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.

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.

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.

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.

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.

Assessing forest cover changes and fragmentation in the Himalayan temperate region: implications for forest conservation and management

This study comprehensively assessed long-term vegetation changes and forest fragmentation dynamics in the Himalayan temperate region of Pakistan from 1989 to 2019.Four satellite images,including Landsat-5 TM and Landsat-8 Operational Land Imager(OLI),were chosen for subsequent assessments in October 1989,2001,2011 and 2019.The classified maps of 1989,2001,2011 and 2019 were created using the maximum likelihood classifier.Post-classification comparison showed an overall accuracy of 82.5%and a Kappa coefficient of 0.79 for the 2019 map.Results revealed a drastic decrease in closed-canopy and open-canopy forests by 117.4 and 271.6 km^(2),respectively,and an increase in agriculture/farm cultivation by 1512.8 km^(2).The two-way ANOVA test showed statistically significant differences in the area of various cover classes.Forest fragmentation was evaluated using the Landscape Fragmentation Tool(LFT v2.0)between 1989 and 2019.The large forest core(>2.00 km^(2))decreased from 149.4 to 296.7 km^(2),and a similar pattern was observed in medium forest core(1.00-2.00 km^(2))forests.On the contrary,the small core(<1.00 km^(2))forest increased from 124.8 to 145.3 km^(2) in 2019.The perforation area increased by 296.9 km^(2),and the edge effect decreased from 458.9 to 431.7 km^(2).The frequency of patches also increased by 119.1 km^(2).The closed and open canopy classes showed a decreasing trend with an annual rate of 0.58%and 1.35%,respectively.The broad implications of these findings can be seen in the studied region as well as other global ecological areas.They serve as an imperative baseline for afforestation and reforestation operations,highlighting the urgent need for efficient management,conservation,and restoration efforts.Based on these findings,sustainable land-use policies may be put into place that support local livelihoods,protect ecosystem services,and conserve biodiversity.

Coupling and Long-term Change Characteristics of Forest Carbon Sink and Forestry Economic Development in China

[Objectives]To analyze the changes in of forest carbon sink and forestry economic development,provide reference for relevant management decisions,ecological governance and resource and environment management,and promote the development of green low-carbon economy in China.[Methods]Based on the data of six forest resource inventories from 1989 to 2018 and related studies,the comprehensive evaluation model of forest carbon sink and forestry economic development,the coupling degree model of forest carbon sink and forestry economic development,and the coupling coordination degree model of forest carbon sink and forestry economic development were adopted.The coupling degree of forest carbon sink and forestry economic development from 1992 to 2018 was analyzed.Stepwise regression and ARIMA model were used to analyze the influencing factors and lagging characteristics of forest carbon sink.The coupling degree between forest carbon sink and forestry economic development in China from 2019 to 2030 was predicted by autoregression and ADF test.The coupling between forest carbon sink and forestry economic development in China and its long-term change characteristics were also discussed in this study.[Results](i)The investment of ecological construction and protection,the actual investment of forestry key ecological projects,GDP and the import of forest products had a significant impact on forest resources carbon stock.The total output value of forestry industry,the actually completed investment of forestry key ecological projects and the export volume of forest products had a significant impact on the forest carbon sink,and the actually completed investment of forestry key ecological projects has the greatest impact on the two.(ii)The impact of actually completed investment of forestry key ecological projects had a lag of 2 years on the forest resources carbon stock and a lag of 1 year on the forest carbon sink.When investing in forest carbon sink,it is necessary to make a good plan in advance,and do a good job in forest resources management and time optimization.(iii)From 1992 to 2018,the coupling degree of forest resources carbon stock,forest carbon sink and long-term development of forestry economy in China was gradually increasing.Although there were some fluctuations in the middle time,the coupling degree of forest resources carbon stock and the long-term development of forestry economy increased by 9.24%annually,and the degree of coupling coordination increased from"serious imbalance"in 1992 to"high-quality coordination"in 2018.From 1993 to 2018,the coupling degree of forest carbon sink and long-term development of forestry economy increased by 9.63%annually,slightly faster than the coupling coordination degree of forest resources carbon stock and long-term development of forestry economy.The coordination level also rose from level 2 in 1993 to level 10 in 2018.(iv)The prediction shows that the coupling coordination degree of forest resources carbon stock,forest carbon sink and the long-term development of forestry economy would increase from 2019 to 2030.The coupling coordination degree(D)values of both were close to 1,the coordination level was also 10 for a long time,and the degree of coupling coordination was also maintained at the"high-quality coordination"level for a long time.[Conclusions]Forest has multiple benefits of society,economy and ecology,and forest carbon sink is only a benefit output.The long-term coupling analysis of forest carbon sink and forestry economic development is a key point to multiple benefit analysis.The analysis shows that the spillover effect and co-evolution effect of forest carbon sink in China are significant.From 1992 to 2018,the coupling coordination degree of forest carbon sink and forestry economic development was gradually rising.The prediction analysis also indicate that the coupling coordination degree between the forest carbon sink and the long-term development of forestry economy will remain at the level of"high-quality coordination"for a long time from 2019 to 2030.Therefore,improving the level of forest management and maintaining the current trend of increasing forest resources are the key to achieving the goal of carbon peaking and carbon neutrality in China.

