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| 1 | Review on carbon storage estimation of forest ecosystem and applications in China显示文摘Background:The accuracy in estimating forest ecosystem carbon storage has drawn extensive attention of researchers in the field of global climate change.However,incomparable data sources and various estimation methods have led to significant differences in the estimation of forest carbon storage at large scales.Methods:In this study,we reviewed fundamental types of forest carbon storage estimation methods and their applications in China.Results:Results showed that the major forest carbon storage estimation methods were classified into 3 major categories and 15 subcategories focusing on vegetation carbon storage estimation,soil carbon storage estimation,and litter carbon storage estimation,respectively.The application in China showed that there have been 3 development stages of research in China since the 1990s.Studies of forest carbon storage estimation in province scales were conducted more frequently in the northeastern,eastern and southwestern provinces such as Zhejiang,Heilongjiang and Sichuan with high forest coverage or large forest area.Inventory-based methods,soil type method,and biomass model were the main forest estimation methods used in China,focusing on vegetation,soil and litter carbon storage estimation respectively.Total forest carbon storage of China was approximate 28.90 Pg C,and the average vegetation carbon density(42.04±5.39 Mg·ha?1)was much lower than that of the whole world(71.60 Mg·ha?1).Vegetation carbon density from average biomass method was the highest(57.07 Mg·ha?1)through comparing nine types of vegetation carbon storage estimation methods applied during 1989 to 1993.Conclusions:Many studies on forest carbon storages have been carried out in China at patch scales or regional scales.These efforts enabled the research of forest carbon storage to reach a relatively advanced stage.Meanwhile,the accumulation of massive research data provides the basis for subsequent research work.Some challenges are also existing.This review could provide a reference for more accurate estimation of forest carbon storage in the future. | Wanlong Sun Xuehua Liu | 2020 | Forest Ecosystems2020，7，1： | 12 |
| 2 | The national forest inventory in China:history-results-international context显示文摘Background:National forest resource assessments and monitoring,commonly known as National Forest Inventories(NFI's),constitute an important national information infrastructure in many countries.Methods:This study presents details about developments of the NFI in China,including sampling and plot design,and the uses of alternative data sources,and specifically· reviews the evolution of the national forest inventory in China through the 20 th and 21 st centuries,with some reference to Europe and the US;· highlights the emergence of some common international themes:consistency of measurement; more efficient sampling designs; implementation of improved technology; expansion of the variables monitored; scientific transparency;· presents an example of how China's expanding NFI exemplifies these global trends.Results:Main results and important changes in China's NFI are documented,both to support continued trend analysis and to provide data users with historical perspective.Conclusions:New technologies and data needs ensure that the Chinese NFI,like the national inventories in other countries,will continue to evolve.Within the context of historical change and current conditions,likely directions for this evolution are suggested. | Wei Sheng Zeng Erkki Tomppo Sean P.Healey Klaus V.Gadow | 2015 | Forest Ecosystems2015，2，4： | 8 |
| 3 | Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery显示文摘Background:Pine wilt disease(PWD)is a major ecological concern in China that has caused severe damage to millions of Chinese pines(Pinus tabulaeformis).To control the spread of PWD,it is necessary to develop an effective approach to detect its presence in the early stage of infection.One potential solution is the use of Unmanned Airborne Vehicle(UAV)based hyperspectral images(HIs).UAV-based HIs have high spatial and spectral resolution and can gather data rapidly,potentially enabling the effective monitoring of large forests.Despite this,few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine.Method:To fill this gap,we used a Random Forest(RF)algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data(data directly collected from trees in the field).We compared relative accuracy of each of these data collection methods.We built our RF model using vegetation indices(VIs),red edge parameters(REPs),moisture indices(MIs),and their combination.Results:We report several key results.For ground data,the model that combined all parameters(OA:80.17%,Kappa:0.73)performed better than VIs(OA:75.21%,Kappa:0.66),REPs(OA:79.34%,Kappa:0.67),and