The changes in soil organic carbon stock and quality across a subalpine forest successional series

Soil organic carbon(SOC)affects the function of terrestrial ecosystem and plays a vital role in global carbon cycle.Yet,large uncertainty still existed regarding the changes in SOC stock and quality with forest succession.Here,the stock and quality of SOC at 1-m soil profile were investigated across a subalpine forest series,including shrub,deciduous broad-leaved forest,broadleaf-conifer mixed forest,middle-age coniferous forest and mature coniferous forest,which located at southeast of Tibetan Plateau.The results showed that SOC stock ranged from 9.8 to29.9 kg·m^(-2),and exhibited a hump-shaped response pattern across the forest successional series.The highest and lowest SOC stock was observed in the mixed forest and shrub forest,respectively.The SOC stock had no significant relationships with soil temperature and litter stock,but was positively correlated with wood debris stock.Meanwhile,the average percentages of polysaccharides,lignins,aromatics and aliphatics based on FTIR spectroscopy were 79.89%,0.94%,18.87%and 0.29%,respectively.Furthermore,the percentage of polysaccharides exhibited an increasing pattern across the forest successional series except for the sudden decreasing in the mixed forest,while the proportions of lignins,aromatics and aliphatics exhibited a decreasing pattern across the forest successional series except for the sudden increasing in the mixed forest.Consequently,the humification indices(HIs)were highest in the mixed forest compared to the other four successional stages,which means that the SOC quality in mixed forest was worse than other successional stages.In addition,the SOC stock,recalcitrant fractions and HIs decreased with increasing soil depth,while the polysaccharides exhibited an increasing pattern.These findings demonstrate that the mixed forest had higher SOC stock and worse SOC quality than other successional stages.The high proportion of SOC stock(66%at depth of 20-100 cm)and better SOC quality(lower HIs)indicate that deep soil have tremendous potential to store SOC and needs more attention under global chan ge.

基于Deep Forest算法的对虾急性肝胰腺坏死病(AHPND)预警数学模型构建

为预报池塘养殖凡纳对虾(Penaeus vannamei)急性肝胰腺坏死病(AHPND)的发生,自2020年开始,笔者对凡纳对虾养殖区开展了连续监测工作,包括与疾病发生相关的环境理化因子、微生物因子、虾体自身健康状况等18个候选预警因子指标,通过数据标准化处理后分析病原、宿主与环境之间的相关性,对候选预警因子进行筛选,基于Python语言编程结合Deep Forest、Light GBM、XGBoost算法进行数据建模和预测性能评判,仿真环境为Python2.7,以预警因子指标作为输入样本(即警兆),以对虾是否发病指标作为输出结果(即警情),根据输入样本和输出结果各自建立输入数据矩阵和目标数据矩阵,利用原始数据矩阵对输入样本进行初始化,结合函数方程进行拟合,拟合的源代码能利用已知环境、病原及对虾免疫指标数据对目标警情进行预测。最终建立了基于Deep Forest算法的虾体(肝胰腺内)细菌总数、虾体弧菌(Vibrio)占比、水体细菌总数和盐度的4维向量预警预报模型,准确率达89.00%。本研究将人工智能算法应用到对虾AHPND发生的预测预报,相关研究结果为对虾AHPND疾病预警预报建立了预警数学模型,并为对虾健康养殖和疾病防控提供了技术支撑和有力保障。

Understorey species distinguish late successional and ancient forests after decades of minimum human intervention: A case study from Slovenia

The main species composition drivers in temperate deciduous forests are environmental conditions, a stand?s age and the site history, e.g., the succession stage and past land use, as well as disturbance regime and current management. We compared plant species diversity and composition in late successional and ancient forests, cooccurring on the same small river island applying species accumulation curves and nonmetric multidimensional scaling, respectively. Given the island?s geomorphological characteristics, we expected these to be very similar before human intervention in the past. The forests experienced differing disturbance regimes in the past, while over the last 30 years, human intervention has been the same and reduced to a minimum. The ancient forest in this study had two major characteristics defining it as old, mature forest: continuity of presence for more than 200years and specific composition. The late successional forest experienced major disturbance in the 20th century and was allowed natural regeneration by bordering on the ancient forest, representing a potential species pool,and by decades of minimum human intervention. Our results showed that, even though there was no difference in species richness, we could still detect differences between the forests, particularly in the abundance and species composition of the understorey, among which geophytes had the most indicative importance. To make our results useful on a broader scale, we composed from the literature a species list of plants indicative for ancient forest and tested its application. These results are important for distinguishing between old and mature secondary stands and particularly for identifying old forest stands, which should be conserved and, in the case of fragmented landscapes, included in a network connecting forest fragments.