Factors Impacting Benefits of Participatory Forest Management in Upper Imenti Forest, Meru County, Kenya

This study focused on identifying factors affecting the benefits of Participatory Forestry Management (PFM) income generating activities in Upper Imenti Forest and whether they are dependent on status of participation in forest management through membership of Community Forest Association (CFA) or not. Cross-sectional survey research design was applied for collecting quantitative data using a semi-structured questionnaire administered to 384 households stratified on the basis of PFM participation status. Qualitative data was collected through focused group discussions using a checklist and key informant interviews using an interview schedule. Using Statistical Package for Social Sciences version 25, Binomial regression with Wald Chi-square was analyzed to identify factors perceived to be significantly influencing benefits for PFM participants and Pearson Chi-square to compare factors perceived to be affecting PFM and non-PFM participants. CFA members participation in PFM was significantly and positively affected by benefits of PFM income generating activities and forest products accessed in the forest. Benefits linked to Plantation Establishment for Livelihood Improvement System (PELIS) for CFA members were significantly reduced by enforcement of moratorium policy since February 2018, diseases and pests, poor PELIS guideline adherence and animal damage. Benefits related to state forest access for firewood by the CFA members were negatively influenced by the moratorium policy. Diseases and pests affected benefits associated with bee keeping significantly. Comparing factors under different PFM participation status, crop production was significantly affected by policy changes, pest and diseases, animal damage and PELIS guideline adherence for CFA members than for Non-CFA members. Policy changes also affected the CFA members significantly in firewood collection and access to fodder in the state forest than the Non-CFA members. Hence, sustainable community participation in Upper Imenti Forest management requires: increasing PFM benefits, addressing factors reducing benefits and enhancing active participation of CFA members in PFM related decision-making processes.

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。

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.

No generality in biodiversity-productivity relationships along elevation in temperate and subtropical forest landscapes

An improved understanding of biodiversity-productivity relationships(BPRs)along environmental gradients is crucial for effective ecosystem management and biodiversity conservation.The stress-gradient hypothesis suggests that BPRs are stronger in stressful environments compared to more favorable conditions.However,there is limited knowledge regarding the variation of BPRs along elevational gradients and their generality across different landscapes.To study how BPRs change with elevation,we harnessed inventory data on 6,431 trees from152 plots surveyed twice in eight to ten year intervals in mountain forests of temperate Europe and subtropical Asia.We quantified the relationship between aboveground productivity and different biodiversity measures,including taxonomic,functional,and phylogenetic diversity.To elucidate the processes underlying BPRs,we studied the variation of different functional traits along elevation across landscapes.We found no general pattern of BPRs across landscapes and elevations.Relationships were neutral for all biodiversity measures in temperate forests,and negative for taxonomic and functional diversity in subtropical forests.BPRs were largely congruent between taxonomic,functional and phylogenetic diversity.We found only weak support for the stress-gradient hypothesis,with BPRs turning from negative to positive(effect not significant)close to the tree line in subtropical forests.In temperate forests,however,elevation patterns were strongly modulated by species identity effects as influenced by specific traits.The effect of traits such as community-weighted mean of maximum plant height and wood density on productivity was congruent across landscapes.Our study highlights the context-dependence of BPRs across elevation gradients and landscapes.Species traits are key modulating factors of BPRs and should be considered more explicitly in studies of the functional role of biodiversity.Furthermore,our findings highlight that potential trade-offs between conserving biodiversity and fostering ecosystem productivity exist,which require more attention in policy and management.

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.

