This study aimed to demonstrate change in spatial correlation between Korean pine （Pinus koraiensis Sieb. et Zucc.） and three rare species, and change in spatial distribution of four species in response to a range o...This study aimed to demonstrate change in spatial correlation between Korean pine （Pinus koraiensis Sieb. et Zucc.） and three rare species, and change in spatial distribution of four species in response to a range of selective cutting intensities. We sampled three plots of mixed Korean pine and broad-leaf forest in Lushuihe Forestry Bureau of Jilin province, China. Plot 1, a control, was unlogged Korean pine broad-leaf forest. In plots 2 and 3, Korean pine was selectively cut at 15 and 30 % intensity, respectively, in the 1970s. Other species were rarely cut. We used point-pattern analysis to research the spatial distributions of four tree species and quantify spatial correlations between Korean pine and the other three species, Amur linden （Tilia amurensis Rupr.）, Manchurian ash （Fraxinus mandshurica Rupr.）, and Mongolian oak （Quercus mongolica Fisch.） in all three plots. The results of the study show that selective cutting at 15 % intensity did not significantly change either the species spatial patterns or the spatial correlation between Korean pine and broadleaf species. Selective cutting at 30 % intensity slightly affected the growth of Korean pine and valuable species in forest communities, and the effect was considered nondestructive and recoverable.展开更多
In Yingzuijie National Nature Reserve, Pinus massoniana forest, mixed broadleaf-coniferous forest and evergreen broad-leaf forest were investigated to study the changing characteristics of woody debris （WD） during v...In Yingzuijie National Nature Reserve, Pinus massoniana forest, mixed broadleaf-coniferous forest and evergreen broad-leaf forest were investigated to study the changing characteristics of woody debris （WD） during various succession stages o1 evergreen broad-leaf forest. The results showed that during various succession stages of evergreen broad-leaf forest in Yingzuijie National Nature Reserve, WD storage of each forest ranged from 1.26 to 8.82 t/hm^2, with the order of P. massoniana forest 〈 mixed broadleaf-coniferous forest 〈 evergreen broad-leaf forest, that is, it increased from early to late stages of the succession. At different succession stages, coarse woody debris （CWD） storage was 2 -9 times more than fine woody debris （FWD） storage, revealing that CWD was dominant in WD of each forest. CWD biomass accounted for 0.66% -2.21% of arbor biomass, so the forests were at the developmental stage.展开更多
To better understand the effect of forest succession on carbon sequestration, we investigated carbon stock and allocation of evergreen broadleaf forest, a major zonal forest in subtropical China. We sought to quantify...To better understand the effect of forest succession on carbon sequestration, we investigated carbon stock and allocation of evergreen broadleaf forest, a major zonal forest in subtropical China. We sought to quantify the carbon sequestration potential. We sampled four forest types, shrub （SR）, pine （Pinus massoniana） forest （PF）, pin~ and broadleaf mixed forest （Mr） and evergreen broadleaf forest （BF）. A regression equation was constructed using tree height and diameter at breast height （DBH） and elements of total tree biomass. The equation was subse- quently utilized to estimate tree carbon storage. The carbon storage of understory, litter, and soil was also estimated.展开更多
Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstruc...Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.展开更多
The basic principle of life table method is deseribed, and the method of tree height instead of tree age in static life table is suggested, and it is also discussed that the possibility of natural poplar -birch forest...The basic principle of life table method is deseribed, and the method of tree height instead of tree age in static life table is suggested, and it is also discussed that the possibility of natural poplar -birch forest recover to broad-leaf Korean pine forest on low pitches in the Xiaoxing'an Mountains by this method. If there is no particular situation, Korean pines after high than 5m under natural Poplar-birch forest will basically survive and make their way into dominant callopy accompanied by climax broad-leaf species.展开更多
A better understanding of the structure and dynamics of disturbed forests is key for forecasting their future successional trajectories.Despite vulnerability of subalpine forests to warming climate,little is known as ...A better understanding of the structure and dynamics of disturbed forests is key for forecasting their future successional trajectories.Despite vulnerability of subalpine forests to warming climate,little is known as to how their community composition has responded to disturbances and climate warming over decades.Before the 1970s,subalpine forests on the southeastern Qinghai-Tibet Plateau mainly experienced logging and fire,but afterwards they were more impacted by climate warming.Thus,they provide an excellent setting to test whether disturbances and climate warming led to changes in forest structure.Based on the analysis of 3145 forest inventory plots at 4-to 5-year resolution,we found that spruce-fir forests shifted to pine and broadleaved forests since the early 1970s.Such a turnover in species composition mainly occurred in the 1994e1998 period.By strongly altering site conditions,disturbances in concert with climate warming reshuffle community composition to warm-adapted broadleaf-pine species.Thus,moderate disturbances shifted forest composition through a gradual loss of resilience of spruce-fir forests.Shifts in these foundation species will have profound impacts on ecosystem functions and services.In the future,broadleaved forests could expand more rapidly than evergreen needle-leaved forests under moderate warming scenarios.In addition to climate,the effects of anthropogenic disturbances on subalpine forests should be considered in adaptive forest management and in projections of future forest changes.展开更多
