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Introduction: Variability in microbial residues within soil aggregates are becoming progressively essential to the nutritive and sustainability of soils, and are therefore broadly regarded as an indispensable part of soil organic matter. It is unexplored how the widespread implementation of microbial fertilisers in agricultural production impacts soil organic nutrients, in particular the microbial residue fraction. Methods: We performed a three-year field experiment to verify the distinct impacts of microbial and organic fertilizers on carbon accumulation in soil microbial leftovers among aggregate fractions. Results: Microbial residual carbon was shown to decrease insignificantly during the application of microbial fertilizer and to rise marginally afterwards with the utilization of organic fertilizer. However, the combined effects of the two fertilizers had substantial impacts on the accumulation of microbial residual carbon. Changes in the structure of the fungi and bacteria shown in this study have implications for the short-term potential of microbial fertilizer shortages to permanent soil carbon sequestration. Additionally, our findings revealed variations in microbial residue accumulation across the microbial fertilizers, with Azotobacter chroococcum fertilizer being preferable to Bacillus mucilaginosus fertilizer due to its higher efficiency. In this scenario of nutrient addition, fungal residues may serve as the primary binding component or focal point for the production of new microaggregates, since the quantity of SOC provided by fungal residues increased while that supplied by bacterial residues decreased. Discussion: Our findings collectively suggested that the mechanisms behind the observed bacterial and fungal MRC (microbial residue carbon) responses to microbial fertilizer or organic fertilizer in bamboo forest soils are likely to be distinct. The application of microbial fertilizers for a limited duration led to a decline soil stable carbon pool, potentially influencing the regulation of soil nutrients in such hilly bamboo forests. [ABSTRACT FROM AUTHOR]

As the carbon (C) credit market evolves, incorporating organic matter into soils has emerged as a key strategy in C farming. Soil heterotrophic respiration (RH) plays a pivotal role in maintaining the C balance in terrestrial ecosystems, yet the contrasting impacts of fresh and pyrogenic organic matter applications on soil RH, and associated underlying mechanisms, have not been fully investigated. Through a 2-year field experiment, we investigated how applying maize straw and its derived biochar affect the physical, chemical, and microbial properties of soil in a subtropical Moso bamboo forest. Results showed that straw application increased soil RH, while biochar application suppressed it. Soil RH was correlated positively with β-glucosidase and cellobiohydrolase activities but negatively with RubisCO enzyme activity. Increased soil RH under straw application was linked to the increased β-glucosidase/cellobiohydrolase activities driven by elevated water-soluble organic C and O-alkyl C levels as well as GH48 and cbhI gene abundances, and the decreased RubisCO enzyme activity caused by reduced cbbL gene abundance. Conversely, reduced soil RH under biochar application was linked to reductions in β-glucosidase and cellobiohydrolase activities induced by increased aromatic C and decreased GH48 and cbhI gene levels, and increases in RubisCO enzyme activity driven by higher cbbL gene abundance. More importantly, changes in soil RH were clearly linked to microbial dynamics. Specifically, increases in the relative abundances of Alphaproteobacteria and Sordariomycetes and decreases in AD3 and Tremellomycetes contributed to the enhanced soil RH under straw application. With biochar application, the reverse effect occurred, ultimately contributing to the reduced soil RH. Our study demonstrates that maize straw application increases while biochar application decreases soil RH in the subtropical forest. These findings reveal that biochar reduced soil RH through changing microbial activity in subtropical forests, providing insight into complex dynamics of soil C cycling in response to diverse interventions. [ABSTRACT FROM AUTHOR]

Moso bamboo (Phyllostachys edulis) forest is one of the important alternative soruces in the tropical and subtropical regions. Its biomass quantification can be a basis of carbon storage estiamtion of the bamboo forest. Based on the destructively sample measurements of the moso bamboo in the Jiangsu Province in China, three forms of the model structures (controlling by sum of equation (CSE), level-1 proportional fitting distribution (L1PFD) and level-2 proportional fitting distribution (L2PFD)), and three estimation algorithms (ordinary least squares (OLS), two stage least square (2SLS) and three stage least square (2SLS)) were evaluated for identifying the best compatible biomass model. Results showed that all the three model structures solved the compatibility problems effectively. With each estimation algorithm applied, difference of the fit statistics between L1PFD and L2PFD was insignifcant. The fit statistics produced by 2SLS were slightly different from those of OLS, but fitting accuracy the latter was slightly higher, and had a more efficient estimation procedure. Thus, we recommend L1PFD model for predicting biomass for moso bamboo with use of diameter at breast height as a predictor variable. Our model will provide a reliable basis for estimating biomass and carbon stock of the moso bamboo forest in China. [ABSTRACT FROM AUTHOR]

Introduction: As a renewable forest resource, bamboo plays a role in sustainable forest development. However, traditional cutting systems, selection cutting (SeC) and clear-cutting (ClC), result in an unsustainable production of bamboo forests due to labor-consuming or bamboo degradation. Recently, a strip clear-cutting (StC) was theoretically proposed to promote the sustainability of bamboo production, while little is known about its application consequence. Methods: Based on a 6-year experiment, we applied the strip clear-cutting system in a typical running bamboo (Phyllostachys glauca McClure) forest to assess its feasibility and sustainability. Using SeC and ClC as controls, we set three treatments with different strip widths (5 m, 10 m, and 20 m) for strip clear-cutting, simplified as StC-5, StC-10, and StC-20, respectively. Then, we investigated leaf physiological traits, bamboo size and productivity, population features, and economic benefits for all treatments. Results: The stands managed by StC had high eco-physiological activities, such as net photosynthetic rate (Pn), photosynthetic nitrogen use efficiency (PNUE), and photosynthetic phosphorus use efficiency (PPUE), and thus grew well, achieved a large diameter at breast height (DBH), and were tall. The stand biomass of StC (8.78 t hm-2 year-1) was 1.19-fold and 1.49-fold greater than that of SeC and ClC, respectively, and StC-10 and StC-20 were significantly higher than SeC or ClC (p< 0.05). The income and profit increased with the increase in stand density and biomass, and StC-20 and StC-10 were significantly higher than SeC or ClC (p< 0.05). Using principal components analysis and subordinate function analysis, we constructed a composite index to indicate the sustainability of bamboo forests. For the sustainability assessment, StC-10 had the highest productive sustainability (0.59 ± 0.06) and the second highest economic sustainability (0.59 ± 0.11) in all cutting treatments. StC-10 had the maximum overall sustainability, with a value of 0.53 ± 0.02, which was significantly higher than that of ClC (p< 0.05). Conclusion: The results verified that StC for Phyllostachys glauca forests is feasible and sustainable as its sustainability index outweighs those of traditional cutting systems (SeC and ClC), and 10 m is the optimum distance for the strip width of StC. Our findings provide a new cutting system for managing other running bamboo forests sustainably. [ABSTRACT FROM AUTHOR]

Bamboo, widely known as ''poor man's timber'' or ''green gold,'' is a key forest resource distributed across tropical and subtropical regions. It is vital for its social, economic, cultural, and ecological benefits, demanding in-depth research for sustainable development. Despite its potential contribution to sustainable development, previous studies on bamboo have been geographically and methodically limited, lacking a comprehensive analysis of its contribution to sustainable livelihoods. This study, employing the PRISMA method for systematic reviews of 127 articles, investigates (1) the distribution and trends of livelihood-based bamboo research and identifies knowledge gaps, (2) bamboo's role in livelihood enhancement, (3) challenges and opportunities in its livelihood values, and (4) strategies to optimize bamboo's livelihood potential. Through this review, we identified most of the research limited to Asia, with limited studies in Africa and Latin America. Out of 1600 species, most of the studies focus on only 83 bamboo species, noting their multifaceted contributions across all livelihood capital types: natural, human, physical, social, and financial. Despite administrative and technical challenges that limit its value, bamboo provides diverse tangible benefits, economic opportunities, environmental improvements, international appeal, and strong sociocultural ties. We advocate for resilient bamboo-based livelihoods through cooperative, participatory, and sustainable management approaches that integrate research and indigenous knowledge to navigate challenges and leverage bamboo's extensive benefits.