MIs(OA:74.38%,Kappa:0.65)in predicting the PWD stage of individual pine tree infection.REPs had the highest accuracy(OA:80.33%,Kappa:0.58)in distinguishing trees at the early stage of PWD from healthy trees.UAV-based HI data yielded similar results:the model combined VIs,REPs and MIs(OA:74.38%,Kappa:0.66)exhibited the highest accuracy in estimating the PWD stage of sampled trees,and REPs performed best in distinguishing healthy trees from trees at early stage of PWD(OA:71.67%,Kappa:0.40).Conclusion:Overall,our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage,although its accuracy must be improved before widespread use is practical.We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data.We believe that these results can be used to improve preventative measures in the control of PWD. | Run Yu Lili Ren Youqing Luo | 2021 | Forest Ecosystems2021，8，3： | 8 |
| 4 | Variation of net primary productivity and its drivers in China’s forests during 2000-2018显示文摘Background:Net primary productivity(NPP)in forests plays an important role in the global carbon cycle.However,it is not well known about the increase rate of China’s forest NPP,and there are different opinions about the key factors controlling the variability of forest NPP.Methods:This paper established a statistics-based multiple regression model to estimate forest NPP,using the observed NPP,meteorological and remote sensing data in five major forest ecosystems.The fluctuation values of NPP and environment variables were extracted to identify the key variables influencing the variation of forest NPP by correlation analysis.Results:The long-term trends and annual fluctuations of forest NPP between 2000 and 2018 were examined.The results showed a significant increase in forest NPP for all five forest ecosystems,with an average rise of 5.2 gC·m-2·year-1 over China.Over 90%of the forest area had an increasing NPP range of 0-161 gC·m-2·year-1.Forest NPP had an interannual fluctuation of 50-269 gC.m-2·year-1 for the five major forest ecosystems.The evergreen broadleaf forest had the largest fluctuation.The variability in forest NPP was caused mainly by variations in precipitation,then by temperature fluctuations.Conclusions:All five forest ecosystems in China exhibited a significant increasing NPP along with annual fluctuations evidently during 2000-2018.The variations in China’s forest NPP were controlled mainly by changes in precipitation. | Yuhe Ji Guangsheng Zhou Tianxiang Luo Yakir Dan Li Zhou Xiaomin Lv | 2020 | Forest Ecosystems2020，7，2： | 8 |
| 5 | Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation显示文摘This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys.It is motivated by the increasing availability of remotely sensed data,which facilitates the development of models predicting the variables of interest in forest surveys.We present,review and compare three different estimation frameworks where models play a core role:model-assisted,model-based,and hybrid estimation.The first two are well known,whereas the third has only recently been introduced in forest surveys.Hybrid inference mixes designbased and model-based inference,since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data.We review studies on large-area forest surveys based on model-assisted,modelbased,and hybrid estimation,and discuss advantages and disadvantages of the approaches.We conclude that no general recommendations can be made about whether model-assisted,model-based,or hybrid estimation should be preferred.The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data.We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass,which are adequately related to commonly available remotely sensed data,and thus purely field based surveys remain important for several important forest parameters. | Goran Stahl Svetlana Saarela Sebastian Schnell Soren Holm Johannes Breidenbach Sean P. Healey Paul L. Patterson Steen Magnussen Erik Naesset Ronald E. McRoberts Timothy G. Gregoire | 2016 | Forest Ecosystems2016，3，2： | 7 |
| 6 | Decomposition dynamics of coarse woody debris of three important central European tree species显示文摘Background:Coarse woody debris(CWD)is an important element of forest structure that needs to be considered when managing forests for biodiversity,carbon storage or bioenergy.To manage it effectively,dynamics of CWD decomposition should be known.Methods:Using a chronosequence approach,we assessed the decomposition rates of downed CWD of Fagus sylvatica,Picea abies and Pinus sylvestris,which was sampled from three different years of tree fall and three different initial diameter classes(>10 –≤ 20 cm,>20 –≤40 cm,>40 cm).Samples originating from wind throws in 1999 were collected along a temperature and precipitation gradient.Based on the decay class and associated wood densities,log volumes were converted into CWD mass and C content.Log fragmentation