Evergreen Broadleaf Forest Research Articles

The heterogeneous response in leaf traits among seasons and plant types of an evergreen broadleaf forest in western China to nitrogen addition was regulated by fertilization intensity

The heterogeneous response in leaf traits among seasons and plant types of an evergreen broadleaf forest in western China to nitrogen addition was regulated by fertilization intensity

Eucalyptus and Native Broadleaf Mixed Cultures Boost Soil Multifunctionality by Regulating Soil Fertility and Fungal Community Dynamics.

The growing recognition of mixed Eucalyptus and native broadleaf plantations as a means of offsetting the detrimental impacts of pure Eucalyptus plantations on soil fertility and the wider ecological environment is accompanied by a clear and undeniable positive impact on forest ecosystem functions. Nevertheless, the question of how mixed Eucalyptus and native broadleaf plantations enhance soil multifunctionality (SMF) and the mechanisms driving soil fungal communities remains unanswered. In this study, three types of mixed Eucalyptus and native broadleaf plantations were selected and compared with neighboring evergreen broadleaf forests and pure Eucalyptus plantations. SMF was quantified using 20 parameters related to soil nutrient cycling. Partial least squares path modeling (PLS-PM) was employed to identify the key drivers regulating SMF. The findings of this study indicate that mixed Eucalyptus and native broadleaf plantations significantly enhance SMF. Mixed Eucalyptus and native broadleaf plantations led to improvements in soil properties (7.60-52.22%), enzyme activities (10.13-275.51%), and fungal community diversity (1.54-29.5%) to varying degrees compared with pure Eucalyptus plantations. Additionally, the mixed plantations exhibit enhanced connectivity and complexity in fungal co-occurrence networks. The PLS-PM results reveal that soil properties, fungal diversity, and co-occurrence network complexity directly and positively drive changes in SMF. Furthermore, soil properties exert an indirect influence on SMF through their impact on fungal diversity, species composition, and network complexity. The findings of this study highlight the significant role of mixed Eucalyptus and native broadleaf plantations in enhancing SMF through improved soil properties, fungal diversity, and co-occurrence network complexity. This indicates that incorporating native broadleaf species into Eucalyptus plantations can effectively mitigate the negative impacts of monoculture plantations on soil health and ecosystem functionality. In conclusion, our study contributes to the understanding of how mixed plantations influence SMF, offering new insights into the optimization of forest management and ecological restoration strategies in artificial forest ecosystems.

Successive monoculture of Eucalyptus spp. alters the structure and network connectivity, rather than the assembly pattern of rhizosphere and bulk soil bacteria

Eucalyptus as a fast-growing timber tree plays a crucial role in maintaining wood supplication and ecosystem balance worldwide. Nonetheless, the management practices of Eucalyptus plantation in southern China have resulted in productivity decline and soil degradation due to high-intensity successive cultivation. Soil bacteria is a sensitive indicator of soil quality, how does the successive planting of Eucalyptus regulate the soil bacterial community structure for instance the abundance of oligotrophic bacteria, network complexity, and soil bacteria assembly remain ambiguity. To explicate the underlying influencing mechanisms of successive cultivation of Eucalyptus plantations on soil bacterial community structure. Four harvests of Eucalyptus plantations that underwent 0, 1, 2, and 3 times of harvesting were conducted to examine variations in the bacterial community between rhizosphere and bulk soils after successive planting of Eucalyptus. An adjacent evergreen broadleaf forest was employed as control. The present study revealed that successive planting of Eucalyptus increased and reduced the relative abundance of Chloroflexi (oligotrophic bacteria) and Proteobacteria (copiotrophic bacteria), respectively. Continuous planting of Eucalyptus did not modify the assembly pattern of soil bacterial communities, which was governed by stochastic processes. Successive planting of Eucalyptus decreased co-occurrence network complexity, and elevated the proportion of rare microorganisms in the keystone bacterial taxa. Soil particle size composition (clay, silt, sand) indirectly influenced the structure of soil bacterial communities by directly affecting pH, carbon, nutrients, and their stoichiometric ratios. Improving soil physical structure, increasing the input of soil carbon, nitrogen, and other nutrient resources, and maintaining a balanced resource allocation may be effective strategies for ensuring enhanced productivity and sustainable utilization of soil in successive Eucalyptus plantations.