Tree species identity and interaction determine vertical forest structure in young planted forests measured by terrestrial laser scanning

Vertical forest structure is closely linked to multiple ecosystem characteristics,such as biodiversity,habitat,and productivity.Mixing tree species in planted forests has the potential to create diverse vertical forest structures due to the different physiological and morphological traits of the composing tree species.However,the relative importance of species richness,species identity and species interactions for the variation in vertical forest structure remains unclear,mainly because traditional forest inventories do not observe vertical stand structure in detail.Terrestrial laser scanning(TLS),however,allows to study vertical forest structure in an unprecedented way.Therefore,we used TLS single scan data from 126 plots across three experimental planted forests of a largescale tree diversity experiment in Belgium to study the drivers of vertical forest structure.These plots were 9–11years old young pure and mixed forests,characterized by four levels of tree species richness ranging from monocultures to four-species mixtures,across twenty composition levels.We generated vertical plant profiles from the TLS data and derived six stand structural variables.Linear mixed models were used to test the effect of species richness on structural variables.Employing a hierarchical diversity interaction modelling framework,we further assessed species identity effect and various species interaction effects on the six stand structural variables.Our results showed that species richness did not significantly influence most of the stand structure variables,except for canopy height and foliage height diversity.Species identity on the other hand exhibited a significant impact on vertical forest structure across all sites.Species interaction effects were observed to be site-dependent due to varying site conditions and species pools,and rapidly growing tree species tend to dominate these interactions.Overall,our results highlighted the importance of considering both species identity and interaction effects in choosing suitable species combinations for forest management practices aimed at enhancing vertical forest structure.

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.

Early response of understory vegetation to the mass dieback of Norway spruce in the European lowland temperate forest

Spruce-dominated forests are commonly exposed to disturbances associated with mass occurrences of bark beetles.The dieback of trees triggers many physical and chemical processes in the ecosystem resulting in rapid changes in the vegetation of the lower forest layers.We aimed to determine the response of non-tree understory vegetation to the mass dieback of Norway spruce(Picea abies)in the first years after the disturbance caused by the European spruce bark beetle(Ips typographus)outbreak.Our study area was the Białowieża Biosphere Reserve covering the Polish part of the emblematic Białowieża Forest,in total 597km^(2).The main data source comprised 3,900 phytosociological relevés(combined spring and summer campaigns)collected from 1,300 systematically distributed forest sites in 2016–2018–the peak years of the bark beetle outbreak.We found that the understory responded immediately to mass spruce dieback,with the most pronounced changes observed in the year of the disturbance and the subsequent year.Shade-tolerant forest species declined in the initial years following the mass spruce dieback,while hemicryptophytes,therophytes,light-demanding species associated with non-forest seminatural communities,as well as water-demanding forest species,expanded.Oxalis acetosella,the most common understory species in the Białowieża Forest,showed a distinct fluctuation pattern,with strong short-term expansion right after spruce dieback,followed by a gradual decline over the next 3–4 years to a cover level 5 percentage points lower than before the disturbance.Thus,our study revealed that mass spruce dieback selectively affects individual herb species,and their responses can be directional and non-directional(fluctuation).Furthermore,we demonstrated that the mass dieback of spruce temporarily increases plant species diversity(α-diversity).

Prediction and driving factors of forest fire occurrence in Jilin Province,China

Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.

Tree structure and diversity shape the biomass of primary temperate mountain forests

Primary forests are spatially diverse terrestrial ecosystems with unique characteristics,being naturally regenerative and heterogeneous,which supports the stability of their carbon storage through the accumulation of live and dead biomass.Yet,little is known about the interactions between biomass stocks,tree genus diversity and structure across a temperate montane primary forest.Here,we investigated the relationship between tree structure(variability in basal area and tree size),genus-level diversity(abundance,tree diversity)and biomass stocks in temperate primary mountain forests across Central and Eastern Europe.We used inventory data from726 permanent sample plots from mixed beech and spruce across the Carpathian Mountains.We used nonlinear regression to analyse the spatial variability in forest biomass,structure,and genus-level diversity and how they interact with plot-level tree age,disturbances,temperature and altitude.We found that the combined effects of genus and structural indices were important for addressing the variability in biomass across different spatial scales.Local processes in disturbance regimes and uneven tree age support forest hete rogeneity and the accumulation of live and dead biomass through the natural regeneration,growth and decay of the forest ecosystem.Structural complexities in basal area index,supporte d by genus-level abundance,positively influence total biomass stocks,which was modulated by tree age and disturbances.Spruce forests showed higher tree density and basal area than mixed beech forests,though mixed beech still contributes significantly to biomass across landscapes.Forest heterogeneity was strongly influenced by complexities in forest composition(tree genus diversity,structure).We addressed the importance of primary forests as stable carbon stores,achieved through structure and diversity.Safeguarding such ecosystems is critical for ensuring the stability of the primary forest,carbon store and biodiversity into the future.