was assessed over one year for log segments of intermediate diameters(>20 – 40 cm)after 8 and 18 years of decomposition.Results:Significantly higher decomposition constants(k)were found in logs of F.sylvatica(0.054 year^(-1))than in P.abies(0.033 year^(-1))and P.sylvestris(0.032 year^(-1)).However,mass loss of P.sylvestris occurred mainly in sapwood and hence k for the whole wood may be overestimated.Decomposition rates generally decreased with increasing log diameter class except for smaller dimensions in P.abies.About 74 % of the variation in mass remaining could be explained by decomposition time(27 %),tree species(11 %),diameter(17 %),the interactive effects between tree species and diameter(4 %)as well as between decomposition time and tree species(3 %)and a random factor(site and tree; 9.5 %),whereas temperature explained only 2 %.Wood fragmentation may play a more important role than previously thought.Here,between 14 % and 30 % of the decomposition rates(for the first 18 years)were attributable to this process.Carbon(C)density(mg C · cm^(-3)),which was initially highest for F.sylvatica,followed by P.sylvestris and P.abies,decreased with increasing decay stage to similar values for all species.Conclusions:The apparent lack of climate effects on decomposition of logs in the field indicates that regional decomposition models for CWD may be developed on the basis of information on decomposition time,tree species and dimension only.These can then be used to predict C dynamics in CWD as input for C accounting models and for habitat management. | Steffen Herrmann Tiemo Kahl Jürgen Bauhus | 2015 | Forest Ecosystems2015，2，4： | 7 |
| 7 | Optimizing continuous cover management of boreal forest when timber prices and tree growth are stochastic显示文摘Background: Decisions on forest management are made under risk and uncertainty because the stand development cannot be predicted exactly and future timber prices are unknown. Deterministic calculations may lead to biased advice on optimal forest management. The study optimized continuous cover management of boreal forest in a situation where tree growth, regeneration, and timber prices include uncertainty.Methods: Both anticipatory and adaptive optimization approaches were used. The adaptive approach optimized the reservation price function instead of fixed cutting years. The future prices of different timber assortments were described by cross-correlated auto-regressive models. The high variation around ingrowth model was simulated using a model that describes the cross- and autocorrelations of the regeneration results of different species and years. Tree growth was predicted with individual tree models, the predictions of which were adjusted on the basis of a climate-induced growth trend, which was stochastic. Residuals of the deterministic diameter growth model were also simulated. They consisted of random tree factors and cross- and autocorrelated temporal terms.Results: Of the analyzed factors, timber price caused most uncertainty in the calculation of the net present value of a certain management schedule. Ingrowth and climate trend were less significant sources of risk and uncertainty than tree growth. Stochastic anticipatory optimization led to more diverse post-cutting stand structures than obtained in deterministic optimization. Cutting interval was shorter when risk and uncertainty were included in the analyses.Conclusions: Adaptive optimization and management led to 6%–14% higher net present values than obtained in management that was based on anticipatory optimization. Increasing risk aversion of the forest landowner led to earlier cuttings in a mature stand. The effect of risk attitude on optimization results was small. | Timo Pukkala | 2015 | Forest Ecosystems2015，2，2： | 6 |
| 8 | Designing near-natural planting patterns for plantation forests in China显示文摘Background: China has a long tradition of managing planted forests. Different species of Populus, Eucalyptus, Larix, Cunninghamia and Pinus are planted to satisfy the local demand for wood products and provide ecological services at the same time. Evidence of the greater resilience of natural forests provides the motivation to develop asymmetric planting patterns, which is the focus of this study. We present a new method for designing plantation patterns that follow those observed in natural ecosystems and to maintain some regularity for operational convenience. Methods: Based on the uniform angle index, we analyzed the spatial structure of six natural forests in different regions of China. The uniform angle index describes the degree of spatial uniformity of the n nearest neighbors of a given reference tree. Accordingly, we identified all possible patterns of a neighborhood group within a regular planting pattern and developed a method to optimize planting point arrangements that contain some randomness as