Twenty years of population dynamics in European beech-oak forest at their rear range margin anticipate changes in its structure and composition

There is an increasing interest in restoring degraded forests,which occupy half of the forest areas.Among the forms of restoration,passive restoration,which involves the elimination of degrading factors and the free evolution of natural dynamics by applying minimal or no management,is gaining attention.Natural dynamics is difficult to predict due to the influence of multiple interacting factors such as climatic and edaphic conditions,composition and abundance of species,and the successional character of these species.Here,we study the natural dynamics of a mixed forest located in central Spain,which maintained an open forest structure,due to intensive use,until grazing and cutting were banned in the 1960s.The most frequent woody species in this forest are Fagus sylvatica,Quercus petraea,Quercus pyrenaica,Ilex aquifolium,Sorbus aucuparia,Sorbus aria and Prunus avium,with contrasting shade and drought tolerance.These species are common in temperate European deciduous forest and are found here near their southern distribution limit,except for Q.pyrenaica.In order to analyze forest dynamics and composition,three inventories were carried out in 1994,2005 and 2015.Our results show that,despite the Mediterranean influence,the natural dynamics of this forest has been mainly determined by different levels of shade tolerance.After the abandonment of grazing and cutting,Q.pyrenaica expanded rapidly due to its lower shade tolerance,whereas after canopy closure and forest densification,shade-tolerant species gained ground,particularly F.sylvatica,despite its lower drought and late-frost tolerance.If the current dynamics continue,F.sylvatica will overtake the rest of the species,which will be relegated to sites with shallow soils and steep slopes.Simultaneously,all the multi-centennial beech trees,which are undergoing a rapid mortality and decline process,will disappear.

Implication of community-level ecophysiological parameterization to modelling ecosystem productivity:a case study across nine contrasting forest sites in eastern China

Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.

Dendroclimatological study of Sabina saltuaria and Abies faxoniana in the mixed forests of the Qionglai Mountains,eastern Tibetan Plateau

Tree-ring chronologies were developed for Sabina saltuaria and Abies faxoniana in mixed forests in the Qionglai Mountains of the eastern Tibetan Plateau.Climate-growth relationship analysis indicated that the two co-exist-ing species reponded similarly to climate factors,although S.saltuaria was more sensitive than A.faxoniana.The strong-est correlation was between S.saltuaria chronology and regional mean temperatures from June to November.Based on this relationship,a regional mean temperature from June to November for the period 1605-2016 was constructed.Reconstruction explained 37.3%of the temperature variance during th period 1961-2016.Six major warm periods and five major cold periods were identified.Spectral analysis detected significant interannual and multi-decadal cycles.Reconstruction also revealed the influence of the Atlantic Multi-decadal Oscillation,confirming its importance on climate change on the eastern Tibetan Plateau.

Life forms affect beta-diversity patterns of larch forests in China

Beta-diversity reflects the spatial changes in community species composition which helps to understand how communities are assembled and biodiversity is formed and maintained. Larch(Larix) forests, which are coniferous forests widely distributed in the mountainous and plateau areas in North and Southwest China, are critical for maintaining the environmental conditions and species diversity. Few studies of larch forests have examined the beta-diversity and its constituent components(species turnover and nestedness-resultant components). Here, we used 483 larch forest plots to determine the total betadiversity and its components in different life forms(i.e., tree, shrub, and herb) of larch forests in China and to evaluate the main drivers that underlie this beta-diversity. We found that total betadiversity of larch forests was mainly dependent on the species turnover component. In all life forms,total beta-diversity and the species turnover component increased with increasing geographic, elevational, current climatic, and paleoclimatic distances. In contrast, the nestedness-resultant component decreased across these same distances. Geographic and environmental factors explained 20%-25% of total beta-diversity, 18%-27% of species turnover component, and 4%-16% of nestedness-resultant component. Larch forest types significantly affected total beta-diversity and species turnover component. Taken together, our results indicate that life forms affect beta-diversity patterns of larch forests in China, and that beta-diversity is driven by both niche differentiation and dispersal limitation. Our findings help to greatly understand the mechanisms of community assemblies of larch forests in China.