We attempted to estimate bamboo expansion after the Great East Japan Earthquake in the Kitakami area, Ishinomaki City, Miyagi Prefecture using satellite remote sensing image classification. Pleiades-1A image obtained on April 30, 2015 and WorldView-3 image obtained on April 29, 2019 were used for the classification by a support vector machine (SVM). The accuracy of the user and producer for the bamboo category were 98.8% and 85.0%, respectively, in the Pleiades-1A image, and they are 91.0% and 81.0%, respectively, in the WorldView-3 image. The overall accuracy for the Pleiades-1A image and WorldView-3 image were 93.0% and 91.0%, respectively. On the classified images, tiny bamboo areas appeared on deciduous broadleaf forest area and they were considered as classification errors. The suitable season to distinguish the bamboo from the deciduous broadleaf tree is before appearance of new leaves on the deciduous trees. Obvious bamboo expansion was recognized in some area by comparison of 2015 Pleiades-1A and the 2019 WorldView-3 images. The lack of the bamboo management may cause its expansion after the earthquake. [ABSTRACT FROM AUTHOR]

IntroductionAs a renewable forest resource, bamboo plays a role in sustainable forest development. However, traditional cutting systems, selection cutting (SeC) and clear-cutting (ClC), result in an unsustainable production of bamboo forests due to labor-consuming or bamboo degradation. Recently, a strip clear-cutting (StC) was theoretically proposed to promote the sustainability of bamboo production, while little is known about its application consequence.MethodsBased on a 6-year experiment, we applied the strip clear-cutting system in a typical running bamboo (Phyllostachys glauca McClure) forest to assess its feasibility and sustainability. Using SeC and ClC as controls, we set three treatments with different strip widths (5 m, 10 m, and 20 m) for strip clear-cutting, simplified as StC-5, StC-10, and StC-20, respectively. Then, we investigated leaf physiological traits, bamboo size and productivity, population features, and economic benefits for all treatments.ResultsThe stands managed by StC had high eco-physiological activities, such as net photosynthetic rate (Pn), photosynthetic nitrogen use efficiency (PNUE), and photosynthetic phosphorus use efficiency (PPUE), and thus grew well, achieved a large diameter at breast height (DBH), and were tall. The stand biomass of StC (8.78 t hm-2 year-1) was 1.19-fold and 1.49-fold greater than that of SeC and ClC, respectively, and StC-10 and StC-20 were significantly higher than SeC or ClC (p< 0.05). The income and profit increased with the increase in stand density and biomass, and StC-20 and StC-10 were significantly higher than SeC or ClC (p< 0.05). Using principal components analysis and subordinate function analysis, we constructed a composite index to indicate the sustainability of bamboo forests. For the sustainability assessment, StC-10 had the highest productive sustainability (0.59 ± 0.06) and the second highest economic sustainability (0.59 ± 0.11) in all cutting treatments. StC-10 had the maximum overall sustainability, with a value of 0.53 ± 0.02, which was significantly higher than that of ClC (p< 0.05).ConclusionThe results verified that StC for Phyllostachys glauca forests is feasible and sustainable as its sustainability index outweighs those of traditional cutting systems (SeC and ClC), and 10 m is the optimum distance for the strip width of StC. Our findings provide a new cutting system for managing other running bamboo forests sustainably.

Vegetation phenology has long been adapted to environmental change and is highly sensitive to climate change. Shifts in phenology also affect feedbacks of vegetation to environmental factors such as topography and climate by influencing spatiotemporal fluctuations in productivity, carbon fixation, and the carbon water cycle. However, there are limited studies which explores the combined effects of the climate and terrain on phenology. Bamboo forests exhibit the outstanding phenological phenomena and play an important role in maintaining global carbon balance in climate change. Therefore, the interaction mechanisms of climate and topography on bamboo forest phenology were analyzed in Zhejiang Province, China during 2001–2017. The partial least squares path model was applied to clarify the interplay between the climate and terrain impacts on phenology under land cover/use change. The results revealed that the average start date of the growing season (SOS) significantly advanced by 0.81 days annually, the end date of the growing season (EOS) was delayed by 0.27 days annually, and the length of the growing season (LOS) increased by 1.08 days annually. There were obvious spatial differences in the partial correlation coefficients between the climate factors and phenological metrics. Although the SOS, EOS and LOS were affected by different climatic factors, precipitation was the dominant factor. Due to the sensitivity of the SOS and EOS to precipitation, a 100 mm increase in regional annual precipitation would cause the average SOS to advance by 0.18 days and the EOS to be delayed by 0.12 days. Regarding the terrain factors affecting climate conditions, there were clear differences in the influences of different altitudes, slopes and aspect gradients on bamboo forest phenology. This study further showed that topographic factors mainly affected the interannual variations in phenological metrics under land cover/use change by affecting precipitation. This study clarified the spatial pattern of bamboo forest phenology and the interactive mechanisms between vegetative phenology and environmental conditions, as this information is crucial in assessing the impact of phenological change on the carbon sequestration potential of bamboo forests.

Bamboo forests have a high carbon sequestration potential. Solar-induced chlorophyll fluorescence (SIF) provides fresh insights into the temporal and geographical variations in bamboo development and its interactions with the environment. SIF can serve as a probe for photosynthesis. In this study, we used distribution information on Chinese bamboo forests as well as a global SIF product, the global Orbiting Carbon Observatory-2 (OCO-2) SIF (GOSIF), which is derived from the OCO-2 carbon satellite. Thus, we used SIF as an indicator of bamboo forest growth. We investigated the spatial and temporal variations as well as the trends of bamboo forest SIF in China from 2008 to 2019 and explained the response mechanisms of bamboo forest growth to climate change and terrain differences in the region. We also evaluated the combined effects of climate and terrain on bamboo forest growth using the partial least squares path model (PLS-PM). The results were as follows: (1) Low values were found in the west and north, while high values were found in the east and south, according to the average bamboo forest SIF values in China from 2008 to 2019. More than 88% of the pixels had significantly increasing values. In conclusion, bamboo forests in China are growing well. (2) Solar radiation (Rad) and minimum temperature (Tmin) promoted the growth of most bamboo stands, while precipitation (Pre) and maximum temperature (Tmax) did the opposite. (3) The terrain, with a digital elevation model (DEM) less than 1000 m and a slope less than 9°, had a positive effect on bamboo forest SIF. (4) Climate and terrain jointly explained 45% of the bamboo forest growth change, and the major factor was climate change.

Bamboo groves predominantly thrive in tropical or subtropical regions. Assessing the efficacy of remote sensing data of various types in extracting bamboo forest information from bright and shadow areas is a critical issue for achieving precise identification of bamboo forests in complex terrain. In this study, 34 features were obtained from Sentinel-1 SAR and Sentinel-2 optical images using the Google Earth Engine platform. The normalized shaded vegetation index (NSVI) was then employed to segment the bright and shadow woodlands. Different features from diverse data sources were evaluated to extract bamboo forest information in the bright and shadow areas, then use the random forest (RF) classification algorithm to extract bamboo forest. The results showed that (1) the red-edge and short-wave infrared bands of Sentinel-2 optical images and their corresponding vegetation indices are significant in bamboo forest information extraction. (2) The dissimilarity and homogeneity of Sentinel-2 texture features in the bright area and dissimilarity in the shadow area, the Sentinel-1 backscatter features in the bright area and the VV and VH in the bright area and VV-VH in the shadow area have some variability between bamboo and nonbamboo forests, which can be used as effective features for bamboo forest extraction. (3) The combination of spectral, texture and backscatter features yields the highest overall classification accuracy and Kappa coefficient, at 87.96% and 0.7435, respectively. This study has the potential for remote sensing refinement of bamboo forest identification in complex terrain areas by utilizing subregion classification methods combined with optical and radar image features.