well as a minimum degree of regularity. Results:(1) There are 13 types of structural units in a regular planting, including seven random units, five even units and one cluster unit;(2) Five near-natural arrangements are presented with a minimum proportion of 50% of random units. These five arrangements represent a combination of regularity for operational convenience and asymmetry. Conclusions: The new planting patterns developed in this study are expected to increase the asymmetric competition and resilience of these important ecosystems. Some experimental plantings, based on our findings, have already been established, e.g., in Pinus tabulaeformis plantations in Tianshui, Gansu Province, and in a Populus deltoides plantation in Fangshan near Beijing. | Gongqiao Zhang Gangying Hui Yanbo Hu Zhonghua Zhao Xiuling Guan Klaus von Gadow Ganggang Zhang | 2019 | Forest Ecosystems2019，6，3： | 6 |
| 9 | Diversity and production in an Afromontane Forest显示文摘Background:This contribution evaluates the effect of forest structure and tree species diversity on plot productivity and individual tree growth in the unique Knysna forests in Southern Africa using mapped tree data from an observational study that has been re-measured over a period of 40 years.Methods:The effects of tree species diversity and forest structure on tree growth and forest production are evaluated on three levels of resolution:a) the forest community(canopy,sub-canopy species),b) the subplots(number of trees per ha,skewness of the diameter distribution,diameter coefficient of variation) and c) the immediate neighborhood of selected reference trees('Mingling','Dominance',Aggregation' and 'Size Variation').Results:An analysis of the community level identified two distinct clusters,one including dominant/canopy species with the highest growth rates and a greater variation of growth,and another cluster which includes the remaining subcanopy species which have a smaller maximum size and lower rates of growth.The area-based structure variables on plot level have a highly significant effect on total basal area growth.However,the effects of forest density and species richness on productivity were not straight forward.Maximum basal area production of about 0.75 m^2/ha/year is achieved at medium levels of richness(around 20 species per ha) and medium levels of density(around 30 m^2/ha basal area) using percentile regression estimates.The relative 'Dominance' of a selected reference tree had a highly significant effect on individual tree growth on all investigated species.Other neighbourhood structure variables were only occasionally significant or not significant at all.Conclusion:This contribution presents a new theoretical framework for analysing natural forests that includes community,plot and neighborhood variables of forest structure and diversity,and a first specific analysis of the structure and dynamics of the Knysna Afromontane Forest,based on a unique set of longterm observations.The species-area(SAR) model developed in this study,represents a new general approach that can be used to derive a common standard of tree species diversity for different plot sizes,the species richness per hectare. | Klaus v.Gadow GongQiao Zhang Graham Durrheim David Drew Armin Seydack | 2016 | Forest Ecosystems2016，3，4： | 5 |
| 10 | Evaporation and potential evapotranspiration in India under conditions of recent and future climate change显示文摘 | N. Chattopadhyay M. Hulme | 1997 | Agricultural and Forest Meteorology1997，，1： | 5 |
| 11 | Estimating the productive potential of five natural forest types in northeastern China显示文摘Background: There is a serious lack of experience regarding the productive potential of the natural forests in northeastern China, which severely limits the development of sustainable forest management strategies for this most important forest region in China. Accordingly, the objective of this study is to develop a first comprehensive system for estimating the wood production for the five dominant forest types.Methods: Based on a network of 384 field plots and using the state-space approach, we develop a system of dynamic stand models, for each of the five main forest types. Four models were developed and evaluated, including a base model and three extended models which include the effects of dominant height and climate variables. The four models were fitted, and their predictive strengths were tested, using the 'seemingly unrelated regression'(SUR) technique.Results: All three of the extended models increased the accuracy of the predictions at varying degrees for the five major natural forest types of northeastern China. The inclusion of dominant height and two climate factors(precipitation and temperature) in the base model resulted in the best performance for all the forest types. On average, the root mean square values were reduced by 13.0% when compared with the base model.Conclusion: Both dominant height and climate factors were important variables in estimating forest production. This study not only presents a new method for estimating forest production for a large region, but also explains regional differences in the effect of site productivity and climate. | Zhaofei Wu Zhonghui Zhang Juan Wang | 2019 | Forest Ecosystems2019，6，4： | 5 |