The Qinba Mountains are climatically and ecologically recognized as the north-south transitional zone of China.Analysis of its phenology is critical for comprehending the response of vegetation to climatic change.We r...The Qinba Mountains are climatically and ecologically recognized as the north-south transitional zone of China.Analysis of its phenology is critical for comprehending the response of vegetation to climatic change.We retrieved the start of spring phenology(SOS)of eight forest communities from the MODIS products and adopted it as an indicator for spring phenology.Trend analysis,partial correlation analysis,and GeoDetector were employed to reveal the spatio-temporal patterns and climatic drivers of SOS.The results indicated that the SOS presented an advance trend from 2001 to 2020,with a mean rate of−0.473 d yr^(−1).The SOS of most forests correlated negatively with air temperature(TEMP)and positively with precipitation(PRE),suggesting that rising TEMP and increasing PRE in spring would forward and delay SOS,respectively.The dominant factors influencing the sensitivity of SOS to climatic variables were altitude,forest type,and latitude,while the effects of slope and aspect were relatively minor.The response of SOS to climatic factors varied significantly in space and among forest communities,partly due to the influence of altitude,slope,and aspect.展开更多
With the rapid economic development and continuous expansion of human activities,forest degradation—characterized by reduced forest stock within the forest including declining carbon storage—poses significant threat...With the rapid economic development and continuous expansion of human activities,forest degradation—characterized by reduced forest stock within the forest including declining carbon storage—poses significant threats to ecosystem stability.Understanding the current status of forest degradation and assessing potential carbon stocks in China are of strategic importance for making forest restoration efforts and enhancing carbon sequestration capacity.In this study,we used the national forest inventory data from 2009 to 2018 to develop a set of standard measures for assessing degraded forests across China,based on five key indicators:forest accumulation growth rate(FAGR),forest recruitment rate(FRR),tree species reduction rate(TSRR),forest canopy cover reduction rate(FCCRR),and forest disaster level(FDL).Additionally,we estimated standing carbon stock,potential carbon stock,and theoretical space to grow by developing a stand growth model,which accounts for stand density across different site classes,to evaluate the restoration potential of degraded forests.The results indicate that degraded forest area in China is 36.15 million hectares,accounting for 20.10% of a total forest area.Standing carbon stock and potential carbon stock of degraded forests in China are 23.93 million tons and 61.90 million tons,respectively.Overall,degraded forest varies significantly across different regions.The results highlight the important trade-offs among environmental factors,policy decisions,and forest conditions,providing a robust foundation for developing measures to enhance forest quality.展开更多
Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satell...Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satellite images of several bands at various frequencies,the mix of high-and low-resolution images that make object classification difficult because of the mixed pixel problem.Accuracy is impacted by the mixed pixel problem,which occurs when pixels belong to different classes and makes detection challenging.To identify mixed pixels,Band Math is used to merge numerous bands to generate a new band NDVI.Thresholding is used to analyze the edges of deforested and non-deforested areas.Segmentation is then used to analyze the pixels which helps to identify the number of mixed pixels to compute the deforested and non-deforested areas.Segmented image pixels are used to categorize the deforestation of the Brazilian Amazon Forest between 2019 and 2023.Verify how many pixels are mixed to improve accuracy and identify mixed pixel issues;compare the mixed and pure pixels of fuzzy clustering with the subtracted morphological image pixels.With the help of segmentation and clustering researchers effectively validate mixed pixels in a specific area.The proposed methodology is easy to analyze and helpful for an appropriate calculation of deforested and non-deforested areas.展开更多
Background:The forest musk deer,a rare fauna species found in China,is famous for its musk secretion which is used in selected Traditional Chinese medicines.However,over-hunting has led to musk deer becoming an endang...Background:The forest musk deer,a rare fauna species found in China,is famous for its musk secretion which is used in selected Traditional Chinese medicines.However,over-hunting has led to musk deer becoming an endangered species,and their survival is also greatly challenged by various high incidence and high mortality respiratory and intestinal diseases such as septic pneumonia and enteritis.Accumulating evidence has demonstrated that Akkermannia muciniphila(AKK)is a promising probiotic,and we wondered whether AKK could be used as a food additive in animal breeding pro-grammes to help prevent intestinal diseases.Methods:We isolated one AKK strain from musk deer feces(AKK-D)using an im-proved enrichment medium combined with real-time PCR.After confirmation by 16S rRNA gene sequencing,a series of in vitro tests was conducted to evaluate the probiotic effects of AKK-D by assessing its reproductive capability,simulated gas-trointestinal fluid tolerance,acid and bile salt resistance,self-aggregation ability,hy-drophobicity,antibiotic sensitivity,hemolysis,harmful metabolite production,biofilm formation ability,and bacterial adhesion to gastrointestinal mucosa.Results:The AKK-D strain has a probiotic function similar to that of the standard strain in humans(AKK-H).An in vivo study found that AKK-D significantly amelio-rated symptoms in the enterotoxigenic Escherichia coli(ETEC)-induced murine diar-rhea model.AKK-D improved organ damage,inhibited inflammatory responses,and improved intestinal barrier permeability.Additionally,AKK-D promoted the reconsti-tution and maintenance of the homeostasis of gut microflora,as indicated by the fact that AKK-D-treated mice showed a decrease in Bacteroidetes and an increase in the proportion of other beneficial bacteria like Muribaculaceae,Muribaculum,and unclas-sified f_Lachnospiaceae compared with the diarrhea model mice.Conclusion:Taken together,our data show that this novel AKK-D strain might be a potential probiotic for use in musk deer breeding,although further extensive system-atic research is still needed.展开更多