Heavy metal pollution in soil is a major global issue, and one effective method for addressing it is phytoremediation through bamboo planting. Nevertheless, there is a notable gap in our knowledge as no studies have explored the characteristics of soil organic matter (SOM) and the bacterial communities in bamboo forests during the remediation process. To bridge this knowledge gap, we conducted research to investigate the impact of different bamboo planting patterns on the SOM characteristics and microbial communities in soils contaminated with heavy metals. The contents of SOM and dissolved organic matter (DOM) in rhizosphere and non-rhizosphere soils differed significantly between monocropping and intercropping systems, with DOM accounting for only 1.7%–2.5% of SOM. Fourier transform infrared spectra showed that the contents of SOM polysaccharides C-O, carbonate C-O, aliphatic methyl, and methylene increased, while the aromatic C=C abundance decreased in the intercropping rhizosphere soil. The differences between bamboo cultivation patterns in the rhizosphere and non-rhizosphere soils were elucidated using the biomarkers, including MND1 and Nitrospira (non-rhizosphere), and Sphingomonas (rhizosphere). Heavy metals, DOM, SOM, and refined organic functional groups, especially C-O in polysaccharides and symmetric carboxylate, were the determining factors of soil bacterial communities. Compared to monocropping, intercropping increased the accumulation of Zn and Cd in bamboo shoots by 35% and 40%, respectively, and hence, intercropping soil, with a low toxicity, was suitable for bamboo shoot sprouting. Intercropping can alter the characteristics of SOM and bacterial communities and plays a vital role in phytoremediation and shoot growth in bamboo forests. Future studies on soil carbon dynamics and nutrient status during heavy metal remediation will improve our knowledge of soil transformation and its impact on soil ecosystem health and productivity. [ABSTRACT FROM AUTHOR]

Bamboo forest has undergone dramatic expansion due to climate changes and human activities, and its direct effects on both carbon storage and biodiversity of the forest ecosystem have occurred in tropical and subtropical regions, especially in China. However, the uncertainty in tracking bamboo forest extent and expansion intensity substantially influenced our assessment of them due to the poor resolution and persistent cloud covers in optical images (e.g., Landsat and Sentinel-2). We developed a straightforward and superior algorithm by coupling vegetation phenology and cloud-free SAR using Sentinel-1 and -2 images to identify bamboo forest at large scales and higher spatial resolution. Specifically, (1) this study analyzed the spectral and phenological characteristics during the bamboo forest growth season; (2) the optimum parameter sets for the SAR backscatter were calibrated against field data by using the genetic algorithm; (3) and then we generated bamboo forest and expansion intensity maps at 10 m spatial resolution for seven study regions in China in 2020. The results showed that the Kappa of the maps was 0.89, and the OA was 94.7% in all study areas, compared with the field data. The accuracy among each study area also performed well in mapping bamboo forest, indicated by Kappa varying from 0.82 to 0.94, and OA ranging from 91.1% to 97.33%. Compared to the national forestry inventory map, our results showed a significant positive linear relationship, with a higher R2 (0.96, p

Remote sensing is an important tool for the quantitative estimation of forest carbon stock. This study presents a multiscale, object-based method for the estimation of aboveground carbon stock in Moso bamboo forests. The method differs from conventional pixel-based approaches and is more suitable for Chinese forest management inventory. This research indicates that the construction of a SPOT-6 multiscale hierarchy with the 30 scale as the optimal segmentation scale achieves accurate information extraction for Moso bamboo forests. The producer's and user's accuracy are 88.89% and 86.96%, respectively. A random generalized linear model (RGLM), constructed using the multiscale hierarchy, can accurately estimate carbon storage of the bamboo forest in the study area, with a fitting and test accuracy (R2) of 0.74 and 0.64, respectively. In contrast, pixel-based methods using the RGLM model have a fitting and prediction accuracy of 0.24 and 0.01, respectively; thus, the object-based RGLM is a major improvement. The multiscale object hierarchy correctly analyzed the multiscale correlation and responses of bamboo forest elements to carbon storage. Objects at the 30 scale responded to the microstructure of the bamboo forest and had the strongest correlation between estimated carbon storage and measured values. Objects at the 60 scale did not directly inherit the forest information, so the response to the measured carbon storage of the bamboo forest was the smallest. Objects at the 90 scale serve as super-objects containing the forest feature information and have a significant correlation with the measured carbon storage. Therefore, in this study, a carbon storage estimation model was constructed based on the multiscale characteristics of the bamboo forest so as to analyze correlations and greatly improve the fitting and prediction accuracy of carbon storage. [ABSTRACT FROM AUTHOR]

Simple Summary: What does not have a name is difficult to understand and protect. Upon the unexpected discovery of an Hynobius salamander in Fujian province, China, we worked on understanding its relationship with other species and ultimately describing it. Please welcome the Fujian Bamboo Salamander to science, a segregated species based on genetics and morphology. While it is related to other southern mainland Chinese species, it may have diverged earlier and share some similarities with morphology and behavior with the Anji salamander. The Fujian Bamboo Salamander is special as it produces vocalization when under threat. The species is, however, incredibly rare, fitting the definition of Critically Endangered in the IUCN Red List of Threatened Species. It is important to describe lineages before they go extinct, as we can only protect what we know. This is especially important in the case of microendemic species likely to be relict populations, such as Hynobius salamanders in southern China. Here, we unexpectedly sampled Hynobius individuals in Fujian province, China, and then worked on determining their taxonomic status. We describe Hynobius bambusicolus sp. nov. based on molecular and morphological data. The lineage is deeply divergent and clusters with the other southern Chinese Hynobius species based on the concatenated mtDNA gene fragments (>1500 bp), being the sister group to H. amjiensis based on the COI gene fragment, despite their geographic distance. In terms of morphology, the species can be identified through discrete characters enabling identification in the field by eye, an unusual convenience in Hynobius species. In addition, we noted some interesting life history traits in the species, such as vocalization and cannibalism. The species is likely to be incredibly rare, over a massively restricted distribution, fitting the definition of Critically Endangered following several lines of criteria and categories of the IUCN Red List of Threatened Species. [ABSTRACT FROM AUTHOR]

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Introducing hyperaccumulators in bamboo forests is an efficient method for heavy metals (HMs) pollution control. HMs can be transferred from soil to bamboo and accumulate in edible bamboo shoots. However, how phytoremediation or cropping systems affect root‐soil interface and transference of HMs from soil to bamboo shoots is unknown. In this study, lei bamboo and Sedum plumbizincicola were planted as a monoculture and intercropping system (bamboo/sedum) on contaminated land. Soil properties, rhizosphere bacterial communities, and HMs concentrations in plants and soils were compared among bamboo in monoculture (B), bamboo in intercropping (BI), sedum in intercropping (SI), and sedum in monoculture (S). In BI, the total nitrogen was 10.8% lower, while total organic carbon (TOC) was 12.3% higher than in B; HMs removal amount in BI was higher than in B, especially cadmium. Intercropping increased the HMs concentrations, bioconcentration factor, translocation factor, and hazard quotient of bamboo shoots. Significant differences in bacterial community structures were confirmed by principal coordinate analysis. Gemmatimonadetes, Actinobacteria, Chloroflexi, and Kaistobacter were identified as biomarkers that increased significantly in intercropping, enhancing the diversity of ecological functions in the rhizosphere. Redundancy analysis revealed that rhizosphere bacterial communities were significantly correlated with soil properties, especially TOC and available phosphorus. Intercropping could remarkably alter soil chemical and microbiological properties and facilitate ecosystem restoration by enhancing soil TOC sequestration, activating rhizobacterial community at the root‐soil interface, and finally increasing HMs removal. As the consumption of bamboo shoots grown in contaminated soils may pose health risks, more attention is needed on this issue in phytoremediation studies. [ABSTRACT FROM AUTHOR]

