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Here, we investigated the capabilities of a lightweight unmanned aerial vehicle (UAV) photogrammetric point cloud for estimating forest biophysical properties in managed temperate coniferous forests in Japan, and the importance of spectral information for the estimation. We estimated four biophysical properties: stand volume (V), Lorey’s mean height (HL), mean height (HA), and max height (HM). We developed three independent variable sets, which included a height variable, a spectral variable, and a combined height and spectral variable. The addition of a dominant tree type to the above data sets was also tested. The model including a height variable and dominant tree type was the best for all biophysical property estimations. The root-mean-square errors (RMSEs) for the best model for V, HL, HA, and HM, were 118.30, 1.13, 1.24, and 1.24, respectively. The model including a height variable alone yielded the second highest accuracy. The respective RMSEs were 131.74, 1.21, 1.31, and 1.32. The model including a spectral variable alone yielded much lower estimation accuracy than that including a height variable. Thus, a lightweight UAV photogrammetric point cloud could accurately estimate forest biophysical properties, and a spectral variable was not necessarily required for the estimation. The dominant tree type improved estimation accuracy.

• Disturbances have altered community dynamics in boreal forests with unknown consequences for belowground ecological processes. Soil fungi are particularly sensitive to such disturbances; however, the individual response of fungal guilds to different disturbance types is poorly understood. • Here, we profiled soil fungal communities in lodgepole pine forests following a bark beetle outbreak, wildfire, clear-cut logging, and salvage-logging. Using Illumina MiSeq to sequence ITS1 and SSU rDNA, we characterized communities of ectomycorrhizal, arbuscular mycorrhizal, saprotrophic, and pathogenic fungi in sites representing each disturbance type paired with intact forests. We also quantified soil fungal biomass by measuring ergosterol. • Abiotic disturbances changed the community composition of ectomycorrhizal fungi and shifted the dominance from ectomycorrhizal to saprotrophic fungi compared to intact forests. The disruption of the soil organic layer with disturbances correlated with the decline of ectomycorrhizal and the increase of arbuscular mycorrhizal fungi. Wildfire changed the community composition of pathogenic fungi but did not affect their proportion and diversity. Fungal biomass declined with disturbances that disrupted the forest floor. • Our results suggest that the disruption of the forest floor with disturbances, and the changes in C and nutrient dynamics it may promote, structure the fungal community with implications for fungal biomass–C.

Fires shape the biogeochemistry and functioning of many ecosystems, and fire frequencies are changing across much of the globe. Frequent fires can change soil carbon (C) and nitrogen (N) storage by altering the quantity and chemistry of plant inputs through changes in plant biomass and composition as well as the decomposition of soil organic matter. How decomposition rates change with shifting inputs remains uncertain because most studies focus on the effects of single fires, where transient responses may not reflect responses to decadal changes in burning frequencies. Here, we sampled seven sites exposed to different fire frequencies. In four of the sites, we intensively sampled both soils and plant communities across four ecosystems in North America and Africa spanning tropical savanna, temperate coniferous savanna, temperate broadleaf savanna, and temperate coniferous forest ecosystems. Each site contained multiple plots burned frequently for 33–61 years and nearby plots that had remained unburned over the same period replicated at the landscape scale. Across all sites, repeatedly burned plots had 25–185% lower bulk soil C and N concentrations but also 2–10-fold lower potential decomposition of organic matter compared to unburned sites. Soil C and N concentrations and extracellular enzyme activities declined with frequent fire because fire reduced both plant biomass inputs into soils and dampened the localized enrichment effect of tree canopies. Examination of soil extracellular enzyme activities revealed that fire decreased the potential turnover of organic matter in the forms of cellulose, starch, and chitin (𝑃 < 0.0001) but not polyphenol and lignin (𝑃 = 0.09), suggesting a shift in soil C and N cycling. Inclusion of 𝛿13C data from three additional savanna sites (19–60 years of altered fire frequencies) showed that soil C losses were largest in sites where estimated tree inputs into soils declined the most (𝑟² = 0.91, 𝑃 < 0.01). In conclusion, repeated burning reduced C and N storage, consistent with previous studies, but fire also reduced potential decomposition, likely contributing to slower C and N cycling. Trees were important in shaping soil C and N responses across sites, but the magnitude of tree effects differed and depended on how tree biomass inputs into soil responded to fire.

