Spatial analysis of carbon storage density of mid-subtropical forests using geostatistics： a case study in Jiangle County, southeast China

The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) distribution in temperate forests. However, our knowledge of CSD in subtropical forests is limited. In this study, Jiangle County was selected as a study case to explore geographic variation in CSD. A spatial heterogeneity analysis by semivariogram revealed that CSD varied at less than the mesoscale(approximately 2000–3000 m). CSD distribution mapped using Kriging regression revealed an increasing trend in CSD from west to east of the study area.Global spatial autocorrelation analysis indicated that CSD was clustered at the village level(at 5% significance).Some areas with local spatial autocorrelation were detected by Anselin Local Moran's I and Getis-Ord G*. A geographically weighted regression model showed different impacts on the different areas for each determinant. Generally, diameter at breast height, tree height, and stand density had positive correlation with CSD in Jiangle County, but varied substantially in magnitude by location.In contrast, coefficients of elevation and slope ranged from negative to positive. Based on these results, we propose certain measures to increase forest carbon storage,including increasing forested area, improving the quality of the current forests, and promoting reasonable forest management decisions and harvesting strategies. The established CSD model emphasizes the important role of midsubtropical forest in carbon sequestration and provides useful information for quantifying mid-subtropical forest carbon storage.

Disentangling the factors that contribute to variation in forest biomass increments in the mid-subtropical forests of China

Mid-subtropical forests are the main vegetation type of global terrestrial biomes, and are critical for maintaining the global carbon balance. However, estimates of forest biomass increment in mid-subtropical forests remain highly uncertain. It is critically important to determine the relative importance of different biotic and abiotic factors between plants and soil, particularly with respect to their influence on plant regrowth. Consequently,it is necessary to quantitatively characterize the dynamicspatiotemporal distribution of forest carbon sinks at a regional scale. This study used a large, long-term dataset in a boosted regression tree（BRT） model to determine the major components that quantitatively control forest biomass increments in a mid-subtropical forested region（Wuyishan National Nature Reserve, China）. Long-term,stand-level data were used to derive the forest biomass increment, with the BRT model being applied to quantify the relative contributions of various biotic and abiotic variables to forest biomass increment. Our data show that total biomass（t） increased from 4.62 9 106 to 5.30 9 106 t between 1988 and 2010, and that the mean biomass increased from 80.19 ± 0.39 t ha-1（mean ± standard error） to 94.33 ± 0.41 t ha-1in the study region. The major factors that controlled biomass（in decreasing order of importance） were the stand, topography, and soil. Stand density was initially the most important stand factor, while elevation was the most important topographic factor. Soil factors were important for forest biomass increment but have a much weaker influence compared to the other two controlling factors. These results provide baseline information about the practical utility of spatial interpolationmethods for mapping forest biomass increments at regional scales.

Carbon storage in evergreen broad-leaf forests in mid-subtropical region of China at four succession stages

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.

Effect of Slash Burning on Nutrient Removal and Soil Fertility in Chinese Fir and Evergreen Broadleaved Forests of Mid-Subtropical China

A Chinese fir forest (Cunninghamia lanceolata, CF) and an evergreen broadleaved forest (EB) located inFujian Province, southeastern China, were examined following slash burning to compare nutrient capital andtopsoil properties with pre-burn levels. After fire, nutrient (N, P and K) removal from burning residues wasestimated at 302.5 kg ha-1 in the CF and 644.8 kg ha-1 in the EB. Fire reduced the topsoil capitals of totalN and P by about 20% and 10%, respectively, in both forests, while K capital was increased in the topsoils ofboth forests following fire. Total site nutrient loss through surface erosion was 28.4 kg (N) ha-1, 8.4 kg (P)ha-1 and 328.7 kg (K) ha-1 in the CF. In the EB, the losses of total N, P and K were 58.5, 10.5 and 396.3kg ha-1, respectively. Improvement of soil structure and increase in mineralization of nutrients associatedwith increased microbe number and enzyme activities and elevated soil respiration occurred 5 days after fire.However, organic matter and available nutrient contents and most of other soil parameters declined one yearafter fire on the burned CF and EB topsoils. These results suggest that short-term site productivity canbe stimulated immediately, but reduced subsequently by soil and water losses, especially in South China,where high-intensity precipitation, steep slopes and fragile soil can be expected. Therefore, the silviculturalmeasurements should be developed in plantation management.