Purpose: Although both bacterial and fungal communities play a substantial role in the transformation of soil nitrogen (N), it is unclear how each community contributes to soil net N mineralization during plant invasion. The current study examined the contributions of bacterial and fungal communities to soil N mineralization in soils from Moso bamboo (a natively invasive forest), mixed bamboo-broadleaf (a moderately invaded forest), and broadleaf (an uninvaded forest) forests using the bactericides and fungicides. Methods: The incubation experiment comprised three different invasion stages of bamboo and three treatments including no biocide (control), bactericide (streptomycin), and fungicide (cycloheximide). The contributions of bacterial and fungal communities to soil net ammonification and nitrification were determined by measuring soil N mineralization rate, microbial gene abundance, community composition, and by constructing structural equation model (SEM). Results: Compared with the broadleaf forest, the bamboo forest had 72.6% higher net ammonification in net mineralization. The net nitrification rate in the broadleaf forest was 118.2% higher than in the bamboo forest. Bactericide application reduced net ammonification rates significantly, but fungicide application raised net nitrification rates in all three forest types. In contrast to the control, bactericide decreased the alpha diversity indices of bacterial and fungal communities and altered the fungal composition. According to the SEM results, forest type had positive effects on fungal composition after adding bactericide, which reduced soil ammonification rate. In contrast, the addition of fungicide increased the bacterial abundance but decreased the fungal abundance, and changed the fungal composition. The SEM results suggested that forest type had positive effects on bacterial abundance after adding fungicide, thus increasing the soil net ammonification rate. Conclusions: These results provide relevant experimental evidence for the role of bacterial and fungal communities in the net ammonification and nitrification of soil, indicating that the bacterial community played a leading role in soil net ammonification during the bamboo invasion. [ABSTRACT FROM AUTHOR]

Bamboo groves predominantly thrive in tropical or subtropical regions. Assessing the efficacy of remote sensing data of various types in extracting bamboo forest information from bright and shadow areas is a critical issue for achieving precise identification of bamboo forests in complex terrain. In this study, 34 features were obtained from Sentinel-1 SAR and Sentinel-2 optical images using the Google Earth Engine platform. The normalized shaded vegetation index (NSVI) was then employed to segment the bright and shadow woodlands. Different features from diverse data sources were evaluated to extract bamboo forest information in the bright and shadow areas, then use the random forest (RF) classification algorithm to extract bamboo forest. The results showed that (1) the red-edge and short-wave infrared bands of Sentinel-2 optical images and their corresponding vegetation indices are significant in bamboo forest information extraction. (2) The dissimilarity and homogeneity of Sentinel-2 texture features in the bright area and dissimilarity in the shadow area, the Sentinel-1 backscatter features in the bright area and the VV and VH in the bright area and VV-VH in the shadow area have some variability between bamboo and nonbamboo forests, which can be used as effective features for bamboo forest extraction. (3) The combination of spectral, texture and backscatter features yields the highest overall classification accuracy and Kappa coefficient, at 87.96% and 0.7435, respectively. This study has the potential for remote sensing refinement of bamboo forest identification in complex terrain areas by utilizing subregion classification methods combined with optical and radar image features. [ABSTRACT FROM AUTHOR]

Forest biomass is an essential indicator of forest ecosystem carbon cycle and global climate change research, and traditional machine learning cannot explain the mechanism of feature variable impact on forest aboveground biomass (AGB). Therefore, we proposed an interpretable bamboo forest AGB prediction method based on Shaply Additive exPlanation (SHAP) and XGBoost model to explain the impact mechanism of feature variables on AGB. The bamboo forest AGB is estimated using the monthly and annual scale leaf area index (LAI), enhanced vegetation index (EVI), ratio vegetation index (RVI), precipitation (Pre), maximum temperature (Tmax), minimum temperature (Tmin) and solar radiation (Rad) data. The results showed that the method could be effectively predict AGB, and precipitation more important than temperature. The framework revealed the threshold effect, exceeded the threshold value, the impacts of LAI_Ann, EVI_Ann, and Pre_11 on AGB were stable. The SHAP interaction value between LAI_Ann and EVI_Ann decreased with increasing EVI_Ann and LAI_Ann. By contrast, when Pre_11 increased, the SHAP interaction value between LAI_Ann and Pre_11 increased with increasing LAI_Ann. The framework could also be easily implemented, providing an interpretable machine learning model of forest AGB. • The interpretable AGB prediction framework enabling both the SHAP and XGBoost model is proposed. • The SHAP method can improve the feature selection process. • The framework can in-depth interpret effect of multiple variables on bamboo forest AGB prediction. • Precipitation impact on AGB more important than temperature in climatic factors. [ABSTRACT FROM AUTHOR]

Heavy metal pollution in soil is a major global issue, and one effective method for addressing it is phytoremediation through bamboo planting. Nevertheless, there is a notable gap in our knowledge as no studies have explored the characteristics of soil organic matter (SOM) and the bacterial communities in bamboo forests during the remediation process. To bridge this knowledge gap, we conducted research to investigate the impact of different bamboo planting patterns on the SOM characteristics and microbial communities in soils contaminated with heavy metals. The contents of SOM and dissolved organic matter (DOM) in rhizosphere and non-rhizosphere soils differed significantly between monocropping and intercropping systems, with DOM accounting for only 1.7%–2.5% of SOM. Fourier transform infrared spectra showed that the contents of SOM polysaccharides C-O, carbonate C-O, aliphatic methyl, and methylene increased, while the aromatic C=C abundance decreased in the intercropping rhizosphere soil. The differences between bamboo cultivation patterns in the rhizosphere and non-rhizosphere soils were elucidated using the biomarkers, including MND1 and Nitrospira (non-rhizosphere), and Sphingomonas (rhizosphere). Heavy metals, DOM, SOM, and refined organic functional groups, especially C-O in polysaccharides and symmetric carboxylate, were the determining factors of soil bacterial communities. Compared to monocropping, intercropping increased the accumulation of Zn and Cd in bamboo shoots by 35% and 40%, respectively, and hence, intercropping soil, with a low toxicity, was suitable for bamboo shoot sprouting. Intercropping can alter the characteristics of SOM and bacterial communities and plays a vital role in phytoremediation and shoot growth in bamboo forests. Future studies on soil carbon dynamics and nutrient status during heavy metal remediation will improve our knowledge of soil transformation and its impact on soil ecosystem health and productivity.

Bacterial communities are usually active and dominant in rhizosphere soil, and play a strong ecological indicator role in soil environment. In order to study the community structure and diversity of soil bacteria in the special bamboo wine brewing environment, the 16S rDNA high-throughput sequencing of soil bacterial communities in the core area of bamboo forest J1, non-bamboo forest J2 and bamboo forest edge area J3 were completed on IonS5 TM XL sequencing platform. The results show that the dominant bacterial communities are mainly concentrated in Acidobacteria, Proteobacteria, Actinobacteria, Chloroflexi, Gemmationadetes and Verrucomicrobia at the phylum level. Among them, the account of soil Actinobacteria OTUs in the core area of bamboo forest J1 was the highest, but the dominant flora at the genus level is Acidothermus of Acidobacteria. For non-bamboo forest J2, the highest proportion of OTUs account is Acidobacteria at the phylum level and the dominant flora at the genus level is Bryobacter of Acidobacteria. The bamboo forest edge area J3 is located at the intersection zone with unstable habitat between bamboo forest and non-bamboo forest, in which the highest proportion of OTUs account is Proteobacteria at the phylum level and the dominant bacteria mainly include Sphingomonas of Proteobacteria, Bryobacter of Acidobacteria, Gemmatimonas of Gemmatinonadetes, etc. The species of soil bacterial community in the bamboo forest edge area J3 are complex, but its structure is still similar to that in the core area of bamboo forest J1. Overall, as the sample gradually approached to the core area of bamboo forest from non-bamboo forest, the diversity of bacterial community generally increased first and then decreased, which may be related to the single habitat of bamboo forest,and the number of individual bacterial flora and community structure changes greatly. The brewing environment of live bamboo wine makes the account of soil Actinobacteria OTUs rather than Proteobacteria in bamboo forest the most at the phylum level, which may be related to the unique environment. [ABSTRACT FROM AUTHOR]