The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and...The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.展开更多
Forest structure is fundamental in determining ecosystem function,yet the impact of bamboo invasion on these structural characteristics remains unclear.We investigated 219 invasion transects at 41 sites across the dis...Forest structure is fundamental in determining ecosystem function,yet the impact of bamboo invasion on these structural characteristics remains unclear.We investigated 219 invasion transects at 41 sites across the distribution areas of Moso bamboo(Phyllostachys edulis)in China to explore the effects of bamboo invasion on forest structural attributes and diameter–height allometries by comparing paired plots of bamboo,mixed bamboo-tree,and non-bamboo forests along the transects.We found that bamboo invasion decreased the mean and maximum diameter at breast height,maximum height,and total basal area,but increased the mean height,stem density,and scaling exponent for stands.Bamboo also had a higher scaling exponent than tree,particularly in mixed forests,suggesting a greater allocation of biomass to height growth.As invasion intensity increased,bamboo allometry became more plastic and decreased significantly,whereas tree allometry was indirectly promoted by increasing stem density.Additionally,a humid climate may favour the scaling exponents for both bamboo and tree,with only minor contributions from topsoil moisture and nitrogen content.The inherent superiority of diameter–height allometry allows bamboo to outcompete tree and contributes to its invasive success.Our findings provide a theoretical basis for understanding the causes and consequences of bamboo invasion.展开更多
The proliferation of robot accounts on social media platforms has posed a significant negative impact,necessitating robust measures to counter network anomalies and safeguard content integrity.Social robot detection h...The proliferation of robot accounts on social media platforms has posed a significant negative impact,necessitating robust measures to counter network anomalies and safeguard content integrity.Social robot detection has emerged as a pivotal yet intricate task,aimed at mitigating the dissemination of misleading information.While graphbased approaches have attained remarkable performance in this realm,they grapple with a fundamental limitation:the homogeneity assumption in graph convolution allows social robots to stealthily evade detection by mingling with genuine human profiles.To unravel this challenge and thwart the camouflage tactics,this work proposed an innovative social robot detection framework based on enhanced HOmogeneity and Random Forest(HORFBot).At the core of HORFBot lies a homogeneous graph enhancement strategy,intricately woven with edge-removal techniques,tometiculously dissect the graph intomultiple revealing subgraphs.Subsequently,leveraging the power of contrastive learning,the proposed methodology meticulously trains multiple graph convolutional networks,each honed to discern nuances within these tailored subgraphs.The culminating stage involves the fusion of these feature-rich base classifiers,harmoniously aggregating their insights to produce a comprehensive detection outcome.Extensive experiments on three social robot detection datasets have shown that this method effectively improves the accuracy of social robot detection and outperforms comparative methods.展开更多
Over the past decades,the expansion of natu-ral secondary forests has played a crucial role in offsetting the loss of primary forests and combating climate change.Despite this,there is a gap in our understanding of ho...Over the past decades,the expansion of natu-ral secondary forests has played a crucial role in offsetting the loss of primary forests and combating climate change.Despite this,there is a gap in our understanding of how tree species’growth and mortality patterns vary with eleva-tion in these secondary forests.In this study,we analyzed data from two censuses(spanning a five-year interval)conducted in both evergreen broadleaved forests(EBF)and temperate coniferous forests(TCF),which have been recovering for half a century,across elevation gradients in a subtropical mountain region,Mount Wuyi,China.The results indicated that the relative growth rate(RGR)of EBF(0.028±0.001 cm·cm^(-1)·a^(-1))and the mortality rate(MR)(20.03%±1.70%)were 27.3%and 16.4%higher,respec-tively,than those of TCF.Interestingly,the trade-off between RGR and MR in EBF weakened as elevation increased,a trend not observed in TCF.Conversely,TCF consistently showed a stronger trade-off between RGR and MR compared to EBF.Generalized linear mixed models revealed that ele-vation influences RGR both directly and indirectly through its interactions with slope,crown competition index(CCI),and tree canopy height(CH).However,tree mortality did not show a significant correlation with elevation.Additionally,DBH significantly influenced both tree growth and mortal-ity,whereas and CH and CCI had opposite effects on tree growth between EBF and TCF.Our study underscores the importance of elevation in shaping the population dynamics and the biomass carbon sink balance of mountain forests.These insights enhance our understanding of tree species’life strategies,enabling more accurate predictions of forest dynamics and their response to environmental changes.展开更多
