Forest Types Research Articles

Classification of Lakebed Geologic Substrate in Autonomously Collected Benthic Imagery Using Machine Learning

Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.

Successional dynamics of carbon sequestration in forests of the eastern United States

AbstractCarbon sequestration in the forests of the eastern United States is an important offset to the country's CO2 emissions. Much of the eastern forestland is the product of reforestation of abandoned agricultural land or recovery following clear‐cutting over a century ago. This has led to concerns that eastern forests are even‐aged and that rates of carbon sequestration will decline as forests increase in carbon. Our objective was to examine the successional dynamics of forest carbon sequestration—using live tree carbon stocks as a proxy for successional status—for the six broadly defined forest types present in the region. We used datasets from the National Forest Inventory (NFI) for the 31 US states from Minnesota south to Louisiana and eastward and analyzed live tree net carbon increment for 2007–2021, the period for which NFI plot remeasurement data were available for all 31 states. Spruce–fir and southern pines were the only forest types for which carbon increment declined even modestly over a significant fraction of the range of live tree carbon observed in the region, and southern pine–hardwood forests were the only forests in which predicted sequestration in live tree carbon declined to zero within the range of carbon stocks observed in the region. Northern hardwood–conifer forests, oak–hickory forests, and lowland forests experienced either no decline or a slight increase in sequestration in live tree carbon across the range of successional status observed in the region. Thus, the average stocks of live tree carbon per unit area increased steadily over the study period. At some point in succession, rates of mortality are expected to increase and balance gross growth, leading to zero net sequestration in live tree carbon. Mature and old‐growth stands, however, are rare in all six forest types, and mortality as a fraction of live tree carbon for all six forest types declined across the range of successional status present in the region. Our results thus provide no support for the hypothesis that the successional dynamics of forests in this region can be expected to lead to near‐term declines in net carbon sequestration.

Overridingly increasing vegetation sensitivity to vapor pressure deficit over the recent two decades in China

Vapor pressure deficit (VPD) shows significant spatial and temporal variability in the context of global climate change, which is important for studying the implications of climate change on the structure and function of ecosystems to analyze the effects of VPD on vegetation dynamics. Spatial patterns of vegetation sensitivity to VPD have been recently investigated, however, the feedback of different vegetation types to VPD may vary depending on physiological characteristics, it is unclear how different types influence the sensitivity to VPD. In this study, the ERA5-Land reanalysis time-series dataset was used to analyze the spatial and temporal trends of VPD under different vegetation types. It was found that VPD showed an increasing trend in vegetated areas over the past 20 years with large spatial heterogeneity, generally increasing with drying conditions. On this basis, the spatial patterns of vegetation sensitivity to VPD and temporal trends in sensitivity were evaluated over the past 20 years in China using the enhanced vegetation index (EVI) and near-infrared reflectance of vegetation (NIRv) which can describe vegetation dynamics. The results show that the sensitivities under the two indices have high spatial consistency, with northeastern and central China showing positive sensitivities and southern China showing negative sensitivities, respectively. The positive sensitivities are relatively high for Deciduous Broadleaf Forests (DBF), Deciduous Needleleaf Forests (DNF), Grasslands (GL), and Croplands (CL) types, while the negative sensitivities are larger for Shrublands (SL) and Savannas (SA) types. Under different climatic zones, the sensitivity of CL and GL are independent of climatic zones (both showing positive), while the sensitivity of SL is negative in the Humid zone and positive in the Semi-Arid zone. Temporally, the sensitivity showed a slow increasing trend over the last 20 years. In terms of vegetation types, sensitivities of Evergreen Broadleaf Forests (EBF), DBF, GL and CL types showed a significant increasing trend (p < 0.05), except for the SL type, which showed a significant decreasing trend (p < 0.05). The trends of sensitivity are not affected by the differences in vegetation types (all of them show an increasing trend) under arid and semi-arid conditions, while dry sub-humid and humid have a greater impact on sensitivity trends. The finding of an overall increase in sensitivity suggests a mechanism of erratic change in vegetation growth under climate change. Notably, the increased sensitivity of certain vegetation types (especially GL and CL) suggests that these may become progressively vulnerable to increased VPD as global climate change persists, with the risk of moving from facilitation to inhibition of photosynthesis.