Root-associated bacteria play a major role in plant health and productivity. However, how organic amendment influences root-associated bacteria is uncertain in Lei bamboo (Phyllostachys praecox) plantations. Here, we compared the rhizosphere and endophytic microbiomes in two Lei bamboo plantations with (IMS) and without (TMS) the application of organic amendment for 16 years. The results showed IMS significantly increased (p < 0.05) the relative abundance of Proteobacteria and significantly decreased (p < 0.05) the relative abundance of Acidobacteria, Bacteroidetes, and Verrucomicrobiota. The root endophytic Proteobacteria and Acidobacteria were significantly higher in abundance (p < 0.05) in the IMS than in the TMS, while Actinobacteria and Firmicutes were significantly lower in abundance. Five taxa were assigned to Proteobacteria and Acidobacteria, which were identified as keystones in the rhizosphere soil microbiome, while two species taxonomically affiliated with Proteobacteria were identified as keystones in the root endophytic microbiota, indicating this phylum can be an indicator for a root-associated microbiome in response to IMS. The soil pH, soil total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), available potassium (AK), and TOC:TP ratio were significantly correlated (p < 0.05) with the bacterial community composition of both rhizosphere soils and root endophytes. TMS increased the microbial network complexity of root endophytes but decreased the microbial network complexity of rhizosphere soil. Our results suggest IMS shapes the rhizosphere and endophytic bacterial community compositions and their interactions differently, which should be paid attention to when designing management practices for the sustainable development of forest ecosystems. [ABSTRACT FROM AUTHOR]

Widespread clearing of natural forests for tea plantations have profoundly altered the local water balance and energy budget. However, studies of comprehensive effects of land‐use conversion on energy and hydrological cycling are still rare. In this study, we used 5 years (2014–2018) of eddy covariance (EC) data, modelled estimates, and hydrological monitoring of different functional layers (canopy, litter and soil layers) to summarize the seasonal and inter‐annual variations and differences of evapotranspiration and water balance components in tea plantations (Camellia sinensis) and natural bamboo forests (Phyllostachysedulis). Results suggested the bamboo forest had higher actual evapotranspiration (ETa) (835 ± 5 mm) than the tea plantation (730 ± 19 mm), owing to differences in canopy conditions and plant physiology. Evident differences in ETa components were found between the tea plantation site and the bamboo forest site. The proportion of transpiration (Etr) was higher at the bamboo site (0.71–0.76) than the tea plantation site (0.60–0.65). Additionally, the soil evaporation ratio (0.10–0.13) was lower at the bamboo forest site than the tea plantation site (0.21–0.24) due to vegetation structure differences altering the radiation energy partitioning between the two sites. Moreover, the tea plantations were more susceptible to drought stress with low water storage in soil and simple rhizome‐root system. The comprehensive water holding capacity of canopy, litter, and soil layers of bamboo forest was 1.0–1.8 times of that in tea plantation. Compared with bamboo forest, pruning and losing of soil with intensive management activities enhanced drainage at the tea plantation site. This study provides insights into land‐use conversion of subtropical forest and managed tea plantation that have important implications on regional energy and water budgets. [ABSTRACT FROM AUTHOR]

Remote sensing is an important tool for the quantitative estimation of forest carbon stock. This study presents a multiscale, object-based method for the estimation of aboveground carbon stock in Moso bamboo forests. The method differs from conventional pixel-based approaches and is more suitable for Chinese forest management inventory. This research indicates that the construction of a SPOT-6 multiscale hierarchy with the 30 scale as the optimal segmentation scale achieves accurate information extraction for Moso bamboo forests. The producer’s and user’s accuracy are 88.89% and 86.96%, respectively. A random generalized linear model (RGLM), constructed using the multiscale hierarchy, can accurately estimate carbon storage of the bamboo forest in the study area, with a fitting and test accuracy (R2) of 0.74 and 0.64, respectively. In contrast, pixel-based methods using the RGLM model have a fitting and prediction accuracy of 0.24 and 0.01, respectively; thus, the object-based RGLM is a major improvement. The multiscale object hierarchy correctly analyzed the multiscale correlation and responses of bamboo forest elements to carbon storage. Objects at the 30 scale responded to the microstructure of the bamboo forest and had the strongest correlation between estimated carbon storage and measured values. Objects at the 60 scale did not directly inherit the forest information, so the response to the measured carbon storage of the bamboo forest was the smallest. Objects at the 90 scale serve as super-objects containing the forest feature information and have a significant correlation with the measured carbon storage. Therefore, in this study, a carbon storage estimation model was constructed based on the multiscale characteristics of the bamboo forest so as to analyze correlations and greatly improve the fitting and prediction accuracy of carbon storage.

It is important to describe lineages before they go extinct, as we can only protect what we know. This is especially important in the case of microendemic species likely to be relict populations, such as Hynobius salamanders in southern China. Here, we unexpectedly sampled Hynobius individuals in Fujian province, China, and then worked on determining their taxonomic status. We describe Hynobius bambusicolus sp. nov. based on molecular and morphological data. The lineage is deeply divergent and clusters with the other southern Chinese Hynobius species based on the concatenated mtDNA gene fragments (>1500 bp), being the sister group to H. amjiensis based on the COI gene fragment, despite their geographic distance. In terms of morphology, the species can be identified through discrete characters enabling identification in the field by eye, an unusual convenience in Hynobius species. In addition, we noted some interesting life history traits in the species, such as vocalization and cannibalism. The species is likely to be incredibly rare, over a massively restricted distribution, fitting the definition of Critically Endangered following several lines of criteria and categories of the IUCN Red List of Threatened Species.

The primary goal of this study was to evaluate avian assemblages in four different land types (Wetland Associated Bamboo Forest, Agricultural Land, Wetland Associated Agricultural Land and Riverside Agricultural Land) located in a flood prone area of South Bengal during the post monsoon months of 2020. Surveys were conducted for 48 days in a land type and time dependent manner to explore the changes in abundance, dominance, evenness and species richness. A total of 18654 observations belonging to 16 orders, 44 families, 70 genera and 81 species were recorded. Despite having lowest total count and third species rich area, Bamboo Forest emerged as the most diverse area with the highest Shannon index (3.37), Evenness index (0.4616) and lowest dominance index (0.06108). Bamboo forests exhibited the maximum values of Simpson 1-D (0.9389), Brillouin index (3.312), Menhinick Index (1.261), Equitability (0.8134) and alpha diversity (Fisher's alpha 11.74). Having maximum number of species occurrence (69), Riverside agricultural land was found to be the least diverse land type (Shannon index 2.847) showing highest value of dominance (0.1203). December attracted the most diverse (Shannon index 3.474) bird community and October showed the lowest value of Shannon index (2.919) with maximum value of dominance (0.123). We conclude that protection of natural habitats like bamboo forests, wetland and tree cover in small villages and proper management of agricultural lands is necessary for promoting species diversity and evenness in a rural environment. [ABSTRACT FROM AUTHOR]

Background: Bamboo forests provides benefits for nature and the welfare of the people of Turen in Malang Regency and Sumbermujur in Lumajang Regency. They interact with the forest to live through the development of forest potential based on local wisdom. This is believed to prevent various adverse impacts on the forest. Local wisdom is related to beliefs or/and taboos, ethics and rules, techniques and technology, as well as forest/land management traditions carried out by the community in building, managing forests, and Turen springs in Malang Regency and Sumbermujur in Lumajang Regency. Therefore, it is important to study the potential of bamboo forests in Turen and Sumbermujur for ecotourism, the development of bamboo forest ecotourism in Turen and Sumbermujur based on local wisdom, and the potential of bamboo forests in Turen and Sumbermujur in sustainable spring conservation. Results: Bamboo forest ecotourism has become an attractive tourist attraction. It is also beneficial for environmental conservation and the welfare of the surrounding community. The potential of bamboo forests in ecotourism development consists of various types of old bamboo that are fertile which offer environmentally friendly tourism activities by prioritizing aspects of nature conservation and socio-cultural empowerment of the local community. This cannot be separated from the belief that bamboo has supernatural powers (as a protector), so they do not dare to take or damage the existing bamboo. This behavior has a positive impact on springs that are still sustainable. Conclusions: Therefore, the charm of the bamboo forest is a potential that can be developed through ecotourism based on local wisdom. The development of bamboo forest ecotourism based on local wisdom is able to meet the living needs of the surrounding community. [ABSTRACT FROM AUTHOR]

The primary goal of this study was to evaluate avian assemblages in four different land types (Wetland Associated Bamboo Forest, Agricultural Land, Wetland Associated Agricultural Land and Riverside Agricultural Land) located in a flood prone area of South Bengal during the post monsoon months of 2020. Surveys were conducted for 48 days in a land type and time dependent manner to explore the changes in abundance, dominance, evenness and species richness. A total of 18654 observations belonging to 16 orders, 44 families, 70 genera and 81 species were recorded. Despite having lowest total count and third species rich area, Bamboo Forest emerged as the most diverse area with the highest Shannon index (3.37), Evenness index (0.4616) and lowest dominance index (0.06108). Bamboo forests exhibited the maximum values of Simpson 1-D (0.9389), Brillouin index (3.312), Menhinick Index (1.261), Equitability (0.8134) and alpha diversity (Fisher’s alpha 11.74). Having maximum number of species occurrence (69), Riverside agricultural land was found to be the least diverse land type (Shannon index 2.847) showing highest value of dominance (0.1203). December attracted the most diverse (Shannon index 3.474) bird community and October showed the lowest value of Shannon index (2.919) with maximum value of dominance (0.123). We conclude that protection of natural habitats like bamboo forests, wetland and tree cover in small villages and proper management of agricultural lands is necessary for promoting species diversity and evenness in a rural environment.