The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ec...The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.展开更多
In this paper,we show that an ideal generated by matching Rota-Baxter equations is a bideal of a Hopf algebra on decorated rooted forests.We then get a bialgebraic structure on the space of decorated rooted forests mo...In this paper,we show that an ideal generated by matching Rota-Baxter equations is a bideal of a Hopf algebra on decorated rooted forests.We then get a bialgebraic structure on the space of decorated rooted forests modulo this biideal.As an application,a connected graded bialgebra and so a graded Hopf algebra on matching Rota-Baxter algebras are constructed,which simplifies the Hopf algebraic structure proposed by[Pacific J.Math.,2022,317(2):441-475].展开更多
Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake;however,frequently occurring climate extremes and human activities have considerably threatened the stability ...Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake;however,frequently occurring climate extremes and human activities have considerably threatened the stability of forests.At the same time,detailed accounts of disturbances and forest responses are not yet well quantified in Asia.This study employed the Breaks For Additive Seasonal and Trend method-an abrupt-change detection method-to analyze the Enhanced Vegetation Index time series in East Asia,South Asia,and Southeast Asia.This approach allowed us to detect forest disturbance and quantify the resilience after disturbance.Results showed that 20%of forests experienced disturbance with an increasing trend from 2000 to 2022,and Southeast Asian countries were more severely affected by disturbances.Specifically,95%of forests had robust resilience and could recover from disturbance within a few decades.The resilience of forests suffering from greater magnitude of disturbance tended to be stronger than forests with lower disturbance magnitude.In summary,this study investigated the resilience of forests across the low and middle latitudes of Asia over the past two decades.The authors found that most forests exhibited good resilience after disturbance and about two-thirds had recovered to a better state in 2022.The findings of this study underscore the complex relationship between disturbance and resilience,contributing to comprehension of forest resilience through satellite remote sensing.展开更多
Collaborative forest management (CFM) is a form of forest governance in which local communities are involved in the management and decision-making processes related to forest resources. It is believed that forests und...Collaborative forest management (CFM) is a form of forest governance in which local communities are involved in the management and decision-making processes related to forest resources. It is believed that forests under such management are better in tree diversity and conservation status and thus hold more carbon stocks. The study assessed the impact of CFM on carbon stocks, tree species diversity & tree species density in Mabira Central Forest Reserve. Data were collected from plots that were systematically laid in the different purposively selected forest areas. The study findings show that there is no difference in stem density and carbon stocks between CFM and non-CFM areas. CFM areas had lower species richness compared to non-CFM areas. CFM areas, however, exhibited more species diversity than non-CFM areas. Climax colonization may favor a few dominant species over others, hence lowering species diversity despite the number of species being many in the understory, hence at the same time increasing species richness. Likewise, disturbance in CFM area may affect natural colonization and favor the emergency of many species either naturally or through assisted regeneration by reforestation, hence increasing diversity, whereas artificial selection of preferred species through harvesting may lower species richness, as observed. Recommendations for improving collaborative forest management (CFM) areas include implementing targeted interventions to enhance carbon sequestration, such as promoting reforestation and afforestation with high-carbon-storing species and strengthening monitoring and evaluation frameworks to assess carbon stock changes over time. Additionally, efforts should focus on enhancing biodiversity conservation by implementing more stringent protection measures and reducing human disturbance while encouraging community participation in biodiversity monitoring and conservation education.展开更多
基金funded by China National Science and Technology Support Program(Grant No.2012BAD21B02)
文摘This study aimed to demonstrate change in spatial correlation between Korean pine （Pinus koraiensis Sieb. et Zucc.） and three rare species, and change in spatial distribution of four species in response to a range of selective cutting intensities. We sampled three plots of mixed Korean pine and broad-leaf forest in Lushuihe Forestry Bureau of Jilin province, China. Plot 1, a control, was unlogged Korean pine broad-leaf forest. In plots 2 and 3, Korean pine was selectively cut at 15 and 30 % intensity, respectively, in the 1970s. Other species were rarely cut. We used point-pattern analysis to research the spatial distributions of four tree species and quantify spatial correlations between Korean pine and the other three species, Amur linden （Tilia amurensis Rupr.）, Manchurian ash （Fraxinus mandshurica Rupr.）, and Mongolian oak （Quercus mongolica Fisch.） in all three plots. The results of the study show that selective cutting at 15 % intensity did not significantly change either the species spatial patterns or the spatial correlation between Korean pine and broadleaf species. Selective cutting at 30 % intensity slightly affected the growth of Korean pine and valuable species in forest communities, and the effect was considered nondestructive and recoverable.