Aboveground carbon sequestration of Cunninghamia lanceolata forests:Magnitude and drivers

Understanding the spatial variation,temporal changes,and their underlying driving forces of carbon sequestration in various forests is of great importance for understanding the carbon cycle and carbon management options.How carbon density and sequestration in various Cunninghamia lanceolata forests,extensively cultivated for timber production in subtropical China,vary with biodiversity,forest structure,environment,and cultural factors remain poorly explored,presenting a critical knowledge gap for realizing carbon sequestration supply potential through management.Based on a large-scale database of 449 permanent forest inventory plots,we quantified the spatial-temporal heterogeneity of aboveground carbon densities and carbon accumulation rates in Cunninghamia lanceolate forests in Hunan Province,China,and attributed the contributions of stand structure,environmental,and management factors to the heterogeneity using quantile age-sequence analysis,partial least squares path modeling(PLS-PM),and hot-spot analysis.The results showed lower values of carbon density and sequestration on average,in comparison with other forests in the same climate zone(i.e.,subtropics),with pronounced spatial and temporal variability.Specifically,quantile regression analysis using carbon accumulation rates along an age sequence showed large differences in carbon sequestration rates among underperformed and outperformed forests(0.50 and 1.80 Mg·ha^(-1)·yr^(-1)).PLS-PM demonstrated that maximum DBH and stand density were the main crucial drivers of aboveground carbon density from young to mature forests.Furthermore,species diversity and geotopographic factors were the significant factors causing the large discrepancy in aboveground carbon density change between low-and high-carbon-bearing forests.Hotspot analysis revealed the importance of culture attributes in shaping the geospatial patterns of carbon sequestration.Our work highlighted that retaining largesized DBH trees and increasing shade-tolerant tree species were important to enhance carbon sequestration in C.lanceolate forests.

Community structure and species diversity dynamics of a subtropical evergreen broad-leaved forest in China:2005 to 2020

Here,we characterize the temporal and spatial dynamics of forest community structure and species diversity in a subtropical evergreen broad-leaved forest in China.We found that community structure in this forest changed over a 15-year period.Specifically,renewal and death of common species was large,with the renewal of individuals mainly concentrated within a few populations,especially those of Aidia canthioides and Cryptocarya concinna.The numbers of individual deaths for common species were concentrated in the small and mid-diameter level.The spatial distribution of community species diversity fluctuated in each monitoring period,showing a more dispersed diversity after the 15-year study period,and the coefficient of variation on quadrats increased.In 2010,the death and renewal of the community and the spatial variation of species diversity were different compared to other survey years.Extreme weather may have affected species regeneration and community stability in our subtropical monsoon evergreen broad-leaved forests.Our findings suggest that strengthening the monitoring and management of the forest community will help better understand the long-and short-term causes of dynamic fluctuations of community structure and species diversity,and reveal the factors that drive changes in community structure.

An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate

As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers.On the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule.The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications.The previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of accuracy.Hence,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF model.In the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,respectively.To examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM AR.Evaluation of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied models.The newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed RF.Also,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHAP)method,and it was found that thrust force per cutter is the most important variable on TBMAR.The GOGHS-RF model can be used in mechanized tunnel projects for predicting and checking performance.

一种基于KMeans与Random Forest的异常温升捕捉方法

针对线路老化、线路过载的火灾频发问题,分析了线路老化、线路过载与异常温升之间的关联性,以电流值、线缆温度作为输入,利用KMeans聚类算法划分可能存在异常温升的区间,通过Random Forest算法识别线路过载问题,可以提前通知用户整改线路,预防火灾的发生。

Evolutionary fingerprint, phylogenetic and forest structure of tropical montane Atlantic cloud forests along an elevation gradient