Introduction: Variability in microbial residues within soil aggregates are becoming progressively essential to the nutritive and sustainability of soils, and are therefore broadly regarded as an indispensable part of soil organic matter. It is unexplored how the widespread implementation of microbial fertilisers in agricultural production impacts soil organic nutrients, in particular the microbial residue fraction., Methods: We performed a three-year field experiment to verify the distinct impacts of microbial and organic fertilizers on carbon accumulation in soil microbial leftovers among aggregate fractions., Results: Microbial residual carbon was shown to decrease insignificantly during the application of microbial fertilizer and to rise marginally afterwards with the utilization of organic fertilizer. However, the combined effects of the two fertilizers had substantial impacts on the accumulation of microbial residual carbon. Changes in the structure of the fungi and bacteria shown in this study have implications for the short-term potential of microbial fertilizer shortages to permanent soil carbon sequestration. Additionally, our findings revealed variations in microbial residue accumulation across the microbial fertilizers, with Azotobacter chroococcum fertilizer being preferable to Bacillus mucilaginosus fertilizer due to its higher efficiency. In this scenario of nutrient addition, fungal residues may serve as the primary binding component or focal point for the production of new microaggregates, since the quantity of SOC provided by fungal residues increased while that supplied by bacterial residues decreased., Discussion: Our findings collectively suggested that the mechanisms behind the observed bacterial and fungal MRC (microbial residue carbon) responses to microbial fertilizer or organic fertilizer in bamboo forest soils are likely to be distinct. The application of microbial fertilizers for a limited duration led to a decline soil stable carbon pool, potentially influencing the regulation of soil nutrients in such hilly bamboo forests., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Cai, Long, Li, Cao, Wang, Zhao, Ren, Zhao, Huang, Lu, Hu and Xu.)

(1) Background--Taking the recreation motivation of bamboo recreation as a starting point, this paper makes an in-depth analysis of the main factors that affect people's bamboo recreation, and comprehensively excavates the recreation resources of bamboo forest to give full play to the recreation function of bamboo forest in order to meet the diversified needs of tourists. (2) Methods--A total of 368 valid questionnaires were obtained from the tourists of bamboo ornamental garden in Fuzhou National Forest Park. The factor analysis of bamboo forest recreation motivation was carried out by using SPSS19. 0. And the relationship between bamboo forest recreation motivation and recreation satisfaction was analyzed by multiple regression analysis. Finally, a diversified bamboo forest recreation model was put forward by integrating subjective and objective data. (3) Results--First of all, through factor analysis, it is concluded that the main recreational motivations of bamboo forest tourists include four categories: physical and mental well-being (21. 924%), self-improvement (21.294%), social interaction (14.756%), and closing for nature (14.030%). Secondly, through multiple linear regression to analyze the relationship between recreational motivations and satisfaction, recreational satisfaction is significantly positively correlated with motivation for physical and mental well-being, yearning for natural motivation, and self-improvement. The R2 of the equation reaches 0.667, indicating that the model has a good degree of fit. The VIF values of the three independent variables are all less than 3, so there is no multicollinearity. The greatest influence on the satisfaction of bamboo forest tourists is physical and mental well-being (0.500), followed by yearning for nature (0.274) and self-improvement (0. 127). The influence of social interaction is not significant, and it may be restricted by the other three motivations, which leads to a decline in its influence on recreational satisfaction in the multiple regression model. Combining with data analysis, four models of bamboo recreation are proposed. Establishing a model of physical and mental health in bamboo places should pay attention to the participation of all citizens. The construction of bamboo space leisure interactive mode requires the laying of interactive places. To construct a bamboo-themed science education model requires perfect activity design. The Construction of bamboo landscape appreciation experience mode is suggested to enrich the scene construction. ⑷ Conclusions and Discussions--With the rapid development of cities, while improving the quality of people's lives, the psychological pressure on urban residents from work and study is increasing, so people are required to relieve the pressure in their leisure time. There are more and more sub-healthy people in the city, which leads to the increasing demand for physical exercise. Bamboo forest environment is rich in a large number of negative oxygen ions, therefore the bamboo forests have gradually become excellent for recreation and exercise. When people are active in the bamboo forest, through the interaction with friends and family, their ideas and abilities will also be improved to a certain extent. The bamboo forest environment will make people feel calm and relaxed, and easy to release the usual pressure. When people are relaxed physically and mentally, they will feel energetic, relieve bad emotions, and promote the generation of social interactions between people. Bamboo forest landscape is an important manifestation of natural landscape. The rich and diverse landscape of bamboo forests can not only convey the positive emotions of the recreation, but also relieve fatigue and make people energetic. By satisfying the recreational motivation of the bamboo forest tourists to improve their recreation satisfaction, people's willingness to revisit and recommend the bamboo forest recreation will be enhanced. The increase of recreational tourists will further explore the various functions of the bamboo forests in order to form a virtuous development. The four bamboo forest recreational modes can not only form a special bamboo forest recreation space individually, but also coexist in a comprehensive bamboo recreation space. It adds more ideas to the development concept of bamboo forest recreation in the future, which is beneficial to the follow-up research and development of bamboo forest recreation in the future. [ABSTRACT FROM AUTHOR]

Root-associated bacteria play a major role in plant health and productivity. However, how organic amendment influences root-associated bacteria is uncertain in Lei bamboo (Phyllostachys praecox) plantations. Here, we compared the rhizosphere and endophytic microbiomes in two Lei bamboo plantations with (IMS) and without (TMS) the application of organic amendment for 16 years. The results showed IMS significantly increased (p < 0.05) the relative abundance of Proteobacteria and significantly decreased (p < 0.05) the relative abundance of Acidobacteria, Bacteroidetes, and Verrucomicrobiota. The root endophytic Proteobacteria and Acidobacteria were significantly higher in abundance (p < 0.05) in the IMS than in the TMS, while Actinobacteria and Firmicutes were significantly lower in abundance. Five taxa were assigned to Proteobacteria and Acidobacteria, which were identified as keystones in the rhizosphere soil microbiome, while two species taxonomically affiliated with Proteobacteria were identified as keystones in the root endophytic microbiota, indicating this phylum can be an indicator for a root-associated microbiome in response to IMS. The soil pH, soil total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), available potassium (AK), and TOC:TP ratio were significantly correlated (p < 0.05) with the bacterial community composition of both rhizosphere soils and root endophytes. TMS increased the microbial network complexity of root endophytes but decreased the microbial network complexity of rhizosphere soil. Our results suggest IMS shapes the rhizosphere and endophytic bacterial community compositions and their interactions differently, which should be paid attention to when designing management practices for the sustainable development of forest ecosystems.