基金Supported by the International Science and Technology Cooperation Program of China(2011DFA90740)Science and Technology Cooperation Program between Ministry of Science and Technology of China and European Union(0906)+1 种基金Research and Innovation Foundation for Young Scholars of Hunan Academy of Forestry(2013LQJ08)Forestry Science and Technology Program of Hunan Province,China(XLK201417)
文摘In Yingzuijie National Nature Reserve, Pinus massoniana forest, mixed broadleaf-coniferous forest and evergreen broad-leaf forest were investigated to study the changing characteristics of woody debris （WD） during various succession stages o1 evergreen broad-leaf forest. The results showed that during various succession stages of evergreen broad-leaf forest in Yingzuijie National Nature Reserve, WD storage of each forest ranged from 1.26 to 8.82 t/hm^2, with the order of P. massoniana forest 〈 mixed broadleaf-coniferous forest 〈 evergreen broad-leaf forest, that is, it increased from early to late stages of the succession. At different succession stages, coarse woody debris （CWD） storage was 2 -9 times more than fine woody debris （FWD） storage, revealing that CWD was dominant in WD of each forest. CWD biomass accounted for 0.66% -2.21% of arbor biomass, so the forests were at the developmental stage.
基金supported by the"Strategic Priority Research Program"of the Chinese Academy of Sciences(XDA05050205)"International Science&Technology Cooperation Program of China(2012DFB30030)""Youth Innovation Fund of Hunan Academy of forestry"and the CFERN&GENE Award Funds for Ecological Papers
文摘To better understand the effect of forest succession on carbon sequestration, we investigated carbon stock and allocation of evergreen broadleaf forest, a major zonal forest in subtropical China. We sought to quantify the carbon sequestration potential. We sampled four forest types, shrub （SR）, pine （Pinus massoniana） forest （PF）, pin~ and broadleaf mixed forest （Mr） and evergreen broadleaf forest （BF）. A regression equation was constructed using tree height and diameter at breast height （DBH） and elements of total tree biomass. The equation was subse- quently utilized to estimate tree carbon storage. The carbon storage of understory, litter, and soil was also estimated.
基金funded by the Directorate of Research and Community Service,Directorate General of Research and Development,Ministry of Higher Education,Science and Technologyin accordance with the Implementation Contract for the Operational Assistance Program for State Universities,Research Program Number:109/C3/DT.05.00/PL/2025.
文摘Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.
文摘The basic principle of life table method is deseribed, and the method of tree height instead of tree age in static life table is suggested, and it is also discussed that the possibility of natural poplar -birch forest recover to broad-leaf Korean pine forest on low pitches in the Xiaoxing'an Mountains by this method. If there is no particular situation, Korean pines after high than 5m under natural Poplar-birch forest will basically survive and make their way into dominant callopy accompanied by climax broad-leaf species.
基金supported by the National Natural Science Foundation of China(42030508)the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(2019QZKK0301)the Key technology research and development projects in Xizang Autonomous Regions(XZ202101ZY0005G).
文摘A better understanding of the structure and dynamics of disturbed forests is key for forecasting their future successional trajectories.Despite vulnerability of subalpine forests to warming climate,little is known as to how their community composition has responded to disturbances and climate warming over decades.Before the 1970s,subalpine forests on the southeastern Qinghai-Tibet Plateau mainly experienced logging and fire,but afterwards they were more impacted by climate warming.Thus,they provide an excellent setting to test whether disturbances and climate warming led to changes in forest structure.Based on the analysis of 3145 forest inventory plots at 4-to 5-year resolution,we found that spruce-fir forests shifted to pine and broadleaved forests since the early 1970s.Such a turnover in species composition mainly occurred in the 1994e1998 period.By strongly altering site conditions,disturbances in concert with climate warming reshuffle community composition to warm-adapted broadleaf-pine species.Thus,moderate disturbances shifted forest composition through a gradual loss of resilience of spruce-fir forests.Shifts in these foundation species will have profound impacts on ecosystem functions and services.In the future,broadleaved forests could expand more rapidly than evergreen needle-leaved forests under moderate warming scenarios.In addition to climate,the effects of anthropogenic disturbances on subalpine forests should be considered in adaptive forest management and in projections of future forest changes.