Constant isometric scaling of soil carbon to nitrogen in Moso bamboo-invaded evergreen broadleaf forests in subtropical China

Constant isometric scaling of soil carbon to nitrogen in Moso bamboo-invaded evergreen broadleaf forests in subtropical China

Changes in soil organic carbon stocks and mineralization following the replacement of secondary evergreen broadleaf forests with tea (Camellia sinensis L.) plantations

AbstractTea plantation ecosystems have a strong potential to sequester carbon (C) and reduce CO2 emissions. However, the effects of different tea planting periods on soil organic carbon (SOC) stocks and mineralization and related mechanisms are unclear. To address this knowledge gap, we investigated the effects of replacing evergreen broadleaf forests with tea plantations on SOC stocks and mineralization rates by examining alterations in SOC pools and composition, microbial community composition, functional genes related to C‐cycling and enzyme activities. The SOC content in forest, 30‐, 50‐ and 100‐year‐old tea plantations were 1.91%, 2.37%, 2.87% and 3.69%, respectively, in the 0–20 cm soil depth (100‐year‐old > 50‐year‐old > 30‐year‐old > forest). Cumulative CO2–C emissions increased by 38.1% (114 mg C kg−1 soil), 49.9% (157 mg C kg−1 soil), and 100.2% (171 mg C kg−1 soil) compared to forest soil (228 mg C kg−1 soil) after tea had been grown for 30, 50 and 100 years, respectively; however, cumulative CO2 emissions did not differ significantly between the 30‐ and 50‐year‐old plantations. The rate of SOC mineralization was positively related to particulate organic carbon (POC), water‐soluble organic carbon (WSOC), microbial biomass C (MBC), and O‐alkyl C contents, as well as β‐glucosidase/cellobiohydrolase activities and GH48/cbhI abundance; by contrast, the SOC mineralization rate was negatively correlated with the aromatic C content. More importantly, bacteria and fungi related to SOC mineralization, such as WPS‐2 and Acidobacteria, and Sordariomycetes, Tremellomycetes, Mortierellomycetes and Agaricomycetes, respectively, had high relative abundances. Our results indicate that replacing forests with tea plantations enhanced both SOC stocks and mineralization rates and that this effect was positively correlated with tea cultivation time. We reveal that an increased length of the tea planting period was conducive to increasing SOC stocks, and mitigating C losses in tea plantation soils is crucial for establishing an ecologically low‐C tea plantation system.

Forest evapotranspiration trends and their driving factors under climate change

Forest evapotranspiration (ET) is expected to increase under global warming. However, the relative contribution of the major drivers (such as leaf area index (LAI), climate forcing, atmospheric CO2, etc.) to long-term ET trends in forest is unclear. In addition, the effects of ET changes induced by driving factors and ET changes induced by forest area changes on total forest ET are still remain to be determined. We aim to explore long-term ET trends in global forest and assess the relative contributions of their influencing factors by a remote sensing-based carbon–water coupling model, the second edition of the Penman-Monteith-Leuning (PML-V2). The results showed that: 1) the ET of global forest increased slightly (11.30 ± 4.23 mm year−1 decade-1, p < 0.05), with the greatest increase observed in evergreen broadleaf forest (20.89 ± 6.96 mm year−1 decade-1, p < 0.01). 2) Simulation experiment indicated that upward global forest ET trend was mainly dominated by climate forcing change (56.71 %), increased LAI (5.07 %), albedo and emissivity change (−0.77 %) and increased CO2 (−37.45 %). Only mixed forest exhibited a decrease in ET trend, which was caused by CO2 concentration counteracted the increase trend of ET induced by climate forcing change and LAI increase, resulting in a decrease trend of ET. Different from broadleaf forests and MF, the increase of LAI in needleleaf forests caused a negative contribution of ET. 3) In the overall increasing trend of global forest ET, the driving factors played a dominant role (53.09 %) and the forest area played a secondary role (46.91 %). Our findings highlight the divergent responses of various forest types under climate change, which is beneficial to forest management and sustainable development.