Phenology has a significant effect on forest growth and directly affects the forest ecosystem carbon cycle. Bamboo forests possess strong carbon sequestration capacities. However, it is not clear whether variations in phenology increase or decrease carbon uptake and storage in subtropical bamboo forests. We first extracted the length of the growing season (LOS) by coupling a data assimilation algorithm and MODIS leaf area index (LAI) data, and then the LOS was used to drive the integrated terrestrial ecosystem carbon-budget (InTEC) model to simulate gross primary productivity (GPP) and net ecosystem productivity (NEP) in Zhejiang Province from 2001 to 2017. Our results showed that the LOS estimation using the assimilated LAI time series was more reliable than that of the MODIS LAI and enhanced vegetation index (EVI). The annual average LOS increased on average by 0.76 day yr−1 from 2001 to 2017. The GPP and NEP simulations based on the LAI assimilation-based phenology indicated that bamboo forest ecosystems possess strong carbon sequestration capacities and act as carbon sinks, with mean annual GPP and NEP values of 434.74 ± 257.93 g C m−2 yr−1 and 141.42 ± 82.54 g C m−2 yr−1, respectively, during 2001–2017. An increase of one day in the regional annual LOS increases the annual average GPP and NEP by 1.34 g C m−2 yr−1 and 0.75 g C m−2 yr−1, respectively. Moreover, the interannual variation of NEP was significantly correlated with precipitation and temperature, whereas GPP was not. Our results demonstrated that phenology extraction based on LAI data assimilation should play an important role in the simulation of bamboo forest productivity with ecological process models. The variation in phenology induced by climate change can strengthen the bamboo forest carbon sink, which is of great significance for subtropical forests coping with climate change in the future.

Phenology plays an important role in revealing the spatiotemporal evolution of forest ecosystem carbon cycles. The accuracy of vegetation phenology estimates based on remote sensing has improved in temperate zones. However, subtropical vegetation is complex, and the corresponding phenology estimates using remote sensing face great challenges. Bamboo forests are subtropical unique forest types and exhibit on– and off-years, fast growth, high productivity and carbon sequestration capability. In this study, we propose a new method to improve phenology estimates of bamboo forests by coupling the particle filter (PF) assimilation algorithm and a logistic model. The phenological metrics are estimated using high-precision leaf area index (LAI) assimilation products and a logistic model from 2001 to 2018, and the results are compared to those extracted from Moderate-Resolution Imaging Spectroradiometer (MODIS) LAI and the enhanced vegetation index (EVI) calculated based on the MODIS reflectance data. The results reveal that the R2 values between the start of the growing season (SOS) and end of the growing season (EOS) estimated by the assimilated LAI and ground-observed values are the highest (>0.50) and the root mean square errors (RMSEs) are the smallest (<6.35 days). A negative correlation occurs between the EVI-simulated and ground-observed SOS and EOS values, which indicates that EVI products cannot be adopted to estimate the phenology of bamboo forests. Compared to the MODIS LAI, the R2 values of the predicted SOS and EOS by the assimilated LAI data are improved by 3.67 times and 12.50%, respectively, and the RMSEs are reduced by 58.91% and 41.13%, respectively. Therefore, the new method solves the problem whereby the phenology of subtropical bamboo forests cannot be accurately extracted from MODIS LAI and EVI products. The temporal and spatial patterns of the SOS and EOS of bamboo forests are estimated with the new method from 2001 to 2018, and the SOS exhibits obvious spatial heterogeneity during on– and off-years, and the SOS during the on-years occurs slightly earlier than that during the off-years. A total of 70.13% of all pixels exhibit a SOS advance trend, while more than half of the areas (58.42%) present an EOS delay trend. The results indicate that coupling the data assimilation algorithm and phenology method greatly improves the estimation precision and reduces the estimation errors of the SOS and EOS of bamboo forests. [ABSTRACT FROM AUTHOR]

Carbon flux is the main basis for judging the carbon source/sink of forest ecosystems. Bamboo forests have gained much attention because of their high carbon sequestration capacity. In this study, we used a boreal ecosystem productivity simulator (BEPS) model to simulate the gross primary productivity (GPP) and net primary productivity (NPP) of bamboo forests in China during 2001–2018, and then explored the spatiotemporal evolution of the carbon fluxes and their response to climatic factors. The results showed that: (1) The simulated and observed GPP values exhibited a good correlation with the determination coefficient (R2), root mean square error (RMSE), and absolute bias (aBIAS) of 0.58, 1.43 g C m−2 day−1, and 1.21 g C m−2 day−1, respectively. (2) During 2001–2018, GPP and NPP showed fluctuating increasing trends with growth rates of 5.20 g C m−2 yr−1 and 3.88 g C m−2 yr−1, respectively. The spatial distribution characteristics of GPP and NPP were stronger in the south and east than in the north and west. Additionally, the trend slope results showed that GPP and NPP mainly increased, and approximately 30% of the area showed a significant increasing trend. (3) Our study showed that more than half of the area exhibited the fact that the influence of the average annual precipitation had positive effects on GPP and NPP, while the average annual minimum and maximum temperatures had negative effects on GPP and NPP. On a monthly scale, our study also demonstrated that the influence of precipitation on GPP and NPP was higher than that of the influence of temperature on them.

Introduction: As a renewable forest resource, bamboo plays a role in sustainable forest development. However, traditional cutting systems, selection cutting (SeC) and clear-cutting (ClC), result in an unsustainable production of bamboo forests due to labor-consuming or bamboo degradation. Recently, a strip clear-cutting (StC) was theoretically proposed to promote the sustainability of bamboo production, while little is known about its application consequence., Methods: Based on a 6-year experiment, we applied the strip clear-cutting system in a typical running bamboo ( Phyllostachys glauca McClure) forest to assess its feasibility and sustainability. Using SeC and ClC as controls, we set three treatments with different strip widths (5 m, 10 m, and 20 m) for strip clear-cutting, simplified as StC-5, StC-10, and StC-20, respectively. Then, we investigated leaf physiological traits, bamboo size and productivity, population features, and economic benefits for all treatments., Results: The stands managed by StC had high eco-physiological activities, such as net photosynthetic rate ( P n ), photosynthetic nitrogen use efficiency (PNUE), and photosynthetic phosphorus use efficiency (PPUE), and thus grew well, achieved a large diameter at breast height (DBH), and were tall. The stand biomass of StC (8.78 t hm -2 yea r-1 ) was 1.19-fold and 1.49-fold greater than that of SeC and ClC, respectively, and StC-10 and StC-20 were significantly higher than SeC or ClC ( p < 0.05). The income and profit increased with the increase in stand density and biomass, and StC-20 and StC-10 were significantly higher than SeC or ClC ( p < 0.05). Using principal components analysis and subordinate function analysis, we constructed a composite index to indicate the sustainability of bamboo forests. For the sustainability assessment, StC-10 had the highest productive sustainability (0.59 ± 0.06) and the second highest economic sustainability (0.59 ± 0.11) in all cutting treatments. StC-10 had the maximum overall sustainability, with a value of 0.53 ± 0.02, which was significantly higher than that of ClC ( p < 0.05)., Conclusion: The results verified that StC for Phyllostachys glauca forests is feasible and sustainable as its sustainability index outweighs those of traditional cutting systems (SeC and ClC), and 10 m is the optimum distance for the strip width of StC. Our findings provide a new cutting system for managing other running bamboo forests sustainably., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Liang, Wang, Shen, Wu, Zou, Yu, Yu, Chen and Shi.)

Aims Accurate estimates of bamboo biomass and net primary productivity (NPP) are required to evaluate the carbon sequestration potential of bamboo forests. However, relevant data that are important for climate change mitigation, have rarely been collected in regions outside of East Asia and India. Information on seasonal patterns of NPP and its components will enable the quantification of factors that influence the carbon balance in bamboo forests. In this study, we quantified the aboveground biomass (AGB) and aboveground NPP of five major bamboo species in northern Laos using monthly data collected over a 12-month period. Methods All live culms in 10, 2 m × 2 m plots (for one monopodial bamboo species: Indosasa sinica) and 30 clumps per species (for four sympodial bamboo species: Bambusa tulda , Cephalostachyum virgatum , Dendrocalamus membranaceus and Gigantochloa sp.) were numbered and measured at breast height. We set 10 or 20 litter traps per species to collect litterfall. Censuses of dead and recruited culms and litterfall collection were performed once per month for 12 months. Important Findings The AGB was highest in I. sinica (59.87 Mg ha−1) and lowest in C. virgatum (11.54 Mg ha−1), and was mostly below the plausible global range for bamboos (32–256 Mg ha−1). The sympatric distribution of multiple bamboo species at the study sites may have suppressed the AGB in four of the five studied species. The aboveground NPP estimates were between 3.43 and 14.25 Mg ha−1 yr−1; those for D. membranaceus (8.20 Mg ha−1 yr−1) and I. sinica (14.25 Mg ha−1 yr−1) were comparable to mean global estimates for temperate evergreen forests (8.78 Mg ha−1 yr−1) and tropical moist forests (10.56 Mg ha−1 yr−1). High culm recruitment rates (15.20–23.39% yr−1) were major contributors to aboveground NPP estimates. Seasonal patterns of aboveground NPP were largely influenced by the phenology of the new culms. In the four sympodial bamboo species, new culms began to emerge following the onset of persistent rainfall, mainly in July and August. However, the sprouting of new culms in the monopodial species I. sinica followed a trend of increasing temperatures, mainly in March and April. Thus, our results indicate that bamboos have considerable potential for sequestering carbon in northern Laos, but that this potential may be affected by climate change. [ABSTRACT FROM AUTHOR]