基金National Key Research and Development Program of China,No.2023YFE0208100,No.2021YFC3000201Natural Science Foundation of Henan Province,No.232300420165。
文摘The Qinba Mountains are climatically and ecologically recognized as the north-south transitional zone of China.Analysis of its phenology is critical for comprehending the response of vegetation to climatic change.We retrieved the start of spring phenology(SOS)of eight forest communities from the MODIS products and adopted it as an indicator for spring phenology.Trend analysis,partial correlation analysis,and GeoDetector were employed to reveal the spatio-temporal patterns and climatic drivers of SOS.The results indicated that the SOS presented an advance trend from 2001 to 2020,with a mean rate of−0.473 d yr^(−1).The SOS of most forests correlated negatively with air temperature(TEMP)and positively with precipitation(PRE),suggesting that rising TEMP and increasing PRE in spring would forward and delay SOS,respectively.The dominant factors influencing the sensitivity of SOS to climatic variables were altitude,forest type,and latitude,while the effects of slope and aspect were relatively minor.The response of SOS to climatic factors varied significantly in space and among forest communities,partly due to the influence of altitude,slope,and aspect.
基金supported by National Key Research and Development Program of China(No.2021YFD2200405(S.R.L.))Natural Science Foundation of China(Grant No.31971653).
文摘With the rapid economic development and continuous expansion of human activities,forest degradation—characterized by reduced forest stock within the forest including declining carbon storage—poses significant threats to ecosystem stability.Understanding the current status of forest degradation and assessing potential carbon stocks in China are of strategic importance for making forest restoration efforts and enhancing carbon sequestration capacity.In this study,we used the national forest inventory data from 2009 to 2018 to develop a set of standard measures for assessing degraded forests across China,based on five key indicators:forest accumulation growth rate(FAGR),forest recruitment rate(FRR),tree species reduction rate(TSRR),forest canopy cover reduction rate(FCCRR),and forest disaster level(FDL).Additionally,we estimated standing carbon stock,potential carbon stock,and theoretical space to grow by developing a stand growth model,which accounts for stand density across different site classes,to evaluate the restoration potential of degraded forests.The results indicate that degraded forest area in China is 36.15 million hectares,accounting for 20.10% of a total forest area.Standing carbon stock and potential carbon stock of degraded forests in China are 23.93 million tons and 61.90 million tons,respectively.Overall,degraded forest varies significantly across different regions.The results highlight the important trade-offs among environmental factors,policy decisions,and forest conditions,providing a robust foundation for developing measures to enhance forest quality.
文摘Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satellite images of several bands at various frequencies,the mix of high-and low-resolution images that make object classification difficult because of the mixed pixel problem.Accuracy is impacted by the mixed pixel problem,which occurs when pixels belong to different classes and makes detection challenging.To identify mixed pixels,Band Math is used to merge numerous bands to generate a new band NDVI.Thresholding is used to analyze the edges of deforested and non-deforested areas.Segmentation is then used to analyze the pixels which helps to identify the number of mixed pixels to compute the deforested and non-deforested areas.Segmented image pixels are used to categorize the deforestation of the Brazilian Amazon Forest between 2019 and 2023.Verify how many pixels are mixed to improve accuracy and identify mixed pixel issues;compare the mixed and pure pixels of fuzzy clustering with the subtracted morphological image pixels.With the help of segmentation and clustering researchers effectively validate mixed pixels in a specific area.The proposed methodology is easy to analyze and helpful for an appropriate calculation of deforested and non-deforested areas.
基金This research was funded by Shaanxi Administration of Traditional Chinese Medicine Projects(2021-QYZL-01,2021-QYPT-001)Key R&D Project in Shaanxi Province(2023-YBSF-463)+1 种基金the Foundation of Science and Technology in Shaanxi Province(2020TD-050)the Fundamental Research Funds for the Central Universities(GK202205010).