Soil C and N Pools in Chinese Fir and Evergreen Broadleaf Forests and their Changes with Slash Burning in Mid-Subtropical China

Soil organic carbon （C） and total nitrogen （N） pools of a Chinese fir （Cunninghamia lanceolata （Lamb.） Hook.） （CF） forest, and an evergreen broadleaf （EB） forest located in mid-subtropical, southeastern China, were compared before clearcutting, with the effect of slash burning on organic C and total N in the top 10 cm of soil before and after burning also being evaluated. Prior to clearcutting CF forest had significantly lower （P 〈0.05） organic C and total N in the soil （0-100 cm） compared to EB forest with approximately 60% of the C and N at the two forest sites stored at the 0 to 40 cm soil. In post-burn samples of the 0-10 cm depth at 5 days, 1 year, and 5 years for CF and EB forests, significantly lower levels （P 〈0.05） of organic C and total N than those in the pre-burn samples were observed. Compared to the pre-burn levels, at post-burn year 5, surface soil organic C storage was only 85% in CF forest and 72% in EB forest, while total N storage was 77% for CF forest and 73% for EB forest. Slash burning caused marked long-term changes in surface soil C and N in the two forest types.

Soil nitrogen transformations varied with plant community under Nanchang urban forests in mid-subtropical zone of China

Soil N transformations using the polyvinyl chloride （PVC） closed-top tube in situ incubation method were studied in Nanchang urban forests of the mid-subtropical region of China in different months of 2007. Four plots of 20 m × 20 m were established in four different plant communities that represented typical successional stages of forest development including shrubs, coniferous forest, mixed forest and broad- leaved forest. Average concentrations of soil NH4^＋-N from January to December were not different among the four plant communities. The concentrations of soil NO3^--N and mineral N, and the annual rotes of ammonification, nitrification and net N-mineralization under the early successional shrub community and coniferous forest were generally lower than that of the late successional mixed and broad-leaved forests （p〈0.05）. Similar differences among the plant communities were also shown in the relative nitrification index （NH4^＋-N/NO3^--N） and relative nitrification intensity （nitrification rate/net N-mineralization rate）. The annual net N-mineralization rate was increased from younger to older plant communities, from 15.1 and 41.4 kg.ha^-1.a^-1 under the shrubs and coniferous forest communities to 98.0 and 112.9 kg.ha^-1.a^-1 under the mixed and broad-leaved forests, respectively. Moreover, the high annual nitrification rates （50-70 kg.ha^-1.a^-1） and its end product, NO3-N （2.4-3.8 mg·kg^-1）, under older plant communities could increase the potential risk of N loss. Additionally, the temporal patterns of the different soil N variables mentioned above varied with different plant community due to the combined affects of natural biological processes associated with forest maturation and urbanization. Our results indicated that urban forests are moving towards a state of＂N saturation＂ （extremely niUification rate and NO3^--N content） as they mature.

Carbon Reserve Characteristics of Arbor Layer in Mid-subtropical Evergreen Broad-leaved Forest

In this paper, secondary forest of Pinus massoniana , coniferous-broad-leaved mixed forest and broad-leaved evergreen forest were taken as research objects, to explore carbon reserve of arbor layer and its spatial distribution characteristics. At different succession stages, the sequence of organic carbon content in each organ was secondary forest of P. massoniana > coniferous-broad-leaved mixed forest> broad-leaved evergreen forest. Carbon reserve of arbor layer was the highest in broad-leaved evergreen forest, which was 129.34 t/hm 2, followed by coniferous-broad-leaved mixed forest (95.83 t/hm 2), and the minimum was 85.27 t/hm 2 in secondary forest of P. massoniana . In each stand type, the sequence of carbon reserve of each organ in arbor layer was trunk>root>branch>leaf>bark. Carbon reserve of arbor layer mainly concentrated in trunk, and the proportion to carbon reserve of arbor layer declined from secondary forest of P. massoniana to broad-leaved evergreen forest, while it had increasing relationship in root. In secondary forest of P. massoniana , coniferous-broad-leaved mixed forest and broad-leaved evergreen forest, individual with the diameter more than 20 cm accounted for the majority of carbon reserve in the arbor layer.