Monitoring plant phenology is vital to maintaining the global carbon balance and management under climate change. Bamboo forest is an essential forest type in subtropical China with a strong carbon sequestration capacity. In recent years, vegetation indices (VIs), which characterize canopy structural parameters, and solar-induced chlorophyll fluorescence (SIF), indicating the photosynthetic activity of vegetation, have provided new perspectives on plant phenology at regional and global scales. However, the best data sources and methods for extracting the phenology of bamboo forests remain to be explored. In this study, new vegetation indices were innovatively constructed by normalizing the VIs (enhanced vegetation index (EVI), two-band enhanced vegetation index (EVI2), and near-infrared reflectance of vegetation (NIRv)) based on Moderate Resolution Imaging Spectroradiometer (MODIS) products and SIF products (GOSIF) based on OCO-2 satellites and then taking the mean values of the normalized VIs (EVI, EVI2 and NIRv) and SIF. We called the new indices SVs (SIF and VIs combined indices, including Se (SIF and EVI combined index), Se2 (SIF and EVI2 combined index), or Sn (SIF and NIRv combined index)). Two time series reconstruction methods (asymmetric Gaussian (AG) function fitting and double logistic (DL) function) and two extractive phenology parameter methods (dynamic threshold method (DT) and comparative threshold method (CT)) were employed to extract phenological information. The advantages of SVs for extracting bamboo forest phenology (BFP) were verified by comparing the extraction performance of VIs, SIF, and SVs on the SOS and EOS of bamboo forests. Thus, the best way to extract BFP was explored, and the spatial distribution and spatial-temporal variation characteristics of BFP in China from 2011 to 2020 were analyzed. The results are described as follows: (1) SVs are better able to extract BFP parameters compared with VIs and SIF, especially in bamboo forest-specific off-years and on-years; (2) SIF has better accuracy than VIs in extracting BFP, where both SOS and EOS values obtained from VIs are overestimated, and SIF can reflect BFP information earlier; and (3) the best data sources for extracting SOS and EOS in bamboo forests are Sn and Se, respectively, and the optimal methods are AG_CT and DL_DT, respectively. Compared with SIF, the R2 values of Sn and Se extracted SOS and EOS are improved by 40.7% and 7.7%, and the RMSE values are reduced by 24.7% and 0.7%, respectively; and (4) the SOS for bamboo forests in China from 2011 to 2020 was mainly concentrated in 80–100 days, with an overall advancing trend; the EOS was mainly concentrated in 300–320 days, with an overall delay. The results show that the SVs obtained by coupling VIs and SIF can better track the BFP information, providing a practical reference for macroscopic monitoring of BFP based on medium-resolution time series data. • We coupled VIs and SIFs to construct new phenological indexes SVs. • SIF captures bamboo forest phenology better than VIs, but SVs are superior. • SOS and EOS of China's bamboo forests are advanced and delayed, respectively. [ABSTRACT FROM AUTHOR]

Bamboo forests are widespread in subtropical areas and are well known for their rapid growth and great carbon sequestration ability. To recognize the potential roles and functions of bamboo forests in regional ecosystems, forest aboveground biomass (AGB)—which is closely related to forest productivity, the forest carbon cycle, and, in particular, carbon sinks in forest ecosystems—is calculated and applied as an indicator. Among the existing studies considering AGB estimation, linear or nonlinear regression models are the most frequently used; however, these methods do not take the influence of spatial heterogeneity into consideration. A geographically weighted regression (GWR) model, as a spatial local model, can solve this problem to a certain extent. Based on Landsat 8 OLI images, we use the Random Forest (RF) method to screen six variables, including TM457, TM543, B7, NDWI, NDVI, and W7B6VAR. Then, we build the GWR model to estimate the bamboo forest AGB, and the results are compared with those of the cokriging (COK) and orthogonal least squares (OLS) models. The results show the following: (1) The GWR model had high precision and strong prediction ability. The prediction accuracy (R2) of the GWR model was 0.74, 9%, and 16% higher than the COK and OLS models, respectively, while the error (RMSE) was 7% and 12% lower than the errors of the COK and OLS models, respectively. (2) The bamboo forest AGB estimated by the GWR model in Zhejiang Province had a relatively dense spatial distribution in the northwestern, southwestern, and northeastern areas. This is in line with the actual bamboo forest AGB distribution in Zhejiang Province, indicating the potential practical value of our study. (3) The optimal bandwidth of the GWR model was 156 m. By calculating the variable parameters at different positions in the bandwidth, close attention is given to the local variation law in the estimation of the results in order to reduce the model error.

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The role of bamboo forest in soil Hg accumulation and emissions was evaluated by analyzing Hg concentration in soil and plant samples as well as Hg flux between soil and air. THg concentrations in soil samples ranged widely from 28.5 to 860 ng g−1 with a mean value of 153 ± 17.3 ng g−1. Methylmercury concentrations in soil samples from forest soil (FS, 0.94 ± 0.20 ng g−1) were significantly higher (p < 0.05) than from bare soil (BS, 0.54 ± 0.07 ng g−1). The mean foliar THg concentration (178 ± 16.8 ng g−1) was significantly higher (p < 0.05) than those in branches (63.1 ± 7.27 ng g−1) and roots (73.1 ± 16.9 ng g−1), indicating that the major source of Hg in bamboo might be from air deposition. Hg flux from FS (25.6 ng m−2 h−1) was significantly lower (p < 0.05) than that from BS (32.2 ng m−2 h−1). The annual decline in Hg emissions due to the presence of the bamboo forest may reach 6.94 kg. [ABSTRACT FROM AUTHOR]

To determine the effect of management intensity on runoff nutrient losses in bamboo forests under natural rainfall conditions, separate field observation stations were set up at the mouths of each field-sized catchment (micro-watershed) in extensively or intensively managed areas, at Qingshan Bamboo Orchard in Lin'an district, Hangzhou city, Zhejiang province. After every successive rainfall during the year, runoff volumes were measured, and water samples from the sand- settling tanks at the observation stations were collected and analyzed for total nitrogen (TN), total phosphorus (TP), nitrate nitrogen (NO3--N), ammonium nitrogen (NH4+-N), and phosphate (PO43-) contents. Simultaneously, soil samples were also collected and analyzed for pH, organic matter, effective nitrogen and available phosphorus contents. The results showed that: (1) Annual runoffs from intensively managed and extensively managed bamboo forests were 8086.52 m3/hm2 and 4850.95 m3/hm2, respectively; (2) Nitrogen loss in runoff from the bamboo forests was dominated by nitrate nitrogen; (3) Intensive management increased the risk of nutrient losses from the bamboo forests; the annual losses of nitrogen and phosphorus from intensively managed areas were 45.26 kg/hm2 and 25.05 kg/hm2, respectively; but they were only 0.31 kg/hm2 and 0.21 kg/hm2, respectively, from extensively managed area. Compared with losses from extensively managed area, the losses of nitrogen and phosphorus from intensively managed area increased by 80.68% and 47.62%, respectively; (4) The TN content in runoff water had a significant negative correlation with alkali- hydrolyzed nitrogen content of the soil, while the TP content in runoff water had a significant positive correlation with soil available phosphorus. [ABSTRACT FROM AUTHOR]