Spatio-temporal dynamics of net primary productivity and the economic value of Spartina alterniflora in the coastal regions of China

This study employs an improved Carnegie–Ames–Stanford Approach (CASA) model to calculate the Net Primary Productivity (NPP) of Spartina alterniflora (SA) and various other land use/land cover types (LULC) across coastal China over multiple years. The research aims to provide significant theoretical and practical insights into carbon sink research in coastal zones, sustainable development, and resource management. Key findings include identifying the first εmax value of 2.219 g C/MJ for SA, addressing a critical data gap in CASA modeling research on invasive plants. SA's NPP exhibited higher values in Shanghai and Zhejiang due to factors such as genetic diversity, invasion duration, and tidal dynamics. In contrast, other LULC exhibited higher NPP values in southern and inland regions, characterized by greater vegetation cover and favorable growing conditions. In 2020, SA and other LULC sequestered 16.352 kt C and 0.821*106 kt C, respectively. From 2000 to 2020, the average annual NPP and total carbon storage of SA and other LULC increased significantly, primarily driven by Shanghai and deciduous needleleaf forests, respectively. Seasonal NPP trends followed summer> spring> autumn> winter, influenced by climate conditions and plant life activities. Economic assessments in 2020 estimated SA's carbon storage value at RMB0.409 billion (Market Value method) or RMB5.562 billion (Carbon Tax method), with RMB2.054 billion attributed to oxygen release values, underscoring its economic and ecological potential. Among other LULC, evergreen broadleaf forests showed the highest carbon storage value (RMB183.463 billion). The study emphasizes the critical role of all LULC in carbon storage and oxygen release, advocating for targeted conservation and land management strategies. It suggests that managing SA should balance stringent control in high-risk areas, lenient measures in low-risk areas, eradication of scattered populations, and maximizing ecological benefits in retention areas, with continuous monitoring and adaptive management strategies to balance conservation and development efforts.

Influence of photosynthetic active radiation on sap flow dynamics across forest succession stages in Dinghushan subtropical forest ecosystem

With the intensification of global change, forests are subjected to varying degrees of drought or high-temperature stress, which has an indelible impact on the growth of trees. However, knowledge on the response of sap flow to environmental changes in different types of forests is still rare, especially in China's subtropical forest ecosystem. Consequently, studying how different tree species regulate their sap flow in response to shifting environmental conditions is essential for understanding forest transpiration, water use efficiency, and drought stress resilience. Therefore, this study aimed to investigate the sap flow dynamics of seven tree species in five forest plots, i.e., pine forest (PF), two types of mixed conifer-broadleaf forests (MF1+MF2), monsoon evergreen broadleaved forest (MEBF), and montane monsoonal evergreen broad-leaf forest (MOBF) at Dinghushan National Reserve in Southern China, using the heat dissipation probe technique and synchronous environmental factor recordings. Results demonstrated a significant influence of photosynthetic active radiation (PAR) on sap flow across all tree species, with mean PAR values ranging from over 1200 to 425 μmol m−2 s−1, establishing it as the principal driving factor. This observation underscores the heightened responsiveness or sensitivity of tree species to variations in PAR as the forest undergoes development and maturation. The correlation between vapor pressure deficit (VPD) and tree sap flow decreased as succession progressed. Moreover, the influence of soil water content (SWC) on sap flow stability against environmental changes increased. Similar patterns were also found between the two MF, with MF-2 displaying ecological characteristics and environmental conditions more closely aligned with those of the late-successional MEBF. The study reveals the intricate relationship between environmental factors and sap flow regulation in tree species within a subtropical forest ecosystem. Addressing a comparative gap in sap flow correlation among dominant tree species at Dinghushan, it establishes a hydro-physiological foundation for understanding tree species substitution during forest succession. The results provide key insights for forest management and climate-related research. Future studies should delve into the long-term implications of observed sap flow dynamics, exploring their impact on tree species adaptability amid ongoing environmental changes.

Droughts and windstorms due to climate change increase variability in species and trait composition of a subtropical monsoon evergreen broadleaf forest in China