Environmental conditions can change markedly over geographical distances along elevation gradients,making them natural laboratories to study the processes that structure communities.This work aimed to assess the influences of elevation on Tropical Montane Cloud Forest plant communities in the Brazilian Atlantic Forest,a historically neglected ecoregion.We evaluated the phylogenetic structure,forest structure(tree basal area and tree density)and species richness along an elevation gradient,as well as the evolutionary fingerprints of elevation-success on phylogenetic lineages from the tree communities.To do so,we assessed nine communities along an elevation gradient from 1210 to 2310 m a.s.l.without large elevation gaps.The relationships between elevation and phylogenetic structure,forest structure and species richness were investigated through Linear Models.The occurrence of evolutionary fingerprint on phylogenetic lineages was investigated by quantifying the extent of phylogenetic signal of elevation-success using a genus-level molecular phylogeny.Our results showed decreased species richness at higher elevations and independence between forest structure,phylogenetic structure and elevation.We also verified that there is a phylogenetic signal associated with elevation-success by lineages.We concluded that the elevation is associated with species richness and the occurrence of phylogenetic lineages in the tree communities evaluated in Mantiqueira Range.On the other hand,elevation is not associated with forest structure or phylogenetic structure.Furthermore,closely related taxa tend to have their higher ecological success in similar elevations.Finally,we highlight the fragility of the tropical montane cloud forests in the Mantiqueira Range in face of environmental changes(i.e.global warming)due to the occurrence of exclusive phylogenetic lineages evolutionarily adapted to environmental conditions(i.e.minimum temperature)associated with each elevation range.

Assessment of large-scale multiple forest disturbance susceptibilities with AutoML framework: an Izmir Regional Forest Directorate case

Disturbances such as forest fires,intense winds,and insect damage exert strong impacts on forest ecosystems by shaping their structure and growth dynamics,with contributions from climate change.Consequently,there is a need for reliable and operational methods to monitor and map these disturbances for the development of suitable management strategies.While susceptibility assessment using machine learning methods has increased,most studies have focused on a single disturbance.Moreover,there has been limited exploration of the use of“Automated Machine Learning(AutoML)”in the literature.In this study,susceptibility assessment for multiple forest disturbances(fires,insect damage,and wind damage)was conducted using the PyCaret AutoML framework in the Izmir Regional Forest Directorate(RFD)in Turkey.The AutoML framework compared 14 machine learning algorithms and ranked the best models based on AUC(area under the curve)values.The extra tree classifier(ET)algorithm was selected for modeling the susceptibility of each disturbance due to its good performance(AUC values>0.98).The study evaluated susceptibilities for both individual and multiple disturbances,creating a total of four susceptibility maps using fifteen driving factors in the assessment.According to the results,82.5%of forested areas in the Izmir RFD are susceptible to multiple disturbances at high and very high levels.Additionally,a potential forest disturbances map was created,revealing that 15.6%of forested areas in the Izmir RFD may experience no damage from the disturbances considered,while 54.2%could face damage from all three disturbances.The SHAP(Shapley Additive exPlanations)methodology was applied to evaluate the importance of features on prediction and the nonlinear relationship between explanatory features and susceptibility to disturbance.

Pitfalls in forest carbon sink projection

Global forests are increasingly crucial for achiev-ing net-zero carbon emissions,with a quarter of the miti-gation efforts under the Paris Climate Agreement directed towards forests.In China,forests currently contribute to 13%of the global land’s carbon sink,but their stability and per-sistence remain uncertain.We examined and identified that published studies suffered from oversimplifications of eco-system succession and tree demographic dynamics,as well as poor constraints on land quality.Consequently,substan-tial estimations might have been suffered from underrepre-sented or ignored crucial factors,including tree demographic dynamics,and disturbances and habitat shifts caused by global climate change.We argue that these essential factors should be considered to enhance the reliability and accuracy of assessments of the potential for forest carbon sinks.