Variation in water utilization by mammal diversity in Khao Phaeng Ma Non-hunting area, Thailand

Access to suitable water sources is important for mammals. This study aimed to compared mammal diversity and water use among water springs, standard artificial ponds, and water pans within the Khao Phaeng Ma Non-Hunting Area in 2020 and 2021. Two camera traps were installed at each water sources for 749 nights with a total of 12 camera traps of 6 water sources. A total of 19,467 photographs were recorded comprising 13,777 photographs of gaur (Bos gaurus, vulnerable and the most important species in the area), and 5690 photographs of other mammals. In the wet season, relative use was highest at standard artificial pond number 2, which is established in the forest plantation area (4 × 4 m spacing, 12–20 m height, and 60%–80 % crown cover) and has a high volume of water, and at water pan number 1, which mimics a natural water spring in the man-made grassland and can supply water to mammals throughout the year. In the dry seasons, relative use was highest at water pan numbers 1 and 2; at the same time, other water sources dried up. During the study period, the number of mammal species was highest at water pan number 1 (10 species, diversity index [H′] = 1.38), and water pan number 2 (11 species, H′ = 1.75). Grazers and browsers, including gaur, sambar deer (Rusa unicolor), northern red muntjac (Muntiacus vaginalis), omnivores (e.g. wild boar, Sus scrofa), and Asian black bear (Ursus thibetanus), used the water pan in the artificial grassland and standard artificial pond in the forest plantation rather than the water spring in the dry evergreen forest. Beside forest types, the use of water springs was associated with water period (months), while the use of standard artificial pond and water pans was associated with water surface area, water depth, altitude, species diversity, and species richness, and number of mammals photographed. The results show that water pans were more suitable for utilization by mammals than are other water sources.

Effects of different forest types on soil microbial biomass and enzyme activities in degraded red soil of subtropical region

Effects of different forest types on soil microbial biomass and enzyme activities in degraded red soil of subtropical region

Verified hypotheses on the "nurse" and "burial" effects on introduced Quercus rubra regeneration in a mesic Scots pine forest.

A previous study on the encroachment of North American northern red oak Quercus rubra L. into the mesic Scots pine forest (in central Poland) revealed high abundances of seedlings and saplings under shrubs, with lower abundances in open areas or clumps of bilberry Vaccinium myrtillus L. It was unclear whether the regeneration success of Q. rubra is enhanced by the presence of shrubs due to their "nurse effect", and how burying acorns of different sizes in soil or moss affects the survival of oak seeds and seedlings (a "burial effect"). Results of a previous observational study were verified in an experimental study: a pool of 900 large-, medium-, and small-sized acorns was sown under moss cover in open areas and within bilberry clumps and in soil under shrubs in 2018 and monitored for 3 years in natural conditions. The majority of sown acorns were lost, mainly due to acorn pilferage, lack of germination and the death of sprouting acorns. However, acorn and seedling survival depended significantly on acorn size and differed among the microsites studied. Viable seedlings were twice as likely to develop from large- and medium-sized as from small-sized acorns, and they grew mainly from acorns sown under moss cover, confirming a positive "burial effect." Seedling survival was three times higher in bilberry and open areas, than under shrubs; however, seedlings "nursed" by shrubs were less threatened by large ungulates. Only a small part of the pool of sown acorns contributes to the reproductive success of Q. rubra in the mesic Scots pine forest. Microsites characteristic to this type of forest are suitable for northern red oak regeneration; however, bilberry favors acorn survival and germination and early seedling growth, moss cover favors acorn survival and germination, while shrubs protect surviving seedlings from herbivory.

Forest type identification by combining multi-temporal GF-6 WFV and Sentinel-2 data

Forest type identification by combining multi-temporal GF-6 WFV and Sentinel-2 data

Optical flow of temperature reveals climate change patterns for agriculture and forestry