Fire and retention island remnants have similar deadwood carbon stock a decade after disturbances in boreal forests of Alberta

In an attempt to reconcile wood extraction and forest biodiversity in managed boreal forests,ecosystem-based forest management(EBM)has become the de facto management approach.Retention forestry represents one prominent way that EBM is implemented in many parts of the world.Retention patches commonly left after harvesting serve as analogues of fire island remnants,which are patches of unburned forests in the burned forest matrix.Although the persistence of retention patches has been questioned,few studies have attempted to quantitatively compare forest attributes in both burned and harvested forests.As part of a larger program examining multiple aspects of ecosystem function in fire and harvest island remnants,we investigated the impact of disturbance type(fire/harvest)and forest edges on C stock in snags and coarse woody debris(CWD)found in island remnants in mixedwood boreal forests of Alberta,Canada.Total C stock(in snags and CWD)was similar between the two disturbance types and edge plots had similar total deadwood C stocks to interiors.The edges of island remnants had about two-fold more snag C stock than their interiors in both disturbance types,but C stock in CWD was unaffected by edge effects and disturbance type.Our results suggest that deadwood C dynamics in island remnants in fire and harvest disturbed boreal forests were similar,thus lending support for the continued implementation of retention forestry in Alberta.

A bibliometric analysis using machine learning to track paradigm shifts and analytical advances in forest ecology and forestry journal publications from 2010 to 2022

Forest habitats are critical for biodiversity,ecosystem services,human livelihoods,and well-being.Capacity to conduct theoretical and applied forest ecology research addressing direct(e.g.,deforestation)and indirect(e.g.,climate change)anthropogenic pressures has benefited considerably from new field-and statistical-techniques.We used machine learning and bibliometric structural topic modelling to identify 20 latent topics comprising four principal fields from a corpus of 16,952 forest ecology/forestry articles published in eight ecology and five forestry journals between 2010 and 2022.Articles published per year increased from 820 in 2010 to 2,354 in 2021,shifting toward more applied topics.Publications from China and some countries in North America and Europe dominated,with relatively fewer articles from some countries in West and Central Africa and West Asia,despite globally important forest resources.Most study sites were in some countries in North America,Central Asia,and South America,and Australia.Articles utilizing R statistical software predominated,increasing from 29.5%in 2010 to 71.4%in 2022.The most frequently used packages included lme4,vegan,nlme,MuMIn,ggplot2,car,MASS,mgcv,multcomp and raster.R was more often used in forest ecology than applied forestry articles.R software offers advantages in script and workflow-sharing compared to other statistical packages.Our findings demonstrate that the disciplines of forest ecology/forestry are expanding both in number and scope,aided by more sophisticated statistical tools,to tackle the challenges of redressing forest habitat loss and the socio-economic impacts of deforestation.

An agent-based model of agricultural land expansion in the mountain forest of Timor Island,Indonesia

The Mutis-Timau Forest Complex,located on Timor Island,Indonesia,is a mountainous tropical forest area that gradually decreases due to deforestation and forest degradation.Previous modelling studies based on patterns indicate that deforestation primarily occurs at lower elevations and near the boundaries of forests and settlements,often associated with shifting cultivation by local farmers.This study adopts a process-based modelling approach,specifically the agent-based model,to simulate land changes,particularly farmers'expansion of agricultural land around the Mutis mountain forest.The underlying concept of this agent-based approach is the interaction between the human and environmental systems.Farmers,representing the human system,interact with the land,which represents the environmental system,through land use decision-making mechanisms.The research was conducted in the Community Forest of the Timor Tengah Utara District,one of the sites within the Mutis-Timau Forest Complex with the highest deforestation rate.Land use change simulations were performed using agent-based modelling from 1999 to 2030,considering the socio-economic conditions of farmers,spatial preferences,land use decisions,and natural transitions.The results revealed that the agricultural area increased by 14%under the Business as Usual scenario and 5%under the Reducing Emission from Deforestation and Forest Degradation scenario,compared to the initial agricultural area of 245 hectares.The probability of farmers deciding to extend agricultural activities was positively associated with the number of livestock maintained by farmers and the size of the village area.Conversely,the likelihood of farmers opting for agricultural extensification decreased with an increase in the area of private land and the farmer's age.These findings are crucial for the managers of the Mutis-Timau Forest Complex and other relevant stakeholders,as they aid in arranging actions to combat deforestation,designing proper forest-related policies,and providing support for initiatives such as reducing emissions from deforestation and forest degradation programs or further incentive schemes.