BackgroundClimate change is accelerating alterations in forest species and community composition worldwide, especially following extreme events like severe droughts and windstorms. Understanding these effects on subtropical forests is crucial for conservation and forest management, but it remains unclear whether the impacts are stochastic or deterministic. MethodsWe analyzed a unique dataset from a 1-ha permanent plot in a subtropical monsoon broadleaf evergreen forest in China, monitored over 26 years with six surveys from 1994 to 2020. The forest has been free from anthropogenic disturbances for over 400 years. In each survey, we measured all trees with a diameter at breast height (DBH) ​≥ ​1 ​cm, and recorded 11 plant functional traits relating to photosynthesis, wood properties, water use, and nutrient dynamics. Using this data, we calculated species and trait dispersion, assessing short-term (∼5 years) and long-term (26 years) trends in species and trait composition following severe droughts and windstorm events. ResultsSevere droughts, and subsequent droughts, increased both species and trait dispersion, while species composition converged, and trait dispersion remained relatively stable throughout the recovery period. Windstorm events led to increased species dispersion but decreased trait dispersion. We observed a clear directional shift in both species and trait composition under these climatic stressors, with a more pronounced increase in trait dispersion compared to species dispersion. ConclusionIn the short term (∼5 years), severe droughts and windstorms increased species composition divergence, while trait composition responses varied. Over 26 years, deterministic processes mainly drove community composition changes, especially for trait composition, although stochastic processes also played a role. These findings suggest enhancing forest resilience to climatic stressors by protecting adaptive species or increasing species diversity in management practices.

Landscape and conservation genetics of western black crested gibbons (Nomascus concolor) in China.

Despite decades of field study, very little is known about the molecular ecology of gibbons, particularly as it relates to their ability to disperse across degraded and fragmentary landscapes. The critically endangered western black crested gibbon (Nomascus concolor) has been reduced to a small, fragmented population with about 1300 individuals. In the largest population genetic study of free-ranging gibbons to date, we sampled 47 of these gibbons from 13 sites in China and generated 15 polymorphic autosomal microsatellite markers. We identify three population clusters of N. concolor in Yunnan centered in 1) the Wuliang and Ailao Mountains, 2) the Yongde Daxueshan Mountains, and 3) an isolated remnant near the border with Vietnam. Within the Wuliang Mountains, we identified four subclusters, three of which are bounded by high-altitude rhododendron forest, and one that is isolated from the main population by ~2 km of degraded forest and pasture. Least-cost path analysis and isolation by resistance modeling demonstrates that the population genetic distances among gibbons in Wuliangshan National Nature Reserve are significantly correlated with geographic paths that avoid use of high-altitude rhododendron forest in favor of evergreen broadleaf forest. Although these gibbons have likely undergone reductions in heterozygosity from recent consanguineous mating, we suggest that their active avoidance of inbreeding on the population level maintains higher than expected levels of genetic diversity. This research provides new insights into how gibbons interact with heterogeneous environments and expands our understanding of their molecular ecology and conservation genetics.

Diurnal Variation in Surface Incident Solar Radiation Retrieved by CERES and Himawari-8

The diurnal variation of surface incident solar radiation (Rs) has a significant impact on the Earth’s climate. Satellite-retrieved Rs datasets display good spatial and temporal continuity compared with ground-based observations and, more importantly, have higher accuracy than reanalysis datasets. Facilitated by these advantages, many scholars have evaluated satellite-retrieved Rs, especially based on monthly and annual data. However, there is a lack of evaluation on an hourly scale, which has a profound impact on sea–air interactions, climate change, agriculture, and prognostic models. This study evaluates Himawari-8 and Clouds and the Earth’s Radiant Energy System Synoptic (CERES)-retrieved hourly Rs data covering 60°S–60°N and 80°E–160°W based on ground-based observations from the Baseline Surface Radiation Network (BSRN). Hourly Rs were first standardized to remove the diurnal and seasonal cycles. Furthermore, the sensitivities of satellite-retrieved Rs products to clouds, aerosols, and land cover types were explored. It was found that Himawari-8-retrieved Rs was better than CERES-retrieved Rs at 8:00–16:00 and worse at 7:00 and 17:00. Both satellites performed better at continental sites than at island/coastal sites. The diurnal variations of statistical parameters of Himawari-8 satellite-retrieved Rs were stronger than those of CERES. Relatively larger MABs in the case of stratus and stratocumulus were exhibited for both hourly products. Smaller MAB values were found for CERES covered by deep convection and cumulus clouds and for Himawari-8 covered by deep convection and nimbostratus clouds. Larger MAB values at evergreen broadleaf forest sites and smaller MAB values at open shrubland sites were found for both products. In addition, Rs retrieved by Himawari-8 was more sensitive to AOD at 10:00–16:00, while that retrieved by CERES was more sensitive to COD at 9:00–15:00. The CERES product showed larger sensitivity to COD (at 9:00–15:00) and AOD (at 7:00–10:00) than Himawari-8. This work helps data producers know how to improve their future products and helps data users be aware of the uncertainties that exist in hourly satellite-retrieved Rs data.