The study of climate change's impact on terrestrial ecosystems is crucial for achieving societal and economic sustainability and human well-being. Domains like agriculture and forestry respond to climate change similarly to other terrestrial natural biomes, experiencing reductions in productivity, migration, and loss of biodiversity. However, there is a research gap in understanding climate velocity for different land cover and land use types, which could reveal vulnerability patterns in agriculture and forestry. To address this gap, we present the first study of climate velocity for major land cover and land use classes with a focus on major crop growing regions and functional forest types at the continental level. To enable this analysis, we introduce a new approach for estimating climate velocity based on optical flow. This approach allows us to conduct a global study, improve ecosystem interconnection representation, and reduce the model's sensitivity to noisy data and parametrization. Our study highlights the significant vulnerability to climate change of agriculture as a land cover type with a climate velocity 15% higher than of other vegetation land cover classes. Furthermore, the analysis of climate velocity for functional tree types reveals the highest expected impact on deciduous and evergreen needleleaf trees primarily concentrated in regions with the highest climate velocity, especially in sub-polar and temperate climates. Conversely, tropical forests dominated by evergreen broadleaf tree types exhibits marked variations in climate velocity with the highest rates in South America and Africa and three times lower in Asia. Additionally, our analysis of climate velocity for agriculture shows that North American croplands experience the highest climate velocity exceeding the global average by 32%. This trend is consistent for major crop types such as soybean that have higher climate velocity than globally for 49%, rapeseed and sunflower for 39%, cotton for 35%, maize for 32%, and wheat for 30%. Notably, areas dedicated to cereals, sugar beet, and sunflowers are located in zones with climate velocities higher than the global average by 15%, 12%, and 9%, respectively. These patterns indicate potential shifts in the agriculture and forestry structures in the near future that coherent with recent climate change studies and will have significant impact on the socio-economic dimension of humanity sustainability.

2021–2022年广东南岭站日尺度气象数据集

The mountainous forest and biodiversity ecological functional area of the Nanling Mountain forest ecosystem is one of the 25 key ecological functional areas in China, covering a variety of forest vegetation types, including tropical and subtropical moist broadleaf forests, coniferous broad-leaved evergreen mixed forest, and mountain top evergreen broad-leaved dwarf forest. The tropical and subtropical moist broadleaf forests are the most typical vegetation type in the Nanling Mountains. Monitoring the meteorological elements in the community can help understand the response mechanism of the tropical and subtropical moist broadleaf forests in the Nanling Mountains to climate change. Based on the Nanling Forest Ecosystem National Field Scientific Observation Research station ("Nanling Station" for short) in the Nanling Mountains, Guangdong, we carried out positioning research in Nanling National Nature Reserve. In this paper, we disclosed the raw data of 10 min average wind speed, precipitation, air temperature, air pressure, solar radiation (i.e. total radiation, reflected radiation, ultraviolet radiation, net radiation, photosynthetically active radiation) as well as relative humidity continuously collected in the subtropical evergreen broad-leaved forest area of the Nanling Station from 2021-2022 on a daily scale after data processing, quality control and evaluation. The dataset accessible to the public can serve as a valuable resource for further insights into the Nanling Mountain Forest Ecosystem, and provide foundation for efforts related to the restoration and protection of forest ecosystems.

2010–2014年哀牢山亚热带常绿阔叶林土壤呼吸数据集

Subtropical forests, as the largest forest type in China, play an important role in regulating global climate change and maintaining atmospheric carbon balance. The carbon emitted by soil through respiration is the main contributor of atmospheric CO2 levels, so even slight changes in soil carbon pool can significantly affect the concentration of atmospheric CO2. Therefore, at present, the magnitude and dynamic change characteristics of soil carbon storage in subtropical forests are attached great importance to. Ailao Mountain in Yunan Province stands as a crucial region for the distribution of subtropical forests in China. This study used a multichannel automated chamber system to estimate soil respiration in a subtropical evergreen broad-leaved forest ecosystem of Ailao Mountain. Ailao Mountain Station for Subtropical Forest Ecosystem Studies is a national field station and a basic observation station of the Chinese Ecosystem Research Network. We gathered soil respiration data from the subtropical evergreen broad-leaved forest in Ailao Mountain from 2011 to 2014, including soil temperature 5cm (TS), soil moisture content 10cm (SWC) and soil respiration data (RS), organized at daily, monthly and annual scales. This dataset is of great significance in revealing the effects of climate change on soil ecological processes in subtropical evergreen broad-leaved forests. It can facilitate precise evaluation of soil organic carbon emissions and forest ecosystem management, and provide both empirical and theoretical basis for further research on the effects of global changes (e.g. climate warming) on soil respiration components, especially with a focus on soil organic carbon emissions.

