) into growth and mortality. Using >10 000 samples, we revealed that naturally regenerated forests have large spatial heterogeneity in net biomass change, and 3/4 of the photosynthetically acquired carbon stock moved to necromass even without anthropogenic disturbances. Actual carbon residence time as living tree biomass was estimated by dividing biomass by growth or mortality rates. The residence time was 107 and 106 years, respectively with large spatial variation among stands (48 and 42 years, respectively, as the difference between 25 and 75 percentile), although studied forest stands have small variation in the forest functional type in a landscape-scale. The best predictors of subsequent decadal biomass changes were two forest structural factors, mean canopy height and canopy height variation in addition to one environmental factor, elevation. Considering the long lifetime of trees, these structural factors may be an indicator of forest soundness rather than a cause of forest growth or mortality. However, in any cases, these structural factors can be powerful predictors of subsequent FBC.

Warmer and drier climates over Amazonia have been predicted for the next century with expected changes in regional water and carbon cycles. We examined the impact of interannual and seasonal variations in climate conditions on ecosystem-level evapotranspiration (ET) and water use efficiency (WUE) to determine key climatic drivers and anticipate the response of these ecosystems to climate change. We used daily climate and eddyflux data recorded at the Guyaflux site in French Guiana from 2004 to 2014. ET and WUE exhibited weak interannual variability. The main climatic driver of ET and WUE was global radiation (Rg), but relative extractable water (REW) and soil temperature (Ts) did also contribute. At the seasonal scale, ET and WUE showed a modal pattern driven by Rg, with maximum values for ET in July and August and for WUE at the beginning of the year. By removing radiation effects during water depleted periods, we showed that soil water stress strongly reduced ET. In contrast, drought conditions enhanced radiation-normalized WUE in almost all the years, suggesting that the lack of soil water had a more severe effect on ecosystem evapotranspiration than on photosynthesis. Our results are of major concern for tropical ecosystem modeling because they suggest that under future climate conditions, tropical forest ecosystems will be able to simultaneously adjust CO2 and H2O fluxes. Yet, for tropical forests under future conditions, the direction of change in WUE at the ecosystem scale is hard to predict, since the impact of radiation on WUE is counterbalanced by adjustments to soil water limitations. Developing mechanistic models that fully integrate the processes associated with CO2 and H2O flux control should help researchers understand and simulate future functional adjustments in these ecosystems.

Background: Previous studies have attempted to determine whether certain risk factors can predict the occurrence of inversion ankle sprains in male collegiate soccer players. However, no consensus has been reached on the predictive risk factors of inversion ankle sprain in this population. Purpose: To identify risk factors for inversion ankle sprains among male collegiate soccer players. Study Design: Cohort study; Level of evidence, 2. Methods: Included were 145 male collegiate soccer players in Japan who were assessed during a preseason medical checkup for potential risk factors of inversion ankle sprain. The preseason assessment included anthropometric measurements, joint laxity and flexibility, muscle flexibility, muscle strength, and balance ability, with a total of 33 variables. The participants were monitored during the 2019 season for inversion ankle sprains as diagnosed by physicians. Results: A total of 31 inversion ankle sprains in 31 players (21.4%) occurred during the season. Only the measured isometric hip abductor strength was significantly lower in injured players as compared with uninjured players. Logistic regression analysis revealed measured hip abductor muscle strength deficit as a significant risk factor for inversion ankle sprain (odds ratio, 0.978 [95% CI, 0.976-0.999]; P = .05). Conclusion: Hip abductor strength deficit was a risk factor for inversion ankle sprain in the study population. This finding could be useful for the prevention of inversion ankle sprains in male collegiate soccer players.

Dry deposition has an impact on nitrogen status in forest environments. However, the mechanism for the high dry-deposition rates of fine nitrate particles (NO3-) observed in forests remains unknown and is thus a potential source of error in chemical transport models (CTMs). Here, we modified and applied a multilayer land surface model coupled with dry-deposition and aerosol dynamic processes for a temperate mixed forest in Japan. This represents the first application of such a model to ammonium nitrate (NH4NO3) gas–particle conversion (gpc) and the aerosol water uptake of reactive nitrogen compounds. Thermodynamics, kinetics, and dry deposition for mixed inorganic particles are modeled by a triple-moment modal method. Data for inorganic mass and size-resolved total number concentrations measured by a filter pack and electrical low-pressure impactor in autumn were used for model inputs and subsequent numerical analysis. The model successfully reproduces turbulent fluxes observed above the canopy and vertical micrometeorological profiles noted in our previous studies. The sensitivity tests with and without gpc demonstrated clear changes in the inorganic mass and size-resolved total number concentrations within the canopy. The results also revealed that within-canopy evaporation of NH4NO3 under dry conditions significantly enhances the deposition flux of fine-NO3- and fine-NH4+ particles, while reducing the deposition flux of nitric acid gas (HNO3). As a result of the evaporation of particulate NH4NO3, the calculated daytime mass flux of fine NO3- over the canopy was 15 times higher in the scenario of “gpc” than in the scenario of “no gpc”. This increase caused high contributions from particle deposition flux (NO3- and NH4+) to total nitrogen flux over the forest ecosystem (∼39 %), although the contribution of NH3 was still considerable. A dry-deposition scheme coupled with aerosol dynamics may be required to improve the predictive accuracy of chemical transport models for the surface concentration of inorganic reactive nitrogen.

The net ecosystem CO 2 exchange is the result of the imbalance between the assimilation process (gross primary production, GPP) and ecosystem respiration (RE). The aim of this study was to investigate temperature sensitivities of these processes and the effect of climate warming on the annual terrestrial net ecosystem CO 2 exchange globally in the boreal and temperate regions. A database of 403 site-years of ecosystem flux data at 101 sites in the world was collected and analyzed. Temperature sensitivities of rates of RE and GPP were quantified with Q 10 , defined as the increase of RE (or GPP) rates with a temperature rise of 10 °C. Results showed that on the annual time scale, the intrinsic temperature sensitivity of GPP ( Q 10 sG ) was higher than or equivalent to the intrinsic temperature sensitivity of RE ( Q 10 sR ). Q 10 sG was negatively correlated to the mean annual temperature (MAT), whereas Q 10 sR was independent of MAT. The analysis of the current temperature sensitivities and net ecosystem production suggested that temperature rise might enhance the CO 2 sink of terrestrial ecosystems both in the boreal and temperate regions. In addition, ecosystems in these regions with different plant functional types should sequester more CO 2 with climate warming.