Although the importance of bryophyte colonies on tree seedling establishment on downed logs is widely known, the mechanisms of how various bryophyte species affect seedlings are poorly understood. In this study, we analyzed the relationships between bryophyte community (colony coverage and thickness of each species) and tree seedlings growing on logs along the decay process. In an old-growth subalpine coniferous forest dominated by spruce, juvenile seedling density of spruce on downed logs was positively associated with the coverage of a liverwort Scapania bolanderi and the thickness of the bryophyte colonies, but was negatively associated with the coverage of a moss Hylocomium splendens . Coverage of S. bolanderi was also associated with shoot length of spruce seedlings, but this effect was negative. Coverage of S. bolanderi increased with log decay and became the most dominant species in the penultimate stage of log decomposition, but was replaced by thicker H. splendens in the final decay stage. These results suggested that S. bolanderi colonies, dominant only in the mid-stage of log decomposition, may indicate a ‘window of time’ for spruce seedlings to colonize on logs in this old-growth subalpine coniferous forest. Thus, when trying to understand sustainable regeneration mechanisms in subalpine forests, this interaction should be considered.

[This corrects the article DOI: 10.1371/journal.pone.0263488.].[This corrects the article DOI: 10.1371/journal.pone.0263488.].

Old‐growth coniferous forests of the Pacific Northwest are among the most productive temperate ecosystems and have the capacity to store large amounts of carbon for multiple centuries. To date, there are considerable gaps in modeling ecosystem fluxes and their responses to physiological constraints in these old‐growth forests. These model shortcomings limit our ability to understand and project how the old‐growth forests of the Pacific Northwest will respond to global climate change. This study applies the cohort‐based Ecosystem Demography Model 2 (ED2) to the Wind River Experimental Forest (Washington, USA), a well‐studied old‐growth Douglas‐fir–western hemlock ecosystem. ED2 is calibrated and validated using an extensive suite of forest inventory, eddy covariance, and biophysical observations. ED2 is able to reproduce observed forest composition and canopy structure, and carbon, water, and energy fluxes at the site. In the simulations, the effect of limited water supply on ecosystem carbon fluxes is mediated primarily by the forest's gross primary productivity (GPP) response, rather than its heterotrophic respiration response. The simulation indicates that stomatal conductance is mainly determined by soil moisture during periods of low vapor pressure deficit (VPD). However, when VPD is high, stomatal conductance is greatly reduced regardless of soil moisture status. During summer droughts, reduced soil moisture and increased VPD result in considerable stomatal closure and GPP reduction, which in turn decreases net carbon uptake. Cohort‐based scheme integrates all canopy layers (species) that have distinct sensitivity to microclimate and respond distinctly to drought. This study is an initial first step to explore the potential importance of cohort‐based model in simulating forest with complex structure, and to lay the foundation for applying cohort‐based model at regional scales across the Pacific Northwest.

Coniferous forest soils have an indispensable ecological role in the global cycles of nutrients on Earth. Despite the fact that microbial communities in this ecosystem were subject of multiple studies, the involvement of individual taxa in the processes of organic matter transformation and the functional roles of dominant and active bacteria are largely unknown. Here, we have performed a comprehensive isolation effort to obtain multiple dominant bacterial taxa from a Picea abies forest soil and provide their physiological characterization. This information allows us to link ecological traits with groups of microorganisms. In the study, conventional culture techniques at acidic pH and low-nutrient content led to the recovery of 299 bacterial isolates. The isolates represented operational taxonomic units (OTUs) that contained 20 and 32 % of all bacterial genomes detected in the litter and soil by 16S amplicon analysis, including some of those bacterial strains representing the most abundant and active OTUs. These included also several isolates of the still underexplored phylum of the Acidobacteria, all of them belonging to the subdivision 1 of the phylum. Acidobacterial isolates produced the widest range of enzymes among all isolates and highest enzyme activities in acidic conditions. Moreover, members of the Acidobacteria represented more than 50 % of the isolates able to grow on disaccharides produced during the breakdown of cellulose, chitin, and starch. Our results indicate that Acidobacteria may play an important ecological role by degrading polysaccharides of plant and fungal origin in the important ecosystems of acidic coniferous forests.