Atmospheric dryness removes barriers to the development of large forest fires

Large forest fires have far-reaching impacts on the environment, human health, infrastructure and the economy. Forest fires become large when all forest types across a landscape are dry enough to burn. Mesic forests are the slowest to dry and can act as a barrier to fire growth when they are too wet to burn. Therefore, identifying the factors influencing fire occurrence in mesic forests is important for gauging fire risk across large landscapes. We quantified the key factors influencing the likelihood that an active wildfire would propagate through mesic forest. We analysed 35 large forest fires (> 2500 ha) that occurred in Victoria, Australia where mesic and drier eucalypt forests are interspersed across mountainous terrain. We used a random forest model to evaluate 15 meteorological, topographic and disturbance variables as potential predictors of fire occurrence. These variables were extracted for points within burnt and unburnt patches of mesic forest. The likelihood of an active wildfire spreading through mesic forest increased by 65 % as vapour pressure deficit (VPD, i.e., atmospheric dryness) rose from 2.5 to 7 kPa. Other variables had substantially less influence (< 20 % change in fire occurrence) and their effects were further reduced when VPD was very high (> 6.5 kPa). Mesic forests were less likely to burn in areas with lower aridity, shallower slopes, and more sheltered topographic positions. Mesic forests 13–15 years following stand-replacing disturbance had 6 % higher chance of burning than long undisturbed forests (50 years post-disturbance). Overall, we show that topography and disturbance history cannot substantially counter the effects of high VPD. Therefore, the effectiveness of mesic forest as a barrier to the development of large forest fires is weakening as the climate warms. Our analysis also identifies areas less likely to burn, even under high VPD conditions. These areas could be prioritised as wildfire refugia.

DYNAMICS OF HEAVY METAL ACCUMULATION IN TROPHIC LEVELS OF FOREST ECOSYSTEMS

The aim of the study is to examine the accumulation of heavy metals (HMs) in trophic levels (soil, wood, tree leaves and fungi of various evolutionary origin) of forest ecosystems.&#x0D; Materials and Methods. The authors examined soil, wood, leaves and fungi in forests with different anthropogenic load intensity. The collecting grounds were selected according to forest management materials. In total, 26 grounds were examined. Sampling of soil and fungi of various trophic levels was carried out on different substrates, in different forest conditions and under different levels of technogenic impact. Leaf and wood samples were taken from phytopathogen-affected and healthy trees. Chemical sample analysis was carried out using a Kvant atomic absorption spectrophotometer.&#x0D; Results. The total heavy metal content in fungi is higher than in wood, but lower than in soil. The total heavy metal content in leaves of Norway maple affected by Rhytisma acerinum is higher compared to the leaves from heathy trees. Iron predominates among the heavy metals found in the fungi under consideration; cadmium content is minimal.&#x0D; Conclusion. The largest amount of accumulated heavy metals was found in the fruiting bodies of the facultative saprotroph, and the smallest amount was in the bodies of the facultative parasite. The forest type and growing conditions affect the heavy metal content in ecosystems.

Differences in dissolved organic matter (DOM) composition of soils from native eucalypt forests and exotic pine plantations impacted by wildfire in Southwest Australia

In recent decades, plantations of exotic species have transformed large tracts of forested landscapes, where they often form a mosaic with the surrounding native forest. Wildfires have also increased in frequency and intensity globally, impacting both plantation and native forests and affecting soil organic matter (SOM), including dissolved organic matter (DOM). DOM of soils is considered highly labile and likely sensitive to effects of fire and changes in land use. However, it is unclear how wildfire influences key characteristics of DOM in exotic plantations compared to native forest. In this study, we investigated the impacts of wildfire on chemical properties of DOM in exotic Pinus radiata plantations and adjacent native jarrah (Eucalyptus marginata) forest in southwest Australia. We coupled fluorescence excitation-emission matrix parallel factor analysis (EEM-PARAFAC) and 1H‐NMR with soil nutrient analyses to characterise soil DOM (0–5 cm) from burned and unburned plots of each forest type, four months after the fire. Four fluorescent components (humic-, fulvic-, microbial and protein-like substances) were derived from soil DOM using the PARAFAC model. DOM from burnt forest soils was predominantly of lower molecular weight (E2:E3) and contained a greater microbial-derived component and a lower fulvic component than unburnt forest. As expected, soil pH and labile inorganic P increased in both forest types after fire. By contrast, an increase in the amount of DOC after fire was only recorded in native forest, while δ15N signatures were more enriched in pine plantation soils after fire but not in native forest soils. Differences in impacts of fire on DOC and δ15N between forest types suggest a different response to fire according forest type, even though these differences were not evident above ground. The 1H NMR spectra of DOM revealed all samples were largely dominated by aliphatic structures. However, there were no significant differences in the overall spectra between forest types or between burnt and unburnt forests. Overall, our findings suggest that transformations in soil DOM after fire were affected by feedbacks between forest type and fire (where soils from pine plantations appeared to be more affected by fire).