Aboveground biomass stocks of species-rich natural forests in southern China are influenced by stand structural attributes,species richness and precipitation

Forests,the largest terrestrial carbon sinks,play an important role in carbon sequestration and climate change mitigation.Although forest attributes and environmental factors have been shown to impact aboveground biomass,their influence on biomass stocks in species-rich forests in southern China,a biodiversity hotspot,has rarely been investigated.In this study,we characterized the effects of environmental factors,forest structure,and species diversity on aboveground biomass stocks of 30 plots(1 ha each) in natural forests located within seven nature reserves distributed across subtropical and marginal tropical zones in Guangxi,China.Our results indicate that forest aboveground biomass stocks in this region are lower than those in mature tropical and subtropical forests in other regions.Furthermore,we found that aboveground biomass was positively correlated with stand age,mean annual precipitation,elevation,structural attributes and species richness,although not with species evenness.When we compared stands with the same basal area,we found that aboveground biomass stock was higher in communities with a higher coefficient of variation of diameter at breast height.These findings highlight the importance of maintaining forest structural diversity and species richness to promote aboveground biomass accumulation and reveal the potential impacts of precipitation changes resulting from climate warming on the ecosystem services of subtropical and northern tropical forests in China.Notably,many natural forests in southern China are not fully stocked.Therefore,their continued growth will increase their carbon storage over time.

Stand dynamics of old-growth hemlock forests in central Bhutan are shaped by natural disturbances

Understanding how past disturbances have influenced the development of forests is critical for deciphering their current structure and composition and forecasting future changes.In this study,dendrochronological methods were applied to uncover the disturbance history of old-growth hemlock-dominated forests in central Bhutan.Analysis of tree-ring samples from two old-growth hemlock stands,located in two different topographic settings,identified the importance of gap-phase dynamics in facilitating recruitment and growth releases and producing complex,multi-aged structure s over time.One site showed evidence of a near stand-replacing disturbance in the late 1700s,while the other showed no evide nce of high-severity disturbance at any time over the last 400 years.At both sites low-to medium-severity disturbances,some of which appear to be associated with cyclones originating in the Bay of Bengal,dominated the disturbance regime.The hemlock stands exhibited a significant positive association between cyclone occurrence and growth release events and between recruitment pulses and growth release events.From 1800 to 1970 there was an increase in recruitment of angiosperm tree species at most sites and a corresponding decline in conifer recruitment.Over the past 50 years there has been little new recruitment;this may be due to light limitation in the understory from shade-tolerant angiosperms and bamboo in the lower strata of these stands.Significant variations in disturbance dynamics and recruitment were observed across the study sites,suggesting that other factors,such as topography and climate,may be influencing long-term stand development patterns.This study highlights the complex interplay between historical disturbance regimes and tree recruitment in shaping the age and size structures of old-growth hemlock forests in central Bhutan.It also provides new insights into the dynamics of these forests that can be used to support effective forest conservation and management in the future.

Accuracy of tree mapping based on hand-held laser scanning comparing leaf-on and leaf-off conditions in mixed forests

The use of mobile laser scanning to survey forest ecosystems is a promising,scalable technology to describe forest 3D structures at high resolution.To confirm the con-sistency in the retrieval of forest structural parameters using hand-held laser scanning(HLS),before operationalizing the method,confirming the data is crucial.We analyzed the per-formance of tree-level mapping based on HLS under differ-ent phenology conditions on a mixed forest in western Spain comprising Pinus pinaster and two deciduous species,Alnus glutinosa and Quercus pyrenaica.The area was surveyed twice during the growing season(July 2022)and once in the deciduous season(February 2022)using several scan-ning paths.Ground reference data(418 trees,15 snags)was used to calibrate the HLS data and to assess the influence of phenology when converting 3D data into tree-level attrib-utes(DBH,height and volume).The HLS-based workflow was robust at isolating tree positions and recognizing stems despite changes in phenology.Ninety-six percent of all pairs matched below 65 cm.For DBH,phenology barely altered estimates.We observed a strong agreement when comparing HLS-based tree height distributions.The values exceeded 2 m when comparing height measurements,confirming height data should be carefully used as reference in remote sensing-based inventories,especially for deciduous species.Tree volume was more precise for pines(r=0.95,and rela-tive RMSE=21.3–23.8%)compared to deciduous species(r=0.91–0.96,and relative RMSE=27.3–30.5%).HLS data and the forest structural complexity tool performed remark-ably,especially in tree positioning considering mixed forests and mixed phenology conditions.