| 12 | Soil-plant co-stimulation during forest vegetation restoration in a subtropical area of southern China显示文摘Background: Soil and vegetation have a direct impact on the process and direction of plant community succession, and determine the structure, function, and productivity of ecosystems. However, little is known about the synergistic influence of soil physicochemical properties and vegetation features on vegetation restoration. The aim of this study was to investigate the co-evolution of soil physicochemical properties and vegetation features in the process of vegetation restoration, and to distinguish the primary and secondary relationships between soil and vegetation in their collaborative effects on promoting vegetation restoration in a subtropical area of China.Methods: Soil samples were collected to 40 cm in four distinct plant communities along a restoration gradient from herb(4–5 years), to shrub(11–12 years), to Pinus massoniana coniferous and broadleaved mixed forest(45–46 years), and to evergreen broadleaved forest(old growth forest). Measurements were taken of the soil physicochemical properties and Shannon–Wiener index(SD), diameter at breast height(DBH), height(H), and biomass. Principal component analysis, linear function analysis, and variation partitioning analysis were then performed to prioritize the relative importance of the leading factors affecting vegetation restoration.Results: Soil physicochemical properties and vegetation features showed a significant trend of improvement across the vegetation restoration gradient, reflected mainly in the high response rates of soil organic carbon(SOC)(140.76%), total nitrogen(TN)(222.48%), total phosphorus(TP)(59.54%), alkaline hydrolysis nitrogen(AN)(544.65%),available phosphorus(AP)(53.28%), species diversity(86.3%), biomass(2906.52%), DBH(128.11%), and H(596.97%).The soil properties(pH, SOC, TN, AN, and TP) and vegetation features(biomass, DBH, and H) had a clear coevolutionary relationship over the course of restoration. The synergistic interaction between soil properties and vegetation features had the greatest effect on biomass(55.55%–72.37%), and the soil properties contributed secondarily(3.30%–31.44%). The main impact factors of biomass varied with the restoration periods.Conclusions: In the process of vegetation restoration, soil and vegetation promoted each other. Vegetation restoration was the cumulative result of changes in soil fertility and vegetation features. | Chan Chen Xi Fang Wenhua Xiang Pifeng Lei Shuai Ouyang and Yakov Kuzyakov | 2020 | Forest Ecosystems2020，7，3： | 5 |
| 13 | Using GEDI lidar data and airborne laser scanning to assess height growth dynamics in fast-growing species:a showcase in Spain显示文摘Background:The NASA’s Global Ecosystem Dynamics Investigation(GEDI)satellite mission aims at scanning forest ecosystems on a multi-temporal short-rotation basis.The GEDI data can validate and update statistics from nationwide airborne laser scanning(ALS).We present a case in the Northwest of Spain using GEDI statistics and nationwide ALS surveys to estimate forest dynamics in three fast-growing forest ecosystems comprising 211,346 ha.The objectives were:i)to analyze the potential of GEDI to detect disturbances,ii)to investigate uncertainty source regarding non-positive height increments from the 2015–2017 ALS data to the 2019 GEDI laser shots and iii)to estimate height growth using polygons from the Forest Map of Spain(FMS).A set of 258 National Forest Inventory plots were used to validate the observed height dynamics.Results:The spatio-temporal assessment from ALS surveying to GEDI scanning allowed the large-scale detection of harvests.The mean annual height growths were 0.79(SD=0.63),0.60(SD=0.42)and 0.94(SD=0.75)m for Pinus pinaster,Pinus radiata and Eucalyptus spp.,respectively.The median annual values from the ALS-GEDI positive increments were close to NFI-based growth values computed for Pinus pinaster and Pinus radiata,respectively.The effect of edge border,spatial co-registration of GEDI shots and the influence of forest cover in the observed dynamics were important factors to considering when processing ALS data and GEDI shots.Discussion:The use of GEDI laser data provides valuable insights for forest industry operations especially when accounting for fast changes.However,errors derived from positioning,ground finder and canopy structure can introduce uncertainty to understand the detected growth patterns as documented in this study.The analysis of forest growth using ALS and GEDI would benefit from the generalization of common rules and data processing schemes as the GEDI mission is increasingly being utilized in the forest remote sensing community. | Juan Guerra-Hernández Adrián Pascual | 2021 | Forest Ecosystems2021，8，1： | 4 |