文摘Background:The forest musk deer,a rare fauna species found in China,is famous for its musk secretion which is used in selected Traditional Chinese medicines.However,over-hunting has led to musk deer becoming an endangered species,and their survival is also greatly challenged by various high incidence and high mortality respiratory and intestinal diseases such as septic pneumonia and enteritis.Accumulating evidence has demonstrated that Akkermannia muciniphila(AKK)is a promising probiotic,and we wondered whether AKK could be used as a food additive in animal breeding pro-grammes to help prevent intestinal diseases.Methods:We isolated one AKK strain from musk deer feces(AKK-D)using an im-proved enrichment medium combined with real-time PCR.After confirmation by 16S rRNA gene sequencing,a series of in vitro tests was conducted to evaluate the probiotic effects of AKK-D by assessing its reproductive capability,simulated gas-trointestinal fluid tolerance,acid and bile salt resistance,self-aggregation ability,hy-drophobicity,antibiotic sensitivity,hemolysis,harmful metabolite production,biofilm formation ability,and bacterial adhesion to gastrointestinal mucosa.Results:The AKK-D strain has a probiotic function similar to that of the standard strain in humans(AKK-H).An in vivo study found that AKK-D significantly amelio-rated symptoms in the enterotoxigenic Escherichia coli(ETEC)-induced murine diar-rhea model.AKK-D improved organ damage,inhibited inflammatory responses,and improved intestinal barrier permeability.Additionally,AKK-D promoted the reconsti-tution and maintenance of the homeostasis of gut microflora,as indicated by the fact that AKK-D-treated mice showed a decrease in Bacteroidetes and an increase in the proportion of other beneficial bacteria like Muribaculaceae,Muribaculum,and unclas-sified f_Lachnospiaceae compared with the diarrhea model mice.Conclusion:Taken together,our data show that this novel AKK-D strain might be a potential probiotic for use in musk deer breeding,although further extensive system-atic research is still needed.
基金Under the auspices of National Natural Science Foundation of China(No.42201374,42071359)。
文摘The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.
基金supported by the National Natural Science Foundation of China(No.31988102)Yunnan Province Major Program for Basic Research Project(No.202101BC070002)+1 种基金Yunnan Province Science and Technology Talents and Platform Program(No.202305AA160014)Yunnan Province Key Research and Development Program of China(No.202303AC100009)。
文摘Forest structure is fundamental in determining ecosystem function,yet the impact of bamboo invasion on these structural characteristics remains unclear.We investigated 219 invasion transects at 41 sites across the distribution areas of Moso bamboo(Phyllostachys edulis)in China to explore the effects of bamboo invasion on forest structural attributes and diameter–height allometries by comparing paired plots of bamboo,mixed bamboo-tree,and non-bamboo forests along the transects.We found that bamboo invasion decreased the mean and maximum diameter at breast height,maximum height,and total basal area,but increased the mean height,stem density,and scaling exponent for stands.Bamboo also had a higher scaling exponent than tree,particularly in mixed forests,suggesting a greater allocation of biomass to height growth.As invasion intensity increased,bamboo allometry became more plastic and decreased significantly,whereas tree allometry was indirectly promoted by increasing stem density.Additionally,a humid climate may favour the scaling exponents for both bamboo and tree,with only minor contributions from topsoil moisture and nitrogen content.The inherent superiority of diameter–height allometry allows bamboo to outcompete tree and contributes to its invasive success.Our findings provide a theoretical basis for understanding the causes and consequences of bamboo invasion.
基金Funds for the Central Universities(grant number CUC24SG018).
文摘The proliferation of robot accounts on social media platforms has posed a significant negative impact,necessitating robust measures to counter network anomalies and safeguard content integrity.Social robot detection has emerged as a pivotal yet intricate task,aimed at mitigating the dissemination of misleading information.While graphbased approaches have attained remarkable performance in this realm,they grapple with a fundamental limitation:the homogeneity assumption in graph convolution allows social robots to stealthily evade detection by mingling with genuine human profiles.To unravel this challenge and thwart the camouflage tactics,this work proposed an innovative social robot detection framework based on enhanced HOmogeneity and Random Forest(HORFBot).At the core of HORFBot lies a homogeneous graph enhancement strategy,intricately woven with edge-removal techniques,tometiculously dissect the graph intomultiple revealing subgraphs.Subsequently,leveraging the power of contrastive learning,the proposed methodology meticulously trains multiple graph convolutional networks,each honed to discern nuances within these tailored subgraphs.The culminating stage involves the fusion of these feature-rich base classifiers,harmoniously aggregating their insights to produce a comprehensive detection outcome.Extensive experiments on three social robot detection datasets have shown that this method effectively improves the accuracy of social robot detection and outperforms comparative methods.
基金funded by the National Natural Science Foundation of China(Grant No.32271872).