PLFA Analysis of Soil Microbial Community Structure in Different Forest Types

Soil soluble organic matter is an important component in the study of carbon and nitrogen cycling in terrestrial ecosystems. Soil microorganisms, as soil decomposers, participate in soil biogeochemical processes and play an important role in maintaining the balance of soil ecosystems. As a typical subtropical regional unit, Queensland, Australia, is a relatively concentrated distribution area of forests in Australia. It is very sensitive to climate change and plays an important role in Australian climate and even global climate change. Its unique natural environment and ecosystem occupy a special position in the world. However, the knowledge of available carbon and nitrogen pool and microbial activity in forest soil is still very limited. Pinus elliottii, Araucaria cunninghamii and Agathis australis are the three most important forest types in southern Queensland, Australia. In our research, the function and structural diversity of soil microbial communities of these three forest types were studied using biochemical and molecular biological methods, and the effective carbon and nitrogen pools of soil of different forest types and related microbial processes were discussed, which has important theoretical guiding significance for further research on the structure and function of soil ecosystem. The number of PLFAs in the soil of P. elliottii was 45, the number of PLFAs in the soil of Araucaria cunninghamii and Agathis australis was 39 and 35, respectively. The number and content of PLFAs monomer in P. elliottii were higher than those in the other two kinds of forest soil.

Effects of urbanization and forest type on species composition and diversity,forest characteristics,biomass carbon sink,and their associations in Changchun,Northeast China:implications for urban carbon stock improvement

Differences in forest attributes and carbon sequestration of each organ and layer between broadleaved and conifer forests of central and outer urban areas are not well-defined,hindering the precise management of urban forests and improvement of function.To clarify the effect of two forest types with different urbanization intensities,we determined differences in vegetation composition and diversity,structural traits,and carbon stocks of 152 plots(20 m×20 m)in urban park forests in Changchun,which had the largest green quantity and carbon density effectiveness.We found that 1.1-fold thicker and healthier trees,and 1.6-to 2.0-fold higher,healthier,denser,and more various shrubs but with sparser trees and herbs occurred in the central urban forests(p<0.05)than in the outer forests.The conifer forests exhibited 30–70%obviously higher tree aboveground carbon sequestration(including stem and leaf)and 20%bigger trees,especially in the outer forests(p<0.05).In contrast,1.1-to 1.5-fold higher branch stocks,healthier and more diverse trees were found in broadleaved forests of both the inner and outer forests(p<0.05).Plant size and dominant species had similarly important roles in carbon stock improvement,especially big-sized woody plants and Pinus tabuliformis.In addition,a higher number of deciduous or needle species positively affected the broadleaved forest of the central urban area and conifer forest of the outer urban area,respectively.These findings can be used to guide precise management and accelerate the improvement of urban carbon function in Northeast China in the future.

Sustaining forest biodiversity:Exploring the effect of long-term natural disturbance dynamics on contemporary lichen communities in primary forest ecosystems

In this era of biodiversity loss and climate change,quantifying the impacts of natural disturbance on forest communities is imperative to improve biodiversity conservation efforts.Epiphytic and epixylic lichens are effective forest quality bioindicators,as they are generally long-lived organisms supported by continuity of specific forest structures and their associated microclimatic features.However,how lichen communities respond to the effects of fluctuating historical disturbances remains unclear.Using a dendrochronological approach,this study investigates how natural disturbance dynamics indirectly influence various lichen community metrics in some of Europe's best-preserved primary mixed-beech forests.Mixed modelling revealed that natural historical disturbance processes have decades-long effects on forest structural attributes,which had both congruent and divergent impacts on lichen community richness and composition.Total species richness indirectly benefited from both historical and recent higher-severity disturbances via increased standing dead tree basal area and canopy openness respectively-likely through the presence of both pioneer and late-successional species associated with these conditions.Red-listed species richness showed a dependence on habitat continuity(old trees),and increased with disturbance-related structures(standing dead trees)whilst simultaneously benefiting from periods without severe disturbance events(old trees and reduced deadwood volume).However,if the disturbance occurred over a century in the past,no substantial effect on forest structure was detected.Therefore,while disturbance-mediated forest structures can promote overall richness,threatened species appear vulnerable to more severe disturbance events-a concern,as disturbances are predicted to intensify with climate change.Additionally,the high number of threatened species found reinforce the critical role of primary forest structural attributes for biodiversity maintenance.Hence,we recommend a landscape-scale conservation approach encompassing forest patches in different successional stages to support diverse lichen communities,and the consideration of long-term disturbance dynamics in forest conservation efforts,as they provide critical insights for safeguarding biodiversity in our changing world.