| 14 | Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years显示文摘Background: In recent decades the future of global forests has been a matter of increasing concern, particularly in relation to the threat of forest ecosystem responses under potential climate change. To the future predictions of these responses, the current forest biomass carbon storage(FCS) should first be clarified as much as possible,especially at national scales. However, few studies have introduced how to verify an FCS estimate by delimiting the reasonable ranges. This paper addresses an estimation of national FCS and its verification using two-step process to narrow the uncertainty. Our study focuses on a methodology for reducing the uncertainty resulted by converting from growing stock volume to above-and below-ground biomass(AB biomass), so as to eliminate the significant bias in national scale estimations.Methods: We recommend splitting the estimation into two parts, one part for stem and the other part for AB biomass to preclude possible significant bias. Our method estimates the stem biomass from volume and wood density(WD), and converts the AB biomass from stem biomass by using allometric relationships.Results: Based on the presented two-step process, the estimation of China’s FCS is performed as an example to explicate how to infer the ranges of national FCS. The experimental results demonstrate a national FCS estimation within the reasonable ranges(relative errors: + 4.46% and-4.44%), e.g., 5.6–6.1 PgC for China’s forest ecosystem at the beginning of the 2010 s. These ranges are less than 0.52 PgC for confirming each FCS estimate of different periods during the last 40 years. In addition, our results suggest the upper-limits by specifying a highly impractical value of WD(0.7 t·m-3) on the national scale. As a control reference, this value decides what estimate is impossible to achieve for the FCS estimates.Conclusions: Presented methodological analysis highlights the possibility to determine a range that the true value could be located in. The two-step process will help to verify national FCS and also to reduce uncertainty in related studies. While the true value of national FCS is immeasurable, our work should motivate future studies that explore new estimations to approach the true value by narrowing the uncertainty in FCS estimations on national and global scales. | Xiaolu Zhou Xiangdong Lei Caixia Liu Huabing Huang Carl Zhou Changhui Peng | 2019 | Forest Ecosystems2019，6，4： | 4 |
| 15 | Energy balance closure at FLUXNET sites显示文摘 | Kell Wilson Allen Goldstein Eva Falge Marc Aubinet Dennis Baldocchi Paul Berbigier Christian Bernhofer Reinhart Ceulemans Han Dolman Chris Field Achim Grelle Andreas Ibrom B.E Law Andy Kowalski Tilden Meyers John Moncrieff Russ Monson Walter Oechel John T | 2002 | Agricultural and Forest Meteorology2002，，1： | 4 |
| 16 | Nutrient resorption strategies of three oak tree species in response to interannual climate variability显示文摘Background:Nutrient resorption is critical for plants toward balancing their nutritional requirements and adapting to environmental variabilities,which further impacts litter quality and nutrient cycling.However,the interannual variability of nutrient resorption under climate change remains unclear.Methods:We investigated the five-year nutrient resorption efficiencies(NuRE,%)of 14 elements in three deciduous oak tree species(Quercus aliena var.acuteserrata,Q.glandulifera,and Q.variabilis)in a warm-temperate forest of Central China and assessed their relationships with interannual climate and soil factors.Results:Nutrient resorption did not differ between species but varied significantly between different years.For each year,N,P,S,K,C,Mg,and Zn were preferentially resorbed in all of the oak species in contrast to Ca,Na,Mn,Ba,Al,Fe,Cu,which were to some extent discriminated.Among the 14 elements,the NuRE of C,N,P,S,Ca,and Mg was more sensitive to interannual climate variations in the three oak species.The carbon resorption efficiency was significantly increased during the driest year of the study(2014);N resorption efficiency was reduced with temperature;whereas N and P resorption efficiency initially decreased and then increased with precipitation.Moreover,the elements with higher NuREs typically had lower coefficient of variation(CV)in all three oak species.Conclusions:Different oak species exhibited analogous nutrient conservation strategies in response to annual climate variabilities,and interannual climate variations strongly impacted plant nutrient resorption.Deciduous plants may establish a tradeoff mechanism to rebalance somatic nutrients for regrowth at the end of the growing season. | Baoming Du Huawei Ji Shirong Liu Hongzhang Kang Shan Yin Chunjiang Liu | 2021 | Forest Ecosystems2021，8，4： | 4 |