Mixed signals of environmental change and a trend towards ecological homogenization in ground vegetation across different forest types

Forest ground vegetation may serve as an early warning system for monitoring anthropogenic global-change impacts on temperate forests. Climate warming may induce a decline of cool-adapted species to the benefit of more thermophilous plants. Nitrogen deposition has been documented to potentially result in soil eutrophication or acidification, which can increase the proportion of species with higher nutrient requirements and species impoverishment caused by competitive exclusion. Abiotic forest disturbances are changing the light conditions in the forest understorey environment. In this resurvey study, we tested the magnitude and direction of change in alpha (species richness) and beta (within-site dissimilarity) diversity and composition of forest ground vegetation in forests of different types in Slovenia over fifteen years. Using plant-derived characteristics (Ellenberg-type indicator values) and by testing a priori predictions concerning expected effects of environmental drivers, we show that the magnitude and direction of forest ground vegetation diversity and floristic changes varies greatly between forest sites. Divergent responses at different sites resulted in low net change of alpha and beta diversity and a weak overall environmental signal. The largest decrease in species number was observed in lowland oak-hornbeam forests, which were also among the sites with the greatest compositional shifts. Changes in beta diversity did not show any consistent trend, and anticipated floristic convergence was not confirmed when all sites were considered. Thermophilization was mainly detected in montane beech sites and alpine spruce forests whereas eutrophication signal was most significant on nutrient-poor sites. Vegetation responses were strongly dependent on initial site conditions. Shrinkage of ecological gradients (process of ecological homogenization) suggests that sites positioned at the ends of the gradients are losing their original ecological character and are becoming more similar to mid-gradient sites that generally exhibit smaller changes. Our results point to the importance of local stand dynamics and overstorey disturbances in explaining the temporal trends in forest ground vegetation. Ground vegetation in Slovenian forests is changing in directions also dictated by multiple regional and global change drivers.

Eurasian aspen (Populus tremula L.): Central Europe's keystone species 'hiding in plain sight'.

Knowledge of Eurasian aspen's (Populus tremula L.) ecological and growth characteristics is of high importance to plant and wildlife community ecology, and noncommercial forest ecosystem services. This research assessed these characteristics, identified aspen's habitat optimum, and examined causality of its current scarce distribution in central Europe. We analyzed a robust database of field measurements (4,656,130 stands) for forest management planning over 78,000 km2 of the Czech territory. Our analysis we used GIS techniques, with basic and multivariate statistics such as general linear models, ordination, and classification. Results describe a species of broad ecological amplitude that has heretofore attracted little research attention. Spatial analysis showed significant differences between aspen and other forest non-forest cover types. Additionally, we found significant association between the proportion of aspen in a stand, the size of forest property, and the forest category. The results demonstrate historic reasons for aspen's widespread presence, though contemporary occurrence is limited. This study advances the concept of a quantitatively based aspen ecological optimum (niche), which we believe may be beneficial for numerous aspen associates in the context of anticipated warming. Irrespective of local ecology (i.e., the realized aspen niche), the study confirms that profit-driven policy in forestry is chiefly responsible for historic aspen denudation in central Europe. Even so, we demonstrate that ample habitat is present. Further solutions for improving aspen resilience are provided to support these keystone systems so vital to myriad dependent flora and fauna.

Comparison of convolutional neural network and support vector machine for identification of forest types and burned areas

Comparison of convolutional neural network and support vector machine for identification of forest types and burned areas

Effects of forest type on carbon storage in the hilly region of Loess Plateau, China

The hilly region of the Loess Plateau has lush vegetation and high carbon sequestration potential. However, previous studies have not focused on differences in carbon storage of different forest types and their causes. This study aimed to explore the carbon storage of forest and identify the main influencing factors of carbon storage to provide basis for improving the carbon fixation capacity of planted forest in the region. Broad-leaved, coniferous, and mixed forests at different altitudes were selected from the Ziwuling Mountains in the Loess hilly region. The carbon storage as well as physical and chemical characteristics of the vegetation and soil samples from different soil layers were measured. The vegetation factor, terrain factor, and soil factor of the sample plot were evaluated by Mantel test and redundancy analysis (RDA). The carbon storage of the mixed forest (138.87 MgC hm−2) showed the highest carbon storage compared to broad-leaved forest (131.97 MgC hm−2) and coniferous forest (113.62 MgC hm−2) in the loess hilly region. The carbon storage of different components followed the order of soil carbon storage, vegetation carbon storage, and litter carbon storage. The soil organic carbon content and forest type had the highest explanations for total carbon storage, accounting for 57 and 26.9% of the variance, respectively. This indicates that forest type is an important factor affecting carbon storage, and selecting mixed forests can achieve better results when creating and transforming carbon sink forests.