Patterns and driving factors of leaf C,N,and P stoichiometry in two forest types with different stand ages in a mid-subtropical zone

Background:Carbon(C),nitrogen(N),and phosphorus(P)stoichiometry is a key indicator of nutrient utilization in plants,and C/N/P ratios are related to the life histories and adaptation strategies of tree species.However,no consensus has been reached on how leaf stoichiometric characteristics are affected by forest type and stand ages.The relationships between leaf stoichiometry and geographical,meteorological,and soil factors also remain poorly understood.Methods:Leaf and soil were sampled from forest stands of different age groups(young,middle-aged,near-mature,and mature)in two forest types(Chinese fir(Cunninghamia lanceolata)forests and evergreen broadleaved forests).The relationships between leaf C,N,and P stoichiometric parameters and geographical,meteorological,and soil factors were analysed by using redundancy analysis(RDA)and stepwise linear regression analysis.Results:Leaf C concentrations peaked in the near-mature stands with increasing age irrespective of forest type.Leaf N and P concentrations fluctuated with a rising trend in Chinese fir forests,while decreased first and increased later from young to mature phases in natural evergreen broadleaved forests.Chinese fir forests were primarily limited by N and P,while natural evergreen broadleaved forests were more susceptible to P limitation.Leaf C,N,and P stoichiometric characteristics in Chinese fir forests were mainly affected by the soil total P concentration(SP),longitude(LNG),growing season precipitation(GSP)and mean temperature in July(JUT).The leaf C concentration was mainly affected by GSP and JUT;leaf N and P concentrations were both positively correlated with LNG;and leaf P was positively correlated with SP.In evergreen broadleaved forests,however,leaf stoichiometric parameters displayed significant correlations with latitude(LAT)and mean annual precipitation(MAP).Conclusions:Leaf stoichiometry differed among forest stands of different age groups and forest types.Leaf C,N,and P stoichiometry was primarily explained by the combinations of SP,LNG,GSP and JUT in Chinese fir forests.LAT and MAP were the main controlling factors affecting the variations in the leaf C,N,and P status in natural evergreen broadleaved forests,which supports the temperature-plant physiological hypothesis.These findings improve the understanding of the distribution patterns and driving mechanisms of leaf stoichiometry linked with stand age and forest type.

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。

The impact of land use/cover change on storage and quality of soil organic carbon in mid-subtropical mountainous area of southern China

Land use/cover change （LUCC） is widely recognized as one of the most important driving forces of global carbon cycles. The influence of converting native forest into plantations, secondary forest, orchard and arable land on stores and quality of soil organic carbon （SOC） was investigated in mid-subtropical mountainous area of southern China. The results showed that LUCC had led to great decreases in SOC stocks and quality. Considerable SOC and light-fraction organic carbon （LFOC） had been stored in the native forest （142.2 t hm^-2 and 14.8 t hm^-2 respectively）. When the native forest was converted to plantations, secondary forest, orchard and arable land, the SOC stocks decreased by 25.6%, 28.7%, 38.0%, 31.8% and 51.2%, respectively. The LFOC stocks decreased by 52.2% to 57.2% when the native forest was converted to woodland plantations and secondary forest, and by 82.1% to 84.2% when converted to economic plantation, orchard and arable land. After the conversion, the ratios of LFOC to SOC （0-60 cm） decreased from 13.3% to about 3.0% to 10.7%. The SOC and LFOC stored at the upper 20 cm were more sensitive to LUCC when compared to the subsurface soil layer. Also, the decline in carbon storage induced by LUCC was greater than the global average level, it could be explained by the vulnerable natural environment and special human management practices. Thus, it is wise to enhance soil carbon sequestration, mitigate elevated atmospheric CO2 and develop ecological services by protecting vulnerable environment, restoring vegetation coverage, and afforesting in mountainous area in mid-subtropics.

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.

A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm

Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face many challenges. This paper studies the problems of difficult feature information extraction,low precision of thin-layer identification and limited applicability of the model in intelligent lithologic identification. The author tries to improve the comprehensive performance of the lithology identification model from three aspects: data feature extraction, class balance, and model design. A new real-time intelligent lithology identification model of dynamic felling strategy weighted random forest algorithm(DFW-RF) is proposed. According to the feature selection results, gamma ray and 2 MHz phase resistivity are the logging while drilling(LWD) parameters that significantly influence lithology identification. The comprehensive performance of the DFW-RF lithology identification model has been verified in the application of 3 wells in different areas. By comparing the prediction results of five typical lithology identification algorithms, the DFW-RF model has a higher lithology identification accuracy rate and F1 score. This model improves the identification accuracy of thin-layer lithology and is effective and feasible in different geological environments. The DFW-RF model plays a truly efficient role in the realtime intelligent identification of lithologic information in closed-loop drilling and has greater applicability, which is worthy of being widely used in logging interpretation.

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。

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.