| 17 | Changes in soil organic carbon contents and fractionations of forests along a climatic gradient in China显示文摘Background: Soil organic carbon(SOC) is a large reservoir of terrestrial carbon(C); it consists of different fractions of varying complexity and stability. Partitioning SOC into different pools of decomposability help better predict the trend of changes in SOC dynamics under climate change. Information on how physical fractions and chemical structures of SOC are related to climate and vegetation types is essential for spatial model ing of SOC processes and responses to global change factors.Method: Soil samples were col ected from multiple representative forest sites of three contrasting climatic zones(i.e. cool temperate, warm temperate, and subtropical) in eastern China. Measurements were made on SOC contents and physical fractions of the 0–20 cm soil layer, and the chemical composition of SOC of the 0–5 cm soil layer, along with measurements and compilation of the basic site and forest stand variables. The long-term effects of temperature, litter inputs, soil characteristics and vegetation type on the SOC contents and factions were examined by means of 'space for time substitution' approach and statistical analysis.Result: Mean annual temperature(MAT) varied from 2.1 °C at the cool temperate sites to 20.8 °C at the subtropical sites. Total SOC of the 0–20 cm soil layer decreased with increasing MAT, ranging from 89.2 g·kg^(-1) in cool temperate forests to 57.7 g·kg^(-1) in subtropical forests, at an average rate of 1.87% reduction in SOC with a 1 °C increase in MAT.With increasing MAT, the proportions of aromatic C and phenolic C displayed a tendency of decreases, whereas the proportion of alkyl C and A/O-A value(the ratio of alkyl C to the sum of O-alkyl C and acetal C) displayed a tendency of increases. Overall, there were no significant changes with MAT and forest type in either the physical fractions or the chemical composition. Based on the relationship between the SOC content and MAT, we estimate that SOC in the top 20 soil layer of forests potentially contribute 6.58–26.3 Pg C globally to the atmosphere if global MAT increases by 1 °C–4 °C by the end of the twenty-first century, with nearly half of which(cf. 2.87–11.5 Pg C) occurring in the 0–5 cm mineral soils.Conclusion: Forest topsoil SOC content decreased and became chemical y more recalcitrant with increasing MAT,without apparent changes in the physical fractions of SOC. | Xiaolu Sun Zuoxin Tang Michael G.Ryan Yeming You Osbert Jianxin Sun | 2019 | Forest Ecosystems2019，6，1： | 4 |
| 18 | Toward managing mixed-species stands: from parametrization to prescription显示文摘A better understanding and a more quantitative design of mixed-species stands will contribute to more integrative and goal-oriented research in mixed-species forests.Much recent work has indicated that the structure and growth of mixed species forests may fundamentally differ from monocultures.Here we suggest how to progress from the present accumulation of phenomenological findings to a design of mixed-species stands and advanced silvicultural prescriptions by means of modelling.First,the knowledge of mixing effects on the structure and growth at the stand,species,and individual tree level is reviewed,with a focus on those findings that are most essential for suitable modelling and silvicultural designs and the regulation of mixed stands as opposed to monocultures.Then,the key role of growth models,stand simulators,and scenario assessments for designing mixed species stands is discussed.The next section illustrates that existing forest stand growth models require some fundamental modifications to become suitable for both monocultures and mixed-species stands.We then explore how silvicultural prescriptions derived from scenario runs would need to be both quantified and simplified for transfer to forest management and demonstrated in training plots.Finally,we address the main remaining knowledge gaps that could be remedied through empirical research. | Hans Pretzsch Eric K. Zenner | 2017 | Forest Ecosystems2017，4，4： | 4 |