Coordination of water use strategies and leaf economic traits in coexisting exotic and native woody species from evergreen and deciduous broadleaf forests

The leaf economics spectrum (LES) describes the covariation of traits relevant for carbon and nutrient economy in different plant species. However, much less is known about the correlation of LES with leaf water economy, not only because some woody species do not follow the rules, but also because they are rarely tested on the widespread, non-native, fast-growing trees. We hypothesized that fast-growing exotic species that spread on the fast side of the LES coordinate their water-use strategies (WUS) to maintain rapid growth, and that the pattern of coordination differs between evergreen and deciduous forests. Using 4 exotic and 4 native species from evergreen and deciduous broadleaf forests in China, we measured 17 traits of LES and WUS and analyzed their functional roles in different species groups. Our results suggest that LES plays a more important role in the coexistence of species within a community, while WUS contributes more to the distribution of species across different regions. The multidimensional coordination of LES and WUS could better explain the growth and distribution of different plant species and shed light on the coexistence of species from different forest types, especially fast-growing woody exotics.

Evaluating the Performance of the Enhanced Ross-Li Models in Characterizing BRDF/Albedo/NBAR Characteristics for Various Land Cover Types in the POLDER Database

The latest versions of the Ross-Li model include kernels that represent isotropic reflection of the surface, describe backward reflection of soil and vegetation systems, characterize strong forward reflection of snow, and adequately consider the hotspot effect (i.e., RossThick-LiSparseReciprocalChen-Snow, RTLSRCS), theoretically able to effectively characterize BRDF/Albedo/NBAR features for various land surface types. However, a systematic evaluation of the RTLSRCS model is still lacking for various land cover types. In this paper, we conducted a thorough assessment of the RTLSRCS and RossThick-LiSparseReciprocalChen (RTLSRC) models in characterizing BRDF/Albedo/NBAR characteristics by using the global POLDER BRDF database. The primary highlights of this paper include the following: (1) Both models demonstrate high accuracy in characterizing the BRDF characteristics across 16 IGBP types. However, the accuracy of the RTLSRC model is notably reduced for land cover types with high reflectance and strong forward reflection characteristics, such as Snow and Ice (SI), Deciduous Needleleaf Forests (DNF), and Barren or Sparsely Vegetated (BSV). In contrast, the RTLSRCS model shows a significant improvement in accuracy for these land cover types. (2) These two models exhibit highly consistent albedo inversion across various land cover types (R2 &gt; 0.9), particularly in black-sky and blue-sky albedo, except for SI. However, significant differences in white-sky albedo inversion persist between these two models for Evergreen Needleleaf Forests (ENF), Evergreen Broadleaf Forests (EBF), Urban Areas (UA), and SI (p &lt; 0.05). (3) The NBAR values inverted by these two models are nearly identical across the other 15 land cover types. However, the consistency of NBAR results is relatively poor for SI. The RTLSRC model tends to overestimate compared to the RTLSRCS model, with a noticeable bias of approximately 0.024. This study holds significant importance for understanding different versions of Ross-Li models and improving the accuracy of satellite BRDF/Albedo/NBAR products.

Different diversity patterns of butterfly and moth assemblages between deciduous and evergreen broad-leaf forests

In this study, we compared the diversity and abundance of two groups of Lepidopteran insects—butterflies and moths—across deciduous (DBL) and evergreen broad-leaved (EBL) tree communities in warm temperate forests. Over three years (from 2018 to 2020) at the Wando Arboretum, we used transect and point methods to sample butterflies and light traps to sample moths. Our findings revealed that the total estimated species richness was higher in EBL compared to DBL. Non-metric multidimensional scaling (NMDS) analysis confirmed distinct moth assemblages between the two tree communities, while butterfly assemblages did not exhibit such separation. The seasonal diversity patterns of butterflies in both forests differed significantly, whereas those of moths exhibited a similar trend with a peak in June. Beta diversity components indicated high turnover rates in moth assemblages across both tree communities and high nestedness in butterfly assemblages within the DBL. Although the diet breadth of butterflies and moths did not significantly differ between the two tree communities, the number of butterfly species per host plant was higher in DBL and that of moths was higher in EBL. Considering the ongoing vegetation transition from DBL to EBL, changes in forest structure—such as canopy openness and tree density—may adversely impact insect communities within DBL.