Seed‐dispersal mode and habitat connectivity underpin variation in carbon stocking between Brazilian biomes

Abstract In tropical forests, about 60%–80% of woody plant species depend on animal–plant interactions for dispersal. The dependence on animal species for dispersal makes this interaction very fragile in the face of anthropogenic changes in land use. Disrupting seed‐dispersal processes, principally zoochoric dispersal, could significantly alter the long‐term carbon storage potential of tropical forests. An important question is how landscape structure changes tree carbon stocks in different types of tropical vegetation and how variation is mediated by the dispersal mode of animal (zoochoric) or abiotic (non‐zoochoric) seeds. We focused on tree plots at 126 sites in Brazil spanning four types of forest and savanna vegetation, and calculated carbon stored in zoochoric, non‐zoochoric, and large frugivore‐dispersed species. Our results showed that carbon stocks in zoochoric species and non‐zoochoric species differ significantly among vegetation types, with rainforests having higher stocks in zoochoric species and deciduous seasonally dry tropical forests having higher values in non‐zoochoric species. A greater area of native vegetation promotes higher proportions of carbon stocks dispersed by large frugivore species, whereas a higher mean shape index reduces this proportion. Synthesis. This study highlights that seed‐dispersal type underpins the variation in carbon stocks between vegetation types and that the maintenance of habitat of large dispersers and connectivity are key for retaining carbon stocks in zoochoric species, particularly in rainforest and cerrado sensu stricto.

Assessment of Temperate Deciduous Forest Communities and Structures after Restoration through the Multi-Reference Ecosystems Framework

The reference forest serves as a model for forest ecosystem restoration and can be employed to assess the vegetation of the Restored Forest, thereby confirming the success of restoration. When evaluating restoration, employing multireference forests is advantageous for discerning gradual changes in Restored Forests. However, in previous studies, their utilization has been limited to comparisons with individual ecosystems. Therefore, this study investigates the status of Restored Forests in previously damaged areas and their resemblance to reference forests across four forest types, namely Climax Forest (CF), Secondary Forest (SF), Restored Forest (RF), and Planted Forest (PF). Reference forests, serving as model targets for restoration, include CF and SF, while RF and PF represent the restoration forests. Six target sites within two temperate deciduous forests (Quercus acutissima and Quercus variabilis) were selected, and a comparative analysis of species diversity, dominance, and evenness was conducted. This study revealed that the dominant species in the top canopy of restoration forests mirrored those in reference forests, with Q. variabilis and Q. acutissima being prevalent. A similarity index of over 60% and a high correlation of 0.987 were observed in the top canopy layer between the reference and restored ecosystems (CF-RF/SF-PF). These findings enhance our understanding of the current status of Restored Forests and advocate for the utilization of multiple reference forests for successful restoration efforts.

Effects of Transformation of Inefficient Camellia oleifera Plantation on Soil Quality and Fungal Communities

Camellia oleifera, a key economic forestry species in southern China, struggles with low productivity due to suboptimal planting management. Recently, transforming old or unadopted varieties of C. oleifera plantations has been recognized as a means to enhance economic benefits and production. However, the impact of these transformations on soil properties and fungal communities has received little attention. In this study, we targeted pre-renewal old C. oleifera and post-renewal young C. oleifera, Pinus massoniana, and Cunninghamia lanceolata. Through field sampling and soil physicochemical property analysis, we developed a soil quality evaluation system that effectively analyzes fungal community structures and identifies key arbuscular mycorrhizal fungi (AMF) species for soil health. We found that the soil quality evaluation system for this region comprises pH, TK, AK, NO3−, PO4− BG, ACP, F.simpson, AMF.shannon, and AMF.ace, which collectively indicated significant improvements in soil quality following transformation. Notably, the nutritional characteristics of the dominant fungal communities underwent marked changes, with an increase in pathogenic fungi in young C. oleifera and an expansion of ectomycorrhizal fungi in P. massoniana forests. The AMF communities in all four types of forest exhibited aggregation, and Scutellospora and Diversispora emerged as key species in the AMF community of C. oleifera. Additionally, Mortierella and Trichoderma were found to enhance plant resistance to pathogenic fungi. This study demonstrates that forestland transformation positively impacts soil quality and fungal community structure in C. oleifera, which provides valuable insights for future soil management in the region, both in terms of soil quality evaluation and fungal conservation.