| 19 | Artificial neural network models predicting the leaf area index:a case study in pure even-aged Crimean pine forests from Turkey显示文摘Background: Leaf Area Index(LAI) is an important parameter used in monitoring and modeling of forest ecosystems. The aim of this study was to evaluate performance of the artificial neural network(ANN) models to predict the LAI by comparing the regression analysis models as the classical method in these pure and even-aged Crimean pine forest stands.Methods: One hundred eight temporary sample plots were collected from Crimean pine forest stands to estimate stand parameters. Each sample plot was imaged with hemispherical photographs to detect the LAI. The partial correlation analysis was used to assess the relationships between the stand LAI values and stand parameters, and the multivariate linear regression analysis was used to predict the LAI from stand parameters. Different artificial neural network models comprising different number of neuron and transfer functions were trained and used to predict the LAI of forest stands.Results: The correlation coefficients between LAI and stand parameters(stand number of trees, basal area, the quadratic mean diameter, stand density and stand age) were significant at the level of 0.01. The stand age, number of trees, site index, and basal area were independent parameters in the most successful regression model predicted LAI values using stand parameters(/?;adj = 0.5431). As corresponding method to predict the interactions between the stand LAI values and stand parameters, the neural network architecture based on the RBF 4-19-1 with Gaussian activation function in hidden layer and the identity activation function in output layer performed better in predicting LAI(SSE(12.1040), MSE(0.1223), RM5 E(0.3497), AIC(0.1040), BIC(-777310) and R2(0.6392)) compared to the other studied techniques.Conclusion: The ANN outperformed the multivariate regression techniques in predicting LAI from stand parameters. The ANN models, developed in this study, may aid in making forest management planning in study forest stands. | ilker Ercanli Alkan Gunlu Muammer Senyurt Sedat Keles | 2018 | Forest Ecosystems2018，5，4： | 4 |
| 20 | Conversion of pure Chinese fir plantation to multi-layered mixed plantation enhances the soil aggregate stability by regulating microbial communities in subtropical China显示文摘Background:Soil aggregates are the basic units of soil structure,and their stability is a key indicator of soil quality and capacity to support ecosystem functions.The impacts of various environmental factors on soil aggregates have been widely studied.However,there remains elusive knowledge on the synergistic effects of changing forest stand structure on soil aggregate stability(SAS),particularly in subtropical China where soil erosion remains a critical issue.Methods:We investigated variations in the components of soil humus(HS),including humic acids(HAs),fulvic acids(FAs),and humins(HMs),under pure Chinese fir(Cunninghamia lanceolata)plantation(PP)and multilayered mixed plantation(MP)comprising C.lanceolata,Castanopsis hystrix,and Michelia hedyosperma.The state of soil aggregate stability,was determined by three separate methods,i.e.,dry-sieving,wet-sieving,and the Le Bissonnais.High-throughput sequencing was used to determine the diversity and composition of microbial communities under PP and MP.We then built partial least squares path models(PLS-PM)for assessing the responses of SAS to the variations in soil microorganisms and HS components.Results:The MP stands had significantly greater SAS(P<0.05),higher content of HAs and more rapid organic matter humification within aggregates,than the PP stands.High-throughput sequencing confirmed that the Pielou andα-diversity index values(Chao1 and Shannon)for fungi were all significantly higher under MP than under PP,while no marked difference was found in bacterialα-diversity between the two plantation types.Moreover,there were markedly greater abundance of three bacterial phyla(Verrucomicrobia,Chloroflexi,and Gemmatimonadetes)and three fungal phyla(Ascomycota,Kickxellomycota,and Glomeromycota),and significantly less abundance of two bacterial phyla(Planctomycetes and Firmicutes)and four fungal phyla(Basidiomycota,Mortierellomycota,Mucoromycota,and Rozellomycota)under MP than under PP.The Chloroflexi and Ascomycota phyla appeared to be the primary drivers of soil aggregate distribution.Our findings revealed that the promotion of SAS under MP was mainly driven by increased soil organic matter(SOM)content,which altered bacterial communities and enhanced fungal diversity,thereby increasing HAs content and the rate of organic matter humification.Conclusions:Considering the combined effects of enhanced soil quality,productivity,and relevant economic costs,introducing broadleaved tree species into Chinese fir plantations can be an effective strategy for stabilizing soil structure against erosion in subtropical China.Our study elucidated the controls on variations of SAS in Chinese fir-dominated plantations and demonstrated the benefit of converting pure Chinese fir plantation to multi-layered mixed plantations in increasing soil structural stability and improving site quality. | Guannv Gao Xueman Huang Haocheng Xu Yi Wang Weijun Shen Wen Zhang Jinliu Yan Xiaoyan Su Shushou Liao Yeming You | 2022 | Forest Ecosystems2022，9，6： | 4 |
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