Spatial distribution patterns and intraspecific and interspecific spatial associations of Quercus myrsinifolia population in Shennongjia, China

Quercus myrsinifolia is one of the dominant species in the evergreen broad-leaf forest on the southern slope of Shennongjia. The study of spatial distribution pattern and spatial correlation of Q. myrsinifolia population will help to understand population development and potential ecological processes, as well as the structure and biodiversity maintenance mechanism of evergreen broad-leaf forests at the northern edge of the subtropics. Based on forest dynamic monitoring data from one 1 hm2 permanent plot on the southern slope of Shennongjia, we employed pair correlation functions g(r) and marked correlation functions to analyze the diameter structure of the Q. myrsinifolia population, spatial distribution patterns at different diameter classes, and intraspecific and interspecific spatial associations. The results showed that diameter structure of Q. myrsinifolia population exhibited an inverted 'J'-shaped distribution, suggesting a healthy regeneration status and belonging to a growing population type. The spatial distribution showed a decreasing trend in aggregation with increasing diameter. Positive correlations among individuals strengthened with closer diameter classes, while weakening with larger diameter differences. Interspecific spatial associations showed an increasing correlation of Q. myrsinifolia with understory dominant species with increasing spatial scales, but no correlation was observed with canopy-dominant species. Our results suggested that the spatial pattern of Q. myrsinifolia populations on the southern slope of Shennongjia was mainly influenced by habitat filtering, seed dispersal limitation, and intraspecific and interspecific competition. Furthermore, the adaptive strategies of Q. myrsinifolia varied when they coexisted with different species.

Assessment of the lagging effect of vegetation response and loss probability in the Pearl River basin under drought stress

We quantified the lag time of vegetation response to drought in the Pearl River basin (PRB) based on the standardized precipitation evapotranspiration index (SPEI) and normalized difference vegetation index (NDVI), and constructed a vegetation loss probability model under drought stress based on the Bayesian theory and two-dimensional joint distribution. We further quantitatively evaluated the spatial variations of loss probability of four vegetation types (evergreen broadleaf forest, mixed forest, grassland, and cropland) under different drought intensities. The results showed that the drought risk in eastern West River, the upper reaches of North River and East River, and southern Pearl River Delta was obviously higher than that in other regions during 1982-2020. The response time of vegetation to drought in high-altitude areas in the upper reaches of PRB (mostly<3 month) was generally shorter than that in low altitude areas (>8 month). Drought exacerbated the probability of vegetation loss, with higher vulnerability of mixed forest than the other three vegetation types. The loss probability of vegetation was lower in northwestern PRB than that in central PRB.

Soil bacterial community structure and co‐occurrence networks in response to the succession of secondary forests in subtropical regions

AbstractA large amount of secondary successional vegetation (subtropical evergreen broadleaved forests) has formed after the extensive deforestation and cultivation of coniferous forests in Wuyi Mountain, Southeast China. However, we lack a detailed understanding of the dynamic changes in microbial community structure and its co‐occurrence network during succession. The features that are responsible for alterations in the soil bacterial community remain poorly defined. Therefore, we compared the soil physicochemical properties, enzyme activities, and bacterial diversity among three different forests (a coniferous forest [CF], early stage of succession; a mixed conifer‐broadleaf forest [CBMF], middle stage of succession; an evergreen broadleaf forest [EBF]; late stage of succession). Results indicated that the contents of soil organic carbon and microbial biomass carbon (MBC) in CBMF were higher compared with those in CF. The alpha diversity indices were the highest in CBMF. Functional annotation of prokaryotic taxa predicted the relative abundances of chemoheterotrophy and aerobic chemoheterotrophy were lower in CF than in the other two forests. Bacterial network topology was affected by forest succession, with CBMF having more complex bacterial networks. Mantel's test indicated the soil nitrate nitrogen content (P = 0.03) was the most important property that shaped the bacterial community composition, bacterial diversity was influenced by soil pH (P = 0.026), and the contents of available phosphorus (P = 0.04) and MBC (P = 0.022) during the succession process. In conclusion, the succession of secondary forests promoted soil nutrient accumulation and improved bacterial diversity and network complexity.