Rainfall use efficiency (RUE) of subtropics evergreen coniferous forests and RUE spatial patterns in Chinese subtropical zone were estimated. RUE and ecosystem net primary productivity (NPP) spatial distribution, as well as the relationship between RUE and rainfall were particularly focused. RUE of subtropical evergreen coniferous forests and the spatial patterns were estimated based on the data collected from the related weather stations and peer-reviewed literatures. In our study, a gradually increasing tendency of NPP from northwestern to southeastern part of the subtropical zone is observed. No significant differences in RUE among these tree species are visible. RUE of the evergreen coniferous forests reduces as the rainfall increases. RUE reaches the peak when rainfall is less than 700 mm. However, the distribution of RUE is not evident. In linear regression, longitude, latitude, and PAR account for approximately 1.4% of the variability in RUE. These findings suggest that the RUE of evergreen coniferous forests in southern China has a functional convergence.

Leaf functional traits are widely used to detect and explain adaptations that enable plants to live under various environmental conditions. This study aims to determine the difference in leaf functional traits among four forest types of Pinus massoniana coniferous and broad‐leaved mixed forests by leaf morphological, nutrients, and stoichiometric traits in the subtropical mountain, Southeastern China. Our study indicated that the evergreen conifer species of P. massoniana had higher leaf dry matter content (LDMC), leaf C content, C/N and C/P ratios, while the three deciduous broad‐leaved species of L. formosana, Q. tissima, and P. strobilacea had higher specific leaf area (SLA), leaf N, leaf P nutrient contents, and N/P ratio in the three mixed forest types. The results showed that the species of P. massoniana has adapted to the nutrient‐poor environment by increasing their leaf dry matter for higher construction costs thereby reducing water loss and reflects a resource conservation strategy. In contrast, the three species of L. formosana, Q. tissima, and P. strobilacea exhibited an optimized resource acquisition strategy rather than resource conservation strategy in the subtropical mountain of southeastern China. Regarding the four forest types, the three mixed forest types displayed increased plant leaf nutrient contents when compared to the pure P. massoniana forest, especially the P. massoniana–L. formosana mixed forest type (PLM). Overall, variation in leaf functional traits among different forest types may play an adaptive role in the successful survival of plants under diverse environments because leaf functional traits can lead to significant effects on leaf function, especially for their acquisition of nutrients and use of light. The results of this study are beneficial to reveal the changes in plant leaf functional traits at the regional scale, which will provide a foundation for predicting changes in leaf traits and adaptation in the future environment. This study aims to determine the difference in leaf functional traits among four forest types of Pinus massoniana coniferous and broad‐leaved mixed forests by leaf morphological, nutrients, and stoichiometric traits in the subtropical mountain, Southeastern China.

In tree Aboveground Biomass (AGB) estimation, the traditional harvest method is accurate but unsuitable for a large-scale forest. The airborne Light Detection And Ranging (LiDAR) is superior in obtaining the point cloud data of a dense forest and extracting tree heights for AGB estimation. However, the LiDAR has limitations such as high cost, low efficiency, and complicated operations. Alternatively, the overlapping oblique photographs taken by an Unmanned Aerial Vehicle (UAV)-loaded digital camera can also generate point cloud data using the Aerial Triangulation (AT) method. However, limited by the relatively poor penetrating capacity of natural light, the photographs captured by the digital camera on a UAV are more suitable for obtaining the point cloud data of a relatively sparse forest. In this paper, an electric fixed-wing UAV loaded with a digital camera was employed to take oblique photographs of a sparse subalpine coniferous forest in the source region of the Minjiang River. Based on point cloud data obtained from the overlapping photographs, a Digital Terrain Model (DTM) was generated by filtering non-ground points along with the acquisition of a Digital Surface Model (DSM) of Minjiang fir trees by eliminating subalpine shrubs and meadows. Individual tree heights were extracted by overlaying individual tree outlines on Canopy Height Model (CHM) data computed by subtracting the Digital Elevation Model (DEM) from the rasterized DSM. The allometric equation with tree height (H) as the predictor variable was established by fitting measured tree heights with tree AGBs, which were estimated using the allometric equation on H and Diameter at Breast Height (DBH) in sample tree plots. Finally, the AGBs of all of the trees in the test site were determined by inputting extracted individual tree heights into the established allometric equation. In accuracy assessment, the coefficient of determination (R2) and Root Mean Square Error (RMSE) of extracted individual tree heights were 0.92 and 1.77 m, and the R2 and RMSE of the estimated AGBs of individual trees were 0.96 and 54.90 kg. The results demonstrated the feasibility and effectiveness of applying UAV-acquired oblique optical photographs to the tree AGB estimation of sparse subalpine coniferous forests.