文摘Over the past decades,the expansion of natu-ral secondary forests has played a crucial role in offsetting the loss of primary forests and combating climate change.Despite this,there is a gap in our understanding of how tree species’growth and mortality patterns vary with eleva-tion in these secondary forests.In this study,we analyzed data from two censuses(spanning a five-year interval)conducted in both evergreen broadleaved forests(EBF)and temperate coniferous forests(TCF),which have been recovering for half a century,across elevation gradients in a subtropical mountain region,Mount Wuyi,China.The results indicated that the relative growth rate(RGR)of EBF(0.028±0.001 cm·cm^(-1)·a^(-1))and the mortality rate(MR)(20.03%±1.70%)were 27.3%and 16.4%higher,respec-tively,than those of TCF.Interestingly,the trade-off between RGR and MR in EBF weakened as elevation increased,a trend not observed in TCF.Conversely,TCF consistently showed a stronger trade-off between RGR and MR compared to EBF.Generalized linear mixed models revealed that ele-vation influences RGR both directly and indirectly through its interactions with slope,crown competition index(CCI),and tree canopy height(CH).However,tree mortality did not show a significant correlation with elevation.Additionally,DBH significantly influenced both tree growth and mortal-ity,whereas and CH and CCI had opposite effects on tree growth between EBF and TCF.Our study underscores the importance of elevation in shaping the population dynamics and the biomass carbon sink balance of mountain forests.These insights enhance our understanding of tree species’life strategies,enabling more accurate predictions of forest dynamics and their response to environmental changes.
基金funded by the Central University D Project(HFW230600022)National Natural Science Foundation of China(71973021)+1 种基金National Natural Science Foundation Youth Funding Project(72003022)Heilongjiang Province University Think Tank Open Topic(ZKKF2022173).
文摘The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.
基金Supported by NSFC(No.12101316)Belt and Road Innovative Talents Exchange Foreign Experts project(No.DL2023014002L)。
文摘In this paper,we show that an ideal generated by matching Rota-Baxter equations is a bideal of a Hopf algebra on decorated rooted forests.We then get a bialgebraic structure on the space of decorated rooted forests modulo this biideal.As an application,a connected graded bialgebra and so a graded Hopf algebra on matching Rota-Baxter algebras are constructed,which simplifies the Hopf algebraic structure proposed by[Pacific J.Math.,2022,317(2):441-475].
基金jointly supported by the National Natural Science Foundation of China [grant number 42265012]the Funding by the Fengyun Application Pioneering Project [grant number FY-APP-ZX-2022.0221]。
文摘Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake;however,frequently occurring climate extremes and human activities have considerably threatened the stability of forests.At the same time,detailed accounts of disturbances and forest responses are not yet well quantified in Asia.This study employed the Breaks For Additive Seasonal and Trend method-an abrupt-change detection method-to analyze the Enhanced Vegetation Index time series in East Asia,South Asia,and Southeast Asia.This approach allowed us to detect forest disturbance and quantify the resilience after disturbance.Results showed that 20%of forests experienced disturbance with an increasing trend from 2000 to 2022,and Southeast Asian countries were more severely affected by disturbances.Specifically,95%of forests had robust resilience and could recover from disturbance within a few decades.The resilience of forests suffering from greater magnitude of disturbance tended to be stronger than forests with lower disturbance magnitude.In summary,this study investigated the resilience of forests across the low and middle latitudes of Asia over the past two decades.The authors found that most forests exhibited good resilience after disturbance and about two-thirds had recovered to a better state in 2022.The findings of this study underscore the complex relationship between disturbance and resilience,contributing to comprehension of forest resilience through satellite remote sensing.
文摘Collaborative forest management (CFM) is a form of forest governance in which local communities are involved in the management and decision-making processes related to forest resources. It is believed that forests under such management are better in tree diversity and conservation status and thus hold more carbon stocks. The study assessed the impact of CFM on carbon stocks, tree species diversity & tree species density in Mabira Central Forest Reserve. Data were collected from plots that were systematically laid in the different purposively selected forest areas. The study findings show that there is no difference in stem density and carbon stocks between CFM and non-CFM areas. CFM areas had lower species richness compared to non-CFM areas. CFM areas, however, exhibited more species diversity than non-CFM areas. Climax colonization may favor a few dominant species over others, hence lowering species diversity despite the number of species being many in the understory, hence at the same time increasing species richness. Likewise, disturbance in CFM area may affect natural colonization and favor the emergency of many species either naturally or through assisted regeneration by reforestation, hence increasing diversity, whereas artificial selection of preferred species through harvesting may lower species richness, as observed. Recommendations for improving collaborative forest management (CFM) areas include implementing targeted interventions to enhance carbon sequestration, such as promoting reforestation and afforestation with high-carbon-storing species and strengthening monitoring and evaluation frameworks to assess carbon stock changes over time. Additionally, efforts should focus on enhancing biodiversity conservation by implementing more stringent protection measures and reducing human disturbance while encouraging community participation in biodiversity monitoring and conservation education.