Impacts of altitude on plant green leaf, fresh litter, and soil stoichiometry in subtropical forests

BackgroundEcological stoichiometric characteristics of carbon (C), nitrogen (N), phosphorus (P), and potassium (K) serve as crucial indicators of nutrient cycling and limitation in terrestrial ecosystems. However, our current understanding of stoichiometric characteristics in subtropical forests and their response to different climate conditions is still limited.MethodsWe selected six altitudes ranging from 700 m to 1,200 m to simulate different climate conditions of an evergreen broadleaf forest in Wuyi Mountain, Fujian Province, China. We investigated C, N, P, and K stoichiometry and homeostasis in the green leaves, newly senesced leaf litter (fresh litter), and soil of this forest.ResultsLeaf P and K levels showed a decline with increasing altitude. Notably, the stoichiometric ratios in different components exhibited a bimodal distribution along the altitudinal gradient. Additionally, a decline trend of N resorption efficiencies was observed as altitude increased. Moreover, weak homeostasis was observed in P and K in green leaves. These findings highlighted the significant impact of altitude on the stoichiometry in evergreen broadleaf forest. This study also contributed to our understanding of the nutrient cycling mechanism and plant growth strategies of evergreen forests under different climate conditions.

Detection of Typical Forest Degradation Patterns: Characteristics and Drivers of Forest Degradation in Northeast China

The accurate identification of forest degradation and its driving factors is a prerequisite for implementing high-quality forest management. However, distinguishing degradation patterns is often neglected in large-scale forest quality assessments. The indicators were constructed to identify typical forest degradation patterns using remote sensing indexes, followed by an analysis of the spatiotemporal dynamics of forest degradation and quantification of the contributions from various driving factors. The results indicated that the constructed indicators could effectively distinguish typical forest degradation patterns, with a fire degradation identification accuracy of 90.0% and a fitting accuracy of drought and pest degradation higher than 0.7. The cold temperate conifer forest zone had the largest proportion of fire degradation, accounting for 67.7% of the area, and totals of 99.0% of the subtropical evergreen broadleaf forest zone and 92.8% of the temperate conifer and broadleaf mixed forest zone were moderately to severely affected by drought, with long-term stability. Additionally, 0.1% of the temperate grassland region and 0.1% of the cold temperate conifer forest zone underwent severe pest infestations, with a long-term stable trend. Meteorological factors were the primary contributors to all typical degradation patterns, accounting for 81.35%, 58.70%, and 82.29%, respectively. The research developed an index for assessing forest degradation and explained the importance of natural and anthropogenic factors in forest degradation. The results are beneficial for the scientific management of forest degradation and for improving forest management efficiency.

Global mapping of fractional tree cover for forest cover change analysis

Fractional tree cover facilitates the characterization of forest cover changes using satellite data. However, there are still substantial challenges in generating fractional tree cover datasets that satisfy the requirements of interannual stability for forest cover change monitoring. In this study, a global annual fractional tree cover dataset, named as GLOBMAP Fractional Tree Cover, was generated from MODIS observations with a resolution of 250 m during the period of 2000–2022. The tree cover estimation was improved relative to conventional global tree cover mapping methods by developing highly discriminative input features and near global sampling training data. MODIS annual observations were realigned at the pixel level to eliminate phenological differences among regions. The realigned annual series were condensed into twelve features showing high separability between trees and herbaceous vegetation to reduce the dimension of features. A global covering training dataset, comprising 465.88 million sample points, was extracted across the globe through the aggregation and combination of forest/land cover maps from ESA WorldCover, GlobeLand30, PALSAR FNF, and ESRI Land Cover to improve the representativeness of training data. A feed-forward neural network was calibrated to predict fractional tree cover from MODIS data. The spatial pattern of the estimation results was generally consistent with the CGLS-LC100 product at global scale, with the average MAE in global vegetated areas of 12.50 %, while our dataset provided extended temporal coverage. The interannual stability of the estimated tree cover series was improved compared to MODIS vegetation continuous fields products for deciduous broadleaf forests, evergreen broadleaf forests, and mixed forests, with the global average value of mean absolute deviation (MAD) in tree cover series reduced by 5.8 %, 46.9 %, and 18.3 %, respectively. The estimation results were assessed using globally distributed validation data around BELMANIP 2.1 sites and those derived from the USGS circa 2010 global land cover reference dataset, leading to the R2 values of 0.93 and 0.73, MAE of 4.24 % and 10.55 %, and RMSE of 11.45 % and 17.98 %, respectively. This dataset could enhance the capability to monitor forest cover changes, particularly gradual changes such as forest recovery.